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2 pages, 148 KiB

Open AccessEditorial

Preface of the 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024)

by Stefano Alvisi, Marco Franchini, Valentina Marsili and Filippo Mazzoni

Eng. Proc. 2024, 69(1), 1; https://doi.org/10.3390/engproc2024069001 - 28 Aug 2024

Cited by 1 | Viewed by 539

Abstract

The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024)—held in Ferrara, Italy, 1–4 July 2024—aimed at involving national and international institutions, public and private companies, professionals, academics, and researchers operating in the [...] Read more.

The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024)—held in Ferrara, Italy, 1–4 July 2024—aimed at involving national and international institutions, public and private companies, professionals, academics, and researchers operating in the field of water distribution and drainage systems management [...] Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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5 pages, 1162 KiB

Open AccessProceeding Paper

The Impacts of Chlorine and Chloramine on Biofilms and Discolouration in Operational Drinking Water Distribution Systems

by Jade Rogers, Vanessa Speight, Katherine Fish, Graeme Moore and Joby Boxall

Eng. Proc. 2024, 69(1), 2; https://doi.org/10.3390/engproc2024069002 - 28 Aug 2024

Viewed by 339

Abstract

While disinfection residuals in drinking water limit planktonic microorganism regrowth during distribution, their impact on biofilms remains uncertain. This study examined how different water qualities, specifically chlorine versus chloramine disinfection residuals, affect drinking water biofilm growth in controlled, fully representative, pipe loop experimental [...] Read more.

While disinfection residuals in drinking water limit planktonic microorganism regrowth during distribution, their impact on biofilms remains uncertain. This study examined how different water qualities, specifically chlorine versus chloramine disinfection residuals, affect drinking water biofilm growth in controlled, fully representative, pipe loop experimental facilities. For the first time, pipe loops were deployed at distribution system extremities, enabling the assessment of biofilms grown in bulk waters with higher water ages than previously studied. Biofilms were grown for three months under comparable hydraulic conditions and temperatures in two operational DWDS (chlorine and chloramine). After three months, experiments regarding hydraulic changes (flushing) were performed to mobilise the biofilm and assess the water quality response. Analysis revealed elevated levels of iron and turbidity, exceeding UK regulatory limits, especially in the chloramine system. Cell count data showed a complex response, with differences likely associated with the residual type. The data provide evidence that chloramine does not restrict biofilm growth and that biofilms grown within chloramine DWDS can present an equal, if not greater, risk to water quality than chlorine counterparts. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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4 pages, 430 KiB

Open AccessProceeding Paper

AI-Assisted Pump Operation for Energy-Efficient Water Distribution Systems

by Niuosha Hedaiaty Marzouny and Rebecca Dziedzic

Eng. Proc. 2024, 69(1), 3; https://doi.org/10.3390/engproc2024069003 - 28 Aug 2024

Viewed by 402

Abstract

Pumping water in water networks is generally the top energy demand for water systems. This study seeks to develop a large language model (LLM)-assisted framework for pump operation. Herein, ChatGPT was used to suggest pump control settings over 24 h that minimize energy [...] Read more.

Pumping water in water networks is generally the top energy demand for water systems. This study seeks to develop a large language model (LLM)-assisted framework for pump operation. Herein, ChatGPT was used to suggest pump control settings over 24 h that minimize energy use while maintaining pressure levels. In the proposed prompts, hourly information about the planned operation, i.e., pump control settings, minimum pressure levels, tank storage levels, and pump energy use, was provided. As the LLM suggests improved scenarios, EPANET results for these scenarios are fed back to it. This allows the LLM to learn and adjust future suggestions. The framework was validated on the example EPANET Net 3. Through iterative data exchange between the LLM and EPANET, the framework led to more energy-efficient pump scheduling. The LLM-assisted framework was compared with a genetic algorithm optimization. The results demonstrated that the proposed method outperformed the GA, achieving an energy reduction of 66.98%. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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5 pages, 860 KiB

Open AccessProceeding Paper

An Analytical Solution for the Hydraulics of Looped Pipe Networks

by Mohammad Mehdi Riyahi, Amin E. Bakhshipour, Carlo Giudicianni, Ulrich Dittmer, Ali Haghighi and Enrico Creaco

Eng. Proc. 2024, 69(1), 4; https://doi.org/10.3390/engproc2024069004 - 28 Aug 2024

Viewed by 417

Abstract

This study introduces an analytical solution for the hydraulic analysis of looped water distribution networks (WDNs). Conventional approaches to solving ∆Q equations for looped water discharge correction entail iterative hydraulic analysis to compute the system pipe flows, velocities, and nodal pressures. In contrast, [...] Read more.

This study introduces an analytical solution for the hydraulic analysis of looped water distribution networks (WDNs). Conventional approaches to solving ∆Q equations for looped water discharge correction entail iterative hydraulic analysis to compute the system pipe flows, velocities, and nodal pressures. In contrast, using the proposed analytical approach, the ∆Q equation is solved with the exact flow directions determined, consolidating known flow directions into a single unknown variable (∆Q) for each loop. Comparative analyses prove that this approach can precisely compute the hydraulic properties of WDNs. Finally, a Z-test hypothesis test is applied to assess the efficacy of the modified shortest-path algorithm. The results show that this algorithm attains an average accuracy of 90% in predicting exact flow directions, with a confidence level of 99%. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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5 pages, 1218 KiB

Open AccessProceeding Paper

Data-Enabled Predictive Control for Optimal Pressure Management

by Gal Perelman and Avi Ostfeld

Eng. Proc. 2024, 69(1), 5; https://doi.org/10.3390/engproc2024069005 - 29 Aug 2024

Viewed by 337

Abstract

Recent developments in control theory coupled with the growing availability of real-time data have paved the way for improved data-driven control methodologies. This study explores the application of a data-enabled predictive control (DeePC) algorithm to optimize the operation of water distribution systems (WDS). [...] Read more.

Recent developments in control theory coupled with the growing availability of real-time data have paved the way for improved data-driven control methodologies. This study explores the application of a data-enabled predictive control (DeePC) algorithm to optimize the operation of water distribution systems (WDS). WDSs are characterized by inherent uncertainties and complex nonlinear dynamics. Hence, classic control strategies that involve physical model-based methods are often hard to implement and infeasible to scale. The DeePC method suggests a paradigm shift by utilizing a data-driven approach. This method employs real-time data to dynamically learn an unknown system’s behavior. It utilizes a finite set of input–output samples (control settings, and measured data) to derive optimal policies, effectively bypassing the need for an explicit mathematical model of the system. In this study, DeePC is applied to a pressure management case study and demonstrates superior performance compared to standard control strategies. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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4 pages, 585 KiB

Open AccessProceeding Paper

Anomaly Localization by Applying Data-Driven Analysis and Parallel Optimization of Hydraulic Model Calibration

by Ashley Hui Zhang, Fred Cao, Alvin Wei Ze Chew, Zheng Yi Wu, Rony Kalfarisi, Xue Meng, Jocelyn Pok, Juen Ming Wong, Kah Cheong Lai, Lennis Seow and Jia Jie Wong

Eng. Proc. 2024, 69(1), 6; https://doi.org/10.3390/engproc2024069006 - 29 Aug 2024

Viewed by 254

Abstract

This paper presents an integrated approach using both data-driven and hydraulic model-based methods to localize anomaly events in near real time (NRT). Upon detecting an NRT anomaly event, the pressure drops at sensor locations are calculated, followed by estimating the pressure drops at [...] Read more.

This paper presents an integrated approach using both data-driven and hydraulic model-based methods to localize anomaly events in near real time (NRT). Upon detecting an NRT anomaly event, the pressure drops at sensor locations are calculated, followed by estimating the pressure drops at junction nodes via an inverse-distance weighted interpolation method. Clustering is then performed based on pressure drops at junction nodes and network topology to segregate and reduce the search areas. Afterwards, a genetic algorithm optimization is performed with hydraulic model simulations to further pinpoint the anomaly hotspots. The integrated method has been tested on real leakage events with field data, where the localized leak hotspots are within 300 m of the ground-truth leaks. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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4 pages, 520 KiB

Open AccessProceeding Paper

Applying Pump Affinity Laws to an Isolated Solar-Powered Pumping Station

by F. Javier Martínez-Solano, Josep Francesc Pons-Ausina, Pedro L. Iglesias-Rey and Gonzalo López-Patiño

Eng. Proc. 2024, 69(1), 7; https://doi.org/10.3390/engproc2024069007 - 29 Aug 2024

Viewed by 684

Abstract

Water pumping is highlighted as the major energy consumer in the water cycle. Solar energy has emerged as a promising alternative to traditional electric networks, particularly in areas lacking an electrical infrastructure. Solar-powered pumping stations are categorized as connected and isolated, with the [...] Read more.

Water pumping is highlighted as the major energy consumer in the water cycle. Solar energy has emerged as a promising alternative to traditional electric networks, particularly in areas lacking an electrical infrastructure. Solar-powered pumping stations are categorized as connected and isolated, with the latter adapting the pump operation based on available solar energy. This article proposes a scheme to adjust the pump operation according to natural factors, like irradiance and temperature, aiming to optimize energy use and minimize investment costs in solar panels. An application of this method in Valencia, Spain, demonstrates significant savings. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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4 pages, 683 KiB

Open AccessProceeding Paper

Co-Design of Water Distribution Systems with Behind-the-Meter Solar

by Jiayu Yao, Wenyan Wu, Angus R. Simpson and Behzad Rismanchi

Eng. Proc. 2024, 69(1), 8; https://doi.org/10.3390/engproc2024069008 - 29 Aug 2024

Viewed by 288

Abstract

The design of water distribution systems (WDSs) is crucial for ensuring a resilient water supply for the future. To improve the energy efficiency of WDSs, behind-the-meter (BTM) solar has been considered as an option. Due to the complex water–energy relationship between WDSs and [...] Read more.

The design of water distribution systems (WDSs) is crucial for ensuring a resilient water supply for the future. To improve the energy efficiency of WDSs, behind-the-meter (BTM) solar has been considered as an option. Due to the complex water–energy relationship between WDSs and their associated BTM solar systems, the co-design of the integrated systems that considers the combined performance of both systems is required. Moreover, the design of WDS also needs to anticipate potential changes in the future due to their long service life, as both future water demand and potential solar PV technology development can have an impact on system performance over time. This study aims to develop an approach for the co-design of WDSs and the BTM solar systems under long-term water demand and solar PV technology development uncertainty. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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5 pages, 437 KiB

Open AccessProceeding Paper

Optimizing Time Series Models for Water Demand Forecasting

by Gal Perelman, Yaniv Romano and Avi Ostfeld

Eng. Proc. 2024, 69(1), 9; https://doi.org/10.3390/engproc2024069009 - 29 Aug 2024

Viewed by 388

Abstract

This study focuses on optimizing time series forecasting models for water demand in a North Italian city as part of the Battle of the Water Demand Forecast (BWDF) challenge. It aims to accurately predict water demands across ten district-metered areas (DMAs) using historical [...] Read more.

This study focuses on optimizing time series forecasting models for water demand in a North Italian city as part of the Battle of the Water Demand Forecast (BWDF) challenge. It aims to accurately predict water demands across ten district-metered areas (DMAs) using historical data and weather information over a one-week horizon. The methodology encompasses data preprocessing, including missing data imputation, feature engineering, and novel normalization techniques, followed by the development and hyperparameter optimization of various data-driven models such as random forest, XGB, LSTM, and Prophet. Extensive cross-validation tests assess each model’s performance, revealing that our refined approach markedly enhances forecast accuracy, demonstrating the importance of model and parameter selection for effective water demand forecasting. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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4 pages, 984 KiB

Open AccessProceeding Paper

An Integrated Framework for Supplementing Online Water Quality Monitoring in the Detection of Contamination Events in Water Distribution Networks

by Camilo Salcedo and Dominic L. Boccelli

Eng. Proc. 2024, 69(1), 10; https://doi.org/10.3390/engproc2024069010 - 29 Aug 2024

Viewed by 312

Abstract

Surveillance Response Systems (SRSs) have been deployed in Water Distribution Networks (WDNs) to detect various contamination events. However, in WDNs, some contaminants may remain undetected by an SRS due to the specificity of online water quality monitoring (OWQM). To overcome this limitation, OWQM [...] Read more.

Surveillance Response Systems (SRSs) have been deployed in Water Distribution Networks (WDNs) to detect various contamination events. However, in WDNs, some contaminants may remain undetected by an SRS due to the specificity of online water quality monitoring (OWQM). To overcome this limitation, OWQM can be supplemented with additional datasets to enhance the detection capabilities of the SRS framework. These additional datasets are based on health-seeking behaviors exhibited by consumers after consuming contaminated water as well as customer complaints. In this research, we implement a set of Bayesian networks in a clustered network to fuse these alternate datasets (simulated using an ABM due to the limited information associated with real events) with traditional OWQM to determine the likelihood of an ongoing contamination event. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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4 pages, 185 KiB

Open AccessProceeding Paper

Integrating Gender+ Perspectives in Hydrology Education

by Rita Bencivenga, Cinzia Leone and Angela Celeste Taramasso

Eng. Proc. 2024, 69(1), 11; https://doi.org/10.3390/engproc2024069011 - 29 Aug 2024

Viewed by 315

Abstract

UniGe’s hydrology course emphasises the importance of resilience in overcoming climate challenges. It is in line with the SDGs, integrates considerations of equality, diversity, and inclusion (EDI), and promotes climate resilience and nature-based solutions. This initiative, included in the UniGe Gender Equality Plan [...] Read more.

UniGe’s hydrology course emphasises the importance of resilience in overcoming climate challenges. It is in line with the SDGs, integrates considerations of equality, diversity, and inclusion (EDI), and promotes climate resilience and nature-based solutions. This initiative, included in the UniGe Gender Equality Plan (GEP), represents a concrete step towards the inclusion of a gender+ perspective in research and teaching in STEM disciplines, one of the five mandatory GEP areas that the Horizon Europe programme requires from all public research institutions applying for funding. The sustainability and replicability of the initiative at EU level will be discussed. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

4 pages, 637 KiB

Open AccessProceeding Paper

The Need for Integrating Governance, Operations, and Social Dynamics into Water Supply/Distribution Modelling

by Lindell Ormsbee, Diana Byrne and Nicholas Magliocca

Eng. Proc. 2024, 69(1), 12; https://doi.org/10.3390/engproc2024069012 - 29 Aug 2024

Cited by 1 | Viewed by 331

Abstract

Water systems in the US are experiencing increasing challenges because of poor governance, unsustainable fiscal policies, an aging workforce, new environmental regulations, and concerns over environmental justice. These challenges will only increase if the specific constraints and barriers to system viability are not [...] Read more.

Water systems in the US are experiencing increasing challenges because of poor governance, unsustainable fiscal policies, an aging workforce, new environmental regulations, and concerns over environmental justice. These challenges will only increase if the specific constraints and barriers to system viability are not first identified and then translated into new policies and best management practices to ensure system sustainability, reliability, resilience, and equity of services. This paper proposes a methodology to accomplish this objective that integrates agent-based models, water distribution models, and sustainability performance models within a larger system dynamics framework. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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4 pages, 469 KiB

Open AccessProceeding Paper

Developing an Open Repository of Water Main Break Prediction Models in Kitchener

by Fatemeh Boloukasli ahmadgourabi and Rebecca Dziedzic

Eng. Proc. 2024, 69(1), 13; https://doi.org/10.3390/engproc2024069013 - 29 Aug 2024

Viewed by 351

Abstract

This study presents an open repository of predictive machine learning models for water main breaks as a way to help manage water supply networks proactively. Lack of standardized datasets has been a challenge in previous research, a problem which is addressed in the [...] Read more.

This study presents an open repository of predictive machine learning models for water main breaks as a way to help manage water supply networks proactively. Lack of standardized datasets has been a challenge in previous research, a problem which is addressed in the present study through provision of a benchmark dataset that features pipe dimensions, age, proximity to previous breaks, and climatic variables, among other elements. The repository allows for model testing and comparison with machine learning algorithms such as XGBoost and LightGBM. Implemented in Python and available on GitHub, this project promotes a collaborative approach towards the enhancement of urban infrastructure management through accurate prediction of water main breaks, leading to fewer interruptions in service. Findings show that, while random splits work well in training and testing, their performance is poor when it comes to future prediction. Conversely, time-based splits maintain a good consistency between training and testing phases, but they lack the capacity to predict future periods. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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5 pages, 1264 KiB

Open AccessProceeding Paper

Cooperative Operational Optimization of Water and Power Systems under Extreme Conditions

by Gal Perelman, Tomer Shmaya, Stelios Vrachimis, Mathaios Panteli, Demetrios G. Eliades and Avi Ostfeld

Eng. Proc. 2024, 69(1), 14; https://doi.org/10.3390/engproc2024069014 - 30 Aug 2024

Viewed by 391

Abstract

This research explores the integrated management of water distribution systems (WDS) and power distribution systems (PDS) to improve their resilience to extreme scenarios. This study delves into the dynamics of a locally managed PDS as an example of extreme operational conditions. The primary [...] Read more.

This research explores the integrated management of water distribution systems (WDS) and power distribution systems (PDS) to improve their resilience to extreme scenarios. This study delves into the dynamics of a locally managed PDS as an example of extreme operational conditions. The primary objective is to minimize load shedding (LS) in the PDS through strategic load shifting in the interconnected WDS, demonstrating the potential of cooperative decision making between the two critical systems. The optimization framework offers a novel approach to managing flexible resources during emergencies by utilizing the mutual links between a WDS and a PDS. Typically, WDSs and PDSs are operated by different operators such that cooperation is limited. This study presents how communication based on limited information sharing between the two systems is sufficient to increase resilience and improve the systems’ functionality, emphasizing the advantages of cooperative decision making. This paper highlights the significance of cross-sectoral collaboration, presenting a viable pathway for managing local infrastructure systems under extreme conditions while ensuring uninterrupted service delivery to communities. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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4 pages, 409 KiB

Open AccessProceeding Paper

Water Demand Forecasting Based on Online Aggregation for District Meter Areas-Specific Adaption

by Jens Kley-Holsteg, Björn Sonnenschein, Gregor Johnen and Florian Ziel

Eng. Proc. 2024, 69(1), 15; https://doi.org/10.3390/engproc2024069015 - 29 Aug 2024

Viewed by 299

Abstract

Short-term water demand forecasting is critical to enable optimal system operation. For practical purposes, the accuracy of the forecast and the adaptability to changing conditions are paramount. Therefore, for the Battle of Water Demand Forecasting (BWDF), we propose a precise and highly flexible [...] Read more.

Short-term water demand forecasting is critical to enable optimal system operation. For practical purposes, the accuracy of the forecast and the adaptability to changing conditions are paramount. Therefore, for the Battle of Water Demand Forecasting (BWDF), we propose a precise and highly flexible forecasting methodology to allow an excellent adaptation to District Meter Areas (DMA)-specific characteristics. The proposed method consists of data cleaning and pre-processing, the training of individual forecast models and finally of combining the individual forecasts by the smoothed Bernstein Online Aggregation (BOA) algorithm. The ensemble of individual forecasting models includes simple time series, high-dimensional linear, and highly non-linear models such as neural networks. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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4 pages, 784 KiB

Open AccessProceeding Paper

Optimal Sewer Network Design Including Pumping Stations

by Juan Saldarriaga, Juana Herrán, María A. González, Yesid Coy and Pedro L. Iglesias-Rey

Eng. Proc. 2024, 69(1), 16; https://doi.org/10.3390/engproc2024069016 - 30 Aug 2024

Viewed by 343

Abstract

In urban areas with a flat terrain, pumping stations must be included to elevate wastewater and avoid extreme excavation depths. These systems are characterized by high operational costs due to the pump’s power consumption. The present work presents a methodology for the optimal [...] Read more.

In urban areas with a flat terrain, pumping stations must be included to elevate wastewater and avoid extreme excavation depths. These systems are characterized by high operational costs due to the pump’s power consumption. The present work presents a methodology for the optimal design of sewer networks including pumping stations, whose objective function is to minimize the construction and operation costs of the system. The methodology was tested on three sewer benchmark networks using two cost functions proposed in the literature. In all the sewer benchmarks, the cost achieved in the present work was compared with the best costs reported in the literature. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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5 pages, 997 KiB

Open AccessProceeding Paper

Minimization of Water Age in Water Distribution Systems under Uncertain Demand

by Kristina Korder, Elad Salomons, Avi Ostfeld and Pu Li

Eng. Proc. 2024, 69(1), 17; https://doi.org/10.3390/engproc2024069017 - 29 Aug 2024

Viewed by 302

Abstract

Most existing approaches to ensuring water quality in water distribution systems (WDSs) are deterministic, i.e., they do not consider uncertainties, although they may have significant impacts on the water quality. It is well recognized that water demand represents a predominant uncertainty in a [...] Read more.

Most existing approaches to ensuring water quality in water distribution systems (WDSs) are deterministic, i.e., they do not consider uncertainties, although they may have significant impacts on the water quality. It is well recognized that water demand represents a predominant uncertainty in a WDS. In addition, water age is often used as an important parameter to describe the water quality in a WDS and can be influenced by water demand and control elements such as pressure-reducing valves (PRVs). Therefore, the aim of this study is to carry out a probabilistic analysis of the impact of demand uncertainty on the water age in the distribution network. Based on the solution of deterministic optimization to minimize the water age, Monte Carlo simulation will be carried out by sampling the uncertain demand to evaluate the stochastic distribution of water age, as well as other operating variables like pressure and flow. As a result, the probability of violating the constraints of such variables can be determined, with the reliability of the operating strategy (e.g., the settings of the PRVs) given by deterministic optimization provided. In cases of low reliability, it is necessary to modify the operating strategy in order to decrease the probability of constraint violation. For this purpose, a chance-constrained optimization problem is formulated, and its benefits for ensuring the user-defined reliability are studied. A benchmark network is used to verify the proposed approach. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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4 pages, 1069 KiB

Open AccessProceeding Paper

Smart Nature-Based Solutions for Stormwater Management in Urban Areas—An Analysis of Pilot Cases

by Kerta Kõiv, Ivar Annus, Nils Kändler, Murel Truu, Katrin Kaur and Kristjan Suits

Eng. Proc. 2024, 69(1), 18; https://doi.org/10.3390/engproc2024069018 - 29 Aug 2024

Viewed by 425

Abstract

Nature-based solutions (NBSs) have been shown to be effective at addressing urban challenges such as flooding, poor water quality, biodiversity loss, and promoting public health and well-being. The European Commission mandates that cities implement NBSs for stormwater management by 2026 to deal with [...] Read more.

Nature-based solutions (NBSs) have been shown to be effective at addressing urban challenges such as flooding, poor water quality, biodiversity loss, and promoting public health and well-being. The European Commission mandates that cities implement NBSs for stormwater management by 2026 to deal with changing climate conditions like heavy rainfall events. Recent flooding events in Germany, France, and Belgium have demonstrated that the rainfall regime has shifted considerably over the last several decades. This study demonstrates, using 7 pilot areas near Baltic Sea region, that the transition from no- and low-tech to high-tech NBSs can have significant positive impacts on flood protection and water quality, as well co-benefits such as public health, highlighting NBSs’ multifaceted advantages. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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4 pages, 2053 KiB

Open AccessProceeding Paper

Burst Localisation in Water Pressurised Pipelines Combining Numerical Data Generation and ANN Transient Signal Processing

by Andrea Menapace, Maurizio Tavelli, Daniele Dalla Torre and Maurizio Righetti

Eng. Proc. 2024, 69(1), 19; https://doi.org/10.3390/engproc2024069019 - 30 Aug 2024

Viewed by 316

Abstract

Transient test-based techniques have been widely identified as one of the best non-intrusive techniques that exploit the propagation of pressure waves along pressurised pipelines, allowing the check of the status of the distribution systems. Although several studies have demonstrated the suitability of this [...] Read more.

Transient test-based techniques have been widely identified as one of the best non-intrusive techniques that exploit the propagation of pressure waves along pressurised pipelines, allowing the check of the status of the distribution systems. Although several studies have demonstrated the suitability of this technique for identifying anomalies in transmission pipelines, including leaks, the potential for automatically analysing transient signals through deep learning procedures has only been superficially investigated. With this aim, this study proposes how a proper synthetic generation of transient signals based on numerical simulations can support the development of neural network-based methodologies for water leak detection and localisation. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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5 pages, 800 KiB

Open AccessProceeding Paper

Experimental Investigation of the Fatigue Strength and Leakage Failure Mode of Corroded Cast Iron Water Pipes

by Edward John, Joby Boxall, Richard Collins, Elisabeth Bowman and Luca Susmel

Eng. Proc. 2024, 69(1), 20; https://doi.org/10.3390/engproc2024069020 - 30 Aug 2024

Viewed by 319

Abstract

Controlled laboratory-based physical evidence is presented, showing how the type of fatigue loading impacts the remaining life and the failure mode of corroded GCI water pipes. Leak-before-burst behavior is shown for pipes experiencing internal water pressure fatigue loading but not for four-point bending [...] Read more.

Controlled laboratory-based physical evidence is presented, showing how the type of fatigue loading impacts the remaining life and the failure mode of corroded GCI water pipes. Leak-before-burst behavior is shown for pipes experiencing internal water pressure fatigue loading but not for four-point bending fatigue. Sharp pits are shown to reduce fatigue strength by up to 5.4 times, with the degree of reduction dependent on alignment. Condition assessments of corroded GCI water pipes must consider both the three-dimensional shape of the corrosion pitting and the loading experienced by the pipe to give a true assessment of the damage caused by a corrosion pit. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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4 pages, 756 KiB

Open AccessProceeding Paper

Empowering Water Engineers to Develop XR Learning Applications with the WATERLINE Project

by Gareth Lewis, Matt B. Johns, Lydia S. Vamvakeridou-Lyroudia, Albert S. Chen, Slobodan Djordjević and Dragan A. Savić

Eng. Proc. 2024, 69(1), 21; https://doi.org/10.3390/engproc2024069021 - 30 Aug 2024

Viewed by 331

Abstract

The over-arching goal of the WATERLINE project is the creation of a European Digital Water Higher Education Institution (HEI) Alliance, with a core part of this goal being the development and delivery of meaningful water engineering education through extended reality technology, allowing students [...] Read more.

The over-arching goal of the WATERLINE project is the creation of a European Digital Water Higher Education Institution (HEI) Alliance, with a core part of this goal being the development and delivery of meaningful water engineering education through extended reality technology, allowing students to engage with virtualised water engineering models, such as flume tanks and water distribution networks in a manner that will promote engaged deep learning. To realise this goal, researchers need to engage with pedagogic, creative, and technical considerations to ensure that water engineering students are presented with engaging applications that provide the “right” knowledge and provide experiences where deep and memorable learning can take place. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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4 pages, 6485 KiB

Open AccessProceeding Paper

CT-Scans: Game-Changer in the Maintenance of PVC Drinking-Water Mains

by Karel van Laarhoven and Amitosh Dash

Eng. Proc. 2024, 69(1), 22; https://doi.org/10.3390/engproc2024069022 - 30 Aug 2024

Viewed by 311

Abstract

CT-scans were successfully used to—for the first time—detect inclusions of foreign material in the pipe walls of PVC pipes. This is of interest because these formerly undetectable inclusions dominate the main failure mechanism of PVC: crack growth. The technique unlocks a step forward [...] Read more.

CT-scans were successfully used to—for the first time—detect inclusions of foreign material in the pipe walls of PVC pipes. This is of interest because these formerly undetectable inclusions dominate the main failure mechanism of PVC: crack growth. The technique unlocks a step forward in the condition assessment of PVC pipes in several ways: it provides researchers with a new way to investigate crack growth in PVC pipes; it provides drinking-water utilities with a method for destructive condition assessment; and CT provides the industry with the reference knowledge needed to develop relevant in-line inspection techniques for PVC mains. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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4 pages, 202 KiB

Open AccessProceeding Paper

Developing a Framework for Smart Stormwater Management in Tallinn, Estonia

by Kristjan Suits, Anatoli Vassiljev, Katrin Kaur, Kerta Kõiv, Nils Kändler and Ivar Annus

Eng. Proc. 2024, 69(1), 23; https://doi.org/10.3390/engproc2024069023 - 30 Aug 2024

Viewed by 267

Abstract

The recently revised European Urban Wastewater Directive 91/271/EEC has prompted a shift in urban stormwater management across Europe. The directive emphasizes the importance of improving stormwater monitoring to prevent urban water quality degradation. Larger organizations with more resources are increasing their stormwater monitoring [...] Read more.

The recently revised European Urban Wastewater Directive 91/271/EEC has prompted a shift in urban stormwater management across Europe. The directive emphasizes the importance of improving stormwater monitoring to prevent urban water quality degradation. Larger organizations with more resources are increasing their stormwater monitoring capabilities. However, there is concern that smaller utilities might lack these resources. A methodology was developed to evaluate stormwater managers’ ability to implement continuous stormwater monitoring solutions. The proposed framework was developed based on a literature review, and it considers environmental, technical, financial, and human resource factors. This proposed framework represents the first step towards putting data-driven urban stormwater management into practice. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

4 pages, 2521 KiB

Open AccessProceeding Paper

Urban Drainage Modelling for the Design of Treatment Technologies

by Margherita Evangelisti, Vittorio Di Federico and Marco Maglionico

Eng. Proc. 2024, 69(1), 24; https://doi.org/10.3390/engproc2024069024 - 31 Aug 2024

Viewed by 341

Abstract

A recent evaluation of the UWWTD confirmed that overflows from combined systems and surface water runoff are a significant pressure of the aquatic environment in terms of pollution. Increasing urbanization, climate change, and the evolution of pollutants suggest that CSOs may worsen in [...] Read more.

A recent evaluation of the UWWTD confirmed that overflows from combined systems and surface water runoff are a significant pressure of the aquatic environment in terms of pollution. Increasing urbanization, climate change, and the evolution of pollutants suggest that CSOs may worsen in the future, impacting on the ecological status of rivers. In the Italian case study, an urban drainage model of the Bologna sewer network is applied to quantify the pollution load discharged from CSOs, which represents the main parameter for the design of treatment technology. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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4 pages, 840 KiB

Open AccessProceeding Paper

Urban Water Demand Forecasting Using DeepAR-Models as Part of the Battle of Water Demand Forecasting (BWDF)

by Andreas Wunsch, Christian Kühnert, Steffen Wallner and Mathias Ziebarth

Eng. Proc. 2024, 69(1), 25; https://doi.org/10.3390/engproc2024069025 - 2 Sep 2024

Viewed by 333

Abstract

The accurate and reliable short-term forecasting of urban water demand plays a crucial role in enabling drinking water utilities to operate sustainably and secure water supplies in the future. Here, we apply state-of-the-art DeepAR models to predict urban water demand in ten district [...] Read more.

The accurate and reliable short-term forecasting of urban water demand plays a crucial role in enabling drinking water utilities to operate sustainably and secure water supplies in the future. Here, we apply state-of-the-art DeepAR models to predict urban water demand in ten district metered areas (DMAs) in a water distribution system in northeastern Italy. DeepAR models are based on long short-term memory networks and can directly provide probabilistic results. For this contribution, we leverage past flow data, current and future weather data, and engineered weather and date features as input to predict flow data one week ahead. A local model for each DMA is prepared and applied after hyperparameter optimization. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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4 pages, 2086 KiB

Open AccessProceeding Paper

The LOTUS International Multifunctional Digital Twin

by Gareth Lewis, Lydia S. Vamvakeridou-Lyroudia, Albert S. Chen, Slobodan Djordjević and Dragan A. Savić

Eng. Proc. 2024, 69(1), 26; https://doi.org/10.3390/engproc2024069026 - 2 Sep 2024

Viewed by 296

Abstract

The LOTUS project was concerned with the development of low-cost innovative technology for water quality and resource management in urban and rural water systems in India. This paper is concerned with the development of a digital twin for the public water distribution network [...] Read more.

The LOTUS project was concerned with the development of low-cost innovative technology for water quality and resource management in urban and rural water systems in India. This paper is concerned with the development of a digital twin for the public water distribution network of Guwahati that will enable researchers from the Guwahati Institute of Technology to develop and test leak detection algorithms. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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4 pages, 1614 KiB

Open AccessProceeding Paper

A Qualitative Approach to Combined Sewer Overflow Modelling on the WATERVERSE Project

by Gareth Lewis, Barry Evans, Lydia S. Vamvakeridou-Lyroudia, Albert S. Chen, Slobodan Djordjević and Dragan A. Savić

Eng. Proc. 2024, 69(1), 27; https://doi.org/10.3390/engproc2024069027 - 2 Sep 2024

Viewed by 292

Abstract

In the UK, combined sewer overflows (CSOs) are currently a hot topic, with the UK’s water regulator (OFWAT) mandating greater visibility and reporting on such incidents. However, there is often little existing support for this given a historic lack of CSO-related data collection. [...] Read more.

In the UK, combined sewer overflows (CSOs) are currently a hot topic, with the UK’s water regulator (OFWAT) mandating greater visibility and reporting on such incidents. However, there is often little existing support for this given a historic lack of CSO-related data collection. This paper looks to build a model of water quality to capture different key CSO versus agricultural runoff events and to develop a digital twin for Totnes and swimming areas of the river Dart. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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5 pages, 2757 KiB

Open AccessProceeding Paper

Employing Extended Kalman Filter for Faulty Sensor Detection in Water Distribution Systems

by Yifan Huang, Meghna Thomas, Matthew Bartos and Lina Sela

Eng. Proc. 2024, 69(1), 28; https://doi.org/10.3390/engproc2024069028 - 2 Sep 2024

Viewed by 325

Abstract

State estimation techniques offer an effective approach for integrating information from hydraulic models with sensor measurements, providing a more accurate representation of the system dynamics. The accuracy of state estimation depends heavily on the reliability of sensor data, making the identification of faulty [...] Read more.

State estimation techniques offer an effective approach for integrating information from hydraulic models with sensor measurements, providing a more accurate representation of the system dynamics. The accuracy of state estimation depends heavily on the reliability of sensor data, making the identification of faulty sensors critical for decision-makers who rely on model estimates. This study proposes a new approach for detecting faulty sensors in water distribution systems to mitigate the adverse effects of incorrect measurements on operational decisions. We utilize the Extended Kalman Filter as the state estimation method and introduce a masking approach for identifying faulty pressure sensors. The effectiveness of the proposed approach is evaluated using a benchmark network model, demonstrating its proficiency in detecting faulty sensor data. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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4 pages, 625 KiB

Open AccessProceeding Paper

A Methodology for Forecasting Demands in a Water Distribution Network Based on the Classical and Neural Networks Approach

by Yesid Coy, Laura González, Laura Basto, Valeria Rodríguez, Santiago Gómez, Juan Perafán, Simón Cardona, Alejandra Tabares and Juan Saldarriaga

Eng. Proc. 2024, 69(1), 29; https://doi.org/10.3390/engproc2024069029 - 2 Sep 2024

Viewed by 457

Abstract

This paper proposes a three (3)-step methodology to forecast the future water demands of a water distribution network (WDN) composed of ten (10) district metered areas (DMAs). First, pre-processing of the time-series data was performed through outlier elimination, imputation by K-Nearest Neighbors (KNN), [...] Read more.

This paper proposes a three (3)-step methodology to forecast the future water demands of a water distribution network (WDN) composed of ten (10) district metered areas (DMAs). First, pre-processing of the time-series data was performed through outlier elimination, imputation by K-Nearest Neighbors (KNN), and statistical data scaling. Second, the model hyperparameters were calibrated using Bayesian optimization. Third, Long Short-Term Memory (LSTM) coded as a Multi-Step Multivariate Time-Series forecasting model was implemented. Our results indicate that the proposed model produces accurate future water demands, suggesting that feasible short-term water demand forecasting models require combining engineering judgment and computational tools to achieve reliability. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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5 pages, 999 KiB

Open AccessProceeding Paper

Operational Effects on Water Quality Evolution in Water Distribution Systems

by Laura González, Yesid Coy, Dominic L. Boccelli and Juan Saldarriaga

Eng. Proc. 2024, 69(1), 30; https://doi.org/10.3390/engproc2024069030 - 2 Sep 2024

Viewed by 288

Abstract

Water distribution systems (WDSs) are subject to operational changes due to variability in demands, the availability of flow rates, system maintenance and unexpected events. This study aims to assess the behavior of water quality in a distribution network associated with operational changes that [...] Read more.

Water distribution systems (WDSs) are subject to operational changes due to variability in demands, the availability of flow rates, system maintenance and unexpected events. This study aims to assess the behavior of water quality in a distribution network associated with operational changes that the system typically undergoes. For this work, two black-box models were compared to predict chlorine concentration at different nodes in a small network and a large network. The model was trained with synthetic data from simulations through the EPANET-Python Toolkit. The results show that the black-box model can be implemented to predict water quality in real time. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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4 pages, 3381 KiB

Open AccessProceeding Paper

Integrating Drone-Captured Sub-Catchment Topography with Multiphase CFD Modelling to Enhance Urban Stormwater Management

by Katrin Kaur, Ivar Annus, Murel Truu, Nils Kändler and Iris Paalmäe

Eng. Proc. 2024, 69(1), 31; https://doi.org/10.3390/engproc2024069031 - 2 Sep 2024

Viewed by 320

Abstract

In this study, a drone-captured spatial data point cloud is used as input for creating a high-resolution modelling domain that accurately represents urban stormwater sub-catchments’ topography. The objective is to map possibilities, showcase the potential, and establish an in-house workflow that is as [...] Read more.

In this study, a drone-captured spatial data point cloud is used as input for creating a high-resolution modelling domain that accurately represents urban stormwater sub-catchments’ topography. The objective is to map possibilities, showcase the potential, and establish an in-house workflow that is as efficient as possible for the high-resolution modelling of stormwater runoff in urban sub-catchments, to provide input for improving urban stormwater management. The computational fluid dynamics model simulation results are compared to geographic information system-based analysis data and field observations, illustrating the benefits and limitations of the approach. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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4 pages, 470 KiB

Open AccessProceeding Paper

Explainable Methods for Water Demand Forecasting as a Key Aspect of Trustworthy Artificial Intelligence

by Claudia Maußner, Martin Oberascher, Arnold Autengruber, Arno Kahl and Robert Sitzenfrei

Eng. Proc. 2024, 69(1), 32; https://doi.org/10.3390/engproc2024069032 - 2 Sep 2024

Viewed by 442

Abstract

The accurate prediction of daily drinking water demand for the next few days is the basis for many operational decisions and applications. In Europe, recently, the “Artificial Intelligence (AI) Act” was authorised, emphasising the trustworthiness and explainability of AI in the future. We [...] Read more.

The accurate prediction of daily drinking water demand for the next few days is the basis for many operational decisions and applications. In Europe, recently, the “Artificial Intelligence (AI) Act” was authorised, emphasising the trustworthiness and explainability of AI in the future. We therefore test and compare different AI methods regarding their performance, transparency and robustness. As the results show, opaque models are not per se superior to linear models, whereas linear models are especially ahead in terms of robustness and transparency. Bayesian linear models are particularly interesting as they additionally output credible intervals indicating upper and lower estimation bounds. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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5 pages, 2122 KiB

Open AccessProceeding Paper

A Comprehensive Virtual Testbed for Modeling Disinfection Byproduct Formation in Water Distribution Networks

by Pavlos Pavlou, Marios Kyriakou, Stelios G. Vrachimis and Demetrios G. Eliades

Eng. Proc. 2024, 69(1), 33; https://doi.org/10.3390/engproc2024069033 - 2 Sep 2024

Viewed by 296

Abstract

Drinking water disinfection by water utilities aims to ensure the safety and high quality of the provided water; however, it can pose a threat to human health due to the formation of disinfection byproducts (DBPs). The prediction and modeling of DBPs are challenging [...] Read more.

Drinking water disinfection by water utilities aims to ensure the safety and high quality of the provided water; however, it can pose a threat to human health due to the formation of disinfection byproducts (DBPs). The prediction and modeling of DBPs are challenging tasks due to the complex reactions within water distribution networks (WDN). To address this challenge, we introduce a virtual testbed based on a realistic WDN in Cyprus that utilizes the EPANET and EPANET-MSX engines to model multi-species reactions for the execution of simulation experiments under various conditions regarding the formation and fate of two families of DBPs within WDNs. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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4 pages, 710 KiB

Open AccessProceeding Paper

Legacy Pipes Unearthed: Decrypting the Enigma of Pressure Dynamics and Burst Events in Limburg, The Netherlands

by Mohamad Zeidan, Bram Hillebrand and Mirjam Blokker

Eng. Proc. 2024, 69(1), 34; https://doi.org/10.3390/engproc2024069034 - 3 Sep 2024

Viewed by 256

Abstract

This research offers valuable insights into both the historical analysis and future management of water distribution network behavior. By examining the impacts of materials and identifying temporal patterns, the study presents a comprehensive viewpoint essential for informed decision-making in water network management. The [...] Read more.

This research offers valuable insights into both the historical analysis and future management of water distribution network behavior. By examining the impacts of materials and identifying temporal patterns, the study presents a comprehensive viewpoint essential for informed decision-making in water network management. The findings emphasize the relationship between pressure dynamics and burst occurrences, leading to opportunities for further investigation and the development of more precise prediction and mitigation strategies for water distribution systems. The results indicate a consistent pattern of higher real positive percentages compared to random detection rates across the years tested. This suggests a significant correlation between burst events and pressure anomalies, with the detection system performing better than random chance. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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4 pages, 176 KiB

Open AccessProceeding Paper

Predicting the Future Failures of Urban Water Systems: Integrating Climate Change and Machine Learning Prediction Models

by Melica Khashei, Fatemeh Boloukasli ahmadgourabi and Rebecca Dziedzic

Eng. Proc. 2024, 69(1), 35; https://doi.org/10.3390/engproc2024069035 - 3 Sep 2024

Viewed by 312

Abstract

The state of watermain systems is intrinsically linked to climate factors such as fluctuations in temperature and variations in rainfall. However, the integration of these climate-related factors into watermain failure prediction models, with a specific focus on climate change impacts, remains insufficiently explored. [...] Read more.

The state of watermain systems is intrinsically linked to climate factors such as fluctuations in temperature and variations in rainfall. However, the integration of these climate-related factors into watermain failure prediction models, with a specific focus on climate change impacts, remains insufficiently explored. In response to these challenges, this research incorporates the potential effects of climate change on the frequency of watermain breaks by utilizing machine learning techniques, including K-Nearest Neighbours, Random Forest, Artificial Neural Network, and Extreme Gradient Boosting. By leveraging projected climate trends, the models provide actionable intelligence that can inform the development of more robust maintenance and rehabilitation strategies. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

4 pages, 1138 KiB

Open AccessProceeding Paper

Application of a Stochastic Model for Water Demand Assessment under Water Scarcity and Intermittent Networks

by Stefania Piazza, Mariacrocetta Sambito and Gabriele Freni

Eng. Proc. 2024, 69(1), 36; https://doi.org/10.3390/engproc2024069036 - 3 Sep 2024

Viewed by 231

Abstract

Climate change is affecting water resources and other aspects of life in many countries, generating more frequent extreme events. Users react to intermittent supply by implementing local private tanks to collect as much water resources as possible to cope with water distribution suspension [...] Read more.

Climate change is affecting water resources and other aspects of life in many countries, generating more frequent extreme events. Users react to intermittent supply by implementing local private tanks to collect as much water resources as possible to cope with water distribution suspension periods. Such tanks are commonly overdesigned due to the common perception that water resources are essential for human activities and the general need of users to safeguard their water supplies. This study evaluated the impact of water scarcity and users’ self-adaptation strategies on water demand under intermittent flow conditions by implementing an experimental campaign in a real network. The analysis was conducted using a short-term water demand forecast model that reproduces periodic patterns observed at an annual, weekly and daily level to evaluate the adaptation response of users concerning the scarcity of water resources through a comparison between the real pattern of the network and the pattern of local tanks. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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4 pages, 586 KiB

Open AccessProceeding Paper

Machine Learning Model for Battle of Water Demand Forecasting

by Mario Pagano, Giovanni Francesco Santonastaso, Armando Di Nardo, Salvatore Cuomo and Vincenzo Schiano Di Cola

Eng. Proc. 2024, 69(1), 37; https://doi.org/10.3390/engproc2024069037 - 3 Sep 2024

Viewed by 346

Abstract

This article investigates the optimization of urban water distribution in the context of population growth and climate change. It highlights the use of the ExtraTreesRegressor algorithm to forecast water demand with greater accuracy. By analyzing a dataset from North-East Italy, the study demonstrates [...] Read more.

This article investigates the optimization of urban water distribution in the context of population growth and climate change. It highlights the use of the ExtraTreesRegressor algorithm to forecast water demand with greater accuracy. By analyzing a dataset from North-East Italy, the study demonstrates the importance of temporal dynamics over meteorological factors in predicting water consumption patterns. The findings present a novel approach to improving water management strategies, demonstrating machine learning’s potential in addressing critical urban infra-structure challenges. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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4 pages, 696 KiB

Open AccessProceeding Paper

Modelling Consumer Demand in Intermittent Water Supply (IWS) Networks: Evidence from Nepal

by Matthew MacRorie, Sally Weston, Kabindra Pudasaini, Robin Price, Vanessa Speight and Richard Collins

Eng. Proc. 2024, 69(1), 38; https://doi.org/10.3390/engproc2024069038 - 3 Sep 2024

Viewed by 310

Abstract

Modelling consumer demand under intermittent water supply (IWS) is an unresolved challenge. To understand withdrawal behaviours in more detail, fifty-six smart meters were installed in households across an IWS network in Lahan, Nepal. The most frequent withdrawal type was small withdrawals (median two [...] Read more.

Modelling consumer demand under intermittent water supply (IWS) is an unresolved challenge. To understand withdrawal behaviours in more detail, fifty-six smart meters were installed in households across an IWS network in Lahan, Nepal. The most frequent withdrawal type was small withdrawals (median two litres), while large tank-filling-type behaviours contributed significantly to a household’s overall water consumption. Behaviour was highly heterogeneous; households with large storage tanks tended to practice tank-filling behaviour significantly more than those without. Consequently, a one-size-fits-all approach to consumer demand modelling may not always be appropriate and could lead to unrealistic predictions of supply inequality. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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4 pages, 238 KiB

Open AccessProceeding Paper

Water Distribution Network Reliability Assessment beyond the Resilience Index

by Joaquim Sousa, João Muranho, Marco Bonora and Mario Maiolo

Eng. Proc. 2024, 69(1), 39; https://doi.org/10.3390/engproc2024069039 - 3 Sep 2024

Viewed by 257

Abstract

Water distribution network design must consider cost and reliability, with reliability being complex to assess, involving mechanical, hydraulic, and water quality aspects. Current metrics like flow entropy and resilience index have known flaws. This paper presents a new index, addressing the known weaknesses [...] Read more.

Water distribution network design must consider cost and reliability, with reliability being complex to assess, involving mechanical, hydraulic, and water quality aspects. Current metrics like flow entropy and resilience index have known flaws. This paper presents a new index, addressing the known weaknesses of the original resilience index and including critical network features in reliability assessment. The new proposed index introduces a novel pressure surplus threshold, setting more realistic pressure limits in operational management. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

4 pages, 693 KiB

Open AccessProceeding Paper

Hybrid Chemical and Data-Driven Model for Stiff Chemical Kinetics Using a Physics-Informed Neural Network

by Matthew Frankel, Mario De Florio, Enrico Schiassi and Lina Sela

Eng. Proc. 2024, 69(1), 40; https://doi.org/10.3390/engproc2024069040 - 3 Sep 2024

Viewed by 308

Abstract

Models of chemical kinetic processes, comprising systems of stiff ordinary differential equations (ODEs), are essential for modeling important chemical reactions relevant to drinking water chemistry, such as disinfectant decay and disinfection byproduct formation. However, the accuracy of these models can be inhibited by [...] Read more.

Models of chemical kinetic processes, comprising systems of stiff ordinary differential equations (ODEs), are essential for modeling important chemical reactions relevant to drinking water chemistry, such as disinfectant decay and disinfection byproduct formation. However, the accuracy of these models can be inhibited by (1) the challenge of fully describing the chemical reaction system, and (2) additional chemical reactions occurring in actual environmental settings that were not accounted for in the laboratory conditions used to develop and calibrate the models. This study proposes the use of a Physics-Informed Neural Network framework, utilizing the eXtreme Theory of Functional Connections (X-TFC) technique to create a hybrid chemical- and data-driven model that incorporates data and the underlying system of ODEs into the trained model in order to increase the accuracy of the predicted chemical concentrations. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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4 pages, 484 KiB

Open AccessProceeding Paper

Sequence-to-Sequence Deep Learning for Urban Water Demand Forecasting

by Mohammad Sina Jahangir and John Quilty

Eng. Proc. 2024, 69(1), 41; https://doi.org/10.3390/engproc2024069041 - 3 Sep 2024

Viewed by 338

Abstract

Accurate urban water demand (UWD) forecasts are key to the effective management of water distribution systems. This research explores the potential of encoder–decoder models, specifically sequence-to-sequence (S2S) deep learning models, for UWD forecasting. Two models were developed as follows: one based on long [...] Read more.

Accurate urban water demand (UWD) forecasts are key to the effective management of water distribution systems. This research explores the potential of encoder–decoder models, specifically sequence-to-sequence (S2S) deep learning models, for UWD forecasting. Two models were developed as follows: one based on long short-term memory (LSTM) networks and another using transformers. The models were trained on data from ten district metered areas (DMAs) in Northeast Italy. The results confirmed that the transformer models consistently outperformed the LSTM models across all DMAs, with an average (across all DMAs) improvement in mean absolute error of 15.3%. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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4 pages, 558 KiB

Open AccessProceeding Paper

Cascade Machine Learning Approach Applied to Short-Term Medium Horizon Demand Forecasting

by Bruno Brentan, Ariele Zanfei, Martin Oberascher, Robert Sitzenfrei, Joaquin Izquierdo and Andrea Menapace

Eng. Proc. 2024, 69(1), 42; https://doi.org/10.3390/engproc2024069042 - 3 Sep 2024

Viewed by 275

Abstract

This work proposes a cascade model incorporating Long–Short-Term Memory (LSTM) and Multi-Layer Perceptron (MLP), which offers a more reliable model to forecast short-term (hourly) and medium horizon (week) water demand. The MLP model integrates the previously forecasted demand with exogenous variables, functioning as [...] Read more.

This work proposes a cascade model incorporating Long–Short-Term Memory (LSTM) and Multi-Layer Perceptron (MLP), which offers a more reliable model to forecast short-term (hourly) and medium horizon (week) water demand. The MLP model integrates the previously forecasted demand with exogenous variables, functioning as a filter to enhance the accuracy of the LSTM estimation. The LSTM model estimates, utilizing a univariate approach, the hourly forecasting of water demand for the entire available dataset and the minimum night flow. The algorithm considers various time series sizes for each DMA and predicts the water demand values for each hour throughout the week. Having forecasted all timesteps with the LSTM, a virtual online process can be implemented to enhance forecasting quality. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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5 pages, 1201 KiB

Open AccessProceeding Paper

Assessing the Impact of Asset Management on Energy Recovery: The ENERGIDRICA Project

by Andres Ariza, Laura Enriquez, Antonietta Simone, Francesco G. Ciliberti, Daniele B. Laucelli and Luigi Berardi

Eng. Proc. 2024, 69(1), 43; https://doi.org/10.3390/engproc2024069043 - 3 Sep 2024

Viewed by 255

Abstract

The ENERGIDRICA project was born in 2017 at a time of transformation in the “management of water infrastructure” in Italy due to socioeconomic and technological events that have determined the current operational context, in which the “digital transition” represents an opportunity to make [...] Read more.

The ENERGIDRICA project was born in 2017 at a time of transformation in the “management of water infrastructure” in Italy due to socioeconomic and technological events that have determined the current operational context, in which the “digital transition” represents an opportunity to make the processes related to the management and planning activities for these systems more effective and efficient. The concept of the water–energy nexus is the basis of ENERGIDRICA because an efficient use of energy in aqueducts has positive hydraulic and CO₂-related impacts. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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4 pages, 1398 KiB

Open AccessProceeding Paper

Efficient Identification Strategy of Isolation Valves to Maintain through Modularity-Based WDN Clustering

by Amirabbas Mottahedin, Carlo Giudicianni, Bruno Brentan and Enrico Creaco

Eng. Proc. 2024, 69(1), 44; https://doi.org/10.3390/engproc2024069044 - 3 Sep 2024

Viewed by 226

Abstract

This paper proposes a novel methodology for identifying a subset of critical isolation valves in water distribution networks (WDNs), the guaranteed operability of which significantly mitigates the risk associated with potential failures of other valves. The methodology employs a modularity-based clustering algorithm based [...] Read more.

This paper proposes a novel methodology for identifying a subset of critical isolation valves in water distribution networks (WDNs), the guaranteed operability of which significantly mitigates the risk associated with potential failures of other valves. The methodology employs a modularity-based clustering algorithm based on the dual segment/valve topology network to define strategic boundary valves between clusters that must be kept operable. A general framework for assessing the efficiency of the identification strategy, which takes into account the uncertainties about location of failed valves and valve failure rates, is also proposed. The results show that the proposed strategy significantly outperforms an identification scenario based on engineering judgment. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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4 pages, 653 KiB

Open AccessProceeding Paper

An Innovative Model-Based Methodology for Rapid Response to Drinking Water Contamination Events

by Sotirios Paraskevopoulos, Stelios G. Vrachimis, Marios S. Kyriakou, Mirjam Blokker, Patrick Smeets, Demetrios G. Eliades, Marios Polycarpou and Gertjan Medema

Eng. Proc. 2024, 69(1), 45; https://doi.org/10.3390/engproc2024069045 - 3 Sep 2024

Viewed by 279

Abstract

In a desktop exercise, a water utility’s emergency response to suspected wastewater contamination in a drinking water network was compared with a model-based approach using PathoINVEST. This tool simulates contamination scenarios and assists with locating the source of contamination using sampling results. The [...] Read more.

In a desktop exercise, a water utility’s emergency response to suspected wastewater contamination in a drinking water network was compared with a model-based approach using PathoINVEST. This tool simulates contamination scenarios and assists with locating the source of contamination using sampling results. The sampling procedure used a portable sensor that offers rapid (20 min time-to-result) screening of fecal contamination. Preliminary results show that the model-based approach is able to find the contamination source faster and with fewer samples than current practices. Integrating modeling and rapid sensor tools in emergency responses improves decision-making and public health protection in drinking water networks. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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4 pages, 654 KiB

Open AccessProceeding Paper

Incorporating Flexibility in the Long-Term Design of Water Distribution Systems Using Operational Variables

by Dennis Zanutto, Andrea Castelletti and Dragan Savic

Eng. Proc. 2024, 69(1), 46; https://doi.org/10.3390/engproc2024069046 - 4 Sep 2024

Viewed by 247

Abstract

This work investigates the effect of operational variables on water distribution system design optimisation. The “Anytown” problem is approached with three formulations of the operational decision variables to examine how different models of such components affect the design solutions and the optimisation process. [...] Read more.

This work investigates the effect of operational variables on water distribution system design optimisation. The “Anytown” problem is approached with three formulations of the operational decision variables to examine how different models of such components affect the design solutions and the optimisation process. The formulations that jointly optimise operations and design decision variables can double the energy surplus for the same cost compared to a design-only formulation. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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5 pages, 9624 KiB

Open AccessProceeding Paper

Metering Error Assessment Model Considering Multiple Factors

by Kunyi Li, Jinliang Gao, Wenyan Wu, Shihua Qi, Huizhe Cao, Wei Qiu, Yuan Tian and Xiaoyu Zhu

Eng. Proc. 2024, 69(1), 47; https://doi.org/10.3390/engproc2024069047 - 4 Sep 2024

Viewed by 278

Abstract

This study investigates novel methods for estimating metering errors in water meters, crucial for effectively managing apparent losses in Water Distribution Networks. Laboratory experiments were conducted to analyze the impact of various factors on metering errors. The Gene Expression Programming (GEP) algorithm was [...] Read more.

This study investigates novel methods for estimating metering errors in water meters, crucial for effectively managing apparent losses in Water Distribution Networks. Laboratory experiments were conducted to analyze the impact of various factors on metering errors. The Gene Expression Programming (GEP) algorithm was used to create a metering error assessment model, which was then validated through field trials in a DMA. Results indicate that metering errors are influenced by factors such as installation position, tilt angle, flow rates, and operational time. The GEP-based model showed high accuracy, with a mean squared error as low as 0.08, and a mere +0.5% difference from actual field measurements. This model offers water utility companies a cost-effective tool to assess metering errors without disassembly, offering a cost-effective tool for enhancing water supply management. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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5 pages, 213 KiB

Open AccessProceeding Paper

Optimizing Short-Term Water Demand Forecasting: A Comparative Approach to the Battle of Water Demand Forecasting

by Bruno Ferreira, Raquel Barreira, João Caetano, Maria Grazia Quarta and Nelson Carriço

Eng. Proc. 2024, 69(1), 48; https://doi.org/10.3390/engproc2024069048 - 4 Sep 2024

Viewed by 290

Abstract

The current paper presents a forecasting methodology for short-term water demand forecasting in the context of the Battle of Water Demand Forecasting. The methodology considers five distinct forecasting techniques, which are compared in terms of their forecasting ability for a preceding period, typically [...] Read more.

The current paper presents a forecasting methodology for short-term water demand forecasting in the context of the Battle of Water Demand Forecasting. The methodology considers five distinct forecasting techniques, which are compared in terms of their forecasting ability for a preceding period, typically spanning a day or a week. The best-performing model is identified through error assessment between model predictions and actual measurements. This model is finally used to estimate the values for the forecasting horizon. This methodology directly considers the importance of tailoring the model to the specific case study and objectives. However, it is computationally intensive and relies on the fact that there will be not much variance between the preceding period and forecasting horizon results. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

4 pages, 1375 KiB

Open AccessProceeding Paper

Application of Feedforward Artificial Neural Networks to Predict the Hydraulic State of a Water Distribution Network

by Leandro Evangelista, Débora Móller, Bruno Brentan and Gustavo Meirelles

Eng. Proc. 2024, 69(1), 49; https://doi.org/10.3390/engproc2024069049 - 4 Sep 2024

Viewed by 276

Abstract

Improving the operational efficiency of water distribution networks (WDNs) is a subject that has been widely explored in the literature. Usually, a hydraulic model is used jointly with optimization methods, which require considerable computational effort, hindering real-time interventions. Surrogate models based on machine [...] Read more.

Improving the operational efficiency of water distribution networks (WDNs) is a subject that has been widely explored in the literature. Usually, a hydraulic model is used jointly with optimization methods, which require considerable computational effort, hindering real-time interventions. Surrogate models based on machine learning are being studied to estimate the hydraulic state of WDNs and reduce the processing time, and the results have been successful. In this paper, different feedforward artificial neural networks (FFNNs) of the multilayer perceptron (MPL) type were developed to estimate important hydraulic parameters that were applied to optimization algorithms, namely, (i) energy consumption; (ii) tank levels; (iii) pressure in consumption nodes; and (iv) minimum pressure. These parameters were chosen because they are frequently used in objective functions, minimizing energy consumption and leakage volume, as well in operational restrictions. The results showed that creating an individual MLP for each parameter can be a good strategy to improve MLP accuracy. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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4 pages, 696 KiB

Open AccessProceeding Paper

Large-Scale Multipurpose Benchmark Datasets for Assessing Data-Driven Deep Learning Approaches for Water Distribution Networks

by Andrés Tello, Huy Truong, Alexander Lazovik and Victoria Degeler

Eng. Proc. 2024, 69(1), 50; https://doi.org/10.3390/engproc2024069050 - 4 Sep 2024

Viewed by 421

Abstract

Currently, the number of common benchmark datasets that researchers can use straight away for assessing data-driven deep learning approaches is very limited. Most studies provide data as configuration files. It is still up to each practitioner to follow a particular data generation method [...] Read more.

Currently, the number of common benchmark datasets that researchers can use straight away for assessing data-driven deep learning approaches is very limited. Most studies provide data as configuration files. It is still up to each practitioner to follow a particular data generation method and run computationally intensive simulations to obtain usable data for model training and evaluation. In this work, we provide a collection of datasets that includes several small- and medium-sized publicly available Water Distribution Networks (WDNs), including Anytown, Modena, Balerma, C-Town, D-Town, L-Town, Ky1, Ky6, Ky8, and Ky10. In total, 1,394,400 h of WDN data operating under normal conditions are made available to the community. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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4 pages, 546 KiB

Open AccessProceeding Paper

Fast Firefighting Water Capacity Assessment Using a Streamlined Single-Loop Hybrid Search

by Felipe Hernández

Eng. Proc. 2024, 69(1), 51; https://doi.org/10.3390/engproc2024069051 - 4 Sep 2024

Viewed by 267

Abstract

The water distribution system firefighting capacity is widely estimated using decades-old methods that are inefficient for the scale of typical models nowadays. This article introduces an updated algorithm that streamlines the estimation by using a single iterative loop that simultaneously solves for hydrant [...] Read more.

The water distribution system firefighting capacity is widely estimated using decades-old methods that are inefficient for the scale of typical models nowadays. This article introduces an updated algorithm that streamlines the estimation by using a single iterative loop that simultaneously solves for hydrant capacity and the hydraulic effects on the network. The method features a hybrid physically based and heuristic local search approach, and a strategy to easily rank the criticality of network elements that might violate service level constraints. Tests on three models of varying size demonstrate the significant accuracy and efficiency benefits of the proposed approach. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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4 pages, 537 KiB

Open AccessProceeding Paper

A Hybrid Graph–Hydraulic Approach for Identifying Critical Elements in Water Distribution Networks

by Rahul Satish, Mohsen Hajibabaei, Martin Oberascher and Robert Sitzenfrei

Eng. Proc. 2024, 69(1), 52; https://doi.org/10.3390/engproc2024069052 - 4 Sep 2024

Viewed by 289

Abstract

Water distribution networks (WDNs) are susceptible to vulnerabilities that necessitate proactive management to ensure efficient incident management. When dealing with a sequence of failures triggered, for example, by hydraulic redistributions under failure conditions, the computational burden often becomes the limiting factor for exploring [...] Read more.

Water distribution networks (WDNs) are susceptible to vulnerabilities that necessitate proactive management to ensure efficient incident management. When dealing with a sequence of failures triggered, for example, by hydraulic redistributions under failure conditions, the computational burden often becomes the limiting factor for exploring scenarios. Therefore, this study proposes a hybrid method combining a graph-based approach for prescreening critical pipes with a hydraulic assessment to rapidly identify critical nodes. Tested on an Austrian WDN, this approach effectively pinpoints primary failures (pipe failures) while reducing computational time. By integrating the hydraulic approach, the method successfully identified the most critical elements due to the failures. This method empowers operators to mitigate the impact of potential failures and enhance disaster robustness. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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4 pages, 437 KiB

Open AccessProceeding Paper

Towards a Consistent Classification System for Condition Assessment of Drainage Pipes

by Zahra Tizmaghz, Jakobus E. van Zyl and Theunis F.P. Henning

Eng. Proc. 2024, 69(1), 53; https://doi.org/10.3390/engproc2024069053 - 4 Sep 2024

Viewed by 227

Abstract

Municipal drainage systems consist of sewer and stormwater pipes. These systems represent a huge investment of public money and are thus important to monitor, model, and manage to ensure optimal operation and service life. Since pipe deterioration is driven by a finite number [...] Read more.

Municipal drainage systems consist of sewer and stormwater pipes. These systems represent a huge investment of public money and are thus important to monitor, model, and manage to ensure optimal operation and service life. Since pipe deterioration is driven by a finite number of root causes and processes, it should be possible to define a uniform classification system that can be applied internationally for different objectives, such as deterioration modelling and asset management. A literature review revealed that no uniform classification system currently exists and that a range of different definitions and criteria are used. This paper proposes a uniform classification system for drainage pipes consisting of three top-level categories (failures, defects, and factors) with subcategories based on functional or temporal considerations. Each category is unambiguously defined, and a classification flow diagram is presented. Adopting a uniform classification system will allow future research to be interpreted more consistently and allow the results of different studies to be compared rationally. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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5 pages, 839 KiB

Open AccessProceeding Paper

Co-Optimization of Water–Energy Nexus Systems and Challenges

by Jiawei Zeng and Zhaoxi Liu

Eng. Proc. 2024, 69(1), 54; https://doi.org/10.3390/engproc2024069054 - 4 Sep 2024

Viewed by 334

Abstract

This study presents an advanced co-optimization model for water–energy nexus systems (WENSs), illustrating considerable benefits in both energy conservation and cost reduction through synergistic operations. Case studies compare the co-optimized operations of a 33-bus power distribution network (PDN) coupled with a commercial-scale 15-node [...] Read more.

This study presents an advanced co-optimization model for water–energy nexus systems (WENSs), illustrating considerable benefits in both energy conservation and cost reduction through synergistic operations. Case studies compare the co-optimized operations of a 33-bus power distribution network (PDN) coupled with a commercial-scale 15-node water distribution network (WDN) via water pumps and a standalone operations of a PDN and WDN, revealing that co-optimization notably decreases the operational costs for both networks by 23% and 49%, respectively, leading to substantial daily savings. In addition, this paper summarizes the current problems based on previous research, delineating the challenges in the co-optimization and management of WENSs, such as modeling inaccuracies, uncertainty management, and multi-stakeholder governance, providing meaningful insights and potential directions for future research. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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4 pages, 182 KiB

Open AccessProceeding Paper

Top Ten Reasons to Use 100 mm Diameter Pipes in North America

by John Gibson and Bryan Karney

Eng. Proc. 2024, 69(1), 55; https://doi.org/10.3390/engproc2024069055 - 4 Sep 2024

Viewed by 264

Abstract

North American fire insurance and the American Water Works Association (AWWA) recommend that no pipes smaller than 150 mm in diameter are used in water distribution networks, mainly for reasons of fire protection. However, the 150 mm requirement reaches back more than one [...] Read more.

North American fire insurance and the American Water Works Association (AWWA) recommend that no pipes smaller than 150 mm in diameter are used in water distribution networks, mainly for reasons of fire protection. However, the 150 mm requirement reaches back more than one hundred years, cited by the AWWA at least as far back as 1916. In general, North American fire flow requirements are shown to be conservative compared to other places in the world. We show how pipe cost, water loss, water age, disinfection byproduct formation, contamination risks, and transients can all be improved with 100 mm diameter pipes. Perhaps most compelling is the fact that 100 mm pipes are used widely elsewhere. Perhaps it is time to consider permitting 100 mm pipes as the minimum recommended size for use in North America, especially in modern residential service. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

4 pages, 1478 KiB

Open AccessProceeding Paper

Battle of Water Demand Forecasting: An Optimized Deep Learning Model

by Mohammadali Geranmehr, Alemtsehay G. Seyoum and Mostapha Kalami Heris

Eng. Proc. 2024, 69(1), 56; https://doi.org/10.3390/engproc2024069056 - 4 Sep 2024

Viewed by 416

Abstract

Ensuring a steady supply of drinking water is crucial for communities, but predicting how much water will be needed is challenging because of uncertainties. As a part of Battle of Water Demand Forecasting (BWDF), this study delves into the application of Long Short-Term [...] Read more.

Ensuring a steady supply of drinking water is crucial for communities, but predicting how much water will be needed is challenging because of uncertainties. As a part of Battle of Water Demand Forecasting (BWDF), this study delves into the application of Long Short-Term Memory (LSTM) networks for water demand forecasting in a city situated in the northeast of Italy. The focus is on forecasting the demand across ten distinct District Metering Areas (DMAs) over four distinct stages. To enhance the performance of the LSTM model, an evolutionary optimization algorithm is integrated, aiming to fine-tune the model’s hyper-parameters effectively. Results indicate the promising potential of this approach for short-term demand forecasting. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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4 pages, 313 KiB

Open AccessProceeding Paper

A Review of Scenario-Based Approaches in Water Systems Design

by Christos Michalopoulos, Ina Vertommen, Christos Makropoulos and Dragan Savic

Eng. Proc. 2024, 69(1), 57; https://doi.org/10.3390/engproc2024069057 - 4 Sep 2024

Viewed by 394

Abstract

For the design of water distribution networks (WDNs), a multitude of factors must be considered to achieve a resilient and robust system, given the long lifespan of these systems. Designers face challenges such as climate and demographic changes, fluctuating water demand, policy shifts, [...] Read more.

For the design of water distribution networks (WDNs), a multitude of factors must be considered to achieve a resilient and robust system, given the long lifespan of these systems. Designers face challenges such as climate and demographic changes, fluctuating water demand, policy shifts, and evolving stakeholder preferences. Traditional models, including both deterministic and various stochastic approaches, often encounter difficulties when dealing with the profound uncertainties present in these variables. As a result, they frequently fail to predict long-term performance accurately. The recent literature has indicated a shift towards non-deterministic methods that embrace these uncertainties, especially through scenario generation techniques. In this paper, we delve into these alternative methodologies, specifically focusing on scenario generation techniques that effectively incorporate deep uncertainties into the design process of WDNs. We aim to identify, categorize, and analyze these methodologies, highlighting their strengths, limitations, and areas for improvement. Finally, we also suggest new research directions for scenario-based planning in WDNs to improve their adaptability and resilience against uncertain futures. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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4 pages, 1113 KiB

Open AccessProceeding Paper

Improving the Performance of Bayesian Decision Networks for Water Quality Sensor Deployment in UDNs through a Reduced Search Domain

by Mariacrocetta Sambito and Antonietta Simone

Eng. Proc. 2024, 69(1), 58; https://doi.org/10.3390/engproc2024069058 - 4 Sep 2024

Viewed by 252

Abstract

The contamination of urban drainage systems (UDNs) represents a serious threat to the environment and public health. Treatment plants are often inefficient in their removal, making timely identification and isolation interventions necessary. In this regard, various monitoring strategies have been proposed, among which [...] Read more.

The contamination of urban drainage systems (UDNs) represents a serious threat to the environment and public health. Treatment plants are often inefficient in their removal, making timely identification and isolation interventions necessary. In this regard, various monitoring strategies have been proposed, among which the Bayesian decision network (BDN) approach has proven to be very effective, although also very complex. To reduce their level of complexity, it is usual to optimize them using approaches based on preconditioning. The present work fits into this framework by proposing a two-phase strategy aimed at identifying an optimal monitoring system for UDNs. The first phase involves reducing the search domain of the system using a complex network theory (CNT) topological metric adapted to infrastructure systems; the second phase implements the Bayesian approach to the new search space to optimize the position of the sensors in the network. The results are promising and reveal that the strategy could be valuable to water utilities. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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4 pages, 1133 KiB

Open AccessProceeding Paper

Optimizing the Performance of Water Distribution Networks: Sectorization and Pressure Management for Leakage Reduction

by Melina Denardi, Jezabel Bianchotti, Gabriel Puccini and Mario Castro-Gama

Eng. Proc. 2024, 69(1), 59; https://doi.org/10.3390/engproc2024069059 - 4 Sep 2024

Viewed by 262

Abstract

Sectorization and pressure management are techniques that simplify leak detection and its control in water networks. This article proposes a novel three-stage methodology. First, using complex network theory, it identifies conceptual cuts to form communities. Second, it optimizes District Measurement Areas (DMAs) by [...] Read more.

Sectorization and pressure management are techniques that simplify leak detection and its control in water networks. This article proposes a novel three-stage methodology. First, using complex network theory, it identifies conceptual cuts to form communities. Second, it optimizes District Measurement Areas (DMAs) by reconnecting these cuts, balancing resilience loss and open connections. Third, it reduces network pressure during off-peak hours by installing pressure-reducing valves to create Pressure Management Zones (PMZs). Applied to an academic network and a real network, this approach establishes both DMAs and PMZs, enhancing the supply quality and reducing leakages. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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5 pages, 191 KiB

Open AccessProceeding Paper

A Water Futures Approach on Water Demand Forecasting with Online Ensemble Learning

by Dennis Zanutto, Christos Michalopoulos, Georgios-Alexandros Chatzistefanou, Lydia Vamvakeridou-Lyroudia, Lydia Tsiami, Konstantinos Glynis, Panagiotis Samartzis, Luca Hermes, Fabian Hinder, Jonas Vaquet, Valerie Vaquet, Demetrios Eliades, Marios Polycarpou, Phoebe Koundouri, Barbara Hammer and Dragan Savić

Eng. Proc. 2024, 69(1), 60; https://doi.org/10.3390/engproc2024069060 - 4 Sep 2024

Viewed by 477

Abstract

This study presents a collaborative framework developed by the Water Futures team of researchers for the “Battle of the Water Demand Forecasting” challenge at the 3rd International WDSA-CCWI Joint Conference. The framework integrates an ensemble of machine learning forecasting models into a deterministic [...] Read more.

This study presents a collaborative framework developed by the Water Futures team of researchers for the “Battle of the Water Demand Forecasting” challenge at the 3rd International WDSA-CCWI Joint Conference. The framework integrates an ensemble of machine learning forecasting models into a deterministic outcome consistent with the competition formulation. The water demand trajectory over a week exhibits complex overlapping patterns and non-linear dependencies to multiple features and time-dependent events that a single model cannot accurately predict. As such, the reconciled forecast from an ensemble of models exceeds the performance of the individual ones and exhibits higher stability across the weeks of the year and district metered areas considered. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

4 pages, 1023 KiB

Open AccessProceeding Paper

Assessment and Variation of Water Quality in Urban Distribution Networks: From Reservoir to Faucet

by Eunhye Jeong, Kyung-Yup Hwang, Sumin Lee, Kwangjun Jung and Hyunjun Kim

Eng. Proc. 2024, 69(1), 61; https://doi.org/10.3390/engproc2024069061 - 3 Sep 2024

Viewed by 297

Abstract

This study focuses on evaluating the spatiotemporal variations in water quality across a potable water distribution network in D City, South Korea, spanning from a reservoir to a large consumer’s tap. Utilizing water quality sensors installed at strategic points (the reservoir, District Metered [...] Read more.

This study focuses on evaluating the spatiotemporal variations in water quality across a potable water distribution network in D City, South Korea, spanning from a reservoir to a large consumer’s tap. Utilizing water quality sensors installed at strategic points (the reservoir, District Metered Area inlet, consumer inlet, tank outlet, and tap), this research observes real-time changes in parameters such as chlorine concentration, turbidity, temperature, pH, and electrical conductivity. The investigation, conducted from 25 January 2024 to 4 February 2024, identifies significant trends such as the gradual decrease in chlorine concentration with distance and time, an increase in turbidity and temperature towards the consumer end, and variations in electrical conductivity. These observations suggest that there is an influence of pipe material interactions, water stagnation, and usage patterns on water quality. This study contributes to understanding the dynamic nature of tap water’s quality, highlighting the need for continuous monitoring and research to manage water quality effectively in urban distribution networks. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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3 pages, 525 KiB

Open AccessProceeding Paper

Stochastic Insights into Leakage Dynamics across Diverse Pipe Materials in Water Distribution Systems

by Soheila Beygi, Jakobus E. van Zyl and Brendon Harkness

Eng. Proc. 2024, 69(1), 62; https://doi.org/10.3390/engproc2024069062 - 4 Sep 2024

Viewed by 277

Abstract

This study developed more realistic stochastic models of pipe failures that incorporate leak types and dimensions based on different pipe materials. The distributions of pipe failure types and properties were identified by analysing photographic records of failed pipes in Auckland, New Zealand. A [...] Read more.

This study developed more realistic stochastic models of pipe failures that incorporate leak types and dimensions based on different pipe materials. The distributions of pipe failure types and properties were identified by analysing photographic records of failed pipes in Auckland, New Zealand. A stochastic model generated leaks in a typical DMA consisting of different pipe materials to different Infrastructure Leakage Index (ILI) levels. After analysing 100 networks for each scenario, the study observed that different pipe materials had distinct leakage exponent distributions. This study provides a tool for better understanding leakage behaviour in different pipe materials and evaluating methods for better water loss management. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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4 pages, 831 KiB

Open AccessProceeding Paper

Efficient Network Representation: Graph Contraction Strategies in Water Distribution Networks

by Daniel Barros, Jordana Alaggio, Gustavo Meirelles, Bruno Brentan and Edevar Luvizotto

Eng. Proc. 2024, 69(1), 63; https://doi.org/10.3390/engproc2024069063 - 4 Sep 2024

Viewed by 251

Abstract

Water distribution networks (WDNs) are becoming more interconnected with other networks, such as energy and the Internet networks, complicating their analysis. This article proposes an alternative method for reducing the WDN search space and skeletonization using graph theory. The network is represented as [...] Read more.

Water distribution networks (WDNs) are becoming more interconnected with other networks, such as energy and the Internet networks, complicating their analysis. This article proposes an alternative method for reducing the WDN search space and skeletonization using graph theory. The network is represented as a weighted and attributed graph with edge weights as diameters and demand values as vertex attributes. A method for contracting vertices and edges based on similarity values is introduced. The methodology was evaluated using global graph analysis metrics, Crowding and Assortativity Coefficients, showing effectiveness particularly in selecting representative network elements. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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4 pages, 568 KiB

Open AccessProceeding Paper

District Information Areas: A Distributed Decision-Making Approach for Urban Water Systems

by Manuel Herrera, Carlo Giudicianni and Enrico Creaco

Eng. Proc. 2024, 69(1), 64; https://doi.org/10.3390/engproc2024069064 - 4 Sep 2024

Viewed by 273

Abstract

This paper presents a comparison between traditional District Metered Areas (DMAs) and an innovative concept called District Information Areas (DIAs) in managing water distribution systems (WDSs). Both aim to improve efficiency and resilience, but differ in approach. DMAs use physical segmentation with measurement [...] Read more.

This paper presents a comparison between traditional District Metered Areas (DMAs) and an innovative concept called District Information Areas (DIAs) in managing water distribution systems (WDSs). Both aim to improve efficiency and resilience, but differ in approach. DMAs use physical segmentation with measurement devices mainly for leak detection, while DIAs employ smart sensors and data analytics for decentralised management. DIAs operate semi-autonomously, making local decisions based on data analysis and coordinating with neighbouring areas. While traditional methods still play a role in maintenance, DIAs aim to enhance sensor coverage and support future digital twin development. The advantages of DIAs include reduced latency, increased flexibility, improved efficiency, and enhanced resilience during disruptions. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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4 pages, 1249 KiB

Open AccessProceeding Paper

Comparative Risk Evaluation of Contaminant Intrusion in Water Distribution Networks via Complex Network Analysis

by Jordana Alaggio, Daniel Bezerra Barros, Bruno Brentan and Gustavo Meirelles

Eng. Proc. 2024, 69(1), 65; https://doi.org/10.3390/engproc2024069065 - 4 Sep 2024

Viewed by 220

Abstract

Water distribution networks (WDNs) aim to ensure uninterrupted delivery of high-quality water; however, they are susceptible to failures that can compromise water quality. Decision-makers need to pinpoint crucial network components to optimize maintenance and improve system efficiency. This research investigates the risks of [...] Read more.

Water distribution networks (WDNs) aim to ensure uninterrupted delivery of high-quality water; however, they are susceptible to failures that can compromise water quality. Decision-makers need to pinpoint crucial network components to optimize maintenance and improve system efficiency. This research investigates the risks of contaminant intrusion in WDNs. Complex network theory (CNT) provides an alternative approach by modeling WDNs as complex networks and analyzing network dynamics, contaminant propagation, and critical elements. EPANET software simulates contamination, while CNT metrics assess node influence. Our findings demonstrate the compatibility and potential hybrid form to work with these methodologies, offering a more efficient approach to WDN risk management. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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4 pages, 210 KiB

Open AccessProceeding Paper

Optimising Water Allocation for Combined Irrigation and Hydropower Systems

by Francesca Peretti, Andrea Menapace and Maurizio Righetti

Eng. Proc. 2024, 69(1), 66; https://doi.org/10.3390/engproc2024069066 - 4 Sep 2024

Viewed by 272

Abstract

The allocation of water resources among different sectors is often driven by distinct objectives, as exemplified by the divergence between hydropower production and irrigation. This study aims to optimise the water–energy nexus of an irrigation system abstracting water directly from a hydroelectric plant [...] Read more.

The allocation of water resources among different sectors is often driven by distinct objectives, as exemplified by the divergence between hydropower production and irrigation. This study aims to optimise the water–energy nexus of an irrigation system abstracting water directly from a hydroelectric plant by minimising the pumping costs for irrigation, ensuring necessary water needs for crops and maximising revenue from hydropower generation. The optimisation procedure was implemented using a methodology based on a particle swarm optimisation algorithm and applied to a real case study located in northern Italy. The findings offer facility operators a management tool to optimise water resources efficiently for different needs. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

4 pages, 2010 KiB

Open AccessProceeding Paper

Exploring the Extraction of Knowledge from Previous Lessons and Disruptive Events in Water Distribution Networks

by David Ayala-Cabrera, Jorge Francés-Chust, Mario Castro-Gama and Samira Islam

Eng. Proc. 2024, 69(1), 67; https://doi.org/10.3390/engproc2024069067 - 5 Sep 2024

Viewed by 231

Abstract

This work explores the various relationships between several parameters in an incident hub of a small real WDN. To facilitate analysis, incident data were previously categorised depending on the nature of the cause of the incident. The data are analysed through spatial analysis, [...] Read more.

This work explores the various relationships between several parameters in an incident hub of a small real WDN. To facilitate analysis, incident data were previously categorised depending on the nature of the cause of the incident. The data are analysed through spatial analysis, based on the transmission of information from the surrounding areas, and are also incorporated to add certain uncertainty to the information. The results of this characterisation are presented and analysed in this contribution. The results are promising in providing water distribution networks with key parameters that promote prediction and classification processes from the lessons learned. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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4 pages, 646 KiB

Open AccessProceeding Paper

Transient Pressure Estimation Using Data-Driven Models: An Approach Based on Ensemble Trees

by Rafael Barreto, Rui Gabriel Souza, Gustavo Meirelles and Bruno Brentan

Eng. Proc. 2024, 69(1), 68; https://doi.org/10.3390/engproc2024069068 - 5 Sep 2024

Viewed by 239

Abstract

The operation of control devices in a water distribution network establishes a transient flow that leads to pressure oscillation during a certain time. Depending on the pressure wave’s amplitude, infrastructure can be exposed to dangerous pressure levels, collapsing or breaking the pipes. Predicting [...] Read more.

The operation of control devices in a water distribution network establishes a transient flow that leads to pressure oscillation during a certain time. Depending on the pressure wave’s amplitude, infrastructure can be exposed to dangerous pressure levels, collapsing or breaking the pipes. Predicting the maximum and minimum head pressure values caused by an operation can assist in the design of safety devices and increase the lifespan of the distribution network. Nevertheless, the calculation of the pressure wave magnitude based on hydraulic equations can be time consuming, reducing the possibility of an optimal approach for designing a protection system. In this sense, this study presents a data-driven model for predicting pressure values caused by transient flows in a water distribution network. The methodology is implemented using an ensemble tree linked to the XGBoost algorithm and it is applied in two case studies. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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4 pages, 184 KiB

Open AccessProceeding Paper

An Ensemble Data-Driven Approach for Enhanced Short-Term Water Demand Forecasting in Urban Areas

by Amin E. Bakhshipour, Hossein Namdari, Alireza Koochali, Ulrich Dittmer and Ali Haghighi

Eng. Proc. 2024, 69(1), 69; https://doi.org/10.3390/engproc2024069069 - 5 Sep 2024

Viewed by 283

Abstract

This study introduces an innovative ensemble data-driven model designed for short-term water demand forecasting within urban areas. By synergistically combining three distinct machine learning approaches—NHiTS, XGBoost regression, and a multi-head 1D convolutional neural network—our model enhances forecasting accuracy and reliability. This integration not [...] Read more.

This study introduces an innovative ensemble data-driven model designed for short-term water demand forecasting within urban areas. By synergistically combining three distinct machine learning approaches—NHiTS, XGBoost regression, and a multi-head 1D convolutional neural network—our model enhances forecasting accuracy and reliability. This integration not only leverages the unique strengths of each method but also compensates for their individual weaknesses, resulting in a robust solution for predicting urban water demand. Tested against the Battle of Water Demand Forecasting dataset (WDSA-CCWI-2024), our ensemble model demonstrates superior performance, offering a promising tool for efficient water resource management and decision making. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

5 pages, 1177 KiB

Open AccessProceeding Paper

Real-Time Demand Forecasting and Multi-Resolution Model Predictive Control for Water Distribution Networks

by Peter C. N. Verheijen, Ward P. de Groot, Dip Goswami and Mircea Lazar

Eng. Proc. 2024, 69(1), 70; https://doi.org/10.3390/engproc2024069070 - 3 Sep 2024

Viewed by 259

Abstract

In this work, we develop a water demand prediction model for MPC that reliably handles unexpected changes from the daily pattern by incorporating a dynamical model over the current measured demand, fitted using machine learning methods. Secondly, in alignment with the new demand [...] Read more.

In this work, we develop a water demand prediction model for MPC that reliably handles unexpected changes from the daily pattern by incorporating a dynamical model over the current measured demand, fitted using machine learning methods. Secondly, in alignment with the new demand estimator, we also propose a multi-resolution MPC prediction horizon. This improves the responsiveness to unforeseeable disturbances with minimal impact on computational efficiency. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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5 pages, 1074 KiB

Open AccessProceeding Paper

Cloud-Based Control and Monitoring of Water Distribution Network Using Free Spectrum Communication Protocols

by Rohit Raphael, Sri Hari Prasath Ramprasad and Sridharakumar Narasimhan

Eng. Proc. 2024, 69(1), 71; https://doi.org/10.3390/engproc2024069071 - 4 Sep 2024

Viewed by 255

Abstract

Utility management demands two basic functions for an optimal automation scenario, which are monitoring and control. Here, we report a novel approach utilizing free spectrum communication technology and the Internet of Things (IoT) framework for Water Distribution Network (WDN) management. We make use [...] Read more.

Utility management demands two basic functions for an optimal automation scenario, which are monitoring and control. Here, we report a novel approach utilizing free spectrum communication technology and the Internet of Things (IoT) framework for Water Distribution Network (WDN) management. We make use of an architecture combining the free spectrum protocols included in the ISM (Industrial, Scientific, and Medical) radio band, along with cloud-based data management. The main aspects of the developed system are user-friendly operation and control, along with reliable and fault-free operation. In this paper, we discuss, in detail, the architecture, hardware design, and software applications associated with the IoT-based wireless monitoring and control of WDNs. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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4 pages, 609 KiB

Open AccessProceeding Paper

A Full and Simplified Water Distribution Network Model Comparison of Skeletonization Results

by Brian Tugume, Mario Castro-Gama and David Ayala-Cabrera

Eng. Proc. 2024, 69(1), 72; https://doi.org/10.3390/engproc2024069072 - 5 Sep 2024

Viewed by 285

Abstract

Skeletonization involves simplifying dense large-scale water distribution network (WDN) models by preserving key components that significantly impact network behavior. This study explores five WDNs and implements various skeletonization techniques to help identify a universal criterion for the optimal level of simplification. Results suggest [...] Read more.

Skeletonization involves simplifying dense large-scale water distribution network (WDN) models by preserving key components that significantly impact network behavior. This study explores five WDNs and implements various skeletonization techniques to help identify a universal criterion for the optimal level of simplification. Results suggest that diverse skeletonization methods affect network topology and hydraulic accuracy. Single-method techniques tend to preserve hydraulic accuracy better but remove fewer pipes, while hybrid methods sacrifice accuracy for simplified topologies and computational time. In addition, a comparative analysis of SkelEpanet and WNTR software shows comparable performance. Ultimately, this work contributes to addressing uncertainties in transferability to real-world networks. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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4 pages, 993 KiB

Open AccessProceeding Paper

Advancing Water Distribution Network Calibration: A Framework for Comparing Static and Mobile Sensing Approaches

by Alemtsehay G. Seyoum, Simon Tait, Alma N. A. Schellart, Will Shepherd and Joby Boxall

Eng. Proc. 2024, 69(1), 73; https://doi.org/10.3390/engproc2024069073 - 5 Sep 2024

Viewed by 252

Abstract

This study introduces a novel framework for conducting a comparative analysis of static and mobile sensing approaches for the collection of data to be used in network calibration. Two new algorithms that optimize deployment for both static and mobile sensors are proposed. The [...] Read more.

This study introduces a novel framework for conducting a comparative analysis of static and mobile sensing approaches for the collection of data to be used in network calibration. Two new algorithms that optimize deployment for both static and mobile sensors are proposed. The results indicate that deploying a single mobile sensor starting from various locations throughout the network for 24 h can yield pipe roughness calibration results as good as, or slightly superior, to those obtained using static sensors at approximately 90% of the potential monitoring nodes. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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5 pages, 4947 KiB

Open AccessProceeding Paper

Assessing Viscoelastic Parameters of Polymer Pipes via Transient Signals and Artificial Neural Networks

by Mostafa Rahmanshahi, Huan-Feng Duan, Alireza Keramat, Nasim Vafaei Rad and Hossein Azizi Nadian

Eng. Proc. 2024, 69(1), 74; https://doi.org/10.3390/engproc2024069074 - 6 Sep 2024

Viewed by 291

Abstract

This study presents a soft-computing-based method for determining polymer pipelines’ creep function parameters (CFPs) and pressure wave speeds (PWSs) through transient flow analysis. To this end, first, a numerical model for transient flow in polymer pipes was developed in the time domain. Then, [...] Read more.

This study presents a soft-computing-based method for determining polymer pipelines’ creep function parameters (CFPs) and pressure wave speeds (PWSs) through transient flow analysis. To this end, first, a numerical model for transient flow in polymer pipes was developed in the time domain. Then, by considering a pipeline with a specific geometry, 2000 transient flow signals were generated for different CFPs and PWSs. The amplitudes obtained by transforming the time-domain pressure signals to the frequency domain using the fast Fourier transform algorithm are the inputs for an artificial neural network model. The results showed that the proposed approach accurately estimated the creep function of the polymer pipes. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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4 pages, 926 KiB

Open AccessProceeding Paper

Volume-Driven and Flow Control Approach to Optimizing Equity in Intermittent Water Supply Systems

by Greg Hendrickson, Gopinathan R. Abhijith and Lina Sela

Eng. Proc. 2024, 69(1), 75; https://doi.org/10.3390/engproc2024069075 - 6 Sep 2024

Viewed by 252

Abstract

Over 1.3 billion people worldwide are serviced by intermittent water supply (IWS) systems, which are characterized by their inability to provide continuous water to consumers for 24 h a day. Consumers in IWS systems often rely on private storage tanks as a coping [...] Read more.

Over 1.3 billion people worldwide are serviced by intermittent water supply (IWS) systems, which are characterized by their inability to provide continuous water to consumers for 24 h a day. Consumers in IWS systems often rely on private storage tanks as a coping mechanism during periods without water access. Although these tanks can improve supply reliability, they also worsen existing inequity in water access, where some consumers have greater access to water than others. This research introduces a simulation–optimization framework that integrates volume-driven demand into hydraulic simulations in order to account for the utilization of private storage tanks in IWS systems. Bayesian optimization is utilized to determine a flow control schedule that maximizes the local supply and global equity amongst consumers. The proposed approach is applied to an IWS system, where we explore the mechanisms through which the disparity in hydraulic conditions across the network creates inequity in water access. The results reveal a hierarchy in supply amongst the consumers that dictates the degree to which consumers have access to water. While flow controls can offset some of the global disparities, the local supply hierarchy is maintained through micro-level consumer behavior that a partially controlled system cannot fully override. This work underscores the importance of the interplay between local consumer behavior and global supply equity and provides insights into the mechanisms behind supply inequity. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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4 pages, 2308 KiB

Open AccessProceeding Paper

Investigation of Pressure Signal and Leak Detection in Pipes by Using Wavelet Transform in Transient Flow

by Nasim Vafaei Rad, Hossein Azizi Nadian, Roberto Ranzi, Mostafa Rahmanshahi and Mahmood Shafaei Bejestan

Eng. Proc. 2024, 69(1), 76; https://doi.org/10.3390/engproc2024069076 - 6 Sep 2024

Viewed by 324

Abstract

Leakages in pipes lead to water loss, so leak detection to prevent water loss is essential. Transient flow is a method to obtain a wide range of pipe flow data, but generally, signal data have various noises also related to leakages. One effective [...] Read more.

Leakages in pipes lead to water loss, so leak detection to prevent water loss is essential. Transient flow is a method to obtain a wide range of pipe flow data, but generally, signal data have various noises also related to leakages. One effective way to detect leaks is to use wavelet transform (WT). So, in this study, by conducting laboratory experiments and using WT, the behavior of the signal and the effectiveness of wavelet transform were investigated. Results of the research showed that WT is very effective for leak detection, noise reduction, and signal analysis for transient flow. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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4 pages, 1783 KiB

Open AccessProceeding Paper

Rethinking On-Demand Irrigation Systems Using IOT Stand-Alone Technologies

by Giacomo Ferrarese, Alessandro Pagano, Davide Troiani, Anna Ceni, Axel I. Hutomo, Nicola Fontana, Gustavo Marini, Stefano Mambretti and Stefano Malavasi

Eng. Proc. 2024, 69(1), 77; https://doi.org/10.3390/engproc2024069077 - 6 Sep 2024

Viewed by 264

Abstract

The integration of Internet of Things (IoT) technologies into pressurized irrigation water distribution networks holds significant potential for optimizing water utilization, especially given the escalating concerns about scarcity and increasing demand. Nevertheless, within the irrigation domain, the utilization of specific technologies and management [...] Read more.

The integration of Internet of Things (IoT) technologies into pressurized irrigation water distribution networks holds significant potential for optimizing water utilization, especially given the escalating concerns about scarcity and increasing demand. Nevertheless, within the irrigation domain, the utilization of specific technologies and management strategies based on IoT technologies is not yet as widespread as their well-established efficacy would suggest. The present work proposes a management strategy based on such technologies to enhance the sustainability of a case study network, using real operational data during the irrigation season. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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4 pages, 3182 KiB

Open AccessProceeding Paper

Pump Switching-Induced Transients in Water Distribution Networks—Preliminary Laboratory Experiments

by Caterina Capponi, Debora Falocci, Bruno Brunone, Yu Xiaodong, Yu Chao and Silvia Meniconi

Eng. Proc. 2024, 69(1), 78; https://doi.org/10.3390/engproc2024069078 - 6 Sep 2024

Viewed by 276

Abstract

The Water Engineering Laboratory (WEL) of the University of Perugia hosts a real-scale water distribution network (WDN) with a service line comprising high-density polyethylene (HPDE) pipes and supplied by two pumps in series. The carried out unsteady-state tests show the WDN behavior during [...] Read more.

The Water Engineering Laboratory (WEL) of the University of Perugia hosts a real-scale water distribution network (WDN) with a service line comprising high-density polyethylene (HPDE) pipes and supplied by two pumps in series. The carried out unsteady-state tests show the WDN behavior during transients due to pump switching-on and -off. In particular, they underline the most pressure-stressed sections of the system. The obtained results can help water utility managers in protecting these sections with the aim to preserve the integrity of the WDN. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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3 pages, 186 KiB

Open AccessProceeding Paper

Water Demand Forecasting with Multi-Objective Computational Intelligence

by Gilberto Reynoso-Meza and Elizabeth Pauline Carreño-Alvarado

Eng. Proc. 2024, 69(1), 79; https://doi.org/10.3390/engproc2024069079 - 6 Sep 2024

Viewed by 335

Abstract

With increasing pressures from population growth, urbanization, and climate change, effective water resource management is crucial. This paper presents a computational intelligence framework employing machine learning and multi-objective optimization for the short-term forecasting battle of urban water demand within District Metered Areas (DMAs). [...] Read more.

With increasing pressures from population growth, urbanization, and climate change, effective water resource management is crucial. This paper presents a computational intelligence framework employing machine learning and multi-objective optimization for the short-term forecasting battle of urban water demand within District Metered Areas (DMAs). Our methodology utilizes historical data from DMAs in North-East Italy, focusing on daily and weekly forecasts to optimize water utility operations and energy purchasing. By integrating environmental variables, the proposed models aim to improve forecasting accuracy, model interpretability, and structural complexity, thus meeting the practical needs of water utilities. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

5 pages, 1743 KiB

Open AccessProceeding Paper

Evaluating Pipe Burst Flooding Impacts in Urban Environments Using a Hazard-Vulnerability-Risk Approach

by Diego A. Paez and Hailiang Shen

Eng. Proc. 2024, 69(1), 80; https://doi.org/10.3390/engproc2024069080 - 6 Sep 2024

Viewed by 237

Abstract

In this paper, a hazard-vulnerability-risk approach is implemented to assess the impacts of water main break flooding events in an urban setting. The hazard component is evaluated through a combination of estimated burst likelihoods for each water distribution pipe and a two-dimensional flooding [...] Read more.

In this paper, a hazard-vulnerability-risk approach is implemented to assess the impacts of water main break flooding events in an urban setting. The hazard component is evaluated through a combination of estimated burst likelihoods for each water distribution pipe and a two-dimensional flooding model for the city’s overland area. Vulnerability is assessed using the damage curves available in the literature for overland flooding. The output of risk is computed in the form of expected annual losses. The application of the proposed approach and the implemented simulation tools are illustrated through a real-life case study at an undisclosed location. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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4 pages, 550 KiB

Open AccessProceeding Paper

Harnessing the Power of Random Forest for Precise Short-Term Water Demand Forecasting in Italian Water Districts

by Adam Kulaczkowski and Juneseok Lee

Eng. Proc. 2024, 69(1), 81; https://doi.org/10.3390/engproc2024069081 - 6 Sep 2024

Viewed by 309

Abstract

Water demand forecasting is essential for ensuring a reliable water supply in any water utility. It involves making accurate predictions for both short- and long-term water needs. Many traditional time series forecasting methods are presently used; however, recent machine learning techniques have grown [...] Read more.

Water demand forecasting is essential for ensuring a reliable water supply in any water utility. It involves making accurate predictions for both short- and long-term water needs. Many traditional time series forecasting methods are presently used; however, recent machine learning techniques have grown in popularity for their robustness and accuracy. Random forest is an emerging machine learning algorithm which was used to forecast short-term water demand for ten district metered areas in Italy. Our predictions on test datasets using the trained model yielded correlations as high as 0.98. Important explanatory variables affecting model performance included consumption patterns represented by the seven-day water demand lag. In this paper, we present a reliable application of the random forest algorithm for short-term water demand forecasting. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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4 pages, 469 KiB

Open AccessProceeding Paper

Empowering Smart Renewable Cities through Hydropower Technology in Urban Drinking Water Supply Systems

by Arantxa Gamón, Andross Pérez, Carmen Sánchez, Honorio Royo, Teresa Oltra, Cristina de Diego, Román Ponz and María Pedro-Monzonís

Eng. Proc. 2024, 69(1), 82; https://doi.org/10.3390/engproc2024069082 - 6 Sep 2024

Viewed by 403

Abstract

Nowadays, the need to improve the efficiency and sustainability of cities is crucial. Considering that the urban water cycle is one of the most energy-demanding services, it is essential to find ways of management that minimize the use of resources and provide an [...] Read more.

Nowadays, the need to improve the efficiency and sustainability of cities is crucial. Considering that the urban water cycle is one of the most energy-demanding services, it is essential to find ways of management that minimize the use of resources and provide an environmentally friendly supply. To tackle this issue, pressure management within water distribution systems is an effective method for reducing energy consumption. LIFE TURBINES aims to address this challenge by implementing turbine systems that recover energy and regulate pressure in drinking supply networks, thus contributing to cities with low greenhouse gas emissions. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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4 pages, 1106 KiB

Open AccessProceeding Paper

Water Quality Modelling in Water Distribution Systems: Pilot-Scale Measurements and Simulation

by Csaba Hős, Dániel Medve, Andrea Taczman-Brückner and Gabriella Kiskó

Eng. Proc. 2024, 69(1), 83; https://doi.org/10.3390/engproc2024069083 - 8 Sep 2024

Viewed by 301

Abstract

We present the results of water quality measurements in a pilot-scale, continuously circulated test rig consisting of HDPE pipe segments, where pH, conductivity, turbidity, salinity, temperature, and dissolved oxygen were measured daily. Microbiological measurements (CFU) on the pipe wall and in the bulk [...] Read more.

We present the results of water quality measurements in a pilot-scale, continuously circulated test rig consisting of HDPE pipe segments, where pH, conductivity, turbidity, salinity, temperature, and dissolved oxygen were measured daily. Microbiological measurements (CFU) on the pipe wall and in the bulk water were measured at least once every week. The measurement campaign lasted for 18 weeks. In the first part of the paper, we provide an overview of the results and our experiences. In particular, the time histories of the measured quantities are presented and assessed. Additionally, the flow velocity was increased in six steps from 0.4 to 1.1 m/s to study biofilm detachment once every week. In the second part of the paper, we attempt to use these measurement results for the parameter identification of standard biofilm models. In particular, we search for indirect connections between our measurement results and model parameters (e.g., yield and growth-limiting parameters) via optimising, where the objective is to recover the measured CFU concentration results as closely as possible. Finally, we present preliminary results on the critical wall shear stress resulting in biofilm detachment. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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4 pages, 567 KiB

Open AccessProceeding Paper

Uncertainty Sources in the Mechanistic Modeling of Legionella within Building Water Systems

by Catalina Ortiz, Fatemeh Hatam and Michèle Prévost

Eng. Proc. 2024, 69(1), 84; https://doi.org/10.3390/engproc2024069084 - 9 Sep 2024

Viewed by 277

Abstract

Predicting Legionella concentrations reaching users through building water systems requires a comprehensive water quality modeling approach. We integrate various frameworks and data to test the effect of nutrient availability, temperature, chlorine, and biofilm interactions in modeling Legionella. We show that neglecting biofilm [...] Read more.

Predicting Legionella concentrations reaching users through building water systems requires a comprehensive water quality modeling approach. We integrate various frameworks and data to test the effect of nutrient availability, temperature, chlorine, and biofilm interactions in modeling Legionella. We show that neglecting biofilm detachment underestimates concentrations up to 5.5 logs, while including it increases estimates by 4.2 logs. This study identifies critical factors and uncertainty sources for characterizing the Legionella fate and transport phenomena within buildings. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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4 pages, 479 KiB

Open AccessProceeding Paper

Improved WDN Design by Coupling Optimal Pipe Sizing and Isolation Valve Placement

by Amirabbas Mottahedin, Carlo Giudicianni, Maria C. Cunha and Enrico Creaco

Eng. Proc. 2024, 69(1), 85; https://doi.org/10.3390/engproc2024069085 - 3 Sep 2024

Viewed by 203

Abstract

This paper presents a novel methodology for the coupled optimization of pipe sizing and isolation valve placement in water distribution networks (WDNs). By employing a bi-objective genetic algorithm, the methodology searches for the best solutions in the trade-off between minimizing the average demand [...] Read more.

This paper presents a novel methodology for the coupled optimization of pipe sizing and isolation valve placement in water distribution networks (WDNs). By employing a bi-objective genetic algorithm, the methodology searches for the best solutions in the trade-off between minimizing the average demand shortfalls caused by segment isolations and minimizing the total installation costs of pipes and valves. The optimization also incorporates a constraint that ensures the telescopic distribution property of pipe diameters, guaranteeing that the pipe diameters narrow down from source(s) to external areas. The outcomes are compared with the traditional design approach, which entails, in separate steps, the least-cost optimization for pipe sizing and the placement of isolation valves at all (N-rule) or all but one (N-1 rule) pipes connected to the generic junction. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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4 pages, 1797 KiB

Open AccessProceeding Paper

Modeling Temperature Fluctuations during Intermittent Water Usage within Water Systems: Water Quality Impact

by Fatemeh Hatam, Catalina Ortiz, Marianne Grimard-Conea and Michèle Prévost

Eng. Proc. 2024, 69(1), 86; https://doi.org/10.3390/engproc2024069086 - 9 Sep 2024

Viewed by 224

Abstract

Temperature is a crucial factor that can influence chemical and microbiological activities within building water systems. Due to factors like widespread water conservation programs or shutdowns resulting from events like the COVID-19 pandemic, water stagnation in these systems can escalate, impacting water temperature. [...] Read more.

Temperature is a crucial factor that can influence chemical and microbiological activities within building water systems. Due to factors like widespread water conservation programs or shutdowns resulting from events like the COVID-19 pandemic, water stagnation in these systems can escalate, impacting water temperature. By integrating EPANET-MSX with field data, this study seeks to simulate and analyze spatial and temporal fluctuations in water temperature and microbial growth resulting from temperature variations. The simulated temperature data and Legionella concentrations at three points are compared with field data during a period of three weeks. Overall, the modeled showerhead temperatures show good alignment with the monitored data, although underestimations occur in specific locations and time periods. The comparison between actual Legionella measurements and simulated concentrations, considering only temperature effects, demonstrates better alignment with field data for daily flushing showers. However, as stagnation increases, discrepancies between the modeled data and actual measurements suggest that other factors, such as available nutrients, may limit growth. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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4 pages, 981 KiB

Open AccessProceeding Paper

Experimental Study on the Hydraulic Impact of Discrete Top Blockages in Gravity Sewers

by Jinzhe Gong, Joshua Sim, Benny Zuse Rousso, Lloyd H. C. Chua and Michael Thomas

Eng. Proc. 2024, 69(1), 87; https://doi.org/10.3390/engproc2024069087 - 9 Sep 2024

Viewed by 266

Abstract

The current study presents experimental results on how discrete top blockages alter the upstream flow depth in a gravity sewer. A full-scale experimental circular open-channel system (DN150, 30 m length) was constructed to simulate a gravity sewer. Discrete top blockages with various heights [...] Read more.

The current study presents experimental results on how discrete top blockages alter the upstream flow depth in a gravity sewer. A full-scale experimental circular open-channel system (DN150, 30 m length) was constructed to simulate a gravity sewer. Discrete top blockages with various heights (80, 90, 100 mm) were tested with various flow rates and channel slopes. For various scenarios, the flow depths just upstream of the blockage were measured and analysed to reveal the impact of the blockages. The measured flow depths consistently exceeded those predicted by a reference formula from the literature, underscoring the difficulty in developing generalisable models. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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4 pages, 1139 KiB

Open AccessProceeding Paper

Residual Chlorine Modeling Sensitivity to Different Decay Models in Optimized and Non-Optimized Water Distribution Networks

by Sergio Serrano, Laura González, Valeria Rodríguez and Juan Saldarriaga

Eng. Proc. 2024, 69(1), 88; https://doi.org/10.3390/engproc2024069088 - 2 Sep 2024

Viewed by 370

Abstract

Water distribution networks (WDNs) are designed to comply with hydraulic and water quality parameters for appropriate operation. Methodologies for WDN optimization have been developed to achieve minimum cost designs, adhering to hydraulic conditions. The purpose of this study is to evaluate chlorine decay [...] Read more.

Water distribution networks (WDNs) are designed to comply with hydraulic and water quality parameters for appropriate operation. Methodologies for WDN optimization have been developed to achieve minimum cost designs, adhering to hydraulic conditions. The purpose of this study is to evaluate chlorine decay in 17 networks, comparing optimal and non-optimal designs, with the aim of defining if optimized designs lead to lower chlorine consumption in the networks. Chlorine consumption is modeled with different scenarios, coefficients, and decay models. Results indicate that consumption generally decreases in optimized networks, with few exceptions. Lastly, results of different bulk decay models are similar; however, wall decay results vary significantly depending on the model. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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5 pages, 1992 KiB

Open AccessProceeding Paper

The Dual Model under Pressure: How Robust Is Leak Detection under Uncertainties and Model Mismatches?

by Enrique Campbell, Edo Abraham, Johannes Koslowski, Olivier Piller and David B. Steffelbauer

Eng. Proc. 2024, 69(1), 89; https://doi.org/10.3390/engproc2024069089 - 9 Sep 2024

Viewed by 239

Abstract

This paper investigates the robustness of one innovative model-based method for leak detection, namely the Dual Model. We evaluate the algorithm’s performance under various leakage scenarios in the L-Town network, despite uncertainties and model mismatches in (i) base demand, (ii) pipe roughness, (iii) [...] Read more.

This paper investigates the robustness of one innovative model-based method for leak detection, namely the Dual Model. We evaluate the algorithm’s performance under various leakage scenarios in the L-Town network, despite uncertainties and model mismatches in (i) base demand, (ii) pipe roughness, (iii) the number of sensors, and (iv) network topology. Our investigation results indicate that the Dual Model is highly sensitive to discrepancies in the first three parameters. However, the impact can be mitigated through sensor-specific calibration, such as adjusting sensor elevations. Moreover, the Dual Model has demonstrated robustness to minor topology mismatches, like those introduced by closed valves. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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5 pages, 2593 KiB

Open AccessProceeding Paper

Experimental Validation of Graph Theory-Based Leak Detection Algorithm

by Lisa Saboo, Subhashree Baskaran, Rohit Raphael, Sri Hari Prasath Ramprasad and Sridharakumar Narasimhan

Eng. Proc. 2024, 69(1), 90; https://doi.org/10.3390/engproc2024069090 - 9 Sep 2024

Viewed by 304

Abstract

In this paper, we present results from a study on leak detection based on graph partitioning. Leaks are isolated using graph partitioning and performing mass balances over the partitions. The algorithms are tested and validated using a scaled-down test facility such as the [...] Read more.

In this paper, we present results from a study on leak detection based on graph partitioning. Leaks are isolated using graph partitioning and performing mass balances over the partitions. The algorithms are tested and validated using a scaled-down test facility such as the Reconfigurable Testbed for Control and Operation of WDN (RTCOP-WDN). The benefits and limitations of the presented techniques along with the required hardware to test these leak detection methods are discussed. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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5 pages, 1105 KiB

Open AccessProceeding Paper

Sensor Placement for Rupture Detection Using a Continuous Monitoring Strategy

by Elena Batzella, Giacomo Ferrarese and Stefano Malavasi

Eng. Proc. 2024, 69(1), 91; https://doi.org/10.3390/engproc2024069091 - 9 Sep 2024

Viewed by 249

Abstract

This work proposes an analysis of the active monitoring method for rupture detection. The analysis regards the effect of sensor sensibility on the effectiveness of the localization method. This paper approaches the problem in two steps: the first step regards the detection of [...] Read more.

This work proposes an analysis of the active monitoring method for rupture detection. The analysis regards the effect of sensor sensibility on the effectiveness of the localization method. This paper approaches the problem in two steps: the first step regards the detection of ruptures according to a method based on a sensitivity matrix and correlation analysis. The second step regards the selection of an effective sensor placement strategy. The aim is to determine the most effective position in terms of rupture localization ability of a predetermined number of sensors using sensor sensibility within the input variables. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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4 pages, 1337 KiB

Open AccessProceeding Paper

Leak Localization Using Autoencoders and Shapley Values

by Prasanna Mohan Doss, Marius Møller Rokstad and Franz Tscheikner-Gratl

Eng. Proc. 2024, 69(1), 92; https://doi.org/10.3390/engproc2024069092 - 10 Sep 2024

Viewed by 361

Abstract

This study outlines the use of a game theoretic approach for preliminary leak localization in water distribution networks. The proposed method consists of an autoencoder model at its core, trained to reconstruct input pressure signals recorded during nominal operation. Any significant change in [...] Read more.

This study outlines the use of a game theoretic approach for preliminary leak localization in water distribution networks. The proposed method consists of an autoencoder model at its core, trained to reconstruct input pressure signals recorded during nominal operation. Any significant change in the signal reconstructions is attributed to the presence of leaks and is determined by tracking statistical discrepancies using a sliding-window changepoint detection technique. Consequently, Shapley values are computed to identify the most influential sensors and approximate localization. With this approach, abrupt leaks were estimated within the 100 m radius and for incipient leaks at high flow rates. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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5 pages, 4349 KiB

Open AccessProceeding Paper

Investigating the Efficacy of Topological Methods for Optimal Sensor Placement in Water Distribution Systems

by Ludovica Palma, Armando Di Nardo, Fatemeh Hatam, Giovanni Francesco Santonastaso and Michèle Prévost

Eng. Proc. 2024, 69(1), 93; https://doi.org/10.3390/engproc2024069093 - 10 Sep 2024

Viewed by 263

Abstract

Water-distribution networks (WDNs) are vital infrastructure that are exposed to the risk of contamination. Several factors contribute to this risk, including insufficient pressure, contamination in water storage tanks and more. Sensor systems are crucial for detecting contaminations promptly. Traditional optimization methods to define [...] Read more.

Water-distribution networks (WDNs) are vital infrastructure that are exposed to the risk of contamination. Several factors contribute to this risk, including insufficient pressure, contamination in water storage tanks and more. Sensor systems are crucial for detecting contaminations promptly. Traditional optimization methods to define sensor locations often require resource-intensive network modeling, posing challenges for water utilities. This study applies a topological approach using betweenness centrality to address sensor placement. Various weights based on the physical structure of the network are tested. Results highlight the effectiveness of weighted topological approaches in minimizing contamination’s public health impact, with the advantage of low computational costs inherent in graph-based network representations. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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4 pages, 445 KiB

Open AccessProceeding Paper

TwinOptPRO—Digital Platform for Online Pump Scheduling Optimization

by Thomas Bernard, Jochen W. Deuerlein, Martin Dresen, Michael Fischer, Nicolai Guth, Rüdiger Höche, Christian Kühnert, Christa Mastaller, Gerhard Rappold, Gordon Schlolaut, Andreas Wunsch and Mathias Ziebarth

Eng. Proc. 2024, 69(1), 94; https://doi.org/10.3390/engproc2024069094 - 10 Sep 2024

Viewed by 277

Abstract

Climate change is leading to a general shortage of raw water availability combined with more pronounced seasonality and dry phases. The goal of the collaborative research project TwinOptPRO is to contribute to EU-wide climate neutrality in 2050 by the minimization of energy supply [...] Read more.

Climate change is leading to a general shortage of raw water availability combined with more pronounced seasonality and dry phases. The goal of the collaborative research project TwinOptPRO is to contribute to EU-wide climate neutrality in 2050 by the minimization of energy supply for water treatment and pumps in drinking water distribution systems. For that purpose, a digital platform that combines different forecasting models with simulation and optimization modules was developed. The aim is to ensure secure and compliant supply to customers in the future while maximizing the use of renewable energy and minimizing costs. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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4 pages, 724 KiB

Open AccessProceeding Paper

Pressure Sensor Placement for Pipe Roughness Calibration Based on Graph-Based Surrogate Model Coupled with Genetic Algorithm

by Mohammad Rajabi, Mohsen Hajibabaei, Massoud Tabesh and Robert Sitzenfrei

Eng. Proc. 2024, 69(1), 95; https://doi.org/10.3390/engproc2024069095 - 10 Sep 2024

Viewed by 260

Abstract

In this study, a graph-based method is implemented for sensor placement in a water distribution network (WDN) instead of using a hydraulic model. The proposed methodology determines the pressure sensors’ location based on the node betweenness centrality of nodes from their source, considering [...] Read more.

In this study, a graph-based method is implemented for sensor placement in a water distribution network (WDN) instead of using a hydraulic model. The proposed methodology determines the pressure sensors’ location based on the node betweenness centrality of nodes from their source, considering the WDN topology and assigning hydraulic-inspired edge weights. Furthermore, the Non-dominated Sorting Genetic Algorithm (NSGA-II) determines the end node of the WDN’s critical paths for sensor placement to maximize monitoring network efficiency to calibrate the model and avoid additional data collection. For different numbers of sensors, the NSGA-II algorithm is implemented 10 times and the final Pareto front is determined. The graph-based approach reduces the sensor placement problem complexity to an acceptable level and can be implemented as a surrogate approach for hydraulic-based sensor placement. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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4 pages, 804 KiB

Open AccessProceeding Paper

Predicting Contamination Spreading in Water Distribution Networks

by Richárd Wéber, Levente Sándor, Ákos Horváth, Gábor Barakka, Gopinathan R. Abhijith and Avi Ostfeld

Eng. Proc. 2024, 69(1), 96; https://doi.org/10.3390/engproc2024069096 - 10 Sep 2024

Viewed by 244

Abstract

High-quality drinking water is an essential need of every modern settlement. Typical analysis applies the EPANET to calculate the water age and the chlorine distribution. However, it cannot cope with diffusion or three-dimensional effects. This study aims to find the potential cases where [...] Read more.

High-quality drinking water is an essential need of every modern settlement. Typical analysis applies the EPANET to calculate the water age and the chlorine distribution. However, it cannot cope with diffusion or three-dimensional effects. This study aims to find the potential cases where the traditional modelling needs adjustment or improvements. This study uses computational fluid dynamics to analyse how non-reacting contaminants (e.g., fluoride, chloride, metal oxides, and micropollutants) spread in water distribution networks. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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5 pages, 1094 KiB

Open AccessProceeding Paper

A Hybrid Graph Hydrodynamic Method for Modelling Multiple Pipe Failure in Stormwater Networks

by Aun Dastgir, Rahul Satish, Mohsen Hajibabaei, Martin Oberascher and Robert Sitzenfrei

Eng. Proc. 2024, 69(1), 97; https://doi.org/10.3390/engproc2024069097 - 10 Sep 2024

Viewed by 204

Abstract

Modelling multiple pipe failure scenarios in stormwater networks is a challenging task due to the computational burden of conventional methods. In this context, this study proposes a hybrid graph hydrodynamic model (GHM) that combines the advantages of graph theory and hydrodynamic modelling to [...] Read more.

Modelling multiple pipe failure scenarios in stormwater networks is a challenging task due to the computational burden of conventional methods. In this context, this study proposes a hybrid graph hydrodynamic model (GHM) that combines the advantages of graph theory and hydrodynamic modelling to enhance the identification of critical pipe failures (i.e., computationally efficient and high accuracy). First, based on graph theory, critical pipe combinations are identified, followed by hydrodynamic modelling to accurately assess the flooding impacts of these critical combinations. The findings underscore the effectiveness of GHM, particularly in scenarios requiring numerous simulation runs. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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5 pages, 2019 KiB

Open AccessProceeding Paper

A Python-Based Tool for Real-Time Reverse Osmosis Data Normalization in Desalination Applications

by Nitin Prasad, Abhilasha Maheshwari, Ganesh Kumar Pandian and Vijaysai Prasad

Eng. Proc. 2024, 69(1), 98; https://doi.org/10.3390/engproc2024069098 - 10 Sep 2024

Viewed by 253

Abstract

This work presents the development of a Python-based data normalization tool designed to facilitate RO performance monitoring The tool generates normalized metrics, including salt rejection, pressure difference, and permeate flow rate, providing a clear and consistent baseline for performance evaluation. To validate the [...] Read more.

This work presents the development of a Python-based data normalization tool designed to facilitate RO performance monitoring The tool generates normalized metrics, including salt rejection, pressure difference, and permeate flow rate, providing a clear and consistent baseline for performance evaluation. To validate the tool’s efficacy, a single-stage RO system was modeled using the WAVE Water Treatment Design Software. The RO was simulated under various operating conditions, and the dataset derived from these simulations was processed using the Python tool, demonstrating its utility in generating and visualizing significant normalized results for effective RO performance monitoring. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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4 pages, 1855 KiB

Open AccessProceeding Paper

The Resilience of Intermittent Water Supply Systems under Limited Water and Electricity Availability

by Faten Ayyash, Akbar A. Javadi and Raziyeh Farmani

Eng. Proc. 2024, 69(1), 99; https://doi.org/10.3390/engproc2024069099 - 10 Sep 2024

Viewed by 254

Abstract

Two main reasons for using intermittent water supply (IWS) systems are water scarcity and power outages. As a result of IWS systems, consumers have inequitable water supply and high operating costs for water utilities. This study proposes a new methodology for assessing and [...] Read more.

Two main reasons for using intermittent water supply (IWS) systems are water scarcity and power outages. As a result of IWS systems, consumers have inequitable water supply and high operating costs for water utilities. This study proposes a new methodology for assessing and improving the IWS systems’ resilience under limited water and electricity supply. First, a global resilience analysis (GRA) of the network was conducted to identify its main vulnerabilities. Second, adaptation intervention strategies were considered to improve the network’s resilience. Results indicate that system resilience is improved through an operation intervention strategy. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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4 pages, 1366 KiB

Open AccessProceeding Paper

Probabilistic Forecasting of Hourly Water Demand

by Panagiotis Kossieris, Ioannis Tsoukalas, Dionysios Nikolopoulos, Georgios Moraitis and Christos Makropoulos

Eng. Proc. 2024, 69(1), 100; https://doi.org/10.3390/engproc2024069100 - 10 Sep 2024

Viewed by 276

Abstract

Timeseries forecasting holds a prominent position in the domain of urban water systems. Most forecasting approaches are designed to provide single-point deterministic forecasts, neglecting the uncertainty in model predictions. In this work, we propose a methodological framework, able to provide probabilistic predictions over [...] Read more.

Timeseries forecasting holds a prominent position in the domain of urban water systems. Most forecasting approaches are designed to provide single-point deterministic forecasts, neglecting the uncertainty in model predictions. In this work, we propose a methodological framework, able to provide probabilistic predictions over lead times of operational interest, by combining machine learning (ML) methods with multivariate statistics (i.e., copulas). The idea is that ML methods can be used to provide deterministic forecasts, and copulas can be used to quantify the predictive uncertainty of the forecasts. We showcase the effectiveness of proposed framework using hourly water demand data from a real-world case study. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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5 pages, 422 KiB

Open AccessProceeding Paper

Interpretable AI for Short-Term Water Demand Forecasting

by Aly-Joy Ulusoy, Carlos Jara-Arriagada, Yuanyang Liu, Bradley Jenks and Ivan Stoianov

Eng. Proc. 2024, 69(1), 101; https://doi.org/10.3390/engproc2024069101 - 10 Sep 2024

Viewed by 336

Abstract

Machine learning models such as artificial neural networks (ANNs) are becoming increasingly popular in short-term water demand forecasting. This is because, despite their lack of interpretability, ANNs are able to capture complex interactions between explanatory variables and water consumption better than a traditional [...] Read more.

Machine learning models such as artificial neural networks (ANNs) are becoming increasingly popular in short-term water demand forecasting. This is because, despite their lack of interpretability, ANNs are able to capture complex interactions between explanatory variables and water consumption better than a traditional time series analysis or simple linear regression. In this work, we forecast the hourly water demand of ten operational district metered areas using optimal trees, a machine learning model which has been shown to combine the interpretability of regression approaches and the accuracy of ANNs. We show that, compared to existing water demand forecasting models, optimal trees offer valuable insights without sacrificing predictive or computational performance. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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5 pages, 810 KiB

Open AccessProceeding Paper

Graph-Based Warm Solutions for Optimal Resilience Enhancement of Water Distribution Networks

by Mohsen Hajibabaei, Amin Minaei, Mohsen Shahandashti and Robert Sitzenfrei

Eng. Proc. 2024, 69(1), 102; https://doi.org/10.3390/engproc2024069102 - 10 Sep 2024

Viewed by 355

Abstract

This study introduces an efficient graph-based approach for optimal resilience enhancement of existing water distribution networks through the re-sizing of specific pipes. It utilizes modified graph metrics to track the spatial failure propagation resulting from pipe (edge) failures. This leads to identifying pipes [...] Read more.

This study introduces an efficient graph-based approach for optimal resilience enhancement of existing water distribution networks through the re-sizing of specific pipes. It utilizes modified graph metrics to track the spatial failure propagation resulting from pipe (edge) failures. This leads to identifying pipes (edges) that are more vulnerable to the failure of others, making them suitable candidates for re-sizing. These selected edges undergo re-sizing using a graph-based design approach, generating diverse graph-based solutions. These solutions later serve as warm solutions for the initial population of evolutionary optimization to speed up convergence. Tested on two networks, this approach outperforms traditional optimization (with random initial populations), increasing computational efficiency by over 90%. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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4 pages, 998 KiB

Open AccessProceeding Paper

Short-Term Water Demand Forecasting Based on LSTM Using Multi-Input Data

by Dingtong Wang, Yanning Li, Benwei Hou and Shan Wu

Eng. Proc. 2024, 69(1), 103; https://doi.org/10.3390/engproc2024069103 - 10 Sep 2024

Viewed by 221

Abstract

This study presents a forecasting framework for the hourly water demand of district metered areas (DMAs) based on a bidirectional long short-term memory (LSTM) model which is a participant in the Battle of Water Demand Forecasting (BWDF) during the 3rd WDSA/CCWI Joint Conference. [...] Read more.

This study presents a forecasting framework for the hourly water demand of district metered areas (DMAs) based on a bidirectional long short-term memory (LSTM) model which is a participant in the Battle of Water Demand Forecasting (BWDF) during the 3rd WDSA/CCWI Joint Conference. The framework consists of three portions: raw data preprocessing, initial forecasting model establishment based on LSTM, and a correction based on weather and holiday factors. The application results in the DMAs provided by the BWDF show that the proposed framework demonstrates reasonable forecasting of water demands. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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4 pages, 525 KiB

Open AccessProceeding Paper

Backup Design Optimization for Water Distribution Networks

by Richárd Wéber, Temirlan Tuyakbayev, Gopinathan R. Abhijith, Elad Salomons, Csaba Hős and Avi Ostfeld

Eng. Proc. 2024, 69(1), 104; https://doi.org/10.3390/engproc2024069104 - 10 Sep 2024

Viewed by 251

Abstract

Rapidly growing cities need significant extensions to their water distribution networks to fulfil the water demands of the population. The design of such systems is still challenging to optimise between the robustness/reliability/vulnerability and the cost. This study presents an idea: If the network [...] Read more.

Rapidly growing cities need significant extensions to their water distribution networks to fulfil the water demands of the population. The design of such systems is still challenging to optimise between the robustness/reliability/vulnerability and the cost. This study presents an idea: If the network layout is already determined, how can optimal diameters be found that balance cost and service quality? On the one hand, the purpose is to determine the cheapest possible network that can still serve every consumer. On the other hand, we extend the idea by optimising all backups of the network. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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4 pages, 893 KiB

Open AccessProceeding Paper

Utilizing Calibration Model for Water Distribution Network Leakage Detection

by Geumchae Shin, Soon Ho Kwon, Suhyun Lim and Seungyub Lee

Eng. Proc. 2024, 69(1), 105; https://doi.org/10.3390/engproc2024069105 - 10 Sep 2024

Viewed by 210

Abstract

Leakage presents a significant challenge in water distribution network (WDN) planning and management. This study introduces a novel methodology for hydraulic model calibration and leak detection based on MCMC-Statistical Distance. The central hypothesis posits that the presence of leaks induces fluctuations in estimated [...] Read more.

Leakage presents a significant challenge in water distribution network (WDN) planning and management. This study introduces a novel methodology for hydraulic model calibration and leak detection based on MCMC-Statistical Distance. The central hypothesis posits that the presence of leaks induces fluctuations in estimated pipe roughness coefficients (PRCs) as the pipe flow changes, reflecting the altered behavior of leaking pipes in energy dissipation. The proposed model comprises two distinct algorithms: (1) PRC estimation using MCMC and (2) a leakage detection algorithm employing a Kolmogorov–Smirnov test. Demonstrated in a simple water distribution network with various scenarios, the results illustrate the model’s potential for real-time leak detection. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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5 pages, 1507 KiB

Open AccessProceeding Paper

Real-Time Burst Localization in Complex Water Transmission Lines Using Hydraulic Gradient Analysis

by Taegon Ko, Raziyeh Farmani, Edward Keedwell and Xi Wan

Eng. Proc. 2024, 69(1), 106; https://doi.org/10.3390/engproc2024069106 - 10 Sep 2024

Viewed by 288

Abstract

This study introduces a methodology for the real-time detection and localization of bursts in water transmission lines by comparing estimated and measured Hydraulic Gradient (HG) values across pipe segments. Employing a deep learning approach, the method analyzes the complex relationships between system states [...] Read more.

This study introduces a methodology for the real-time detection and localization of bursts in water transmission lines by comparing estimated and measured Hydraulic Gradient (HG) values across pipe segments. Employing a deep learning approach, the method analyzes the complex relationships between system states such as flows, HGs, pump and valve operations. The approach capitalizes on the difference in HG values before and after a burst, enabling precise burst localization. Tested on a real incident, the method proved effective in accurately identifying burst locations, offering a practical solution for operators. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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4 pages, 1016 KiB

Open AccessProceeding Paper

An Innovative Solar Pump Applicable in Water Distribution Networks

by Hana Javadi Nejad, Behrouz Pirouz, Michele Turco, Seyed Navid Naghib, Stefania Anna Palermo and Patrizia Piro

Eng. Proc. 2024, 69(1), 107; https://doi.org/10.3390/engproc2024069107 - 10 Sep 2024

Viewed by 348

Abstract

The analysis of GHG emissions for different sectors shows that one of the main contributions, responsible for 25%, is electricity and heat production. An important aspect of electricity use concerns motor pumps, which are used for both urban water supply and agricultural water [...] Read more.

The analysis of GHG emissions for different sectors shows that one of the main contributions, responsible for 25%, is electricity and heat production. An important aspect of electricity use concerns motor pumps, which are used for both urban water supply and agricultural water systems. Generally, the highest consumption corresponds to summer, when the maximum solar radiation makes the use of solar water pumps possible. However, the total conversion of energy by conventional solar pumps is about 10% of the solar energy. This low efficiency has limited the choice of solar water pumps to areas without alternative power sources. Moreover, the final efficiency will further decrease due to that of other parts of the system, so, in order to achieve higher efficiency and sustainability, a novel method for solar water pumps must be developed. The new solar pump that we propose will take advantage of the efficiency of solar concentration dishes to absorb solar radiation, which is about 80–90%, will pump water using water vapor pressure, and will not need an electrical motor. It will offer several benefits besides high efficiency in pumping water, like the number of mechanical parts required and their maintenance costs, making its application easy and removing the limitations of typical systems. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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4 pages, 675 KiB

Open AccessProceeding Paper

Impact of Infiltration Systems on Illicit Waters in Sewer Networks

by Anita Raimondi, Tecla Casari and Umberto Sanfilippo

Eng. Proc. 2024, 69(1), 108; https://doi.org/10.3390/engproc2024069108 - 10 Sep 2024

Viewed by 219

Abstract

The frequent effects of urbanization and climate change make stormwater runoff control critical. Infiltration systems can provide multiple benefits to the environment, i.e., flood risk mitigation, stormwater quality improvement, aquifer recharge, and a reduction in the activation of combined sewer overflows. However, their [...] Read more.

The frequent effects of urbanization and climate change make stormwater runoff control critical. Infiltration systems can provide multiple benefits to the environment, i.e., flood risk mitigation, stormwater quality improvement, aquifer recharge, and a reduction in the activation of combined sewer overflows. However, their use must be carefully planned since they can cause illicit waters in the sewer network due to the deterioration of pipes and junctions. This study proposes a theoretical framework and a case study to assess the interaction between the deterioration of a sewer and the infiltration coming from the soil surface and/or from infiltration systems. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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5 pages, 539 KiB

Open AccessProceeding Paper

Enhancing Insights into Intermittent Water Supply Systems: Uncertainty and Sensitivity Analyses of Hydraulic Model

by Döndü Sarışen, Raziyeh Farmani and Fayyaz Ali Memon

Eng. Proc. 2024, 69(1), 109; https://doi.org/10.3390/engproc2024069109 - 10 Sep 2024

Viewed by 261

Abstract

So far, many researchers have attempted to tackle issues associated with intermittent water supply (IWS) systems, such as the inequitable distribution of water, by employing deterministic models that rely on multiple assumptions about input parameters. However, owing to the diverse practices and operations [...] Read more.

So far, many researchers have attempted to tackle issues associated with intermittent water supply (IWS) systems, such as the inequitable distribution of water, by employing deterministic models that rely on multiple assumptions about input parameters. However, owing to the diverse practices and operations associated with IWS systems, significant uncertainty prevails in various aspects, including user water consumption, supply characteristics, and household tank sizes. In this work, a novel uncertainty quantification framework for assessing uncertain model input parameters is proposed. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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4 pages, 479 KiB

Open AccessProceeding Paper

Performance Evaluation of Machine Learning Methods for Drinking Water Contamination Detection

by Valts Urbanovičs, Sergei Parshutin, Jānis Rubulis, Mārtiņš Bonders, Katrīna Dambeniece, Roberts Ozols, Dāvids Štēbelis and Sandis Dejus

Eng. Proc. 2024, 69(1), 110; https://doi.org/10.3390/engproc2024069110 - 10 Sep 2024

Viewed by 228

Abstract

The aim of the study is to train a machine learning (ML) model for drinking water contamination detection and compare performance to statistical methods and existing anomaly detection solutions. A pilot drinking water supply system was made and equipped with drinking water quality [...] Read more.

The aim of the study is to train a machine learning (ML) model for drinking water contamination detection and compare performance to statistical methods and existing anomaly detection solutions. A pilot drinking water supply system was made and equipped with drinking water quality sensors and a contamination dosing system. The results from this study demonstrated that using the statistical Mahalanobis distance (MD) method to predict the classification of drinking water measurements yields a 99% accuracy, 23% precision, and 28% F-score result (for wastewater contamination); however, the ML model yields a 99% accuracy, 98% precision, and a 98% F-score result. The results show that the application of ML methods can improve drinking water contamination detection speed and accuracy. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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4 pages, 208 KiB

Open AccessProceeding Paper

Staged Design of Water Distribution Networks: A Reinforcement Learning Approach

by Lydia Tsiami, Christos Makropoulos and Dragan Savic

Eng. Proc. 2024, 69(1), 111; https://doi.org/10.3390/engproc2024069111 - 10 Sep 2024

Viewed by 271

Abstract

Effectively planning the design of a water distribution network for the long term is a challenging task for water utilities, mainly due to the deep uncertainty that characterizes some of its most important design parameters. In an effort to navigate this challenge, this [...] Read more.

Effectively planning the design of a water distribution network for the long term is a challenging task for water utilities, mainly due to the deep uncertainty that characterizes some of its most important design parameters. In an effort to navigate this challenge, this work investigates the potential of reinforcement learning in the lifecycle design of water networks. To this end, a deep reinforcement learning agent was trained to identify a sequence of cost-effective interventions across multiple construction phases within a network’s lifecycle under both deterministic and uncertain conditions. Our approach was tested on a modified benchmark of the New York Tunnels problem with promising results. The agent achieved comparable performance with the baseline heuristic algorithm in the deterministic setting and devised a flexible design strategy when multiple future scenarios were considered. These preliminary findings highlight the potential of reinforcement learning in the lifecycle design of water networks and represent a step towards the integration of more adaptive planning approaches in the field. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

4 pages, 720 KiB

Open AccessProceeding Paper

Attributing Minimum Night Flow to Individual Pipes in Real-World Water Distribution Networks Using Machine Learning

by Matthew Hayslep, Edward Keedwell, Raziyeh Farmani and Joshua Pocock

Eng. Proc. 2024, 69(1), 112; https://doi.org/10.3390/engproc2024069112 - 10 Sep 2024

Viewed by 227

Abstract

This article introduces an explainable machine learning model for estimating the amount of flow that each pipe in a district metered area (DMA) contributes to the minimum night flow (MNF). This approach is validated using the MNF of DMAs and pipe failures, showing [...] Read more.

This article introduces an explainable machine learning model for estimating the amount of flow that each pipe in a district metered area (DMA) contributes to the minimum night flow (MNF). This approach is validated using the MNF of DMAs and pipe failures, showing good results for both tasks. The predictions from this model could be used to guide leak management or intervention strategies. In total, 800 DMAs ranging from rural to urban networks and representing nearly 12 million meters of pipe from a UK water company are used to train, validate, test, and evaluate the methodology. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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4 pages, 1033 KiB

Open AccessProceeding Paper

Nature-Based Solutions in Cities—A View from a Water Supply Perspective

by Martin Oberascher, Aun Dastgir, Carolina Kinzel and Robert Sitzenfrei

Eng. Proc. 2024, 69(1), 113; https://doi.org/10.3390/engproc2024069113 - 10 Sep 2024

Viewed by 262

Abstract

Nature-Based Solutions (NBSs) are decentralised and planted system elements with multiple benefits, requiring sufficient irrigation during dry weather periods to ensure plant health. In this work, the effects of the large-scale implementation of NBSs in the city centre of Klagenfurt from a water [...] Read more.

Nature-Based Solutions (NBSs) are decentralised and planted system elements with multiple benefits, requiring sufficient irrigation during dry weather periods to ensure plant health. In this work, the effects of the large-scale implementation of NBSs in the city centre of Klagenfurt from a water supply perspective are investigated, combining hydraulic analysis with water resource availability. As the large-scale implementation of NBSs in public squares shows, a coordinated NBS implementation strategy is required to ensure compatibility with the city’s water resources and infrastructure. This also emphasises the importance of alternative water sources for sustainable operations. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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4 pages, 726 KiB

Open AccessProceeding Paper

EWA—A Web-Based Awareness Creation Tool for Change Impact on Water Supply

by Anika Stelzl, Georg Arbesser-Rastburg, Valentin Adler, David Camhy, Johanna Pirker and Daniela Fuchs-Hanusch

Eng. Proc. 2024, 69(1), 114; https://doi.org/10.3390/engproc2024069114 - 10 Sep 2024

Viewed by 213

Abstract

Climate and demographic changes force water utilities to adapt to shifts in both water demand and water availability. The web-based EWA tool supports Austrian water utilities in addressing these problems. Based on water demand and availability forecasts from 2025 to 2055, it encourages [...] Read more.

Climate and demographic changes force water utilities to adapt to shifts in both water demand and water availability. The web-based EWA tool supports Austrian water utilities in addressing these problems. Based on water demand and availability forecasts from 2025 to 2055, it encourages robust planning by calculating different performance indicators based on hydraulic models. It provides a platform for assessing water distribution systems, integrating forecast and operational scenarios, and performance indicators. Users can assess long-term impacts, adjust planning approaches, and visualize results through specific graphs. Tutorials help users navigate the tool, while gamified challenges aim at testing problem-solving skills and motivating users to improve their performance and raise awareness. The EWA tool facilitates resilient and forward-looking planning, which is critical to adapting to climate change and demographic shifts while ensuring sustainable water resource management. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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5 pages, 1094 KiB

Open AccessProceeding Paper

Incorporation and Mobilisation of Health-Related Organisms from within Drinking Water Biofilm

by Jiwon Park, Frances Pick, Katherine Fish, Dominic Quinn, Cindy Smith, Vanessa Speight and Joby Boxall

Eng. Proc. 2024, 69(1), 115; https://doi.org/10.3390/engproc2024069115 - 11 Sep 2024

Viewed by 283

Abstract

The present study explored the incorporation of health-related organisms within drinking water biofilms and bulk water quality using benchtop-scale distribution systems. The annular reactors simulated the dead-end pipes of distribution systems with low shear stress but maintained a chlorine residual and formed young [...] Read more.

The present study explored the incorporation of health-related organisms within drinking water biofilms and bulk water quality using benchtop-scale distribution systems. The annular reactors simulated the dead-end pipes of distribution systems with low shear stress but maintained a chlorine residual and formed young biofilms on plastic surfaces. Spiked coliforms and Escherichia coli were introduced to the annular reactors after 1 month of growth. Although initially detected in the spike, the coliforms were inactivated in the bulk water phase, likely due to environmental stresses, such as nutrient starvation and residual chlorine. Also, coliform incorporation within biofilm was only detected in a single coupon in the reactor 24 h post-spike (with 100% lake water), suggesting they were not incorporated or under the detection limit. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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5 pages, 1952 KiB

Open AccessProceeding Paper

Admittance Matrix Method for Modeling Transients in a Laboratory Water Network

by Caterina Capponi, Debora Falocci, Bruno Brunone, Aaron Zecchin and Silvia Meniconi

Eng. Proc. 2024, 69(1), 116; https://doi.org/10.3390/engproc2024069116 - 10 Sep 2024

Viewed by 239

Abstract

This paper presents an innovative application of the admittance matrix method for modeling the transient response of a real laboratory pipeline network: a two-loop district metered area (DMA) setup at the University of Perugia’s Water Engineering Laboratory comprising high-density polyethylene (HDPE) pipes. By [...] Read more.

This paper presents an innovative application of the admittance matrix method for modeling the transient response of a real laboratory pipeline network: a two-loop district metered area (DMA) setup at the University of Perugia’s Water Engineering Laboratory comprising high-density polyethylene (HDPE) pipes. By employing the admittance matrix method, the computational efficiency of the modeling process is significantly enhanced. Our findings underscore the importance of considering viscoelastic parameters calibrated by a genetic algorithm to optimize the simulation of experimental data. The outcomes demonstrate a robust methodology capable of capturing the nuanced behaviors of complex water distribution systems, providing a critical tool for engineers and researchers in the field. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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4 pages, 596 KiB

Open AccessProceeding Paper

Modelling Variable Speed Pumps for Flow and Pressure Control Using Nash Equilibrium

by Jochen W. Deuerlein, Sylvan Elhay, Olivier Piller, Michael Fischer and Angus R. Simpson

Eng. Proc. 2024, 69(1), 117; https://doi.org/10.3390/engproc2024069117 - 11 Sep 2024

Viewed by 350

Abstract

Recently, the Nash equilibrium, known from game theory, was used for steady state calculation of pressurized pipe systems with general flow and pressure control devices. The concept is now applied to pumping stations. It is assumed that at least one of the pumps [...] Read more.

Recently, the Nash equilibrium, known from game theory, was used for steady state calculation of pressurized pipe systems with general flow and pressure control devices. The concept is now applied to pumping stations. It is assumed that at least one of the pumps has a frequency controller that enables the pump to deliver a given set flow or set pressure by adaptation of pump speed. For hydraulic calculation, the system is decomposed into the local pumping station and a surrogate link with flow or pressure constraints at one of its end nodes. This method is demonstrated for a small example system. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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4 pages, 729 KiB

Open AccessProceeding Paper

Combining Physical and Network Data for Attack Detection in Water Distribution Networks

by Côme Frappé - - Vialatoux and Pierre Parrend

Eng. Proc. 2024, 69(1), 118; https://doi.org/10.3390/engproc2024069118 - 11 Sep 2024

Viewed by 330

Abstract

Water distribution infrastructures are increasingly incorporating the IoT in the form of sensing and computing power to improve control over the system and achieve greater adaptability to water demand. This evolution, from physical to cyber-physical systems, comes with an attack perimeter extended from [...] Read more.

Water distribution infrastructures are increasingly incorporating the IoT in the form of sensing and computing power to improve control over the system and achieve greater adaptability to water demand. This evolution, from physical to cyber-physical systems, comes with an attack perimeter extended from physical infrastructure to cyberspace. Being able to detect this novel kind of attack is gaining traction in the scientific community. Machine learning detection algorithms, which are showing encouraging results in cybersecurity applications, are leveraging the increasing number of datasets published in the water distribution community for better attack detection. These datasets also begin to reflect this novel cyber-physical aspect in two ways, first by conducting cyberattacks against the testbed infrastructures during data acquisition, and secondly by including network traffic data along with the physical data captured during the experimentations. However, current machine learning models do not fully take into account this cyber-physical component, being only trained either on the physical or on the network data. This paper addresses this problem by providing a multi-layer approach to applying machine learning to cyber-physical systems, by combining physical and network traffic data and assessing their effects on the attack detection performance of machine learning algorithms, as well as the cross-impact with data enriched with graph metrics. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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4 pages, 625 KiB

Open AccessProceeding Paper

The Impact of Building Occupancy on Water Demand Characteristics in Residential Buildings: A Sensitivity Analysis

by Brendan M. Josey and Jinzhe Gong

Eng. Proc. 2024, 69(1), 119; https://doi.org/10.3390/engproc2024069119 - 11 Sep 2024

Viewed by 289

Abstract

A stochastic water demand model was used to undertake a sensitivity study to evaluate building occupancy against selected premise plumbing design parameters. The results demonstrate that building occupancy has a strong positive correlation for estimating the peak demand, average demand, and peak hourly [...] Read more.

A stochastic water demand model was used to undertake a sensitivity study to evaluate building occupancy against selected premise plumbing design parameters. The results demonstrate that building occupancy has a strong positive correlation for estimating the peak demand, average demand, and peak hourly water consumption (Spearman’s coefficient: 0.995–0.99), and a strong negative correlation to stagnation (the percentage of time a building spends at zero flow; Spearman’s coefficient: −0.996). The results indicate that building occupancy should be taken into consideration in premise plumbing design, which currently mainly focuses on the type and number of fixtures. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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4 pages, 170 KiB

Open AccessProceeding Paper

Enhancing Water Demand Forecasting: Leveraging LSTM Networks for Accurate Predictions

by Fatemeh Boloukasli ahmadgourabi, Melica Khashei Varnamkhasti, Morad Nosrati Habibi, Niuosha Hedaiaty Marzouny and Rebecca Dziedzic

Eng. Proc. 2024, 69(1), 120; https://doi.org/10.3390/engproc2024069120 - 12 Sep 2024

Viewed by 329

Abstract

This study aims to create a reliable water-demand forecasting system using Long Short-Term Memory networks. The model integrates hourly water demands from 10 District Metered Areas of a Water Distribution Network in northeast Italy and weather data, handling missing values with LSTM-based data [...] Read more.

This study aims to create a reliable water-demand forecasting system using Long Short-Term Memory networks. The model integrates hourly water demands from 10 District Metered Areas of a Water Distribution Network in northeast Italy and weather data, handling missing values with LSTM-based data imputation. It considers temporal aspects like time, weekdays, holidays, and weekend patterns, employing sine and cosine transformations to capture daily cycles. To ensure the model’s robustness, the testing was conducted during the last week of the dataset, specifically week 81, with iterative adjustments to the LSTM’s hyperparameters to optimize prediction accuracy. These tuning efforts focused on learning rate, number of layers, and batch size, tailored to maximize the system’s performance. This method is essential for smart decision-making in water utility management and demonstrates significant potential for improving operational efficiencies. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

5 pages, 2272 KiB

Open AccessProceeding Paper

Three-Dimensional Reconstruction of Water Leaks in Water Distribution Networks from Ground-Penetrating Radar Images by Exploring New Influencing Factors with Multi-Agent and Intelligent Data Analysis

by Samira Islam and David Ayala-Cabrera

Eng. Proc. 2024, 69(1), 121; https://doi.org/10.3390/engproc2024069121 - 10 Sep 2024

Viewed by 213

Abstract

This paper promotes water distribution networks’ (WDNs) sustainability and efficiency by integrating intelligent data analysis with ground-penetrating radar (GPR) to better interpret GPR images for detecting water leaks, favouring their asset assessment. This work uses GPR data from a laboratory setting to investigates [...] Read more.

This paper promotes water distribution networks’ (WDNs) sustainability and efficiency by integrating intelligent data analysis with ground-penetrating radar (GPR) to better interpret GPR images for detecting water leaks, favouring their asset assessment. This work uses GPR data from a laboratory setting to investigates the effects of various parameters on image interpretability across pipes. This methodology aims to advance the automation of leak and pipe identification, improving data interpretation and reducing dependency on human experts for leakage detection purposes. The findings suggest the possibility of uncovering new features enhancing GPR image interpretability, presented in 3D models. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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5 pages, 1231 KiB

Open AccessProceeding Paper

From Deterministic to Probabilistic Forecasts of Water Demand

by Annalaura Gabriele, Daniela Biondi, Rudy Gargano and Ezio Todini

Eng. Proc. 2024, 69(1), 122; https://doi.org/10.3390/engproc2024069122 - 12 Sep 2024

Viewed by 301

Abstract

This work presents the application of the MCP as the integrator of two NN-type models, to provide probabilistic forecasts of water demand within the frame of the WDSA 2024 Battle. The proposed approach allows assessing the probability distribution of future values of water [...] Read more.

This work presents the application of the MCP as the integrator of two NN-type models, to provide probabilistic forecasts of water demand within the frame of the WDSA 2024 Battle. The proposed approach allows assessing the probability distribution of future values of water demand conditional to the deterministic model forecasts. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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4 pages, 855 KiB

Open AccessProceeding Paper

Application of a Neural Network Model to Short-Term Water Demand Forecasting

by Faten Ayyash, Matthew Hayslep, Taegon Ko, Mulenga Kalumba, Kondwani Simukonda and Raziyeh Farmani

Eng. Proc. 2024, 69(1), 123; https://doi.org/10.3390/engproc2024069123 - 12 Sep 2024

Viewed by 385

Abstract

Relationships between water demand, pressure, and leakage highlight the need for accurate supply to match demand. This study addresses the challenges of forecasting short-term water demand and was part of the Battle for Water Demand Forecasting competition involving 10 real-world District Metered Areas [...] Read more.

Relationships between water demand, pressure, and leakage highlight the need for accurate supply to match demand. This study addresses the challenges of forecasting short-term water demand and was part of the Battle for Water Demand Forecasting competition involving 10 real-world District Metered Areas in Italy. A nine-layer convolutional neural network model was proposed that considers demand from previous time steps, time of the day, weather conditions, day type, and other deterministic temporal factors to predict water demand. Bayesian optimization was used for hyperparameter tuning. The model can predict and forecast short-term water demand with reasonable accuracy. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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5 pages, 208 KiB

Open AccessProceeding Paper

Determination of the Costs of Potable Water Extraction in the Municipality of Villagran, Guanajuato, Mexico

by Ma. Magdalena Sánchez-Astello and Diego Armando Dolores Cantú

Eng. Proc. 2024, 69(1), 124; https://doi.org/10.3390/engproc2024069124 - 12 Sep 2024

Viewed by 234

Abstract

In this work, the costs generated from the extraction of water from the wells of the operating body of the Potable Water Board of the Municipality of Villagrán, Guanajuato (JUMAPAV) were determined, in which the characteristics of each well were considered for evaluation [...] Read more.

In this work, the costs generated from the extraction of water from the wells of the operating body of the Potable Water Board of the Municipality of Villagrán, Guanajuato (JUMAPAV) were determined, in which the characteristics of each well were considered for evaluation and analysis. The unit costs were determined through the unit price analysis methodology proposed by the Regulation of the Law of Public Works and Related Services (RLOPSRM, 2012), the electromechanical efficiency of the wells was calculated and the influence on its value in energy costs and on the volume extracted was evaluated. Finally, the price of the agency’s fixed rate for 10 m³ of water was compared with the price obtained from the proposed analysis. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

4 pages, 351 KiB

Open AccessProceeding Paper

Water Demand Forecast Using Generalized Autoregressive Moving Average Models

by Maria Mercedes Gamboa-Medina and Fabrizio Silva Campos

Eng. Proc. 2024, 69(1), 125; https://doi.org/10.3390/engproc2024069125 - 12 Sep 2024

Viewed by 231

Abstract

Short-time forecasting of the demand on water distribution networks is a challenging task because of the high variability and uncertainty of that demand. Of the different approaches used, we consider the probability modeling of demand time series to be the most interesting, and [...] Read more.

Short-time forecasting of the demand on water distribution networks is a challenging task because of the high variability and uncertainty of that demand. Of the different approaches used, we consider the probability modeling of demand time series to be the most interesting, and specifically propose the use of Generalized Autoregressive Moving Average (GARMA) models. The complete proposed model uses a gamma probability density function, variables for weekends, and harmonic functions for daily and weekly seasonality, among other parameters. In the context of the Battle of Water Demand Forecasting, we train and test the model with a demand database for ten District Metered Areas. We obtain high accuracy, with mean absolute error values of around 0.25 L/s to 1.89 L/s. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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4 pages, 3058 KiB

Open AccessProceeding Paper

A Hybrid Modelling for Both Pressure-Dependent and Volume-Based Demand in Pressure-Driven Analysis

by João Muranho, Joaquim Sousa, Ana Ferreira, Alfeu Sá-Marques and Abel Gomes

Eng. Proc. 2024, 69(1), 126; https://doi.org/10.3390/engproc2024069126 - 12 Sep 2024

Viewed by 216

Abstract

Water distribution network (WDN) simulation models are usually classified as demand-driven or pressure-driven, depending on whether the demands are independent of or dependent on network pressures, respectively. In real-world networks, both types of demands coexist in the same building. This paper presents a [...] Read more.

Water distribution network (WDN) simulation models are usually classified as demand-driven or pressure-driven, depending on whether the demands are independent of or dependent on network pressures, respectively. In real-world networks, both types of demands coexist in the same building. This paper presents a hybrid modelling approach that combines volume-based and pressure-dependent demands in the same model, allowing for different pressure–demand relationships. This hybrid modelling approach is intended to produce more realistic results when modelling WDNs, and it was implemented in WaterNetGen, an EPANET extension. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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5 pages, 1018 KiB

Open AccessProceeding Paper

Spatial Analysis of Water Temperature in a Drinking Water Distribution System for Climate Change Adaptation

by Chiara Cincotta, Mirjam Blokker, Cristiana Bragalli and Zoran Kapelan

Eng. Proc. 2024, 69(1), 127; https://doi.org/10.3390/engproc2024069127 - 12 Sep 2024

Viewed by 365

Abstract

The analysis of the spatial distribution of drinking water temperature (DWT) in the drinking water distribution system (DWDS) can allow for the detection of hotspots and the identification of suitable mitigation interventions to enhance the climate resilience. For this purpose, a water temperature [...] Read more.

The analysis of the spatial distribution of drinking water temperature (DWT) in the drinking water distribution system (DWDS) can allow for the detection of hotspots and the identification of suitable mitigation interventions to enhance the climate resilience. For this purpose, a water temperature model is implemented in EPANET-MSX and coupled with the hydraulic model of the DWDS in the town of Almere (the Netherlands). This model is then used to assess the effectiveness of a range of interventions against the unwanted water warming under a climate scenario of an extreme air temperature increase in a Dutch summer. Finally, a solution scenario is suggested to comply with the Dutch legislative limit of 25 °C on DWT at the tap. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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5 pages, 1391 KiB

Open AccessProceeding Paper

Energy Assessment of Water Networks Based on New Performance Indicators

by Maria Cristina Morani, Armando Carravetta, Oreste Fecarotta and Renato Montillo

Eng. Proc. 2024, 69(1), 128; https://doi.org/10.3390/engproc2024069128 - 12 Sep 2024

Viewed by 269

Abstract

In this study, a new methodology based on performance indices is presented to carry out a detailed energy audit of water systems. Given a water network, the proposed procedure allows for a direct assessment of the critical areas in terms of energy efficiency, [...] Read more.

In this study, a new methodology based on performance indices is presented to carry out a detailed energy audit of water systems. Given a water network, the proposed procedure allows for a direct assessment of the critical areas in terms of energy efficiency, as well as for a detailed quantification of the energy benefits resulting from the new management strategies proposed to increase the sustainability of the network. To verify the viability of the methodology, a pressure control strategy is proposed, based on the installation of pressure-reducing valves, containing the excess pressure and thus the water leakage within the system. The operation strategy is carefully designed by the use of a global optimization solver, searching for both the number and location of the devices in order to maximize water savings and minimize the investment cost. The energy benefits resulting from the pressure control are then investigated by the assessment of the performance indices. According to the obtained results, the proposed methodology is a useful tool to assess the vulnerability and inefficiency of a given network, as well as to quantify the benefits resulting from the new management strategies. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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4 pages, 615 KiB

Open AccessProceeding Paper

Leveraging Potentials of Local and Global Models for Water Demand Forecasting

by Matthias Groß and Lukas Hans

Eng. Proc. 2024, 69(1), 129; https://doi.org/10.3390/engproc2024069129 - 12 Sep 2024

Viewed by 238

Abstract

This paper examines the effectiveness of local and global models in predicting water demand, employing data from the Battle of Water Demand Forecasting. Utilizing LightGBM models under local, semi-global, and global settings, we analyze the performance of these models across different configurations. The [...] Read more.

This paper examines the effectiveness of local and global models in predicting water demand, employing data from the Battle of Water Demand Forecasting. Utilizing LightGBM models under local, semi-global, and global settings, we analyze the performance of these models across different configurations. The results suggest that inadequately optimized hyperparameters do not always enhance model performance, but well performing hyperparameters can be appropriate for different model types inside the domain of water demand forecasting. Semi-global and global models frequently outperformed local models, underscoring the benefits of contextual information. Our findings indicate that while semi-global approaches offer promising results, extensive tuning and a strategic selection of a time series for modeling are imperative for forecasting accuracy. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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4 pages, 479 KiB

Open AccessProceeding Paper

Modeling Water Availability during a Blackout under Consideration of Uncertain Demand Response

by Bernhard Jonathan Sattler, Andrea Tundis, John Friesen and Peter F. Pelz

Eng. Proc. 2024, 69(1), 130; https://doi.org/10.3390/engproc2024069130 - 12 Sep 2024

Viewed by 263

Abstract

Water distribution systems (WDSs) need electric power supply to operate their pumps. Long-lasting power outages (blackouts) can disrupt the availability of water for citizens. If the water supply is limited by constrained pumping capacities caused by the blackout, water demand reduction could help [...] Read more.

Water distribution systems (WDSs) need electric power supply to operate their pumps. Long-lasting power outages (blackouts) can disrupt the availability of water for citizens. If the water supply is limited by constrained pumping capacities caused by the blackout, water demand reduction could help preserve this limited supply, while increased water withdrawal, i.e., stockpiling, could deplete it. This study investigates the effects and subsequent uncertainty of demand response, especially stockpiling, on WDSs in a blackout. Therefore, we (i) model residential water demand reduction, regular water demand, and water stockpiling in a blackout, (ii) simulate the effect of the demand response on the WDS of Darmstadt, Germany, and (iii) investigate uncertainty resulting from the demand response and initial states of the WDS at time of the onset of the blackout. The findings indicate that the demand response and initial tank levels are the main sources of uncertainty and that demand-side management bears the potential to improve water service availability during a blackout. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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4 pages, 1178 KiB

Open AccessProceeding Paper

ALLIEVI as a Tool for Simulating Hydraulic Transients in Energy Recovery Systems

by Roberto del Teso, Elena Gómez, Elvira Estruch-Juan and Javier Soriano

Eng. Proc. 2024, 69(1), 131; https://doi.org/10.3390/engproc2024069131 - 12 Sep 2024

Viewed by 309

Abstract

ALLIEVI is a software developed by the Universitat Politècnica de València to model and analyze hydraulic transients in pressurized water systems. ALLIEVI allows for the modeling of valve and pump maneuvers, including pressure reducing valves (VRPs) and energy recovery elements such as turbines [...] Read more.

ALLIEVI is a software developed by the Universitat Politècnica de València to model and analyze hydraulic transients in pressurized water systems. ALLIEVI allows for the modeling of valve and pump maneuvers, including pressure reducing valves (VRPs) and energy recovery elements such as turbines and pumps operating as turbines (PATs). In this work, two practical cases are presented in which ALLIEVI is used as a tool, either to adjust the energy recovery potential of a system or to calculate the hydraulic transient generated by maneuvers of an energy recovery system. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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4 pages, 1411 KiB

Open AccessProceeding Paper

Effects of User-Induced Transients on a Service Line: Preliminary Results from WEL (Perugia, Italy)

by Valentina Marsili, Debora Falocci, Caterina Capponi, Silvia Meniconi, Filippo Mazzoni, Stefano Alvisi, Bruno Brunone and Marco Franchini

Eng. Proc. 2024, 69(1), 132; https://doi.org/10.3390/engproc2024069132 - 13 Sep 2024

Viewed by 263

Abstract

The integrity of water service lines (SLs), crucial components in water distribution networks, is potentially threatened by transients generated by users’ activity. This paper presents the results of laboratory tests carried out at the Water Engineering Laboratory of the University of Perugia (Italy) [...] Read more.

The integrity of water service lines (SLs), crucial components in water distribution networks, is potentially threatened by transients generated by users’ activity. This paper presents the results of laboratory tests carried out at the Water Engineering Laboratory of the University of Perugia (Italy) to investigate the effects of user behavior on an SL. In particular, transients due to changes in the discharge in the SL, simulating the activation of domestic devices, are investigated. The analysis of the effect of such maneuvers provides insights that can assist water utility managers in the design, installation and maintenance of SLs. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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5 pages, 4202 KiB

Open AccessProceeding Paper

Computational Fluid Dynamics Analysis of an Innovative Multi-Purpose Green Roof

by Seyed Navid Naghib, Behrouz Pirouz, Hana Javadi Nejad, Michele Turco, Stefania Anna Palermo and Patrizia Piro

Eng. Proc. 2024, 69(1), 133; https://doi.org/10.3390/engproc2024069133 - 13 Sep 2024

Viewed by 289

Abstract

In this study, to improve the application and performance of conventional green roof systems, a novel multi-purpose green roof system was simulated numerically using computational fluid dynamics (CFD). The innovative multi-purpose green roof contains a soil layer and water filter, meaning the water [...] Read more.

In this study, to improve the application and performance of conventional green roof systems, a novel multi-purpose green roof system was simulated numerically using computational fluid dynamics (CFD). The innovative multi-purpose green roof contains a soil layer and water filter, meaning the water retention time not only depends on the soil media but also depends on the filter’s pore size, improving the impact on runoff quality and quantity. In this regard, after mesh sensitivity analysis, the developed model was validated using experimental data, and the results show the accuracy of CFD in the simulation of porous media and filters. Comparisons between experimental and numerical results demonstrate the impact of proper porosity values in the simulation of a porous environment and reveal the source of errors in the numerical prediction of capillary flow in soil media, which can be minimized by adaptive consideration of the parameters, such as wall adhesion and appropriate wettability. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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4 pages, 1197 KiB

Open AccessProceeding Paper

A Flushing Duration Model for a Campaign against Contamination in Water Distribution Systems

by Hao Cao and Pu Li

Eng. Proc. 2024, 69(1), 134; https://doi.org/10.3390/engproc2024069134 - 13 Sep 2024

Viewed by 212

Abstract

Contamination poses a significant risk to public health by degrading water quality in water distribution systems (WDSs). As one of the key tasks of a response strategy to contamination incidents in a WDS, pipe system flushing has been widely implemented in practice. However, [...] Read more.

Contamination poses a significant risk to public health by degrading water quality in water distribution systems (WDSs). As one of the key tasks of a response strategy to contamination incidents in a WDS, pipe system flushing has been widely implemented in practice. However, due to the complexity of the network structure and chemical reaction within the pipe system, determining the flushing duration is still one of the significant challenges for a given network. To address this problem, a model for determining the flushing duration is developed. This model is based on calculating the traveling trajectory of the contaminant inside the network. This is carried out by discretizing the one-dimension advection equation and calculating the variation of the contaminant concentration from one segment to another over time. As a preliminary study, we focus on simplified scenarios where contaminants exhibit no chemical reaction within the WDS. The proposed model is applied and analyzed through a simulation study and a laboratory testbed. The results demonstrate the efficacy of the model for determining flushing duration, which can offer valuable insights for real-world applications and serve as a crucial reference for water utility companies. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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5 pages, 2414 KiB

Open AccessProceeding Paper

Pressure Management in Water Distribution Networks by Means of Pumps as Turbines: A Case Study in Northern Italy

by Lucrezia Manservigi, Valentina Marsili, Filippo Mazzoni, Giulia Anna Maria Castorino, Saverio Farsoni, Enzo Losi, Stefano Alvisi, Marcello Bonfè, Marco Franchini, Pier Ruggero Spina and Mauro Venturini

Eng. Proc. 2024, 69(1), 135; https://doi.org/10.3390/engproc2024069135 - 13 Sep 2024

Viewed by 371

Abstract

Pressure control by means of pressure-reducing valves (PRVs) is a possible strategy to reduce water losses in water distribution networks (WDNs). However, PRV replacement with energy-harvesting devices—such as pumps as turbines (PATs)—can lead to a more sustainable management of water systems. This study [...] Read more.

Pressure control by means of pressure-reducing valves (PRVs) is a possible strategy to reduce water losses in water distribution networks (WDNs). However, PRV replacement with energy-harvesting devices—such as pumps as turbines (PATs)—can lead to a more sustainable management of water systems. This study analyzes the case study of a WDN located in Northern Italy, of which the layout is supposed to be upgraded by installing a PAT for both pressure reduction and energy recovery. To identify the optimal PAT to install (i.e., the one that maximizes energy recovery), a fleet of forty-five turbomachines is hypothetically employed. The study reveals that the hydraulic regulation of the optimal PAT allows recovering over 50% of the hydraulic energy available in the WDN. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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5 pages, 1250 KiB

Open AccessProceeding Paper

Regrowth of Microorganisms from Treatment to Tap in Operational Drinking Water Supply Networks

by Isabel Carneiro, Katherine Fish, Peter Jarvis, John Haley, Fiona Webber, Paul Gaskin and Joby Boxall

Eng. Proc. 2024, 69(1), 136; https://doi.org/10.3390/engproc2024069136 - 13 Sep 2024

Viewed by 270

Abstract

This research provides new understanding of the (re)growth of microorganisms within drinking water distribution networks. Flow cytometry data quantifying total and intact cell counts from consumers’ taps are currently rare, and its value for aiding understanding of the growth of microorganisms is unknown. [...] Read more.

This research provides new understanding of the (re)growth of microorganisms within drinking water distribution networks. Flow cytometry data quantifying total and intact cell counts from consumers’ taps are currently rare, and its value for aiding understanding of the growth of microorganisms is unknown. In this study, changes in microbial concentrations from the treatment works to customers’ taps were measured (using flow cytometry) in two UK drinking water distribution networks. Throughout each network, five locations were sampled for five consecutive days within a week, and to assess seasonal impacts, this was repeated twice in each network. Significant growth of microorganisms was observed in both networks during autumn, particularly at higher-water-age taps. These results give novel emphasis to the active impact of the distribution system on microbiological growth by using flow cytometry data collected in a systematic way from treatment through to customers’ taps. Such understanding is essential to achieving the delivery of safe and aesthetically pleasing drinking water to customers. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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4 pages, 797 KiB

Open AccessProceeding Paper

Accelerating Urban Drainage Simulations: A Data-Efficient GNN Metamodel for SWMM Flowrates

by Alexander Garzón, Zoran Kapelan, Jeroen Langeveld and Riccardo Taormina

Eng. Proc. 2024, 69(1), 137; https://doi.org/10.3390/engproc2024069137 - 13 Sep 2024

Viewed by 365

Abstract

Computational models for water resources often experience slow execution times, limiting their application. Metamodels, especially those based on machine learning, offer a promising alternative. Our research extends a prior Graph Neural Network (GNN) metamodel for the Storm Water Management Model (SWMM), which efficiently [...] Read more.

Computational models for water resources often experience slow execution times, limiting their application. Metamodels, especially those based on machine learning, offer a promising alternative. Our research extends a prior Graph Neural Network (GNN) metamodel for the Storm Water Management Model (SWMM), which efficiently learns with less data and generalizes to new UDS sections via transfer learning. We extend the metamodel’s functioning by adding flowrate prediction, crucial for assessing water quality and flooding risks. Using an Encoder–Processor–Decoder architecture, the metamodel displays high accuracy on the simulated time series. Future work is aimed at incorporating more physical principles and testing further transferability. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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5 pages, 667 KiB

Open AccessProceeding Paper

Calculating Availability of Production Plants

by Ralph Beuken, Peter Drolenga and Ron Jong

Eng. Proc. 2024, 69(1), 138; https://doi.org/10.3390/engproc2024069138 - 14 Sep 2024

Viewed by 260

Abstract

Substandard Supply Minutes is the key performance indicator for asset management in the drinking water sector. A novel methodology translates production site failures into outage scenarios, allowing for calculation of Substandard Supply Minutes (SSM) based on all clients in the supply area. Drinking [...] Read more.

Substandard Supply Minutes is the key performance indicator for asset management in the drinking water sector. A novel methodology translates production site failures into outage scenarios, allowing for calculation of Substandard Supply Minutes (SSM) based on all clients in the supply area. Drinking water utilities can conduct scenario studies, pinpoint high-risk assets, and compare production sites. This method can contribute to a better risk-based policy for design, investment and maintenance. Effective implementation necessitates a deeper understanding of failures of components at production sites. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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4 pages, 939 KiB

Open AccessProceeding Paper

Contributions to Leak and Air Pocket Detection Using Transient Pressure Signals

by Dídia Covas, Marta Cabral, João Paulo Ferreira and Helena Ramos

Eng. Proc. 2024, 69(1), 139; https://doi.org/10.3390/engproc2024069139 - 14 Sep 2024

Viewed by 337

Abstract

This study presents insights into how existing faults in pipe systems, like leaks and air pockets, modify transient pressure waves in terms of shape, damping, and phase shift, based on experimental tests conducted at the Hydraulics Laboratory of the Instituto Superior Técnico. Leaks [...] Read more.

This study presents insights into how existing faults in pipe systems, like leaks and air pockets, modify transient pressure waves in terms of shape, damping, and phase shift, based on experimental tests conducted at the Hydraulics Laboratory of the Instituto Superior Técnico. Leaks have a major effect on pressure wave damping and shape that increases with the leak size; however, they also preserve the wave phase. The air pocket effect strongly depends on the air pocket size and location, tending to increase wave damping and delay. Also, there is an air pocket volume that leads to the maximum pressures being higher than Joukowsky’s overpressure. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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4 pages, 2213 KiB

Open AccessProceeding Paper

Deep Learning for Automated Water Segmentation through CCTV Images in Agricultural Reservoirs

by Suhyun Lim, Soon Ho Kwon, Geumchae Shin and Seungyub Lee

Eng. Proc. 2024, 69(1), 140; https://doi.org/10.3390/engproc2024069140 - 10 Sep 2024

Viewed by 193

Abstract

Estimating water levels in agricultural reservoirs is crucial for sustainable water management. However, accurate estimation faces limitations due to data scarcity and the labor-intensive nature of image processing. To address this, we propose an automatic image segmentation model for agricultural reservoirs based on [...] Read more.

Estimating water levels in agricultural reservoirs is crucial for sustainable water management. However, accurate estimation faces limitations due to data scarcity and the labor-intensive nature of image processing. To address this, we propose an automatic image segmentation model for agricultural reservoirs based on transfer learning. We evaluated its accuracy using CCTV images and achieved a high accuracy rate of 95–99%. This automated approach can assure improvements in water level estimation in unmeasured agricultural reservoirs by providing advanced image processing results. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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4 pages, 819 KiB

Open AccessProceeding Paper

Modelling the Dynamics of P. aeruginosa in the Formation of Biofilms

by Dinesh Singh Bhandari, Dominic Quinn, Erifyli Tsagkari, Katherine Fish, Frances Pick, Joby Boxall, Cindy Smith, Siming You and William Sloan

Eng. Proc. 2024, 69(1), 141; https://doi.org/10.3390/engproc2024069141 - 14 Sep 2024

Viewed by 596

Abstract

The accumulation, growth, and re-mobilization of pathogens on the pipe walls in drinking water distribution systems are processes that affect the risk of exposure at the tap. We present a model that uses the Buckingham Pi theory to embody the physics of Pseudomonas [...] Read more.

The accumulation, growth, and re-mobilization of pathogens on the pipe walls in drinking water distribution systems are processes that affect the risk of exposure at the tap. We present a model that uses the Buckingham Pi theory to embody the physics of Pseudomonas aeruginosa accumulation and move within the system. We apply it to model experimental data from a biofilm annular reactor operated in conditions that are commensurate with the flow in DWDS. By calibrating the model for this benchtop system, we intend to identify the most important physical parameters for use in a simpler, more prudent model, for application in large-scale DWDS. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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4 pages, 5386 KiB

Open AccessProceeding Paper

Hybrid Transient-Machine Learning Methodology for Leak Detection in Water Transmission Mains

by Caterina Capponi, Andrea Menapace, Silvia Meniconi, Daniele Dalla Torre, Maurizio Tavelli, Maurizio Righetti and Bruno Brunone

Eng. Proc. 2024, 69(1), 142; https://doi.org/10.3390/engproc2024069142 - 15 Sep 2024

Viewed by 408

Abstract

This contribution proposes a hybrid approach integrating transient test-based techniques with machine learning for automatic leak detection in water transmission mains. Transient numerical simulations calibrated using experimental tests are used to develop a data-driven method based on neural networks to identify leak locations [...] Read more.

This contribution proposes a hybrid approach integrating transient test-based techniques with machine learning for automatic leak detection in water transmission mains. Transient numerical simulations calibrated using experimental tests are used to develop a data-driven method based on neural networks to identify leak locations and characteristics. The accuracy of leak localization is demonstrated using three different degrees of noise in terms of mean absolute error, ranging between 0.54 m and 2.1 m. This proposed hybrid approach shows prospects for in-field applications. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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4 pages, 1516 KiB

Open AccessProceeding Paper

Automated Pump Placement Algorithms for Optimal Sewer Network Design in Areas with Complex Terrain

by Ralf Habermehl, Amin E. Bakhshipour, Timo C. Dilly, Ali Haghighi and Ulrich Dittmer

Eng. Proc. 2024, 69(1), 143; https://doi.org/10.3390/engproc2024069143 - 12 Sep 2024

Viewed by 236

Abstract

We present a set of algorithms for automatically determining the best locations for lift stations and pressurized pipes in sewer networks. These algorithms are integrated into an optimization framework for automatic sewer network planning. The algorithms are developed based on graph theory and [...] Read more.

We present a set of algorithms for automatically determining the best locations for lift stations and pressurized pipes in sewer networks. These algorithms are integrated into an optimization framework for automatic sewer network planning. The algorithms are developed based on graph theory and metaheuristic optimization to optimize the allocation of lift stations and pressure pipes. The proposed algorithms are applied to a real large-scale test case in Paranatinga, Brazil, and the results are compared with an existing design. This comparison highlights the algorithms’ effectiveness in designing cost-efficient sewer networks in areas with complex terrain. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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4 pages, 2077 KiB

Open AccessProceeding Paper

Evaluation of Free-Chlorine Data from Online Sensors in a Water Supply Network

by Angeliki Aisopou and Ivan Stoianov

Eng. Proc. 2024, 69(1), 144; https://doi.org/10.3390/engproc2024069144 - 18 Sep 2024

Viewed by 259

Abstract

The use of data from reagent-free water quality sensors in water supply networks, which monitor at a high spatiotemporal resolution, is limited by variations in data quality and sensor sensitivity. This study examines a dataset from state-of the-art sensors installed in a UK [...] Read more.

The use of data from reagent-free water quality sensors in water supply networks, which monitor at a high spatiotemporal resolution, is limited by variations in data quality and sensor sensitivity. This study examines a dataset from state-of the-art sensors installed in a UK water distribution network, providing unprecedented spatiotemporal resolution. By comparing continuous free chlorine data with monthly grab samples using Bland–Altman plots, we quantify the uncertainties of sensors. The results indicate that unlike the grab samples, data from the online sensors offer significant insights into the fluctuations in water quality dynamics. An analysis of sensor performance and limitations identifies sources of uncertainty. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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4 pages, 490 KiB

Open AccessProceeding Paper

Parameter Estimation in Water Distribution Networks Using an Error-in-Variables Approach

by Ebadu Rahman, Sumanth Srinivas Parthasarathy, Akshaya Venkataramanan, Sri Hari Prasath Ramprasad, Rajasundaram Mathiazhagan and Sridharakumar Narasimhan

Eng. Proc. 2024, 69(1), 145; https://doi.org/10.3390/engproc2024069145 - 18 Sep 2024

Viewed by 316

Abstract

A well-calibrated model of a water distribution network is necessary for monitoring, control, and operation. In this work, we address the problem of parameter estimation in water distribution networks (WDNs). Typical parameters to be estimated include the coefficients used to model major (pipes) [...] Read more.

A well-calibrated model of a water distribution network is necessary for monitoring, control, and operation. In this work, we address the problem of parameter estimation in water distribution networks (WDNs). Typical parameters to be estimated include the coefficients used to model major (pipes) and minor (joints, etc.) losses due to friction. The problem of parameter estimation is a nonlinear regression problem and is solved using the error-in-variables approach. The method is illustrated using data from an experimental facility. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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4 pages, 2391 KiB

Open AccessProceeding Paper

A Novel Multi-Step Forecasting-Based Approach for Enhanced Burst Detection in Water Distribution Systems

by Xi Wan, Raziyeh Farmani, Edward Keedwell and Xiao Zhou

Eng. Proc. 2024, 69(1), 146; https://doi.org/10.3390/engproc2024069146 - 12 Sep 2024

Viewed by 210

Abstract

Burst detection in water asset management is a crucial issue in ensuring the efficient and sustainable operation of water distribution systems. For an online burst detection method based on flow time series data, the challenge arises in the variability of anomaly definitions across [...] Read more.

Burst detection in water asset management is a crucial issue in ensuring the efficient and sustainable operation of water distribution systems. For an online burst detection method based on flow time series data, the challenge arises in the variability of anomaly definitions across different datasets, rendering a one-size-fits-all anomaly detection algorithm impossible. Additionally, existing prediction-driven anomaly detection schemes, relying on single-step prediction, face accuracy issues due to susceptibility to input data contamination. In this paper, a novel scheme for burst detection is proposed to address the limitations of existing methods. The approach incorporates a multi-step forecasting model, offering multiple sources for the forecasting, and aggregates the forecasts to establish a common expectation for the data pattern. A metric termed Local Residual Discrepancy (LRD) is proposed to score deviation between predictions and observations. The effectiveness of the proposed method is evaluated through its application to both synthetic and real datasets. Experimental results reveal significant improvements in detection accuracy achieved by the LRD metric, irrespective of the underlying prediction model. This research contributes to the advancement of burst detection methodologies, offering a more robust and versatile approach applicable to varied datasets and prediction models in water distribution systems. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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4 pages, 1762 KiB

Open AccessProceeding Paper

A 24/7 Cloud-Hosted Solution Evaluation for Anomaly Detection and Localization of Large-Scale Water Distribution Networks in Singapore

by Alvin Wei Ze Chew, Zheng Yi Wu, Ashley Zhang, Fred Cao, Rony Kalfarisi, Xue Meng, Jocelyn Pok, Juen Ming Wong, Kah Cheong Lai, Lennis Seow and Jia Jie Wong

Eng. Proc. 2024, 69(1), 147; https://doi.org/10.3390/engproc2024069147 - 18 Sep 2024

Viewed by 306

Abstract

In this study, a novel cloud-hosted software solution, titled as Anomaly Leak Finder (ALF), has been developed in collaboration with PUB, Singapore’s national water agency, to enhance leak detection and localization in four major water distribution networks (WDNs) in Singapore. The large networks [...] Read more.

In this study, a novel cloud-hosted software solution, titled as Anomaly Leak Finder (ALF), has been developed in collaboration with PUB, Singapore’s national water agency, to enhance leak detection and localization in four major water distribution networks (WDNs) in Singapore. The large networks which span over 1000 km of underground pipelines are monitored 24/7 with 90+ smart sensors. Leveraging on near real-time hydraulic time-series data, ALF employs data-driven prediction (DDP) and physics-based simulation (PBS) models to minimize the total non-revenue water (NRW) losses by detecting and localizing hidden pipe leak events before they become disruptive events. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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4 pages, 486 KiB

Open AccessProceeding Paper

Pseudomonas aeruginosa Interactions with Drinking Water Biofilm after an Acute Spike in Annular Bioreactors—Attachment, Persistence, Release, and Reattachment

by Dominic Quinn, Erifyli Tsagkari, Dinesh S. Bhandari, Katherine Fish, Siming You, William T. Sloan, Joby Boxall and Cindy J. Smith

Eng. Proc. 2024, 69(1), 148; https://doi.org/10.3390/engproc2024069148 - 19 Sep 2024

Viewed by 574

Abstract

The potential of DWDS pipewall biofilms to shelter and propagate opportunistic pathogens is currently poorly understood. Here, we use an annular biofilm reactor approach to quantify the fate of the opportunistic pathogen Pseudomonas aeruginosa when introduced to a simulated DWDS environment. We found [...] Read more.

The potential of DWDS pipewall biofilms to shelter and propagate opportunistic pathogens is currently poorly understood. Here, we use an annular biofilm reactor approach to quantify the fate of the opportunistic pathogen Pseudomonas aeruginosa when introduced to a simulated DWDS environment. We found that P. aeruginosa was capable of swift attachment to surfaces and able to persist for up to 14 days under shear stress conditions. Further, we demonstrate that P. aeruginosa is capable of detachment/reattachment and mobilisation through the bulk water, potentially acting as a source of inoculum to drinking water. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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4 pages, 1276 KiB

Open AccessProceeding Paper

Residential End Uses of Water: Global Evidence

by Filippo Mazzoni, Stefano Alvisi, Mirjam Blokker, Steven Buchberger, Andrea Castelletti, Andrea Cominola, Marie-Philine Gross, Heinz E. Jacobs, Peter Mayer, David B. Steffelbauer, Rodney A. Stewart, Ashlynn S. Stillwell, Velitchko Tzatchkov, Victor-Hugo Alcocer Yamanaka and Marco Franchini

Eng. Proc. 2024, 69(1), 149; https://doi.org/10.3390/engproc2024069149 - 19 Sep 2024

Viewed by 610

Abstract

Understanding the residential end uses of water is helpful for the sustainable management of water resources and the implementation of water conservation strategies. In this study, over one hundred studies were systematically reviewed to provide a comprehensive overview of the state-of-the-art research on [...] Read more.

Understanding the residential end uses of water is helpful for the sustainable management of water resources and the implementation of water conservation strategies. In this study, over one hundred studies were systematically reviewed to provide a comprehensive overview of the state-of-the-art research on end-use water consumption. Each study was reviewed, clustered, and subjected to a multilevel analysis aimed at quantitatively comparing the characteristics of the end uses of water available in the literature. The findings of this work support water utilities, researchers, policy makers, and consumers in identifying the key aspects of water end uses and exploring their main features across different geographical, socioeconomic, and cultural regions of the world. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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4 pages, 427 KiB

Open AccessProceeding Paper

Sensor Placement and State Estimation in Water Distribution Systems Using Edge Gaussian Processes

by Bulat Kerimov, Vincent Pons, Spyros Pritsis, Riccardo Taormina and Franz Tscheikner-Gratl

Eng. Proc. 2024, 69(1), 150; https://doi.org/10.3390/engproc2024069150 - 19 Sep 2024

Viewed by 406

Abstract

The operation of water distribution systems is based on reliable knowledge about the steady state of the system. This involves sensors to measure flow, facilitating a comprehensive overview of the system’s performance. Given the costs associated with sensor installation and operation, it is [...] Read more.

The operation of water distribution systems is based on reliable knowledge about the steady state of the system. This involves sensors to measure flow, facilitating a comprehensive overview of the system’s performance. Given the costs associated with sensor installation and operation, it is important to be strategic with sensor allocation. Recently developed Gaussian Processes with topological kernels can efficiently model mass and energy conservative flows and provide uncertainty bounds. Our work proposes a novel method of state estimation and a greedy search algorithm for water flow meter placement based on the uncertainty bounds provided by a Gaussian Process. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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4 pages, 795 KiB

Open AccessProceeding Paper

Optimized Integration of Solar and Battery Systems in Water Distribution Networks

by Anudeep Bhatraj, Elad Salomons and Mashor Housh

Eng. Proc. 2024, 69(1), 151; https://doi.org/10.3390/engproc2024069151 - 19 Sep 2024

Viewed by 394

Abstract

Water Distribution Networks (WDNs) are traditionally known as significant energy users, leading to numerous studies aimed at enhancing their energy efficiency. However, despite the growing attention towards renewable energy, there has been limited focus on seamlessly incorporating sustainable energy solutions into WDNs. We [...] Read more.

Water Distribution Networks (WDNs) are traditionally known as significant energy users, leading to numerous studies aimed at enhancing their energy efficiency. However, despite the growing attention towards renewable energy, there has been limited focus on seamlessly incorporating sustainable energy solutions into WDNs. We present an optimization framework for designing and operating WDNs that integrate renewable energy sources. This model considers the unique constraints and needs of each system component. Drawing from realistic capital and operational cost estimates, this combined system refines the arrangement of both water and energy elements (for instance, determining the appropriate size for solar panels and battery systems and the capacity of pumping stations). It also suggests optimal daily operational strategies for the different seasons of the year, such as when to charge batteries or when to activate/deactivate pumps. Our findings highlight that when water and renewable energy systems are cohesively designed and operated, it can markedly boost the energy efficiency of WDNs, furthering the sustainability goals of both the water and energy sectors. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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4 pages, 786 KiB

Open AccessProceeding Paper

A Novel Reverse Unidirectional Flushing (R-UDF) Method to Mobilize Iron Oxide Particles from PVC Pipes of a Full-Scale Laboratory System

by Benjamin Anderson, Artur Sass Braga, Yves Filion and Sarah Jane Payne

Eng. Proc. 2024, 69(1), 152; https://doi.org/10.3390/engproc2024069152 - 19 Sep 2024

Viewed by 177

Abstract

The aim of the present work is to test a novel Reverse Unidirectional Flushing (R-UDF) approach to achieve an enhanced removal rate of iron oxide particles from drinking water pipes. The project utilized a full-scale PVC pipe loop laboratory system to successfully isolate [...] Read more.

The aim of the present work is to test a novel Reverse Unidirectional Flushing (R-UDF) approach to achieve an enhanced removal rate of iron oxide particles from drinking water pipes. The project utilized a full-scale PVC pipe loop laboratory system to successfully isolate direction as a particle mobilization factor. Even after successive flushing operations in one direction, a subsequent flush in the opposite direction mobilized new particles from the pipe wall surface. This shows that there are some areas in the pipe loop system that may protect deposited particles from flushing shear stresses in a determined flow direction. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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5 pages, 766 KiB

Open AccessProceeding Paper

Energy Optimization in Pressurized Water Networks: Exploring Case Studies with Energos Tool for Sustainable Solutions

by Elena Gómez, Roberto del Teso, Elvira Estruch-Juan and Enrique Cabrera

Eng. Proc. 2024, 69(1), 153; https://doi.org/10.3390/engproc2024069153 - 19 Sep 2024

Viewed by 294

Abstract

This paper describes energy diagnostics for water networks, which are complex systems with one or several inputs and multiple outputs, and also describes the ENERGOS tool created to perform the diagnostics. This tool was designed and conceived to be easy to use and [...] Read more.

This paper describes energy diagnostics for water networks, which are complex systems with one or several inputs and multiple outputs, and also describes the ENERGOS tool created to perform the diagnostics. This tool was designed and conceived to be easy to use and mainly requires few data from the system. For target setting, ENERGOS has a set of wizards that guide the user in setting these limits and proposes values based on experience, the literature or regulations. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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5 pages, 683 KiB

Open AccessProceeding Paper

A Study on Short-Term Water-Demand Forecasting Using Statistical Techniques

by Jungwon Yu, Hyansu Bae, Mi-Seon Kang, Kwang-Ju Kim and In-Su Jang

Eng. Proc. 2024, 69(1), 154; https://doi.org/10.3390/engproc2024069154 - 20 Sep 2024

Viewed by 272

Abstract

This paper proposes a method for short-term weekly water-demand forecasting combining various statistical techniques. In the proposed method, training datasets are prepared through exploratory data analysis, several data preprocessing steps, and an input selection step; also, forecasting models are constructed by support vector [...] Read more.

This paper proposes a method for short-term weekly water-demand forecasting combining various statistical techniques. In the proposed method, training datasets are prepared through exploratory data analysis, several data preprocessing steps, and an input selection step; also, forecasting models are constructed by support vector regression. After this, weekly water-demand forecasts are calculated using iterated and direct strategies. To verify the performance, the proposed method is applied to urban hourly water-demand datasets provided by the Battle of Water Demand Forecasting organized in the 3rd WDSA-CCWI Joint Conference. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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4 pages, 372 KiB

Open AccessProceeding Paper

Predictive Model for Short-Term Water Demand Forecasting and Feature Analysis in Urban Networks

by Jorge E. Pesantez, Morgan DiCarlo, Fayzul Pasha and Emily Z. Berglund

Eng. Proc. 2024, 69(1), 155; https://doi.org/10.3390/engproc2024069155 - 15 Sep 2024

Viewed by 417

Abstract

Variability in water use and user characteristics influences the operational management of water distribution systems (WDS). Types of water use and external factors including socioeconomic characteristics and weather variables can affect the normal operation of WDS. Accurate demand prediction is crucial, yet existing [...] Read more.

Variability in water use and user characteristics influences the operational management of water distribution systems (WDS). Types of water use and external factors including socioeconomic characteristics and weather variables can affect the normal operation of WDS. Accurate demand prediction is crucial, yet existing methods lack industry-wide comparability. This study applies a supervised learning model, IONET, that utilizes feedforward neural networks for short-term demand forecasting. IONET incorporates lagged demand, seasonal predictors, and weather variables. Tested on Italian DMA data, it swiftly produces accurate forecasts across various horizons. Feature importance analysis underscores the significance of seasonal variables and lagged demand. The IONET model offers prompt training and valuable insights for optimizing WDS management, facilitating the digital transformation of water infrastructure. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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5 pages, 757 KiB

Open AccessProceeding Paper

Online Temperature Modeling in the Hangzone Sonnenberg, Zurich

by Fabio Belotti, Harald Tarnowski, Zdenek Svitak and Petr Ingeduld

Eng. Proc. 2024, 69(1), 156; https://doi.org/10.3390/engproc2024069156 - 20 Sep 2024

Viewed by 235

Abstract

Continuous measurements within the water distribution network of the Water Supply Zurich (WVZ) revealed surprisingly high water temperatures in different locations, especially during the summer months. Initial investigations were unable to determine the source of the elevated water temperatures, so the WVZ initiated [...] Read more.

Continuous measurements within the water distribution network of the Water Supply Zurich (WVZ) revealed surprisingly high water temperatures in different locations, especially during the summer months. Initial investigations were unable to determine the source of the elevated water temperatures, so the WVZ initiated a pilot project for online monitoring and modeling of the water temperature in the network for the Hangzone Sonnenberg pressure zone. Modeling the interaction of the initial water source temperature, water source mixing and heat exchange due to ground temperature is one of the main challenges in this project. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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4 pages, 567 KiB

Open AccessProceeding Paper

Water Leakage Pre-Localization in Drinking Water Networks via the Cosmic-Ray Neutron Sensing Technique

by Luca Morselli, Federica Lorenzi, Andrea Basso and Luca Stevanato

Eng. Proc. 2024, 69(1), 157; https://doi.org/10.3390/engproc2024069157 - 20 Sep 2024

Viewed by 385

Abstract

Water leaks in drinking water networks contribute significantly to water losses and pose challenges to infrastructure sustainability. This study introduces a novel approach using Cosmic-Ray Neutron Sensing (CRNS) for pre-localizing leaks. We present a CRNS-based roving system that can detect the neutrons and [...] Read more.

Water leaks in drinking water networks contribute significantly to water losses and pose challenges to infrastructure sustainability. This study introduces a novel approach using Cosmic-Ray Neutron Sensing (CRNS) for pre-localizing leaks. We present a CRNS-based roving system that can detect the neutrons and muons produced by cosmic rays, providing real-time, below-ground water content data while addressing local variations. These data are analyzed using a one-class Support Vector Machine trained in an unsupervised manner. Finally, a brief overview of a proof of concept of the method conducted in a water district in Northern Italy is shown, highlighting preliminary results alongside some limitations. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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4 pages, 861 KiB

Open AccessProceeding Paper

Interpretable Sewer Defect Detection with Large Multimodal Models

by Riccardo Taormina and Job Augustijn van der Werf

Eng. Proc. 2024, 69(1), 158; https://doi.org/10.3390/engproc2024069158 - 20 Sep 2024

Viewed by 512

Abstract

Large Multimodal Models are emerging general AI models capable of processing and analyzing diverse data streams, including text, imagery, and sequential data. This paper explores the possibility of exploiting multimodality to develop more interpretable AI-based predictive tools for the water sector, with a [...] Read more.

Large Multimodal Models are emerging general AI models capable of processing and analyzing diverse data streams, including text, imagery, and sequential data. This paper explores the possibility of exploiting multimodality to develop more interpretable AI-based predictive tools for the water sector, with a first application for sewer defect detection from CCTV imagery. To this aim, we test the zero-shot generalization performance of three generalist large language-vision models for binary sewer defect detection on a subset of the SewerML dataset. We compared the LMMs against a state-of-the-art unimodal Deep Learning approach which has been trained and validated on >1 million SewerML images. Unsurprisingly, the chosen benchmark showcases the best performances, with an overall F1 Score of 0.80. Nonetheless, OpenAI GPT4-V demonstrates relatively good performances with an overall F1 Score of 0.61, displaying equal or better results than the benchmark for some defect classes. Furthermore, GPT4-V often provides text descriptions aligned with the provided prediction, accurately describing the rationale behind a certain decision. Similarly, GPT4-V displays interesting emerging behaviors for trustworthiness, such as refusing to classify images that are too blurred or unclear. Despite the significantly lower performance from the open-source models CogVLM and LLaVA, some preliminary successes suggest good potential for enhancement through fine-tuning, agentic workflows, or retrieval-augmented generation. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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4 pages, 494 KiB

Open AccessProceeding Paper

Review of Reduced-Order Models for Online Protection of Water Distribution Networks

by Cheima Djemel, Olivier Piller, Thierry Horsin, Chloé Mimeau and Iraj Mortazavi

Eng. Proc. 2024, 69(1), 159; https://doi.org/10.3390/engproc2024069159 - 19 Sep 2024

Viewed by 289

Abstract

This paper presents a review of reduced-order models (ROMs) and digital twins, with a primary focus on their application to water distribution networks (WDNs). Initially, we concentrated on the physical modelling of WDNs. Following this, we introduced relevant programming, specifically addressing WDNs and [...] Read more.

This paper presents a review of reduced-order models (ROMs) and digital twins, with a primary focus on their application to water distribution networks (WDNs). Initially, we concentrated on the physical modelling of WDNs. Following this, we introduced relevant programming, specifically addressing WDNs and solving equations for extended-period simulations. This paper then explored various ROM methods outlined in the existing literature. Lastly, we highlighted recent initiatives in the implementation of digital twins and approaches aimed at reducing uncertainty. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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4 pages, 548 KiB

Open AccessProceeding Paper

Automatic Distribution of PRVs for Leakage Reduction

by Ramon Pérez, Guillem Roca and Sergi Grau

Eng. Proc. 2024, 69(1), 160; https://doi.org/10.3390/engproc2024069160 - 23 Sep 2024

Viewed by 246

Abstract

In this work, an automatic distribution of the pressure reduction valves (PRVs) is proposed. First, a well-calibrated hydraulic model is required. The model of Manresa, a city of Catalunya in the Mediterranean area, was calibrated using pressure sensors, and the background leakage was [...] Read more.

In this work, an automatic distribution of the pressure reduction valves (PRVs) is proposed. First, a well-calibrated hydraulic model is required. The model of Manresa, a city of Catalunya in the Mediterranean area, was calibrated using pressure sensors, and the background leakage was estimated using weighted emitter coefficients. Simulating the model in real boundary conditions highlights the areas of maximum background leakage. The manual introduction of a PRV shows its effectiveness regarding leakage reduction. An algorithm for finding the high-pressure areas and their boundary pipes is presented. The introduction of the PRV, taking into account the flow constraints, produces a new scenario. Finally, the leakage reduction thanks to the pressure control by means of new actuators is evaluated. The leakage is reduced by around 6%. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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4 pages, 1573 KiB

Open AccessProceeding Paper

Assessing the Operation of a Well Field by Coupling EPANET to the Results of a Hydrogeological Study

by Ștefan-Dragoș Găitănaru, Iulian Iancu, Sanda-Carmen Georgescu and Andrei-Mugur Georgescu

Eng. Proc. 2024, 69(1), 161; https://doi.org/10.3390/engproc2024069161 - 23 Sep 2024

Viewed by 234

Abstract

Due to the increased development of urban areas and climate change, water resource management is gaining more attention. Among the most important aspects under scrutiny is improving the reliability of water resources. In this paper, the focus is on the dynamic modelling of [...] Read more.

Due to the increased development of urban areas and climate change, water resource management is gaining more attention. Among the most important aspects under scrutiny is improving the reliability of water resources. In this paper, the focus is on the dynamic modelling of a well field in EPANET. By dynamic modelling, we mean that the numerical model can adjust the water levels in the wells with respect to the extracted flow rate, according to the results of the hydrogeological study of the area. The operation of a well field must sometimes be realized at partial loads. In this latter case, all the duty points of the pumps in operation change and the flow rates may exceed the maximum allowed values, leading to the rapid clogging of the wells. The model and results obtained for different operating scenarios will be presented in the paper. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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4 pages, 2067 KiB

Open AccessProceeding Paper

Tool to Model the Potential Risk of Legionella Growth in Premise Plumbing Systems

by Kevin Vargas, Michael Waak, Franz Tscheikner-Gratl and Marius Rokstad

Eng. Proc. 2024, 69(1), 162; https://doi.org/10.3390/engproc2024069162 - 23 Sep 2024

Viewed by 245

Abstract

Water quality problems due to stagnation during periods of low or no demand in buildings, such as the growth of Legionella bacteria, may arise in potable cold and hot water systems. Premise plumbing installations should therefore be designed and constructed to prevent bacterial [...] Read more.

Water quality problems due to stagnation during periods of low or no demand in buildings, such as the growth of Legionella bacteria, may arise in potable cold and hot water systems. Premise plumbing installations should therefore be designed and constructed to prevent bacterial growth, and then operated to provide satisfactory protection against Legionella. In several building types, over 50% of the total energy usage is connected to hot water production. In large part, this is because hot water systems are maintained at 60 to 70 °C to deter Legionella growth, which may be at odds with sustainability goals. With the latter in mind, recent studies have combined both hydraulics and temperature modelling, obtaining satisfactory prediction results when tested by making digital twins. In the present study, a tool was developed which allows users to see the detailed results of premise plumbing system modelling through a web-based interactive dashboard. The hydraulics are modelled using WNTR, water demands are generated with pySIMDEUM, and temperature is modelled using heat transfer theory for conduction and convection. Some examples are presented to illustrate the extent of the tool, as well as visualising indicators relevant to Legionella growth potential, such as water age and temperature range. This tool can support building managers and designers with improving serviceability, minimising environmental footprint, and providing safe water in new and existing premise plumbing systems. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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4 pages, 1926 KiB

Open AccessProceeding Paper

Sizing Behind-the-Meter Solar PV Systems for Water Distribution Networks

by Qi Zhao, Wenyan Wu, Jiayu Yao, Angus Ross Simpson, Ailsa Willis and Lu Aye

Eng. Proc. 2024, 69(1), 163; https://doi.org/10.3390/engproc2024069163 - 23 Sep 2024

Viewed by 326

Abstract

This study investigates three methods for sizing behind-the-meter (BTM) solar PV systems for pumped water distribution networks (WDNs). The three methods are (1) the industry method based on current industry practices, (2) the minimum total life cycle cost (TLCC) method to minimize TLCC [...] Read more.

This study investigates three methods for sizing behind-the-meter (BTM) solar PV systems for pumped water distribution networks (WDNs). The three methods are (1) the industry method based on current industry practices, (2) the minimum total life cycle cost (TLCC) method to minimize TLCC through the life of solar PV systems, and (3) the minimum payback method to minimize the time to pay off the capital investment in solar PV systems. The industry method risks over-sizing, while the minimum payback method risks under-sizing. The minimum TLCC method leads to systems with balanced performance. The findings offer decision-makers insights when selecting solar PV systems for WDNs. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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4 pages, 870 KiB

Open AccessProceeding Paper

Reinterpretation of Water Temperature Measurements

by Aulia Galama-Tirtamarina and Mirjam Blokker

Eng. Proc. 2024, 69(1), 164; https://doi.org/10.3390/engproc2024069164 - 24 Sep 2024

Viewed by 322

Abstract

Drinking water temperatures above 25 °C have been measured more often since Dutch drinking water companies are required to take Random Day Time (RDT) samples. The objective of this study was to obtain more information from the required temperature measurements. A total of [...] Read more.

Drinking water temperatures above 25 °C have been measured more often since Dutch drinking water companies are required to take Random Day Time (RDT) samples. The objective of this study was to obtain more information from the required temperature measurements. A total of 34,595 drinking water temperature measurements between 2012 and 2021 were analyzed and compared with the temperature prediction from a soil temperature model (STM), developed by Blokker and Pieterse-Quirijns (2013) and Agudelo-Vera et al. (2015). More than 300 exceedances of the modeled urban soil temperature were found (ca. 1%). While there were only four measurements with temperatures higher than 25 °C. By looking at the locations of the temperature exceedances, drinking water companies can further investigate whether there are other heat sources near these locations. Using the STM calculations as a reference for the measured drinking water temperature has provided more options for locating hotspots. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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5 pages, 394 KiB

Open AccessProceeding Paper

First- and Second-Order Sensitivities of Steady-State Solutions to Water Distribution Systems

by Olivier Piller, Sylvan Elhay, Jochen W. Deuerlein and Angus R. Simpson

Eng. Proc. 2024, 69(1), 165; https://doi.org/10.3390/engproc2024069165 - 19 Sep 2024

Viewed by 185

Abstract

First-order approximations have been used with some success for criticality analysis; sensitivity analysis of physical networks, such as water distribution systems; and uncertainty propagation of model parameters. Certain limitations have been reported regarding the accuracy of the results, particularly when non-linearity is dominant. [...] Read more.

First-order approximations have been used with some success for criticality analysis; sensitivity analysis of physical networks, such as water distribution systems; and uncertainty propagation of model parameters. Certain limitations have been reported regarding the accuracy of the results, particularly when non-linearity is dominant. In this paper, we show how to efficiently derive the first- and second-order sensitivities with respect to variation in their parameters. This makes it possible to improve the first-order estimate when necessary. The method is illustrated on a small example system. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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4 pages, 2967 KiB

Open AccessProceeding Paper

Area Leakage Estimation in Water Distribution Systems: A Focus on Background Leakage

by Raghavarshith Bandreddi and Raziyeh Farmani

Eng. Proc. 2024, 69(1), 166; https://doi.org/10.3390/engproc2024069166 - 24 Sep 2024

Viewed by 179

Abstract

Leakage is a major issue faced by utilities across the world. Background leaks constitute a large component, and their small size makes it challenging to localize. This paper presents a hydraulic model-based approach to localize background leaks. The proposed methodology clusters nodes into [...] Read more.

Leakage is a major issue faced by utilities across the world. Background leaks constitute a large component, and their small size makes it challenging to localize. This paper presents a hydraulic model-based approach to localize background leaks. The proposed methodology clusters nodes into leak groups using node-weighted spectral clustering and estimates background leakage in each leak group using optimization. The algorithm successfully localized 113 out of 118 background leaks (no leak size >0.28% of the bulk supply) and estimated the leakage amount using simulated data. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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4 pages, 1260 KiB

Open AccessProceeding Paper

A Multivariate LSTM Model for Short-Term Water Demand Forecasting

by Aly K. Salem and Ahmed A. Abokifa

Eng. Proc. 2024, 69(1), 167; https://doi.org/10.3390/engproc2024069167 - 25 Sep 2024

Viewed by 1018

Abstract

Accurate water demand forecasting is crucial for the effective operation and management of water distribution networks. Predicting future water demand empowers utilities to optimally operate system components. Various data-driven methodologies have been proposed for water demand forecasting, including artificial neural networks and econometric [...] Read more.

Accurate water demand forecasting is crucial for the effective operation and management of water distribution networks. Predicting future water demand empowers utilities to optimally operate system components. Various data-driven methodologies have been proposed for water demand forecasting, including artificial neural networks and econometric models. Recently, Long Short-Term Memory (LSTM) was shown to be particularly relevant for this application. Nevertheless, few studies have utilized multivariate-LSTM (M-LSTM) models for water demand forecasting. This study introduces an M-LSTM model incorporating historical water demands, meteorological data, and social variables to forecast short-term water demand. The proposed M-LSTM model performance was tested by applying it to the ten district metered areas (DMAs) case study of the Battle of Water Demand Forecasting (BWDF). The results demonstrated the model’s ability to accurately predict the hourly water demand one week in advance. The mean absolute error of the predictions ranged between 0.5 and 2.2 l/s (2.8% to 12.9% of the average demand). The results also showed a strong correlation between the prediction error and the variability of the water demand data. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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4 pages, 1984 KiB

Open AccessProceeding Paper

Towards Optimal Scheduling of Intermittent Water Supply Systems Incorporating Consumer Behavior

by Sriman Pankaj Boindala, Gopinathan R. Abhijith, K. Ihjas and Avi Ostfeld

Eng. Proc. 2024, 69(1), 168; https://doi.org/10.3390/engproc2024069168 - 25 Sep 2024

Viewed by 340

Abstract

Intermittent water supply (IWS) systems, originally intended for continuous supply, have been compelled to adopt intermittent supply due to factors such as water scarcity, financial limitations, ineffective operational tactics, unexpected increases in demand, and infrastructure deterioration. In response, consumers have adapted by employing [...] Read more.

Intermittent water supply (IWS) systems, originally intended for continuous supply, have been compelled to adopt intermittent supply due to factors such as water scarcity, financial limitations, ineffective operational tactics, unexpected increases in demand, and infrastructure deterioration. In response, consumers have adapted by employing flexible behaviors and utilizing storage tanks to manage water during non-supply periods. This study aims to present a methodology for devising an optimal schedule for intermittent operations, prioritizing consumer equity. The framework is tailored to a real-world intermittent network in rural South India, accounting for practical constraints and fluctuations in demand. This article only shows the preliminary analysis of the system; the development of the optimization framework is still a work in progress. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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4 pages, 1035 KiB

Open AccessProceeding Paper

Experimental Setup for Measuring the Effect of Biofilm Build-up on Heat Transfer in Drinking Water Pipes

by Konstantinos Glynis, Mirjam Blokker, Zoran Kapelan and Dragan Savić

Eng. Proc. 2024, 69(1), 169; https://doi.org/10.3390/engproc2024069169 - 25 Sep 2024

Viewed by 369

Abstract

Biofilm formation in drinking water distribution systems (DWDSs) poses challenges to water quality and system integrity. Traditional measurement methods often involve intrusive techniques, disrupting the biofilm ecosystem, while non-intrusive methods offer promising alternatives. This paper explores the feasibility of using non-intrusive temperature sensing [...] Read more.

Biofilm formation in drinking water distribution systems (DWDSs) poses challenges to water quality and system integrity. Traditional measurement methods often involve intrusive techniques, disrupting the biofilm ecosystem, while non-intrusive methods offer promising alternatives. This paper explores the feasibility of using non-intrusive temperature sensing to monitor biofilm growth in PVC pipes. Through experiments using the SLIMER 2.0 setup, the biofilm accumulation’s impact on the heat transfer properties is investigated. Preliminary results show successful biofilm growth under controlled conditions, with temperature measurements revealing alterations in heat resistance, hence providing a basis for biofilm monitoring. This study contributes to advancing biofilm monitoring techniques, offering insights for improved water quality management in DWDSs. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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5 pages, 3339 KiB

Open AccessProceeding Paper

Development of an Integrated System for Efficient Water Resource Management Using ESP32, MicroPython and the IoT

by Marina Lloys, Josep Lluis Guixà, Claudia Dragoste, Jordi Cots, Teresa Escobet and Sergi Grau

Eng. Proc. 2024, 69(1), 170; https://doi.org/10.3390/engproc2024069170 - 25 Sep 2024

Viewed by 386

Abstract

This article describes the development and implementation of a water resource management system utilizing open technologies such as the ESP32 microcontroller and MicroPython. This system stands out for its low cost, high efficiency and adaptability to various environments, thanks to the integration of [...] Read more.

This article describes the development and implementation of a water resource management system utilizing open technologies such as the ESP32 microcontroller and MicroPython. This system stands out for its low cost, high efficiency and adaptability to various environments, thanks to the integration of free or low-cost communications such as LoRaWAN and NB-IoT, as well as the use of open-source programming, which offers flexibility. The article details the use of JSN-SR04T ultrasonic sensors, manufactured by JINZHAN, a company based in China, for water-level measurement and the use of 3D printing to manufacture customized components, demonstrating a scalable and replicable solution for efficient water management. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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4 pages, 622 KiB

Open AccessProceeding Paper

Optimal Sensor Placement in Water Distribution Networks Using Dynamic Prediction Graph Neural Networks

by Aly K. Salem and Ahmed A. Abokifa

Eng. Proc. 2024, 69(1), 171; https://doi.org/10.3390/engproc2024069171 - 25 Sep 2024

Viewed by 356

Abstract

Sensors are a key component of water distribution networks due to their role in monitoring system variables. Specifically, water quality (WQ) sensors are utilized to measure chlorine concentrations in order to maintain water quality standards. However, the prohibitive costs of deploying these sensors [...] Read more.

Sensors are a key component of water distribution networks due to their role in monitoring system variables. Specifically, water quality (WQ) sensors are utilized to measure chlorine concentrations in order to maintain water quality standards. However, the prohibitive costs of deploying these sensors constrain their ubiquitous use. As a result, WQ sensors are typically placed in a subset of junctions that are selected via an optimization process. This study presents a framework for optimizing WQ sensor placement to maximize chlorine concentration state estimation, that is, the inference of water quality parameters at unmonitored junctions based on the measurements from monitored junctions. This is performed by integrating a Dynamic Prediction Graph Neural Network (DP-GNN) model with a Genetic Algorithm (GA). The DP-GNN model is trained to predict chlorine concentrations at all junctions based on the measurements from sensors with different placements, whereas the GA uses these predictions to find the optimal sensor placement. The framework performance was tested by applying it to the C-town benchmark network, considering different numbers of sensors. The results demonstrated the impact of different sensor placements on the prediction accuracy of the DP-GNN model. Additionally, the results showed the framework’s ability to find the sensor placement that maximizes the chlorine concentration state estimation performance. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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4 pages, 458 KiB

Open AccessProceeding Paper

A Hydroacoustic Model for the Identification of Incipient Cavitation: A Preliminary Study

by Renato Montillo, Maria Cristina Morani, Oreste Fecarotta and Armando Carravetta

Eng. Proc. 2024, 69(1), 172; https://doi.org/10.3390/engproc2024069172 - 25 Sep 2024

Viewed by 245

Abstract

Recent research has focused on the dynamic control and regulation of hydraulic devices like pumps and turbines to enhance the efficiency of water systems. These devices are adjusted to maintain nearly optimal hydraulic conditions and operating efficiency, although achieving both can be challenging [...] Read more.

Recent research has focused on the dynamic control and regulation of hydraulic devices like pumps and turbines to enhance the efficiency of water systems. These devices are adjusted to maintain nearly optimal hydraulic conditions and operating efficiency, although achieving both can be challenging due to factors like machine type and changes in distribution patterns. Incipient cavitation, which can cause mechanical damage and reduce efficiency, presents a specific challenge. It produces a distinct noise which this study aims to detect through a proposed methodology. Using the LES WALE model in OpenFOAM and Lighthill’s acoustic analogy, this research simulates and analyzes the noise generated by the dynamic of a confined flow. This work aims to be the starting point for more complex models. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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5 pages, 1448 KiB

Open AccessProceeding Paper

A Parametric Evaluation of Leakages in Water Distribution Networks

by Giovanna Darvini, Martina Gambadori and Luciano Soldini

Eng. Proc. 2024, 69(1), 173; https://doi.org/10.3390/engproc2024069173 - 23 Sep 2024

Viewed by 197

Abstract

One of the main problems of water distribution systems is the management and the evaluation of water losses. At the Laboratory of Hydraulics and Maritime Constructions at the Università Politecnica delle Marche, experimental research on this topic was conducted to measure the water [...] Read more.

One of the main problems of water distribution systems is the management and the evaluation of water losses. At the Laboratory of Hydraulics and Maritime Constructions at the Università Politecnica delle Marche, experimental research on this topic was conducted to measure the water volume exiting from a known shape and size hole at fixed hydraulic conditions. The obtained results were also used as input data for the Evolutionary Polynomial Regression (EPR) analysis for the construction of prediction models that could be employed for the management of water leakages in pressurized networks. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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4 pages, 1189 KiB

Open AccessProceeding Paper

Exploring the Impact of Pulsed Demand Model on the Quality Sensor Placement in Water Distribution Networks

by Carlo Giudicianni and Enrico Creaco

Eng. Proc. 2024, 69(1), 174; https://doi.org/10.3390/engproc2024069174 - 26 Sep 2024

Viewed by 292

Abstract

In this work, the impact of the actual pulsed nature of demand on the water quality sensor placement problem was investigated. The optimization was carried out by minimizing alternatively the extent of contamination and exposed population to ingestion by considering two alternative demand [...] Read more.

In this work, the impact of the actual pulsed nature of demand on the water quality sensor placement problem was investigated. The optimization was carried out by minimizing alternatively the extent of contamination and exposed population to ingestion by considering two alternative demand modelling conditions: (i) a smooth top-down deterministic approach (TDA), and (ii) a pulsed demand bottom-up stochastic approach (BUA). An Italian water distribution network was tested, and results show that the contamination extension and sensor locations are affected by demand modeling and that monitoring system performance may be overestimated if the deterministic approach is used, leading to dangerous management choices. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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4 pages, 1772 KiB

Open AccessProceeding Paper

Short-Term Urban Water Demand Forecasting Using an Improved NeuralProphet Model

by Yao Yao, Haixing Liu, Fengrui Gao, Hongcai Guo and Jiaxuan Zou

Eng. Proc. 2024, 69(1), 175; https://doi.org/10.3390/engproc2024069175 - 26 Sep 2024

Viewed by 305

Abstract

The use of machine learning models for short-term network flow prediction has become increasingly widespread in recent years. Existing data-driven models are usually able to achieve good accuracy, but machine learning models are usually weakly interpretable and cannot provide clear decision guidance to [...] Read more.

The use of machine learning models for short-term network flow prediction has become increasingly widespread in recent years. Existing data-driven models are usually able to achieve good accuracy, but machine learning models are usually weakly interpretable and cannot provide clear decision guidance to decision makers in practical applications. Determining the input data shape of the model has an important impact on improving the interpretability of the model and understanding the relationship between the input factors and the application scenarios in the case. In this study, we used an integrated model for urban water demand prediction, which is based on the NeuralProphet model, and introduced the MIC method to screen the model input factors, which led to improvements in the accuracy of the prediction model. The aim of this work is also to improve the interpretability of water demand forecasting methodologies and the applicability of this model in the context of climate change and the complexity of urban water management, in order to help water managers make optimal water resource allocation decisions under different future scenarios. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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4 pages, 200 KiB

Open AccessProceeding Paper

An Approach Based on the Use of Commercial Codes and Engineering Judgement for the Battle of Water Demand Forecasting

by Alfredo Iglesias-Rey, Carlos Alfonso López Hojas, F. Javier Martínez-Solano and Pedro L. Iglesias-Rey

Eng. Proc. 2024, 69(1), 176; https://doi.org/10.3390/engproc2024069176 - 27 Sep 2024

Viewed by 340

Abstract

This paper demonstrates the synergistic use of engineering judgment and statistical/deep learning models, implemented through a four-step process using the software SAS Viya 4. Initial data filtering, input variable determination, and simultaneous application of RNN, LSTM, and GRU forecasting algorithms are conducted. Results [...] Read more.

This paper demonstrates the synergistic use of engineering judgment and statistical/deep learning models, implemented through a four-step process using the software SAS Viya 4. Initial data filtering, input variable determination, and simultaneous application of RNN, LSTM, and GRU forecasting algorithms are conducted. Results are evaluated based on Battle of Water Demand Forecasting criteria, refining parameters iteratively for enhanced prediction accuracy. The methodology iteratively incorporates new data, streamlining neural network resolution. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

4 pages, 1848 KiB

Open AccessProceeding Paper

Short-Term Water Demand Forecasting Using Machine Learning Approaches in a Case Study of a Water Distribution Network Located in Italy

by Qidong Que, Jinliang Gao, Wenyan Wu, Huizhe Cao, Kunyi Li, Hanshu Zhang, Yi He and Rui Shen

Eng. Proc. 2024, 69(1), 177; https://doi.org/10.3390/engproc2024069177 - 29 Sep 2024

Viewed by 449

Abstract

Machine learning’s application in short-term water demand forecasting remains a pivotal area of research in water distribution system studies. This investigation reveals a distinctive distribution pattern for the daily demand following dataset preprocessing with Random Forest and the quartile method. Inspired by the [...] Read more.

Machine learning’s application in short-term water demand forecasting remains a pivotal area of research in water distribution system studies. This investigation reveals a distinctive distribution pattern for the daily demand following dataset preprocessing with Random Forest and the quartile method. Inspired by the findings, this study introduces a novel Water Demand Forecast Framework (WDFF) using DMA characteristics and the CNN–Attention–LSTM architecture. By analyzing the relationship between the total and DMA-specific demand, the WDFF is found to enhance the predictions. It demonstrates expedited convergence and reduces the loss metric, demonstrating its potential to elevate the predictive precision in water demand forecasting. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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4 pages, 607 KiB

Open AccessProceeding Paper

Predicting Net Inflow for 10 DMAs in North-East Italy

by Kristina Arsova, Claudia Quintiliani, Dennis Schol and Maaike Walraad

Eng. Proc. 2024, 69(1), 178; https://doi.org/10.3390/engproc2024069178 - 27 Sep 2024

Viewed by 211

Abstract

This paper introduces a two-step methodology for short-term water demand forecasting. In the first step, a pre-processing analysis of the inflow input data is conducted to evaluate completeness and quality, ensuring optimal data integrity. Subsequently, in the second step, a robust machine-learning algorithm [...] Read more.

This paper introduces a two-step methodology for short-term water demand forecasting. In the first step, a pre-processing analysis of the inflow input data is conducted to evaluate completeness and quality, ensuring optimal data integrity. Subsequently, in the second step, a robust machine-learning algorithm is employed to predict the water demand patterns. The methodology is applied across 10 District Metering Areas (DMAs) in the north-east of Italy, each characterized by unique demographic features. Accordingly, tailored features are carefully selected for inclusion in the water demand forecast for each DMA. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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4 pages, 1495 KiB

Open AccessProceeding Paper

Week-Ahead Water Demand Forecasting Using Convolutional Neural Network on Multi-Channel Wavelet Scalogram

by Adithya Ramachandran, Hatem Mousa, Andreas Maier and Siming Bayer

Eng. Proc. 2024, 69(1), 179; https://doi.org/10.3390/engproc2024069179 - 30 Sep 2024

Viewed by 617

Abstract

Water management is vital for building an adaptive and resilient society. Water demand forecasting aids water management by learning the underlying relationship between consumption and governing variables for optimal supply. In this paper, we propose a week-ahead hourly water demand forecasting technique based [...] Read more.

Water management is vital for building an adaptive and resilient society. Water demand forecasting aids water management by learning the underlying relationship between consumption and governing variables for optimal supply. In this paper, we propose a week-ahead hourly water demand forecasting technique based on deep learning (DL) utilizing an encoded representation of historical supply data and influencing exogenous variables for a District Metered Area (DMA). We deploy a CNN model with and without attention and evaluate the model’s ability to forecast the supply for different DMAs with varying characteristics. The performances are quantitatively and qualitatively compared against a baseline LSTM. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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5 pages, 1260 KiB

Open AccessProceeding Paper

Data Analysis to Assess and Improve the Operation of Combined Sewer Overflow Structures with Static Optimization

by Karim Sedki, Yannic Brüning and Ulrich Dittmer

Eng. Proc. 2024, 69(1), 180; https://doi.org/10.3390/engproc2024069180 - 30 Sep 2024

Viewed by 246

Abstract

Combined sewer systems contain flow-dividing structures. These provide retention volumes for hydraulic overloads of the sewer system during storm weather events. The operation of these structures can be optimized by adjusting the continuous flows of their flow control devices. With that, it is [...] Read more.

Combined sewer systems contain flow-dividing structures. These provide retention volumes for hydraulic overloads of the sewer system during storm weather events. The operation of these structures can be optimized by adjusting the continuous flows of their flow control devices. With that, it is possible to improve the efficiency of entire systems in terms of emissions by making better use of the existing volumetric capacity. To assess this potential, water level measurements from CSO storage tanks were analyzed using statistical methods such as scaling, deviation, and frequency analysis. The data analysis also obtained meta information, such as weir heights and continuation flows, which were more accurate than manual measurements taken in the tank or from construction plans. The main steps involved data preprocessing and meta data gathering to separate events and evaluate the system’s basic functioning. This was followed by optimization of the settings of the flow control devices using an emulator and a genetic algorithm. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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5 pages, 653 KiB

Open AccessProceeding Paper

Application of Primary Network Analysis in Real Water Distribution Systems

by Lorenzo Carmelo Zingali, Michele Monaci and Cristiana Bragalli

Eng. Proc. 2024, 69(1), 181; https://doi.org/10.3390/engproc2024069181 - 8 Oct 2024

Viewed by 286

Abstract

Water distribution systems (WDSs) play a vital rule in communities, ensuring well-being and supporting social and economic growth. Consequently, they are recognized as critical infrastructures for which identifying priorities in design and maintenance interventions is a fundamental step. This work applies a methodology [...] Read more.

Water distribution systems (WDSs) play a vital rule in communities, ensuring well-being and supporting social and economic growth. Consequently, they are recognized as critical infrastructures for which identifying priorities in design and maintenance interventions is a fundamental step. This work applies a methodology founded on graph theory based algorithmic approach to identify a connected subgraph named the Primary Network (PN) in complex WDSs by focusing on the potentially most suitable paths for transferring water resources in a perspective of interconnection of water sources. Furthermore, the PN can constitute the supporting infrastructure on which to set up a possible WDS sectorization. An efficient implementation is discussed, and the results are presented for a real WDS. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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4 pages, 712 KiB

Open AccessProceeding Paper

Sensor Location for Hydraulic Transient Monitoring and Leakage Location

by Rui Gabriel Souza, Bruno Brentan and Gustavo Meirelles

Eng. Proc. 2024, 69(1), 182; https://doi.org/10.3390/engproc2024069182 - 8 Oct 2024

Viewed by 282

Abstract

Distribution Networks operate dynamically due to variable water consumption, but optimal operation is hindered by leakages, which increase treatment costs, energy consumption, and water shortage risks. Detecting and locating leaks, especially slow or low-flow ones, is challenging with steady-state data. However, during transient [...] Read more.

Distribution Networks operate dynamically due to variable water consumption, but optimal operation is hindered by leakages, which increase treatment costs, energy consumption, and water shortage risks. Detecting and locating leaks, especially slow or low-flow ones, is challenging with steady-state data. However, during transient events, pressure oscillations are influenced by leaks, providing valuable signal attenuation for leak location. This study evaluates the pressure signal during valve closures to identify optimal monitoring points and valve operation rules, aiming to maximize information collection during transients. The findings aim to enhance leak detection strategies and improve network efficiency. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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4 pages, 2786 KiB

Open AccessProceeding Paper

Optimized Design of Dead-End Spoiler Using PIV

by Jinliang Gao, Kunyi Li, Wenyan Wu, Shihua Qi, Huizhe Cao, Wei Qiu, Junjun He, Jiawen Zhang and Yanchen Ding

Eng. Proc. 2024, 69(1), 183; https://doi.org/10.3390/engproc2024069183 - 9 Oct 2024

Viewed by 253

Abstract

In this study, the efficacy of varying spoiler design parameters on regulating dead-end contaminant diffusion was investigated using particle image velocimetry (PIV) technology. The optimal spoiler design parameters were identified under low Reynolds number turbulence, including variables such as tilt angle, height, width, [...] Read more.

In this study, the efficacy of varying spoiler design parameters on regulating dead-end contaminant diffusion was investigated using particle image velocimetry (PIV) technology. The optimal spoiler design parameters were identified under low Reynolds number turbulence, including variables such as tilt angle, height, width, and installation position. The findings of this study present a novel approach for improving water quality in WDNs by installing spoilers in dead-ends while offering valuable insights and providing guidance for the design and optimization of these spoilers. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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4 pages, 401 KiB

Open AccessProceeding Paper

Analysis of Inequity in Rural Water Supply Schemes—A Case Study from Central India

by Varghese Kurian, Shankar Narasimhan and Sridharakumar Narasimhan

Eng. Proc. 2024, 69(1), 184; https://doi.org/10.3390/engproc2024069184 - 9 Oct 2024

Viewed by 257

Abstract

In water-scarce regions, it is common to design water networks for a continuous supply but operate them intermittently, resulting in a potentially inequitable supply. We analyze the case of a network in Central India designated to supply water to 107 villages from a [...] Read more.

In water-scarce regions, it is common to design water networks for a continuous supply but operate them intermittently, resulting in a potentially inequitable supply. We analyze the case of a network in Central India designated to supply water to 107 villages from a single source. Several villages received zero or negligible inflow due to a variety of reasons. We developed a model of the network using the limited data available from the network and performed a pressure-driven analysis of the system. The key reasons for inequity in the supply were identified to be the excess withdrawal by villages located near the source, and the presence of air locks caused by the unevenness of the terrain. We report the effectiveness of several mitigating strategies. It is revealed that no single solution fits all, as different scenarios require different solutions. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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5 pages, 3630 KiB

Open AccessProceeding Paper

Large-Scale Real-Time Hydraulic and Quality Model of Combined Sewer Network—Case Study in Helsinki, Finland

by Markus I. Sunela, Pedro Almeida, Hanna Riihinen and Hannes Björninen

Eng. Proc. 2024, 69(1), 185; https://doi.org/10.3390/engproc2024069185 - 10 Oct 2024

Viewed by 303

Abstract

A method for a real-time now- and forecasting hydraulic and quality simulation model for combined sewer networks, based on an enhanced version of the Storm Water Management Model (SWMM) simulator, with added support for storing the hot start file at any time during [...] Read more.

A method for a real-time now- and forecasting hydraulic and quality simulation model for combined sewer networks, based on an enhanced version of the Storm Water Management Model (SWMM) simulator, with added support for storing the hot start file at any time during the simulation, the rotational speed control of the pumps, multiple dry weather flows with unique patterns, and improvements for quality simulations over control devices is presented. The methodology is applied in the combined sewer network of Helsinki, Finland. The model includes all pipes and dry weather flows, including the pollutants, catchment hydrology, infiltration, snowpacks, and other climate aspects. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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4 pages, 476 KiB

Open AccessProceeding Paper

Full-Scale Water Supply System Pipe Burst Analysis Method and Application in Case Studies

by Markus I. Sunela, Janne Väyrynen and Lauri Rantala

Eng. Proc. 2024, 69(1), 186; https://doi.org/10.3390/engproc2024069186 - 10 Oct 2024

Viewed by 315

Abstract

This paper presents an EPANET pressure-dependent analysis-based method for analyzing bursts in every pipe in a water supply system (WSS) and applies the method to large Finnish WSSs. EPANET is enhanced with the per-junction required and minimum pressures, a flow- and pressure-controlled pump [...] Read more.

This paper presents an EPANET pressure-dependent analysis-based method for analyzing bursts in every pipe in a water supply system (WSS) and applies the method to large Finnish WSSs. EPANET is enhanced with the per-junction required and minimum pressures, a flow- and pressure-controlled pump battery component and a full control system model to accurately capture the dynamic behavior of the whole system, including the effect of control system parameters and settings. The results are combined with population and income data, and the correlations of the various physical and hydraulic parameters affecting the burst effects are analyzed. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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5 pages, 1518 KiB

Open AccessProceeding Paper

Using the Acoustic Velocity Vector to Assess the Condition of Buried Water Pipes

by Joanna Watts, Michael-David Johnson and Kirill Horoshenkov

Eng. Proc. 2024, 69(1), 187; https://doi.org/10.3390/engproc2024069187 - 9 Oct 2024

Viewed by 270

Abstract

Traditionally, acoustic methods for leak inspection are based on the measurement of the acceleration of the external pipe wall or of the acoustic pressure in the pipe. This work presents an alternative inspection methodology based on measuring the acoustic velocity vector in the [...] Read more.

Traditionally, acoustic methods for leak inspection are based on the measurement of the acceleration of the external pipe wall or of the acoustic pressure in the pipe. This work presents an alternative inspection methodology based on measuring the acoustic velocity vector in the fluid filling the pipe. Unlike the acoustic pressure, the acoustic quantity is very sensitive to the presence of a pipe wall defect. Such defects are important to detect before they develop into leaks, which can lead to the loss of water, environmental pollution and service disruption. A new sensor design is proposed to measure the acoustic velocity vector in a pipe. A model is presented to demonstrate the underpinning theory behind this new sensor technology. The results of this model are compared with experimental data based on measurements of the acoustic velocity in an exhumed section of ductile iron pipe. These sensors can be deployed on robots to autonomously monitor the deterioration of buried pipes to support proactive asset management at a low operational cost. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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4 pages, 746 KiB

Open AccessProceeding Paper

Multi-Model Demand Forecasting in Water Distribution Network Districts

by Enrico Creaco, Carlo Giudicianni and Manuel Herrera

Eng. Proc. 2024, 69(1), 188; https://doi.org/10.3390/engproc2024069188 - 14 Oct 2024

Viewed by 253

Abstract

A multi-model including three modelling elements is developed to solve the Battle of Water Demand Forecasting problem. The first two modelling elements working in parallel are a pattern-based algorithm and a Random Forest model. By varying the algorithm setting and predictors, 42 algorithms [...] Read more.

A multi-model including three modelling elements is developed to solve the Battle of Water Demand Forecasting problem. The first two modelling elements working in parallel are a pattern-based algorithm and a Random Forest model. By varying the algorithm setting and predictors, 42 algorithms are constructed and calibrated using demand and weather data in the previous weeks to the generic n-th week, when the objective is the prediction of the hourly demand pattern in the n + 1-th week. Then, a third modelling element is used, which consists of an optimizer aimed at combining the results yielded by the 42 algorithms by analyzing algorithm performance in the n-th week. The same algorithm combination is used to forecast demand at the n + 1-th week. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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5 pages, 642 KiB

Open AccessProceeding Paper

Optimal Location of Best Management Practices for Flood Mitigation in Urban Drainage Systems

by Enrico Creaco, Arianna Dada, Giovanna Grossi and Sara Todeschini

Eng. Proc. 2024, 69(1), 189; https://doi.org/10.3390/engproc2024069189 - 14 Oct 2024

Viewed by 223

Abstract

The present work presents a bi-objective optimization methodology, which is aimed at simultaneously minimizing the total installation costs of management systems as well as urban flooding, as a tool to be conveniently adopted as part of a decision support system to help identify [...] Read more.

The present work presents a bi-objective optimization methodology, which is aimed at simultaneously minimizing the total installation costs of management systems as well as urban flooding, as a tool to be conveniently adopted as part of a decision support system to help identify the optimal location of best management practices (BMPs). For each sub-catchment present in an urban drainage system, the decision variables include the rate of impervious areas to be used for BMP installation. The performance of the urban drainage system following optimal BMP installation is tested against climate change scenarios obtained from a real case study conducted in the industrial area of Brescia; the numerical model of this study can be obtained via the EPASWMM software. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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5 pages, 1006 KiB

Open AccessProceeding Paper

Identifying Hydraulic Conditions for Discolouration Material Accumulation

by Reinar Lokk, Joby Boxall and Stewart Husband

Eng. Proc. 2024, 69(1), 190; https://doi.org/10.3390/engproc2024069190 - 15 Oct 2024

Viewed by 272

Abstract

Understanding the interactions between hydraulic conditions and the accumulation of discolouration material in drinking water distribution systems is crucial to help identify risk locations and inform effective maintenance. With two accumulation processes now acknowledged and the known range in size and characteristics of [...] Read more.

Understanding the interactions between hydraulic conditions and the accumulation of discolouration material in drinking water distribution systems is crucial to help identify risk locations and inform effective maintenance. With two accumulation processes now acknowledged and the known range in size and characteristics of discolouration material, this is not a trivial challenge. A full-scale pipe loop system, adapted for precise flow control and with multiple turbidity monitors, was dosed with discolouration material collected from operational networks. By tracking changes in bulk water material loading, this study indicates that at above 1.25 L/s (0.25 m/s, Re 15,000, 0.213 N/m²), a change in accumulation behaviour occurs. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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5 pages, 790 KiB

Open AccessProceeding Paper

Monolithic and Decomposition Methods for Optimal Scheduling of Dynamically Adaptive Water Networks

by Bradley Jenks, Aly-Joy Ulusoy and Ivan Stoianov

Eng. Proc. 2024, 69(1), 191; https://doi.org/10.3390/engproc2024069191 - 14 Oct 2024

Viewed by 272

Abstract

This paper presents an optimal scheduling problem for coordinating pressure and self-cleaning operations in dynamically adaptive water networks. Our problem imposes a set of time-coupling constraints to manage pressure variations during the transition between operational modes. Solving this time-coupled, nonlinear optimization problem poses [...] Read more.

This paper presents an optimal scheduling problem for coordinating pressure and self-cleaning operations in dynamically adaptive water networks. Our problem imposes a set of time-coupling constraints to manage pressure variations during the transition between operational modes. Solving this time-coupled, nonlinear optimization problem poses challenges for off-the-shelf nonlinear solvers due to its high memory demands. We compare the performance of a decomposition method using the alternating direction method of multipliers (ADMM) with a gradient-based sequential convex programming (SCP) monolithic solver. Solution quality and computational efficiency are evaluated using a model of a large-scale network in the UK. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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5 pages, 874 KiB

Open AccessProceeding Paper

Simulation of a Case-Study Intermittent Water Distribution Network by Using the Storm Water Management Model

by Aurora Gullotta and Alberto Campisano

Eng. Proc. 2024, 69(1), 192; https://doi.org/10.3390/engproc2024069192 - 14 Oct 2024

Viewed by 254

Abstract

An EPA-SWMM model was used for the simulation of the intermittent water distribution system (WDS) of a small municipality in southern Italy. The model was compared with field data collected during an experimental campaign carried out in the intermittent WDS. The whole cycle [...] Read more.

An EPA-SWMM model was used for the simulation of the intermittent water distribution system (WDS) of a small municipality in southern Italy. The model was compared with field data collected during an experimental campaign carried out in the intermittent WDS. The whole cycle of operation of the WDS was simulated, including the filling, distribution and emptying phases of the intermittent network. The modelling also included water leakages and private tanks that are normally interposed between network pipes and end users. Comparison of model results and experimental observations concerned water levels at the reservoirs and pressures at specific nodes of the WDS during some days of the experiments. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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5 pages, 1521 KiB

Open AccessProceeding Paper

Raw Water Main Flow Conditioning to Manage Material Load and Treatment Capacity

by Stewart Husband, Neil Walkington-Mayo and Joby Boxall

Eng. Proc. 2024, 69(1), 193; https://doi.org/10.3390/engproc2024069193 - 15 Oct 2024

Viewed by 281

Abstract

A water treatment works in the UK endured elevated inlet turbidity and iron concentrations following increased demands in the raw water supply main, reducing its capacity by blocking filters that required costly extra cleaning. Adding flow and turbidity monitoring allowed novel raw water [...] Read more.

A water treatment works in the UK endured elevated inlet turbidity and iron concentrations following increased demands in the raw water supply main, reducing its capacity by blocking filters that required costly extra cleaning. Adding flow and turbidity monitoring allowed novel raw water main variable condition discolouration model (VCDM) simulations to track the accumulation and mobilisation behaviour, showing the full 18.7 km contributing material and risk returning in only 2 months, helping explain the multiple annual events. The utility is now applying operational efficient flow conditioning, developed here using the VCDM, to manage risks and capacity. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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5 pages, 626 KiB

Open AccessProceeding Paper

Operating Water Distribution Systems for Equitable Access to Clean Water

by Brent Vizanko, Tomer Shmaya, Sriman Pankaj Boindala, Avi Ostfeld and Emily Berglund

Eng. Proc. 2024, 69(1), 194; https://doi.org/10.3390/engproc2024069194 - 10 Oct 2024

Viewed by 369

Abstract

Water distribution systems (WDSs) are designed to deliver potable water across urban areas. Unpredicted changes in water demands and hydraulics can increase the residence time in pipes, leading to the growth of microbes and decreased water quality at some locations in a network. [...] Read more.

Water distribution systems (WDSs) are designed to deliver potable water across urban areas. Unpredicted changes in water demands and hydraulics can increase the residence time in pipes, leading to the growth of microbes and decreased water quality at some locations in a network. During the COVID-19 pandemic, large-scale reductions in demands, especially in industrial and commercial areas as individuals worked from home, led to hot-spots of increased water age. In response to reduced water quality, consumers may avoid using tap water for end uses including drinking, cooking, and cleaning. The lack of access to clean water can create high costs for some households due to the cost of buying bottled water. Inequitable access to safe, affordable water is explored in this research in the context of the COVID-19 pandemic through a coupled framework. This research extends an existing agent-based modeling (ABM) framework that simulated COVID-19 transmission, social distancing decision-making, reductions in water demands, and flows in a water distribution system. The ABM is extended in this work to simulate households that perceive water quality problems with tap water and choose to buy bottled water for cooking, cleaning, and hygienic purposes. Agents choose tap water avoidance behaviors based on water age, a surrogate for water quality. Equity is evaluated using the cost of water, both tap and bottled, as a percentage of income. An optimization approach is coupled with the ABM framework and applied to design operational strategies that improve equitable access to safe affordable water. A graph theory approach identifies valves that should be opened and closed to improve water quality at nodes and maximize equity. The results demonstrate an increase in water age due to social distancing behaviors, and water of high age is observed to be disproportionately located near industrial areas. Adjusted income demonstrates inequities in access to safe and affordable water. Operational strategies are developed to improve equity for a community through valve operations that improve the equitable delivery of safe water. This research develops an approach to assess equity of the quality of delivered water and can be used to facilitate WDS management that provides equitable access to safe water. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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4 pages, 1855 KiB

Open AccessProceeding Paper

Transient Flow Dynamics in Tesla Valve Configurations: Insights from Computational Fluid Dynamics Simulations

by Mohamad Zeidan, Davaasuren Yondonjamts, Márton Németh, Gopinathan R. Abhijith, Richard Wéber and Avi Ostfeld

Eng. Proc. 2024, 69(1), 195; https://doi.org/10.3390/engproc2024069195 - 12 Oct 2024

Viewed by 385

Abstract

This study investigates the transient flow dynamics and pressure interactions within Tesla valve configurations through comprehensive computational fluid dynamics (CFD) simulations. Previous observations indicated that Tesla valves effectively reduce the amplitude of pressure transients, prolonging their duration and distributing energy over an extended [...] Read more.

This study investigates the transient flow dynamics and pressure interactions within Tesla valve configurations through comprehensive computational fluid dynamics (CFD) simulations. Previous observations indicated that Tesla valves effectively reduce the amplitude of pressure transients, prolonging their duration and distributing energy over an extended timeframe. While suggesting a potential role for Tesla valves as pressure dampers during transient events, the specific mechanisms behind this behavior remain unexplored. The research focuses on elucidating the internal dynamics of Tesla valves during transient events, aiming to unravel the processes responsible for the observed attenuation in pressure transients. The study reveals the emergence of distinctive “pressure pockets” within Tesla valves, deviating from conventional uniform pressure fronts. These pockets manifest as discrete chambers with varying lengths and volumes, contributing to a non-uniform propagation of pressure throughout the system. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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4 pages, 743 KiB

Open AccessProceeding Paper

Inclusion of Water Age in Conjunctive Optimal Operation of Water and Power Grids

by Tomer Shmaya and Avi Ostfeld

Eng. Proc. 2024, 69(1), 196; https://doi.org/10.3390/engproc2024069196 - 15 Oct 2024

Viewed by 238

Abstract

Water distribution systems (WDSs) are critical infrastructure systems designed to safely supply water to consumers. As complex systems, they require constant operational decision-making, which is often the result of an optimization process. WDSs require power for pumping and the operation of water treatment [...] Read more.

Water distribution systems (WDSs) are critical infrastructure systems designed to safely supply water to consumers. As complex systems, they require constant operational decision-making, which is often the result of an optimization process. WDSs require power for pumping and the operation of water treatment facilities. Power is supplied through power grids (PGs)—essential infrastructure which must be strategically operated as well, under constraints. This work is focused on the effects of PG operation on water quality, which is a major operational challenge of WDSs. The inclusion of the PG as part of the WDS optimal operation problem has the potential of influencing flow directions in the WDS, which in turn affects water quality. In this work, a model for the optimal operation of water and power networks is constructed, including water age considerations. The model is applied to a simple case study, containing a small WDS connected to a small PG. The results demonstrate the effect of PG operation on water quality. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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4 pages, 646 KiB

Open AccessProceeding Paper

Examining the Effect of Small-Amplitude Transients on Bacterial Community Composition in Water Distribution Pipes

by Artur Sass Braga, Mariele de Souza Parra Agostinho, Benjamin Anderson, Yves Filion and Cristovão Vicente Scapulatempo Fernandes

Eng. Proc. 2024, 69(1), 197; https://doi.org/10.3390/engproc2024069197 - 18 Oct 2024

Viewed by 285

Abstract

This research explores the microbial ecology within drinking water distribution systems (DWDS). The aim of the paper was to examine the impact of small-amplitude transients on the bacterial composition in bulk water and biofilms. The findings highlight the dominance of Proteobacteria and the [...] Read more.

This research explores the microbial ecology within drinking water distribution systems (DWDS). The aim of the paper was to examine the impact of small-amplitude transients on the bacterial composition in bulk water and biofilms. The findings highlight the dominance of Proteobacteria and the significant transformation of microbial communities in response to changes in environmental conditions. The study underscores the complex interplay between operational strategies and microbial dynamics in DWDS and emphasizes the necessity for ongoing research to enhance water quality management amidst climate change challenges. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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5 pages, 883 KiB

Open AccessProceeding Paper

Examining the Effect of Small-Amplitude Transients on Biofilm Development in Water Distribution Pipes

by Mariele de Souza Parra Agostinho, Artur Sass Braga, Benjamin Anderson, Yves Filion and Cristovão Vicente Scapulatempo Fernandes

Eng. Proc. 2024, 69(1), 198; https://doi.org/10.3390/engproc2024069198 - 18 Oct 2024

Viewed by 262

Abstract

This research explores the influence of chronic, small-amplitude hydraulic transients on biofilm development within water distribution systems (WDSs). Utilizing a unique experimental setup, it contrasts the biofilm dynamics under steady and transient hydraulic conditions. Findings reveal biofilms developed by transient conditions notably enhance [...] Read more.

This research explores the influence of chronic, small-amplitude hydraulic transients on biofilm development within water distribution systems (WDSs). Utilizing a unique experimental setup, it contrasts the biofilm dynamics under steady and transient hydraulic conditions. Findings reveal biofilms developed by transient conditions notably enhance adhesion and resistance to flushing, challenging the conventional focus on steady-state hydraulic scenarios. The research underscores the importance of integrating transient hydraulic effects into water distribution system management and design, to improve water quality and system integrity. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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5 pages, 1033 KiB

Open AccessProceeding Paper

Hydraulic Transient Data Assimilation in Pipe Networks Using the Kalman Filter

by Jiawei Ye, Wei Zeng, Martin Lambert, Aaron Zecchin and Nhu Cuong Do

Eng. Proc. 2024, 69(1), 199; https://doi.org/10.3390/engproc2024069199 - 18 Oct 2024

Viewed by 340

Abstract

Hydraulic transient data assimilation in pipe networks plays a critical role in monitoring the network’s behaviours, thereby ensuring the efficiency and reliability of water supply systems. However, the existing Kalman filter-based methods integrated with traditional numerical models face a severe computational burden with [...] Read more.

Hydraulic transient data assimilation in pipe networks plays a critical role in monitoring the network’s behaviours, thereby ensuring the efficiency and reliability of water supply systems. However, the existing Kalman filter-based methods integrated with traditional numerical models face a severe computational burden with a significant number of state variables due to the need to discretise pipes into multiple pipe segments. This paper presents a novel Kalman filter approach that implements an efficient hydraulic transient model that requires fewer pipe segments and is particularly suited when the frequency of the transient fluctuation is low. As the number of state variables is reduced, a faster estimation of the system hydraulic states is enabled, as is an enhanced accuracy of transient predictions. The proposed method was tested in two pipe network simulations with user demands: a 7-pipe network and a 51-pipe network. The results indicate that the method provides accurate transient predictions and robust estimation of transient states in real time, and has high performance and efficiency for large pipe networks. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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5 pages, 952 KiB

Open AccessProceeding Paper

Design Storms for First Flush Modelling at Sewer Inlets

by Gianfranco Becciu, Anita Raimondi and Umberto Sanfilippo

Eng. Proc. 2024, 69(1), 200; https://doi.org/10.3390/engproc2024069200 - 21 Oct 2024

Viewed by 336

Abstract

First flush is one of the key phenomena in the dynamics of pollutants in urban drainage. It is affected by a number of factors, like the characteristics of urban surfaces and drainage systems, the rainfall patterns, the street sweeping frequency and efficiency, and [...] Read more.

First flush is one of the key phenomena in the dynamics of pollutants in urban drainage. It is affected by a number of factors, like the characteristics of urban surfaces and drainage systems, the rainfall patterns, the street sweeping frequency and efficiency, and the gully pot features. This paper discusses how a storm event can maximize pollution mass and concentration in first flush runoff. It turns out that the critical events derive from particular combinations of factors and not necessarily from the maximum values of rainfall depths or intensities. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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5 pages, 1144 KiB

Open AccessProceeding Paper

Machine Learning-Based Digital Twin for Water Distribution Network Anomaly Detection and Localization

by Prerna Pandey, Nikolaj T. Mücke, Shashi Jain, Parthasarathy Ramachandran, Sander M. Bohté and Cornelis W. Oosterlee

Eng. Proc. 2024, 69(1), 201; https://doi.org/10.3390/engproc2024069201 - 21 Oct 2024

Viewed by 564

Abstract

This paper presents the development of a Digital Twin (DTwin) to detect and localize the leaks in water distribution networks (WDNs), using single-stage and two-stage data-driven models. In the single-stage model, we test the anomalies in the dataset using Logistic Regression and Random [...] Read more.

This paper presents the development of a Digital Twin (DTwin) to detect and localize the leaks in water distribution networks (WDNs), using single-stage and two-stage data-driven models. In the single-stage model, we test the anomalies in the dataset using Logistic Regression and Random Forest. In the two-stage model, a linear regression model predicts pressure differences between sensor pairs in the first stage. Based on this, we compute the distribution of residuals. In the second stage, changes in the residual distribution are classified using Multinomial Logistic Regression and Random Forest models to compute possible leak locations’ posterior probabilities. We have tested these models on a real-time dataset. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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4 pages, 2098 KiB

Open AccessProceeding Paper

Contributions for Carbon-Neutrality in the Water Sector: From Theory to Practice

by Helena M. Ramos and Dídia Covas

Eng. Proc. 2024, 69(1), 202; https://doi.org/10.3390/engproc2024069202 - 22 Oct 2024

Viewed by 296

Abstract

This research aims to present relevant developments carried out in the domains of energy recovery and the associated digital technology in the water sector. These include the implementation of digital twins of a PRV and energy converters. Several performance tests have been carried [...] Read more.

This research aims to present relevant developments carried out in the domains of energy recovery and the associated digital technology in the water sector. These include the implementation of digital twins of a PRV and energy converters. Several performance tests have been carried out in pumps operating as turbines (PATs) when replacing pressure-reducing valves (PRVs) or coupled to them. Based on virtual prototype of turbines, the numerical modelling of a PRV and tested PATs, with radial and axial impellers, have been developed. On the other hand, Digital Twins (DTs) provide useful data collection/analysis tools for reproducing disruption scenarios for resilience assessment purposes and analyzing asset prognosis and the system efficiency to determine proactive management models. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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4 pages, 602 KiB

Open AccessProceeding Paper

Battle of Water Demand Forecasting: Integrating Machine Learning with a Heuristic Post-Process for Short-Term Prediction of Urban Water Demand

by Alexander Sinske, Altus de Klerk and Adrian van Heerden

Eng. Proc. 2024, 69(1), 203; https://doi.org/10.3390/engproc2024069203 - 22 Oct 2024

Viewed by 327

Abstract

The challenge in water demand forecasting within a Northeast Italy water distribution network (WDN) involves predicting demands across ten distinct District Metered Areas (DMAs) with varying characteristics and demand profiles. This is critical for optimizing system operation in the near future. The available [...] Read more.

The challenge in water demand forecasting within a Northeast Italy water distribution network (WDN) involves predicting demands across ten distinct District Metered Areas (DMAs) with varying characteristics and demand profiles. This is critical for optimizing system operation in the near future. The available data begins in January 2021, with unknown impacts of post-COVID socio-economic changes, like work-from-home policies. To address this, the team integrates heuristic and Machine Learning (ML) techniques to predict short-term demands and fill data gaps. A heuristic post-processing step, using weighted sums and historical trends, refines these predictions. This approach combines ML with traditional methods with a view to servicing developing nations. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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5 pages, 455 KiB

Open AccessProceeding Paper

Examining the Effect of Small-Amplitude Transients on the Shear Strength of Biofilms in Water Distribution Pipes

by Mariele de Souza Parra Agostinho, Artur Sass Braga, Benjamin Anderson, Yves Fillion and Cristovão Vicente Scapulatempo Fernandes

Eng. Proc. 2024, 69(1), 204; https://doi.org/10.3390/engproc2024069204 - 22 Oct 2024

Viewed by 286

Abstract

The dynamics of biofilm detachment from the pipe walls of drinking water distribution systems was investigated through experiments in a full-scale pipe loop laboratory system. Biofilms grown under steady-state and transitory flow rates were compared. Flow cytometry was used to quantify the microbial [...] Read more.

The dynamics of biofilm detachment from the pipe walls of drinking water distribution systems was investigated through experiments in a full-scale pipe loop laboratory system. Biofilms grown under steady-state and transitory flow rates were compared. Flow cytometry was used to quantify the microbial cells of the biofilms, and biofilm shear strength was evaluated based on their capacity to resist mobilization when subjected to elevated flushing flow rates. The results suggest that biofilms grown under transitory flow regimes may develop stronger adhesion strength to the pipe wall. This paper contributes to the enhanced understanding of biofilm behaviour in drinking water systems and its potential impacts on water quality. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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4 pages, 879 KiB

Open AccessProceeding Paper

Physics-Informed Machine Learning for Universal Surrogate Modelling of Water Quality Parameters in Water Distribution Networks

by Ivo Daniel, Gopinathan R. Abhijith, J. Nathan Kutz, Avi Ostfeld and Andrea Cominola

Eng. Proc. 2024, 69(1), 205; https://doi.org/10.3390/engproc2024069205 - 25 Oct 2024

Viewed by 503

Abstract

Modelling and assessing water quality parameters in water distribution networks is essential for providing safe drinking water to end users. While simulation-based modeling approaches rely on costly differentiation for numerical solvers, surrogate models using Artificial Neural Networks (ANNs) can predict solutions with minimal [...] Read more.

Modelling and assessing water quality parameters in water distribution networks is essential for providing safe drinking water to end users. While simulation-based modeling approaches rely on costly differentiation for numerical solvers, surrogate models using Artificial Neural Networks (ANNs) can predict solutions with minimal computational effort. In this work, we formulate the idea of a universal surrogate model for predicting water quality dynamics that, once trained, will apply to all water distribution networks. To this end, we adapt the idea of meta-parameterized ANNs to account for variable boundary and initial conditions. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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5 pages, 1557 KiB

Open AccessProceeding Paper

A Data-Driven Analysis for Understanding and Risk Estimation of Discolouration in Drinking Water Distribution Systems

by Grigorios Kyritsakas, Stewart Husband, Killian Gleeson, Katrina Flavell and Joby Boxall

Eng. Proc. 2024, 69(1), 206; https://doi.org/10.3390/engproc2024069206 - 11 Nov 2024

Viewed by 234

Abstract

This paper presents machine learning analysis to understand the factors impacting iron concentrations and discolouration customer contacts in drinking water distribution systems. Fourteen years of network sampling and additional data from a large UK utility were collated, analysed, and interpreted using self-organising maps [...] Read more.

This paper presents machine learning analysis to understand the factors impacting iron concentrations and discolouration customer contacts in drinking water distribution systems. Fourteen years of network sampling and additional data from a large UK utility were collated, analysed, and interpreted using self-organising maps (SOMs), which include complex network theory (CNT) centrality metrics for the first time, investigating how possible explanatory variables interact. The outputs are used to inform ensemble decision trees for risk estimation of iron exceedance and customer contacts for each of the utility’s DMAs, helping inform proactive maintenance. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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5 pages, 574 KiB

Open AccessProceeding Paper

iOLE—Human-Centered Software Design for Leakage Detection in Water Distribution Networks

by Ivo Daniel, David Steffelbauer, Ella Steins, Jonas Schorr, Sophie Persigehl, Enrique Campbell, Johannes Koslowski, Jens Kley-Holsteg, Bernd Lindemann and Andrea Cominola

Eng. Proc. 2024, 69(1), 207; https://doi.org/10.3390/engproc2024069207 - 20 Nov 2024

Viewed by 194

Abstract

Leakages in water distribution networks still pose major challenges to water utilities. Despite numerous technological advances, the adoption of digital leakage detection technology remains a slow process. Here, we present the project iOLE—intelligent Online LEakage detection, where we aim to increase the applicability [...] Read more.

Leakages in water distribution networks still pose major challenges to water utilities. Despite numerous technological advances, the adoption of digital leakage detection technology remains a slow process. Here, we present the project iOLE—intelligent Online LEakage detection, where we aim to increase the applicability of automated leak detection in practice through enhanced user experience and detection robustness. iOLE employs a human-centered design approach that involves the feedback of potential users during its development process to maximize subsequent user acceptance. To this end, we design a graphical user interface, combine model-based and data-driven leakage detection, and conduct a comprehensive robustness analysis. Full article

(This article belongs to the Proceedings of The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024))

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