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Urban Sewer System Management
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Urban Sewer System Management

A special issue of Water (ISSN 2073-4441). This special issue belongs to the section "Urban Water Management".

Deadline for manuscript submissions: closed (15 June 2023) | Viewed by 23264

Special Issue Editors

Dr. Keshab Sharma

E-Mail Website
Guest Editor
Australian Centre for Water and Environmental Biotechnology, The University of Queensland, Brisbane, Australia
Interests: integrated water system management; odour and corrosion control; process modelling; sewer systems; wastewater treatment
Special Issues, Collections and Topics in MDPI journals
Dr. Oriol Gutierrez

E-Mail Website
Guest Editor
Catalan Institute for Water Research (ICRA), Girona, Spain
Interests: in-sewer processes; odour and corrosion mitigation; micropollutants; integrated management of urban water system

Special Issue Information

Dear Colleagues,

Sewer systems are integral part of urban water systems as they collect and transport domestic and industrial wastewater from different sources for centralized treatment and disposal. They are traditionally built to safeguard public health. Sewer networks are one of the most critical urban infrastructures, as their construction, operation, and maintenance requires substantial investment. Water utilities across the globe are facing a number of serious challenges in relation to the management of sewers. These key challenges include inadequate hydraulic capacity leading to frequent overflows and flooding, uncontrolled sewer overflows polluting receiving water, sedimentation and sewer blockages, rapid deterioration of pipe material due to corrosion needing system rehabilitation, and odour issues. Sewer systems globally are under the threat of sulfide-induced odour and corrosion problems. The highly dynamic nature of these systems in terms of both flow and wastewater composition adds further to the above listed problems.

The management of sewers have been mostly a reactive response, mainly due to poor understanding of the causes of the operational problems and lack of proper tools for making long term predictions of sewer conditions and systematic dealing of the problems. Several technologies are available for mitigating some of the problems that sewer systems are facing, but these require further optimization. Continuous monitoring of sewer systems for the assessments of their conditions as well as their performance is an essential element of sewer management. Although new technologies are continuously emerging, understanding of their effectiveness and longevity in harsh sewer environment is limited.  As such, there are many unresolved research questions in relation to the methods, tools, and technology used in sewer management.

This Special Issue of Water accepts papers that aim to fill in these research gaps and provide knowledge and technology development for cost-effective management of wastewater collection system (sewers). This includes papers focusing on:

  • Emerging technologies in sewer monitoring;
  • Hydraulic modelling;
  • In-sewer processes and their impacts on sewer management;
  • Interactions with drinking water and wastewater treatment systems;
  • Realtime control;
  • Sewer assets management;
  • Sewer design and operational issues;
  • Sewer overflows;
  • Sewer process modelling;
  • Technologies for odour and corrosion control.

Dr. Keshab Sharma
Dr. Oriol Gutierrez
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Water is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • assets management
  • corrosion
  • emerging technologies
  • hydraulic modelling
  • odour
  • process modelling
  • realtime monitoring and control
  • sewer overflow
  • sewer processes

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Further information on MDPI's Special Issue polices can be found here.

Published Papers (5 papers)

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Research

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14 pages, 1580 KiB  
Article
Developing a Data Quality Evaluation Framework for Sewer Inspection Data
by Hossein Khaleghian and Yongwei Shan
Water 2023, 15(11), 2043; https://doi.org/10.3390/w15112043 - 27 May 2023
Cited by 3 | Viewed by 1694
Abstract
The increasing amount of data and the growing use of them in the information era have raised questions about the quality of data and its impact on the decision-making process. Currently, the importance of high-quality data is widely recognized by researchers and decision-makers. [...] Read more.
The increasing amount of data and the growing use of them in the information era have raised questions about the quality of data and its impact on the decision-making process. Currently, the importance of high-quality data is widely recognized by researchers and decision-makers. Sewer inspection data have been collected for over three decades, but the reliability of the data was questionable. It was estimated that between 25% and 50% of sewer inspection data is not usable due to data quality problems. In order to address reliability problems, a data quality evaluation framework is developed. Data quality evaluation is a multi-dimensional concept that includes both subjective perceptions and objective measurements. Five data quality metrics were defined to assess different quality dimensions of the sewer inspection data, including Accuracy, Consistency, Completeness, Uniqueness, and Validity. These data quality metrics were calculated for the collected sewer inspection data, and it was found that consistency and uniqueness are the major problems based on the current practices with sewer pipeline inspection. This paper contributes to the overall body of knowledge by providing a robust data quality evaluation framework for sewer system data for the first time, which will result in quality data for sewer asset management. Full article
(This article belongs to the Special Issue Urban Sewer System Management)
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17 pages, 4418 KiB  
Article
Urban Drainage: The Challenges and Failure Assessment Using AHP, Addis Ababa, Ethiopia
by Mengistu A. Jemberie, Assefa M. Melesse and Brook Abate
Water 2023, 15(5), 957; https://doi.org/10.3390/w15050957 - 1 Mar 2023
Cited by 6 | Viewed by 8774
Abstract
Urban drainage infrastructures are facing critical challenges due to a lack of integrated asset management, periodic maintenance, improper design, and construction methodologies. The objective of this study is to understand the urban drainage challenges and assess the failure causes and their impacts to [...] Read more.
Urban drainage infrastructures are facing critical challenges due to a lack of integrated asset management, periodic maintenance, improper design, and construction methodologies. The objective of this study is to understand the urban drainage challenges and assess the failure causes and their impacts to recommend possible mitigation measures. Drainage failure causes and impacts are analyzed using the analytical hierarchy process (AHP) qualitative multicriteria decision model after conducting technical group discussions, interviews, and technical field surveys. The assessment was performed by taking representative samples from both cross- and longitudinal drainage infrastructures. The AHP analysis results showed that approximately 35.5% and 28.6% of failure causes are debris and various solid wastes for cross- and longitudinal drainage structures with correlation coefficients of 0.93 and 0.95, respectively. The result showed that design and construction defects are the second major failure causes. The research results showed that urbanization has a direct relationship with major drainage failure causes, resulting from man-made debris and solid waste clogging. On the other hand, drainage failure caused by siltation, drifts, and vegetation is higher in newly developing semi-urban and agricultural areas. The number of barrels in cross-drainage structures also contribute significantly to cross-drainage failure by creating a flow barrier due to the intermediate columns. The drainage failure impact assessment result showed that both cross- and longitudinal drainage failures primarily impact road pavement following transport disruption and traffic accidents, accounting for 38.5%, 18%, and 16%, respectively. Our research recommended that the mitigation measures for drainage failure are proper asset management and maintenance, appropriate construction supervision, and awareness creation, with weights of 36.3%, 15.5%, and 15.3%, respectively. As a drainage problem mitigation measure, the longitudinal drainage analysis results showed that the provision of a combination of cross-fall slopes, gutter slopes, and local depressions at the inlets can contribute to an increase in the trapping efficiency of the drainage system by 50%, which can reduce surface flooding substantially. Full article
(This article belongs to the Special Issue Urban Sewer System Management)
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20 pages, 4751 KiB  
Article
Towards a Combined Physical and Social Evaluation of Climate Vulnerability in Coastal Urban Megacities
by Komali Kantamaneni, Qiong Li, Haotian Wu, Mingyu Zhu, Athanasia Apostolopoulou, Weijie Xu, Inji Kenawy, Lakshmi Priya Rajendran, Louis Rice, Carlos Jimenez-Bescos, Sigamani Panneer and Robert Ramesh Babu Pushparaj
Water 2023, 15(4), 712; https://doi.org/10.3390/w15040712 - 11 Feb 2023
Cited by 5 | Viewed by 3078
Abstract
Coastal urban megacities across Asia face significant risks from climate change, including coastal flooding, high temperatures, urban heat island impacts and air pollution. These hazards are associated with negative impacts on infrastructure, communities and the environment. To identify the current intensity of climate [...] Read more.
Coastal urban megacities across Asia face significant risks from climate change, including coastal flooding, high temperatures, urban heat island impacts and air pollution. These hazards are associated with negative impacts on infrastructure, communities and the environment. To identify the current intensity of climate change impacts in coastal urban megacities, an integrated evaluation method is needed. Firstly, the present study assesses the climate change impacts of Guangzhou, a Chinese coastal urban megacity, for both physical and social aspects. This study includes 60 years of time-series data for 1960–2020 to examine temperatures, precipitation, humidity and air pollution in Guangzhou city. At the same time, a survey was conducted between April and July 2022 in this megacity and collected the views of 336 people on climate change and its associated environmental impacts. Secondly, the Ganzhou city results are compared with existing data from similar nearby cities to evaluate the diverse climate change trends. Results show that during 1961-1990, the city received the most rainfall in May, reaching 283.6 mm. From 1990 to 2020, June recorded the highest rainfall of 356.6 mm and shows an increase of 73 mm during that period. The very severe monsoon season brought an increased risk of flooding. Results also revealed that the warmest month is July, and the coldest month is January, and both months showed increased temperatures of 0.60 ℃. Comparison results revealed that Guangzhou is not the only city which scored increased highest temperatures; other nearby cities including Heyuan, Shantou and Shaoguan also scored increased highest temperatures. The survey reveals that the majority of respondents (75%) perceived the increased frequency of extreme weather, including typhoons, heavy rainfall and multiple days of hot weather, such as higher temperatures and an increased number of hot days. In the responses to the questions related to the heat island effect, more than 80% of residents are aware of the existence of the heat island and its impacts. People believe that the primary causes of the urban heat island problem are industrial production and anthropogenic heat generated by the city. These results will be helpful to local and national policy and decision makers to revise and/or develop new strategies to improve the environment and quality of life in coastal megacities, particularly Ganzhou. Full article
(This article belongs to the Special Issue Urban Sewer System Management)
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21 pages, 3790 KiB  
Article
Application of Regression-Based Machine Learning Algorithms in Sewer Condition Assessment for Ålesund City, Norway
by Lam Van Nguyen and Razak Seidu
Water 2022, 14(24), 3993; https://doi.org/10.3390/w14243993 - 7 Dec 2022
Cited by 6 | Viewed by 2779
Abstract
Predicting the condition of sewer pipes plays a vital role in the formulation of predictive maintenance strategies to ensure the efficient renewal of sewer pipes. This study explores the potential application of ten machine learning (ML) algorithms to predict sewer pipe conditions in [...] Read more.
Predicting the condition of sewer pipes plays a vital role in the formulation of predictive maintenance strategies to ensure the efficient renewal of sewer pipes. This study explores the potential application of ten machine learning (ML) algorithms to predict sewer pipe conditions in Ålesund, Norway. Ten physical factors (age, diameter, depth, slope, length, pipe type, material, network type, pipe form, and connection type) and ten environmental factors (rainfall, geology, landslide area, population, land use, building area, groundwater, traffic volume, distance to road, and soil type) were used to develop the ML models. The filter, wrapper, and embedded methods were used to assess the significance of the input factors. A dataset consisting of 1159 inspected sewer pipes was used to construct the sewer condition models, and 290 remaining inspections were used to verify the models. The results showed that sewer material and age are the most significant factors, otherwise the network type is the least contributor affecting the sewer conditions in the study area. Among the considered ML models, the Extra Trees Regression (R2 = 0.90, MAE = 11.37, and RMSE = 40.75) outperformed the other ML models and it is recommended for predicting sewer conditions for the study area. The results of this study can support utilities and relevant agencies in planning predictive maintenance strategies for their sewer networks. Full article
(This article belongs to the Special Issue Urban Sewer System Management)
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Review

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21 pages, 769 KiB  
Review
Impacts of Extreme Rainfalls on Sewer Overflows and WSUD-Based Mitigation Strategies: A Review
by Nitin Muttil, Tasnim Nasrin and Ashok K. Sharma
Water 2023, 15(3), 429; https://doi.org/10.3390/w15030429 - 20 Jan 2023
Cited by 11 | Viewed by 5733
Abstract
Extreme rainfall events cause an increase in the flow into aging sewer networks, which can lead to Sanitary Sewer Overflows (SSOs). This literature review presents a complete assessment of the application of Water Sensitive Urban Design (WSUD) approaches as mitigation strategies for reducing [...] Read more.
Extreme rainfall events cause an increase in the flow into aging sewer networks, which can lead to Sanitary Sewer Overflows (SSOs). This literature review presents a complete assessment of the application of Water Sensitive Urban Design (WSUD) approaches as mitigation strategies for reducing rainfall-induced SSOs. The review highlights the various WSUD techniques identified in past studies for reducing sewer overflows. In these studies, it was identified that permeable pavements, green roofs, raingardens/bio-retention cells and rainwater tanks were the most popular WSUD strategies that have been extensively used in the past for the mitigation of sewer overflows. WSUD or “green” approaches also have enormous environmental, social and economic benefits when compared to the conventional “gray” approaches for sewer overflow mitigation. However, there have been limited studies conducted in the past that highlight and quantify the benefits of WSUD approaches for sewer overflow mitigation, particularly when such strategies are applied at a large scale (e.g., city scale). This review has identified the modelling software, SWMM, to be the most widely applied tool that has been used in the literature for WSUD modelling. It was also identified that with climate change-induced extreme rainfall events on the increase, WSUD-based “green” strategies alone may not be enough for the mitigation of sewer overflows. A suitable sewer overflow mitigation strategy could be green or a hybrid green-gray strategy, which would need to be identified based on a detailed context specific analysis. Full article
(This article belongs to the Special Issue Urban Sewer System Management)
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