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A special issue of Water (ISSN 2073-4441). This special issue belongs to the section "Water Resources Management, Policy and Governance".

Deadline for manuscript submissions: closed (30 April 2019) | Viewed by 85984

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Special Issue Editors

Prof. Dr. Guangtao Fu

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Guest Editor

Centre for Water Systems, University of Exeter, North Park Road, Exeter EX4 4QF, UK
Interests: artificial intelligence; water system analysis; flood management; system resilience analysis
Special Issues, Collections and Topics in MDPI journals

Dr. Monica Rivas Casado

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Guest Editor

School of Water, Energy and Environment, Cranfield University, College Road, Cranfield, Bedfordshire MK430AL, UK
Interests: surface water flooding; standardised monitoring approaches; systems engineering; disruptive technologies; climate change; extreme events
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Dr. Fanlin Meng

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Guest Editor

College of Engineering, Mathematics and Physical Sciences, Harrison Building, Streatham Campus, University of Exeter, North Park Road, Exeter EX4 4QF, UK
Interests: modelling and risk and resilience management of urban water systems; optimisation; water policy
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Prof. Dr. Roy Kalawsky

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Guest Editor

Wolfson School of Mechanical, Electric and Manufacturing Engineering, Loughborough University, Loughborough, UK
Interests: MBSE; digital thread; digital-twins; digital transformation; systems engineering
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Special Issue Information

Dear Colleagues,

Flooding has been increasingly recognized as a global threat due to the extent and magnitude of damage it poses around the world each year. Flooding, which can occur from fluvial, pluvial, coastal and groundwater sources, causes significant economic, social and environmental consequences, and the costs and disruption to communities, businesses and economies are expected to increase as a result of urbanization, economic growth and climate change. For example, flooding is the greatest threat posed by climate change in the UK, with 3.6 million people at risk by the 2050s according to the first UK climate change risk assessment report published in 2012.

To reduce flood losses, we need to understand both current and future risks, develop cost-effective intervention strategies, and increase the resilience of local communities and critical infrastructure to flood events. This requires innovative approaches, advanced computer models and tools to assess flood risk and resilience. In particular, there is a need to understand how resilience can be effectively built into flood defense systems and interlinked critical infrastructure systems in the flood management process. This Special Issue will provide a platform for researchers and engineers to share and discuss state-of-the-art scientific knowledge and best practices in flood management.

This Special Issue aims to address key challenges towards a more flood resilient future, encompassing not only both flood risk and resilience, but also their intersections. It will cover a full suite of flood issues, including, but not limited to, system monitoring and early warning, flood modelling and assessment, structural and non-structural measures, policies and financial instruments, social dynamics and communication by which flood management knowledge within communities is learned and shared.

Prof. Guangtao Fu
Dr. Monica Rivas Casado
Dr. Fanlin Meng
Prof. Roy Kalawsky
Guest Editors

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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.

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Keywords

Adaptation strategy
cascade effect
community vulnerability
environmental sustainability
flood modelling
flood monitoring
flood insurance
mitigation strategy
resilience analysis
risk assessment

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Published Papers (12 papers)

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Editorial

Jump to: Research

5 pages, 197 KiB

Open AccessEditorial

Towards Integrated Flood Risk and Resilience Management

by Guangtao Fu, Fanlin Meng, Mónica Rivas Casado and Roy S. Kalawsky

Water 2020, 12(6), 1789; https://doi.org/10.3390/w12061789 - 23 Jun 2020

Cited by 17 | Viewed by 4254

Abstract

Flood resilience is an emerging concept for tackling extreme weathers and minimizing the associated adverse impacts. There is a significant knowledge gap in the study of resilience concepts, assessment frameworks and measures, and management strategies. This editorial introduces the latest advances in flood risk and resilience management, which are published in 11 papers in the Special Issue. A synthesis of these papers is provided in the following themes: hazard and risk analysis, flood behaviour analysis, assessment frameworks and metrics, and intervention strategies. The contributions are discussed in the broader context of the field of flood risk and resilience management and future research directions are identified for sustainable flood management. Full article

(This article belongs to the Special Issue Flood Risk and Resilience)

Research

Jump to: Editorial

22 pages, 1982 KiB

Open AccessEditor’s ChoiceArticle

Guidelines for the Use of Unmanned Aerial Systems in Flood Emergency Response

by Gloria Salmoral, Monica Rivas Casado, Manoranjan Muthusamy, David Butler, Prathyush P. Menon and Paul Leinster

Water 2020, 12(2), 521; https://doi.org/10.3390/w12020521 - 13 Feb 2020

Cited by 39 | Viewed by 8733

Abstract

There is increasing interest in using Unmanned Aircraft Systems (UAS) in flood risk management activities including in response to flood events. However, there is little evidence that they are used in a structured and strategic manner to best effect. An effective response to flooding is essential if lives are to be saved and suffering alleviated. This study evaluates how UAS can be used in the preparation for and response to flood emergencies and develops guidelines for their deployment before, during and after a flood event. A comprehensive literature review and interviews, with people with practical experience of flood risk management, compared the current organizational and operational structures for flood emergency response in both England and India, and developed a deployment analysis matrix of existing UAS applications. An online survey was carried out in England to assess how the technology could be further developed to meet flood emergency response needs. The deployment analysis matrix has the potential to be translated into an Indian context and other countries. Those organizations responsible for overseeing flood risk management activities including the response to flooding events will have to keep abreast of the rapid technological advances in UAS if they are to be used to best effect. Full article

(This article belongs to the Special Issue Flood Risk and Resilience)

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18 pages, 3427 KiB

Open AccessArticle

Intelligent Storage Location Allocation with Multiple Objectives for Flood Control Materials

by Wei Wang, Jing Yang, Li Huang, David Proverbs and Jianbin Wei

Water 2019, 11(8), 1537; https://doi.org/10.3390/w11081537 - 25 Jul 2019

Cited by 13 | Viewed by 5508

Abstract

Intelligent storage is an important element of intelligent logistics and a key development trend in modern warehousing and logistics. Based on the characteristics of flood control materials and their intelligent storage, this study established a flood control material storage location allocation model reflecting the multiple objectives of retrieval efficiency and shelf stability and used a weighting method to transform a multi-objective optimization problem into a single-objective optimization problem. We then used the facilities and equipment planning and storage location allocation in the intelligent storage area for provincial flood control materials at the Zhenjiang warehouse of the Jiangsu water conservancy and flood control material reserve center as a case study. Empirical analysis was performed and used the genetic algorithm and Matrix Laboratory (MATLAB) software to optimize the storage location allocation of provincial flood prevention supplies at this warehouse, and it achieved effective results. Full article

(This article belongs to the Special Issue Flood Risk and Resilience)

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9 pages, 1281 KiB

Open AccessCommunication

Achieving Urban Flood Resilience in an Uncertain Future

by Richard Fenner, Emily O’Donnell, Sangaralingam Ahilan, David Dawson, Leon Kapetas, Vladimir Krivtsov, Sikhululekile Ncube and Kim Vercruysse

Water 2019, 11(5), 1082; https://doi.org/10.3390/w11051082 - 24 May 2019

Cited by 51 | Viewed by 8895

Abstract

Preliminary results of the UK Urban Flood Resilience research consortium are presented and discussed, with the work being conducted against a background of future uncertainties with respect to changing climate and increasing urbanization. Adopting a whole systems approach, key themes include developing adaptive approaches for flexible engineering design of coupled grey and blue-green flood management assets; exploiting the resource potential of urban stormwater through rainwater harvesting, urban metabolism modelling and interoperability; and investigating the interactions between planners, developers, engineers and communities at multiple scales in managing flood risk. The work is producing new modelling tools and an extensive evidence base to support the case for multifunctional infrastructure that delivers multiple, environmental, societal and economic benefits, while enhancing urban flood resilience by bringing stormwater management and green infrastructure together. Full article

(This article belongs to the Special Issue Flood Risk and Resilience)

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16 pages, 6335 KiB

Open AccessArticle

Use of Artificial Intelligence to Improve Resilience and Preparedness Against Adverse Flood Events

by Sara Saravi, Roy Kalawsky, Demetrios Joannou, Monica Rivas Casado, Guangtao Fu and Fanlin Meng

Water 2019, 11(5), 973; https://doi.org/10.3390/w11050973 - 9 May 2019

Cited by 67 | Viewed by 10036

Abstract

The main focus of this paper is the novel use of Artificial Intelligence (AI) in natural disaster, more specifically flooding, to improve flood resilience and preparedness. Different types of flood have varying consequences and are followed by a specific pattern. For example, a flash flood can be a result of snow or ice melt and can occur in specific geographic places and certain season. The motivation behind this research has been raised from the Building Resilience into Risk Management (BRIM) project, looking at resilience in water systems. This research uses the application of the state-of-the-art techniques i.e., AI, more specifically Machin Learning (ML) approaches on big data, collected from previous flood events to learn from the past to extract patterns and information and understand flood behaviours in order to improve resilience, prevent damage, and save lives. In this paper, various ML models have been developed and evaluated for classifying floods, i.e., flash flood, lakeshore flood, etc. using current information i.e., weather forecast in different locations. The analytical results show that the Random Forest technique provides the highest accuracy of classification, followed by J48 decision tree and Lazy methods. The classification results can lead to better decision-making on what measures can be taken for prevention and preparedness and thus improve flood resilience. Full article

(This article belongs to the Special Issue Flood Risk and Resilience)

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19 pages, 9679 KiB

Open AccessArticle

A Conceptual Time-Varying Flood Resilience Index for Urban Areas: Munich City

by Kai-Feng Chen and Jorge Leandro

Water 2019, 11(4), 830; https://doi.org/10.3390/w11040830 - 19 Apr 2019

Cited by 65 | Viewed by 8200

Abstract

In response to the increased frequency and severity of urban flooding events, flood management strategies are moving away from flood proofing towards flood resilience. The term ‘flood resilience’ has been applied with different definitions. In this paper, it is referred to as the capacity to withstand adverse effects following flooding events and the ability to quickly recover to the original system performance before the event. This paper introduces a novel time-varying Flood Resilience Index (FRI) to quantify the resilience level of households. The introduced FRI includes: (a) Physical indicators from inundation modelling for considering the adverse effects during flooding events, and (b) social and economic indicators for estimating the recovery capacity of the district in returning to the original performance level. The district of Maxvorstadt in Munich city is used for demonstrating the FRI. The time-varying FRI provides a novel insight into indicator-based quantification methods of flood resilience for households in urban areas. It enables a timeline visualization of how a system responds during and after a flooding event. Full article

(This article belongs to the Special Issue Flood Risk and Resilience)

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24 pages, 4430 KiB

Open AccessArticle

From Multi-Risk Evaluation to Resilience Planning: The Case of Central Chilean Coastal Cities

by Pilar Barría, María Luisa Cruzat, Rodrigo Cienfuegos, Jorge Gironás, Cristián Escauriaza, Carlos Bonilla, Roberto Moris, Christian Ledezma, Maricarmen Guerra, Raimundo Rodríguez and Alma Torres

Water 2019, 11(3), 572; https://doi.org/10.3390/w11030572 - 19 Mar 2019

Cited by 18 | Viewed by 5691

Abstract

Multi-hazard evaluations are fundamental inputs for disaster risk management plans and the implementation of resilient urban environments, adapted to extreme natural events. Risk assessments from natural hazards have been typically restricted to the analysis of single hazards or focused on the vulnerability of specific targets, which might result in an underestimation of the risk level. This study presents a practical and effective methodology applied to two Chilean coastal cities to characterize risk in data-poor regions, which integrates multi-hazard and multi-vulnerability analyses through physically-based models and easily accessible data. A matrix approach was used to cross the degree of exposure to floods, landslides, tsunamis, and earthquakes hazards, and two dimensions of vulnerability (physical, socio-economical). This information is used to provide the guidelines to lead the development of resilience thinking and disaster risk management in Chile years after the major and destructive 2010 Mw8.8 earthquake. Full article

(This article belongs to the Special Issue Flood Risk and Resilience)

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18 pages, 6052 KiB

Open AccessArticle

A Model-Based Engineering Methodology and Architecture for Resilience in Systems-of-Systems: A Case of Water Supply Resilience to Flooding

by Demetrios Joannou, Roy Kalawsky, Sara Saravi, Monica Rivas Casado, Guangtao Fu and Fanlin Meng

Water 2019, 11(3), 496; https://doi.org/10.3390/w11030496 - 8 Mar 2019

Cited by 21 | Viewed by 6547

Abstract

There is a clear and evident requirement for a conscious effort to be made towards a resilient water system-of-systems (SoS) within the UK, in terms of both supply and flooding. The impact of flooding goes beyond the immediately obvious socio-aspects of disruption, cascading and affecting a wide range of connected systems. The issues caused by flooding need to be treated in a fashion which adopts an SoS approach to evaluate the risks associated with interconnected systems and to assess resilience against flooding from various perspectives. Changes in climate result in deviations in frequency and intensity of precipitation; variations in annual patterns make planning and management for resilience more challenging. This article presents a verified model-based system engineering methodology for decision-makers in the water sector to holistically, and systematically implement resilience within the water context, specifically focusing on effects of flooding on water supply. A novel resilience viewpoint has been created which is solely focused on the resilience aspects of architecture that is presented within this paper. Systems architecture modelling forms the basis of the methodology and includes an innovative resilience viewpoint to help evaluate current SoS resilience, and to design for future resilient states. Architecting for resilience, and subsequently simulating designs, is seen as the solution to successfully ensuring system performance does not suffer, and systems continue to function at the desired levels of operability. The case study presented within this paper demonstrates the application of the SoS resilience methodology on water supply networks in times of flooding, highlighting how such a methodology can be used for approaching resilience in the water sector from an SoS perspective. The methodology highlights where resilience improvements are necessary and also provides a process where architecture solutions can be proposed and tested. Full article

(This article belongs to the Special Issue Flood Risk and Resilience)

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15 pages, 39360 KiB

Open AccessArticle

Impact of Urban Growth and Changes in Land Use on River Flood Hazard in Villahermosa, Tabasco (Mexico)

by Omar S. Areu-Rangel, Luis Cea, Rosanna Bonasia and Victor J. Espinosa-Echavarria

Water 2019, 11(2), 304; https://doi.org/10.3390/w11020304 - 12 Feb 2019

Cited by 50 | Viewed by 6346

Abstract

The city of Villahermosa, a logistical center in the State of Tabasco’s economy, is affected by recurrent river floods. In this study, we analyzed the impact of two factors that are the most probable causes of this increase in flood hazard: changes in land use in the hydrological catchments upstream of the city, and the uncontrolled urbanization of the floodplains adjacent to the main river channels. Flood discharges for different return periods were evaluated, considering land uses of the catchments, both as they were in 1992 and as they are today. These flood discharges were then used in a 2D shallow water model to estimate the increase of water depths in the city from 1992 to the present day. To evaluate the influence of urban expansion on inundation levels, three future urbanization scenarios were proposed on the basis of the urban growth rate forecast for 2050. Results confirm that the change in land use in the hydrological catchments is the main factor that explains the increase in inundation events observed over recent years. This study also provides useful insights for future city planning that might help to minimize the flood impact on Villahermosa. Full article

(This article belongs to the Special Issue Flood Risk and Resilience)

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17 pages, 1086 KiB

Open AccessArticle

Analysis of the Public Flood Risk Perception in a Flood-Prone City: The Case of Jingdezhen City in China

by Zhiqiang Wang, Huimin Wang, Jing Huang, Jinle Kang and Dawei Han

Water 2018, 10(11), 1577; https://doi.org/10.3390/w10111577 - 4 Nov 2018

Cited by 58 | Viewed by 8186

Abstract

Understanding and improving public flood risk perception is conducive to the implementation of effective flood risk management and disaster reduction policies. In the flood-prone city of Jingdezhen, flood disaster is one of the most destructive natural hazards to impact the society and economy. However, few studies have been attempted to focus on public flood risk perception in the small and medium-size city in China, like Jingdezhen. Therefore, the purpose of this study was to investigate the public flood risk perception in four districts of Jingdezhen and examine the related influencing factors. A questionnaire survey of 719 randomly sampled respondents was conducted in 16 subdistricts of Jingdezhen. Analysis of variance was conducted to identify the correlations between the impact factors and public flood risk perception. Then, the flood risk perception differences between different groups under the same impact factor were compared. The results indicated that the socio-demographic characteristics of the respondents (except occupation), flood experience, flood knowledge education, flood protection responsibility, and trust in government were strongly correlated with flood risk perception. The findings will help decision makers to develop effective flood risk communication strategies and flood risk reduction policies. Full article

(This article belongs to the Special Issue Flood Risk and Resilience)

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21 pages, 1185 KiB

Open AccessArticle

Automated Floodway Determination Using Particle Swarm Optimization

by Huidae Cho, Tien M. Yee and Joonghyeok Heo

Water 2018, 10(10), 1420; https://doi.org/10.3390/w10101420 - 10 Oct 2018

Cited by 2 | Viewed by 5691

Abstract

The floodway plays an important role in flood modeling. In the United States, the Federal Emergency Management Agency requires the floodway to be determined using an approved computer program for developed communities. It is a local government’s interest to minimize the floodway area because encroachment areas may be permitted for human activities. However, manual determination of the floodway can be time-consuming and subjective depending on the modeler’s knowledge and judgments, and may not necessarily produce a small floodway especially when there are many cross sections because of their correlation. Very little work has been done in terms of floodway optimization. In this study, we propose an optimization method for minimizing the floodway area using the Isolated-Speciation-based Particle Swarm Optimization algorithm and the Hydrologic Engineering Center’s River Analysis System (HEC-RAS). This method optimizes the floodway by defining an objective function that considers the floodway area and hydraulic requirements, and automating operations of HEC-RAS. We used a floodway model provided by HEC-RAS and compared the proposed, manual, and default HEC-RAS methods. The proposed method consistently improved the objective function value by 1–40%. We believe that this method can provide an automated tool for optimizing the floodway model using HEC-RAS. Full article

(This article belongs to the Special Issue Flood Risk and Resilience)

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13 pages, 2361 KiB

Open AccessArticle

Nonstationary Flood Frequency Analysis Using Univariate and Bivariate Time-Varying Models Based on GAMLSS

by Ting Zhang, Yixuan Wang, Bing Wang, Senming Tan and Ping Feng

Water 2018, 10(7), 819; https://doi.org/10.3390/w10070819 - 21 Jun 2018

Cited by 51 | Viewed by 5218

Abstract

With the changing environment, a number of researches have revealed that the assumption of stationarity of flood sequences is questionable. In this paper, we established univariate and bivariate models to investigate nonstationary flood frequency with distribution parameters changing over time. Flood peak Q and one-day flood volume W₁ of the Wangkuai Reservoir catchment were used as basic data. In the univariate model, the log-normal distribution performed best and tended to describe the nonstationarity in both flood peak and volume sequences reasonably well. In the bivariate model, the optimal log-normal distributions were taken as marginal distributions, and copula functions were addressed to construct the dependence structure of Q and W₁. The results showed that the Gumbel-Hougaard copula offered the best joint distribution. The most likely events had an undulating behavior similar to the univariate models, and the combination values of flood peak and volume under the same OR-joint and AND-joint exceedance probability both displayed a decreasing trend. Before 1970, the most likely combination values considering the variation of distribution parameters over time were larger than fixed parameters (stationary), while it became the opposite after 1980. The results highlight the necessity of nonstationary flood frequency analysis. Full article

(This article belongs to the Special Issue Flood Risk and Resilience)

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