Global threats such as climate change, population growth, and rapid urbanization pose a huge future challenge to water management, and, to ensure the ongoing reliability, resilience and ...sustainability of service provision, a paradigm shift is required. This paper presents an overarching framework that supports the development of strategies for reliable provision of services while explicitly addressing the need for greater resilience to emerging threats, leading to more sustainable solutions. The framework logically relates global threats, the water system (in its broadest sense), impacts on system performance, and social, economic, and environmental consequences. It identifies multiple opportunities for intervention, illustrating how mitigation, adaptation, coping, and learning each address different elements of the framework. This provides greater clarity to decision makers and will enable better informed choices to be made. The framework facilitates four types of analysis and evaluation to support the development of reliable, resilient, and sustainable solutions: “top‐down,” “bottom‐up,” “middle based,” and “circular” and provides a clear, visual representation of how/when each may be used. In particular, the potential benefits of a middle‐based analysis, which focuses on system failure modes and their impacts and enables the effects of unknown threats to be accounted for, are highlighted. The disparate themes of reliability, resilience and sustainability are also logically integrated and their relationships explored in terms of properties and performance. Although these latter two terms are often conflated in resilience and sustainability metrics, the argument is made in this work that the performance of a reliable, resilient, or sustainable system must be distinguished from the properties that enable this performance to be achieved.
Impact Statement
Water management faces major challenges over the coming decades, with existing social, ecological, and technical water subsystems subject to emerging global threats such as climate change, urbanization, and depletion of resources. Current methods may be able to deal with these threats individually; however, recent experiences have revealed serious problems, and, without new ideas and approaches, levels of service will be challenged significantly by future change. This research, therefore, provides a framework that addresses the need to provide safe (reliable) water management that is also resilient and sustainable in the face of emerging threats and highlights opportunities for intervention. In doing so, it aims to provide greater clarity to decision makers, allowing better informed choices to be made. It also connects the additional global challenges of climate change, energy, food production, agriculture, and health, all of which may be threats to water management and/ or consequences of water system failure.
Reducing energy consumption and maintenance costs of a pumping system is seen as an important but difficult multi-objective optimization problem. Many evolutionary algorithms, such as particle swarm ...optimization (PSO), multi-objective particle swarm optimization (MOPSO), and non-dominated sorting genetic algorithm II (NSGA-II) have been used. However, a lack of comparison between these approaches poses a challenge to the selection of optimization approach for stormwater drainage pumping stations. In this paper, a new framework for comparing multi-objective approaches is proposed. Two kinds of evolutionary approaches, single-objective optimization and multi-objective optimization, are considered. Three approaches representing these two types are selected for comparison, including PSO with linear weighted sum method (PSO-LWSM), MOPSO with technique for order preference by similarity to an ideal solution (MOPSO-TOPSIS), and NSGA-II with TOPSIS (NSGA-II-TOPSIS). Four optimization objectives based on the number of pump startups/shutoffs, working hours, energy consumption, and drainage capacity are considered, of which the first two are new ones quantified in terms of operational economy in this paper. Two comparison methods—TOPSIS and operational economy and drainage capacity (E&C)—are used. The framework is demonstrated and tested by a case in China. The average values of the TOPSIS comprehensive evaluation index of the three approaches are 0.021, 0.154, and 0.375, respectively, and for E&C are 0.785, 0.813, and 0.839, respectively. The results show that the PSO-LWSM has better optimization results. The results validate the efficiency of the framework. The proposed framework will help to find a better optimization approach for pumping systems to reduce energy consumption and maintenance costs.
Wastewater-based epidemiology (WBE) is a valuable tool for monitoring the circulation of COVID-19. However, while variations in population size are recognised as major sources of uncertainty, ...wastewater SARS-CoV-2 measurements are not routinely population-normalised. This paper aims to determine whether dynamic population normalisation significantly alters SARS-CoV-2 dynamics observed through wastewater monitoring, and whether it is beneficial or necessary to provide an understanding of COVID-19 epidemiology. Data from 394 sites in England are used, and normalisation is implemented based on ammoniacal nitrogen and orthophosphate concentrations. Raw and normalised wastewater SARS-CoV-2 metrics are evaluated at the site and spatially aggregated levels are compared against indicators of prevalence based on the Coronavirus Infection Survey and Test and Trace polymerase chain reaction test results. Normalisation is shown, on average, to have a limited impact on overall temporal trends. However, significant variability in the degree to which it affects local-level trends is observed. This is not evident from previous WBE studies focused on single sites and, critically, demonstrates that while the impact of normalisation on SARS-CoV-2 trends is small on average, this may not always be the case. When averaged across many sites, normalisation strengthens the correlation between wastewater SARS-CoV-2 data and prevalence indicators; however, confidence in the improvement is low.
Resilience has been increasingly pursued in the management of water distribution systems (WDSs) such that a system can adapt to and rapidly recover from potential failures in face of a deep uncertain ...and unpredictable future. Topology has been assumed to have a great impact on resilience of WDSs, and is the basis of many studies on assessing and building resilience. However, this fundamental assumption has not been justified and requires investigation. To address this, a novel framework for mapping between resilience performance and network topological attributes is proposed. It is applied to WDSs here but can be adaptable to other network systems. In the framework, resilience is comprehensively assessed using stress-strain tests which measure system performance on six metrics corresponding to system resistance, absorption and restoration capacities. Six key topological attributes of WDSs (connectivity, efficiency, centrality, diversity, robustness and modularity) are studied by mathematical abstraction of WDSs as graphs and measured by eight statistical metrics in graph theory. The interplay between resilience and topological attributes is revealed by the correlations between their corresponding metrics, based on 85 WDSs with different sizes and topological features. Further, network variants from a single WDS are generated to uncover the value of topological attribute metrics in guiding the extension/rehabilitation design of WDSs towards resilience. Results show that only certain aspects of resilience performance, i.e. spatial and temporal scales of failure impacts, are strongly influenced by some (not all) topological attributes, i.e. network connectivity, efficiency, modularity and centrality. Metrics for describing the topological attributes of WDSs need to be carefully selected; for example, clustering coefficient is found to be weakly correlated with resilience performance compared to other metrics of network connectivity (due to the grid-like structures of WDSs). Topological attribute metrics alone are not sufficient to guide the design of resilient WDSs and key details such as the location of water sources also need to be considered.
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•Key topological attributes for resilient water distribution systems are identified.•Time-related resilience metrics strongly correlate to some topological attributes.•Topological indicators alone are not sufficient for guiding system design.•Trade-offs can exist between different aspects of system resilience.•Network topology has different influence for risk and resilience management.
Reliability, risk and resilience are strongly related concepts and have been widely utilised in the context of water infrastructure performance analysis. However, there are many ways in which each ...measure can be formulated (depending on the reliability of what, risk to what from what, and resilience of what to what) and the relationships will differ depending on the formulations used. This research has developed a framework to explore the ways in which reliability, risk and resilience may be formulated, identifying possible components and knowledge required for calculation of each and formalising the conceptual relationships between specified and general resilience. This utilises the Safe & SuRe framework, which shows how threats to a water system can result in consequences for society, the economy and the environment, to enable the formulations to be derived in a logical manner and to ensure consistency in any comparisons. The framework is used to investigate the relationship between levels of reliability, risk and resilience provided by multiple operational control and design strategies for an urban wastewater system case study. The results highlight that, although reliability, risk and resilience values may exhibit correlations, designing for just one is insufficient: reliability, risk and resilience are complementary rather than interchangeable measures and one cannot be used as a substitute for another. Furthermore, it is shown that commonly used formulations address only a small fraction of the possibilities and a more comprehensive assessment of a system's response to threats is necessary to provide a comprehensive understanding of risk and resilience.
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•Framework developed to explore components of reliability, risk and resilience.•Shortcomings of commonly used formulations illustrated.•Reliability, risk and resilience-based design and operation of wastewater systems explored.•Lowest risk solutions do not necessarily provide the highest specified resilience.•Reliability, risk and resilience shown to be complementary measures.
To deal with the threat of urban flooding, it is necessary to assess the flood resilience of urban drainage systems at the planning and design stage. This study proposes a system resilience ...assessment methodology based on a ‘do-nothing’ benchmark. In this new benchmark, the number of flooded nodes used in computation of mean flood duration in the system is that observed under a ‘do-nothing’ scenario (i.e. with no intervention), irrespective of the scenario under evaluation. This methodology is demonstrated using a case study in Chizhou city, China, a simple stormwater drainage network with seven subcatchments. Schemes of interventions (with distributed storage tanks) that aim to mitigate flooding are then produced by zero-one integer programming and schemes sampling. The results show that the proposed method can compute the mean flood duration and system resilience reasonably and helps identify effective intervention schemes. Compared with traditional methods, this resilience assessment method based on a ‘do-nothing’ scenario can correctly indicate the change in trend of system resilience provided by different schemes, and aids understanding of different interventions to improve system resilience to urban flooding. This study also provides a new way to test different interventions and to explore which provide the greatest improvement in system resilience.
•A system resilience assessment methodology based on a ‘do-nothing’ benchmark is presented.•The number of flooded nodes in the system is determined on a ‘do-nothing’ basis.•Schemes of interventions are produced by zero-one integer programming and schemes sampling.•The method will help understanding of different interventions and improve system resilience.
Storage is important for flood mitigation and non-point source pollution control. However, to seek a cost-effective design scheme for storage tanks is very complex. This paper presents a two-stage ...optimization framework to find an optimal scheme for storage tanks using storm water management model (SWMM). The objectives are to minimize flooding, total suspended solids (TSS) load and storage cost. The framework includes two modules: (i) the analytical module, which evaluates and ranks the flooding nodes with the analytic hierarchy process (AHP) using two indicators (flood depth and flood duration), and then obtains the preliminary scheme by calculating two efficiency indicators (flood reduction efficiency and TSS reduction efficiency); (ii) the iteration module, which obtains an optimal scheme using a generalized pattern search (GPS) method based on the preliminary scheme generated by the analytical module. The proposed approach was applied to a catchment in CZ city, China, to test its capability in choosing design alternatives. Different rainfall scenarios are considered to test its robustness. The results demonstrate that the optimal framework is feasible, and the optimization is fast based on the preliminary scheme. The optimized scheme is better than the preliminary scheme for reducing runoff and pollutant loads under a given storage cost. The multi-objective optimization framework presented in this paper may be useful in finding the best scheme of storage tanks or low impact development (LID) controls.
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•Scientific methods for choosing reasonable candidates before optimization needed.•Framework of two-stage optimization to find an optimal scheme is presented.•Objectives are to minimize flooding, total suspended solids (TSS) load and storage cost.•Preliminary scheme was based on AHP and flood and TSS reduction efficiency.•Generalized pattern search (GPS) method was used for optimization.
In recent years, urban flooding has been a frequent occurrence, and seriously threatens the safety of lives and properties. Rational placement of distributed storage tanks is one of the effective ...ways to solve urban flooding, addressing stormwater management and rainwater reuse. However, existing optimization methods (such as genetic algorithm (GA) and other evolutionary algorithms) for determining the placement of storage tanks typically have a high computational burden; as such, they can be very time-consuming, and are not conducive to energy saving, carbon reduction and work efficiency improvements. In this study, a new approach and framework based on a resilience characteristic metric (RCM) and reduced modelling requirements are proposed. In this framework, the resilience characteristic metric, which is based on the linear superposition principle of system resilience metadata, is introduced, and a small number of simulations based on a coupling of MATLAB with SWMM are used to obtain the final placement scheme of storage tanks. The framework is demonstrated and verified with two cases in Beijing and Chizhou, China, and compared with a GA. The GA requires 2000 simulations for two cases (considering the placement of 2 and 6 tanks respectively), while the proposed method needs 44 simulations for the Beijing case and 89 simulations for the Chizhou case. The results show that the proposed approach is feasible and effective, and cannot only obtain a relative better placement scheme, but also considerably reduce computational time and energy consumption. It significantly improves the efficiency of determining the placement scheme of storage tanks. This method provides a new approach for the determining better storage tank placement schemes, and is useful for informing device placement in sustainable drainage systems.
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•A new methodology based on a resilience characteristic metric and reduced modelling is presented.•Top storage tank placement schemes are preselected using a resilience characteristic metric.•Modelling requirements for final scheme selection are reduced.•The framework provides new perspectives to develop more effective intervention schemes.
Evaluating and enhancing resilience in water infrastructure is a crucial step towards more sustainable urban water management. As a prerequisite to enhancing resilience, a detailed understanding is ...required of the inherent resilience of the underlying system. Differing from traditional risk analysis, here we propose a global resilience analysis (GRA) approach that shifts the objective from analysing multiple and unknown threats to analysing the more identifiable and measurable system responses to extreme conditions, i.e. potential failure modes. GRA aims to evaluate a system's resilience to a possible failure mode regardless of the causal threat(s) (known or unknown, external or internal). The method is applied to test the resilience of four water distribution systems (WDSs) with various features to three typical failure modes (pipe failure, excess demand, and substance intrusion). The study reveals GRA provides an overview of a water system's resilience to various failure modes. For each failure mode, it identifies the range of corresponding failure impacts and reveals extreme scenarios (e.g. the complete loss of water supply with only 5% pipe failure, or still meeting 80% of demand despite over 70% of pipes failing). GRA also reveals that increased resilience to one failure mode may decrease resilience to another and increasing system capacity may delay the system's recovery in some situations. It is also shown that selecting an appropriate level of detail for hydraulic models is of great importance in resilience analysis. The method can be used as a comprehensive diagnostic framework to evaluate a range of interventions for improving system resilience in future studies.
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•A method is developed to measure water systems' resilience to various failure modes.•The method identifies the range of failure impacts and reveals critical scenarios.•Increased resilience to one failure mode may decrease resilience to another.•Increasing capacity may not always improve resilience and may delay system recover.•The same degree of failure can result in very different level of failure impacts.
•New method to provide performance-based quantification of general resilience.•Effects of unknown threats addressed using a middle-state based approach.•The key to enhancing general resilience of ...urban wastewater systems is identified.•Important responses not captured by specified resilience to individual system failures.•Improvement in specified resilience does not guarantee improvement in general resilience.
General resilience addresses the resilience of a water system to any threat including unknowns, in contrast to specified resilience to individual identified threats. However, quantification of general resilience is challenging and previous assessments have typically been qualitative or based on system properties that are assumed to be indicative of resilient performance. Here we present a General Resilience Assessment Methodology (GRAM), which uses a middle-state based approach to decompose general resilience into contributing components to provide a quantitative and performance-based resilience assessment. GRAM enables the accounting of the effects of any threat if all modes of system failure are identifiable. It is applied to an integrated urban wastewater system where five interventions are explored. The results obtained show that whilst substantial improvements in specified resilience are achieved, increasing the general resilience of the system is challenging. However, general resilience analysis enables identification of system failure modes to which level of service is least resilient and highlights key opportunities for intervention development. GRAM is beneficial as it can inform the development of interventions to increase the resilience of a system to unknowns such as unforeseeable natural hazards in a quantifiable manner.
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