Abstract
Optimizing the design and operation of an Urban Water System (UWS) faces significant challenges over its lifespan to account for the uncertainties of important stressors that arise from population growth rates, climate change factors, or shifting demand patterns. The analysis of a UWS’s performance across interdependent subsystems benefits from a multi-model approach where different designs are tested against a variety of metrics and in different times scales for each subsystem. In this work, we present a stress-testing framework for UWSs that assesses the system’s resilience, i.e., the degree to which a UWS continues to perform under progressively increasing disturbance (deviation from normal operating conditions). The framework is underpinned by a modeling chain that covers the entire water cycle, in a source-to-tap manner, coupling a water resources management model, a hydraulic water distribution model, and a water demand generation model. An additional stochastic simulation module enables the representation and modeling of uncertainty throughout the water cycle. We demonstrate the framework by “stress-testing” a synthetic UWS case study with an ensemble of scenarios whose parameters are stochastically changing within the UWS simulation timeframe and quantify the uncertainty in the estimation of the system’s resilience.
Highlights
We proposed and demonstrated an uncertainty-aware source-to-tap simulation framework that employs a modeling chain that can capture the complex behavior of interdependent subsystems in Urban Water System (UWS)
The stress-testing framework is applicable and transferable to real-world cases, being flexible to account for any type of scenario developed, in collaboration with stakeholders in any of the interdependent subsystems that comprise a UWS
The same approach can be applied to shorter periods, to estimate resilience in scenarios dealing with medium-term uncertainty, e.g., during economic crises, pandemics, droughts, etc. to test system configuration changes or management decisions against ensembles of rapidly changing parameters and variables
Summary
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. Stochastic computational methods can be used to generate valid topologies of UWS subsystems and test their designs (such as, for example the approach adopted by Zhang et al [25] assessing combined sewer systems’ resilience) To undertake such an analysis at the level of whole UWSs, several different simulation models are required, with different data needs, computational complexity, spatial and temporal scale, as well as modeler skills and experience required. We provide a remedy to the above challenges by developing and demonstrating a source-to-tap simulation and stress-testing framework for UWSs. We propose a standardized and transferable methodology, which is able to assess the overall system’s resilience under long-term uncertainty and stochasticity, aiming to support water utilities to improve evidence-based decision making for long-term infrastructure planning
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