Improving the Resilience of Postdisaster Water Distribution Systems Using Dynamic Optimization Framework
Publication: Journal of Water Resources Planning and Management
Volume 146, Issue 2
Abstract
Improving the resilience of water distribution systems (WDSs) to handle natural disasters (e.g., earthquakes) is a critical step toward sustainable urban water management. This requires the water utility to be able to respond quickly to such disaster events, and in an organized manner, to prioritize the use of available resources to restore service rapidly while minimizing the negative impacts. Many methods have been developed to evaluate the WDS resilience, but few efforts are made so far to improve the resilience of a postdisaster WDS through identifying optimal sequencing of recovery actions. To address this gap, the authors propose a new dynamic optimization framework in this study in which the resilience of a postdisaster WDS is evaluated using six different metrics. A tailored genetic algorithm is developed to solve the complex optimization problem driven by these metrics. The proposed framework is demonstrated using a real-world WDS with 6,064 pipes. Results obtained show that the proposed framework successfully identifies near-optimal sequencing of recovery actions for this complex WDS. The gained insights, conditional on the specific attributes of the case study, include the following: (1) the near-optimal sequencing of a recovery strategy heavily depends on the damage properties of the WDS; (2) replacements of damaged elements tend to be scheduled at the intermediate-late stages of the recovery process due to their long operation time; and (3) interventions to damaged pipe elements near critical facilities (e.g., hospitals) should not be necessarily the first priority to recover due to complex hydraulic interactions within the WDS.
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Data Availability Statement
All data and models used during the study appear in the published article, and the codes generated during the study are available from the corresponding author by request.
Acknowledgments
This work is funded by the National Science and Technology Major Project for Water Pollution Control and Treatment (2017ZX07201004); the Excellent Youth Natural Science Foundation of Zhejiang Province (LR19E080003); the Funds for International Cooperation and Exchange of the National Natural Science Foundation of China (No. 51761145022); and The National Natural Science Foundation of China (No. 51708491).
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Information & Authors
Information
Published In
Journal of Water Resources Planning and Management
Volume 146 • Issue 2 • February 2020
Copyright
©2019 American Society of Civil Engineers.
History
Received: Mar 10, 2019
Accepted: Jul 24, 2019
Published online: Dec 4, 2019
Published in print: Feb 1, 2020
Discussion open until: May 4, 2020
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