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Selecting Indicators and Optimizing Decision Rules for Long-Term Water Resources Planning

Lookup NU author(s): Dr Anna MurgatroydORCiD

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This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).


Abstract

Decision rules provide an intuitive framework for water resources planning. Having adopted a rule-based plan, decision makers can monitor critical variables to trigger timely adaptation actions when the variables pass their predetermined thresholds. However, establishing a strategy that is comprised of a set of decision rules raises methodological challenges: (i) to identify observable indicators that provide reliable information about current and future change, (ii) to choose suitable statistics to characterize nonstationary time series that are germane to system performance, and (iii) to optimize threshold levels that trigger interventions. We propose a methodology that addresses these methodological challenges whilst explicitly balancing expected risks of water shortages with the costs of intervention in the water supply system. The four-step framework uses a multiobjective evolutionary algorithm to search for and to identify the combinations of indicator-informed decision rules that govern if, when, and what supply options should be included in the water resource system. The rule-based strategies are dynamically tested against an extensive ensemble of future climate and demand scenarios to examine the trade-offs between strategy cost and level of service. The framework is applied to the London water system (England) using regional climate simulations to identify strategic rules for a 60-year planning period. The results demonstrate the utility of the framework, identifying observable indicators and decision thresholds that are used in optimal rule-based planning strategies. In key areas of the solution space, rule-based strategies reduce expected restriction costs on average by 13.1%, and as much as 24.1%, for a given intervention cost.


Publication metadata

Author(s): Murgatroyd A, Hall JW

Publication type: Article

Publication status: Published

Journal: Water Resources Research

Year: 2021

Volume: 57

Issue: 5

Print publication date: 01/05/2021

Online publication date: 15/04/2021

Acceptance date: 11/04/2021

Date deposited: 09/08/2024

ISSN (print): 0043-1397

ISSN (electronic): 1944-7973

Publisher: Wiley-Blackwell Publishing, Inc.

URL: https://doi.org/10.1029/2020WR028117

DOI: 10.1029/2020WR028117

Data Access Statement: The Weather@Home sequences can be downloaded from the Center for Environmental Data Analysis repository (https://catalogue.ceda.ac.uk/uuid/4eb66be638e04d759939a7af571f18ad). CEH Gridded rainfall estimates can be found in the CEH data repository (https://catalogue.ceh.ac.uk/documents/ee9ab43d-a4fe-4e73-afd5-cd4fc4c82556). The DECIPHeR flow series is available at https://doi.org/10.5523/bris.2pkv9oxgfzvts235zrui7xz00g. Monthly water demand profile has been published by Dobson and Mijic (2020) and accessed via https://zenodo.org/record/3764678#.Xs0JNmhKhPY. Demand projections at company level have been published by the Environment Agency (2019), accessed at https://data.gov.uk/dataset/fb38a40c-ebc1-4e6e-912c-bb47a76f6149/revised-draft-water-resources-management-plan-2019-supply-demand-data-at-company-level-2020-21-to-2044-45#licence-info.


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Funding

Funder referenceFunder name
1788712
Engineering and Physical Sciences Research Council
Environment Agency
Thames Water

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