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Quartet trade-off for regional water resources allocation optimization with multiple water sources: A decentralized bi-level multi-objective model under hybrid uncertainty
Journal article   Peer reviewed

Quartet trade-off for regional water resources allocation optimization with multiple water sources: A decentralized bi-level multi-objective model under hybrid uncertainty

Yaru He, Yan Tu, Jun Liu, Hongwei Shi and Benjamin Lev
Journal of hydrology (Amsterdam), v 619, 129341
Apr 2023
DOI: https://doi.org/10.1016/j.jhydrol.2023.129341
Featured in Collection :   UN Sustainable Development Goals @ Drexel

Abstract

Bi-level multi-objective optimization Chaotic-particle swarm optimization Hybrid uncertainty Multiple water sources Regional water resources allocation
Multiple uncertainties from water resource allocation have posed new challenges to balanced regional development. On the one hand, in the context of global water shortage crisis, groundwater, as an important water supply module, is facing severe risk of shortage. On the other hand, the regional authorities need to coordinate the contradictory water demand brought by the heterogeneous water use objectives from multiple water use levels, and these demands are also subject to complex uncertainties. How to mitigate the risks posed by uncertainties, ensure regional water security and balance participants, is attracting the keen attention of decision-makers around the world. Therefore, this study establishes a decentralized bi-level multi-objective regional water resources allocation (RWRA) optimization model under hybrid uncertainty, aiming at an optimal quartet trade-off of equity, sustainability, equilibrium, and efficiency. To deal with the hybrid uncertainty in the model, water demand is set as a random fuzzy number, and the groundwater constraint is combined with fuzzy chance-constrained programming (FCCP). Then, the decentralized bi-level multi-objective model is solved by the bi-level interactive method based on the satisfactory solution incorporated with the chaotic-particle swarm optimization (CPSO) algorithm. The proposed model and solution approach are then applied to the Dongjiang River Basin in Guangdong Province of China to verify the validity and utility of the model. The results show that (1) the model can effectively meet the different objectives requirements of regional authority and sub-areas; (2) groundwater constraint parameters has a significant impact on the model results, especially the Gini coefficient decreases by 13.6% when groundwater is used as a water source supplement; (3) from single-level model to decentralized bi-level model, the satisfactory balance of the two levels increases from 0.1457 to 0.793, which indicates that the decentralized bi-level model makes the two levels more balanced than the single-level model. Based on the results, some management recommendations for participants are finally provided. •A decentralized bi-level multi-objective programming model for RWRA is established.•Quartet trade-off of equity, sustainability, equilibrium, efficiency is considered.•Groundwater constraint is combined with FCCP to reflect water supply uncertainty.•Random fuzzy variable is utilized to describe the uncertain water demand in RWRA.•A case study in the Dongjiang River of China is applied to verify the proposal.

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8 Record Views
25 citations in Web of Science
20 citations in Scopus

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UN Sustainable Development Goals (SDGs)

This publication has contributed to the advancement of the following goals:

#11 Sustainable Cities and Communities
#13 Climate Action
#6 Clean Water and Sanitation

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Collaboration types
Domestic collaboration
International collaboration
Web of Science research areas
Engineering, Civil
Geosciences, Multidisciplinary
Water Resources
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