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Administrative and market-based allocation mechanism for regional water resources planning
Journal article   Peer reviewed

Administrative and market-based allocation mechanism for regional water resources planning

Yan Tu, Xiaoyang Zhou, Jun Gang, Merrill Liechty, Jiuping Xu and Benjamin Lev
Resources, conservation and recycling, v 95, pp 156-173
Feb 2015
DOI: https://doi.org/10.1016/j.resconrec.2014.12.011
Featured in Collection :   UN Sustainable Development Goals @ Drexel

Abstract

Allocation of regional water resources Interactive programming Multi-objective bi-level optimization Particle swarm optimization Uncertainty Water rights
•An administrative and market-based optimization method is presented for solving a regional water resources allocation problem.•A multi-objective bi-level programming model is proposed.•Multiple uncertainties are considered.•A bi-level interactive method based on satisfactory solution with global–local neighbor adaptive particle swarm optimization (GLN-aPSO) is designed.•The practicality and efficiency of the model is verified through an analysis of a real-life example. The aim of this paper is to present an administrative and market-based optimization method for solving a problem of regional water resources allocation by considering a hierarchical structure under multiple uncertainties. To accomplish this, a multi-objective bi-level programming model is developed based on the water right distribution in a river basin. In this model, the stream flow (i.e., water supply) and water demand are considered as a fuzzy random variable and a random fuzzy variable, respectively. The regional authority, the leader in the hierarchy, seeks to maximize the total benefit to society while simultaneously minimizing pollution emissions. The sub-areas, the followers in the hierarchy, seek to maximize their own economic benefits. To deal with the inherent uncertainty, a transformation of variables into fuzzy variables is done, and through the expected value operation, the fuzzy variables are subsequently transformed into determined ones. For solving the complex non-linear bi-level programming model, a bi-level interactive method based on satisfactory solution with global–local–neighbor adaptive particle swarm optimization (GLN-aPSO) is designed as a combined solution method. A case study is presented to demonstrate the applicability and efficiency of this method. The interactive solutions associated with different minimal satisfactory degrees of the two objectives in the upper level have been generated. They can help the regional authority and the sub-areas to identify desired water allocation schemes according to their preferences and practical conditions, as well as facilitate in-depth analyses of tradeoffs between the objectives in the two levels. Finally, to verify that it is reasonable to use bi-level programming the results are compared with those of using single level programming.

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61 citations in Web of Science
68 citations in Scopus

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UN Sustainable Development Goals (SDGs)

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

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

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Collaboration types
Domestic collaboration
International collaboration
Web of Science research areas
Engineering, Environmental
Environmental Sciences
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