Emergency water supply decision-making of transboundary river basin considering government–public perceived satisfaction

Author:

Wang Weiwei1,Zhou Haiwei123,Guo Lidan123

Affiliation:

1. Business School, Hohai University, Nanjing, China

2. International River Research Centre, Hohai University, Nanjing, China

3. Jiangsu Provincial Collaborative Innovation Center of World Water Valley and Water Ecological Civilization, NanJing, China

Abstract

The emergency supply of transboundary water resources is a prominent problem affecting the social and economic development of basin countries. However, current water supply decisions on transboundary water resources may ignore the psychological perception of multi-stakeholders, and the evolution of emergencies increases the uncertainty of decision making. Both factors would lead to the low acceptance of water-related decisions. Utility satisfaction, perceived losses, and quantity satisfaction were selected in this paper to identify the perceived satisfaction of upstream governments, downstream governments, and the public, respectively, over multiple decision-making stages. A modeling framework combining prospect theory and the multi-stage multi-objective programming methodology was then developed to measure the perceived satisfaction of different stakeholders in a watershed under emergency. A two-stage NSGA-II and TOPSIS based approach was adopted to find the optimal compromise solution to solve the model. The framework was applied in the Lancang–Mekong River basin to provide suggestions to decision makers. Upstream decision makers must choose a moderate proportional fairness degree when making emergency decisions to maximize the perceived satisfaction of all stakeholders. Meanwhile, the perceived loss of downstream countries with low water demand should be considered first in the formulation of emergency water supply plans. Furthermore, although water supply from upstream countries can improve perceived water quantity satisfaction of downstream publics, additional actions must still be taken to change the traditional concepts of the public.

Publisher

IOS Press

Subject

Artificial Intelligence,General Engineering,Statistics and Probability

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