Handling uncertainty in optimal design of reservoir water quality monitoring systems

作     者：Pourshahabi, Shokoufeh Rakhshandehroo, Gholamreza Talebbeydokhti, Nasser Nikoo, Mohammad Reza Masoumi, Fariborz 

作者机构：Shiraz Univ Dept Civil & Environm Engn Shiraz Iran Shiraz Univ Environm Res & Sustainable Dev Ctr Shiraz Iran Univ Mohaghegh Ardabili Dept Civil Engn Ardebil Iran 

出 版 物：《ENVIRONMENTAL POLLUTION》 (环境污染)

年 卷 期：2020年第266卷第Part2期

页      面：115211-115211页

核心收录：

学科分类：0830[工学-环境科学与工程（可授工学、理学、农学学位）] 08[工学] 

基　　金：Shiraz University 

主　　题：Reservoir monitoring system Uncertainty Many-objective optimization model Information theory Nonlinear interval number programming 

摘      要：In the present paper, a scenario-based many-objective optimization model is developed for the spatio-temporal optimal design of reservoir water quality monitoring systems considering uncertainties. The proposed methodology is based on the concept of nonlinear interval number programming and information theory, while handling uncertainties of temperature, reservoir inflow, and inflow constituent concentration. A reference-point-based non-dominated sorting genetic algorithm (NSGA-III) is used to deal with the many-objective optimization problem. The proposed model is developed for the Karkheh reservoir system in Iran as a real-world problem. The results show excellent performance of the optimized water quality sampling locations instead of all potential ones in providing adequate information about the reservoir water quality status. The presented uncertainty-based model leads to a 55.73% reduction in the radius of the uncertain interval caused by different scenarios. Handling uncertainties in a spatio-temporal many-objective optimization problem is the main contribution of this study, yielding a reliable and robust design of a reservoir monitoring system that is less sensitive to various scenarios. (C) 2020 Elsevier Ltd. All rights reserved.