Cyclic storage approach for conjunctive operation of surface and groundwater systems (Case study: ZarrinehRoud catchment area)

Abstract

In this research, the problem of optimal conjunctive operation of surface and groundwater systems is investigated by proposing a cyclic storage approach. This problem is solved here using mathematical programming and some efficient Meta heuristic algorithms. For this purpose, the mathematical model of this system is defined and first solved by the nonlinear programming (NLP) method. In addition, the performance of the artificial bee colony (ABC) algorithm, genetic algorithm (GA), gravitational search algorithm (GSA) and, particle swarm optimization (PSO) algorithms are also studied to solve this problem. Here, two case studies, meaning a hypothetical benchmark system and conjunctive use of Buchan dam reservoir and Miandoab aquifer located in the catchment area of Urmia Lake (ZarrinehRoud catchment area) as a real problem, are considered to study the performance of proposed methods. In other words, for the hypothetical benchmark system, the results show that the optimal operating cost and related computational time are equal to 5.2428 Billion Rials and 5400 s, respectively, obtained by using the NLP method. In addition, in comparison with the result of the NLP method, the operation costs increased by 26.36%, 26.1%, 44.91% and, 21.28% using ABC, GA, GSA and, PSO algorithms, respectively. However, the computational time is extremely decreased in comparison with the related value of the NLP method using these algorithms for a particular case. In other words, for the real benchmark system, the results show that the optimal operating cost and related computational time are equal to 139.0145 Billion Rials and 259,200 s, respectively, obtained by using the NLP method. In addition, in comparison with the result of the NLP method, the operation costs increased by 43.74%, 32.32%, and 50.57% using ABC, GA and, PSO algorithms, respectively. However, by using this algorithm, the computational time is extremely decreased in comparison with the related value of the NLP method for a particular case. Furthermore, in both case studies, the water demands are fully stratified using the proposed methods. Therefore, the obtained results show the efficiency and effectivity of the proposed methods to solve this complex optimization problem considering a cyclic storage approach. © 2023, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.