4.7 Article

Simulation-based multi-objective optimization framework for sustainable management of coastal aquifers in semi-arid regions

Journal

JOURNAL OF ENVIRONMENTAL MANAGEMENT
Volume 338, Issue -, Pages -

Publisher

ACADEMIC PRESS LTD- ELSEVIER SCIENCE LTD
DOI: 10.1016/j.jenvman.2023.117785

Keywords

Multi -objective optimization; Seawater intrusion; Pumping scheme; Groundwater management; Sustainable development; Gini coefficient

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Groundwater is a strategic water supply source in arid and semi-arid coastal regions, but growing demand and scarce water sources may lead to pressure on this resource and degrade water quality. A sustainable management model is developed to address these concerns, considering groundwater quality, economic efficiency, and social inclusion. The model is solved using simulation-based optimization and three evolutionary algorithms, with NSGA-II performing the best in terms of solution quality.
Groundwater is a strategic source of water supply, especially in arid and semi-arid coastal regions. Growing demand, along with scarce water sources, may impose intense pressure on this precious resource. This pressure will degrade water quality for future use and cause social inequality, despite supplying current needs. A novel sustainable management model for water allocation is developed to address these interconnected concerns in coastal aquifers. Three aspects of sustainable development are considered: groundwater quality with total dissolved solids (TDS) indicator for the environmental part, gross value added from water for the economic efficiency, and the Gini coefficient for social inclusion and equity. The problem is solved with a simulation-based multi-objective optimization framework using a numerical variable-density simulation code and three approved evolutionary algorithms, NSGA-II, NRGA, and MOPSO. The obtained solutions are integrated to enhance the solutions' quality by using each algorithm's strengths and dominated members' elimination. In addition, the optimization algorithms are compared. The results showed that NSGA-II is the best in terms of solutions quality, with the least number of total dominated members (20.43%) and a 95% success rate of obtained Pareto front. NRGA was supreme in finding extreme solutions, the least computational time, and diversity, with an 11.6% higher diversity value than the second competitive NSGA-II. MOPSO was the best in spacing quality indicator, followed by NSGA-II, showing their great arrangement and evenness in obtained solution space. MOPSO has the propensity for premature convergence and needs more stringent stopping criteria. The method is applied to a hypothetical aquifer. Still, the obtained Pareto fronts are determined to assist decision-makers in real-world coastal sustainable management problems by illustrating existing patterns among different objectives.

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