Optimal management of coastal aquifers using artificial jellyfish search algorithm

In the current study, a simulation-optimization model is presented using a new metaheuristic optimization algorithm called artificial Jellyfish Search (JS) to develop sustainable saltwater intrusion optimal management strategies for coastal aquifers. The simulation model is based on the finite element method (FEM). The effectiveness of the proposed model is tested by application to the real aquifer system of Miami Beach aquifer, Spain with management decisions of maximizing the total economic benefit and the total pumping rate. The model is also applied to the case study of El-Arish Rafah aquifer, Egypt to maximize the total pumping rate. The results of both cases are compared to that obtained by using genetic algorithm (GA), probabilistic global search Lausanne (PGSL), shuffled frog leaping (SFL) and particle swarm optimization (PSO). The efficiency rate metric and statistical indices are used to assess the performance of the proposed model. For Miami Beach aquifer, an optimal benefit of 24.93 ($/d) was obtained and which is equivalent to that by PSO and SFLA but higher than that of GA and PGSL and with the highest pumping rate of 5544.62 (m(3)/s). The model also had the highest efficiency rates compared to PSO, PGSL and SFLA. For El-Arish Rafah aquifer, a maximum optimal pumping rate of 55,619.43 (m3/s) is determined. The results show that the model can be considered as an effective and efficient management tool.

Automated summary

In this study, a simulation-optimization model based on the artificial Jellyfish Search algorithm is developed for sustainable saltwater intrusion management in coastal aquifers. The model is tested using real aquifer systems and compared with other optimization algorithms, demonstrating its efficiency and effectiveness.