Application of sharing genetic algorithm for optimization of groundwater management problems in Wadi El-Farigh, Egypt

Abstract

Management of groundwater resources is very important for regions where freshwater supply is naturally limited. Long-term planning of groundwater usage requires method-based new decision support tools. These tools must be able to predict the change in the groundwater storage with sufficient accuracy and must allow exploring management scenarios with respect to different criteria such as sustainability and cost. So, a multi-objective optimization algorithm is used for groundwater management problem. In this paper, a genetic algorithm (GA) with two additional techniques, Pareto optimality ranking and fitness sharing, was applied to simultaneously maximize the pumping rate and minimize pumping cost. The methodology proposed herein has more Pareto optimal solutions, however, it is desirable to find the ones scattered uniformly over the Pareto frontier to provide a variety of compromise solutions to the decision maker. A groundwater resources management model is performed through a combined simulation-optimization model. This model is called the multi-objective genetic algorithm (MOGA) for optimization which combines the MODFLOW and GA. MOGA model applied in Wadi El-Farigh, Egypt, to develop the maximum pumping rate and minimum operation cost as well as to predict the future changes in both pumping rate and pumping operation cost. Model makes a feasible solution in groundwater management. Finally a compromise solution is presented from a set of Pareto optimal solutions to help the decision maker.

Optimal well locations using genetic algorithm for Tushki Project, Western Desert, Egypt

“…The results showed that under the increasing of pumping rate by 25 %, the optimal pumping rate and drawdown ranged from 638 138 to 595 978 m 3 day −1 and from 4. that the optimal pumping rate and the corresponding drawdown range from 190 699 to 179 423 m 3 day −1 and 6.13 to 8.34 m respectively. Gad and Khalaf (2013) used MOGA model to develop the maximum pumping rate and minimum operation cost as well as to predict the future changes in both pumping rate and pumping operation cost in the Miocene aquifer of Wadi El-Farigh, West Delta, Egypt. They concluded that the compromise solution among the set of Pareto optimal solutions for the three proposed scenarios in MAIWF at year 2050 are optimal pumping of 576 130 m 3 day −1 with optimal cost of USD 533 332 for the first scenario, optimal pumping of 667 130 m 3 day −1…”

Multi-objective optimal model for sustainable management of groundwater resources in an arid and semiarid area using a coupled optimization-simulation modeling

“…), using analytic element models to simulate an aquifer under limited and special conditions (Gaur et al, 2011;Majumder and Eldho, 2016, and etc. ), use meta-models to communicate between simulation and optimization models (Rogers and Dowla, 1994;Karamouz et al, 2007;Tabari, 2015;Alizadeh et al, 2017), create or modify MODFLOW and MT3DMS codes (Wang and Zheng, 1994;GAD and Khalaf, 2013;Elci and Tamer Ayvaz, 2014;Sreekanth et al, 2015;Luo et al, 2016;Ayvaz, 2016;Ghaseminejad and Shourian, 2019;Norouzi Khatiri et al, 2020 , and etc. ).…”

Optimal Well Locations using Genetic Algorithm for Tushki Project, Western Desert, Egypt

“…Saafan et al, (2011) applied multi-objective genetic algorithm (MOGA) Code in El-Farafra depression, Egypt to study the maximum pumping rate and minimum operation cost. Gad and Khalaf, (2013) used MOGA model to develop the maximum pumping rate and minimum operation cost in the Miocene aquifer of Wadi El-Farigh, West Delta, Egypt.…”