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

Abstract

Abstract. Groundwater depletion is one of the most important problems threaten the national projects in Egypt. The optimal distribution of well locations and pumping rates mitigate this problem. In this paper, a trial to mitigate this problem in Tushki National Project, south western desert, Egypt was carried out via delineating the optimal well locations and optimal pumping rates. The methodology of combination between simulation and optimization techniques was applied. A linked simulation-optimization model for obtaining the optimum management of groundwater flow is used in this research. MODFLOW packages are used to simulate the groundwater flow system. This model is integrated with an optimization model OLGA (Optimal well Location using Genetic Algorithm technique) which is based on the genetic algorithm (GA). Two management cases were considered by running the model in Abu Simbel-Tushki area with adopted steady and transit calibrated parameters. The first case (fixed well location) is found that the optimum value of the objective function (maximum pumping rate). In the second case (flexible well location with the moving well option) locations of wells are to be decided by the OLGA model itself within a user defined region of the model grid until the optimal location is reached. Also, the prediction of the future changes in both head and flow were made in steady and transient states.

Groundwater well optimization to minimize contaminant movement from a surficial shallow aquifer to a lower water supply aquifer using stochastic simulation-optimization modeling techniques: Strategy formulation

“…Since evaluating each chromosome's fitness in genetic algorithm is inherently independent, each evaluation process is simulated simultaneously by distributing it to separate parallel processors. The genetic algorithm is used in groundwater literature to solve problems like well location and pumping rate optimization [12 , 13 , 26] , aquifer remediation [10 , 16 , 17 , 23] , and parameter estimation [15] .…”

“…Khalaf and Gad [12] use Visual MODFLOW as the simulation model and a genetic algorithm constructed with Fortran as the optimization program. Huang and Mayer [10] develop a simulation-optimization model to find the optimal solution by coupling a hypothetical MODFLOW model with the genetic algorithm optimization process.…”

Multi‐Objective Optimization of Managed Aquifer Recharge

“…Moharram et al () used MODFLOW with a multi‐objective variation of GA to minimize the operational costs of pumping and maximize the total pumping rates from the aquifer located beneath the El‐Farafra Oasis in Egypt. Khalaf and Gad () applied combination of MODFLOW and genetic algorithm to optimize locations of pumping wells and their pumping rates aiming in maximization of total pumping rates under permissible maximal head drawdown constrains in Tushki area in Egypt.…”