Two-objective design of groundwater-level monitoring network using NSGA-II in Eshtehard plain

Groundwater monitoring plays a significant role in groundwater management to control aquifer behavior. Thus, a groundwater monitoring network is required to control spatial and temporal fluctuations of groundwater characteristics. This study describes a new optimization method to design an optimum groundwater-level monitoring network and was implemented on Eshtehard aquifer. Database of the study was provided by kriging interpolation. Optimization of groundwater monitoring network was implemented by Non-Dominated Sorting Genetic Algorithm II (NSGA-II) with two objective functions of minimizing the root mean square error (RMSE) and minimizing the number of network wells which representing the cost of constructing, maintenance service and collecting data. Inverse Distance Weighting (IDW) was used to compute the groundwater-level in simulation part of optimization. The result of the study is a Pareto front showing the number of wells and corresponding RMSE which would be a guideline for groundwater monitoring network design. By selecting the required accuracy of the monitoring network data, the number of observation wells and their locations in the study area would be demonstrated.