Design of the Optimal Groundwater Quality Monitoring Well Network Using MODFLOW and MT3D Models

A properly monitoring well network can provide quantity and quality data needed to make informed decision making about the state of the environment. The selection of the optimum number of monitoring wells and their spatial distribution is a major challenge for the hydrogeologist. On the other hand, improper distribution of monitoring wells or an insufficient number of them does not properly represent the state of the environment. In this study, the current monitoring network in the study area was evaluated according to the simulation results of MODFLOW and MT3D models. Then, the monitoring network was designed based on the wells in the area with the optimization method developed in this study. The optimization model consists of two objective functions to maximize the Nash Sutcliffe coefficient and to minimize the costs simultaneously, which was defined as one target function by applying the weighting factor W. Genetic algorithm was used to solve the optimization model. The results showed that the finding of the optimal value depends on the value of the weight coefficient (W). Therefore, the best value of W is selected according to an acceptable trade-off between cost and spatial distribution of wells in the area. To choose the best solution, PBIAS, RMSE, and regression coefficients were used in which their values were acceptable in this study. Also, the higher the average optimal TDS values than the average observed TDS values indicated that the optimal network could provide groundwater quality data for more polluted areas. The method presented in this study for other pollutants should be evaluated and validated.