Optimization of DRASIC Model for assessment of groundwater vulnerability to nitrate pollution in Kashan Aquifer using statistical methods and sensitivity analysis

In this study, the optimized DRASTIC model parameters and land use layer (LU) were used to assess specific vulnerability in Kashan aquifer using statistical methods. Information layers were prepared, rated (deterministic and fuzzy-statistical), weighted (original and statistical) and combined (by Index-Overlay method) in GIS environment. For optimization of DRASTIC model, nonlinear regression for fuzzy-statistical rating (scaling) and Pearson correlation coefficients between nitrate concentrations and scaling parameters of DRASTIC model and sensitivity analysis (removal and single-parameter) were performed to determine and modify weighted parameters. As a result, RASIC-LU model with statistical rating and weighting, single-parameter sensitivity analysis, determined the best selection model based on correlation coefficient = 61.1%, P-Value= 0.001 and with parameters of net recharge, aquifer media, soil media, impact of vadose zone, hydraulic conductivity and land use with weight values of 2.50, 4.63, 4.15, 3.03, 1.96 and 2.00 respectively. According to this model, western and southern parts of the aquifer has a high and very high pollution risk due to high net recharge, pollutant land use and coarse-grain material in the impact of vadose zone, soil and aquifer media. In addition, sensitivity analysis based on mean squares error (MSE) indicated that this model is more sensitive to removal and increase of parameters weight of land use, soil media, impact of vadose zone, aquifer media, net recharge and hydraulic conductivity, and shows a decreasing ternd, respectivily.