Assessment and validation of groundwater vulnerability to nitrate based on a modified DRASTIC model: a case study in Jilin City of northeast China.

The assessment of groundwater vulnerability to pollution has become a useful tool for groundwater pollution prevention and control. Following the theory of overlay index method and with the aid of GIS technique and a statistical method, this study employed a modified DRASTIC model to assess the groundwater vulnerability to nitrate in Jilin City of northeast China. In order to reduce the subjectivity of the overlay index method, the model was optimized by rebuilding the index system, adjusting the rating scale of each index, reassigning the index weights and comparing grading methods for groundwater vulnerability to nitrate. The criteria for these optimizations were the correlation coefficient of each index with the nitrate concentration in groundwater. Net recharge (R), soil type (S), impact of vadose zone (I), groundwater velocity (V) and land use type (L) were picked up to compose the index system. And then the accuracy of vulnerability mapping was discussed by a group of integrated indicators, including the corresponding relationship between the extreme nitrate concentration and the vulnerability classes, F statistic and class difference between the groundwater vulnerability classification and concentration classification of NO(3)-N. The optimized model graded by geometrical interval method improved the correlation between vulnerability index and nitrate concentration to the order of 0.6698 which was 0.4098 higher than that by the DRASTIC model. By level difference calculation, the correct vulnerability regions accounted for 64.45% of the study area. Lastly, sensitivity analyses indicated that the soil media and groundwater velocity were the most critical factors affecting groundwater vulnerability to nitrate. In short, RSIVL model was suitable to assess the groundwater vulnerability to nitrate in the study area with readily available hydrogeological and hydrochemical data. Hence, the mapping of groundwater vulnerability to nitrate can be applied for sensible groundwater resource management and land use planning.