Statistical models for the assessment of nitrate contamination in urban groundwater using GIS

Abstract

The purpose of this study is to develop statistical models for groundwater quality assessment in urban areas using Geographic Information Systems (GIS). To develop the models, the concentrations of nitrate (expressed as nitrogen, NO3-N), which are different according to the type of land use, well depth and distribution of rainfall, were analyzed in the Seoul (the capital of South Korea) area. Data such as land use, location of wells and groundwater quality data for nitrate contamination were collected and a database constructed within GIS. The distribution of NO3-N concentrations is not normal, and the results of the Mann-Whitney U-test analysis show the difference of NO3-N concentration by well depth and by distribution of rainfall. In both the shallow and deep wells, the radius of influence is 200 m in the dry season and 250 m in the rainy season, showing the tendency to increase in the rainy season. The results of correlation and regression analysis indicate that mixed residential and business areas and cropped field areas are likely to be the major contributor of increasing NO3-N concentration. Land uses are better correlated with NO3-N in deep wells than in shallow wells.