Application of a weights-of-evidence method and GIS to regional groundwater productivity potential mapping

Abstract

The aim of this study is to analyze the relationship among groundwater productivity data including specific capacity (SPC) and transmissivity (T) as well as its related hydrogeological factors in a bedrock aquifer, and subsequently, to produce the regional groundwater productivity potential (GPP) map for the area around Pohang City, Korea using a geographic information system (GIS) and a weights-of-evidence (WOE) model. All of the related factors, including topography, lineament, geology, forest, and soil data were collected and input into a spatial database. In addition, SPC and T data were collected from 83 and 81 well locations, respectively. Four dependent variables including SPC values of ≥6.25 m3/d/m (Case 1) and T values of ≥3.79 m2/d (Case 3) corresponding to a yield (Y) of ≥500 m3/d, and SPC values of ≥3.75 m3/d/m (Case 2) and T values of ≥2.61 m2/d (Case 4) corresponding to a Y of ≥300 m3/d were also input into a spatial database. The SPC and T data were randomly selected in an approximately 70:30 ratio to train and validate the WOE model. Tests of conditional independence were performed for the used factors. To assess the regional GPP for each dependent variable, W+ and W- of each factor's rating were overlaid spatially. The results of the analysis were validated using area under curve (AUC) analysis with the existing SPC and T data that were not used for the training of the model. The AUC of Cases 1, 2, 3 and 4 showed 0.7120, 0.6893, 0.6920, and 0.7098, respectively. In the case of the dependent variables, Case 1 had an accuracy of 71.20% (AUC: 0.7120), which is the best result produced in this analysis. Such information and the maps generated from it could be used for groundwater management, a practice related to groundwater resource exploration.