The application of Dempster–Shafer theory of evidence for assessing groundwater vulnerability at Galal Badra basin, Wasit governorate, east of Iraq

The process of delineating areas that are more susceptible to pollution from anthropogenic sources has become an important issue for groundwater resources management and land-use planning. In this study, an attempt was made to delineate aquifer vulnerability zones for nitrate contamination at Galal Badra basin, east of Iraq using Dempster–Shafer method of evidence in GIS platform. First, an inventory map of the wells with elevated nitrate concentration (>3 mg/L) was prepared. The map showed that there are 63 wells with elevated nitrate concentrations in the study area. These data were partitioned randomly into two sets, for training and testing. The partition criterion was 70/30, 44 wells for training and 19 wells for testing. Then, the most influencing evidential thematic factors in determining aquifer vulnerability were selected depending on the availability of data. These factors were groundwater depth, hydraulic conductivity, slope, soil, and land use land cover (LULC). The spatial association between well locations and evidential thematic layers was investigated by means of mass functions (belief, disbelief, uncertainty, and plausibility) of Dempster–Shafer method. The integrated belief function was used to produce groundwater aquifer vulnerability index (GVI) for the study area. The pixel values of GVI were reclassified into five categories: very low, low, moderate, high, and very high using Jenks classification scheme. The very low–low zones cover 32 % (209 km²). These classes mainly concentrate on the eastern parts of the study area and occupy small zone in the central part. The moderate zone extends over an area of 42 % (279 km²) and mainly encompasses the western part of the study area. The high–very high zones cover 26 % (170 km²) and these zones concentrate on the central part of the study area. The results indicate that the aquifer system in the study area is moderately vulnerable to contamination by nitrate. The model was validated by using relative operating characteristic technique. The success and prediction rates for area under the curve (AUC) were 0.86 and 0.77, respectively, indicating that the model has good capability to delineate aquifer vulnerability zones for nitrate contamination in the study area.