Assessment of groundwater vulnerability in an urban area: a comparative study based on DRASTIC, EBF, and LR models

Abstract

The groundwater vulnerability assessment is known as a useful tool for predicting and prevention of groundwater pollution. This study targets the DRASTIC, evidential belief function (EBF), and logistic regression (LR) models to assess vulnerability in Kabul aquifers, Afghanistan Country. The growth of urban sprawl, groundwater overexploitation, and lack of suitable municipal sewage systems as anthropogenic sources have been the main potential to increase groundwater contaminants such as nitrate in the study area. The vulnerability map has been developed based on various effective factors including altitude, slope (percentage rise), aspect, curvature, land-use type, drainage density, distance from river, annual mean precipitation, net recharge, geology/lithology units, the impact of the vadose zone, aquifer media, depth to water (unsaturated zone), saturated zone, drawdown, and hydraulic conductivity. To identify groundwater pollution, the spatial variation of nitrate concentration data in 2018 was considered indication of groundwater pollution. Based on descriptive statistics, the value of 2.65 mg/l (the median of the pixel values of nitrate map) was selected as a threshold to differentiate the occurrence and non-occurrence of pollution. The groundwater quality data were selected and randomly divided into two datasets for training and validation, including 70% and 30%, respectively. The success-rate and prediction-rate curves were computed based on the receiver operating characteristic (ROC) curve and the area under the curve (AUC) to estimate the efficiency of models. The ROC-AUC of success rates for EBF, LR, and DRASTIC models were estimated to be 67%, 66%, and 52%, respectively. Moreover, the ROC-AUC of the prediction rates of the EBF, LR, and DRASTIC models were obtained 61%, 63%, and 55%, respectively. Based on correlation between mean nitrate concentration and the mean vulnerability indexes in each model, the EBF model is the most compatible with the current developed vulnerability zones as the role of mankind in changing the environment in real conditions in comparison to LR and DRASTIC models.

Keywords: Afghanistan; DRASTIC; Evidential belief function; Groundwater pollution; Logistic regression; Vulnerability map.