Abstract
The sustainability management of groundwater resource globally is challenged by its vulnerability to pollution resulting from anthropogenic activities. In order to address this problem, the DRASTIC index model (DIM) method among the existing vulnerability modeling techniques is commonly used. OWA-DRASTIC index model (ODIM) technique is another recently developed method for the same task. This study investigated the application of these vulnerability-biased modeling methods in a multi-faceted geologic setting at Perak Province, Malaysia with the view of establishing their efficiencies. The models considered seven pollution potential conditioning factors (PPCFs) obtained from difference data sources. Applying the GIS-based multi-criterial algorithm of these models, the PPCFs were related for developing multi-parameters-based vulnerability index model equations. Groundwater vulnerability to pollution index (GVPI) maps was produced from the synthesized estimated results of the applied multi-parameters-based vulnerability index model equations. The reliability of the produced GVPI maps was established using analyzed groundwater quality data results. The obtained prediction accuracy results for the ODIM-based GVPI map and DIM-based GVPI map are 85.71 and 64.29%, respectively. Besides, the regression coefficient results obtained from the spatially estimate from the DIM and ODIM’ vulnerability index’s values relationship with the pH and manganese concentrations give 83 and 85% for the ODIM technique and 68 and 63% for the DIM technique, respectively. The overall results indicated that the applied ODIM method in the area is a better alternative to the conventional DIM method. The produced GVPI maps can be useful to regional planners and environmental managers entrusted with the protection of groundwater resource.
Highlights
The susceptibility of groundwater to pollution is a consequence of a finite combination of different factors ranging from the variation in hydrogeological settings and human activities whose togetherness often formed dynamic system (Pathak et al 2014; Pradhan et al 2013)
The overlay and index methods among these aforementioned methods are relatively simple and often pave ways for easy combination of different parameters’ themes through allocation of numerical index. The renown of this index methods that have been investigated for vulnerability prediction in the field of groundwater hydrology with attractive results are such as DRASTIC, GOD, AVI and SINTACS (Aller et al 1987; Neshat et al 2014; Foster 1987; Van Stemproot et al 1993; Daly and Drew 1999)
The specific objectives of this study are as follows: (1) produce the groundwater vulnerability to pollution index (GVPI) map through DRASTIC model index, (2) produce the groundwater vulnerability to pollution index (GVPI) map through Ordered weighted averaging (OWA)-DRASTIC model index, (3) validated the produced GVPI maps using the groundwater quality analyzed results obtainable in the area and (4) analyzed the validation results to evaluate the efficiency of the models with the view of
Summary
The susceptibility of groundwater to pollution is a consequence of a finite combination of different factors ranging from the variation in hydrogeological settings and human activities whose togetherness often formed dynamic system (Pathak et al 2014; Pradhan et al 2013). These interrelated factors interact in a manner by which the quality monitoring of groundwater system could be predicted. The renown of this index methods that have been investigated for vulnerability prediction in the field of groundwater hydrology with attractive results are such as DRASTIC, GOD, AVI and SINTACS (Aller et al 1987; Neshat et al 2014; Foster 1987; Van Stemproot et al 1993; Daly and Drew 1999)
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