Application of vulnerability modeling techniques in groundwater resources management: a comparative study

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.

Do Termitaria Indicate the Presence of Groundwater? A Case Study of Hydrogeophysical Investigation on a Land Parcel with Termite Activity

“…Borehole drillers in this part of the world often rely on a physical interpretation of field VES curves to select drill sites with reasonable success rates as allowing more time for proper interpretation is a burden on them especially when dealing with ignorant clients. In the second technique, thematic maps of the primary and secondary geoelectric parameters were produced in the ArcGIS 10.7 environment using the kriging interpolation technique (e.g., [ 28 , 29 ]). This was followed by integration of all the thematic layers for the purpose of evaluating the groundwater potential disposition of the entire study area and selecting the best points for potential drilling success as shown in the methodology flow chart ( Figure 3 ).…”

Modeling assessment of groundwater vulnerability to contamination risk in a typical basement terrain using TOPSIS-entropy developed vulnerability data mining technique

“…According to the studies [ [4] , [5] ], groundwater vulnerability refers to an aquifer unit’s susceptibility to pollution, leachate plumes brought on by anthropogenic activities, and pollutant properties from the surface. According to a study [ 6 ], an area’s groundwater vulnerability can be evaluated using a variety of conditioning factors. According to studies [ 4 , [7] , [8] , [9] ], these variables, such as land use, net recharge, longitudinal conductance, aquifer properties, topography, and hydraulic conductivity, among others, can provide information about how vulnerable an area may be.…”

Meta-heuristic algorithms in optimizing GALDIT framework: A comparative study for coastal aquifer vulnerability assessment

“…Among various methods for assessing groundwater vulnerability, the rating methods are the most popular one. Numerous studies have used the rating frameworks to assess the groundwater vulnerability (Mogaji 2018;Bouderbala et al 2016;Neshat and Pradhan 2015a;Neshat et al 2014 a, b, c;Pacheco et al 2015;Gorgij and Moghaddam 2016;Neshat and Pradhan 2017;Nadiri et al 2017b;Arauzo 2017;Kazakis and Voudouris 2015;Majandang and Sarapirome 2013;Ribeiro et al 2017;Pacheco and Fernandes 2013;Khosravi et al 2018;Trabelsi et al 2016;.…”