A GIS-Based Comparative Groundwater Vulnerability Assessment Using Modified-DRASTIC, Modified-SINTACS and NV Index in a Porous Aquifer, Greece

Abstract

Groundwater vulnerability assessment is of pivotal importance for the sustainable management of groundwater resources, particularly in regions with intense agricultural activity. This research primarily aims to assess and delineate groundwater vulnerability zones using a comparative approach of three different GIS-based modified models, namely Pesticide DRASTIC-LU, Nitrate SINTACS-LU and Nitrate NV index. For this reason, eight hydrogeological parameters were employed to analyze the spatial distribution of groundwater vulnerability in the Nea Moudania aquifer, Chalkidiki, Greece. This multi-model methodology was implemented to ascertain the most reliable method for the study area. Results indicated that the southern and southwestern parts of the study area exhibited the highest vulnerability potential, whilst the northern part displayed the lowest. Moreover, single-parameter sensitivity analysis has revealed that land use and topography were the most critical parameters of the vulnerability indexes, whereas hydraulic conductivity was the least influential. Finally, the three vulnerability models were validated with nitrate concentrations of groundwater samples. Results revealed that the Nitrate NV index was the most accurate method, trailed by the Pesticide DRASTIC-LU and the Nitrate SINTACS-LU.

Groundwater vulnerability assessment using a GIS-based DRASTIC method in the Erbil Dumpsite area (Kani Qirzhala), Central Erbil Basin, North Iraq

“…This parameter holds significant relevance for groundwater quality degradation, representing the perpendicular distance between the ground surface and the water table (Kirlas et al 2023). Generally, higher values of this parameter correlate with a lower likelihood of groundwater pollution, as pollutants must travel a longer distance to reach and enter the water table.…”

“…Regions with low slopes tend to exhibit a higher potential for groundwater pollution, due to the low surface run-off rate and high infiltration rate, facilitating the migration of pollu-tants to the aquifer. Conversely high slope areas experience lower infiltration, resulting in reduced groundwater vulnerability (Kirlas et al 2023).…”

“…Despite its popularity, DRASTIC method has been criticized for its subjectivity and uncertainty in parameters' ratings and weights (Goyal et al 2021;Ekanem et al 2022;Xiong et al 2022). To address these concerns, researchers have modified the method to enhance its efficiency and accuracy for specific aquifers (Fannakh and Farsang, 2022;Kirlas et al 2023). Modifications include optimizing ratings and weights using methods such as Analytic Hierarchy Process (AHP), Fuzzy AHP, Analytic Network Process (ANP), multiple linear regression and sensitivity analysis and Shannon entropy (Sener and Davraz, 2012;Garewal et al 2017;Jhariya et al 2019;Alamne et al 2022;Kirlas et al 2022b;Shakeri et al 2023;Torkashvand et al 2023).…”

“…Modifications include optimizing ratings and weights using methods such as Analytic Hierarchy Process (AHP), Fuzzy AHP, Analytic Network Process (ANP), multiple linear regression and sensitivity analysis and Shannon entropy (Sener and Davraz, 2012;Garewal et al 2017;Jhariya et al 2019;Alamne et al 2022;Kirlas et al 2022b;Shakeri et al 2023;Torkashvand et al 2023). Additionally, researchers have proposed the incorporation of extra factors like land use, irrigation type and water quality index (Brindha and Elango, 2015;Sarkar and Pal, 2021;Abera et al 2022;Mkumbo et al 2022;Rauf et al 2022;Kirlas et al 2023;Taghavi et al 2023). Another limitation of the DRASTIC method is the absence of a standardized formula for examining and validating the accuracy of the final vulnerability map (Patel et al 2022).…”

Groundwater Vulnerability to Nitrate Contamination from Fertilizers Using Modified DRASTIC Frameworks

“…The flexibility of the DRASTIC method leads scholars to apply different types of modification to it. The modification strategies vary from adding other physical factors, such as land use, to the original parameters [15][16][17][18] to enhancing the DRASTIC rating and weighting systems [19][20][21][22]. In a comparative study, Kirlas, Karpouzos [18] incorporated their study area's land use as a parameter of DRASTIC.…”