VULNERABILITY ANALYSIS OF GROUNDWATER USING A GIS-BASED MODIFIED SINTACS-AHP METHOD
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The main goal of using a groundwater vulnerability model is to map the sensitivity of groundwater to contamination. The consequences of the many types and qualities of pollution are disregarded using vulnerability models. Groundwater vulnerability assessment is the technique that is most frequently used to ensure the quality of groundwater (GVA). Researchers have already used the SINTACS method and a modified SINTACS method for GVA. However, there are shortcomings, such as the weighting and rating not being appropriate for the hydro-geological conditions, the intrinsic attributes and qualities of the supplemental SINTACS elements on GVA not being assessed by pairwise comparison using the Multi-Criteria Decision Analysis (MCDA) approach to adjust the weights and rates, etc. This paper proposes a novel strategy:
In addition to the other parameters employed in the conventional SINTACS approach, Land cover (LuLc) and Lineament (Ln) is taken into account. The weights of the parameters are then adjusted using the SINTACS approach that has since been modified and integrated with the analytical hierarchy process (AHP). In the research area, this modified SINTACS approach has been used to obtain a more accurate picture of the groundwater's susceptibility to nitrate pollution. The findings of the analysis utilizing the modified SINTACS-AHP approach show that the areas that fall within the very low and very highly vulnerable zones are 10.54% and 18.24%, respectively. Using nitrate concentration field data, all of the models were validated. To verify the model's predictions, thirty sites groundwater samples were obtained from identified groundwater susceptibility zones. With an accuracy of 86.7%, the results of the Modified SINTACS-AHP approach were demonstrated to be significantly related to the nitrate concentration of groundwater samples taken from the study area. Monitoring sensitive areas of the city are crucial to preventing groundwater contamination in the future.