Introducing reverse Multi Influencing Factor technique in DRASTIC model for groundwater vulnerability assessment

被引:3
作者
Ganwer, Sandhya [1 ]
Sinha, Manish Kumar [1 ]
Multaniya, Amit Prakash [1 ]
Ghodichore, Nikhil [1 ]
机构
[1] Chhattisgarh Swami Vivekanand Tech Univ, Univ Teaching Dept, Dept Environm & Water Resources Engn, Bhilai 491107, Chhattisgarh, India
关键词
Aquifer vulnerability; DRASTIC; GIS; MIF; Reverse-MIF; Groundwater contamination/ quality; Sensitivity analysis; POLLUTION; GIS; AQUIFER; MIF;
D O I
10.1016/j.gsd.2024.101106
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Effective groundwater resource management has become essential to the development of urbanized areas, particularly in regions with significant agricultural and industrial activity. In the present study, a multi -criteria decision -analysis techniques methodology was used to assess the groundwater vulnerability of Seonath basin. The objective of this study is to identify the areas that are more susceptible to groundwater contamination by incorporating various hydrogeological layers from DRASTIC into the geographical information system (GIS) platform. To enhance the weights of the DRASTIC parameters used for the identification of the groundwater vulnerability index values, apart from the application of the widely -used multiple influencing factors (MIF) method, a new modified MIF method (hereafter named RMIF) was also introduced and applied. Based on their index map, the final results were classified into five vulnerable classes: very low, low, moderate, high, and very high. Lower index values indicated areas that were less vulnerable, and vice versa. DRASTIC-RMIF is performing better than DRASTIC and DRASTIC-MIF, respectively majority of the total area lies in moderately vulnerable zones: 77.50 %, 70.52 % and 28.20 %. In order to validate the groundwater vulnerability zones, we also attempted to test and create a relationship between nitrate and the final groundwater vulnerability result. And the coefficient of determination of DRASTIC, DRASTIC-MIF, and DRASTIC-RMIF methods were 0.6, 0.4, and 0.8, respectively. From this validation DRASTIC-RMIF obtained the most accurate result among all weighting techniques due to local hydrogeological condition. Model validation showed a significant association between the sample nitrate concentration values and the DRASTIC-RMIF model index values. Decision/Policy makers must identify vulnerable zones in order to manage and maintain an identification system for groundwater supplies.
引用
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页数:15
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