Groundwater vulnerability assessment using DRASTIC model: a comparative analysis of conventional, AHP, Fuzzy logic and Frequency ratio method

被引:0
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作者
Smitarani Lad
Rashmi Ayachit
Ajaykumar Kadam
Bhavana Umrikar
机构
[1] Savitribai Phule Pune University,Department of Environmental Sciences
[2] Savitribai Phule Pune University,Geoinformatics Division, Department of Geography
[3] Savitribai Phule Pune University,Department of Geology
关键词
Groundwater vulnerability; DRASTIC; Analytic hierarchy process; Fuzzy logic; Frequency ratio;
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摘要
Groundwater quality issues are drawing attention of researchers, developers, practitioners and planners throughout the world wherein besides geogenic sources, the activities such as urbanization, agriculture and industry are the precursors in polluting this precious natural resource. India is one such country where groundwater is the prime drinking water source especially in rural areas. Thus, along with the water scarcity, groundwater quality issues are posing challenge in front of the nation. Therefore, in current scenario, groundwater vulnerability prediction has an utmost importance. Hence it is the prime responsibility of the researchers to demarcate the vulnerable areas using simple and effective tools for establishing groundwater quality monitoring networks and implementing preventive measures. In the present study, a standard DRASTIC methodology has been employed to identify the critical areas for groundwater contamination. Further, the weights assigned to seven DRASTIC parameters were modified by using Analytical Hierarchical Process, Fuzzy logic and Frequency ratio method to understand the best fit method for vulnerability prediction. The reclassified rated thematic layers were integrated using weighted overlay function in GIS. The obtained results were grouped into four vulnerability zones: very low, low, moderate and high. The Standard, AHP, Fuzzy logic and Frequency Ratio based DRASTIC models revealed the area under high groundwater susceptibility as 84.68, 73.01, 89.13 and 82.97 km2 respectively. The resultant vulnerability maps were verified by superimposing groundwater quality (nitrate concentration point values) data.
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页码:543 / 553
页数:10
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