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Multi-collinearity Based Parameter Optimization and Comparison among Multi-criteria Decision Analysis to Map Groundwater Potential Zones

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Journal of the Geological Society of India

Abstract

Zonation of groundwater potential is a vital technique for long-term water governance and urban planning, particularly in agrarian countries such as India. As a result, the present groundwater potential mapping study was carried out in Tiruvannamalai district, Tamil Nadu, India to assess the capability of the aquifer using 21 groundwater conditioning parameters. An overlay analysis was performed to create a database for multicollinearity analysis to optimize the parameters. Normalization, weight allocation, and ranking of locations based on the assessment value were performed using Multi Criteria Decision Analysis (MCDA) techniques such as Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) and Multi-Objective Optimization based on Ratio Analysis (MOORA). The results of MCDA techniques were integrated with Remote Sensing (RS) and Geographical Information System (GIS) for the identification of groundwater potential zones. Based on the TOPSIS, 5.17 % of the area was classified as very high potential and 9.38 % of the area was classified as a very low potential zones. Similarly, the MOORA technique classified 5.54% of zones as very high and 13.55% as very low potential. Validation of results were done using groundwater level and groundwater draft data and prediction accuracy of MOORA and TOPSIS was found to be more than 80%.

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Correspondence to S. Parimalarenganayaki.

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Multi-collinearity Based Parameter Optimization and Comparison among Multi-criteria Decision Analysis to Map Groundwater Potential Zones

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Venkatesh, S., Parimalarenganayaki, S. Multi-collinearity Based Parameter Optimization and Comparison among Multi-criteria Decision Analysis to Map Groundwater Potential Zones. J Geol Soc India 99, 1158–1164 (2023). https://doi.org/10.1007/s12594-023-2441-7

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  • DOI: https://doi.org/10.1007/s12594-023-2441-7

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