Remote Sensing and GIS Based Groundwater Potential & Recharge Zones Mapping Using Multi-Criteria Decision Making Technique

Rajat Agarwal () and P. Garg

Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), 2016, vol. 30, issue 1, 243-260

Abstract: Remote Sensing (RS) and Geographical Information System (GIS) play a crucial role to understand the division of groundwater, an important resource of water supply all over the world. In this present study, groundwater potential and recharge zone maps, are delineated for Loni and Morahi watersheds, Unnao and Rae Bareli district, Uttar Pradesh, India using RS, GIS and Multi-Criteria Decision Making (MCDM) techniques. The Satty’s Analytical Hierarchical Process (AHP) is used as a MCDM technique to normalise the weights of various thematic layers and their classes for delineating the groundwater potential and recharge zone maps. Thematic layers were integrated using weighted overlay in a GIS environment to generate groundwater potential and recharge zone maps. The output potential map is further classified into five zones on the basis of their histograms, viz., ‘very poor’, ‘poor’, ‘good’, ‘very good’ and ‘excellent’. The area falling in the excellent zone is about 150.93 km 2 (7.06 % of the total study area), which covers a major portion of the Ganga river. It discriminates the areas where the terrain is suitable for groundwater storage. However, the area falling in the very poor zone is about 372.03 km 2 (17.42 % of the total study area) and covers the Loni river south-eastern portion and some areas in north-eastern sides. Groundwater recharge map is classified into four zones namely; ‘most suitable’, ‘moderately suitable’, ‘poorly suitable’ and ‘not suitable’. Yield data of the 40 pumping wells are used to verify the groundwater potential zone map, and the results were found to be good. Copyright Springer Science+Business Media Dordrecht 2016

Keywords: RS; GIS; AHP; GWPZ; GWRZ; MCDM (search for similar items in EconPapers)
Date: 2016
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Citations: View citations in EconPapers (18)

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DOI: 10.1007/s11269-015-1159-8

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