Assessment of Groundwater Potential in a Semi-Arid Region of India Using Remote Sensing, GIS and MCDM Techniques

Abstract

Remote sensing (RS) and geographic information system (GIS) are promising tools for efficient planning and management of vital groundwater resources, especially in data-scarce developing nations. In this study, a standard methodology is proposed to delineate groundwater potential zones using integrated RS, GIS and multi-criteria decision making (MCDM) techniques. The developed methodology is demonstrated by a case study in Udaipur district of Rajasthan, western India. Initially, ten thematic layers, viz., topographic elevation, land slope, geomorphology, geology, soil, pre-and post-monsoon groundwater depths, annual net recharge, annual rainfall, and proximity to surface water bodies were considered in this study. These thematic layers were scrutinized by principal component analysis technique to select influential layers for groundwater prospecting. Selected seven thematic layers and their features were assigned suitable weights on the Saaty's scale according to their relative importance in groundwater occurrence. The assigned weights of the thematic layers and their features were then normalized by using AHP (analytic hierarchy process) MCDM technique and eigenvector method. Finally, the selected thematic maps were integrated by weighted linear combination method in a GIS environment to generate a groundwater potential map. Thus, four groundwater potential zones were identified and demarcated in the study area, viz., 'good', 'moderate', 'poor' and 'very poor' based on groundwater potential index values. The area falling in the 'good' zone is about 2,113 km 2 (17% of the total study area), which encompasses major portions of Sarada,

Application of remote sensing, GIS and MCA techniques for delineating groundwater prospect zones in Kashipur block, Purulia district, West Bengal

“…All the themes were integrated using "Spatial Analyst Module" of TNT mips pro 2012. Each theme and its individual class were assigned weight and rank (Table 1) based on the existing literature (Saraf and Choudhary 1998;Rao and Jugran 2003;Prasad et al 2008;Jha et al 2010;Machiwal et al 2011;Mukherjee et al 2012;Singh et al 2013). Individual themes have been assigned weights (Wt) and based on the knowledge upon their significance to groundwater, dif- Fig.…”

“…In recent times, digital techniques come out as a rapid and cost-effective tool, and are being used to integrate different data to decipher groundwater potential zones. In recent times, many workers have used the approach of RS and GIS for delineation of groundwater potential zones and artificial recharge sites (Chatterjee and Bhattacharya 1995;Teeuw 1995;Krishnamurthy et al 1996;Saraf and Choudhary 1998;Shahid and Nath 1999;Goyal et al 1999;Murthy 2000;Obi et al 2000;Pratap et al 2000;Shahid et al 2000;Jaiswal et al 2003;Srinivasa and Jugran 2003;Kamal and Midorikawa 2004;Nag 2005;Sener et al 2005;Sreedevi et al 2005;Gustavsson et al 2006;Srivastava and Bhattacharya 2006;Singh et al 2007Jasrotia et al2007Kumar et al 2007;Chenini et al 2010;Machiwal et al 2011;Talabi and Tijani 2011;Kuria et al 2012;Gumma and Pavelic 2013;Nag and Ghosh 2013;Nag and Saha 2014;Olutoyin 2014;Nag and Ray 2015). Furthermore, GIS is also being used for multi-criteria analysis for groundwater resource evaluation (Saraf et al 2004;Rao and Jugran 2003).…”

A GIS Based Approach into Delineating Liquefaction Susceptible Zones Through Assessment of Site-Soil-Geology-A Case Study of Madang and Morobe Province in Papua New Guinea (PNG)

“…Also the class of each factor was assigned weightage according to its potentiality in liquefaction hazard. The assigned weight or rank for each factor or class is based on different experts' opinions; therefore, pair-wise comparison, as introduced by Saaty (1980) for weights assigned was carried out basically to normalise the weights and to calculate the consistency ratio in order to be consistent of the weights and ranks assigned (Machiwal et al, 2011). Any process of weight assigned and normalizing weights were performed outside GIS environment using Microsoft excel.…”

Identification of artificial groundwater recharging zone using a GIS-based fuzzy logic approach: a case study in a coal mine area of the Damodar Valley, India

“…As groundwater is dynamic and interdisciplinary in nature, an integrated approach of RS and GIS techniques is very useful in groundwater resource management (Chowdhury et al 2010). Recently, around the world, several researchers have used RS and GIS techniques for the evaluation of potential groundwater zones (Basavarajappa et al 2013;Chenini et al 2010;Dinesh Kumar et al 2007;Machiwal et al 2011;Machiwal and Singh, 2015;Magesh et al 2012;Sener et al 2005;Shaban et al 2006;Yeh et al 2009). In particular, a number of researchers have studied groundwater protection zones and the groundwater level in Jharkhand state in India with the help of RS and GIS techniques (Chandra et al 2015;Chowdary et al 2009;Rai et al 2005;Sharma and Kujur 2012;Srivastava et al 2012).…”