GIS Based Groundwater Modeling Study to Assess the Effect of Artificial Recharge: A Case Study from Kodaganar River Basin, Dindigul District, Tamil Nadu

Abstract

Groundwater is a dynamic and replenishable natural resource. The numerical modeling techniques serve as a tool to assess the effect of artificial recharge from the water conservation structures and its response with the aquifers under different recharge conditions. The objective of the present study is to identify the suitable sites for artificial recharge structures to augment groundwater resources and assess its performance through the integrated approach of Geographic Information System (GIS) and numerical groundwater modeling techniques using MODFLOW software for the watershed located in the Kodaganar river basin, Dindigul district, Tamil Nadu. Thematic layers such as geology, geomorphology, soil, runoff, land use and slope were integrated to prepare the groundwater prospect and recharge site map. These potential zones were categorized as good (23%), moderate (54%), and poor (23%) zones with respect to the assigned weightage of different thematic layers. The major artificial recharge structures like percolation ponds and check dams were recommended based on the drainage morphology in the watershed. Finally, a three-layer groundwater flow model was developed. The model was calibrated in two stages, which involved steady and transient state condition. The transient calibration was carried out for the time period from January 1989 to December 2008. The groundwater model was validated after model calibration. The prediction scenario was carried out after the transient calibration for the time period of year up to 2013. The results show that there is 15 to 38% increase in groundwater quantity due to artificial recharge. The present study is useful to assess the effect of artificial recharge from the proposed artificial structures by integrating GIS and groundwater model together to arrive at reasonable results.

Identification of Groundwater Potential Zones Using Remote Sensing and GIS Techniques: A Case Study of the Shatt Al-Arab Basin

“…Around the world, different methods have been used in delineating GWPZs such as integration of remote sensing and GIS with resistivity data [77], influence factor (IF) [47,51,66], statistical methods [78,79], groundwater modeling [80], and analytical hierarchy process (AHP) [63,74,81]. These methods have been proven as reliable and effective, and have been used by many researchers.…”

Groundwater recharge potential zonation using an ensemble of machine learning and bivariate statistical models

“…With the variety of techniques available for recharge assessment, selecting the appropriate technique is often not easy. Implementing some of these techniques may be restricted by some factors such as the resources available, precision level needed 21 , the space and time scales, reliability/range of recharge evaluation, as well as time and cost 22,23 . The methods can generally be categorized as being either direct or indirect.…”

Impact assessment of check dam recharge sites in the pappiredipatti Watershed (South India) by using LULC and NDVI Data

“…This impact can be digni ed the change ow of water in river , or forecast by hydrologi cal simulation model is used and combined with land use and land cover change situations of the aspect, it has allows for assess ing the impression of the change on groundwater recharge and discharge of river sites. The in uences of land use change in the context of recharge studies deliberated by various researcher such as Albhaisi et al,2013,Bhaskar Narjary et al,2014,Juan Ramón Raposo et al 2013,Tran Van.,2012, Sashikkumar et al,2017,Kenji jinno et al,2009,Dams et al,2008,Hamid Hosseinimarandi et al,2014Bertrand leterme and dirk mallants.,2011,Stiefel et al,2009,Vahid Amini Parsa et al,2016,Ala-aho P et al,2015, Rana Chatterjee et al,2009,Marcelo Varni et al,2013.,Ranu Rani et al,2009and Oke et al,2013. An objective of this study to validate the impact of land use and land cover variation on groundwater recharge sites in area of data resulting from Landsat satellite images by using a simulated model (Molusce), for Pappiredipatti watershed, South India.…”