Identifying groundwater recharge zones using remote sensing & GIS techniques in Amaravathi aquifer system, Tamil Nadu, South India
Tóm tắt
In order to increase the sustainability of the wells and arrest the declining groundwater level trends in Amaravathi aquifer system, southern India, remote sensing and geographic information system (GIS) approach was attempted to identify favourable regions for construction of artificial recharge structures. GIS overlay analysis was carried out wherein 8 layers viz. geology, geomorphology, slope, soil, land use, post monsoon water level, weathering depth and waterbodies/drainage were integrated. Survey of India toposheet, Indian Remote Sensing Satellite IC data and ASTER data were used to develop the various thematic maps. These maps were later transferred to raster data. Groundwater level from the monitoring stations and weathering thickness data from the 248 deep wells constructed were used for the integration. Four zone namely very high, high, moderate and very poor have been demarcated. About 45% of the study area was categorised as high to very highly feasible zone. The existing artificial recharge structures in the region were also plotted and proposed artificial recharge structures were calculated. About 166 masonry check dam, 155 nala bunds, 575 recharge shafts (within tanks), 716 percolation ponds (repair, renovation and restoration) have been calculated and implementation of the proposed structures would create an additional water resource of 198 million m3 annually.
Tài liệu tham khảo
TWB. Deep Wells and Prudence: Towards Pragmatic Action for Addressing Groundwater Overexploitation in India. Washington, DC: The World Bank; 2010.
CGWB. Aquifer Mapping and Ground Water Management. Chennai: Central Ground Water Board; 2015.
CGWB. Ground Water Scenario in India. Faridabad: Central Ground Water Board; 2016.
Sener E, Davraz A, Ozcelik M. An integration of GIS and remote sensing in groundwater investigations: a case study in Burdur, Turkey. Hydrogeol J. 2005;13:826–34.
Prasad RK, Mondal NC, Banerjee P, Nandakumar MV, Singh VS. Deciphering potential groundwater zone in hard rock through the application of GIS. Environ Geol. 2008;55:467–75.
Sander P, Chesley MM, Minor TB. Groundwater assessment using remote sensing and GIS in a rural groundwater project in Ghana: lessons learned. Hydrogeol J. 1996;4:40–9.
Suganthi S, Elango L, Subramanian SK. Groundwater potential zonation by remote sensing and GIS techniques and its relation to the groundwater level in the coastal part of the Arani and Koratalai river basin, southern India. Earth Sci Res J. 2013;17:87–95.
Samadder RK, Kumar S, Gupta RP. Paleochannels and their potential for artificial groundwater recharge in the western ganga plains. J Hydrol. 2011;400:154–64.
Rathod IM, Aruchamy S. Spatial analysis of rainfall variation in Coimbatore district Tamil Nadu using GIS. Int J Geomat Geosci. 2010;1:106–18.
Sukumar S, Devadass CSC, Brema J. Rainfall distribution and variability in Coimbatore district, Tamil Nadu using GIS technique. Int J Earth Sci Eng. 2016;9:596–603.
CGWB. Dynamic Ground Water Resources of India. Faridabad: Central Ground Water Board; 2017.
Sreenivas A. Aquifer Mapping of 58F/15 Toposheet Area Comprising of Parts Of Dindigul District, Tamil Nadu. Chennai: Central Ground Water Board; 2014.
Preeja KR, Joseph S, Thomas J, Vijith H. Identification of groundwater potential zones of a tropical river basin (Kerala, India) using remote sensing and GIS techniques. J Indian Soc Remote. 2011;39:83–94.
Patil SG, Mohite NM. Identification of groundwater recharge potential zones for a watershed using remote sensing and GIS. Int J Geomat Geosci. 2014;4:485–98.
Kamaraj R, Gunalan N, Krishnan M, Krishnamurthy RR. Role of remote sensing and GIS in finding suitable artificial recharge zones in and around Neyveli basin, Cuddalore district, Tamil Nadu, India. J Acad Ind Res. 2014;3:295–300.