摘要
Groundwater potential zones were demarcated with the help of remote sensing and Geographic Informa- tion System （GIS） techniques. The study area is composed rocks of Archaean age and chamockite dominated over others. The parameters considered for identifying the groundwater potential zone of geology slope, drainage density, geomorphic units and lineament density were generated using the resource sat （IRS P6 LISS IV MX） data and survey of India （SO1） toposheets of scale 1：50000 and integrated them with an inverse distance weighted （IDW） model based on GIS data to identify the ground- water potential of the study area. Suitable weightage factors were assigned for each category of these para- meters. For the various geomorphic units, weightage factors were assigned based on their capability to store ground-water. This procedure was repeated for all the other layers and resultant layers were reclassified. The reclassi- fied layers were then combined to demarcate zones as very good, good, moderate, low, and poor. This groundwater potentiality information could be used for effective identification of suitable locations for extraction of potable water for rural populations.
Groundwater potential zones were demarcated with the help of remote sensing and Geographic Informa- tion System （GIS） techniques. The study area is composed rocks of Archaean age and chamockite dominated over others. The parameters considered for identifying the groundwater potential zone of geology slope, drainage density, geomorphic units and lineament density were generated using the resource sat （IRS P6 LISS IV MX） data and survey of India （SO1） toposheets of scale 1：50000 and integrated them with an inverse distance weighted （IDW） model based on GIS data to identify the ground- water potential of the study area. Suitable weightage factors were assigned for each category of these para- meters. For the various geomorphic units, weightage factors were assigned based on their capability to store ground-water. This procedure was repeated for all the other layers and resultant layers were reclassified. The reclassi- fied layers were then combined to demarcate zones as very good, good, moderate, low, and poor. This groundwater potentiality information could be used for effective identification of suitable locations for extraction of potable water for rural populations.
