Identifying the hill torrents and Groundwater Resources for a remote area of District Jamshoro using Remote Sensing and Geographical Information System

Abstract

Water resources are the major segments of the sustainable development in any region of the world.The current study identifies the hill torrents and groundwater resourcesin the Kohistan region of district Jamshoro, Sindh province of Pakistan. The study area is a hilly, mountainous range with arid to semi-arid climatic conditions, the high altitude do not allow the source of perennial/canal system, and depending on source of precipitation. Remote sensing data of Alos DEM of 30-meter resolution were obtained throughUSGS earth explorer official website. Shape filewas developed through the Google Earth Pro and ArcGIStechnique. HECGeoHMS was used to obtain hill torrents through processing tools and the stream definition was automated fixed to delineate the watershed area covering >= 75 km2.IdentifiedThe Groundwater resource into two categories of dug well and deep well. The study showed various ranges in the length of hill torrents 0.12 to 43.30 km, the depth of dug well aquifer 08.23-33.50 and deep well 91.50 to 164 meters in the region. Due to some research limitations the number 52 hill torrents, 33 dug wells and 11 deep wells were identified. Hill torrents carry runoff for the least period of rainy days, the torrential beds percolate the runoff and recharge shallow aquifers in the region, while deep aquifers recharges through adjoining watersheds. Water resourcepotential in the study area could be established by efficient heavy machinery to strengthening the torrential beds, and farms periphery bund structures, channelize watercourses, developed different ranges of ponds and reservoirs to capture floodwater, which enhance the recharge capacity of groundwater and introduce a high efficiency irrigation system in the study area. The spatial variation of water resources through modeling assessment has a major importance in the planning and development. Remote Sensing and GIS techniques enable the analysis with accurate results by consuming short time.