Water Resource Management Of Simlapal Micro-Watershed Using Rs- Gis Based Universal Soil Loss Equation, Bankura District, W.B, India.
V. S. S. Kiran, Y. K. Srivastava, M Jagannadha Rao
Key Words: USLE, Watershed, Remote Sensing and GIS
Abstract: Water is one of the essential natural resource for the very survival of life on the planet Earth. Demand for water is increasing day by day, with the ever increasing population, resulted severe water crisis. We need water for agriculture, industry, human and cattle consumption. The available water is also affected by problem of pollution and contamination. Therefore it is very important to manage this very essential resource in a sustainable manner. Hence, we need proper management and development plan to conserve, restore or recharge water, where soil loss is very high due to various topographical conditions. The USLE (Universal Soil Loss Equation) method is one of the significant RS-GIS tools for prioritization of micro watersheds. A watershed is an ideal unit for study and to implement any model of water management towards achieving sustainable development. The significant factors for the planning and development of a watershed are its physiography, drainage, geomorphology, soil, land use/land cover and available water resources. In the current study, the micro-watershed priority fixation has been adopted under USLE model using Remote Sensing data. SRTM DEM, rainfall data and soil maps have been used to derive various thematic layers. The study area (Simlapal, W.B.) was subjected to USLE model of classifying and prioritizing the micro watersheds. The study area is divided into 22 sub-watersheds with areas ranging from 25 to 30 sq. km from the drainage map. Again each sub-watershed is divided into micro-watersheds with areas ranging from 5to10 sq. km. Thus 77 micro-watersheds were delineated for the present study area, considering all the controlling factors. Based on the results the 77 micro- watersheds could be prioritized in to five ranges viz very high, high, medium, low and very low.
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