Ecology, Environment and Conservation Paper

Vol 21, Issue 3, 2015; Page No.(1571-1578)

REMOTE SENSING & GIS BASED MULTI CRITERIA MODEL FOR IDENTIFICATION OF RWH SITES

Ravi Kumar, Manoj Joseph and J.R. Sharma

Abstract

Rain Water Harvesting (RWH) is an important step towards maximizing water availability and land productivity in the semi-arid areas. However, selection of appropriate sites for different RWH technologies on a large scale presents a great challenge, since the necessary biophysical data and infrastructure are often lacking. The selection of potential areas depends on a multitude of factors including biophysical and socioeconomic conditions. A systematic scientific approach to the selection of feasible sites for RWH interventions can improve the performance and rate of adoption. For larger areas, application of Remote Sensing and GIS can be helpful for a first screening and identification of areas potentially suitable for RWH. The objective of this study is to identify suitable areas for RWH in a cluster of 50 villages in Jodhpur and Barmer district of Rajasthan. A GIS based model has been developed to generate suitability maps for in-situ RWH by using multi criteria evaluation. Basic parameters like land use/ land cover, soil texture, rainfall, slope and flow accumulation are analyzed and considered for the analysis. Weights were assigned to each parameter based on their relative importance for RWH with the help of literature and field level discussion. Using ArcGIS, maps for each criterion were generated and suitability maps for in-situ RWH has been prepared using weighted overlay analysis. A model has been developed using ArcGIS model builder to generate the RWH suitability map. The input to this model includes maps of rainfall, slope, soil texture (clay percentage), flow accumulation (drainage) and Land Use/Cover. Suitability index map was generated with five suitability levels i.e. ‘very high’, ‘high’, ‘moderate’, ‘low’ and ‘very low’. From the analysis suitable areas for rain water harvesting are identified. It has been observed that based on the given criteria, 4471.2 ha of the study area is highly suitable for RWH.

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