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dc.contributor.authorSujatha, Evangelin Ramani
dc.contributor.authorSridhar, Venkataramana
dc.date.accessioned2018-11-26T13:45:44Z
dc.date.available2018-11-26T13:45:44Z
dc.date.issued2018-11-09
dc.identifier.citationSujatha, E.R.; Sridhar, V. Spatial Prediction of Erosion Risk of a Small Mountainous Watershed Using RUSLE: A Case-Study of the Palar Sub-Watershed in Kodaikanal, South India. Water 2018, 10, 1608.
dc.identifier.urihttp://hdl.handle.net/10919/86150
dc.description.abstractAn erosion model using the Revised Universal Soil Loss Equation (RUSLE) equation derived from the Advanced Spaceborne Thermal Emission and Reflection Global Digital Elevation Model (ASTER G-DEM) and LANDSAT 8 is presented in the study. This model can be a cost-effective, quick and less labor-intensive tool for assessing erosion in small watersheds. It can also act as a vital input for the primary assessment of environmental degradation in the region, and can aid the formulation of watershed development planning strategies. The Palar River, which drains into Shanmukha Nadi, is a small mountain watershed. The town of Kodaikanal, a popular tourist attraction in Tamilnadu, forms part of this sub-watershed. This quaint, hill-town has been subjected to intense urbanization and exhaustive changes in its land use practices for the past decade. The consequence of this change is manifested in the intense environmental degradation of the region, which results in problems such as increased numbers of landslides, intense soil erosion, forest fires and land degradation. The nature of the terrain, high precipitation, and intense agriculture exponentially increase the rate of soil erosion. Spatial prediction of soil erosion is thereby a valuable and mandatory tool for sustainable land use practices and economic development of the region. A comprehensive methodology is employed to predict the spatial variation of soil erosion using the revised soil loss equation in a geographic information system (GIS) platform. The soil erosion susceptibility map shows a maximum annual soil loss of 3345 Mg·ha−1·y−1, which correlates with scrub forests, degraded forests, steep slopes, high drainage density and shifting cultivation practices. The erosion map shows that the central region is subjected to intense erosion while the inhabited southern part is less prone to erosion. A small patch of severe soil loss is also visible on the eastern part of the northern fringe. About 4% of the sub-watershed is severely affected by soil erosion and 18% falls within a moderate erosion zone. The growing demand for land and infrastructure development forces the shift of urbanization and agriculture to these less-managed spaces. In light of this scenario, the spatial distribution of erosion combined with terrain and hydro-morphometry can aid in sustainable development and promote healthy land use practices in the region.en_US
dc.format.mimetypeapplication/pdfen_US
dc.language.isoen_USen_US
dc.publisherMDPI
dc.rightsCreative Commons Attribution 4.0 International (CC BY 4.0)*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.titleSpatial Prediction of Erosion Risk of a Small Mountainous Watershed Using RUSLE: A Case-Study of the Palar Sub-Watershed in Kodaikanal, South Indiaen_US
dc.typeArticle - Refereeden_US
dc.date.updated2018-11-22T14:22:51Z
dc.title.serialWater
dc.identifier.doihttps://doi.org/10.3390/w10111608
dc.type.dcmitypeTexten_US


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Creative Commons Attribution 4.0 International (CC BY 4.0)
License: Creative Commons Attribution 4.0 International (CC BY 4.0)