Spatial Prediction of Erosion Risk of a Small Mountainous Watershed Using RUSLE: A Case-Study of the Palar Sub-Watershed in Kodaikanal, South India

An 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.

[1]  S. Keesstra,et al.  Assessing hillslope-channel connectivity in an agricultural catchment using rare-earth oxide tracers and random forests models , 2017 .

[2]  E. Sujatha,et al.  Landslide Hazard and Risk Mapping Using the Weighted Linear Combination Model Applied to the Tevankarai Stream Watershed, Kodaikkanal, India , 2015 .

[3]  H. Arnoldus An approximation of the rainfall factor in the Universal Soil Loss Equation. , 1980 .

[4]  Leo Stroosnijder,et al.  Reducing Sediment Connectivity Through man‐Made and Natural Sediment Sinks in the Minizr Catchment, Northwest Ethiopia , 2017 .

[5]  Jeroen M. Schoorl,et al.  Evaluating choices in multi-process landscape evolution models , 2011 .

[6]  Ashish Pandey,et al.  Physically based soil erosion and sediment yield models revisited , 2016 .

[7]  J. F. Martínez-Murillo,et al.  Overland flow generation mechanisms affected by topsoil treatment: Application to soil conservation , 2015 .

[8]  S. Keesstra,et al.  Use of barley straw residues to avoid high erosion and runoff rates on persimmon plantations in Eastern Spain under low frequency–high magnitude simulated rainfall events , 2016 .

[9]  V. Prasuhn Soil erosion in the Swiss midlands: Results of a 10-year field survey , 2011 .

[10]  G. R. Foster,et al.  Predicting soil erosion by water : a guide to conservation planning with the Revised Universal Soil Loss Equation (RUSLE) , 1997 .

[11]  Peng Jian,et al.  Retraction Note: Assessment of soil erosion using RUSLE and GIS: a case study of the Maotiao River watershed, Guizhou Province, China , 2009, Environmental Earth Sciences.

[12]  Jeroen M. Schoorl,et al.  Evaluating the hydrological component of the new catchment-scale sediment delivery model LAPSUS-D , 2014 .

[13]  V. Chaplot,et al.  Tillage impact on soil erosion by water: Discrepancies due to climate and soil characteristics , 2016 .

[14]  W. H. Wischmeier,et al.  Predicting rainfall erosion losses : a guide to conservation planning , 1978 .

[15]  N. Hoyos Spatial modeling of soil erosion potential in a tropical watershed of the Colombian Andes , 2005 .

[16]  Ashish Pandey,et al.  Soil Erosion Assessment in a Hilly Catchment of North Eastern India Using USLE, GIS and Remote Sensing , 2008 .

[17]  A. Giménez-Morera,et al.  The impact of cotton geotextiles on soil and water losses from Mediterranean rainfed agricultural land , 2010 .

[18]  D. Shrestha Assessment of soil erosion in the Nepalese Himalaya : a case study in Likhu Khola Valley, Middle Mountain Region , 1997 .

[19]  J. Rodrigo‐Comino,et al.  Impact of lithology and soil properties on abandoned dryland terraces during the early stages of soil erosion by water in south‐east Spain , 2017 .

[20]  Thomas E. Fenton,et al.  Long-Term Effects of Compaction on Soil Properties Along the Mormon Trail, South-Central Iowa, USA , 2012 .

[21]  S. D. Angima,et al.  Soil erosion prediction using RUSLE for central Kenyan highland conditions , 2003 .

[22]  I. D. Moore,et al.  Modelling Erosion and Deposition: Topographic Effects , 1986 .

[23]  C. K. Mutchler,et al.  Revised slope steepness factor for the universal soil loss equation , 1987 .

[24]  Peng Jian,et al.  RETRACTED ARTICLE: Assessment of soil erosion using RUSLE and GIS: a case study of the Maotiao River watershed, Guizhou Province, China , 2009 .

[25]  V. Prasannakumar,et al.  Estimation of soil erosion risk within a small mountainous sub-watershed in Kerala, India, using Revised Universal Soil Loss Equation (RUSLE) and geo-information technology , 2012 .

[26]  P. Tarolli,et al.  The immediate effectiveness of barley straw mulch in reducing soil erodibility and surface runoff generation in Mediterranean vineyards. , 2016, The Science of the total environment.

[27]  R. K. Frevert,et al.  Soil and Water Conservation Engineering , 1955, Soil Science Society of America Journal.

[28]  A. Pandey,et al.  Soil erosion modeling of a Himalayan watershed using RS and GIS , 2009 .

[29]  J. Poesen,et al.  The European Soil Erosion Model (EUROSEM): A dynamic approach for predicting sediment transport from fields and small catchments. , 1998 .

[30]  Jagannath Aryal,et al.  A geospatial approach to assessing soil erosion in a watershed by integrating socio-economic determinants and the RUSLE model , 2014, Natural Hazards.

[31]  Ayad M. Fadhil Al-Quraishi Soil Erosion Risk Prediction with RS and GIS for the Northwestern Part of Hebei Province, China , 2003 .

[32]  A. García-Díaz,et al.  Eleven years after shrub revegetation in semiarid eroded soils. Influence in soil properties , 2016 .

[33]  M. Seeger,et al.  Temporal changes in soil water erosion on sloping vineyards in the Ruwer- Mosel Valley. The impact of age and plantation works in young and old vines , 2017 .

[34]  G. R. Foster,et al.  A Process-Based Soil Erosion Model for USDA-Water Erosion Prediction Project Technology , 1989 .

[35]  H. Ramesh,et al.  Assessment of soil erosion by RUSLE model using remote sensing and GIS - A case study of Nethravathi Basin , 2016 .

[36]  Dhruva V. V. Narayana,et al.  Estimation of Soil Erosion in India , 1983 .

[37]  Dao Kim Nguyen Thuy Binh,et al.  Erosion and Nutrient Loss on Sloping Land under Intense Cultivation in Southern Vietnam , 2008 .

[38]  Filippos Vallianatos,et al.  Soil erosion prediction using the Revised Universal Soil Loss Equation (RUSLE) in a GIS framework, Chania, Northwestern Crete, Greece , 2009 .

[39]  Mark A. Nearing,et al.  Sediment tracers in water erosion studies: current approaches and challenges , 2013, Journal of Soils and Sediments.

[40]  V. Prasannakumar,et al.  Spatial prediction of soil erosion risk by remote sensing, GIS and RUSLE approach: a case study of Siruvani river watershed in Attapady valley, Kerala, India , 2011 .

[41]  Arabinda Sharma,et al.  Integrating terrain and vegetation indices for identifying potential soil erosion risk area , 2010, Geo spatial Inf. Sci..

[42]  Venkataramana Sridhar,et al.  Mapping debris flow susceptibility using analytical network process in Kodaikkanal Hills, Tamil Nadu (India) , 2017, Journal of Earth System Science.

[43]  I. Moore,et al.  Physical basis of the length-slope factor in the universal soil loss equation , 1986 .

[44]  S. Keesstra,et al.  Policies can help to apply successful strategies to control soil and water losses. The case of chipped pruned branches (CPB) in Mediterranean citrus plantations , 2018, Land Use Policy.

[45]  Artemi Cerdà,et al.  Soil erosion assessment on tillage and alternative soil managements in a Sicilian vineyard , 2011 .