A Review of RUSLE Model

  • Kaushik Ghosal
  • Santasmita Das BhattacharyaEmail author
Cover Article


In this paper, we attempted to review the soil erosion studies conducted throughout the globe using Revised Universal Soil Loss Equation (RUSLE). We searched the SCI, Scopus, Web of Science, Google Scholar database and various theses for this study. Though RUSLE is the most widely used model for estimation of soil erosion, the factors, namely rainfall erosivity, soil erodibility, slope length and steepness, cover management and conservation practice; vary greatly over different climatic zones, soil properties, slope, land cover and crop phase, respectively. Depending upon those variations, researchers have developed various sets of equation for different factors of RUSLE. These equations can be useful to map soil loss for many places on this planet.


RUSLE for soil erosion Rainfall erosivity factor (RSoil erodibility factor (KSlope length and steepness factor (LS) Cover management factor (CConservation practice factor (P



  1. Adediji, A., Tukur, A., & Adepoju, K. (2010). Assessment of revised universal soil loss equation (RUSLE) in Katsina Area, Katsina State of Nigeria using remote sensing (RS) and geographic information system (GIS). Iranica Journal of Energy & Environment,1(3), 255–264.Google Scholar
  2. Agarwal, D., et al. (2016). Soil erosion mapping of watershed in Mirzapur district using RUSLE model in GIS environment. International Journal of Students’ Research In Technology & Management,4(3), 56–63.CrossRefGoogle Scholar
  3. Agele, D., Lihan, T., Sahibin, A., & Rahman, Z. (2013). Application of the RUSLE model in forecasting soil erosion at downstream of the Pahang river basin, Malaysia. Journal of Applied Sciences Research,9(1), 413–424.Google Scholar
  4. Amsalu, T., & Mengaw, A. (2014). GIS based soil loss estimation using RUSLE model: The case of Jabi Tehinan Woreda, ANRS, Ethiopia. Natural Resources,5, 616–626.CrossRefGoogle Scholar
  5. Angima, S., et al. (2003). Soil erosion prediction using RUSLE for central Kenyan highland conditions. Agriculture, Ecosystems & Environment,97, 295–308.CrossRefGoogle Scholar
  6. Arnoldus, H., Boodt, M. & Gabriels, D., (1980). An approximation of the rainfall factor in the Universal Soil Loss Equation. s.l.:s.n.Google Scholar
  7. Babu, R., Dhyani, B., & Kumar, N. (2004). Assessment of erodibility status and refined Iso- erodent map of India. Indian Journal of Soil Conservation,32(2), 171–177.Google Scholar
  8. Babu, R., Tejwani, K., Agrawal, M. & Bhusan, L., (1979). Rainfall intensity duration-return equation and nomographs of India.Google Scholar
  9. Baby, A., & Nair, A. (2016). Soil erosion estimation of Kuttiyadi River Basin Using RUSLE. International Advanced Research Journal in Science, Engineering and Technology,3(3), 275–279.Google Scholar
  10. Benkobi, L., Trlica, M., & Smith, J. (1994). Evaluation of a redefined surface cover sub-factor for use in RUSLE. Journal of Range Management,47, 74–78.CrossRefGoogle Scholar
  11. Bewket, W., & Teferi, E. (2009). Assessment of soil erosion hazard and prioritization for treatment at the watershed level: Case study in the Chemoga watershed, Blue Nile Basin, Ethiopia. Land Degradation & Development,20, 609–622.CrossRefGoogle Scholar
  12. Bhandari, K., & Darnsawasdi, R. (2015). Application of remote sensing and participatory soil erosion assessment approach for soil erosion mapping in a watershed. Walailak Journal of Science and Technology,12(8), 689–702.Google Scholar
  13. Bhat, S., et al. (2017). Soil erosion modeling using RUSLE & GIS on micro watershed of J&K. Journal of Pharmacognosy and Phytochemistry,6(5), 838–842.Google Scholar
  14. Biswas, S. S., & Pani, P. (2015). Estimation of soil erosion using RUSLE and GIS techniques: A case study of Barakar River basin, Jharkhand. India. Modeling Earth Systems and Environment,1(4), 1–13.Google Scholar
  15. Bonilla, C. A., Reyes, J. L., & Magri, A. (2010). Water erosion prediction using the revised universal soil loss equation (RUSLE) in a GIS framework, Central Chile. Chilean Journal of Agricultural Research,70(1), 159–169.CrossRefGoogle Scholar
  16. Bu, Z., et al. (2003). The progress of quantitative remote sensing method for annual soil losses and its application in Taihu-Lake Watersheds. Acta Pedol Sin,40(1), 1–9. (in Chinese).Google Scholar
  17. Cai, C. (1998). Prediction of nutrients loss caused by soil erosion and assessment of fertility with GIS at small watershed level. PhD thesis.Google Scholar
  18. Chatterjee, S., Krishna, A. P., & Sharma, A. P. (2014). Geospatial assessment of soil erosion vulnerability at watershed level in some sections of the Upper Subarnarekha river basin, Jharkhand, India. Environmental Earth Sciences,71, 357–374.CrossRefGoogle Scholar
  19. Chen, T., Li, P. & Zhang, L., (2008). Retrieving vegetation cover by using BP neural network based on ‘‘Beijing-1’’ microsatellite data. China. In The International conference on earth observation data processing and analysis (ICEODPA2008).Google Scholar
  20. Chen, T., et al. (2011). Regional soil erosion risk mapping using RUSLE, GIS, and remote sensing a case study in Miyun Watershed, North China. Environmental Earth Sciences,63, 533–541.CrossRefGoogle Scholar
  21. Dahe, P., & Borate, P. (2015). Development of erosion hotspots for Kaas Plateau (ESZ) of Western Ghat, Maharashtra using RUSLE and arc GIS. International Journal of Remote Sensing & Geoscience (IJRSG),4(4), 35–43.Google Scholar
  22. Das, G., & Guchait, R. (2016). Modeling of risk of soil erosion in Kharkai Watershed using RUSLE and TRMM Data: A geospatial approach. International Journal of Science and Research (IJSR), 5(10), 1–10.Google Scholar
  23. Demirci, A., & Karaburun, A. (2012). Estimation of soil erosion using RUSLE in a GIS framework a case study in the Buyukcekmece Lake watershed, northwest Turkey. Environmental Earth Sciences,66, 903–913.CrossRefGoogle Scholar
  24. Desmet, P., & Govers, G. (1996). A GIS-procedure for the automated calculation of the USLE LS-factor on topographically complex landscape units. Journal of Soil and Water Conservation,51(5), 427–433.Google Scholar
  25. Diodato, N. (2004). Estimating Rusle’s rainfall factor in the part of Italy with a Mediterranean rainfall regime. Hydrology and Earth System Sciences,8, 103–107.CrossRefGoogle Scholar
  26. Efthimiou, N., Lykoudi, E., & Karavitis, C. (2014). Soil erosion assessment using the RUSLE model and GIS. European Water,47, 15–30.Google Scholar
  27. El-Swaify, S., & Dangler, E. (1976). Erodibilities of selected tropical soils in relation to structural and hydrologic parameters. In G. Foster (Ed.), Soil Erosion Prediction and Control (pp. 105–114). Ankeny: Soil and Water Conservation Society.Google Scholar
  28. Ferro, V., Giordano, G., & Lovino, M. (1991). Isoerosivity and erosion risk map for Sicily. Hydrological Sciences Journal,36(6), 549–564.CrossRefGoogle Scholar
  29. Flabouris, K. (2008). Study of rainfall factor R on the RUSLE law.Google Scholar
  30. Foster, G., McCool, D., Renard, K., & Moldenhauer, W. (1981). Conversion of the universal soil loss equation to SI metric units. Journal of Soil and Water Conservation,36(6), 355–359.Google Scholar
  31. Foster, G., Meyer, L., & Onstad, C. (1977). An erosion equation derived from basic erosion principles. Transactions of the ASAE,20(4), 683–687.CrossRefGoogle Scholar
  32. Fu, B. J., et al. (2005). Assessment of soil erosion at large watershed scale Using RUSLE and GIS: A case study in the Loess Plateau of China. Land Degradation & Development,16, 73–85.CrossRefGoogle Scholar
  33. Ganasri, B., & Ramesh, H. (2016). Assessment of soil erosion by RUSLE model using remote sensing and GIS—A case study of Nethravathi Basin. Geoscience Frontiers,7, 953–961.CrossRefGoogle Scholar
  34. Gashaw, T., Tulu, T., & Argaw, M. (2017). Erosion risk assessment for prioritization of conservation measures in Geleda watershed, Blue Nile basin, Ethiopia. Environmental Systems Research, 6(1), 1–14.CrossRefGoogle Scholar
  35. Gashaw, T., Tulu, T., & Argaw, M. (2017b). Erosion risk assessment for prioritization of conservation measures in Geleda watershed, Blue Nile basin, Ethiopia. Environmental Systems Research,6(1), 1–14.CrossRefGoogle Scholar
  36. Gaudasasmita, K. (1987). Contribution to geo-information system operation for prediction of erosion. ITC, Netherlands: s.n.Google Scholar
  37. Gelagay, H. (2016). RUSLE and SDR model based sediment yield assessment in a GIS and remote sensing environment: A case study of Koga Watershed, Upper Blue Nile Basin, Ethiopia. Hydrology Current Research,7(2), 239.CrossRefGoogle Scholar
  38. Ghosh, K. G., Mukhopadhyay, S., & Pal, S. (2015). Surface runoff and soil erosion dynamics: A case study on Bakreshwar river basin, eastern India. International Research Journal of Earth Sciences,3(7), 11–22.Google Scholar
  39. Gitas, I. et al. (2009). Multi-temporal soil erosion risk assessment in N. Chalkidiki using a modified USLE raster model. s.l., In EARSeL eProceedings (pp. 40–52).Google Scholar
  40. Goldman, S., & Wischmeier, W. (1986). Erosion and sediment control handbook. New York: McGraw Hill.Google Scholar
  41. Gutman, G., & Ignatov, A. (1998). The derivation of the green vegetation fraction from NOAA/AVHRR data for use in numerical weather prediction models. International Journal of Remote Sensing,19(8), 1533–1543.CrossRefGoogle Scholar
  42. Hammad, A. A., Lundekvam, H., & Børresen, T. (2005). Adaptation of RUSLE in the eastern part of the mediterranean region. Environmental Management,34(6), 829–841.CrossRefGoogle Scholar
  43. Helden, U. (1987). An assessment of woody biomass, community forests, land use and soil erosion in Ethiopia. s.l.: Lund University Press.Google Scholar
  44. Hickey, R. (2000). Slope angle and slope length solutions for GIS. Cartography,29, 1–8.CrossRefGoogle Scholar
  45. Hurni, H. (1985). Soil conservation manual for Ethiopia.Google Scholar
  46. ICONA, (1988). Agresividad de la lluvia en España. Madrid, España, Servicio de Publicaciones del Ministerio de Agricultura, Pesca y Alimentación (p. 39).Google Scholar
  47. Irvem, A., Topalog ˘lu, F., & Uygur, V. (2007). Estimating spatial distribution of soil loss over Seyhan River Basin in Turkey. Journal of Hydrology,336, 30–37.CrossRefGoogle Scholar
  48. Joshi, V., Susware, N., & Sinha, D. (2016). Estimating soil loss from a watershed in Western Deccan, India, using Revised Universal Soil Loss Equation. Landscape & Environment,10(1), 13–25.CrossRefGoogle Scholar
  49. Kalambukattu, J., & Kumar, S. (2017). Modelling soil erosion risk in a mountainous watershed of Mid-Himalaya by integrating RUSLE model with GIS. Eurasian Journal of Soil Science,6(2), 92–105.Google Scholar
  50. Kamuju, N. (2015). A study on estimation and comparison of average annual soil erosion with different slope length [L] and Steepness factors[S] by RUSLE model using remote sensing and GIS technology. IJITR International Journal of Innovative Technology and Research,3(5), 2424–2431.Google Scholar
  51. Kamuju, N. (2016). spatial identification and classification of soil erosion prone zones using remote sensing & gis integrated ‘rusle’ model and ‘sateec gis system. International journal of engineering sciences & research technology,5(10), 676–686.Google Scholar
  52. Kartic, K. M., Annadurai, R., & Ravichandran, T. (2014). Assessment of soil erosion susceptibility in Kothagiri. International Journal of Scientific and Research Publications Taluk Using Revised Universal Soil Loss Equation (RUSLE) and Geo-Spatial Technology, 4(10), 1–13.Google Scholar
  53. KICT, (1992). The development of selection standard for calculation method of unit sediment yield in rivers. KICT 89-WR-113. Google Scholar
  54. Kim, S.-M., et al. (2012). Estimation of soil erosion and sediment yield from mine tailing dumps using GIS: a case study at the Samgwang mine, Korea. Geosystem Engineering,15(1), 2–9.CrossRefGoogle Scholar
  55. Kumar, S., & Kushwaha, S. (2013). Modelling soil erosion risk based on RUSLE-3D using GIS in a Shivalik sub-watershed. Journal of Earth System Science,122(2), 389–398.CrossRefGoogle Scholar
  56. Lee, G., & Lee, K. (2006). Scaling effect for estimating soil loss in the RUSLE model using remotely sensed geospatial data in Korea. Hydrology and Earth System Sciences,3, 135–157.CrossRefGoogle Scholar
  57. Lema, B., et al. (2016). Use of the revised universal soil loss equation (RUSLE) for soil and nutrient loss estimation in long-used rainfed agricultural lands, North Ethiopia. Physical Geography,37(3–4), 276–290.CrossRefGoogle Scholar
  58. Lopez-Vicente, M., Navas, A., & Mach´ın, J. (2008). Identifying erosive periods by using RUSLE factors in mountain fields of the Central Spanish Pyrenees. Hydrology and Earth System Sciences,12, 523–535.CrossRefGoogle Scholar
  59. Loureiro, N., & Coutinho, M. (2001). A new procedure to estimate the RUSLE El30 index, based on monthly rainfall data and applied to the Algarve region, Portugal. Journal of Hydrology,250, 12–18.CrossRefGoogle Scholar
  60. Lufafa, A., et al. (2003). Prediction of soil erosion in a Lake Victoria basin catchment using a GIS-based Universal Soil Loss model. Agricultural Systems,76, 883–894.CrossRefGoogle Scholar
  61. Maria, K., Pantelis, S., & Filippos, V. (2009). Soil erosion prediction using the Revised Universal soil loss equation (RUSLE) in a GIS framework, Chania, Northwestern Crete, Greece. Environmental Geology,57, 483–497.CrossRefGoogle Scholar
  62. Markose, V. & Jayappa, K., (2016). Soil loss estimation and prioritization of sub-watersheds of Kali River basin, Karnataka, India, using RUSLE and GIS. Environmental Monitoring and Assessment. Scholar
  63. Markose, V., & Jayappa, K. (2016b). Soil loss estimation and prioritization of sub-watersheds of Kali River basin, Karnataka, India, using RUSLE and GIS. Environmental Monitoring and Assessment,188(4), 1–16.CrossRefGoogle Scholar
  64. McCool, D., Brown, L., Foster, G., & Mutchler, L. (1987). Revised slope steepness factor for the Universal Soil Loss Equation. Transactions of the ASAE (American Society of Agricultural Engineers),30, 1387–1396.CrossRefGoogle Scholar
  65. McFarlane, D., Delroy, N., & Van, S. V. (1991). Water erosion of potato land in Western Australia. Australian journal of soil and water conservation, 4(1), 33–40.Google Scholar
  66. Mcroberts, R., Nelson, M., & Wendt, D. (2002). Stratified estimation of forest area using satellite imagery, inventory data, and the kNearest Neighbors technique. Remote Sensing of Environment,82, 457–468.CrossRefGoogle Scholar
  67. Mhangara, P., Kakembo, V., & Lim, K. (2012). Soil erosion risk assessment of the Keiskamma catchment, South Africa using GIS and remote sensing. Environmental Earth Sciences,65(7), 2087–2102.CrossRefGoogle Scholar
  68. Millward, A. A., & Mersey, J. E. (1999). Adapting the RUSLE to model soil erosion potential in a mountainous tropical watershed. Catena,38, 109–129.CrossRefGoogle Scholar
  69. Moore, I., & Burch, F. (1986). Physical basic of the length–slope factor in the Universal Soil Loss Equation. Soil Science Society of America Journal,50, 1294–1298.CrossRefGoogle Scholar
  70. Morgan, R. P. C. (1986). Soil erosion and conservation. s.l.: Longman.Google Scholar
  71. Morgan, R. (1995). Soil Erosion and Conservation (2nd ed.). UK: Longman.Google Scholar
  72. Morgan, R., & Davidson, D. (1991). Soil Erosion and Conservation. UK: Longman Group.Google Scholar
  73. Mulengera, M., & Payton, R. (1999). Estimating the USLE-soil erodibility factor in developing tropical countries. Trop Agric (Trinidad),76(1), 17–22.Google Scholar
  74. Naqvi, H. R., Devi, L. M., & Siddiqui, M. A. (2012). Soil loss prediction and prioritization based on revised universal soil loss estimation (RUSLE) model using geospatial technique. International Journal of Environmental Protection,2(3), 39–43.Google Scholar
  75. Oliveira, J. A., Dominguez, J. M. L., Nearing, M. A., & Oliveira, P. T. S. (2015). A GIS-based procedure for automatically calculating soil loss from the universal soil loss equation: Gisus-m. American Society of Agricultural and Biological Engineers,31(6), 907–917.Google Scholar
  76. Onori, F., Bonis, P. D., & Grauso, S. (2006). Soil erosion prediction at the basin scale using the revised universal soil loss equation (RUSLE) in a catchment of Sicily (southern Italy). Environmental Geology,50, 1129–1140.CrossRefGoogle Scholar
  77. Pal, S., & Shit, M. (2017). Application of RUSLE model for soil loss estimation of Jaipanda watershed, West Bengal. Spatial Information Research,25(3), 399–409.CrossRefGoogle Scholar
  78. Parveen, R., & Kumar, U. (2012). Integrated approach of universal soil loss equation (USLE) and geographical information system (GIS) for soil loss risk assessment in Upper South Koel Basin, Jharkhand. Journal of Geographic Information System,4, 588–596.CrossRefGoogle Scholar
  79. Parysow, P., Wang, G., Gertner, G., & Anderson, A. (2003). Spatial uncertainty analysis for mapping soil erodibility based on joint sequential simulation. CATENA,53, 65–78.CrossRefGoogle Scholar
  80. Prasannakumar, V., Shiny, R., Geetha, N., & Vijith, H. (2011). 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. Environmental Earth Sciences,64, 965–972.CrossRefGoogle Scholar
  81. Rahaman, S., Aruchamy, S., Jegankumar, R., & Ajeez, S. (2015). Estimation of annual average soil loss, based on RUSLE model in Kallar watershed, Bhavani basin, Tamil Nadu, India. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, II-2/W2, 207–214.CrossRefGoogle Scholar
  82. Ramu, M., & Mahalingam, B. (2015). Quantification of soil erosion by water using GIS and remote sensing techniques: A study of Pandavapura Taluk, Mandya district, Karnataka, India. ARPN Journal of Earth Sciences,4(2), 103–110.Google Scholar
  83. Ranzi, R., Le, T. H., & Rulli, M. C. (2012). A RUSLE approach to model suspended sediment load in the Lo river (Vietnam): Effects of reservoirs and land use changes. Journal of Hydrology,422–423, 17–29.CrossRefGoogle Scholar
  84. Rao, Y., (1981). Evaluation of cropping management factor in universal soil loss equation under natural rainfall condition of Kharagpur, India. Bangkok, Proceedings of the Southeast Asian Regional Symposium on Problems of Soil Erosion and Sedimentation, Asian Institute of Technology (AIT), (p. 241–254).Google Scholar
  85. Renard, K., Foster, G., Weesies, G. & McCool, (1997). Predicting soil erosion by water: a guide to conservation planning with the Revised Universal Soil Loss Equation RUSLE. Handbook No. 703. US Department of Agriculture, (pp. 404).Google Scholar
  86. Renard, K., & Freimund, J. (1994). Using monthly precipitation data to estimate the R-factor in the RUSLE. Journal of Hydrology,157, 287–306.CrossRefGoogle Scholar
  87. Römkens, M., Prasad, S., & Poesen, J. (1986). Soil erodibility and properties (pp. 492–504). s.n.: Hamburg.Google Scholar
  88. Roose, E., (1975). Érosion et ruissellement en afrique de l’ouest vingt années de mesures en petites parcelles expérimentales. cyclo: orstom.Google Scholar
  89. Roose, E., (1996). Land Husbandry-Components and strategy, s.l.: FAO Corporate Document Repository 70 FAO Soil Bulletin ISBN 92-5-103451-6. Chapter 5.Google Scholar
  90. Rosewell, C. (1993). Soilloss—A program to assist in the selection of the management practices to reduce erosion (2nd ed.). s.l.: Soil Conservation Service of New South Wales.Google Scholar
  91. Rozos, D., Skilodimou, H. D., Loupasakis, C., & Bathrellos, G. D. (2013). Application of the revised universal soil loss equation model on landslide prevention. An example from N. Euboea (Evia) Island, Greece. Environmental Earth Sciences,70, 3255–3266.CrossRefGoogle Scholar
  92. Samanta, R., Bhunia, G., & Shit, P. (2016). Spatial modelling of soil erosion susceptibility mapping in lower basin of Subarnarekha river (India) based on geospatial techniques. Modeling Earth Systems and Environment, 2(99), 1–13.Google Scholar
  93. Santra, P., Goyal, R., Tewari, J., & Roy, M. (2014). Assessment of potential soil loss rate by wind and water erosion in Jodhpur region of western Rajasthan. India: Global Soil Map.Google Scholar
  94. Schwab, G. O., Fangmeier, D. D. & Elliot, W. J., (1994). Soil and Water Conservation Engineering. fourth ed. s.l.:s.n.Google Scholar
  95. Schwab, G., Frevert, R., & Edminster, T. (1981). Soil water conservation engineering (3rd ed.). New York: Wiley.Google Scholar
  96. Secretaria de Agricultura y Recursos Hidraulicos, (1991). Manual de Prediccion de Peridas de Suelo por Erosion, Colegio de Postgraduados, Guadalajara, 115 pp: s.n.Google Scholar
  97. Sewnet, G. H. (2016). USLE and SDR Model Based Sediment Yield Assessment in a GIS and Remote Sensing Environment; A Case Study of Koga Watershed, Upper Blue Nile Basin. Ethiopia. Hydrology Current Research,7(2), 1–10.Google Scholar
  98. Sharpley, A., & Williams, J. (1990). EPIC-erosion/productivity impact calculator: 1. model documentation (p. 1768). Washington: US Department of Agriculture Technical Bulletin No.Google Scholar
  99. Shi, Z. H., Cai, C. F., Ding, S. W., Wang, T. W., & Chow, T. L. (2004). Soil conservation planning at the small watershed level using RUSLE with GIS: a case study in the Three Gorge Area of China. CATENA,55, 33–48. Scholar
  100. Shinde, V., Tiwari, K., & Singh, M. (2010). Prioritization of micro watersheds on the basis of soil erosion hazard using remote sensing and geographic information system. International Journal of Water Resources and Environmental Engineering,2(3), 130–136.Google Scholar
  101. Shit, P., Nandi, A. & Bhunia, G. (2015). Soil erosion risk mapping using RUSLE model on jhargram sub-division at West Bengal in India. Modeling Earth Systems and Environment. Scholar
  102. Sigalos, G., Loukaidi, V., Dasaklis, S. & Alexouli-Livaditi, A., (2010). Assessment of the quantity of the material transported downstream of Sperchios river, central Greece, Patras: Bulletin of the Geological Society of Greece, 2010, Proceedings of the 12th International Congress.Google Scholar
  103. Simms, A. D., Woodroffe, C. D. & Jones, B. G. (2003). Application of RUSLE for erosion management in a coastal catchment, Southern NSW. International Congress on Modelling and Simulation, July, Volume 2, (pp. 678–683).Google Scholar
  104. Singh, G. (1981). Soil loss and pre-diction research in India. Dehra Dun: Central Soil and Water Conservation Research Training Institute.Google Scholar
  105. Sorrentino, G. (2001). Indagine regionale sulla stima dell’aggressività della pioggia nello studio dell’erosione idrica (p. 222). Cosenza: Thesis, Università degli Studi della Calabria, Facoltà di Ingegneria.Google Scholar
  106. Swarnkar, S., Malini, A., Tripathi, S., & Sinha, R. (2017). Assessment of uncertainties in soil erosion and sediment yield estiamtes at ungauged basins: an application to the Garra River basin. India. Hydrology and Earth System Sciences, 22(4), 2471–2485.CrossRefGoogle Scholar
  107. Terranova, O., Antronico, L., Coscarelli, R., & Iaquinta, P. (2009). Soil erosion risk scenarios in the Mediterranean environment using RUSLE and GIS: An application model for Calabria (southern Italy). Geomorphology,112, 228–245.CrossRefGoogle Scholar
  108. Tew, K. (1999). Production of Malaysian soil erodibility nomograph in relation to soil erosion issues. 27 ed. Jalan SS 14/2D, 47500 Subang Jaya, Selangor DarulEhsan, Malaysia: VT SoilErosion Research & Consultancy.Google Scholar
  109. Tirkey, A. S., Pandey, A., & Nathawat, M. (2013). Use of satellite data, GIS and RUSLE for estimation of average annual soil loss in daltonganj watershed of Jharkhand (India). Journal of Remote Sensing Technology,1(1), 20–30.CrossRefGoogle Scholar
  110. Torri, D., Poesen, J., & Borselli, L. (1997). Predictability and uncertainty of the soil erodibility factor using a global dataset. CATENA,31, 1–22.CrossRefGoogle Scholar
  111. USDA, (1951). Soil survey manual. In Soil Conservation Service, Soil Survey Staff, U.S. Dept. of Agricultural handbook 18. (p. 503). Washington D.C., USA: U.S. Govt. Print Office.Google Scholar
  112. USDA-SCS. (1972). ‘Hydrology’ in SCS national engineering handbook, section 4. Washington DC: US Department of Agriculture.Google Scholar
  113. Van, R. R., Hamilton, M., & Hickey, R. (2001). Estimating the LS Factor for RUSLE through iterative slope length processing of digital elevation data within ArcInfo Grid. Cartography,30(1), 27–35.CrossRefGoogle Scholar
  114. Van, D. K. J., Jones, R., & Montanarella, L. (2000). Soil erosion risk assessment in Europe. Luxembourg: Office for Official Publications of the European Communities.Google Scholar
  115. Vezina, K., Bonn, F., & Pham, V. (2006). Agricultural land-use patterns and soil erosion vulnerability of watershed units in Vietnam’s northern highlands. Landscape Ecology,21(8), 1311–1325.CrossRefGoogle Scholar
  116. Vinay, M., Ramu & Mahalingam, B., (2015). Quantification of soil erosion by water using GIS and remote sensing techniques: A study of Pandavapura Taluk, Mandya District, Karnataka. India. ARPN Journal of Earth Sciences, 4(2), 103–110.Google Scholar
  117. Wener, C. (1981). Soil conservation in Kenya. Nairobi: Ministry of Agriculture, Soil Conservation Extension Unit.Google Scholar
  118. Wischmeier, W., & Smith, D. (1957). Factors affecting sheet and rill erosion. Transactions. American Geophysical Union,38(6), 889–896.CrossRefGoogle Scholar
  119. Wischmeier, W. & Smith, D., 1978. Predicting rainfall erosion losses—A guide to conservation planning. Agriculture Handbook No.537, pp. 3–4.Google Scholar
  120. Wischmeier, W. & Smith, D., (1978). Predicting rainfall erosion lossesA guide to conservation planning. s.l.:USDA Agricultural Handbook No. 537.Google Scholar
  121. Xu, L., Xu, X., & Meng, X. (2013). Risk assessment of soil erosion in different rainfall scenarios by RUSLE model coupled with information diffusion model: A case study of Bohai Rim, China. CATENA,100, 74–82.CrossRefGoogle Scholar
  122. Xu, L., et al. (2007). Simple method of estimating rainfall erosivity under different rainfall amount of Beijing. Research of Soil and Water Conservation,6, 398–402.Google Scholar
  123. Yang, Y. & Shi, D., (1994). Study on Soil Erosion in the Three Gorge Area of the Changjiang River.Google Scholar
  124. Yu, B., & Rosewell, C. J. (1998). Rainfall erosivity and its estimation for Australia’s tropics. Australian Journal of Soil Research,36, 143–165.CrossRefGoogle Scholar
  125. Yue-Qing, X., et al. (2008). Adapting the RUSLE and GIS to model soil erosion risk in a mountains karst watershed, Guizhou Province, China. Environmental Monitoring and Assessment,141, 275–286.CrossRefGoogle Scholar
  126. Zarris, D., Vlastara, M., & Panagoulia, D. (2011). Sediment delivery assessment for a transboundary mediterranean catchment: The example of Nestos River Catchment. Water Resources Management,25, 3785–3803.CrossRefGoogle Scholar
  127. Zhao, W., Fu, B., Chen, L. & Zhang, Q. (2004). Estimation of rainfall erosivity using rainfall amount: a case study in hilly and gully area of Loess Plateau in northern Shaanxi. Land Change and Eco-environmental Construction. Google Scholar

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© Indian Society of Remote Sensing 2020

Authors and Affiliations

  1. 1.Department of Mining EngineeringIndian Institute of Engineering Science and Technology, ShibpurHowrahIndia

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