Eurasian Journal of Soil Science

Volume 6, Issue 2, Apr 2017, Pages 92-105
DOI: 10.18393/ejss.286442
Stable URL: http://ejss.fess.org/10.18393/ejss.286442
Copyright © 2017 The authors and Federation of Eurasian Soil Science Societies



Modelling soil erosion risk in a mountainous watershed of Mid-Himalaya by integrating RUSLE model with GIS

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Kalambukattu,J., Kumar,S., 2017. Modelling soil erosion risk in a mountainous watershed of Mid-Himalaya by integrating RUSLE model with GIS. Eurasian J Soil Sci 6(2):92-105. DOI : 10.18393/ejss.286442
Kalambukattu,J.,,& Kumar,S. 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. DOI : 10.18393/ejss.286442
Kalambukattu,J.,, and ,Kumar,S."Modelling soil erosion risk in a mountainous watershed of Mid-Himalaya by integrating RUSLE model with GIS" Eurasian Journal of Soil Science, 6.2 (2017):92-105. DOI : 10.18393/ejss.286442
Kalambukattu,J.,, and ,Kumar,S. "Modelling soil erosion risk in a mountainous watershed of Mid-Himalaya by integrating RUSLE model with GIS" Eurasian Journal of Soil Science,6(Apr 2017):92-105 DOI : 10.18393/ejss.286442
JG,Kalambukattu.S,Kumar "Modelling soil erosion risk in a mountainous watershed of Mid-Himalaya by integrating RUSLE model with GIS" Eurasian J. Soil Sci, vol.6, no.2, pp.92-105 (Apr 2017), DOI : 10.18393/ejss.286442
Kalambukattu,Justin ;Kumar,Suresh Modelling soil erosion risk in a mountainous watershed of Mid-Himalaya by integrating RUSLE model with GIS. Eurasian Journal of Soil Science, (2017),6.2:92-105. DOI : 10.18393/ejss.286442

How to cite

Kalambukattu, J., G. Kumar, S., G.2017. Modelling soil erosion risk in a mountainous watershed of Mid-Himalaya by integrating RUSLE model with GIS. Eurasian J. Soil Sci. 6(2): 92-105. DOI : 10.18393/ejss.286442

Author information

Justin Kalambukattu , Agriculture and Soils Department, Indian Institute of Remote Sensing, Uttarakhand, India Dehradun, India
Suresh Kumar , Agriculture and Soils Department, Indian Institute of Remote Sensing, Uttarakhand, India

Publication information

Article first published online : 09 Sep 2016
Manuscript Accepted : 01 Sep 2016
Manuscript Received: 28 Jun 2016
DOI: 10.18393/ejss.286442
Stable URL: http://ejss.fesss.org/10.18393/ejss.286442

Abstract

Soil erosion is one of the major cause of land degradation and is a serious threat to food security and agricultural sustainability. Revised Universal Soil Loss equation (RUSLE) model using remote sensing (RS) and Geographical Information Systems (GIS) inputs was employed to estimate soil erosion risk in a watershed of mid-Himalaya in Uttarakhand state, India. Spatial distribution of soil erosion risk area in the watershed was estimated by integrating various RUSLE factors (R, K, LS, C, P) in raster based GIS environment. RUSLE model factor maps were generated using remote sensing satellite data (IRS LISS III and LANDSAT-8) and Digital elevation model. Agriculture (59%) was found to be the dominant land use system followed by scrub land (20%) in the watershed. Rainfall erosivity (R) factor was estimated using past 23 years rainfall data. SRTM DEM was used to generate slope length –steepness (LS) factor in this highly rugged terrain. Nearly 70% of the watershed is having steep to moderately steep slope (>40%). Satellite data was interpreted to prepare physiographic map at 1:50,000 scale. Surface soil samples collected in each physiograpohic unit was analyzed to generate soil erodibility (K) map. Soil erodibility factor ranged from 0.033 to 0.077 in the watershed. Soil erosion risk analysis showed that 36.25%, 9.31%, 15.80%, 15.27%, 11.46% and 11.89% area of watershed falls under very low, low, moderate, moderate high, high and very high erosion risk classes respectively. The average annual erosion rate was predicted to be 65.84 t/ha/yr. The soil erosion rates were predicted to vary from 3.24 t/ha/yr in dense mixed forest cover to 87.98 t/ha/yr in open scrub land. The soil erosion map thus generated employing remote sensing and GIS techniques, can serve as a tool for deriving strategies for effective planning and implementation of various management and conservation practices for soil and water conservation in the watershed.

Keywords

Himalaya, watershed, soil erosion, revised universal soil loss equation (RUSLE) model, remote sensi

Corresponding author

References

Adediji, A., Tukur, A.M., Adepoju, K.A., 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.

Angima, S.D., Stott, D.E., O’Neill, M.K., Ong, C.K., Weesies, G.A., 2003. Soil erosion prediction using RUSLE for central Kenyan highland conditions. Agriculture, Ecosystems and Environment 97(1-3): 295-308.

Ashiagbor, G., Forkuo, E.K., Laari, P., Aabeyir, R., 2013. Modeling soil erosion using RUSLE and GIS tools. International Journal of Remote Sensing & Geoscience 2(4): 1-17.

Babu, R., Dhyani, B.L., Kumar, N., 2004. Assessment of erodibility status and refined Iso- Erodent Map of India. Indian Journal of Soil Conservation 32(2): 171–177.

Boggs, G., Devonport, C., Evans, K., Puig, P., 2001. GIS-based rapid assessment of erosion risk in a small catchment in the wet/dry tropics of Australia. Land Degradation and Development 12(5): 417-434.

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.

Dabral, P.P., Baithuri, N., Pandey, A., 2008. Soil erosion assessment in a hilly catchment of north eastern India using USLE, GIS and Remote Sensing. Water Resources Management 22(12): 1783–1798.

Elangovan, A.B., Seetharaman, R., 2011. Estimating Rainfall Erosivity of the Revised Universal Soil Loss Equation from daily rainfall depth in Krishanagiri Watershed region of Tamil Nadu, India. International Conference on Environmental and Computer Science IPCBEE, IACSIT Press, Vol. 19. Singapore.

FAO. 2011. The state of the world’s land and water resources for food and agriculture (SOLAW) ‐ Managing systems at risk. Food and Agriculture Organization of the United Nations, Rome, Italy.

Farhan, Y., Zregat, D., Farhan, I., 2013. Spatial Estimation of Soil Erosion Risk Using RUSLE Approach, RS, and GIS Techniques: A Case Study of Kufranja Watershed, Northern Jordan. Journal of Water Resource and Protection 5(12): 1247-1261.

Garde, R. J., Kothyari, U.C., 1987. Sediment yield estimation. Journal Irrigation and Power (India) 44(3): 97-123.

Haile, G.W., Fetene, M., 2011. Assessment of soil erosion hazard in Kilie catchment, East Shoa, Ethiopia. Land Degradation and Development 23(3): 293-306.

Hofer, T., 1998. Do land use changes in the Himalayas affect downstream flooding? Traditional understanding and new evidences. Memoir Geological society of India 19: 119-141.

Hyeon, S.K., Julien, P.Y., 2006.  Soil erosion modeling using RUSLE and GIS on the IMHA watershed. Water Engineering Research 7 (1): 29-41

IFPRI,. 2012. 2011 Global Food Policy Report. International Food Policy Research Institute, Washington, DC. USA. Available at: http://www.ifpri.org/cdmref/p15738coll2/id/126897/filename/127108.pdf [access date: 05.08.2016]

Ives, J.D., Messerli, B., 1989. The Himalayan Dilemma- reconciling development and conservation. United Nations University, Routledge, New York, USA.

Jain, S.K., Kumar, S., Varghese, J., 2001. Estimation of soil erosion for a Himalayan watershed using GIS technique. Water Resources Management 15(1): 41-54.

Jasrotia, A.S., Singh, R., 2006. Modeling runoff and soil erosion in a catchment area, using the GIS, in the Himalayan region, India. Environmental Geology 51(1): 29-37.

Krishna Bahadur, K.C., 2009. Mapping soil erosion susceptibility using remote sensing and GIS: a case of the Upper Nam Wa Watershed, Nan Province, Thailand. Environmental Geology 57(3): 695-705.

Kumar, S., Kushwaha, S.P.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.

Lal, R., Stewart, B.A., 1990. Advances in Soil Science. Vol. 11, Soil Degradation. Springer Verlag, New York, USA. 345p.

Lee, G.S., Lee, K.H., 2006. Scaling effect for estimating soil loss in the RUSLE model using remotely sensed geospatial data in Korea. Hydrology and Earth System Sciences Discussions 3: 135-157.

Lim, K.J., Sagong, M., Engel, B.A., Tang, Z., Choi, J.,  Kim, K.S., 2005. GIS based sediment assessment tool. Catena 64(1): 61–80.

Lu, D., Li, G., Valladares, G. S., Batistella, M., 2004. Mapping soil erosion risk in Rondônia, Brazilian Amazonia: using RUSLE, remote sensing and GIS. Land Degradation & Development 15 (5): 499-512.

Millward, A.A., Mersey, J.E., 1999. Adapting the RUSLE to model soil erosion potential in mountainous tropical watershed. Catena 38 (2): 109-129.  

Mitasova, H., Hofierka, J., Zlocha, M., Iverson, L.R., 1996. Modeling topographic potential for erosion and deposition using GIS. International Journal of Geographical Information Systems 10(5): 629-641.

Moore, I.D., Burch, G.J., 1986. Physical basis of the length-slope factor in the universal soil loss equation. Soil Science Society of America Journal 50(5): 1294–1298.

Morgan, R.P.C., 2005. Soil Erosion and Conservation, 3rd Edition. Blackwell Publishing, Malden, USA. 303p.

Pandey, A., Chowdary, V.M., Mai, B.C., 2007. Identification of critical erosion prone areas in the small agricultural watershed using USLE, GIS and remote sensing. Water Resources Management 21(4): 729- 746.

Pimentel, D., Harvey, C., Resosudarmo, P., Sinclair, K., Kurz, D., Mcnair, M., Crist, S., Shpritz, L., Fitton, L., Saffouri, R., Blair, R., 1995. Environmental and economic costs of soil erosion and conservation benefits. Science 267 (5201): 1117-1123.

Poreba, G.J., Prokop, P., 2011. Estimation of soil erosion on cultivated fields on the hilly Meghalaya plateau, north-east India. Geochronometria 38 (1): 77-84.

Prasannakumar, V H. Vijith, S. Abinod, N. Geetha., 2012. 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. Geoscience Frontiers 3(2): 209-215.

Rao, Y.P., 1981. Evaluation of cropping management factor in universal soil loss equation under natural rainfall condition of Kharagpur, India.  In: Proceedings of Southeast Asian regional symposium on problems of soil erosion and sedimentation, Asian Institute of Technology, Bangkok, p. 241-254.

Renard, K.G., Foster, G.R., Weesies, G.A., McCool, D.K., Yoder, D.C., 1997. .Predicting soil erosion by water: A guide to conservation planning with the revised universal soil loss equation (RUSLE). U.S. Department of Agriculture, Agricultural Research Service, Agriculture Handbook No. 703,  Washington DC, USA. 384p.

Rio+20, 2012. Report of the United Nations Conference on Sustainable Development. Rio de Janeiro, Brazil 20–22 June 2012

Sati, S.P., Sundriyal, Y.P., Naresh, R., Surekha, D., 2011. Recent landslides in Uttarakhand: nature’s fury or human folly. Current Science 100 (11): 1617-1620.

Shiono, T., Kamimura, K., Okushima, S., Fukumoto, M., 2002. Soil loss estimation on a local scale for soil conservation planning. Japan Agricultural Research Quarterly 36(3): 157-161.

Singh, G., Chandra, S., Babu, R., 1981. Soil loss and prediction research in India. Central Soil and Water Conservation Research and Training Institute, Bulletin No.T-12/D9, Dehra Dun.

Sun, W., Shao, Q., Liu, J., Zhai, J., 2014. Assessing the effects of land use and topography on soil erosion on the Loess Plateau in China. Catena 121: 151-163.

Tian, Y.C., Zhou, Y.M., Wu, B.F., Zhou, W.F., 2009. Risk assessment of water soil erosion in upper basin of Miyun Reservoir, Beijing, China. Environonment Geology 57(4): 937–942.

Tirkey, A.S., Pandey, A.C., Nathawat, M.S., 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.

UNCCD. 1994. Elaboration of an International convention to combat desertification in countries experiencing serious drought and/or desertification, particularly in Africa. United Nations, General Assembly. A/AC.241/27 12 September 1994, Article 2. Available at: http:// www.unccd.int/Lists/SiteDocumentLibrary/conventionText/conv-eng.pdf [access date: 05.08.2016]

USDA-SCS , 1972. National Engineering Handbook, Section 4, Hydrology Chapter 21. Design Hydrographs. US Department of Agriculture, Washington DC, USA. Available at: http://directives.sc.egov.usda.gov/OpenNonWebContent.aspx?content=18393.wba [access date: 05.08.2016]

Wani, S.P., Garg, K,K., 2009. Watershed management concept and principles. Available at: http://oar.icrisat.org/3914/1/1._Watershed_Management_Concept.pdf [access date: 05.08.2016]

Wischmeier, W.H., Smith, D.D., 1965. Predicting rainfall-erosion losses from cropland east of the rocky mountains: Guide for selection of practices for soil and water conservation. U.S. Department of Agriculture, Agricultural Research Service, Issue 282 of Agriculture Handbook. Washington DC, USA. p. 47.

Wischmeier, W.H., Smith, D.D., 1978. Predicting rainfall erosion losses: A guide to conservation planning. U.S. Department of Agriculture, Agricultural Research Service, Issue 537 of Agriculture Handbook. Washington DC, USA. p. 58.

Abstract

Soil erosion is one of the major cause of land degradation and is a serious threat to food security and agricultural sustainability. Revised Universal Soil Loss equation (RUSLE) model using remote sensing (RS) and Geographical Information Systems (GIS) inputs was employed to estimate soil erosion risk in a watershed of mid-Himalaya in Uttarakhand state, India. Spatial distribution of soil erosion risk area in the watershed was estimated by integrating various RUSLE factors (R, K, LS, C, P) in raster based GIS environment. RUSLE model factor maps were generated using remote sensing satellite data (IRS LISS III and LANDSAT-8) and Digital elevation model. Agriculture (59%) was found to be the dominant land use system followed by scrub land (20%) in the watershed. Rainfall erosivity (R) factor was estimated using past 23 years rainfall data. SRTM DEM was used to generate slope length –steepness (LS) factor in this highly rugged terrain. Nearly 70% of the watershed is having steep to moderately steep slope (>40%). Satellite data was interpreted to prepare physiographic map at 1:50,000 scale. Surface soil samples collected in each physiograpohic unit was analyzed to generate soil erodibility (K) map. Soil erodibility factor ranged from 0.033 to 0.077 in the watershed. Soil erosion risk analysis showed that 36.25%, 9.31%, 15.80%, 15.27%, 11.46% and 11.89% area of watershed falls under very low, low, moderate, moderate high, high and very high erosion risk classes respectively. The average annual erosion rate was predicted to be 65.84 t/ha/yr. The soil erosion rates were predicted to vary from 3.24 t/ha/yr in dense mixed forest cover to 87.98 t/ha/yr in open scrub land. The soil erosion map thus generated employing remote sensing and GIS techniques, can serve as a tool for deriving strategies for effective planning and implementation of various management and conservation practices for soil and water conservation in the watershed.

Keywords: Himalaya, watershed, soil erosion, revised universal soil loss equation (RUSLE) model, remote sensing, GIS.

References

Adediji, A., Tukur, A.M., Adepoju, K.A., 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.

Angima, S.D., Stott, D.E., O’Neill, M.K., Ong, C.K., Weesies, G.A., 2003. Soil erosion prediction using RUSLE for central Kenyan highland conditions. Agriculture, Ecosystems and Environment 97(1-3): 295-308.

Ashiagbor, G., Forkuo, E.K., Laari, P., Aabeyir, R., 2013. Modeling soil erosion using RUSLE and GIS tools. International Journal of Remote Sensing & Geoscience 2(4): 1-17.

Babu, R., Dhyani, B.L., Kumar, N., 2004. Assessment of erodibility status and refined Iso- Erodent Map of India. Indian Journal of Soil Conservation 32(2): 171–177.

Boggs, G., Devonport, C., Evans, K., Puig, P., 2001. GIS-based rapid assessment of erosion risk in a small catchment in the wet/dry tropics of Australia. Land Degradation and Development 12(5): 417-434.

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.

Dabral, P.P., Baithuri, N., Pandey, A., 2008. Soil erosion assessment in a hilly catchment of north eastern India using USLE, GIS and Remote Sensing. Water Resources Management 22(12): 1783–1798.

Elangovan, A.B., Seetharaman, R., 2011. Estimating Rainfall Erosivity of the Revised Universal Soil Loss Equation from daily rainfall depth in Krishanagiri Watershed region of Tamil Nadu, India. International Conference on Environmental and Computer Science IPCBEE, IACSIT Press, Vol. 19. Singapore.

FAO. 2011. The state of the world’s land and water resources for food and agriculture (SOLAW) ‐ Managing systems at risk. Food and Agriculture Organization of the United Nations, Rome, Italy.

Farhan, Y., Zregat, D., Farhan, I., 2013. Spatial Estimation of Soil Erosion Risk Using RUSLE Approach, RS, and GIS Techniques: A Case Study of Kufranja Watershed, Northern Jordan. Journal of Water Resource and Protection 5(12): 1247-1261.

Garde, R. J., Kothyari, U.C., 1987. Sediment yield estimation. Journal Irrigation and Power (India) 44(3): 97-123.

Haile, G.W., Fetene, M., 2011. Assessment of soil erosion hazard in Kilie catchment, East Shoa, Ethiopia. Land Degradation and Development 23(3): 293-306.

Hofer, T., 1998. Do land use changes in the Himalayas affect downstream flooding? Traditional understanding and new evidences. Memoir Geological society of India 19: 119-141.

Hyeon, S.K., Julien, P.Y., 2006.  Soil erosion modeling using RUSLE and GIS on the IMHA watershed. Water Engineering Research 7 (1): 29-41

IFPRI,. 2012. 2011 Global Food Policy Report. International Food Policy Research Institute, Washington, DC. USA. Available at: http://www.ifpri.org/cdmref/p15738coll2/id/126897/filename/127108.pdf [access date: 05.08.2016]

Ives, J.D., Messerli, B., 1989. The Himalayan Dilemma- reconciling development and conservation. United Nations University, Routledge, New York, USA.

Jain, S.K., Kumar, S., Varghese, J., 2001. Estimation of soil erosion for a Himalayan watershed using GIS technique. Water Resources Management 15(1): 41-54.

Jasrotia, A.S., Singh, R., 2006. Modeling runoff and soil erosion in a catchment area, using the GIS, in the Himalayan region, India. Environmental Geology 51(1): 29-37.

Krishna Bahadur, K.C., 2009. Mapping soil erosion susceptibility using remote sensing and GIS: a case of the Upper Nam Wa Watershed, Nan Province, Thailand. Environmental Geology 57(3): 695-705.

Kumar, S., Kushwaha, S.P.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.

Lal, R., Stewart, B.A., 1990. Advances in Soil Science. Vol. 11, Soil Degradation. Springer Verlag, New York, USA. 345p.

Lee, G.S., Lee, K.H., 2006. Scaling effect for estimating soil loss in the RUSLE model using remotely sensed geospatial data in Korea. Hydrology and Earth System Sciences Discussions 3: 135-157.

Lim, K.J., Sagong, M., Engel, B.A., Tang, Z., Choi, J.,  Kim, K.S., 2005. GIS based sediment assessment tool. Catena 64(1): 61–80.

Lu, D., Li, G., Valladares, G. S., Batistella, M., 2004. Mapping soil erosion risk in Rondônia, Brazilian Amazonia: using RUSLE, remote sensing and GIS. Land Degradation & Development 15 (5): 499-512.

Millward, A.A., Mersey, J.E., 1999. Adapting the RUSLE to model soil erosion potential in mountainous tropical watershed. Catena 38 (2): 109-129.  

Mitasova, H., Hofierka, J., Zlocha, M., Iverson, L.R., 1996. Modeling topographic potential for erosion and deposition using GIS. International Journal of Geographical Information Systems 10(5): 629-641.

Moore, I.D., Burch, G.J., 1986. Physical basis of the length-slope factor in the universal soil loss equation. Soil Science Society of America Journal 50(5): 1294–1298.

Morgan, R.P.C., 2005. Soil Erosion and Conservation, 3rd Edition. Blackwell Publishing, Malden, USA. 303p.

Pandey, A., Chowdary, V.M., Mai, B.C., 2007. Identification of critical erosion prone areas in the small agricultural watershed using USLE, GIS and remote sensing. Water Resources Management 21(4): 729- 746.

Pimentel, D., Harvey, C., Resosudarmo, P., Sinclair, K., Kurz, D., Mcnair, M., Crist, S., Shpritz, L., Fitton, L., Saffouri, R., Blair, R., 1995. Environmental and economic costs of soil erosion and conservation benefits. Science 267 (5201): 1117-1123.

Poreba, G.J., Prokop, P., 2011. Estimation of soil erosion on cultivated fields on the hilly Meghalaya plateau, north-east India. Geochronometria 38 (1): 77-84.

Prasannakumar, V H. Vijith, S. Abinod, N. Geetha., 2012. 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. Geoscience Frontiers 3(2): 209-215.

Rao, Y.P., 1981. Evaluation of cropping management factor in universal soil loss equation under natural rainfall condition of Kharagpur, India.  In: Proceedings of Southeast Asian regional symposium on problems of soil erosion and sedimentation, Asian Institute of Technology, Bangkok, p. 241-254.

Renard, K.G., Foster, G.R., Weesies, G.A., McCool, D.K., Yoder, D.C., 1997. .Predicting soil erosion by water: A guide to conservation planning with the revised universal soil loss equation (RUSLE). U.S. Department of Agriculture, Agricultural Research Service, Agriculture Handbook No. 703,  Washington DC, USA. 384p.

Rio+20, 2012. Report of the United Nations Conference on Sustainable Development. Rio de Janeiro, Brazil 20–22 June 2012

Sati, S.P., Sundriyal, Y.P., Naresh, R., Surekha, D., 2011. Recent landslides in Uttarakhand: nature’s fury or human folly. Current Science 100 (11): 1617-1620.

Shiono, T., Kamimura, K., Okushima, S., Fukumoto, M., 2002. Soil loss estimation on a local scale for soil conservation planning. Japan Agricultural Research Quarterly 36(3): 157-161.

Singh, G., Chandra, S., Babu, R., 1981. Soil loss and prediction research in India. Central Soil and Water Conservation Research and Training Institute, Bulletin No.T-12/D9, Dehra Dun.

Sun, W., Shao, Q., Liu, J., Zhai, J., 2014. Assessing the effects of land use and topography on soil erosion on the Loess Plateau in China. Catena 121: 151-163.

Tian, Y.C., Zhou, Y.M., Wu, B.F., Zhou, W.F., 2009. Risk assessment of water soil erosion in upper basin of Miyun Reservoir, Beijing, China. Environonment Geology 57(4): 937–942.

Tirkey, A.S., Pandey, A.C., Nathawat, M.S., 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.

UNCCD. 1994. Elaboration of an International convention to combat desertification in countries experiencing serious drought and/or desertification, particularly in Africa. United Nations, General Assembly. A/AC.241/27 12 September 1994, Article 2. Available at: http:// www.unccd.int/Lists/SiteDocumentLibrary/conventionText/conv-eng.pdf [access date: 05.08.2016]

USDA-SCS , 1972. National Engineering Handbook, Section 4, Hydrology Chapter 21. Design Hydrographs. US Department of Agriculture, Washington DC, USA. Available at: http://directives.sc.egov.usda.gov/OpenNonWebContent.aspx?content=18393.wba [access date: 05.08.2016]

Wani, S.P., Garg, K,K., 2009. Watershed management concept and principles. Available at: http://oar.icrisat.org/3914/1/1._Watershed_Management_Concept.pdf [access date: 05.08.2016]

Wischmeier, W.H., Smith, D.D., 1965. Predicting rainfall-erosion losses from cropland east of the rocky mountains: Guide for selection of practices for soil and water conservation. U.S. Department of Agriculture, Agricultural Research Service, Issue 282 of Agriculture Handbook. Washington DC, USA. p. 47.

Wischmeier, W.H., Smith, D.D., 1978. Predicting rainfall erosion losses: A guide to conservation planning. U.S. Department of Agriculture, Agricultural Research Service, Issue 537 of Agriculture Handbook. Washington DC, USA. p. 58.



Eurasian Journal of Soil Science