Estimate the annual soil loss in Kummattipatti Nadi watershed using rusle model through geospatial technology


Soil erosion and soil loss is one of the common problems threatening the environment. This degrading phenomenon declines the soil fertility and significantly affects the agricultural activity. As a consequence, the productivity of soil is affected unquestionably. In this reason, there is a basic need to take up conservation and management measures which can be applied to check further soil erosion. Even though, soil erosion is a mass process spread cross the watershed, it is not economically viable to implement conservation techniques to the entire watershed. However, a method is a pre-requisite to identify the most vulnerable areas and quantify the soil erosion. In this study, Revised Universal Soil Loss Equation (RUSLE) has been accepted to estimate soil erosion in the Kummattipatti Nadi watershed part of the Coimbatore district of Tamil Nadu, India. This model has several parameters including runoff-rainfall erosivity factor (R), soil erodability Factor (K), topographic factor (LS), cropping management factor (C), and support practice factor (P). All these layers are prepared through geographical information system (GIS) by using various data sources and data preparation methods. The results of the study shows that the annual average soil loss within the watershed is about 6 t/ha/yr (metric ton per hectare per year). Higher soil erosion is observed in the land use classes of gullied wasteland, open scrub forest and degraded plantation. The soil erosion risk is extremely higher on the steep slopes and adjoining foothills. The proper conservation and management strategies has to be implement in this watershed for the development.

Keyword : soil erosion, soil loss, erosivity, erodability, erosion risk, RUSLE, remote sensing and GIS

How to Cite
Shaikh, S., Palanisamy, M., & Sheik Mohideen, A. R. (2020). Estimate the annual soil loss in Kummattipatti Nadi watershed using rusle model through geospatial technology. Geodesy and Cartography, 46(2), 75-82.
Published in Issue
Jul 14, 2020
Abstract Views
PDF Downloads
Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.


Angima, S. D., Stott, D. E., O’Neill, M. K., Ong, C. K., & Weesies, G. A. (2003). Soil erosion prediction using RUSLE for central Kenyanhighland conditions. Agriculture, Ecosystems & Environment, 97, 295–308.

Balasubramani, K., Veena Mohan, Kumaraswamy, K., & Saravanabavan, V. (2015). Estimation of soil erosion in a semiarid watershed of Tamil Nadu (India) using revised universal soil loss equation (rusle) model through GIS. Modeling Earth Systems and Environment, 1, 10.

Biesemans, J., Meirvenne, M. V., & Gabriels, D. (2000). Extending the RUSLE with the Monte Carlo error propagation technique to predict long-term average oV-site sediment accumulation. Journal of Soil and Water Conservation, 55, 35–42.

Benkobi, L., Trlica, M. J., & Smith, J. L. (1994). Evaluation of a re. ned surface cover subfactor for use in RUSLE. Journal of Range Management, 47, 74–78.

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 Resource Management, 22(12), 1783–1798.

Desmet, P. J. J., & Govers, G. (1996). A GIS procedure for automatically calculating the USLE LS factor on topographically complex landscape units. Journal of Soil and Water Conservation, 51(5), 427–433.

Dunn, M., & Hickey, R. (1998). The effect of slope algorithms on slope estimates within a GIS, Cartography, 27(1), 9–15.

Foster, G. R., & Wischmeier, W. H. (1974). Evaluating irregular slopes for soil loss prediction, Transactions of the American Society of Agricultural Engineers, 17(2), 305–309.

Hickey, R. (2000). Slope angle and slope length solutions for GIS. Cartography, 29(1), 1–8.

Kouli, M., Soupios, P., & Vallianatos, F. (2009). Soil erosion prediction using the revised universal soil loss equation (RUSLE) in a GIS framework, Chania, Northwestern Crete, Greece. Environmental Geology, 57(3), 483–497.

Mhangara, P., Kakembo, V., & Lim, K. (2012). Soil erosion risk assessment of the Keiskamma catchment, South Africa using GIS and remote sensing. Environmental Earth Science, 65(7), 2087–2102.

Moore, I., & Burch, G. (1986). Physical basis of the length-slope factor in the Universal Sol Loss Equation. Soil Society of America Journal, 50, 194–1298.

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.

Prasannakumar, V., Vijith, H., Abinod, S., & Geetha, N. (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.

Rahaman, S. A., Aruchamy, S., Jegankumar, R., & Ajeez, S. A. (2015). Estimation of annual average soil loss based on RUSLE model in Kallar watershed, Bhavani basin, Tamil Nadu, India. ISPRS Annals Photogrammertry, Remote Sensing and Spatial Information Sciences, II-2/W2, 207–214.

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.

Renard, K. G., & Ferreira, V. A. (1993). RUSLE model description and database sensitivity. Journal of Environmental Quality, 22, 458–466.

Renard, K. G., Foster, G. R., Weesies, G. A., McCool, D. K., & Yoder, D. C. (1996). Predicting soil erosion by water: a guide to conservation Planning with the revised universal soil loss equation (RUSLE) (Agriculture Handbook No. 703). USA Department of Agriculture, Washington.

Sharma, A., Tiwari, K. N., & Bhadoria, P. B. S. (2011). Effect of land use land cover change on soil erosion potential in an agricultural Watershed. Environmental Monitoring and Assessment, 173(1–4), 789–801.

Schwab, G. O., Fangmeier, D. D., Elliot, W. J., & Frevert, R. K. (1993). Soil and water conservation engineering (4 ed., pp. 68–91). John Wiley and Sons, Inc.

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(1), 33–48.

Singh, G., Babu, R., Narain, P., Bhushan, L. S., & Abrol, I. P. (1981). Soil loss prediction research in India (Bull. No. T12/D-9). Central Soil and Water Conservation Research Training Institute, Dehradun.

Van der Knijff, J. M., Jones, R. J. A., & Montanarella, L. (2000). Soil erosion risk assessment in Europe (EUR 19044 EN). Ispra: European Soil Bureau, Joint Research Centre.

Van Remortel, R., Hamilton, M., & Hickey, R. (2001). Estimating the LS factor for RUSLE through iterative slope length processing of digital elevation data. Cartography, 30(1), 27–35.

Vijith, H., Suma, M., Rekha, V. B., Shiju, C., & Rejith, P. G. (2012). An assessment of soil erosion probability and erosion rate in a tropical mountainous watershed using remote sensing and GIS. Arabian Journal of Geosciences, 5(4), 797–805.

Wischmeier, W. H., & Smith, D. D. (1978). Predicting rainfall erosion, soil losses, A Guide to conservation planning (Agriculture handbook No. 537). Department of Agriculture, USDA, Washington, DC.

Yang, D., Kanae, S., Oki, K., Koike, K., Musiake, K. (2003). Global potential soil erosion with reference to land use and climate changes. Hydrological Process, 17, 2913–2928.