Eurasian Journal of Soil Science

Volume 6, Issue 3, Jun 2017, Pages 206-215
DOI: 10.18393/ejss.288350
Stable URL: http://ejss.fess.org/10.18393/ejss.288350
Copyright © 2017 The authors and Federation of Eurasian Soil Science Societies



Estimation of Soil loss by USLE Model using GIS and Remote Sensing techniques: A case study of Muhuri River Basin, Tripura, India

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Bera,A., 2017. Estimation of Soil loss by USLE Model using GIS and Remote Sensing techniques: A case study of Muhuri River Basin, Tripura, India. Eurasian J Soil Sci 6(3):206-215. DOI : 10.18393/ejss.288350
,& Bera,A. (2017). Estimation of Soil loss by USLE Model using GIS and Remote Sensing techniques: A case study of Muhuri River Basin, Tripura, India Eurasian Journal of Soil Science, 6(3):206-215. DOI : 10.18393/ejss.288350
, and ,Bera,A. "Estimation of Soil loss by USLE Model using GIS and Remote Sensing techniques: A case study of Muhuri River Basin, Tripura, India" Eurasian Journal of Soil Science, 6.3 (2017):206-215. DOI : 10.18393/ejss.288350
, and ,Bera,A. "Estimation of Soil loss by USLE Model using GIS and Remote Sensing techniques: A case study of Muhuri River Basin, Tripura, India" Eurasian Journal of Soil Science,6(Jun 2017):206-215 DOI : 10.18393/ejss.288350
A,Bera "Estimation of Soil loss by USLE Model using GIS and Remote Sensing techniques: A case study of Muhuri River Basin, Tripura, India" Eurasian J. Soil Sci, vol.6, no.3, pp.206-215 (Jun 2017), DOI : 10.18393/ejss.288350
Bera,Amit Estimation of Soil loss by USLE Model using GIS and Remote Sensing techniques: A case study of Muhuri River Basin, Tripura, India. Eurasian Journal of Soil Science, (2017),6.3:206-215. DOI : 10.18393/ejss.288350

How to cite

Bera, A., 2017. Estimation of Soil loss by USLE Model using GIS and Remote Sensing techniques: A case study of Muhuri River Basin, Tripura, India. Eurasian J. Soil Sci. 6(3): 206-215. DOI : 10.18393/ejss.288350

Author information

Amit Bera , Department of Geography and Disaster Management, Tripura University, Suryamaninagar, Tripura, India

Publication information

Article first published online : 27 Jan 2017
Manuscript Accepted : 25 Jan 2017
Manuscript Received: 04 Dec 2016
DOI: 10.18393/ejss.288350
Stable URL: http://ejss.fesss.org/10.18393/ejss.288350

Abstract

Soil erosion is a most severe environmental problem in humid sub-tropical hilly state Tripura. The present study is carried out on Muhuri river basin of Tripura state, North east India having an area of 614.54 Sq.km. In this paper, Universal Soil Loss Equation (USLE) model, with Geographic Information System (GIS) and Remote Sensing (RS) have been used to quantify the soil loss in the Muhuri river basin. Five essential parameters such as Runoff-rainfall erosivity factor (R), soil erodibility Factor (K), slope length and steepness (LS), cropping management factor (C), and support practice factor (P) have been used to estimate soil loss amount in the study area. All of these layers have been prepared in GIS and RS platform (Mainly Arc GIS 10.1) using various data sources and data preparation methods. In these study DEM and LISS satellite data have been used. The daily rainfall data (2001-2010) of 6 rain gauge stations have been used to predict the R factor. Soil erodibility (K) factor in Basin area ranged from 0.15 to 0.36. The spatial distribution map of soil loss of Muhuri river basin has been generated and classified into six categories according to intensity level of soil loss. The average annual predicted soil loss ranges between 0 to and 650 t/ha/y. Low soil loss areas (70 t/ha/y) of soil erosion was found along the main course of Muhuri River.

Keywords

Soil loss, erosion risk, USLE, GIS, remote sensing, Muhuri river

Corresponding author

References

Bera, A., Namasudra, P., 2016. Impact of shifting cultivation on the environmental changes in Gumti River Basin, Tripura. International Journal of Recent Scientific Research 7(6): 11771-11774.

Biswal, S.K., 2015. Mathematical model for flow and sediment yield estimation on Tel river basin of India. A dissertation submitted in partial fulfilment of the requirements for the award of the degree of master of technology in civil engineering with specialization in water resources engineering. Department of Civil Engineering National Institute of Technology Rourkela, India. 51p.

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(1): 357-374. 

Devatha, C. P., Deshpande, V., Renukaprasad, M.S., 2015. Estimation of soil loss using USLE model for Kulhan Watershed, Chattisgarh - A case study. Aquatic Procedia 4: 1429-1436. 

El-Swaify, S.A., 1997. Factors affecting soil erosion hazards and conservation needs for tropical steeplands. Soil Technology 11(1): 3-16.

Ganasri, B.P., Ramesh, H., 2016. Assessment of soil erosion by RUSLE model using remote sensing and GIS-A case study of Nethravathi Basin. Geoscience Frontiers 7(6): 953–961.  

Ghosh, K., De, S. K., Bandyopadhyay, S., & Saha, S. (2013). Assessment of soil loss of the Dhalai river basin, Tripura, India using USLE. International Journal of Geosciences 4(1): 11-23.

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.

Miller, R.W., Donahue, R.L., 1990. Soils: An introduction to soils and plant growth. 6th Edition. Prentice Hall, Englewood Cliffs, New Jersey, USA. 768 pp

Ozsoy, G., Aksoy, E., Dirim, M.S., Tumsavas, Z., 2012. Determination of soil erosion risk in the Mustafakemalpasa River Basin, Turkey, using the revised universal soil loss equation, geographic information system, and remote sensing. Environmental Management 50(4): 679-694.

Pandey, A., Chowdary, V.M., Mal, 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.

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). Agriculture Handbook, Vol. 703. US Department of Agriculture, US Government Printing Office, Washington DC, USA.

Renard, K.G., Yoder, D.C., Lightle, D.T., Dabney, S.M., 2011. Universal soil loss equation and revised universal soil loss equation. In: Handbook of Erosion Modeling. Morgan, R.P.C., Nearing, M.A. (Eds.). Blackwell Publishing Ltd. Oxford, England. pp. 137–167

Singh, G., Rambabu, V.V., Chandra, S., 1981. Soil loss prediction research in India, Bulletin of Central Soil & Water Conservation Research & Training Institute, T12/D9. Dehradun, India. 70 p

Stoddart, D.R., 1969. Ecology and morphology of recent coral reefs. Biological Reviews 44(4): 433-498.

Tideman, E.M., 1996. Watershed management: guidelines for Indian conditions. Omega Scientific Publisher, New Delhi, India.  101 p.

Toy, T.J., Foster, G.R., Renard, K.G., 2002. Soil erosion: processes, prediction, measurement, and control. John Wiley & Sons. New York, USA. 338 p.

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.

Wischmeier, W.H., Smith, D.D., 1978. Predicting rainfall erosion losses: A guide to conservation planning. Agriculture Handbook, Vol. 537. US Department of Agriculture, US Government Printing Office, Washington DC, USA.

Yildirim, U., 2012. Assessment of soil erosion at the Değirmen Creek watershed area, Afyonkarahisar, Turkey. Proceedings of ISEPP (International Symposium on Environmental Protection and Planning: Geographic Information Systems (GIS) and Remote Sensing (RS) Applications). 28-29 June 2011, İzmir, Turkey. pp. 73-80.

Abstract

Soil erosion is a most severe environmental problem in humid sub-tropical hilly state Tripura. The present study is carried out on Muhuri river basin of Tripura state, North east India having an area of 614.54 Sq.km. In this paper, Universal Soil Loss Equation (USLE) model, with Geographic Information System (GIS) and Remote Sensing (RS) have been used to quantify the soil loss in the Muhuri river basin. Five essential parameters such as Runoff-rainfall erosivity factor (R), soil erodibility Factor (K), slope length and steepness (LS), cropping management factor (C), and support practice factor (P) have been used to estimate soil loss amount in the study area. All of these layers have been prepared in GIS and RS platform (Mainly Arc GIS 10.1) using various data sources and data preparation methods. In these study DEM and LISS satellite data have been used. The daily rainfall data (2001-2010) of 6 rain gauge stations have been used to predict the R factor. Soil erodibility (K) factor in Basin area ranged from 0.15 to 0.36. The spatial distribution map of soil loss of Muhuri river basin has been generated and classified into six categories according to intensity level of soil loss. The average annual predicted soil loss ranges between 0 to and 650 t/ha/y. Low soil loss areas (<25 t/ha/y) have been recorded under very densely forested areas and intensely plantation (mainly Rubber plantation) area. The high rate (>70 t/ha/y) of soil erosion was found along the main course of Muhuri River.

Keywords: Soil loss, erosion risk, USLE, GIS, remote sensing, Muhuri river.

References

Bera, A., Namasudra, P., 2016. Impact of shifting cultivation on the environmental changes in Gumti River Basin, Tripura. International Journal of Recent Scientific Research 7(6): 11771-11774.

Biswal, S.K., 2015. Mathematical model for flow and sediment yield estimation on Tel river basin of India. A dissertation submitted in partial fulfilment of the requirements for the award of the degree of master of technology in civil engineering with specialization in water resources engineering. Department of Civil Engineering National Institute of Technology Rourkela, India. 51p.

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(1): 357-374. 

Devatha, C. P., Deshpande, V., Renukaprasad, M.S., 2015. Estimation of soil loss using USLE model for Kulhan Watershed, Chattisgarh - A case study. Aquatic Procedia 4: 1429-1436. 

El-Swaify, S.A., 1997. Factors affecting soil erosion hazards and conservation needs for tropical steeplands. Soil Technology 11(1): 3-16.

Ganasri, B.P., Ramesh, H., 2016. Assessment of soil erosion by RUSLE model using remote sensing and GIS-A case study of Nethravathi Basin. Geoscience Frontiers 7(6): 953–961.  

Ghosh, K., De, S. K., Bandyopadhyay, S., & Saha, S. (2013). Assessment of soil loss of the Dhalai river basin, Tripura, India using USLE. International Journal of Geosciences 4(1): 11-23.

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.

Miller, R.W., Donahue, R.L., 1990. Soils: An introduction to soils and plant growth. 6th Edition. Prentice Hall, Englewood Cliffs, New Jersey, USA. 768 pp

Ozsoy, G., Aksoy, E., Dirim, M.S., Tumsavas, Z., 2012. Determination of soil erosion risk in the Mustafakemalpasa River Basin, Turkey, using the revised universal soil loss equation, geographic information system, and remote sensing. Environmental Management 50(4): 679-694.

Pandey, A., Chowdary, V.M., Mal, 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.

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). Agriculture Handbook, Vol. 703. US Department of Agriculture, US Government Printing Office, Washington DC, USA.

Renard, K.G., Yoder, D.C., Lightle, D.T., Dabney, S.M., 2011. Universal soil loss equation and revised universal soil loss equation. In: Handbook of Erosion Modeling. Morgan, R.P.C., Nearing, M.A. (Eds.). Blackwell Publishing Ltd. Oxford, England. pp. 137–167

Singh, G., Rambabu, V.V., Chandra, S., 1981. Soil loss prediction research in India, Bulletin of Central Soil & Water Conservation Research & Training Institute, T12/D9. Dehradun, India. 70 p

Stoddart, D.R., 1969. Ecology and morphology of recent coral reefs. Biological Reviews 44(4): 433-498.

Tideman, E.M., 1996. Watershed management: guidelines for Indian conditions. Omega Scientific Publisher, New Delhi, India.  101 p.

Toy, T.J., Foster, G.R., Renard, K.G., 2002. Soil erosion: processes, prediction, measurement, and control. John Wiley & Sons. New York, USA. 338 p.

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.

Wischmeier, W.H., Smith, D.D., 1978. Predicting rainfall erosion losses: A guide to conservation planning. Agriculture Handbook, Vol. 537. US Department of Agriculture, US Government Printing Office, Washington DC, USA.

Yildirim, U., 2012. Assessment of soil erosion at the Değirmen Creek watershed area, Afyonkarahisar, Turkey. Proceedings of ISEPP (International Symposium on Environmental Protection and Planning: Geographic Information Systems (GIS) and Remote Sensing (RS) Applications). 28-29 June 2011, İzmir, Turkey. pp. 73-80.



Eurasian Journal of Soil Science