Assessment soil erosion using RUSLE model and identification the most effective factor in Dekhan watershed basin of southern Kerman

Nezhadafzali, Keramat; Shahrokhi, Mohmmad Reza; Bayatani, Fateme

doi:10.22111/jneh.2018.21894.1316

Assessment soil erosion using RUSLE model and identification the most effective factor in Dekhan watershed basin of southern Kerman

Document Type : Research Article

Authors

¹ Assistant Professor of Geography, Jiroft University, Jiroft, Iran

² MA in Water Resources Engineering, Azad University, Kerman

³ PhD Student of Climatology, Hakim Sabzevari University, Iran

10.22111/jneh.2018.21894.1316

Abstract

The soil is one of the most important factors of production that has a great influence on human economic and social life. The surface of the earth is generally covered by soil and other surface deposits. Soil erosion is one of the most important problems and problems we face today. Increasing exploitation and lack of proper human management of the natural environment have a great effect on the intensification of soil degradation and erosion processes. In this research, the effective parameters analysis of erosion and sediment production in Dakehah basin with a total area of 9923.2 ha in southern Kerman province was studied using the Revised Universal Soil Erosion Model (RUSLE). Data and tools used in the research include data from meteorological stations, digital elevation model (DEM), ETM 2015 satellite imagery, GIS and remote sensing (RS) It should be. By studying the effective factors in this model, which includes rainfall erosivity factor, soil erodibility factor, topographic factor, and vegetation, the purpose of this study is to estimate the annual soil erosion in the study area. The erosion rate of the basin is estimated. Accordingly, annual soil erosion in the whole study area is estimated at 67 tons per hectare per year. The results of this study show that the highest effect on the estimation of erosion, a topographic factor with the highest coefficient of explanation was 92.6 In this research, the effectiveness of RUSLE technologies of annual soil erosion is confirmed by the new model of GIS and remote sensing for quantitative estimation of soil erosion values.

Keywords

References

References (in Persian)

Ahmadi, H., (2008). Applied Geomorphology Wind Erosion, Volume II, Tehran University Press, 706p.

Refahi, H, (1996). Water erosion and its control - Tehran University, 551p.

Ayyoubi, S, Khorramali, F&, Joybari, S., (2007), Using Landsat Technique to Determine the Most Appropriate Dimensions of the Earth's Digital Model Model for Estimating the Topographic Characteristics (LS) of Estimated Estimate of RUSLE Estimation in Tash Local Area (Golestan Province), Research and Buildings in Natural Resources 77, 129p.

Archi, S, Niyazi, Y., (2010). Investigating GIS and RS Application for Estimating Soil Erosion and Sediment Load Using the RUSLE Model (Case Study: Upper Ilam Dam Basin), Aboukhak Protection Research Journal. 17. (2), pp.1-27.

Rezai, P, Farid, P, Ghorbani, M & Kazemi, M., (1393). Estimating soil erosion using the RUSLE model and identifying its most effective factor in the Gabriq basin - south-east of Hormozgan province, a few geomorphologic studies. 3(1), pp.97-113.

Noohegar, A, Kazemi, M., (1392). Erosion risk assessment using ICONA model (Case study: Tang-Bastanak Watershed, Shiraz), Geographical Research Quarterly, 28, pp.1-14.

References (in English)

Arnold, J.G, Srinivasan, R. Muttiah, R.S. Williams, J.R. (1998), Large area hydrologic modeling and assessment part I: Model development1, Wiley Online Library.

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(3), pp. 903-913.

Flanagan, D. Nearing, M. (1995), USDA-Water Erosion Prediction Project: Hillslope profile and watershed model documentation, NSERL report.

Hoyos, N. (2005), Spatial modeling of soil erosion potential in a tropical watershed of the Colombian Andes.Catena, 63(1),pp.85-108.

Ganasri, B. Ramesh, H. (2015), Assessment of soil erosion by RUSLE model using remote sensing and GIS-A case study of Nethravathi Basin, Geoscience Frontiers.

Morgan, R. Quinton, J. Smith, R. Govers, G. Poesen, J. Auerswald, K. Chisci, G. Torri, D. Styczen, M. (1998), The European Soil Erosion Model (EUROSEM): a dynamic approach for predicting sediment transport from fields and small catchments.Earth surface processes and landforms,23(6),pp.527-544.

Park, S. Oh, C. Jeon, S. Jung, H. Choi, C. (2011), Soil erosion risk in Korean watersheds assessed using the revised universal soil loss equation. Journal of Hydrology,399(3),pp.263-273.

Pimentel, D. Harvey, C.Resosudarmo, P. Sinclair, K. (2012), Soil erosion assessment and its correlation with landslide events using remote sensing data and GIS: a case study at Penang Island Malaysia. Environmental monitoring and assessment, 184(2), pp. 715-727.

Renard, K.G. Freimund, J.R. (1994), Using monthly precipitation data to estimate the R-factor in the revised USLE.Journal of hydrology.157(1),pp.287-306.

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(3),pp.228-245.

Wang, E. Xin, C. Williams, J.R. Xu, C. (2006), Predicting soil erosion for alternative land uses. Journal of environmental quality,35(2),pp.459-467.

Wischmeier, W.H., & Smith, D.D. (1994), Predicting rainfall erosion. losses: a guide to conservation planning, Agriculture Handbook, Vol. 537. US Department of Agriculture, Washington, DC, P58

Van Remortel, R.D. Maichle, R.W. Hickey, R.J. (2004), Computing the LS factor for the Revised Universal Soil Loss Equation through array-based slope processing of digital elevation data using a C++ executable.Computers & Geosciences,30(9),pp. 1043-1053.

Yu, B.Rosewell, C. (1996), Technical Notes: A Robust Estimator of the R-factor for the Universal Soil Loss Equation. Transactions of the ASAE,39(2),pp.559-561.