A Determination of the most Suitable Cell Size of the Digital Elevation Model to compute the Topographic Factor in RUSLE

Document Type : Research Paper


1 Assistant Professor, Dept. of Soil Science, Urmia University

2 Ph.D Student, Dept. of Soil Science, Shahrekord University


Preparation of the topographic factor (LS) map in RUSLE model is a very tedious step because of the complicated effects of topography on soil loss. The objective of this study was to determine the suitable cell size of Digital Elevation Model (DEM) for computing LS factor by the method of Moore and Wilson (1992) in a 5326 ha area, northwest of Tehran Province. Towards this end, cell sizes of 30, 50, 100, 200 and 400 m were derived from the 10 m cell size in ArcGIS 9.3. The appropriate cell size was selected making use of the criteria of spatial dependence and the coefficient of determination (R2). Results revealed that in the preparation of flow accumulation map, the sinks created in digital elevation models must be resolved. Also, analysis of variograms showed that the calculated LS factor obtained from DEM of 50 m cell size is of the most spatial dependence (0.613) with the highest coefficient of determination (R2=0.983). As a result, a DEM of 50 m cell size was found out to lead to the production of a more accurate LS factor map.


Main Subjects

Amini, M., Afyuni, M., Khademi, H., Abbaspour, K. C., and Schulin, R. (2005). Mapping risk of cadmium and lead contamination to human health in soils of central Iran. Science of the Total Environment, 347, 64-77.
Asadi, H., Vazifehdoost, M., Moussavi, A., and Honarmand, M. (2011). Assessment and mapping of soil erosion hazard in Navrood watershed using revised universal soil loss equation (RUSLE), geographic information system (GIS) and remote sensing (RS). Report of Researches Guilan Regional Water Company, 13. (In Farsi)
Ayoubi, S. h., Khormali, F.. and Shataee, S. h. (2008). Optimal resolution investigation of digital elevation models by goestatistcal technique to compute topographic factor (LS) for RUSLE equation in Talesholia district, Golestan Province. Pajouhesh and Sazandegi, 77, 122-129. (In Farsi)
Blanco, A. C. and Nadaoka, K. (2006). A comparative assessment and estimation of potential soil erosion rates and patterns in Laguna lake watershed using three models: Towards development of an erosion index system for integrated watershed-lake management. Philippines, Symposium on Infrastructure Development and the Environment, 12.
Curran, P. J. and Dungan J. L. (1989). Estimation of single- to- noise: A new procedure applied to AVIRIS data. IEEE Transaction on Geosciences and Remote Sensing, 27, 620-628.
Darwishzadeh, A. (2006). Geology of Iran. Amir Kabir press institute.
Desmet, P. J. J. and Govers, G. (1996). A GIS procedure for automatically calculating the USLE LS factor on topographically complex landscape units. J. Soil and Water Cons, 51, 5. 427-433.
Eguen , M., Aguilar, C., Herrero, J., Millares, A.. and Polo, M. J. (2012). On the influence of cell size in physically-based distributed hydrological modelling to assess extreme values in water resource planning. Nat. Hazards Earth Syst. Sci., 12, 1573–1582.
Gitas, I. Z., Douros, K., Minakou, C.. and Silleos, G. N. (2009). Multi-temporal soil erosion risk assessment in N. Chalkidiki using a modified USLE raster model. European Association Remote Sensing Labratories Proceedings, 8, 1. 40-52.
Kinnell, P. I. A. (1997) The miscalculation of the USLE topographic factors in GIS. Australia, University of Canberra, 4.
Kinnell, P. I. A. (2010). Event soil loss, runoff and the Universal Soil Loss Equation family of models: A review. Journal of Hydrology, 385, 384–397.
Knijff, J. M., Jones, R. J. A.. and Montanarella, L. (2000). Soil erosion risk assessment in European. Space Applications Institute, 38.
Lal, R. and Elliot, W. (1994). Erodibility and erosivity, In Lal, R. (ed.), Soil erosion research methods, Soil and Water Conservation Society, Ankeny, 181-208.
Millward, A. A. and Mersey, J. E. (1999). Adapting the RUSLE to model soil erosion potential in a mountainous tropical watershed. Catena, 38, 109–129.
Mitasova, H., Hoferka, J., Zlocha, M., and Iverson L. R. (1996). Modeling topographic potential for erosion and deposition using GIS. Journal of Geographical Information Science, 10, 629-641.
Mohammadi, j. (1385). Pedometrics 2 (Spatial Statistics). Pelk press.
Moore, I. D. and Wilson J. P. (1992). Length-slope factors for Revised Universal Soil Loss Equation. Simplified method of estimation. Journal of soil and water conservation, 47, 423- 428.
Najafinejad, A., Mardian, M., Varvani, J., and Sheikh, V. B. (2011). Evaluation and comparison of representative hill slope and raster based hill slope methods for computation of topography factor in USLE. J. of Soil Management and Sustainable Production, 1(1), 99-114. (in Farsi)
Rafahi, H. Gh. (2006). Water erosion and conservation. University of Tehran Press.
Renard, K. G., Foster, C. R., Weesies, G. A., McCool, D. K., and Yoder, D. C. (1997). Predicting Soil erosion by water. A guide to conservation planning with the Universal Soil Loss Equation (RUSLE) Government Printing Office. Washington D.C. pp: 1-404.
Sharma, A., Tiwari, K. N., and Bhadoria, P. B. S. (2011). Determining the optimum cell size of digital elevation model for hydrologic application. J. Earth Syst. Sci., 120(4), 573–582.
Tian, Y. C., Zhou, Y. M., Wu, B. F., and Zhou, W. F. (2009). Risk assessment of water soil erosion in upper basin of Miyun Reservoir, Beijing, China. Environ Geol, 57, 937–942.
Truman, C. C., Wauchope, R. D., Sumner, H. R., Davis, J. G., Gasch, G. J., Hook, J. E., Chandler, L. D., and Johnson, A. W. (2001). Slpoe length effects on runoff and sediment delivery. J. Soil Water Conserv, 56(3), 249-256.
Vrieling, A., Sterk, G., and Beaulieu, N. (2002). Erosion risk mapping: a methodological case study in the Colombian eastern plains. Jour. Soil and water conserve, 57, 158–163.
Wachal, D. J. and Banks, K. E. (2007). Integrating GIS and erosion modeling: A tool for watershed management. Esri International User Conference. No.UC1038. 11p.
Wang, G., Gartner, G. Z., Parysow, P., and Anderson, A. B. (2001). Spatial prediction and uncertainty assessment of topographic factor for the Revised Universal Soil Loss Equation using digital elevation models. Journal of Photogrammetry and Remote Sensing, 56, 65-80.
Wang, G., Gertner, G., Fang, S., and Anderson, A. B. (2003). Mapping multiple variables for predicting soil loss by geostatistical methods with TM images and a slope map. Photogrammetric Engineering and Remote Sensing, 69, 889–898.
Wischmeier, W. H. and Smith D. D. (1978). Predicting rainfall erosion losses. A guide to conservation planning. USDA. Agr. Res. Ser. Handbook 537.