Assessment of spatial distribution of soil erodibility in Khoor and Biabanak Regions

Document Type : Research Article


1 PhD Student, Department of Desert Engineering, Faculty of Natural Resources and Geosciences, University of Kashan, Kashan, Iran

2 Assistant Professor, Department of Geography and Ecotourism, Faculty of Natural Resources and Geosciences, University of Kashan, Kashan, Iran

3 Associate Professor, Department of Desert Engineering, Faculty of Natural Resources and Geosciences, University of Kashan, Kashan, Iran

4 Associate Professor, Department of Renewable Energies and Environment, University of Tehran, Tehran, Iran


Currently, erosion is one of the most important environmental problems in Iran watersheds. Therefore, determination of the sediment and soil erodibility is very important for conservation and management of natural resources. The current study aims to evaluate the spatial distribution of soil erodibility and its relationship with some of the soil properties using geostatistical methods in the Khoor and Biabanak regions. For this purpose, 33 soil samples were taken from depths of 0-50 cm along three transects from playa to mountain units for determination of the components of sand, clay, silt, organic carbon and organic matter. Values of K factor and SEI were calculated using the values of these parameters. Finally, to determine the spatial distribution, interpolation methods were tested and the most suitable method was chosen. The results showed that Radial Basis Function was the most suitable of interpolation methods for the spatial distribution of the elements of sand, clay and K factor with RMSE 3.27, 3.22 and 0.0036, respectively. The simple Kriging method was suitable for carbon components and organic material with RMSE 0.34 and 0.59, respectively. For silt, Kriging Ordinary with RMSE 0.88, and for SEI index, Universal Kriging method with RMSE 0.0014 were suitable. According to the results of soil erodibility values, minimum and maximum amounts of K factor with 0.025 and 0.07 t h MJ− 1 mm− 1, as well as minimum and maximum values of SEI with 0.03 and 0.07 are extensive in the East, West and North West areas, respectively.


Main Subjects

[1]. FAO/UNEP. Provisional methodology for assessment and mapping of desertification. FAO, Rome. 1984
[2]. Karam A, Safarian A, Hajje Foroshnia Sh. Estimation of soil erosion in the watershed zoning Mamlou (zaragh Tehran) using methods modified universal equation of soil erosion and the analytic hierarchy process. Researches in Earth Sciences. 2010; 1(2): 73-86. (In Persian)
[3]. Young R, Mutchler C. Edibility of some Minnesota soils. J. Soil Water Conserv. 1977; 32(3): 180–200.
[4]. Wallace A, Terry RE. Soil conditioners, soil quality and soil sustainability. Marcel Dekker, New York, NY, 1998: 1–41.
[5]. Sadeghi SHR, Kianei-e-Harchagani M, Saeedi P, Allafi Badi M. Assessing capability of RUSLE in estimation of storm’s sediment. Forth Conference on Sciences and Watershed Management Engineering of Iran. Karaj, Iran. 2008. (In Persian)
[6]. Wang GG, Gertner X, Anderson A. Uncertainty assessment of soil erodibility factor for revised universal soil loss equation. Catena. 2001; 46: 1-14.
[7]. Parysow P, Wang G, Gertner G, Anderson AB. Spatial uncertainty analysis for mapping soil erodibility based on joint sequential simulation. Catena. 2003; 736: 1-14.
[8]. Wischmeier WH, Mannering JV. Relation of soil properties to its erodibility. Soil Sci. Am. Proc. 1969; 33: 131-136.
[9]. Hoyos N. Spatial modeling of soil erosion potential in a tropical watershed of the Colombian Andes. Catena. 2005; 63: 85-108.
[10]. Rodriguez RR, Arbelo CD, Guerra JA, Natario MJS, Armas CM. Organic carbon stocks and soil erodibility in Canary Islands Andosols. Catena. 2006; 66: 228-235.
[11]. Charman PEV, Murphy BW. Soils (their properties and management). Second edition, Land and Water Conservation, New South Wales, Oxford, 2000: 206-212.
[12]. Duiker SW, Flanagan DC, Lal R. Erodibility and infiltration characteristics of five major soils of southwest Spain. Catena. 2001; 45: 103-121.
[13]. Miller RW, Gardiner DT. Soils in our environment. 8th edition. Prentice-Hall Inc. United State of America. 1998: 75-81.
[14]. Santos FL, Reis JL, Martins OC, Castanheria NL, Serralherio RP. Comparative assessment of infiltration, runoff and erosion of sprinkler irrigation soils. Biosystems Engineering. 2003; 86(3): 355-364.
[15]. Burrough PA. Sampling designs for quantifying map unit composition. In: Mausbach Mj, Wilding LP. (Eds), Spatial variability of soils and landforms. Soil Science Society American Journal. 1991; 28: 89-125.
[16]. Millward AA, Mersey JE. Adapting the RUSLE to model soil erosion potential in a mountainous tropical watershed. Catena. 1999; 3: 109-129.
[17]. Wang G, Gertner G, Fang S, Anderson AB. Mapping multiple variables for predicting soil loss by geostatistical methods with TM images and a slope map. Photogrammetric Engineering and Remote Sensing. 2003; 69: 889-898.
[18]. Goovaert P. Geostatistic in soil science: State of the art and perspective. Geoderma. 1999; 38:45- 93.
[19]. Deutsch CV. Geostatistical reservoir modeling. Oxford University Press. 2002.
[20]. Kariminazar M, Fakhire A, Fayznia S, Rashki SA, Mirsolayman SJ. Evaluation of methods for estimating the speed of wind erosion in plain Sistan. Journal Natural Resources. 2009; 62 (3): 405 -417. (In Persian)
[21]. Foster GR, Young RA, Romkens MJM, Onstad CA. Processes of soil erosion by water. In: Follett RF, and Stewart BA. Soil erosion and crop productivity. American Society of Agronomy, Inc., Soil Science Society of America, Madison, Wisconsin, USA. 1985: 137-159.
[22]. Rejman J, Turski R, Paluszek J. Spatial and temporal variability in erodibility of loess soil. Soil and Tillage Research. 1998; 46: 61-68.
[23]. Gee GW, Bauder JW. Particle size analysis, In: A. Klute (Ed), Methods of Soil Analysis. Part one and second edition, Agron. Monogr.9. ASA and SSSA, Madison, W.I. 1986; 404-407.
[24]. Klute A. Methods of soil analysis part I. Physical and mineralogical methods. 2nd Ed. Soil Science Society of America. 1986.
[25]. Chien YJ, Lee DY, Guo HY, Houng KH. Geostatical analysis of soil properties of mid-west Taiwan soils. Soil Science. 1997; 162: 291- 298.
[26]. Zhang K, Li S, Peng W, Yu B. Erodibility of agriculture soils and loess plateau of China. Soil and Illage. Res. 2004; 76: 157-165.
[27]. Wang G, Gertner G, Singh V, Shinkareva S, Parysow P, Anderson A. Spatial and temporal prediction and uncertainty of soil loss using the RUSLE: a case study of the rainfall runoff erosivity R Factor. Ecological Modelling. 2002; 153: 143-155.
[28]. Irvem A, Topalolu F, Uygur V. Estimating spatial distribution of soil loss over Seyhan River Basin in Turkey. Journal of Hydrology. 2007; 336: 30-37.
[29]. Rodríguez RP, Marques MJ, Bienes R. Spatial variability of the soil erodibility parameters and their relation with the soil map at subgroup level. Environmental Sciences. 2007; 378 (1-2): 166-173.
[30]. Sokouti Oskouie R. Evaluation of structure of spatial variation of the soil erodibility in the Orumieh region, Proceedings of the 9th Congress on Soil. Tehran, Iran. 2005; 482-487. (In Persian)
[31]. Saremi Naeini MA, Zareian Jahromi M, Ekhtesasi MR, Mohammadian Behbahani A. Wind threshold velocity surviving by using Geo-statistics (case study: Yazd city). 10th National Congress on Soil Science. Karaj, Iran. 2007. (In Persian)
[32]. Wilson JP, Lorang MS. Spatial models of soil erosion and GIS. In spatial models and GIS. New potential and new models, Fotheringham AS, Wegener, M. (Eds). Taylor and Francis: Philadelphia, PA, 2000; 83-108.
[33]. Vaezi A, Bahrami HA, Sadeghi SHR, Mahdian MH. The new monograph to estimate erosion-risk factor (K) in the semi-arid region in the northwestern part of the territory of Iran. Journal of Soil and Water Sciences (Science and Technology of Agriculture and Natural Resources). 2009; 13(49): 69-80. (In Persian)
[34]. Nelson DW, Sommer LE. Total carbon, organic carbon, and organic matter. In: A.L. Page (ed.) Methods of Soil Analysis. 2nd ed. ASA Monogr. Amer. Soc. Agron. Madison. 1982; 9(2): 539- 579.
[35]. Wischmeier W, Smith D. Predicting rainfall erosion losses: a guide to conservation planning. Agricultural Handbook No. 537. Washington DC, USA: U.S. 1978.
[36]. Renard KG, Foster GR, Weessies GA. McCool DK. Predicting soil erosion by water: a guide to conservation planning with the Revised Universal Soil Loss Equation (RUSLE). In: Yoder DC, editor. U.S. Department of Agriculture, Agriculture Handbook 703, Geomorphology 2002; 47(2–4): 189–209.
[37]. Webb NP, McGowan HA, Phinn SR, Leys JF, McTainsh GH. A model to predict land susceptibility to wind erosion in Western Queensland, Australia. Environmental Modelling & Software. 2009; 24: 214-227.
[38]. Mirzaee S. Vulnerability assessment and risk mapping using GIS Shahrekord plain groundwater pollution and DRASTIC model and SINTACS. Master's Thesis on Soil Science, Faculty of Agriculture, University of Shahrekord, 2009. (In Persian)
[39]. Faraji Sabokbar HS, Azizi Gh. Evaluate the accuracy of spatial interpolation, Case study: modeling Kardeh rainfall areas of Mashhad. Geographical Journal. 2006; 58: 1-15. (In Persian)
[40]. Anderson SH. An evaluation of spatial interpolation methods on air temperature in Phoenix. AZ. 2000.
[41]. Matkan A, Shakiba A, Yazdani A. Evaluate different methods of interpolation to estimate daily rainfall, Case study: Fars province. Territory. 2007; 13: 54-67. (In Persian)
Volume 4, Issue 2
June 2017
Pages 561-571
  • Receive Date: 30 December 2016
  • Revise Date: 11 March 2017
  • Accept Date: 15 March 2017
  • First Publish Date: 22 June 2017