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Use of USLE/GIS technology integrated with geostatistics to assess soil erosion risk in different land uses of Indagi Mountain Pass—Çankırı, Turkey

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Environmental Geology

Abstract

The universal soil loss equation (USLE) is an erosion model to estimate average soil loss that would generally result from splash, sheet, and rill erosion from agricultural plots. Recently, use of USLE has been extended as a useful tool predicting soil losses and planning control practices by the effective integration of the GIS-based procedures to estimate the factor values on a grid cell basis. This study was performed for five different lands uses of Indağı Mountain Pass, Cankırı to predict the soil erosion risk by the USLE/GIS methodology for planning conservation measures in the site. Of the USLE factors, rainfall-runoff erosivity factor (USLE-R) and topographic factor (USLE-LS) were greatly involved in GIS. These were surfaced by correcting USLE-R site-specifically using DEM and climatic data and by evaluating USLE-LS by the flow accumulation tool using DEM and watershed delineation tool to consider the topographical and hydrological effects on the soil loss. The study assessed the soil erodibility factor (USLE-K) by randomly sampled field properties by geostatistical analysis. Crop management factor for different land-use/land cover type and land use (USLE-C) was assigned to the numerical values from crop and flora type, canopy and density of five different land uses, which are plantation, recreational land, cropland, forest and grassland, by means of reclassifying digital land use map available for the site. Support practice factor (USLE-P) was taken as a unit assuming no erosion control practices. USLE/GIS technology together with the geostatistics combined these major erosion factors to predict average soil loss per unit area per unit time. Resulting soil loss map revealed that spatial average soil loss in terms of the land uses were 1.99, 1.29, 1.21, 1.20, 0.89 t ha−1 year−1 for the cropland, grassland, recreation, plantation and forest, respectively. Since the rate of soil formation was expected to be so slow in Central Anatolia of Turkey and any soil loss of more than 1 ton ha−1 year−1 over 50–100 years was considered as irreversible for this region, soil erosion in the Indağı Mountain Pass, to the great extent, attained the irreversible state, and these findings should be very useful to take mitigation measures in the site.

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References

  • Akman Y (1995) Türkiye Orman Vejetasyonu, Ank Üniv Fen Fakültesi Botanik Ana Bilim Dalı (in Turkish), Ankara, pp 143–154

  • Aytuğ B (1970) Arkeolojik araştırmaların ışığı altında İç Anadolu Stepi, İ. Ü. Orman Fa k (in Turkish). Dergisi, Seri A 20(1):127–143

    Google Scholar 

  • Bartsch KP, van Miegroet H, Boettinger J, Dobrwolski JP (2002) Using empirical erosion models and GIS to determine erosion risk at Camp Williams. J Water Conserv 57:29–37

    Google Scholar 

  • Basaran M, Ozcan AU, Erpul G, Çanga MR (2006) Spatial variability of organic matter and some soil properties of mineral topsoil in Çankiri İndagi blackpine (Pinus nigra) plantation region. J Appl Sci 6(2):445–452

    Google Scholar 

  • Basaran M, Erpul G, Tercan AE, Canga MR (2007) The effects of land use changes on some soil properties in İndağı Mountain Pass, Çankırı, Turkey (in press)

  • Bayramin I, Erpul G, Erdogan HE (2006) Use of CORINE methodology to assess soil erosion risk in the semi-arid area of Beypazari, Ankara. Turk J Agric For 30:81–100

    Google Scholar 

  • Beurden SAHA, van Riezebos HTh (1988) The application of geostatistics in erosion hazard mapping. Soil Technol 1(4):349–364

    Article  Google Scholar 

  • Boardman J (1988) Severe erosion on agricultural land in East Sussex, UK, October (1987). Soil Technol 1:333–348

    Article  Google Scholar 

  • Burgess TM, Webster R (1986) Optimal interpolation and isarithmic mapping of soil properties: II. Block kriging. J Soil Sci 31:333–344

    Article  Google Scholar 

  • Burrough PA (1986) Principles of geographical information system for land resources assessment. Clarendon Press, Oxford

    Google Scholar 

  • Celik I (2005) Land-use effects on organic matter and physical properties of soil in a southern Mediterranean highland of Turkey. Soil Till 83(2):270–277

    Article  Google Scholar 

  • Cerda A (1996) Soil aggregate stability in three Mediterranean environments. Soil Technol 9:133–140

    Article  Google Scholar 

  • Cerri CEP, Dematte JAM, Ballester MVR, Martinelli LA, Victoria RL, Roose E (2001) GIS erosion risk assessment of the Piracicaba River Basin, southeastern Brazil. Mapp Sci Remote Sens 38:157–171

    Google Scholar 

  • Desmet PJJ, Govers G (1996) A GIS procedure for automatically calculating the USLE LS factor on topographically complex landscape units. J Soil Water Conserv 51:427–433

    Google Scholar 

  • Dogan O (2002) Erosive potentials of rainfalls in Turkey and erosion index values of universal soil loss equation. Publications of Ankara Research Institutes. General Directorate of Rural Service, Turkey. Publication no. 220, Report no:R-120

  • EEA (1999) Environment in the European Union at the Turn of the Century. Environmental assessment report 2

  • Eedy W (1995) The use of GIS in environmental assessment. Impact Assess 13:199–206

    Google Scholar 

  • Erdoğan EH, Erpul G, Bayramin İ (2006) Use of USLE/GIS methodology for predicting soil loss in a semi-arid agricultural watershed (in press)

  • Evrendilek F, Celik I, Kilic S (2004) Changes in soil organic carbon and other physical soil properties along adjacent Mediterranean forest, grassland, and cropland ecosystems in Turkey. J Arid Environ 59:743–752

    Article  Google Scholar 

  • Foster GR, McCool DK, Renard KG, Moldenhauer WC (1981) Conversion of universal soil loss equation to SL metric units. J Soil Water Conserv 36:355–359

    Google Scholar 

  • Goovaert P (1999) Geostatistics in soil science: state of the art and perspective. Geoderma 38:45–93

    Google Scholar 

  • Grimm M, Jones RJA, Rusco E, Montanarella L (2003) Soil erosion risk in Italy: a revised USLE approach. European Soil Bureau Research Report No.11, EUR 20677 EN, (2002). Office for official publications of the European communities, Luxembourg, p 28

    Google Scholar 

  • Haynes RJ (1999) Size and activity of the soil microbial biomass under grass and arable management. Biol Fertil Soils 30:210–216

    Article  Google Scholar 

  • Hession WC, Shanholtz VO (1988) A geographic information system for targeting non point-source agricultural pollution. J Soil Water Conserv 43(3):264–266

    Google Scholar 

  • Journal AG, Huijbregts CS (1978) Mining Geostatistics. Akademic, New York, pp 600

    Google Scholar 

  • Kinnell PIA (2001) Slope length factor for applying the USLE-M to erosion in grid cells. Soil Till Res 58:11–17

    Article  Google Scholar 

  • Klik A, Truman CC (2003) What is a typical rainstorm? In: Gabriels D, Cornelis W (eds) proceedings of international symposium, 25 years of assessment of erosion, 22 Ð 26 September, 2003. Ghent, Belgium, pp 93–98

  • Lal R, Blum WH (1997) Methods for assessment of soil degradation. CRC Press, LLC

    Google Scholar 

  • Lee S (2004) Soil erosion assessment and its verification using the Universal Soil Loss Equation and geographic information system: a case study at Boun, Korea. Environ Geol 45:457–465

    Article  Google Scholar 

  • Lu D, Lı G, Valladares GS, Batistella M (2004) Mapping soil erosion risk in Rondonia, Brazilian Amazonia: Using RUSLE, remote sensing and GIS. Land Degrad Dev 15:499–512

    Article  Google Scholar 

  • Ma JW, Xue Y, Ma CF, Wang ZG (2003) A data fusion approach for soil erosion monitoring in the Upper Yangtze River Basin of China based on universal soil loss equation (USLE) model. Int J Remote Sens 24:4777–4789

    Article  Google Scholar 

  • Martin A, Gunter J, Regens J (2003) Estimating erosion in a riverine watershed, Bayou Liberty—Tchefuncta River in Louisiana. Environ Sci Pollut Res 4:245–250

    Article  Google Scholar 

  • Matheron G (1965) Principles of geostatistics. Econ Geol 58:1246–1266

    Google Scholar 

  • Millward AA, Mersey JE (1999) Adapting the RUSLE to model soil erosion potential in a mountainous tropical watershed. Catena 38:109–129

    Article  Google Scholar 

  • Moore ID, Burch GJ (1986a) Modeling erosion and deposition. Topographic effects Trans Am Soc Agric Eng 29:1624–1630 1640

    Google Scholar 

  • Moore ID, Burch GJ (1986b) Physical basis of the length-slope factor in the universal soil loss equation. Soil Sci Soc Am J 50:1294–1298

    Article  Google Scholar 

  • Ogawa S, Saito G, Mino N, Uch Da S, Khan NM, Shafiq M (1997) Estimation of soil erosion using USLE and Landsat TM in Pakistan, GIS development. Net, ACRS, pp 1–5

  • Ouyang D, Bartholic J (2001) Web-based GIS application for soil erosion prediction. ASAE, pp 260–263

  • Özhan S, Balcı N, Özyuvacı N, Hızal A, Gökbulak F, Serengil Y (2005) Cover and management factors for the universal soil-loss equation for forest ecosystems in the Marmara region, Turkey. For Ecol Manage 214:118–123

    Article  Google Scholar 

  • Parysow p, Wang G, Gertner G, Anderson AB (2003) Spatial uncertainty analysis mapping soil erodibility based on joint sequential simulation. Catena 736:1–14

    Google Scholar 

  • Poesen JW, Boardman J, Wilcox B, Valentin C (1996) Water erosion monitoring and experimentation for global change studies. J Soil Water Conserv 1996:386–390

    Google Scholar 

  • Renard KG, Foster GA, Weesies DA, Mccool DK, Yoder DC (1997) Predicting soil erosion by water: a guide to conservation planning with the revised universal soil loss equation (RUSLE) Agriculture handbook No. 703. USDA, Washington, DC

    Google Scholar 

  • Shepherd TG, Newman RH, Ross CW, Dando JL (2001) Tillage inducedchanges in soil structure and soil organic matter fraction. Aust J Soil Res 39:465–489

    Article  Google Scholar 

  • Soil Survey Staff, (1951) Soil survey manual. Agriculture handbook No. 18. US Department of Agriculture. US Government Printing Office, Washington, DC

    Google Scholar 

  • Sparling GP, Shepherd TG, Kettles HA (1992) Changes in soil C, microbial C and aggregate stability under continuous maize and cereal cropping, and after restoration to pasture in soils from Manawatu region, New Zealand. Soil Till Res 24:141–225

    Article  Google Scholar 

  • Toy TJ, Foster GR (1998) In: Galetevic JR (ed) Guidelines for the revised universal soil loss equation (RUSLE) version 1.06 on mined lands, construction sites, and reclaimed lands. The office of technology transfer western regional coordinating center office of surface mining 1999 Broadway, Suite 3320 Denver, CO 80202–5733

  • Trangmar BB, Yost RS, Wade MK, Uehara G, Sudjadi M (1987) Spatial variation of soil properties and rice yield in recently cleared land. Soil Sci Soc Am J 51:668–674

    Article  Google Scholar 

  • Van der Kniff JM, Jones RJA, Montanarella L (2000) Soil erosion risk assessment in Europe, EUR 19044 EN, 44pp. Office for official publications of the European communities, Luxembourg

    Google Scholar 

  • Ventura SJ, Chrisman NR, Conncrs K, Gurda RF, Martin RW (1988) A land information system for soil erosion control planning. J Soil Water Conserv 43(3):230–233

    Google Scholar 

  • Wall GJ, Coote DR, Pringle EA, Shelton IJ (1997) RUSLEFACrevised universal soil loss equation for application in Canada. Centre for land and biological resources research, research branch, agriculture and agri-food, Ottawa, Canada

  • Wang G, Gertner GZ, Liu X, Anderson AB (2001) Uncertainty assessment of soil erodibility factor for revised universal soil losse equation. Catena 46:1–14

    Article  Google Scholar 

  • Wang G, Gertner G, Fang S, Anderson AB (2003) Mapping multiple variables for predicting soil loss by geostatistical methods with TM images and a slope map. Photogramm Eng Remote Sens 69:889–898

    Google Scholar 

  • Wilson JP, Lorang MS (2000) Spatial models of soil erosion and GIS. In: Fotheringham AS, Wegener M (eds) Spatial models and GIS: new potential and new models, Taylor & Francis, Philadelphia, pp 83–108

    Google Scholar 

  • Wischmeier WH, Smith DD (1978) Predicting rainfall erosion losses—a guide for conservation planning. USDA, Agricultural Handbook 537. Washington, DC

    Google Scholar 

  • Wischmeier WH, Johnson CB, Cross BV (1971) A soil Erodibility nomograph for farmland and construction sites. J Soil Sci Water Conserv 26(5):189–193

    Google Scholar 

  • Wu R, Tiessen H (2002) Effect of land use on soil degradation in Alpine grassland soil, China. Soil Sci Soc Am J 66:1648–1655

    Article  Google Scholar 

Download references

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Correspondence to Mustafa Basaran.

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Ozcan, A.U., Erpul, G., Basaran, M. et al. Use of USLE/GIS technology integrated with geostatistics to assess soil erosion risk in different land uses of Indagi Mountain Pass—Çankırı, Turkey. Environ Geol 53, 1731–1741 (2008). https://doi.org/10.1007/s00254-007-0779-6

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  • DOI: https://doi.org/10.1007/s00254-007-0779-6

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