Use of USLE/GIS technology integrated with geostatistics to assess soil erosion risk in different land uses of Indagi Mountain Pass—Çankırı, Turkey
- 761 Downloads
- 36 Citations
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.
Keywords
USLE/GIS technology Geostatistics Erosion risk assessment Land useReferences
- Akman Y (1995) Türkiye Orman Vejetasyonu, Ank Üniv Fen Fakültesi Botanik Ana Bilim Dalı (in Turkish), Ankara, pp 143–154Google Scholar
- Aytuğ B (1970) Arkeolojik araştırmaların ışığı altında İç Anadolu Stepi, İ. Ü. Orman Fa k (in Turkish). Dergisi, Seri A 20(1):127–143Google 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 57:29–37Google 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):445–452Google 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)Google Scholar
- 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 30:81–100Google Scholar
- Beurden SAHA, van Riezebos HTh (1988) The application of geostatistics in erosion hazard mapping. Soil Technol 1(4):349–364CrossRefGoogle Scholar
- Boardman J (1988) Severe erosion on agricultural land in East Sussex, UK, October (1987). Soil Technol 1:333–348CrossRefGoogle Scholar
- Burgess TM, Webster R (1986) Optimal interpolation and isarithmic mapping of soil properties: II. Block kriging. J Soil Sci 31:333–344CrossRefGoogle Scholar
- Burrough PA (1986) Principles of geographical information system for land resources assessment. Clarendon Press, OxfordGoogle 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):270–277CrossRefGoogle Scholar
- Cerda A (1996) Soil aggregate stability in three Mediterranean environments. Soil Technol 9:133–140CrossRefGoogle 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 38:157–171Google 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 51:427–433Google 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-120Google Scholar
- EEA (1999) Environment in the European Union at the Turn of the Century. Environmental assessment report 2Google Scholar
- Eedy W (1995) The use of GIS in environmental assessment. Impact Assess 13:199–206Google 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)Google Scholar
- 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 59:743–752CrossRefGoogle Scholar
- Foster GR, McCool DK, Renard KG, Moldenhauer WC (1981) Conversion of universal soil loss equation to SL metric units. J Soil Water Conserv 36:355–359Google Scholar
- Goovaert P (1999) Geostatistics in soil science: state of the art and perspective. Geoderma 38:45–93Google 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 28Google Scholar
- Haynes RJ (1999) Size and activity of the soil microbial biomass under grass and arable management. Biol Fertil Soils 30:210–216CrossRefGoogle Scholar
- Hession WC, Shanholtz VO (1988) A geographic information system for targeting non point-source agricultural pollution. J Soil Water Conserv 43(3):264–266Google Scholar
- Journal AG, Huijbregts CS (1978) Mining Geostatistics. Akademic, New York, pp 600Google Scholar
- Kinnell PIA (2001) Slope length factor for applying the USLE-M to erosion in grid cells. Soil Till Res 58:11–17CrossRefGoogle 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 93–98Google Scholar
- Lal R, Blum WH (1997) Methods for assessment of soil degradation. CRC Press, LLCGoogle 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 45:457–465CrossRefGoogle 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 15:499–512CrossRefGoogle 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 24:4777–4789CrossRefGoogle Scholar
- Martin A, Gunter J, Regens J (2003) Estimating erosion in a riverine watershed, Bayou Liberty—Tchefuncta River in Louisiana. Environ Sci Pollut Res 4:245–250CrossRefGoogle Scholar
- Matheron G (1965) Principles of geostatistics. Econ Geol 58:1246–1266Google Scholar
- Millward AA, Mersey JE (1999) Adapting the RUSLE to model soil erosion potential in a mountainous tropical watershed. Catena 38:109–129CrossRefGoogle Scholar
- Moore ID, Burch GJ (1986a) Modeling erosion and deposition. Topographic effects Trans Am Soc Agric Eng 29:1624–1630 1640Google Scholar
- Moore ID, Burch GJ (1986b) Physical basis of the length-slope factor in the universal soil loss equation. Soil Sci Soc Am J 50:1294–1298CrossRefGoogle 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 1–5Google Scholar
- Ouyang D, Bartholic J (2001) Web-based GIS application for soil erosion prediction. ASAE, pp 260–263Google Scholar
- 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 214:118–123CrossRefGoogle Scholar
- Parysow p, Wang G, Gertner G, Anderson AB (2003) Spatial uncertainty analysis mapping soil erodibility based on joint sequential simulation. Catena 736:1–14Google Scholar
- Poesen JW, Boardman J, Wilcox B, Valentin C (1996) Water erosion monitoring and experimentation for global change studies. J Soil Water Conserv 1996:386–390Google 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, DCGoogle Scholar
- Shepherd TG, Newman RH, Ross CW, Dando JL (2001) Tillage inducedchanges in soil structure and soil organic matter fraction. Aust J Soil Res 39:465–489CrossRefGoogle Scholar
- Soil Survey Staff, (1951) Soil survey manual. Agriculture handbook No. 18. US Department of Agriculture. US Government Printing Office, Washington, DCGoogle 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 24:141–225CrossRefGoogle 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 80202–5733Google Scholar
- 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 51:668–674CrossRefGoogle 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, LuxembourgGoogle 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):230–233Google Scholar
- Wall GJ, Coote DR, Pringle EA, Shelton IJ (1997) RUSLEFAC–revised universal soil loss equation for application in Canada. Centre for land and biological resources research, research branch, agriculture and agri-food, Ottawa, CanadaGoogle Scholar
- Wang G, Gertner GZ, Liu X, Anderson AB (2001) Uncertainty assessment of soil erodibility factor for revised universal soil losse equation. Catena 46:1–14CrossRefGoogle 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 69:889–898Google 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 83–108Google Scholar
- Wischmeier WH, Smith DD (1978) Predicting rainfall erosion losses—a guide for conservation planning. USDA, Agricultural Handbook 537. Washington, DCGoogle Scholar
- Wischmeier WH, Johnson CB, Cross BV (1971) A soil Erodibility nomograph for farmland and construction sites. J Soil Sci Water Conserv 26(5):189–193Google Scholar
- Wu R, Tiessen H (2002) Effect of land use on soil degradation in Alpine grassland soil, China. Soil Sci Soc Am J 66:1648–1655CrossRefGoogle Scholar