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Soil erosion and sediment yield modeling using RS and GIS techniques: a case study, Iran

نمذجة تآكل التربة وتحقيق الرسوبيات باستخدام تقنيات الRS و GIS : دراسة حالة ، إيران

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Abstract

Water erosion is a serious and continuous environmental problem in many parts of the world. The need to quantify the amount of erosion, sediment delivery, and sediment yield in a spatially distributed form has become essential at the watershed scale and in the implementation of conservation efforts. In this study, an effort to predict potential annual soil loss and sediment yield is conducted by using the Revised Universal Soil Loss Equation (RUSLE) model with adaptation in a geographic information system (GIS). The rainfall erosivity, soil erosivity, slope length, steepness, plant cover, and management practice and conservation support practice factors are among the basic factors that are obtained from monthly and annual rainfall data, soil map of the region, 50-m digital elevation model, remote sensing (RS) techniques (with use of Normalized Difference Vegetation Index), and GIS, respectively. The Ilam dam watershed which is located southeast part of Ilam province in western Iran is considered as study area. The study indicates that the slope length and steepness of the RUSLE model are the most effective factors controlling soil erosion in the region. The mean annual soil loss and sediment yield are also predicted. Moreover, the results indicated that 45.25%, 12.18%, 12.44%, 10.79%, and 19.34% of the study area are under minimal, low, moderate, high, and extreme actual erosion risks, respectively. Since 30.13% of the region is under high and extreme erosion risk, adoption of suitable conservation measures seems to be inevitable. So, the RUSLE model integrated with RS and GIS techniques has a great potential for producing accurate and inexpensive erosion and sediment yield risk maps in Iran.

بحث رقم

التآكل الناتج عن المياه هي مشكله بيئية خطيرة ومستمرة في العديد من أجزاء العالم. ولقد أصبح من الضروري تحديد كمية التآكل و الرواسب المستلمة والرواسب العائدة في شكل التوزيع المكاني على نطاق مستجمعات المياه و لتحقيق جهود حفظ المياه. تقدم هذه الدراسة جهدا لحساب توقع فقدان التربة السنوي وقد قيمت الرواسب المستلمة باستخدام نموذج معادلات فقدان التربة العالمي المراجع (RUSLE) مندمجة مع نظام المعلومات الجغرافي GIS. نحر سقوط الأمطار و تآكل التربة و وطول الانحدار وشدة الانحدار steepness و الغطاء النباتي والممارسات الإدارية وممارسات دعم الاحتفاظ هي من العوامل الأساسية التي تم الحصول عليها من بيانات هطول الأمطار الشهرية والسنوية و خارطة التربة للمنطقة ونموذج الارتفاعات الرقمي (DEM) و تقنيات التحكم من بعد (RS) (مع استخدام NDVI) و الGIS على الترتيب. منطقة الدراسة تشمل نقطة تحول سد ILAM والتي تقع في الجزء الجنوبي الشرقي من مقاكعة ILAM في شرق إيران. أشارت الدراسة أن طول انحدار وشدة انحدار نموذج الRUSLE هي أكثر العوامل المؤثرة التي تتحكم في تآكل التربة في المنطقة. كما امكن توقع المتوسط السنوي لخسائر والرسوبيات المحققة. أكثر من ذلك ، أشارات النتائج أن 45.25% و 12.18% و 12.44% و 10.79% و 19.34% من منطقة الدراسة تقع تحت أدنى و أقل و متوسط و عالي و أقصى مخاطر التآكل الحقيقي ، على الترتيب. بما أن 30.13% من المنطقة تقع تحت مخاطر تآكل عالي و أقصى (بالغ) ، فإن اعتماد التدابير المنسبة أصبحت لا مفر منها. وبناءاً عليه ، فإن نموذج RUSLE متكاملا مع تقنيات RS و GIS ذو أهمية كبيرة لإنتاج خرائط مخاطر الآكل والرسوبيات ذات دقة عالية رخيصة في إيران.

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References

  • Arnold JG, Srinivasan R, Muttiah RS, Williams JR (1998) Large area hydrologic modeling and assessment: part I. Model development. J Am Water Resour Assoc 34(1):73–89

    Article  Google Scholar 

  • Azami Ayad (2006) Comparison of various methods for estimating sediment yield in Ilam dam watershed. M.Sc. thesis, Gorgan University

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

    Google Scholar 

  • Biot K, Lu XX (1995) Loss of yield caused by soil erosion on sandy soils in the UK. Soil use manage 11:157–162

    Article  Google Scholar 

  • Boggs G, Devonport C, Evans K, Puig P (2001) GIS-based rapid assessment of erosion risk in a small catchment in the wet/dry tropics of Australia. Land Degrad Dev 12:417–434

    Article  Google Scholar 

  • Boyce RC (1975) Sediment routing with sediment delivery ratios. Present and prospective technology for ARS. USDA, Washington, DC

    Google Scholar 

  • Bruce RR, Langdale GW, East LJ, Miller WP (1995) Surface soil degradation and soil productivity restoration and maintenance. Soil Sci Soc Am J 59:654–660

    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 Sciences Remote Sens 38:157–171

    Google Scholar 

  • Dabral PP, Baithuri N, Pandey A (2008) Soil erosion assessment in a hilly catchment of North Eastern India using USLE, GIS and remote sensing. Water Resour Manage 22:1783–1798

    Article  Google Scholar 

  • Dennis MF, Rorke MF (1999) The relationship of soil loss by interill erosion to slope gradient. Catena 38:211–222

    Google Scholar 

  • FAO/UNEP (1994) Land degradation in south Asia: its severity causes and effects upon the people. FAO, UNEP and UNEP project, Rome

    Google Scholar 

  • Flanagan DC, Nearing MA (1995) USDA water erosion prediction project: hillslope profile and watershed model documentation. NSERL report no. 10. USDA-ARS National Soil Erosion Research Laboratory, West Lafayette

    Google Scholar 

  • Irvem A, Topaloglu F, Uygur V (2007) Estimating spatial distribution of soil loss over Seyhan River Basin in Turkey. J Hydrol 336(1–2):30–37

    Article  Google Scholar 

  • Jianping Z (1999) Soil erosion in Guizhou province of China: a case study in Bijie prefecture. Soil Use Manage 15:68–70

    Article  Google Scholar 

  • Kinnell PIA (2000) AGNPS-UM: applying the USLE-M within the agricultural non point source pollution model. Environ Model Softw 15(3):331–341

    Article  Google Scholar 

  • Lim KJ, Choi J, Kim K, Sagong M, Engel BA (2003) Development of sediment assessment tool for effective erosion control (SATEEC) in small scale watershed. Trans Korean Soc Agric Eng 45(5):85–96

    Google Scholar 

  • Lin CY (1997) A study on the width and placement of vegetated buffer strips in a mudstone-distributed watershed. J China Soil Water Conserv 29(3):250–266, in Chinese with English abstract

    Google Scholar 

  • Lin C, Lin W, Chou W (2002) Soil erosion prediction and sediment yield estimation: the Taiwan experience. Soil Tillage Res 68:143–152

    Article  Google Scholar 

  • Lufafa A, Tenywa MM, Isabirye M, Majaliwa MJG, Woomer PL (2003) Prediction of soil erosion in a Lake Victoria basin catchment using a GIS-based universal soil loss model. Agric Syst 76:883–894

    Article  Google Scholar 

  • Masoudi M, Patwardhan AM, Gore SD (2006) Risk assessment of water erosion for the Qareh Aghaj subbasin, southern Iran. Stoch Environ Res Risk Assess 21:15–24

    Article  Google Scholar 

  • Millward AA, Mersey JE (1999) Adapting the RUSLE to model soil erosion potential in a mountainous tropical watershed. Catena 3:109–129

    Article  Google Scholar 

  • Moore ID, Wilson JP (1992) Length–slope factors for the Revised Universal Soil Loss Equation: simplified method of estimation. J Soil Water Conserv 47:423–428

    Google Scholar 

  • Morgan RPC (1995) Soil erosion and conservation. Longman, London, pp 23–37

    Google Scholar 

  • Morgan RPC, Quinton JN, Smith RE, Govers G, Poesen J, Auerswald K, Chisci G, Torri D, Styczen ME (1998) The European Soil Erosion Model (EUROSEM): a dynamic approach for predicting sediment transport from fields and small catchments. Earth Surf Process Land 23:527–544

    Article  Google Scholar 

  • Nepta Advisory Cooperation (2001) Detail project of Ilam Dam watershed, Jahad and Agriculture Organization of Ilam province, p 135

  • Oldeman LR, Hakkeling RTA, Sombroek WG (1990) World map of the status of human-induced soil degradation GLASOD. Work. pap. 90/07. ISRIC, Wageningen

    Google Scholar 

  • Ouyang D, Bartholic J (2001) Web-based GIS application for soil erosion prediction. Proceedings of an international symposium—soil erosion research for the 21st century, Honolulu, HI. Jan 3–5

  • Pandey A, Chowdary VM, Mal BC (2007) Identification of critical erosion prone areas in the small agricultural watershed using USLE, GIS and remote sensing. Water Resour Manage 21(4):729–746

    Article  Google Scholar 

  • Pandey A, Chowdary VM, Mal BC (2009) Sediment yield modelling of an agricultural watershed using MUSLE, remote sensing and GIS. J Paddy Water Environ 7(2):105–113

    Article  Google Scholar 

  • Programme and Budget Organization (1996) First national report on human development of Iran. Programme and Budget Organization, Tehran

    Google Scholar 

  • Renard KG, Freimund JR (1994) Using monthly precipitation data to estimate the R factor in the revised USLE. J Hydrol 157:287–306

    Article  Google Scholar 

  • Renard KG, Foster GR, Weesies GA, Porter JP (1991) RUSLE: revised universal soil loss equation. J Soil Water Conserv 46(1):30–33

    Google Scholar 

  • Reusing M, Schneider T, Ammer U (2000) Modeling soil erosion rates in the Ethiopian Highlands by integration of high resolution MOMs-2/D2-stereo-data in a GIS. Int J Remote Sens 21:1885–1896

    Article  Google Scholar 

  • Sadeghi SHR, Ggaderi Vangah B, Safaeeian NA (2007) Comparison between effects of open grazing and manual harvesting of cultivated summer rangelands of Northern Iran on infiltration, runoff and sediment yield. Land Degrad Dev 18:608–620. doi:10,1002:1dr.799

    Article  Google Scholar 

  • USDA (1972) Sediment sources, yields, and delivery ratios. National Engineering Handbook, section 3 Sedimentation. USDA, Washington, DC

    Google Scholar 

  • Vanoni VA (1975) Sedimentation engineering, manual and report no. 54. American Society of Civil Engineers, New York

    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 Sensing 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 and Francis, Philadelphia, pp 83–108

    Google Scholar 

  • Wischmeier WH, Smith DD (1978) Predicting rainfall erosion. losses: a guide to conservation planning. Agriculture handbook, vol. 537. US Department of Agriculture, Washington, DC

    Google Scholar 

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

    Google Scholar 

  • Yue-Qing X, Shao X-M, Kong X-B (2008) Adapting the RUSLE and GIS to model soil erosion risk in a mountains karst watershed, Guizhou Province, China. Environ Monit Assess 141:275–286

    Article  Google Scholar 

  • Yitayew M, Pokrzywka SJ, Renard KG (1999) Using GIS for facilitating erosion estimation. Appl Eng Agric 15(4):295–301

    Google Scholar 

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Authors and Affiliations

  1. Department of Watershed Management, Agriculture College, University of Ilam, Ilam, Iran

    Saleh Arekhi

  2. Msc of Watershed Management, Department of Natural Resources, Yazd University, Yazd, Iran

    Yaghoub Niazi

  3. Department of Range and Watershed Management, University of Guilan, Somehe sara, Iran

    Aman Mohammad Kalteh

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  1. Saleh Arekhi
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  2. Yaghoub Niazi
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  3. Aman Mohammad Kalteh
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Correspondence to Saleh Arekhi.

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Arekhi, S., Niazi, Y. & Kalteh, A.M. Soil erosion and sediment yield modeling using RS and GIS techniques: a case study, Iran. Arab J Geosci 5, 285–296 (2012). https://doi.org/10.1007/s12517-010-0220-4

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