دوره 5، شماره 1 - ( 3-1397 )                   جلد 5 شماره 1 صفحات 96-83 | برگشت به فهرست نسخه ها


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saffari A, saffari A, karami J. Investigation about the influence of land-cover and land use changes on soil erodibility potential, case study: Gharesou, Gorganrood. Journal of Spatial Analysis Environmental Hazards 2018; 5 (1) :83-96
URL: http://jsaeh.khu.ac.ir/article-1-2701-fa.html
صفاری امیر، نوری عباسعلی، کرمی جلال. بررسی تاثیر تغییرات پوشش و کاربری زمین در قابلیت فرسایش خاک – مطالعه موردی حوضه قره‌سو گرگانرود. تحلیل فضایی مخاطرات محیطی. 1397; 5 (1) :83-96

URL: http://jsaeh.khu.ac.ir/article-1-2701-fa.html


1- دانشگاه خوارزمی
2- دانشگاه خوارزمی ، a_nouri_63@yahoo.com
3- دانشگاه تربیت مدرس
چکیده:   (6381 مشاهده)

فرسایش خاک یکی از ریسک‌های اصلی تهدیدکننده منابع آب و خاک در ایران است که رابطه‌ای قوی با نوع پوشش و کاربری زمین دارد. در این پژوهش بوسیله مدل RUSLE با بهره‌گیری از تصاویر سنجنده‌هایTM ، ETM و OLI ماهواره لندست در یک بازه 30 ساله برای سه سال 1985 ، 2000و 2015 تاثیر تغییرات پوشش زمین بر پتانسیل فرسایش خاک در حوضه آبخیز قره‌سو مورد بررسی قرار گرفت. نتایج تغییرات پوشش زمین نشان‌دهنده کاهش پوشش‌های جنگل متراکم، جنگل با تراکم کم و باغ و مرتع در برابر افزایش سطوح کشاورزی، زمین‌های بدون پوشش و سکونتگاه‌های انسانی در طی بازه سی ساله است. همچنین نتایج مدل RUSLE سیر افزایشی پتانسیل فرسایش خاک درحوضه آبخیز قره‌سو را نشان می‌دهد، هرچند که در نواحی جلگه‌ای با کاربری کشاورزی روندی معکوس با روند کلی در نتیجه اصلاح و تغییر الگوی کشت و رشد کشاورزی آبی دیده می‌شود. میانگین پتانسیل فرسایش خاک برآورد شده درحوضه قره‌سو برای 1985 ، 2000و 2015 به ترتیب 102.02، 103.11و 103.76 تن در هکتار در سال است. همچنین در کلاس‌های بیش از 100 (تن در سال در هکتار) یا طبقات با پتانسیل خیلی زیاد و بحرانی این مقدار از 43.8 درصد به 45.5 درصد از مساحت حوضه در سال 2015 افزایش یافته است. این روند افزایشی در سطح زیر حوضه ها نیز مورد آزمون قرار گرفت و در اکثر آنها پتانسیل فرسایش خاک بر اساس روند تغییرات کاربری زمین رو به افزایش است.

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نوع مطالعه: پژوهشي | موضوع مقاله: تخصصي
دریافت: 1396/5/3 | پذیرش: 1396/12/19 | انتشار: 1397/3/22

فهرست منابع
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6. Biesemans, J., Meirvenne, M.V., and Gabriels, D. 2000. Extending the RUSLE with the Monte Carlo error propagation technique to predict long-term average off-site sediment accumulation. J. Soil Water Conservation, 55: 35-42.
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11. Deore, S.J. 2006. Prioritization of Micro-watersheds of Upper Bhama Basin on the Basis of Soil Erosion Risk Using Remote Sensing and GIS Technology. Ph.D. Thesis. Department of Geography. University of Pune.
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23. Renard, K. G., & Freimund, J.R. 1994. Using monthly precipitation data to estimate the R factor in the revised USLE, J. Hydrol, 157: 287-306. [DOI:10.1016/0022-1694(94)90110-4]
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27. Wang, G., Gertner, G., Fang, S., and Anderson, AB. 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. [DOI:10.14358/pers.69.8.889]
28. Wijitkosum S. 2012, Impacts of land use changes on soil erosion in Pa Deng sub-district, adjacent area of Kaeng Krachan National Park, Thailand. Soil and Water Research, 7(1): 10-17.
29. Williams JR. 1975. Sediment routing for agricultural watersheds. Water Resour Bull 11: 965–974. [DOI:10.1111/j.1752-1688.1975.tb01817.x]
30. Wischmeier, W.H., and Smith, D.D. 1978. Predicting rainfall erosion. Losses: a guide to conservation planning. Agriculture Handbook, Vol. 537. US Department of Agriculture, Washington, DC.
31. Ahmed, T. 2000. Fuzzy class membership approach to soil modeling, Agricultural Systems,63: 97-110.
32. Alkharabsheh, M. M., Alexandeidis, T. K., Bilas, G., Misopolinos, N., & Silleos, N. 2013. The Impact of Land Cover Change on soil erosin hazard in northen Jordan using remote sensing and GIS. Procedia Environmental Sciences, 19: 912-921. [DOI:10.1016/j.proenv.2013.06.101]
33. Bahadur, K. C. Krishna. 2009. Mapping soil erosion susceptibility using remote sensing and GIS: a case of the Upper Nam Wa Watershed, Nan Province, Thailand. Environ Geol, 57:695–705. DOI 10.1007/s00254-008-1348-3
34. Bartsch, KP. Van Miegroet, H., Boettinger, J., Dobrwolski, JP. 2002. Using empirical erosion models and GIS to determine erosion risk at Camp Williams, Journal of Soil and Water Conservation, 57: 29–37.
35. Benkobi, L., Trlica, M.J., and Smith, J.L. 1994. Evaluation of a refined surface cover subfactor for use in RUSLE. J. Range Manage. 47: 74-78. [DOI:10.2307/4002845]
36. Biesemans, J., Meirvenne, M.V., and Gabriels, D. 2000. Extending the RUSLE with the Monte Carlo error propagation technique to predict long-term average off-site sediment accumulation. J. Soil Water Conservation, 55: 35-42.
37. Boardman J., Ligneau L., De Roo A.P.J., and Vandaele K. 1994. Flooding of property by run off from agricultural land in northwestern Europe. Geomorph, 10: 183-196. [DOI:10.1016/b978-0-444-82012-9.50017-7]
38. Bruce, R.R., Langdale, G.W., East, L.J., and Miller, W.P. 1995. Surface soil degradation and soil productivity restoration and maintanace. Soil Sci. Soc. Am. J. 59: 654-660. doi:10.2136/sssaj1995.03615995005900030003x
39. Chakroun, H., Bonn, F., Fortin, J.P., 1993, Combination of single storm erosion and hydrological models into a geographic information system, Farm Land Erosion: In Temperate Plains Environment and Hills, 261–270. [DOI:10.1016/b978-0-444-81466-1.50027-7]
40. Clark R.D. 1980. Erosion condition classification system. Bureau of Land Management, Denver Service Center, Denver CO.
41. Deore, S.J. 2006. Prioritization of Micro-watersheds of Upper Bhama Basin on the Basis of Soil Erosion Risk Using Remote Sensing and GIS Technology. Ph.D. Thesis. Department of Geography. University of Pune.
42. Fox, A.D., Desholm, M., Kahlert, J., Christensen, T.K., and Petersen, K. 2006. Information needs to support environmental impact assessment of the effects of European marine offshore wind farms on birds. Special Issue: Wind, Fire and Water: Renewable Energy and Birds. 148: 129-144. [DOI:10.1111/j.1474-919x.2006.00510.x]
43. Garcia-ruiz, j. m. 2010. The effects of land uses on soil erosion in Spain: A review. Catena, 81(1), 1-11. [DOI:10.1016/j.catena.2010.01.001]
44. Haan, C.T., Barfield, B.J., and Hayes, J.C. 1994. Design hydrology and sedimentology for small catchments. Academic Press, San Diego.
45. Haen HD. 1991. Environmental consequences of agricultural growth In: Vosti SA, Reardon T, Winfried Von Urff (eds) Agricultural sustainability, growth and poverty alleviation and policies, Feldafing.
46. Laflen, J.M., Lane, L.J., Foster, G.R. 1991. WEPP: a new generation of erosion prediction technology, Journal of Soil and Water Conservation, 46, No. 1, PP. 34–38.
47. McCool, D.K., Brown, L.C., and Foster, G.R. 1987. Revised slope steepness factor for the universal soil loss equation. Trans. Am. Soc. Agric. Eng. 30: 1387-1396. [DOI:10.13031/2013.30576]
48. Millward, A.A., and Mersey, J.E. 1999. Adapting the RUSLE to model soil erosion potential in a mountainous tropical watershed. Catena, 3: 109-129. [DOI:10.1016/s0341-8162(99)00067-3]
49. Monchareon L .1982. Application of soil maps and report for soil and water conservation. Department of land development, Bangkok.
50. Moore, I., Burch, G., 1986, Physical basis of the length-slope factor in the universal soil loss equation, Soil Science Society of America Journal, 50: 1294–1298. [DOI:10.2136/sssaj1986.03615995005000050042x]
51. Pacheco F.A.L., Varandas S.G.P., Fernandes L.S., Junior R.V. 2014. Soil losses in rural watersheds with environmental land use conflicts. Sci. Total Environ. 485: 110 - 120
52. Pimental D., Harvey C., Resosudarmo P., Sinclair K., Kurz D., McNair M., Crist S., Shpritz L., Saffouri R., and Blair R. 1995. Environmental costs of soil erosion and conservation benefits. Science, 267: 1117-1123.
53. Renard, K. G., & Freimund, J.R. 1994. Using monthly precipitation data to estimate the R factor in the revised USLE, J. Hydrol, 157: 287-306. [DOI:10.1016/0022-1694(94)90110-4]
54. Renard, K.G., Foster, G.R., Weesies, G.A. & Porter, J.P., 1991, RUSLE: revised universal soil loss equation. Journal of Soil and Water Conservation, 46: 30-33.
55. Van der Knijff, J.M., Jones, R.J.A., Montanarella, L. 2000. Soil Erosion Risk Assessment in Europe, EUR 19044 EN. Office for Official Publications of the European Communities, Luxembourg.
56. Veihe, A. 2002. The spatial variability of erodibility and its relation to soil types: a study from northern Ghana, Geoderma, 106: 101-120. [DOI:10.1016/s0016-7061(01)00120-3]
57. Wang, G., Gertner, G., Fang, S., and Anderson, AB. 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. [DOI:10.14358/pers.69.8.889]
58. Wijitkosum S. 2012, Impacts of land use changes on soil erosion in Pa Deng sub-district, adjacent area of Kaeng Krachan National Park, Thailand. Soil and Water Research, 7(1): 10-17.
59. Williams JR. 1975. Sediment routing for agricultural watersheds. Water Resour Bull 11: 965–974. [DOI:10.1111/j.1752-1688.1975.tb01817.x]
60. Wischmeier, W.H., and Smith, D.D. 1978. Predicting rainfall erosion. Losses: a guide to conservation planning. Agriculture Handbook, Vol. 537. US Department of Agriculture, Washington, DC.

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