• صفحه اصلی
  • ارزیابی وضعیت بیابان‌زایی در دشت شهربابک با استفاده از مدل مدالوس و داده‌های سنجش از دور

اشتراک گذاری

آدرس مقاله


کد مقاله : NEI-2302-1209 (R3) بازدید : 203 صفحه: 38 - 59

نوع مقاله: پژوهشی

ارزیابی وضعیت بیابان‌زایی در دشت شهربابک با استفاده از مدل مدالوس و داده‌های سنجش از دور

محورهای موضوعی : بیابان زدایی , GIS

محمد ابراهیم عفیفی 1 , وحید سهرابی 2

1 - عضو هیات علمی گروه جغرافیا دانشگاه ازاد اسلامی واحد لارستان
2 - جغرافیا و برنامه ریزی شهری،دانشکده علوم انسانی،دانشگاه آزاد واحد لارستان،ایران

تاریخ دریافت : 1401/10/18 تاریخ پذیرش : 1402/02/18 تاریخ انتشار : 1402/03/31

کلید واژه: مدالوس, بیابان‌زایی, سنجش‌ازدور, شهربابک,

چکیده مقاله :

مسئله تحقیق: تخریب سرزمین یک فرایند جهانی است که در نهایت منجر به کاهش حاصلخیزی خاک می‌شود و اگر مفهوم آن را نوعی ناپایداری و عدم تعادل در رابطه بین انسان و محیط قلمداد کنیم، باید پذیرفت که بخش اعظمی از جهان و کشور ایران با این مشکل زیست‌محیطی روبرو است. مقابله با پدیده تخریب سرزمین و بیابان‌زایی نیازمند ارزیابی و پایش نوع و شدت تخریب اراضی، تعیین دلایل تخریب صورت‌گرفته و اتخاذ اقدامات لازم برای مواجهه با مشکل پیش‌آمده و نیز بررسی صحت انجام پروژه‌های مزبور است .هدف ارزیابی بیابان‌زایی دشت شهربابک می‌باشد. فناوری سنجش‌ازدور نقش بسیار ارزنده‌ای در ارزیابی و پایش تخریب سرزمین و بیابان‌زایی در مقیاس‌های محلی، منطقه‌ای و جهانی دارد و سبب ایجاد رویکرد جدیدی در مطالعات مربوط به ارزیابی و پایش بیابان‌زایی گردیده است . باتوجه‌به اهمیت مسئله تخریب، در این مطالعه سعی شد با استفاده از داده‌های سنجش‌ازدور و مدل مدالوس به ارزیابی بیابان‌زایی حوزه آبخیز شهربابک پرداخته شود. در گام اول، بر اساس وضعیت منطقه، شش معیار اقلیم، خاک، پوشش گیاهی، آب زیرزمینی و مدیریت و سیاست برای ارزیابی میزان تخریب، مدنظر قرار گرفت. شاخص‌ها بر اساس میزان تأثیرشان بر فرایند تخریب، کمّی و به هرکدام از آن‌ها طبق روش فازی امتیازی بین 5/0 تا 1 داده شد و در مقیاس پیکسل مورد بررسی قرار گرفتند. نتایج به‌دست‌آمده حاکی از آن است که 4 درصد از سطح منطقه در رده خفیف،10 درصد منطقه در رده متوسط و 86 درصد منطقه در رده شدید بیابان زایی قرار دارد. از نظر حساسیت محدوده به تخریب، 4% از مساحت کل محدوده در طبقه بالقوه، 22% در طبقه شکننده A، %50 در طبقه شکننده B، %20 در طبقه شکننده C و 3% در طبقه بحرانی قرار دارد؛ بنابراین حدود 92% از مساحت منطقه در طبقه شکننده قرار دارد.

چکیده انگلیسی:

Research problem: Land destruction is a global process that ultimately leads to a decrease in soil fertility, and if we consider its concept as a kind of instability and imbalance in the relationship between humans and the environment, it should be accepted that a large part of the world and the country of Iran are dealing with this problem. The environment is facing. Dealing with the phenomenon of land destruction and desertification requires evaluating and monitoring the type and severity of land destruction, determining the causes of the destruction and taking the necessary measures to face the problem, as well as checking the accuracy of the said projects. The aim of desertification evaluation is Babak Shahr Plain. Remote sensing technology plays a very valuable role in the evaluation and monitoring of land degradation and desertification at local, regional and global scales and has led to the creation of a new approach in studies related to the evaluation and monitoring of desertification. Considering the importance of the destruction issue, in this study, an attempt was made to evaluate the desertification of the Shahrbabak watershed using remote sensing data and Medalus model. In the first step, based on the situation of the region, six parameters of climate, soil, vegetation, underground water and management and policy were considered to evaluate the level of destruction. The indicators were quantified based on their effect on the destruction process and each of them was given a score between 0.5 and 1.5 according to the fuzzy method and were studied in pixel scale. The obtained results indicate that 4% of the area is in the mild category, 10% of the area is in the moderate category, and 86% of the area is in the severe category of desertification. In terms of the area's sensitivity to destruction, 4% of the total area of the area is in the potential class, 22% in the fragile class A, 50% in the fragile class B, 20% in the fragile class C and 3% in the critical class; Therefore, about 92% of the area of the region is in the fragile layer.

منابع و مأخذ:


  1. Abuzaid, A. S., Abdelatif, A. D. 2022. Assessment of desertification using modified MEDALUS model in the north Nile Delta, Egypt. Geoderma, 405, 115400.
    2.
  2. Ahmadi, H. 2006. Applied Geomorphology, Wind Erosion. Tehran University Press, pp. 592.
    3.
  3. Ahmad, B., Moghadamnia A., Hashemi, Z., Javadi M. R., Miri, A.2013. Valuation of desertification with wind erosion criteria using Micd.fao.unep models in Sistan drainage area. Iran Pasture and Desert Research Quarterly, Volume 19, Number 4.
    4.
  4. Arab-Amari, R., Rezaei, K., Sohrabi. B. 2018. Quantitative assessment of desertification risk using modified Medalus model, case study: Shahroud-Bastam watershed. Watershed Engineering and Management, 508-522, 11(2).
    5.
  5. Arya, A.S., Dhinwa, P.S., Pathan, S.K., Raj, K.G .2009. Desertification land degradation status mapping of India. Current Science, 97(10): 1478-1483.
    6.
  6. 6.Bakr, N., Weindorf, D.C., Bahnassy, M.H., Marei, S.M., El-Badawi, M.M. 2010. Monitoring land cover changes in a newly reclaimed area of Egypt using multi-temporal Landsat data. Applied Geography 30(4),592-605.
    7.
  7. 7.Boudjemline, F., Semar, A. 2018. Assessment and mapping of desertification sensitivity with MEDALUS model and GIS–Case study: basin of Hodna, Algeria. Journal of water and land development, 36(1): 17-26. doi:https://doi.org/10.2478/jwld-2018-0002
    8.
  8. 8.Contador, J.F.L., Schnabel, S., Gutiérrez, A.G.,Fernandez, M.P. 2009. Mapping sensitivity to land degradation in Extremadura. SW Spain. Land Degradation & Development, 20(2): 129-144. doi:https://doi.org/10.1002/ldr.884
    9.
  9. D’Odorico, P., Bhattachan, A., Davis, k., Ravi, S., Runyan, C. 2013. Global desertification: Drivers and feedbacks. Advances in Water Resources, 51: 326–344. doi:https://doi.org/10.1016/j.advwatres.2012.01.01
    10.
  10. 10.Dutta, S., Chaudhuri, G. 2015. Evaluating environmental sensitivity of arid and semiarid regions in northeastern Rajasthan, India. Geographical Review, 105(4):441 .doi:https://doi.org/10.1111/j.1931-0846.2015.12093.x
    11.
  11. Zahtabyan, Gh., Javadi, M.R., Ahmadi, H., Azarnivand, H. 2018. Investigating the effect of wind erosion due to desertification erosion and presenting a regional model of desertification in the Mahan watershed, Journal of Research and Development in Natural Resources, Number 73, Winter 2015.
    12.
  12. Golafshani, M ., Zahtabian, Gh ., Khosravi, H.,Malekian, A ., Ahmad Ali, Khalid and Bagheri, S. 1400.Early warning of desertification of the Mashhad plain aquifer based on the prediction of qualitative and quantitative parameters of groundwater, Irrigation and Water Engineering of Iran, Vol. : 11, number: 4.
    13.
  13. Hadeel, A.S., Mushtak, T., Jabbar, M.T., Chen, X. 2010.Application of remote sensing and GIS in the study of environmental sensitivity to desertification: a case study in Basrah Province, southern part of Iraq. Applied Geomatics, 2(3): 101-112.doi:https:// doi.org/10.1007/s12518-010-0024-y
    14.
  14. Hashemi, Z., Pahlwanroi, A., Moghadamnia, A., Javadi, M. R., Miri, A.2013.Evaluation of the potential of desertification using the IMDPA model in the Sistan plain (Zahk case study).Desert Ecosystem Engineering Journal , number 5.
    15.
  15. Javadi, M. R. 2008. Evaluation of management measures applied to control desert conditions in the Mahan watershed. The 5th National Conference on Watershed Sciences and Engineering of Iran. Sustainable management of natural disasters. Gorgan University of Agricultural Sciences and Natural Resources.
    16.
  16. Kadović R, Ali Mansour, Y., Bohajar. V., Perović, S., Belanović Simić, M., Todosijević, S., Tošić, M., Anđelić, D., Mlađan, Dovezenski U. 2016. Land sensitivity analysis of degradation using MEDALUS model, case study: Deliblato Sands, Serbia. Archives of Environmental Protection, 42(4): 114-124.
    17.
  17. 17.Kazeminia, A., Rangzan, K., Mahmoudabadi, M. 2016. study of the intensity of desertification using Medalos model (case study: West Ahvaz lands), Quarterly Journal of Remote Sensing and Geographical Information System in Natural Resources, Volume: 8, Number: 2.
    18.
  18. Lahlaoi H., Rhinane, H., Hilali, A., Lahssini, S., Moukrim, S. 2017. Desertification assessment using MEDALUS model in watershed Oued El Maleh, Morocco. Geosciences, 7(50): 1-16. doi:https://doi.org/10.3390/geosciences7030050
    19.
  19. Lee, E.J, Piao, D., Song, C., Kim, J., Lim, H., Kim, E., Moon, J., Kafatos, M., Lamchin ,M., Jeon, S.W., Lee, W.2019. Assessing environmentally sensitive land to desertification using MEDALUS method in Mongolia. Forest Science and Technology, 15(4): 210-220
    20.
  20. 20.Melchiade, B. 2014. Secretariat of the convention to combat desertification. CSD-17 Intergovernmental Preparatory Meeting Panel on Desertification. New York, February 26.
    21.
  21. 21.Parori, A., Hosseini, S., Pahlvanroi, A., Moghadamnia, A., Shahriari, A., Ekhsati, M. 1390.Comparative study of ICD and ESAs models in order to prepare a map of desertification in Niatek region of Sistan. Watershed research (research and development), 24 (90),42-54 .
    22.
  22. Pradhan, B., Saber, H., Rahimi, A. 2018. Desertification sensitivity analysis using MEDALUS model and GIS: a case study of the Oases of Middle Draa Valley, Morocco. Sensors, 18(7): 2230.doi:https://doi.org/10.3390/s18072230
    23.
  23. Prăvălie, R., Patriche, C., Săvulescu, I., Sîrodoev, I., Bandoc, G., & Sfîcă, L. 2020. Spatial assessment of land sensitivity to degradation across Romania. A quantitative approach based on the modified MEDALUS methodology. Catena, 187, 104407.‏
    24.
  24. Rahimi, M., Damavandi, A., Jafarian, V. 2014. review of the applications of remote sensing in the assessment and monitoring of land degradation and desertification, Geographical Information Quarterly (Sephehr), Volume 22, Number 87, pp.115-128.
    25.
  25. Rasuly, A., Naghdifar, R., Rasoli, M. 2010. Detecting of Arasbaran forest changes applying image processing procedures and GIS techniques. Procedia Environmental Sciences, 2: 454-464.
    26.
  26. Rezaipoor Baghedar, A.H, Bahrami, H., Rafee, S., Khosravi ,H. 2015. An evaluation on the intensity of desertification by using IMDPA model (Case study: Baghedar region, Yazd). Arid Regions Geographic Studies, 5(19): 42-54.
    27.
  27. Sarbari, M., Unq, M., Mohammadian ,B., Akbari, M. 2019. Evaluation and modeling of temporal-spatial land use changes in the expansion of the intensity of desertification in the arid regions of northeastern Iran (fern), Quarterly Journal of Geography and Environmental Hazards, Vol. : 9, number: 2.
    28.
  28. Schulz, J.J., Cayuela, L., Echeverria, C., Salas, J., Benayas, J. 2010. Monitoring land cover change of the dryland forest landscape ofCentral Chile (1975–2008). AppliedGeography, 30(3): 436-447.
    29.
  29. Seifi, A., Riahi, M. 2016. qualitative zoning of Shahrbabak aquifer from the perspective of erosivity and sedimentation, suitability for agriculture, drinking and pressurized irrigation, Journal of Water and Wastewater, Volume: 28, Number: 111.
    30.
  30. Taghipour, S., Fazeli, A., Kazemi, B. 2016. A case study of desertification hazard mapping using the MEDALUS (ESAs) methodology in southwest Iran. Journal of Natural Resources and Development, 6: 1–8.
    31.
  31. 31.UNEP, 1992, World Atlas of Desertification, Edward Arnold, London.
    32.
  32. 32.Veron, S.R., Paruelo, J.M., Oesterheld, M. 2006.Assessing desertification, Journal of Arid Environments, 66: 751-763.
    33.
  33. Wijitkosum, S. 2020. Reducing vulnerability to desertification by using the spatial measures in a degraded area in Thailand. Land, 9(2): .doi:https://doi.org/10.3390 /land9020049
    34.
  34. Xu, D., Ding, X. 2018. Assessing the impact of desertification dynamics onregional ecosystem service value in North China from 1981 to 2010. EcosystemServices,172-180.doi:https://doi.org/10.1016/j.ecoser.2018.03.002
    35.
  35. Xu, D., Song, A., Li, D., Ding, X., Wang, Z. 2019. Assessing the relative role of climate change and human activities in desertification of North China from 1981 to 2010. Frontiers of Earth Science, 13(1): 43-54. doi:https://doi.org/10.1007/s11707-018-0706-Xu D, You X, Xia C. 2019.
    36.
  36. 35.Yaghmaian, N., Asadi, H., Rezaei, Siddiqa.2016. zoning and risk assessment of land degradation using Medalos method in Siahpoosh basin of Ardabil province, water and soil protection researches, volume: 24, number: 1.
    37.
  37. Zhang, C., Wang, X., Li, J., Hua, T. 2020. Identifying the effect of climate change on desertification in northern China via trend analysis of potential evapotranspiration andprecipitation.EcologicalIndicators,112:106141.doi:https://doi.org/10.1016/j.ecolind.2020.106141
    38.
  38. Hashemi, Z., Pahlwanroi, A., Moghadam Niya,A., Javadi, M.R., Miri, A. 2019 Evaluation of the current desertification situation in the Sistan drainage area with an emphasis on water erosion criteria Watershed Research Journal (Ancient Research and Construction), Number 91.
    39.
_||_

مقالات مرتبط

حقوق این وب‌سایت متعلق به سامانه مدیریت نشریات دانشگاه آزاد اسلامی است.
حق نشر © 1403-1400

صفحه اصلی| عضویت/ ورود| درباره سند| تماس با ما|
[English] [العربية] [en] [ar]