مطالعات جغرافیایی مناطق کوهستانی

مطالعات جغرافیایی مناطق کوهستانی

پهنه‌­بندی پتانسیل خطر زمین­‌لغزش در شهرستان علی‌­آباد کتول

نوع مقاله : مقاله پژوهشی

نویسندگان
گروه جغرافیای طبیعی، دانشکده علوم اجتماعی، دانشگاه محقق اردبیلی، اردبیل، ایران.
چکیده
هدف: زمین‌لغزش از مهمترین مخاطرات محیطی می­‌باشد که وقوع آن خسارات انسانی و اقتصادی فراوانی را درپی دارد و با شناسایی مناطق در معرض این خطر، می‌توان درحد ممکن از وقوع این پدیده جلوگیری کرد. شهرستان علی‌آباد کتول با توجه به شرایط خاص آب‌وهوایی، فیزیوگرافی، زمین‌شناسی و انسانی، همواره درمعرض خطر زمین‌لغزش بوده است. لذا، هدف از این پژوهش شناسایی پهنه‌های مستعد وقوع زمین‌لغزش در سطح این شهرستان می‌باشد.
روش: با مرور پیشینۀ پژوهشی، استفاده از مطالعات میدانی و بررسی شرایط موجود در منطقه، ابتدا عوامل ارتفاع، شیب، جهت شیب، زمین‌شناسی، فاصله از گسل، فاصله از رودخانه، فاصله از راه‌های ارتباطی، کاربری اراضی و بارش به‌عنوان متغیرهای تأثیرگذار بر وقوع زمین‌لغزش شناسایی شد. در نهایت نقشۀ حساسیت زمینلغزش با استفاده از روش تصمیم‌گیری چندمعیارۀ مارکوس استخراج گردید.
نتایج: با توجه به نتایج حاصله، به‌ترتیب؛ عوامل شیب، کاربری‌اراضی و بارش با ضرایب وزنی 153/0، 142/0 و 138/0 بیشترین اهمّیت را در وقوع زمین‌لغزش شهرستان علی‌آبادکتول، به خود اختصاص دادند. با نظر به نقشة پهنه‌‌بندی به ترتیب؛ 902/151 و 622/253 کیلومترمربع از مساحت شهرستان، در طبقۀ بسیار پرخطر و پرخطر قرار دارد که بایستی این پهنه‌ها از لحاظ کارهای مدیریتی و اجرای پروژههای حفاظتی در اولویت توجه قرار گیرند. همچنین با توجه به بهره‌گیری از روش منحنی راک، دقت روش مارکوس در شناسایی مناطق مستعد وقوع خطر زمین‌لغزش در شهرستان علی‌آباد کتول با سطح زیرمنحنی (89/0)، بسیارخوب می‌باشد.
نتیجه­ گیری: نقشه پهنه‌بندی خطر زمین‌لغزش شهرستان علی‌آباد کتول نشان می‌دهد که بخش قابل توجهی از مساحت آن (حدود ۴۱۴ کیلومتر مربع) در طبقات پرخطر و بسیار پرخطر قرار دارد که نیازمند اولویت‌بندی فوری برای اقدامات مدیریتی و حفاظتی است.
کلیدواژه‌ها

Abdulla, A., Baryannis, G., & Badi, I. 2023. An integrated machine learning and MARCOS method for supplier evaluation and selection. Decision Analytics Journal, 9, 100342, 1-11. https://doi.org/10.1016/j.dajour.2023.100342
Abedini, M., Mozafari, H. & Faalnaziri, M. 2022. Investigating and comparing the effectiveness of information value models and frequency ratio coefficient and Shannon's entropy in zoning rock fall risk (case study: Zanjan-Teham-Taram road). Journal of Geographical Studies of Mountainous Areas, 3(1), 55-75. https://doi.org/10.52547/gsma.3.1.5 (In Persian).
Ahmadpour, A., Ghaforpur Anbaran, P. & Babayyan, H. R. 2024. Landslide and Rockfall susceptibility zoning in the area of Kerend-e Gharb and Sarpol –e Zahab (the axis of Pataq pass) in Kermanshah province. Journal of Geographical Studies of Mountainous Areas, 5(2), 39-58. https://doi.org/10.22034/gsma.2024.715552  (In Persian).
Arshad, MW., Mesran, M., Setiawansyah, S., Ryan Randy Suryono, RR., & Rahmanto, Y (2023). Combination of CRITIC Weighting Method and Multi-Atributive Ideal-Real Comparative Analysis in Staff Admissions. Journal of Computer Science and Information Technology, 2 (4), 77-86. https://doi.org/10.47065/explorer. v4i2.1428
Asghari Saraskanroud, S., & Piroozi, E .2024. Identification and Zoning of Areas Prone to the Occurrence of Landslides Using the Aras Multi-Criteria Analysis Method (Study Area: Qaranqoochay Watershed in the Southeast of East Azarbaijan Province). Geography and Environmental Planning, 35(3), 65-94. https://doi.org/10.22108/gep.2024.140985.16396 (In Persian).
Asghari saraskanroud, S., & Piroozi, E. 2022. Comparative evaluation of WLC, OWA, VIKOR, and MABAC multi-criteria decision-making methods in landslide risk zoning Case study: Givi-chay watershed of Ardabil province. Physical Geography Research, 54(1), 65-94. https://doi.org/10.22059/jphgr.2022.333658.1007656 (In Persian).
Asghari Sareskanrood, S., Mohammadzadeh Shishegaram, M., & Asghari Sareskanrood, S (2022). Zoning and estimation of range movements in Hashtroud city using radar interferometry and MABAC model. Environmental Management Hazards, 9(2), 133-150. https://doi.org/10.22059/jhsci.2022.346994.736 (In Persian).
Badola, SH., Mishra, V.N., Parkash, S., & Pandey, M. 2023. Rule-based fuzzy inference system for landslide susceptibility mapping along national highway 7 in Garhwal Himalayas, India. Quaternary Science Advances, 11, 1-12. https://doi.org/10.1016/j.qsa.2023.100093
Bhattacharyya, R., & Mukherjee, S. 2021. Fuzzy Membership Function Evaluation by Non-LinearRegression: An Algorithmic Approach. Fuzzy infomation and engineering, 12 (4), 412–434. https://doi.org/10.1080/16168658.2021.1911567
Caleca, F., Scaini, C., Frodella, W., & Tofani, V. 2024. Regional-scale landslide risk assessment in Central Asia. Nat. Hazards Earth Syst. Sci., 24, 13–27. https://doi.org/10.5194/nhess-24-13-2024.
Entezari, M., Esteki, S., & Gholamhaydari, H. 2024. Investigation of State of Landslide in Tarom Watershed Using Risk-Vulnerability Superimposed Model. Journal of Geography and Planning, 28(89), 61-39. https://doi.org/10.22034/gp.2023.54607.3073 (In Persian).
Esfandyari Darabad, F., Rostami, G., Mostafazadeh, R. & Abedini, M. 2024. Spatial assessment and zoning of landslide risk in Zamkan watershed using support vector machine and logistic regression. Hydrogeomorphology, 11(40), 123-102. https://doi.org/10.22034/hyd.2024.61467.1737 (In Persian).
Esposito, G., Carabella, C., Paglia, G., & Miccadei, E. 2021. Relationships between Morphostructural/Geological Framework and Landslide Types: Historical Landslides in the Hilly Piedmont Area of Abruzzo Region (Central Italy). Land, 10(3), 287, 1-28. https://doi.org/10.3390/land10030287
Golipour, S., Hosseinzadeh, S. R. & pourali, M. 2022. Identifying landslide prone slopes and classification of its types using logistic regression model and fuzzy logic (Case study: Ghahremanlou Catchment, North Khorasan Province). Quantitative Geomorphological Research, 11(1), 209-228. https://doi.org/10.22034/gmpj.2022.336132.1343 (In Persian).
Jafarzadeh Ghoushchi, S., Shaffiee Haghshenas, S., Memarpour Ghiaci, A. Guido, G., & Vitale, A. 2023. Road safety assessment and risks prioritization using an integrated SWARA and MARCOS approach under spherical fuzzy environment. Neural Comput & Applic, 35, 4549–4567. https://doi.org/10.1007/s00521-022-07929-4
Javan, F., Atashbahar, R. and Motalebpoor, A. (2025). Zoning of Environmental Hazards in Tourism Destinations with Emphasis on Flooding (Case Study: Sarvabad County, Kurdistan Province). Journal of Environmental Research in Mountainous Regions, 1(3), 43-56. https://doi.org/10.22034/ermr.2025.144141.1025 (In Persian).
Keshavarz, S. R., Bayati Eshkaftaki, J. & Almodaresi, S. A. 2022. Spatial analysis of the amount of landslides using radar interferometric technique in order to reduce hazards (Study area: Sarbaz area in Isfahan province). Environmental Management Hazards, 9(3), 271-288. https://doi.org/10.22059/jhsci.2023.347893.741 (In Persian).
Kumar, A., Sharma, R., & Bansal, V. 2022. Spatial Prediction of Landslide Hazard using GIS-multi-criteria Decision Analysis in Kullu District of Himachal Pradesh, India. Journal of Mining and Environment, 13(4), 943-956. https://doi.org/10.22044/jme.2022.12235.2222 .
Madadi, A. & piroozi, E. 2023. Landslide risk zoning in the upstream basin of Yamchi Dam in Ardabil province, using multi-criteria decision making methods MARCOS and CODAS. Quantitative Geomorphological Research, 12(1), 73-94. https://doi.org/10.22034/gmpj.2023.370812.1390 (In Persian).
Madadi, A., Piroozi, E. & Faal Naziri, M. 2021. A Comparative Evaluation of MABAC and CODAS Multi-Criteria Decision Algorithms in Landslide Risk Zoning (Case Study: Kowsar County). Geography and Environmental Planning, 31(4), 1-24. https://doi.org/10.22108/gep.2020.124723.1348. (In Persian).
Mahmoody-Vanolya, N., Argany, M. & Jelokhani-Niaraki, M. 2021. Multi-hazard potential mapping of Mazandaran province using multi-criteria spatial decision analysis. Environmental Management Hazards, 8(4), 395-411. https://doi.org/10.22059/jhsci.2022.332933.686 (In Persian).
Materazzi, M., Bufalini, M., Gentilucci, M., Pambianchi, G., Aringoli, D., & Farabollini, P. 2021. Landslide hazard assessment in a monoclinal setting (Central Italy): Numericalvs, geomorphological approach. Land, 10 (6), 624, 1-22. https://doi.org/10.3390/land10060624.
Nanehkaran, Y. A., Chen, B., Cemiloglu, A., Chen, J., Anwar, S., Azarafza, M., & Derakhshani, R. 2023. Riverside Landslide Susceptibility Overview: Leveraging Artificial Neural Networks and Machine Learning in Accordance with the United Nations (UN) Sustainable Development Goals. Water, 15(15), 2707, 1-28. https://doi.org/10.3390/w15152707.
Nasiri, M., Mohammadzade, M., lotfalian, M., & Parsakhoo A. 2022. Zoning and Field Study of Landslid es along Forest Roads of Darabkola-Sari. J Watershed Manage Res. 13(26), 105-114. https://doi.org/10.52547/jwmr.13.26.105 (In Persian).
Ou, L., Huang, C. & Cao, Y. 2024. Research on landslide hazard assessment based on improved analytic hierarchy process optimizing multiple rainfall indicators. Discov Appl Sci, 6 (409), 1-16. https://doi.org/10.1007/s42452-024-06119-2.
Rostamizad, G., & Dastranj, A. 2024. Evaluating the sensitivity of the landslide event using the support vector machine algorithm. Water and Soil Management and Modelling, 4(4), 299-312. https://doi.org/10.22098/mmws.2023.13934.1379 (In Persian).
Sadeghi, H. and Javan, F. (2024). The Evaluation of Tourist Villages of Iran in terms of Geophysical Vulnerability using Fuzzy Scenarios. Journal of Rural Research, 15(4), 85-100. https://doi.org/10.22059/jrur.2024.383580.1993 (In Persian).
Sadeghi, H. and Javan,F. (2025). Vulnerability of Iranian tourism villages in terms of Landslide hazard using GIS. Geography, 23(84), 153-170. https://doi.org/10.22034/jiga.2025.2055364.1385 (In Persian).
Saha, A., Villuri, VGK., Bhardwaj, A., & Kumar, S.A. 2023. Multi-Criteria Decision Analysis (MCDA) Approach for Landslide Susceptibility Mapping of a Part of Darjeeling District in North-East Himalaya, India. Applied Science, 13(8), 5062, 1-23. https://doi.org/10.3390/app130850629.
Sharifi, H., Ramazanipore, M., Ebrahimi, L. & Haghzad, A. 2022. Landslide hazard zoning of Noor city using network analysis model. Economic Geography Research, 2(6), 40-55. https://dor.org/20.1001.1.27173747.1400.2.6.4.0. (In Persian).
Sim, K.B., Lee, M.L. & Wong, S.Y. A. 2022. review of landslide acceptable risk and tolerable risk. Geoenviron Disasters, 9 (3), 1-17. https://doi.org/10.1186/s40677-022-00205-6.
Singh, U., Nandan, R., & Tiwari, A. 2024. Recent Trends and Techniques in Landslide Hazard Assessment. Qeios,4, 1-12.https://doi.org/10.32388/LBYEQN .
Tesfa, CH., & Sewnet, D. 2024. GIS-based MCDM approach for landslide hazard zonation mapping in east Gojjam zone, central Ethiopia. Quaternary Science Advances, 15 (10), 1-11. https://doi.org/10.1016/j.qsa.2024.100210.
Vojtekova, J., & Vojtek, M. 2020. Assessment of landslide susceptibility at a localspatial scale applying the multi-criteria analysisand GIS: a case study from Slovaki, Geomatics. Natural Hazards and Risk, 11 (1), 131–148. https://doi.org/10.1080/19475705.2020.1713233.
Zivari, R. 2015. Karst Development Potential in Khosh yeilagh Carbonate Formation in Aliabad Katul area, Golestan Province, Master's thesis, Faculty of Earth Sciences, Applied Geology, Kharazmi University. (In Persian) https://irandoc.ac.ir/