نوع مقاله : پژوهشی

نویسندگان

1 دانشجوی دکترا دانشگاه تبریز

2 استاد تمام گروه ژئومورفولوژی دانشگاه تبریز

3 استاد تمام گروه ژئومورفولوژی تبریز

چکیده

زمین‌لغزش هر ساله جان هزاران نفر را در سراسر جهان می‌گیرد و خسارت‌های هنگفتی را به مردم و دولت‌ها تحمیل می‌کند. پهنه‌بندی خطر زمین‌لغزش، نواحی سطح زمین را به مناطق ویژه و تفکیک ‌شده‌ای از درجات بالقوه و بالفعل به لحاظ خطرپذیری تقسیم‌بندی می‌کند. این امر می‌تواند مبنایی برای برنامه‌ریزی‌های بلندمدت در سطح منطقه‌ای و محلی محسوب شود. هدف از انجام این پژوهش، بررسی و پهنه‌بندی خطر زمین‌لغزش در حوضه رود زرد واقع در شرق استان خوزستان با استفاده از روش منطق فازی است. بدین منظور ابتدا از طریق بازدیدهای میدانی، نقشه‌های زمین‌شناسی و توپوگرافی و با مرور منابع قبلی و بررسی شرایط منطقه، نه عامل طبقات ارتفاعی، شیب، جهت شیب، فاصله از گسل، فاصله از رودخانه، فاصله از جاده، بارش، لیتولوژی و کاربری اراضی به ‌عنوان عوامل مؤثر، بررسی و انتخاب شدند. پس از طبقه‌بندی داده‌ها و مرحله فازی‌سازی، نقشه‌های پهنه‌بندی خطر زمین‌لغزش با استفاده از عملگر گامای فازی با مقادیر 7/0، 8/0، 9/0 تهیه شدند. نقشه‌های به ‌دست ‌آمده در 5 کلاس بسیار زیاد، زیاد، متوسط، کم و بسیار کم طبقه‌بندی شدند. نتایج حاصل از جمع کیفی نشان داد که عملگر گامای 9/0 فازی در مقایسه با دیگر عملگرهای فازی مناسب‌تر است. تحلیل نقشه‌های طبقه‌بندی ‌شده نشان داد که 56/21 درصد از مساحت منطقه در پهنه با خطر زیاد و 24/43 درصد از مساحت منطقه در پهنه با خطر کم قرار گرفته است. در‌ مجموع، می‌توان گفت که بخشی از مناطق مرکزی و شمال غربی منطقه در معرض خطر بالا قرار گرفته و مناطق غربی و شرقی حوضه در پهنه خطر متوسط تا پایین می‌باشند.

کلیدواژه‌ها

عنوان مقاله [English]

Landslide Hazard Zoning in the Yellow River Basin Using Fuzzy Logic

نویسندگان [English]

  • sayedeh masumeh mousavi 1
  • Mohammad Hossein Rezaei Moghaddam 2
  • Masumeh rajabi 3

1 p.h.d student Tabriz univercity

2 Professor, Department of Geomorphology, Faculty of Planning and Environmental Sciences, University of Tabriz

3 uivercity of tabriz

چکیده [English]

Landslides claim the lives of thousands of people around the world each year, causing enormous damage to people and governments. Landslide risk zoning divides landslides into specific and distinct areas of potential and actual degrees in terms of risk, this process is based on recognizing the qualitative characteristics of the area and quantitative modeling based on the data of the study area. This can be the basis for long-term planning at the regional and local levels.The purpose of this study is to investigate and zoning landslide risk in the Yellow River Basin located in the east of Khuzestan province using fuzzy logic method; For this purpose, first through field visits, geological maps and topography and by reviewing previous sources and reviewing the conditions of the region; Nine factors: elevation, slope, direction of slope, distance from fault, distance from river, distance from road, precipitation, lithology and land use were considered and selected as effective factors on landslide occurrence. Landslide hazard zoning maps were prepared using fuzzy gamma operator with values ​​of 0.7, 0.8, 0.9. Then, the obtained maps were classified into 5 classes: very high, high, medium, low and very low.The results of the qualitative sum showed that the 0.9 fuzzy gamma operator is more suitable than other fuzzy operators. The results of the classified maps showed that 21.56% of the area in the high-risk zone and 43.24% of the area The area is located in a low risk zone.

کلیدواژه‌ها [English]

  • Geomorphological hazards
  • fuzzy logic
  • quality aggregate index
  • Yellow River
  • Khuzestan
Abdollahzadeh, A., ownegh, M., Sadoddin, A., Mostafazadeh, R. (2016). Comparison of two methods for determining landslide risk areas in Ziarat watershed of Golestan province, the Journal of Crisis Management, Spring and Summer 2016, 5(9) 55-78(in Persian)
Chung, C.J. & Fabbri, A.G. (2008). Validation of spatial prediction models for landslide hazard mapping. Natural hazard, Vol.30, pp: 451-472.
Dai, FC. & Lee, CF. (2002). Landslide characteristics and slope instability modeling using GIS -Hong Kong, Geomorphology, Vol.42, n (3-4), 213–228.
Dymond, J. R., Ausseeil, A.G., shepherd, J.D., & Buettner, I. (2006). Validation of a Region Wide Model of Landslide susceptibility in the Manawatu. Wanganui Region of New Zealand, Geomorphology, Vol. 74: 70- 79.
Abedini, M.; Fathi, M H. (2014). Zoning of landslide risk sensitivity in Khalkhal Chay watershed using multi-criteria models, Quantitative Geomorphological Research, No. 4, 8: 85-71(in Persian).
Aksoy, B., and Ercanoglu, M. (2012). Landslide identification and classification by object-based image analysis and fuzzy logic: An example from the Azdavay region (Kastamonu, Turkey), Computers & Geosciences, 38(1): 87-97.
Amira Ahmadi, A.; Naami tabar. M.; Golkar Ostadi, B. (2017). Prioritization and zoning of factors affecting landslide occurrence using entropy model (Case study: Bajgiran region, Quchan), hydrogeomorphology, 3(11): 127- 104(in Persian).
Arab Ameri, A.; Halabian, A H. (2015). Landslide Hazard Zoning Using AHP Bivariate Statistical Model and Zarand Basin Geographical Information System, Natural Geographical Quarterly, 8(28): 86-65(in Persian).
Ashqali Farahani, A.; Teshneh lab, M.; Ghayoumian, J.; Fatemi Aghda, S.M. (2014). Investigation of landslide risk using fuzzy logic (case study of Rudbar region), Journal of Science, University of Tehran, 31(1): 64-43(in Persian).
Balali, F.; Wahabzadeh, Gh; Pourghasemi, H.; Forouzanfar, M. (2016). Landslide Tendency Zoning Using Fuzzy Logic Method (Case Study: Part of Nekarood catchment), Journal of Iranian Geological Engineering Association, 9, (3 & 4): 30-19(in Persian).
Champati-ray, P.K,. Dimri, S. Lakhera, R.C., and Sati, S. (2007). Fuzzy-based method for landslide hazard assessment in active seismic zone of Himalaya, Landslides, 4(2): 101- 111.
Dhianaufal, D., Kristyanto, T. H. W., Indra, T. L., and Syahputra, R. (2018). Fuzzy Logic Method for Landslide Susceptibility Mapping in Volcanic Sediment Area in Western Bogor, Proceedings of the 3rd International Symposium on Current Progress in Mathematics and Sciences 2017 (ISCPMS2017) AIP Conf.
Faraji, Hojjat; A., Adel. (2016). Fuzzy Management Science, Fifth Edition, Mehraban Book Publisher.
Gee, M.D. (1991). Classification of landslide hazard zonztion methodes and 3.a test of predictive capability, Landslide, Bell(ed), Balkema, Rotterdam (in Persian).
Geological Survey, (1966). Description of Haft Gol Square Geological Maps, Dehler, Asmari. (In Persian)
Hassani, Sir.; Urmia, A.; Maleki, Z. (2017). Landslide risk zoning of Kan-Solghan road by fuzzy logic method, Quarterly Journal of Environmental Geology, 11(38): 35-50. (In Persian)
Hosseinabadi, M.; Mousavi, S M.; Nazemi, M. (2019). Earthquake and landslide hazard zoning by fuzzy logic method in Bagheran mountain range (south of Birjand), Quarterly Journal of Geography and Development, 17(55): 174-153(in Persian).
Ishaqi, A.; Motamed Vaziri, B.; Faizunia, S. (2009). Zoning the risk of occurrence of mass movements using logistic regression method (Case study: Saffarud watershed), Geographical Quarterly of the Land, Year 6(24): 77-67(in Persian).
Lee S. (2004). Application of Likelihood Ratio and Logistic Regression Models to Landslide Susceptibility Mapping Using GIS. The Journal of Environmental Management, 34(66): 223-232.
Leonardia, G., Palamaraa, R., and Cirianni, F. (2016). Landslide Susceptibility Mapping Using a Fuzzy Approach, Procedia Engineering, 161: 380-387.
Madadi, A., Mehri, M., Ney Niva, S P. (2020., Investigation of effective factors in landslides in Ardal basin (Chaharmahal Bakhtiari province) using logistic regression method, New findings of applied geology, Fourteenth year, No. 27: 112-123(in Persian)
Marzbani, M., Shirzadi, H., and Fathi, M. (2016). Landslide hazard zoning using information value model in geographic information system (GIS) case study (Dareh Shahr watershed-Simakan). The First International Conference on Natural Hazards and Environmental Crises. Strategies and Challenges. (In Persian).
Malchevsky, Y. (1999), Geographic Information System and Multi-Criterion Decision Analysis, translated by Parhizgar, Akbar. Ghaffari Gilande, Ata, Second Edition, (2011), Tehran: Samat Publications,
Moghimi, I.; Alavi Panah, S K.; Jafari, K. (2008), Evaluation and zoning of effective factors in landslide occurrence in the northern slopes of Aladagh (Case study: Chenaran drainage basin in North Khorasan province), Geographical Research, No. 64: 75-53(in Persian).
Moradi, H.; Mohammadi, M.; Pourghasemi, H. R.; Mostafazadeh, R. (2010), Landslide risk analysis in Golestan province using Dempster-Schaefer theory, Earth knowledge research, 1(3): pp. 14-1(in Persian).
Moradi, H., Mohammadi, M., Pourghasemi, H., Mostafazadeh R. (2012) Landslide risk analysis in Golestan province using Dempster-Shafer theory, Journal of Earthquake Research, Fall 2010, 1(3): 1-14(in Persian)
Mosafaee, J., Onegh, M. and Shariat Jaffar, I. (.2009). Comparison of the efficiency of the experimental and statistical method of landslide ranger zoning (Case study of Alamoot Roud Watershed), Journal of Water and Soil Conservation Studies, 6(4): 43-61(in Persian).
Motavi, S., Hosseinzadeh, M., Ismaili, R, Darfashi, K. (2014), Evaluating the accuracy of multivariate regression methods, (MR logistic regression), (LR Analytic Hierarchy Process (AHP) and fuzzy logic (FL) in Landslide Hazard Zoning of Taleghan Watershed, Quantitative Geomorphological Research, Fourth Year, No. 1, pp. 1-20(in Persian)
Mokhtari D., Rezaei Moghadam M. H., Moezz, S. (2021). Zoning of detrital flow risk using FUZZY-SAW model Case study: Leylan Chay catchment, northwestern Iran, 8(27): 101-81 Serial Number 27, (in Persian)
Nojavan, M.R., Shahzaidi, S., Sadat, Davoodi, M., Amin al-Ra'i, A. (2019). landslide risk zoning using a combination of two models of hierarchical and quasi depletion process (Case study: Kameh watershed, Isfahan province, Quantitative Geomorphological Research, Seventh Year, No. 4:142-159(in Persian)
Piravan, H.; Shariat Jafari, M. (2013), Presenting a comprehensive method for determining the erodibility of lithological units with a view to Iranian geology, Journal of Watershed Engineering and Management, 5(3): 213-119(in Persian)
Pourghasemi, H. (2013). Landslide risk prediction using data mining methods in the north of Tehran, PhD thesis, Tarbiat Modares University, Faculty of Natural Resources, Department of Watershed Management. (in Persian)
Pourghasemi, H. R., Goli Jirandeh, A., Pradhan, B,. Xu C. and Gokceoglu, C. (2013). Landslide Susceptibility Mapping Using Support Vector Machine and GIS, Journal of Earth System Science, 122(2), pp: 349-369. (in Persian)
Pourghasemi, H.; Moradi, H.; Fatemi Aqda, S M.; Mahdavifar, M. R.; Mohammadi, M. (2011), Evaluation of Geomorphological and Geological Factors in Landslide Hazard Mapping Using Fuzzy Logic and Hierarchical Analysis Method (Case Study: Part of Haraz Watershed), Soil and Water Conservation Research (Agricultural Sciences and Natural Resources), 18(4):20-1(in Persian).
Pourghasemi. H., Moradi H., Mohammadi. M., Mostafa Zadeh. R., Goli Jirandeh, A. (2012), Landslide risk zoning using Bayesian theory, (Agricultural Science and Technology and Natural Resources, Water and Soil Science, 16(62), Winter 2012(in Persian)
Qanawati, E.; Karam, A.; Taghavi Moghadam, E. (2014). Application of Fuzzy Logic in Identification and Zoning of Landslide-Slip Risk Case Study of Taleghan Watershed, Engineering Geology and Environment, 24(94):16-9. (In Persian)
Qarahi, H.; Bohloli, B.; Mobile, A.; Shariat Jafari, M. (2011). Preparation of Sensitivity Map of Landslide Phenomenon Using Hierarchical Analysis and Bivariate Statistical Model in Alborz Dam Reservoir, Journal of Earth Sciences, 21(81): 100-93. (in Persian).
Rustaei, Sh., Mokhtari d., Hosseini, Z., Atmani Haghviran, M. (2015), Investigation of Landslide Potential in the Meymeh River Basin in Ilam Province by Network Analysis (ANP), Journal of Hydrogeomorphology, 1(4), Page 101, Fall 2015, (in Persian)
Rustaei, Sh.; Hejazi, A.; Rajabi, M; Jalali, N; Najafi Igdir, A. (2018). Application of fuzzy logic in landslide risk zoning in Nazlouchai watershed, Quantitative Geomorphological Research, 6(4): 119-103 Series 24, (in Persian)
Rezaei Moghaddam, M. H., Nikjoo, M. R., Valizadeh Kamran, K, Balvasi, I. A, Balvasi, M. (2017). Application of artificial neural network model in landslide risk zoning, geography and spring 2017 planning, No. 59(in Persian)
Sabuya, F., Alves, M. G., & Pinto, W. D. (2006). Assessment of failure susceptibility of soil slopes sing fuzzy logic, Engineering Geology, 86(4): 211-224.
Sharafi, S., Sadeghi Rad, M., Javadinia, Z. (2020). Paleogeomorphology reconstruction of Dela landslide and formation of Shimbar Dam Lake in Indika city, Khuzestan province, Quarterly Journal of Applied Geographical Sciences Research (in Persian)
Shariat Jafari, M. (1996), Landslide (Principles and principles of natural slope stability), first edition, Sazeh Publications (in Persian).
Taheri, S. M. (2002), Introduction to the theory of fuzzy sets, second edition, University Jihad Publications, Ferdowsi University of Mashhad.(in Persian)
Vandromme. R., Thiery, Y., Bernardie, S., Sedan.O. (2020). Landslides Induced by Climatic Events): A single tool to integrate shallow and deep landslides for susceptibility and hazard assessment, Geomorphology.
Wang, L. (2016). Fuzzy systems and fuzzy control, translation (Dariush Afyoni, Nima Saffarpour, Mohammad Tashnehlab), first edition, Khajeh Nasir al-Din Tusi University.
Yamani, M.; Hasanpour, S.; Mustafaei, A; Shadman Rudpashti, M. (2012), Landslide Hazard Zoning Map in Karun Bozorg Watershed Using AHP Model in GIS Environment, Geography and Environmental Planning, Volume 23, Number 48, Number 4, pp. 56- 39(in Persian).
Zhu, A. X., Wang, R., Qiao, J., Qin, C. Z., Chen, Y., Liu, J., Du, F., Lin, y., and Zhu, T. (2014). An expertknowledge-based approach to landslide susceptibility mapping using GIS and fuzzy logic, Geomorphology, 7: 128-138.