پهنه بندي حساسيت خطر وقوع زمين لغزش در حوضه آبخيز خلخال چاي با استفاده از مدل هاي چند معياره

Landslides susceptibility risk zonation with fuzzy AHP multi-criteria models logic models (Case Cause Study: Khalkhal Chai catchment

زمين لغزش يكي از انواع حركات توده اي مي باشد، كه تحت تاثير عوامل متنوع طبيعي و انساني، هيدرولوژيكي، اقليمي ايجادشده و به وسيله حضور مستمر عناصر متعددي از جمله بارش و رطوبت تشديد مي‌گردد. از اقدامات اساسي جهت دستيابي به راهكارهاي كنترل و مديريت حركت‌هاي توده‌اي، شناسايي عوامل موثر در وقوع اين پديده مي‌باشد. در تحقيق حاضر كه مستخرج از نتايج نهايي طرح پژوهشي است و در آن از تركيب مدل هاي منطق فازي و تحليل سلسله‌مراتبي (Fuzzy-AHP) به عنوان يكي از روش‌هاي قابل‌استفاده و كاربردي به طور موردي در حوضه آبخيز خلخال چاي در استان اردبيل مورد استفاده قرار گرفته است، اقدام به شناسايي عوامل موثر بر وقوع زمين لغزش و پهنه بندي مناطق مستعد خطر وقوع زمين لغزش نموديم. نتايج به دست آمده از تحقيق حاضر نشان مي دهد؛ عواملي نظير شيب، ليتولوژي، ارتفاع، بارش، فاصله از رودخانه، زمين‌شناسي، كاربري اراضي، گسل و جهت شيب به ترتيب اولويت به عنوان مهم‌ترين عوامل موثر در لغزش به منظور پهنه بندي شناسايي گرديده و مورد مطالعه قرار گرفتند. يافته هاي تحقيق نشانگر آن است كه حدود (21.82) درصد از زمين لغزش‌ها با مساحتي در حدود (46.30) كيلومترمربع در زمره مناطق با لغزه خيزي زياد و خيلي زياد و در مناطق شرق و شمال شرق حوضه واقع‌شده‌اند. مناطق با خطر متوسط با مساحت (41.30) كيلومترمربع بيشتر در منطقه شرق و جنوب غرب حوضه آبريز واقع‌شده است. مناطق با حساسيت كم و خيلي كم نيز (124.54) كيلومترمربع در واقع (58.7) درصد از سطح حوضه را به خود اختصاص داده اند. لذا در برنامه ريزي هاي محيطي و هرگونه دخالت در شرايط محيط طبيعي و ساخت‌وساز در مناطق شمال شرق و شرق حوضه بهتر است با مطالعات دقيق و علمي صورت گيرد تا منجر به تشديد ناپايداري شيب ها و مخاطرات محيطي نشود.

Introduction Landslide hazard zonation with the benefit of multi-criteria techniques (MCDM ) declare critical areas susceptibility to Landslide occurring their results can be used and to the environmental planning. In recent decades number of different types of hazards is greatly increased due to human activities and its encroachment on the natural environment. Compared with other natural hazards such as volcanic eruptions and ?oods, landslides cause considerable damage to human beings and massive economic losses (Guzzetti, 2005). According to preliminary estimates, about 500 billion riyals annual are caused economic damage in Iran by landslide occurrence (Hosseinzadeh et al., 1388:27). Today Because of the rapid development of computing power and Geographical Information System (GIS) technology, a vast number of quantitative or statistical Methods have been applied to assess landslide susceptibility (Wang, 2013:81). In this study Khalkhal Chai catchment (Ardabil) has Zonation for landslide susceptibility By using Fuzzy AHP (MCDM) Methods And landslide predisposing factors such as (distance from river, Lithology, land slope, distance from fault, drainage density, aspect and land use, distance from roads and elevation). - Methodology -Fuzzy AHP model The fuzzy logic model and analysis a hierarchy as one of the method of use of the application in case little Khalkhal watershed. Basin in Ardebil province is used. The results of the study indicate that factors such as slope, lithology, elevation, rainfall, distance from the river, geology, land use, slope failure and landslides prioritized as the most important factors in order to study the zoning were. Keywords: zoning, land slide, Fuzzy AHP, GIS, Khalkhal watershed basin Fuzzy AHP model is Generalization of the classical set theory in mathematical science and is a new approach to يقف8خ0-=ح-0987658-the expression of uncertainty and confusion routine. Fuzzy sets are defined by membership functions. For each fuzzy set is a number between zero and one Where zero indicates the lack full membership and one indicates full membership (Hosseini et al, 1390). Fuzzy model is done using several functions. The most important operators of the fuzzy logic can be pointed to Fuzzy Product, Fuzzy Sum gamma operator and etc. Gamma operator is defined based on Fuzzy Product and Fuzzy Sum (Equation 1). Equation (1) ?_(combination=((Fuzzy Algebraic Sum)(Fuzzy Algebraic Product))^(1-?) ) Where ?_combination layers obtained from the fuzzy gamma and the ? parameter is defined in the zero and one. Considering studies conducted and their results and compare different values of gamma, in this study, the Gamma 8/0 was used and landslide susceptibility map was produced. 3– Discussion According to the method mentioned above layers intended after preparation were used for zonation and landslide susceptibility zonation map was. Final Maps has obtained with using the methods and classified In the 5 risk class: very low susceptibility, low susceptibility, moderate susceptibility, high susceptibility and high susceptibility). For the compare models, were used from Landslide Index (Equation 2) and using it were evaluated entire risk Category. Equation (2) Li=((Si/Ai))/((?n(Si/Ai) ) )*100 In above equation Si is area landslide occurred In each zone risk, Ai area of each risk zone, N number of risk Category and Li index landslide occurrence in each risk zone is to Percentage. 4– Conclusion Research findings indicate that approximately (21.82%) of the landslide area around (46.30) square kilometer zone with high and very high seismicity Landslide in East and North-East regions of the basin in terms of slope, type Formation of Privacy fault distance, distance river Buffer are located in the high sensitive area to landslide. An area with moderate risk area (41.30) square kilometers in area, is located in East and South West Catchment. Areas with low and very low sensitivity (124.54) square kilometer in 58.7 percent of the basin into account.