Zonation of Landslide Risk using Fuzzy and AHP Model (Case Study: Komeh Basin, Isfahan Province

aaIntroduction Iran has natural potential for creating a wide range of landslides; Because of different climatic zones, Topography, tectonic activity and seismicity, geology and natural condition. The basin of Komeh is located in southern Isfahan province. This research studies the factors affecting the occurrence of landslides and makes draw a hazard zonation map to identify sensitive areas with potential hazards.in order to, an appropriate solution could be used to the crisis and the risk of landslides to reduce damage and improve the environmental situation. Now a day Landslide and mass movements have been studied in scientific and international contexts Introduction Iran has natural potential for creating a wide range of landslides; Because of different climatic zones, Topography, tectonic activity and seismicity, geology and natural condition. The basin of Komeh is located in southern Isfahan province. This research studies the factors affecting the occurrence of landslides and makes draw a hazard zonation map to identify sensitive areas with potential hazards.in order to, an appropriate solution could be used to the crisis and the risk of landslides to reduce damage and improve the environmental situation. Now a day Landslide and mass movements have been studied in scientific and international contexts Methodology In this research, the zoning and preparation of hazard maps are based on the combination of landslides in the region with effective criteria. The recorded landslide points of the Komeh basin have been identified by field studies, satellite images with high spatial resolution, geological and topographic maps and converted to Landslide zones. Then, effective independent variables (such as slope, direction of amplitude, elevation, lithology or geology, land use, fault, waterway, rainfall and communication path network) were identified in the occurrence of landslide phenomenon and Using relative frequency method, the relative weight of each floor was calculated from each variable. Finally, by comparing and overlapping the mapping of landslides and hazard zonation maps in GIS, to evaluate and compare the fuzzy landslide risk zoning operators using two methods, of quality Sum (Qs) and method ( P). so appropriate operator with survey area and different classes of risk of landslide occurrence in the Komeh basin. Results Fuzzy maps were created after recognizing the factors affecting landslide and zoning as effective factors in the area. Using fuzzy functions and fuzzy maps were created. Considering the relative weights calculated the geological variable as the most effective and then gradient variable occurrence of slopes of the basin of Komeh was based on specialist's idea. After weighing each variable Based on the relative weights obtained from the hierarchical analysis, Landslide hazard zonation map of Komeh basin was provided by five fuzzy logic overlapping operators, Sum, Product, Gamma 0.7, Gamma 0.8 and Gamma 0.9. Results Fuzzy maps were created after recognizing the factors affecting landslide and zoning as effective factors in the area. Using fuzzy functions and fuzzy maps were created. Considering the relative weights calculated the geological variable as the most effective and then gradient variable occurrence of slopes of the basin of Komeh was based on specialist's idea. After weighing each variable Based on the relative weights obtained from the hierarchical analysis, Landslide hazard zonation map of Komeh basin was provided by five fuzzy logic overlapping operators, Sum, Product, Gamma 0.7, Gamma 0.8 and Gamma 0.9. - Discussion & Conclusions Generally, in this region a quantitative fuzzy method is Able to find and recognize landslides zone. Landslide is one of the most dangerous natural disasters, and some important factor such as slope, elevation range, lithology, geology... in landslide creation. Factors were identified in the region and using weight ratio model. Fuzzy weighting and weight of the criteria were determined using hierarchical analysis method. The results show that the elevation 1775-2000 with a rainfall of 500 mm, slop more 30 to 40 degrees, slopes in the northern direction due to rainfall and humidity, marn zones, intervals of 0-100 m from the rivers, distance between 0-100 m from road, 0-100 m from fault, garden and agricultural lands, they have the Most landslides allocate themselves. The value of the index (Qs) shows that the fuzzy gamma0.8 operator is with 7.09. The most appropriate method of overlapping fuzzy logic was to obtain a gamma value of 0.8 for the landslide hazard map of basin komeh. Discussion & Conclusions Generally, in this region a quantitative fuzzy method is Able to find and recognize landslides zone. Landslide is one of the most dangerous natural disasters, and some important factor such as slope, elevation range, lithology, geology... in landslide creation. Factors were identified in the region and using weight ratio model. Fuzzy weighting and weight of the criteria were determined using hierarchical analysis method. The results show that the elevation 1775-2000 with a rainfall of 500 mm, slop more 30 to 40 degrees, slopes in the northern direction due to rainfall and humidity, marn zones, intervals of 0-100 m from the rivers, distance between 0-100 m from road, 0-100 m from fault, garden and agricultural lands, they have the Most landslides allocate themselves. The value of the index (Qs) shows that the fuzzy gamma0.8 operator is with 7.09. The most appropriate method of overlapping fuzzy logic was to obtain a gamma value of 0.8 for the landslide hazard map of basin komeh. Key Words: Zoning; Landslide; komeh basin; Fuzzy Logic.