نوع مقاله : مقاله پژوهشی
دانش آموخته دکتری ژئومورفولوژی، دانشکده برنامهریزی و علوم محیطی، دانشگاه تبریز.
عنوان مقاله [English]
Study of Landslides using a Fuzzy Model in Abgalal Watershed in Khuzestan Province
As one of the global dilemmas that inflicts heavy human, financial and economic losses on an annual basis, study of mass movement has special importance, particularly with the increase in population and settlements over steep slopes prone to mass movement. International statistics related to human and financial losses caused by this phenomenon are steadily increasing. Frequent landslide events, their daily expansion in many parts of Iran in recent years and their destructive effects have attracted greater interest in responsible authorities, especially landslide experts, than ever before. Identifying and zoning areas susceptible to landslides is necessary for reducing losses. Since preparation of landslide susceptibility maps substantially improves land use planning, it can serve as an efficient method for decreasing human and financial losses resulting from landslides. Correct and systematic landslide hazard zonation and factors influencing it can be useful and effective in making decisions for containment, control and reduction of losses caused by this phenomenon
The Abgalal Watershed is located in Khuzestan Province, southwestern Iran. It forms one of the sub-watersheds of the Zard River. The physical tools used in the study included the 1:100,000 geological map, the 1:50,000 topographic map, the 30 m digital elevation model and the precipitation data obtained from the Meteorological Organization. GIS was used to measure the shapes and geomorphological parameters. Fuzzy logic evaluates the probability a pixel would be assigned to fuzzy sets considering the fuzzy membership function. Fuzzy sets do not have clear boundaries and membership or non-membership in a specific fuzzy set is a gradual process. There are two common methods for defining fuzzy sets: in the form of a function or in numbers. In the former, the degree of membership is presented as a function and in the latter specific degrees of membership are assigned to discreet values.
Results and Discussion
Following preparation of the distribution map of landslide prone areas, the distribution of these areas was studied in the form of nine factors influencing landslide occurrence. Each information layer (elevation classes, slope, orientation of slope, distance from fault, distance from river, precipitation, land use and lithology) were classified into five categories each receiving a score of 1 to 5 based on degree of susceptibility to landslides. The category with highest degree of susceptibility to landslide received a score of 5. The factor maps were combined with the landslide distribution map to determine the relationship between landslides and factors influencing its occurrence and also to prepare the landslide hazard zoning map.
This research studied the landslide-prone areas in the Abgalal Watershed using a fuzzy logic model. Using field studies, geological and topographic maps, reviewing the previous research conducted on this subject, and also investigating the existing conditions in the study region, eight factors (elevation classes, slope, direction of slope, lithology, distance from fault, distance from river, land use and precipitation) were studied as the factors influencing landslide occurrence. Following the fuzzification stage, landslide zoning maps were prepared using fuzzy gamma operators (for gamma values equal to 0.7, 0.8 and 0.9). The results of the qualitative addition method revealed that the fuzzy gamma operator ( at gamma=0.9) was more suitable than the others. Finally, the obtained map was classified into the very high, high, moderate, low and very low susceptibility categories, with 1.6% and 94% of the study region in the high and very low susceptibility zones, respectively. These results demonstrated that the study region had high potential for landslide occurrence due to the presence of a river network, precipitation, rangelands, urban areas, and weak lithology. Moreover, large areas lying south of the study region also have high potential for sliding movement.