عنوان مقاله [English]
Landslide is one of the natural phenomena that often rapid fall of the volume of sediments occur along domains. One of the undeniable effects of this phenomenon, intensification of soil erosion and transmission sediment to behind the dams of drainage basins. Since that the predicted time of occurrence of landslide is out of human knowledge, therefore, identification of sensitive areas to landslides and rating it can help prevent some of the risk of landslide occurrence. One of the main measures in this regard are mapping landslide hazard event. This process that based on understanding the natural features and quantitative modeling based on data from the study area occurs, can be a basis for further actions and planning for future development in the regional scale, regional and local level to be considered. Many researchers have studied the landslide zoning, Including: Gee, 1992, Van Westen et al, 1997, Guzzetti, et al, 2000, Saro Lee et al, 2001, Murat et al, 2002, Chowd Hury et al, 2003, pozhm, 1996, hagh shenas, 1996, bodaghi, 1997, farahani, 2001, sefidgari, 2002, shirani, 2004, izadi, 2006.
Marbor river has a high potential for landslides and large landslides that have occurred. For mapping landslides in this area, aerial photo 1:40000, 1993 was interpreted and slip areas were identified and their positions in Google earth were determined. And finally position of 113 landslides in this area in GIS used. Several factors are involved in the occurrence of landslides, in this study, 9 factors lithology, land use, vegetation, rainfall, slope, aspect, distance from roads, distance from faults and distance from rivers was investigated and a total of 54 parameters were obtained for landslide zoning.
2.1 Landslide Index
Landslide index is percentage slip level in each zone to zone an area divided by the total surface area of proportion to the total slip. (Van Westen 1998, shirani, 2005).
That: Li is index of risk landslide occurrence in each area to percent, Si is area of landslide in each danger zone, Ai is area of each danger zone, n is number of zones.
2.2Accurately model (P)
The accuracy of the method is sliding surface area ratio in the medium to high risk zones to total area of the zone. (farahani, 2001, shirani et al, 2010).
Equation 2: P = KS/S
That, P is model accuracy in medium to high risk zones. KS is area of landsliding in the medium to high risk zones. S is area of danger zones.
2.3 Accuracy of model (Qs)
to determine the accuracy of the model, first Density ratio (Dr) is calculated and then accuracy of model by equation 4 is calculated. (Gee, 1992, shirani, 2005).
Equation 3: Dr= Percentage of landslides/percentage of area
That: Qs is total quality. Dr is Density ratio. N is number of risk categories. S is area ratio to the total area of each category of risk.
Results showed that, AHP expertise in low sensitivity zones with the highest percentage of land area is allocated to the region and the area has the lowest percentage of area at risk is very high and the highest percentage of moderate-risk zone is located on the sliding surface. Qs of model was 0/35 and P model was 1/53, but increasing the compression ratio and landslide susceptibility index model in this region is moderately messy and in AHP consolidated method range with low sensitivity to most of the area is allocated and range with very low risk, the region has the lowest surface area and surface slip, but most of the slip surface located in high-risk area.
This study was conducted with AHP expertise and AHP consolidated to landslide hazard zonation. For comparison logical models all factors and parameters were identical. Finally, 9 factors in 54 parameters as risk factors for the zoning district were selected and entered to the regression equation. Factors and parameters set using experts and field observations for AHP expertise were prioritized and entered to the process. Also, from the regression coefficients obtained and comments expertise integrated was used for AHP consolidated. After processes zoning models produced were put to the test. In AHP consolidated method factors such as distance from roads, lithology, vegetation, distance from river, land use, slope, aspect, rainfall and distance from fault had the greatest impact respectively. According to the results, model compilation for all zones of the AHP consolidated method, compliance with conditions of more landslides. According to the chart of landslides, AHP consolidated method in introducing the zones with very high sensitivity most important is the capability. In AHP consolidated method, values of P and Qs 1/73 and 0/45 respectively, in AHP expertise method 1/57 and 0/35. The numerical values of these parameters is more, models of higher accuracy is obtained. In fact P showed map accuracy of medium and high to top risk categories and the higher the value of these parameters, the model is closer to reality and any amount is more Qs map accuracy is higher for all categories and finally, the validity of the model used is higher. Therefore in this study, AHP consolidated method to the accuracy of indicators (Q) and total Quality (Qs) have better performance than the AHP expertise method. Weighting consolidated method, have more power than the expertise method for prioritization of appropriate parameters.