Identification of Areas Susceptible to Landslides in the Sarpol Zahab Basin
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Abstract:
Introduction

Materials movement on slope and especially landslides are among the most damaging threats that have been accelerating with human manipulation in natural systems in recent decades (Imami and Ghayumian, 2003). These movements annually cause a lot of financial and psychological damage around the world in different parts of the country. The rapid population growth, the expansion of cities in mountainous areas, the difficulty of predicting the occurrence of landslide events and the multiple factors affecting this phenomenon reveal the necessity of zoning the risk of landslide. Since prediction of the precise time of mass movements is very difficult, identification of these areas is very important (Mosafaei et al., 2009). Using the zoning of the risk of a landslide event, it is possible to identify vulnerable areas with potential risk, and by providing appropriate management approaches and techniques, to some extent prevent the occurrence of landslides or damage caused by them reduced. Accordingly, the purpose of this study is to identify areas susceptible to landslide in the Sarpolzahab Basin. The Sarpolzahab Basin is one of the mountainous regions of the western part of the country which is prone to various types of slopes due to special geomorphological conditions. In this research, for the potential estimation of areas susceptible to landslide, two models of WLC and OWA for zoning and an analysis of the network (AHP) model for weighting into layers have been used.

Methodology

The research methodology is based on software, library and analytical methods. In this research, eight layers of information were used to identify landslide susceptibility. Information layers include: 1 elevation, 2 slopes, 3 slopes, 4 rivers, 5 faults, 6 lithology, 7 communication paths and 8 land use areas. The general trend of the present research is that in order to identify the susceptible landslides, information layers were first provided (the choice of information layers was based on the purpose of the research and according to the experts' opinion), and then these layers were based on the opinion of the experts (5 geomorphologist) and using the network analysis model (AHP). After weighing the information layers, the weight is applied to each of the layers, and then, in order to combine and combine the information layers, three methods of fuzzy logic, WLC and OWA have been used.

Results

In this research, in order to achieve the desired goals, information layers are first provided. After providing information layers to combine information layers, layers are standardized using fuzzy area. Layer standardization is based on expert opinion and research objectives. For layers of elevation and gradient, gradient and high-lying areas of value near 1 and low-gradient and low-lying areas are considered to be close to zero. For layers of slope directions, the northern directions are worth close to 1 and the southern directions are close to zero. Also, areas near the lines of the fault, the river and the communication path are worth close to 1 and the distant areas are close to zero. For the land use, the uncovered areas are close to 1, and areas with dense vegetation are close to zero. For the lithology layer, areas with low resistance to lithology such as marl, lime and alluvium have a value of close to 1, and areas with more resilient lithology (basalt areas) are close to zero.

 Discussion and conclusion

The results of this study indicate that the studied basin has high potential for slippery slopes movement. In fact, the existence of hurdles and the availability of other parameters have led to a relatively large and large part of the eastern basin. Comparison of potentiometric methods suggests that in all three methods, the eastern regions have the highest and western regions with the least potential for landslide occurrence. In the fuzzy logic method, the potential class has the highest potential of 195 km2, and the average potential class with the 121 km2 has the smallest extent, which mainly includes the western regions and the outlet of the basin. In the OWA method, the relatively large potential floor area has a maximum area of 210 square kilometers, which mainly includes the central and eastern heights of the basin. In this method, the high potentiality class with the area of 116 km has the lowest status, and mostly you are the northern and central areas of the basin. In the WLC method, the relatively high potential class with 180 and a high potential floor area of 120 km2 has the highest and the smallest extent.

Article Type:
Research/Original Article
Language:
Persian
Published:
Hydrogeomorphology, Volume:5 Issue:20, 2019
Pages:
121 - 140
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