ارزیابی حساسیت زمین‌لغزش با استفاده از مدل‌های ویکور و میانگین وزنی مرتب‌شده مطالعه موردی شهرستان سوادکوه

ABSTRACT
Landslides can occur due to human activities and environmental factors that have destructive effects. Reaching zoning of the risk of this phenomenon can help to make decisions to reduce losses and damages caused by this phenomenon. In this study, to prepare a landslide risk map, various natural factors including height, slope, slope direction, precipitation, soil type, distance from the waterway and distance from the fault have been used. Also, the historical information on the earthquake occurrence has been used to estimate the effect of each criterion and sub-criteria. For this purpose, by using the frequency ratio (FR) method, the impact of sub-criteria and by using Shannon's entropy method, the weight of each criterion has been calculated. Also, after calculating the weights of criteria and sub-criteria, VIKOR and weighted average (OWA) methods have been used to prepare a risk map. Based on the obtained results, the criterion of soil type with a weight value of 0.33 has the most effective weight. To compare different methods, the FR criterion has been used, which based on the results obtained, the OWA method has better results for α values ​​equal to 10 and 2.
Extended Abstract
Introduction
Landslides or range movements are natural phenomena that can have irreparable effects. The intervention of human activities such as road construction, tunnel digging, tree cutting, and mining activities can aggravate this phenomenon. Of course, environmental factors such as heavy rains, earthquakes, and lowering the underground water level can cause this phenomenon. Landslides, by destroying the people's public property and environment, make the continuation of human life a severe problem. It is very important to identify the prone areas and prepare hazard maps, followed by planning to manage the conditions after the landslide event, and it helps the planners to make the necessary preparations before any disaster occurs. To consider In this study, the VIKOR method is used as one of the MCDM methods. Based on the review of previous studies, this method has not been used in other studies in accordance with the subject of this study. Also, the criteria used in this study include elevation, slope, slope direction, precipitation, soil type, distance from the fault, distance from the river, and distance from waterways, which are weighted by Shannon's entropy method and Frequency ratio.
 
Methodology
Shannon entropy- Frequency Ratio(FR): This method is widely used in multi-criteria decision-making, and considering that it can determine the importance of the criteria without needing an expert's opinion and calculate the weight for each criterion, it is of interest. Also, this method can be useful when there is a lot of inconsistency between experts' opinions. First, the probability density (E_ij) of landslide occurrence for each class of the desired factor is calculated. The FR is equivalent to the ratio of the relative percentage of the number of relevant events in a certain class to the relative percentage of the area of the class in the studied area. After that, the entropy value is calculated. Also, in the next step, the information value should be calculated. The information value shows the importance of the relevant factor in creating the event, and the larger its value, the higher the importance of that factor. Finally, to reach the weight of each factor, the information value must be multiplied by the value of the average FR.
VIKOR: This method ranks the options by calculating how close each option is to the ideal solution, which receives the decision matrix and the criteria's weight vector as input. In the first step, the data should be normalized. After normalization, the values of the decision matrix must be multiplied by the weight of each criterion to reach the value of the weighted normalized matrix. In the next step, partial agreement with the ideal answer and partial disagreement with the ideal solution (should be calculated. This method uses a linear relationship in terms of and to evaluate and ranking options.
OWA: The OWA method is one of the information integration methods based on priority weighting. The information integration is given a weight based on the priority of the information source among other information sources. Two sets of weights can be included in OWA. The set of weights of the criteria that were calculated in this study using the Shannon entropy-frequency ratio method. The weight of the criteria specifically determines the importance of each information source. The set of order weights is specified for each priority. The order weight is determined according to the rank and position of the information source compared to other information sources.
 
Results and Discussion
The layers of information used in this study include slope layer, aspect, elevation, distance from the fault, distance from the rivers, soil type, and precipitation. This study was conducted in Savadkuh county of Mazandaran province. Based on the values obtained, the criteria of soil type and elevation with weight weights of 0.33 and 0.23, respectively, have the greatest effect in causing landslides. Also, the criterion of distance from the rivers with a weight of 0.01 has had the least effect.
Among the different soil types, the Malisol (mol) type has the greatest effect in causing landslides with an impact of 0.68% compared to other types, which is due to the fact that this soil is always moist and soft, It has a high potential in creating landslides. Also, for the sub-criteria related to elevation, the highest number of landslides occurred at elevations of 100 to 1200 meters above sea level, which are actually hillsides. This phenomenon has been less at higher altitudes, which can be attributed to the type of soil at higher altitudes, mostly rocks and stones. According to the obtained map, 72.08% of the points were placed in very high and high-risk areas, and its rate was 10.8% for low and very low-risk areas. Also, 19.82% of the points are located in medium-risk areas, which is a significant amount, and it seems that other factors can be considered in determining the event's potential.
 
Conclusion
After calculating the weight of the criteria and sub-criteria, VIKOR and OWA methods were used to combine different layers. As a result, eight landslide risk zoning maps were obtained. The maps obtained from the OWA method for α values equal to 10 and 2 have the best results based on the DR criteria. Based on the obtained maps, the northern regions of the region have a higher potential for this phenomenon to occur, and the soil type of the northern regions and lower altitudes (domains) have increased the potential for this phenomenon to occur. Also, agricultural activities increase the probability of occurrence, which is higher in the northern regions. Based on the obtained results, it can be said that the OWA method, which produces a wide range of outputs, can be a suitable method for reducing the issue of uncertainty because of different values of α and comparing the obtained maps. In reality, you can choose the best result. Therefore, one of the advantages of this method over the VIKOR method is the reduction of uncertainty.
Also, based on the results obtained from this study, the high number of points in each class cannot be used as a measure of accuracy alone because, for example, in the OWA method with an α value equal to zero, more than 95% of the points are in the high-risk class. At the same time, more than 87% of the region's area was placed in this class, which caused more points to be placed. The DR method was a criterion for comparing different ways by considering the relative number of points and the relative area of the corresponding class. The maps obtained from this study can be used to improve road safety and make better decisions in the design of roads, railways, and power transmission lines.
 
Funding
There is no funding support.
 
Authors’ Contribution
All of the authors approved the content of the manuscript and agreed on all aspects of the work.
 
Conflict of Interest
Authors declared no conflict of interest.
 
Acknowledgments
We are grateful to all the scientific consultants of this paper.