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2018, 12(4): 635-658 |
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Rajabi A M, Khosravi H. The Zoning of Earthquake-Induced Earthquake Hazards using the AHP Model. Journal of Engineering Geology 2018; 12 (4) :635-658
URL: http://jeg.khu.ac.ir/article-1-2551-en.html
URL: http://jeg.khu.ac.ir/article-1-2551-en.html
1- Engineering Geology Department, School of Geology, College of Science, University of Tehran, Iran , amrajabi@ymail.com; amrajabi@ut.ac.ir
2- Department of Civil Engineering, University of Qom, Qom, Iran
2- Department of Civil Engineering, University of Qom, Qom, Iran
Abstract: (4358 Views)
Introduction
In general, landslides, in particular, earthquake-induced landslides, are among the phenomena that have caused great damages in recent years in Iran and the world. Although many studies have been done on the identification and description of landslides in general, the study of landslides caused by the earthquake, especially in Iran, is at the beginning stages. In a few studies, some landslides and some of their characteristics have been introduced. A magnitude 7.7 earthquake occurred in the Guilan Province was occurred on May 31, 1990. This earthquake is one of the most important earthquakes in Iran history due to its magnitude and occurrence of landslides. In various studies, the most important landslides have been listed. The development of quantitative and qualitative studies on earthquakes that have caused many landslides (such as the Manjil, Avaj, Firoozabad, Kojur, Sarein and Ahar and Varzaghan earthquakes) increase our understanding of natural disasters and, consequently, the management of the dangers resulting from them. The purpose of this research is to identify the factors affecting the occurrence of landslides caused by earthquakes, to determine the impact of each on the occurrence of this phenomenon, and also to prepare a map of earthquake hazard zonation hazard by utilizing the methods used in this research. In this study, hierarchical analysis method has been used to prioritize the factors affecting the occurrence of landslide and also the zoning of earthquake landslide hazard in the study area.
Research Methodology
The study area is located between 49˚ 30ꞌ and 49 ꞌ45˚ and latitudes 36º 00 ꞌ 45" and 36º 30ꞌ 52" with a surface area of 309.30 km2. In this research, in order to zoning the earthquake-induced landslides hazard, in addition to providing a map of landslides, seven factors influencing the occurrence of this phenomenon were identified and examined. These factors included elevation, slope, arias intensity, friction angle, adhesion, curvature of the slope and aspect. In this research, Analytic Hierarchy Process (AHP) method, one of the multi-criteria decision making models, was used with two approaches to using expert knowledge and data and expert knowledge together to prioritize the factors influencing the occurrence of landslide. Finally, two landslide hazard zonation maps were prepared. In a hierarchical analysis method related to the expert judgment, it was used to determine the priority of different criteria and sub-criteria and convert them into small amounts of oral judgments (expert opinion) based on the pair comparison, in which the decision maker preferred the factor in relation to other factors using the relevant tables, these judgments are converted into small amounts. In the method of using data and expert judgment simultaneously, first, in order to determine the priority of criteria from oral judgments (collection of expert opinions), we used to determine the importance or weight (Wi) of each sub-criterion (R) is also used to link the landslide area to each class and landslide area in the region.
Results
The results obtained from the paired comparison of the effective factors in the occurrence of landslide show that the relative preference of the factors include the factor of arias intensity, friction angle, slope, adhesion, aspect, height and curvature of the amplitude. The greatest influence on the sub-criteria for the sub-criteria is 10-11.54, which is related to the arias factor and also the lowest effect for the sub-standard of the domain curvature factor. Also, according to the zoning maps, in the first model, 73% and in the second model, 57% of the surface area are very high and very high risk areas, which indicates the high sensitivity of the study area to the earthquake-induced earthquake phenomenon.
According to the results obtained from the verification and evaluation of the models and comparison of the mapped data with the hierarchical analysis method (using expert knowledge and data) and a method that uses only expert knowledge, the map is derived from a method where bundles of knowledge and data are used simultaneously, in order to weigh the parameters, it is more in line with the map of the landing list of the region.
Conclusion
According to the results obtained from the review and evaluation of the two models in a method in which knowledge and data were used together, the QS value was 0.40 and the accuracy of the method (P) was 0.016. However, in a method in which only the expert judgment used to weigh the criteria and sub-criteria, the sum of the quality and accuracy of the method were calculated to be 0.37 and 0.006, respectively. Hierarchical analysis method, in which the benchmarks and sub-criteria of benchmark knowledge and data are used together, have a better performance than the other model, and the results are closer to reality. In addition, it also works better in distinguishing between high and high risk areas../files/site1/files/124/5rajabi%DA%86%DA%A9%DB%8C%D8%AF%D9%87.pdf
In general, landslides, in particular, earthquake-induced landslides, are among the phenomena that have caused great damages in recent years in Iran and the world. Although many studies have been done on the identification and description of landslides in general, the study of landslides caused by the earthquake, especially in Iran, is at the beginning stages. In a few studies, some landslides and some of their characteristics have been introduced. A magnitude 7.7 earthquake occurred in the Guilan Province was occurred on May 31, 1990. This earthquake is one of the most important earthquakes in Iran history due to its magnitude and occurrence of landslides. In various studies, the most important landslides have been listed. The development of quantitative and qualitative studies on earthquakes that have caused many landslides (such as the Manjil, Avaj, Firoozabad, Kojur, Sarein and Ahar and Varzaghan earthquakes) increase our understanding of natural disasters and, consequently, the management of the dangers resulting from them. The purpose of this research is to identify the factors affecting the occurrence of landslides caused by earthquakes, to determine the impact of each on the occurrence of this phenomenon, and also to prepare a map of earthquake hazard zonation hazard by utilizing the methods used in this research. In this study, hierarchical analysis method has been used to prioritize the factors affecting the occurrence of landslide and also the zoning of earthquake landslide hazard in the study area.
Research Methodology
The study area is located between 49˚ 30ꞌ and 49 ꞌ45˚ and latitudes 36º 00 ꞌ 45" and 36º 30ꞌ 52" with a surface area of 309.30 km2. In this research, in order to zoning the earthquake-induced landslides hazard, in addition to providing a map of landslides, seven factors influencing the occurrence of this phenomenon were identified and examined. These factors included elevation, slope, arias intensity, friction angle, adhesion, curvature of the slope and aspect. In this research, Analytic Hierarchy Process (AHP) method, one of the multi-criteria decision making models, was used with two approaches to using expert knowledge and data and expert knowledge together to prioritize the factors influencing the occurrence of landslide. Finally, two landslide hazard zonation maps were prepared. In a hierarchical analysis method related to the expert judgment, it was used to determine the priority of different criteria and sub-criteria and convert them into small amounts of oral judgments (expert opinion) based on the pair comparison, in which the decision maker preferred the factor in relation to other factors using the relevant tables, these judgments are converted into small amounts. In the method of using data and expert judgment simultaneously, first, in order to determine the priority of criteria from oral judgments (collection of expert opinions), we used to determine the importance or weight (Wi) of each sub-criterion (R) is also used to link the landslide area to each class and landslide area in the region.
Results
The results obtained from the paired comparison of the effective factors in the occurrence of landslide show that the relative preference of the factors include the factor of arias intensity, friction angle, slope, adhesion, aspect, height and curvature of the amplitude. The greatest influence on the sub-criteria for the sub-criteria is 10-11.54, which is related to the arias factor and also the lowest effect for the sub-standard of the domain curvature factor. Also, according to the zoning maps, in the first model, 73% and in the second model, 57% of the surface area are very high and very high risk areas, which indicates the high sensitivity of the study area to the earthquake-induced earthquake phenomenon.
According to the results obtained from the verification and evaluation of the models and comparison of the mapped data with the hierarchical analysis method (using expert knowledge and data) and a method that uses only expert knowledge, the map is derived from a method where bundles of knowledge and data are used simultaneously, in order to weigh the parameters, it is more in line with the map of the landing list of the region.
Conclusion
According to the results obtained from the review and evaluation of the two models in a method in which knowledge and data were used together, the QS value was 0.40 and the accuracy of the method (P) was 0.016. However, in a method in which only the expert judgment used to weigh the criteria and sub-criteria, the sum of the quality and accuracy of the method were calculated to be 0.37 and 0.006, respectively. Hierarchical analysis method, in which the benchmarks and sub-criteria of benchmark knowledge and data are used together, have a better performance than the other model, and the results are closer to reality. In addition, it also works better in distinguishing between high and high risk areas../files/site1/files/124/5rajabi%DA%86%DA%A9%DB%8C%D8%AF%D9%87.pdf
Subject:
En. Geology
Received: 2016/08/10 | Accepted: 2016/10/29 | Published: 2019/02/10
Received: 2016/08/10 | Accepted: 2016/10/29 | Published: 2019/02/10
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