Earthquake risk–sensitive model for urban land use planning

Natural Hazards - Analysis of the run-out of landslides is essential and vital for disaster mitigation. However, accurate run-out analysis is difficult because of the uncertainty of earthquake...     

Earthquake risk assessment in urban fabrics based on physical,socioeconomic and response capacity parameters (a case study: Tehran city)

Determination of the priorities for improvement of vulnerable urban fabrics based on a comprehensive assessment is among the main desires of local governments in earthquake-prone countries like Iran. However, in most countries, the comprehensive and absolute estimation of seismic risk is not possible due to shortages of the required data. In this paper, a new method is proposed for estimation of the risk through combination of hazard, vulnerability and response capacity indicators. Also, new evaluation methods based on relative scheme are presented for simple quantification of indicators in urban areas suffering from limited or insufficient database. For this purpose, important vulnerability parameters at urban areas are classified into physical, human life and socioeconomic groups. New hazard factors are also defined to evaluate the risk through combination of each vulnerability indicator and its directly related hazard factor. In addition, the capacity of response activities is accounted for in the model using planning, resource, accessibility and evacuation capacity indicators. The post-earthquake reduction of response capacity is also measured by means of reduction factors. Then, total relative seismic risk index is defined and calculated at each urban division (or zone) by weighted combination of the mentioned risk and response capacity indicators. This index represents the state of the risk in each zone in comparison with the others. The proposed method is applied to assess the earthquake risk at 22 municipal districts of Tehran. The results show that physical, human life and overall risk indices in district 15 of the city are considerably greater than the others. Meanwhile, in socioeconomic aspects, district 6 has the highest risk. Also, the analysis of the results demonstrates the major contribution of the response capacity term to determine the mitigation priorities. Finally, the results are compared with JICA (2000), using the same data, to show the efficiency of the proposed model. It is shown that the introduced method can significantly improve the results of the risk estimation and mitigation priorities.