The impact of epistemic uncertainty on an earthquake loss model

Models capable of estimating losses in future earthquakes are of fundamental importance for emergency planners, for the insurance and reinsurance industries, and for code drafters. Constructing a loss model for a city, region or country involves compiling databases of earthquake activity, ground conditions, attenuation equations, building stock and infrastructure exposure, and vulnerability characteristics of the exposed inventory, all of which have large associated uncertainties. Many of these uncertainties can be classified as epistemic, implying—at least in theory—that they can be reduced by acquiring additional data or improved understanding of the physical processes. The effort and cost involved in refining the definition of each component of a loss model can be very large, for which reason it is useful to identify the relative impact on the calculated losses due to variations in these components. A mechanically sound displacement‐based approach to loss estimation is applied to a test case of buildings along the northern side of the Sea of Marmara in Turkey. Systematic variations of the parameters defining the demand (ground motion) and the capacity (vulnerability) are used to identify the relative impacts on the resulting losses, from which it is found that the influence of the epistemic uncertainty in the capacity is larger than that of the demand for a single earthquake scenario. Thus, the importance of earthquake loss models which allow the capacity parameters to be customized to the study area under consideration is highlighted. Copyright © 2005 John Wiley & Sons, Ltd.     

安徽省地质灾害气象预报预警模型研究

通过对基于地质环境信息平台的地质灾害气象预报预警模型构建进行了探讨。拟在先期已具备的地质灾害预警分区、地质灾害易发分区基础上,以地质灾害"易发度"、预报降雨量、有效降雨量为因子,采用logistic回归模型确定各个评价单元的预警等级,经插值计算、图斑合并,实现地质灾害气象风险预警。     

A new assessment model for evacuation vulnerability in urban areas

In the high-speed urbanization process of China, the urban population has been increasing significantly, leading to a high-density aggregation of population. However, the sharp increase in population density has not produced commensurate improvements in the road networks. On the contrary, the population increase induced a serious evacuation vulnerability, which cities experience during various hazards and catastrophic events. Therefore, research on evacuation vulnerability is important to urban planning. To assess the evacuation vulnerability, the optimal and worst scenarios should be considered because all possible evacuation plans occur between these extremes. However, most previous evacuation vulnerability studies are based on the worst-case scenario, only providing an upper bound of a potential evacuation assessment. To provide a more comprehensive theoretical basis for decision-makers to understand the consequences caused by all possible evacuations, this paper proposes an optimal evacuation vulnerability assessment model that provides the lower bound on potential evacuation difficulties. The model is solved by a stepwise spreading algorithm based on Graph Theory. Subsequently, to evaluate the effectiveness of the model, the study adopts the model to assess the evacuation capability of different road network topologies. A comparison with previous research was performed. The model was demonstrated in an application to the South Luogu Alley of Beijing, China. The significance of this paper is that the combination of our model with previous research may provide a more complete theoretical basis for an evacuation vulnerability assessment.     

Vulnerability of Kuwait coast to sea level rise

Assessing coastal vulnerability to sea level rise (SLR) at local and regional scales is a fundamental step for designing successful long-term coastal management plans. This study was thus designed to assess Kuwait coastal vulnerability to SLR at four scenarios (.5, 1, 1.5 and 2 m). Potential inundated areas and the number of people at risk were estimated based on these SLR scenarios. A coastal vulnerability index (CVI) map of Kuwait was then computed based on the lowest scenario using eight parameters: elevation, coastal slope, geomorphology, distance to 20-m isobath, population, land use, cultural heritage and transportation. The geographic distribution of inundated areas at an SLR of .5 m revealed that the northern islands of Kuwait and coastal areas along Kuwait Bay would be highly impacted, whereas the coastal area near Shuaibah Port was the most influenced among the southern coasts. Most of the coastal area exhibited a moderate vulnerability to SLR, especially the northern islands. This study presented an initial vulnerability assessment for Kuwait coasts to SLR, which can be extended with more variables. The integrated remote sensing and geographic information system methodology demonstrated in this study can be applied in similar studies elsewhere.     

Hispanic Immigrants' Vulnerabilities to Flood and Hurricane Hazards in Two United States Metropolitan Areas

Research reveals that disasters are disproportionately debilitating for marginalized social groups. Numerous studies have examined racial/ethnic dimensions of disaster vulnerability, but few have focused on Hispanic immigrants. More research on Hispanic immigrants is needed, since they constitute a major component of the Hispanic population—the largest and fastest‐growing minority group in the U.S.—and because they experience distinctive cultural and immigration status disadvantages. We examine the flood/hurricane vulnerabilities of Hispanic immigrants in comparison to U.S.–born Hispanics and non‐Hispanic whites. Using mixed methods to analyze data from 429 surveys and 31 interviews with residents living in flood zones, we examine differences in self‐protective action, risk perception, and hazard knowledge between the three groups in Houston and Miami. Hispanic immigrants exhibited lower levels of self‐protection and hazard knowledge, and higher perceptions of risk, which reflects their heightened vulnerability. Risk‐reduction programs should target the particular vulnerabilities of Hispanic immigrants, and future studies should examine their vulnerabilities in other contexts.     

Landfill site selection based on reliability concepts using the DRASTIC method and AHP integrated with GIS – a case study of Bengaluru city,India

The selection of landfill sites for municipal solid waste (MSW) disposal involves consideration of geological, hydrological and environmental parameters which exhibit large spatial variability. Therefore, it is necessary to define, to what extent the chosen sites are reliable such that the probability of environmental pollution and health risks to population is minimal. In the present study, groundwater vulnerability to contamination has been assessed using the standard DRASTIC method. The results showed that the study region has 9.45% of very less, 32.94% of less, 25.47% of moderate, 22.79% of high and 9.35% of very high vulnerable zones. The study also revealed that none of the landfills are located in safe zones. This suggests that it requires proper remedial measures to avoid environmental pollution. A landfill site selection process has been carried out using the Analytical Hierarchy Process integrated with Geographical Information System tools. The obtained results showed that only 3.59?km² (0.08%) of the total area is suitable for landfills. The reliability analysis of the site suitability revealed that landfills are located at unreliable locations where the probability of risk to environmental pollution is high. The presented approach assists decision-makers in selecting reliable locations for the safe disposal of MSW.     

Development of groundwater favourability map using GIS-based driven data mining models: an approach for effective groundwater resource management

The development of groundwater favourability map is an effective tool for the sustainability management of groundwater resources in typical agricultural regions, such as southern Perak Province, Malaysia. Assessing the potentiality and pollution vulnerability of groundwater is a fundamental phase of favourability mapping. A geographic information system (GIS)-based Boolean operator of a spatial analyst module was applied to combine a groundwater potentiality map (GPM) model and a groundwater vulnerability to pollution index (GVPI) map, thereby establishing the favourable zones for drinking water exploration in the investigated area. The area GPM model was evaluated by applying a GIS-based Dempster–Shafer–evidential belief function model. In the evaluation, six geoelectrically determined groundwater potential conditioning factors (i.e. overburden resistivity, overburden thickness, aquifer resistivity, aquifer thickness, aquifer transmissivity and hydraulic conductivity) were synthesized by employing the probability-based algorithms of the model. The generated thematic maps of the seven hydrogeological parameters of the DRASTIC model were considered as pollution potential conditioning factors and were analysed with the developed ordered weighted average–DRASTIC index model algorithms to construct the GVPI map. Approximately 88.8 and 85.71% prediction accuracies for the Groundwater Potentiality and GVPI maps were established using the reacting operating characteristic curve method and water quality status–vulnerability zone relationship scheme, respectively. Finally, the area groundwater favourability map (GFM) model was produced by applying a GIS-based Boolean operator on the Groundwater Potentiality and GVPI maps. The GFM model reveals three distinct zones: ‘not suitable’, ‘less suitable’ and ‘very suitable’ zones. The area analysis of the GFM model indicates that more than 50% of the study area is covered by the ‘very suitable’ zones. Results produce a suitability map that can be used by local authorities for the exploitation and management of drinking water in the area. The study findings can also be applied as a tool to help increase public awareness of groundwater issues in developing countries.     

Implications of Japan’s long term climate mitigation target and the relevance of uncertain nuclear policy

Achieving long-term climate mitigation goals in Japan faces several challenges, starting with the uncertain nuclear power policy after the 2011 earthquake, the uncertain availability and progress of energy technologies, as well as energy security concerns in light of a high dependency on fuel imports. The combined weight of these challenges needs to be clarified in terms of the energy system and macroeconomic impacts. We applied a general equilibrium energy economic model to assess these impacts on an 80% emission reduction target by 2050 considering several alternative scenarios for nuclear power deployment, technology availability, end use energy efficiency, and the price of fossil fuels. We found that achieving the mitigation target was feasible for all scenarios, with considerable reductions in total energy consumption (39%–50%), higher shares of low-carbon sources (43%–72% compared to 15%), and larger shares of electricity in the final energy supply (51%–58% compared to 42%). The economic impacts of limiting nuclear power by 2050 (3.5% GDP loss) were small compared to the lack of carbon capture and storage (CCS) (6.4% GDP loss). Mitigation scenarios led to an improvement in energy security indicators (trade dependency and diversity of primary energy sources) even in the absence of nuclear power. Moreover, preliminary analysis indicates that expanding the range of renewable energy resources can lower the macroeconomic impacts of the long term target considerably, and thus further in depth analysis is needed on this aspect.

Key policy insights

• For Japan, an emissions reduction target of 80% by 2050 is feasible without nuclear power or CCS.

• The macroeconomic impact of such a 2050 target was largest without CCS, and smallest without nuclear power.

• Energy security indicators improved in mitigation scenarios compared to the baseline.

     

基于雷电监测资料的南充市雷电灾害风险区划研究

选取闪电密度、雷暴日、经济损失风险、生命损失风险等作为各县(市、区)雷电灾害易损性评估指标;并在此基础上,建立雷电灾害评估体系,对各县(市、区)的雷灾易损性进行了综合评价,进行区划分析。基于南充市雷电监测数据和人文经济指标而制作的全市雷电灾害风险区划,可以为全市雷电灾害防御提供科学依据,能有效降低因雷电灾害带来的生命财产损失和社会影响,提高灾害天气预报、预警能力,提升气象防灾减灾能力。基于南充市雷电监测数据而统计出的闪电密度、雷暴日数更具客观性。