Seismic damage evaluation in urban areas using the capacity spectrum method: Application to Barcelona

Conceptual aspects related to seismic vulnerability, damage and risk evaluation are discussed first, together with a short review of the most widely used possibilities for seismic evaluation of structures. The capacity spectrum method and the way of obtaining seismic damage scenarios for urban areas starting from capacity and fragility curves are then discussed. The determination of capacity curves for buildings using non-linear structural analysis tools is then explained, together with a simplified expeditious procedure allowing the development of fragility curves. The seismic risk of the buildings of Barcelona, Spain, is analyzed in the paper, based on the application of the capacity spectrum method. The seismic hazard in the area of the city is described by means of the reduced 5% damped elastic response spectrum. The information on the buildings was obtained by collecting, arranging, improving and completing a broad database of the dwellings and current buildings. The buildings existing in Barcelona are mainly of two types: unreinforced masonry structures and reinforced concrete buildings with waffled-slab floors. The ArcView software was used to create a GIS tool for managing the collected information in order to develop seismic risk scenarios. This study shows that the vulnerability of the buildings is significant in Barcelona and, therefore, in spite of the low-to-moderate seismic hazard in the region, the expected seismic risk is considerable.     

Evaluating sources of uncertainty in Australian runoff projections

Generating estimates of the future impacts of climate change on human and natural systems is confounded by cascading uncertainties which propagate through the impact assessment. Here, a simple stochastic rainfall–runoff model representing 238 river basins on the Australian continent was used to assess the sensitivity of the risk of runoff changes to various sources of uncertainty. Uncertainties included global mean temperature change, greenhouse gas stabilisation targets, catchment sensitivities to climatic change, and the seasonality of runoff, rainfall, and evaporation. Model simulations provided estimates of the first-order risk of climate change to Australian catchments, with several regions having high likelihoods of experiencing significant reductions in future runoff. Climate uncertainty (at global and regional scales) was identified as the dominant driving force in hydrological risk assessments. Uncertainties in catchment sensitivities to climatic changes also influenced risk, provided they were sufficiently large, whereas structural assumptions of the model were generally negligible. Collectively, these results indicate that rigorous assessment of climate risk to water resources over relatively long time-scales is largely a function of adequately exploring the uncertainty space of future climate changes.     

奥布公路泥石流危险性评价

作为喀喇昆仑公路的重要组成部分,奥依塔克-布伦口(简称奥布)公路受到沿线数量众多且规模较大的泥石流影响,常导致行车中断,人员和车辆安全受到威胁。在现场地质考察和走访基础上,依据ArcGIS工具对奥布公路段的15条典型泥石流沟开展了重点调查和危险性评价。首先对汇流面积、纵坡度、面积宽度比、堆积区面积和距公路距离等5个评价因子属性进行归一化处理;然后采用两层结构的层次分析法计算得到影响因子的权重,随后将属性函数与权重乘积加和,得到灾害易发性指数(DFRD);最后对泥石流危险度(DRFR)进行计算分析和危险程度分级。结果发现,高-中度危险的11条泥石流主要分布在布伦口峡谷上游、盖孜检查站和加水沟之间,构成了泥石流灾害发育较为集中且危害性较大的路段。工程上相应采用隧道、高架桥等绕避措施,取得较好成效。     

影响公众震灾风险认知的因素分析——以新疆喀什、乌鲁木齐地区为例

研究震灾风险认知及其影响因素有助于从公众视角揭示风险潜在因素,为降低灾害风险提供决策依据.本文以新疆的喀什、乌鲁木齐为研究区,通过问卷调查方式,采用假设检验和相关分析等统计方法,研究影响公众的临震心理、风险估计、地震知识水平、防震意愿及行为等震灾风险认知的因素.结果表明:影响因素包括性别、教育水平、收入水平、家庭结构、房屋结构、居住区危险性等;因素之间互相联系与风险认知因子形成正、负反馈链,其中收入水平影响了风险感知是否能转化为防减灾的积极行为.并在灾害风险分析的基础上提出了减轻地震灾害风险的对策建议.     

GIS-based risk assessment of grassland fire disaster in western Jilin province, China

Grassland fire disasters have occurred frequently and adversely affected livestock agriculture and social-economic development greatly in the grassland regions of Jilin province, China. Moreover, both the frequency of grassland fire and loss from them are considered to be increasing with the global warming and economic development. This study presents a methodology for risk analysis and assessment of grassland fire disaster, taking western Jilin province as a case study area based on geographic information system (GIS). The composite grassland fire disaster risk index (GFDRI) combined the hazard of grassland fire, the exposure of the region, the vulnerability and emergency response and recovery capability for grassland fire disaster of the region were developed to assess and compare risk of grassland fire disaster in different counties in western Jilin province, China using the natural disaster risk index method (NDRIM), analytic hierarchy process (AHP) and weighted comprehensive method (WCM). Then, the risk degree of grassland fire disaster was assessed and regionalized in the western Jilin province, China based on GFDRI by using GIS. It is shown that the most places of western Jilin province were in mediate risk. Zhenlai, Tongyu were in heavy risk. Taobei, Ningjiang, Fuyu were in light risk. The information obtained from interviewing the district official committees in relation to result compiled was statistically evaluated. The GFDRI was developed to be an easily understandable tool that can be used to assess and compare the relative risk of grassland fire disaster in different counties in t western Jilin province, China, and to compare the different relative contributions of various factors, e.g., frequency of grassland fire and quality of emergency evacuation plan. The GFDRI is specifically intend to support local and national government agencies of grassland fire disaster management as they (1) make resource allocation decisions; (2) make high-level planning decisions; and (3) raise public awareness of grassland fire disaster risk, its causes, and ways to manage it.     

The selection of corrosion prior distributions for risk based integrity modeling

The deterioration of the condition of process plants assets has a major negative impact on the safety of its operation. Risk based integrity modeling provides a methodology to quantify the risks posed by an aging asset. This provides a means for the protection of human life, financial investment and the environmental damage from the consequences of its failures. This methodology is based on modeling the uncertainty in material degradations using probability distributions, known as priors. Using Bayes theorem, one may improve the prior distribution to obtain a posterior distribution using actual inspection data. Although the choice of priors is often subjective, a rational consensus can be achieved by judgmental studies and analyzing the generic data from the same or similar installations. The first part of this paper presents a framework for a risk based integrity modeling. This includes a methodology to select the prior distributions for the various types of corrosion degradation mechanisms, namely, the uniform, localized and erosion corrosion. Several statistical tests were conducted based on the data extracted from the literature to check which of the prior distributions follows data the best. Once the underlying distribution has been confirmed, one can estimate the parameters of the distributions. In the second part, the selected priors are tested and validated using actual plant inspection data obtained from existing assets in operation. It is found that uniform corrosion can be best described using 3P-Weibull and 3P-Lognormal distributions. Localized corrosion can be best described using Type1 extreme value and 3P-Weibull, while erosion corrosion can best be described using the 3P-Weibull, Type1 extreme value, or 3P-Lognormal distributions.     

Floods on the rivers within the Kama basin and flood-control measures

We examine the conditions of flood formation on water bodies in Permsky Krai. A spatio-temporal analysis is made of the development of floods on rivers. We demonstrate the possibility of using protection and bank-strengthening structures with an example of the Sylva, Iren and Shakva rivers in the area of the city of Kungur.     

Hot-topics and Prospects of Global Platform for Disaster Risk Reduction: Based on 2017 Global Platform for Disaster Risk Reduction in Cancun,Mexico

A brief introduction to the Fifth Session of Global Platform for Disaster Risk Reduction, which was held in Cancun, Mexico, organized by United Nations International Strategy for Disaster Reduction (UN/ISDR) and hosted by the Government of Mexico from 22 May to 26 May 2017, was firstly provided. Combined with “Sendai Framework for Disaster Risk Reduction 2015-2030”, “Transforming our world: the 2030 Agenda for Sustainable Development”, and related work on natural disaster risk reduction at global, regional, country and local scales, some hot-topics and prospects of global platform for disaster risk reduction were put forward. Some findings were concluded, consisting of understanding disaster risk, disaster risk governance, building and enhancing resilience to disasters, coherence between the Sendai Framework, the 2030 Agenda for Sustainable Development and Climate Change Adaptation (CCA). Implementing the Disaster Risk Reduction (DRR) through cross-sectoral collaboration, removing barriers and promoting public-private cooperation in DRR and other types of partnership among multi-stakeholders will become the main force pattern of DRR in the near future. Large-scale disaster risk governance caused by multi-hazards (disaster cluster), disaster chain and disaster compound will be the main trend in scientific research of DRR. Building regional disaster risk reduction platform (e.g. the Silk Road Economic Belt and the 21^st-Century Maritime Silk Road) and sharing the technologies and information of disaster risk reduction will be the main contents of DRR practices. Building and optimization of institutional mechanisms on DRR will be the trend of DRR idea. Improving and enhancing the support to communities, vulnerable groups and locals on DRR will be the main trend in DRR achievements’ application and demonstration in China.     

Capturing channelized reservoir connectivity uncertainty with amalgamation curves

During reservoir characterization all the geological uncertainties affecting the quantity and distribution of hydrocarbons should be captured to assess the risks affecting final recovery.In a typical modeling workflow the geological uncertainties are accounted for through the construction of a sufficiently large set of 3-D static models. Out of this set, a few representative models are selected and dynamically simulated so as to correlate the geological characteristics of the reservoir with its dynamic performance and to propagate the uncertainty onto the final recovery factors, yet maintaining the computational run time acceptable. In channelized depositional environments, which are strongly heterogeneous, the selection approach must also account for channel connectivity, which plays a key role in the possibility of efficiently draining the reservoir for a reasonable number of wells.This study can be seen as a step forward in the assessment of the risks associated to the development of channelized reservoirs under the assumption that a way to express the concept of channel connectivity is channel amalgamation. Channel amalgamation is here defined through amalgamation curves which are numerically described using a set of indexes whose combination provide spatial information of channel intersections. These indexes were calculated for a full set of 3-D geological models and used to steer the selection of a representative model sub-set for subsequent fluid flow simulations.The validity of the index-based selection was verified on different sets of synthetic reservoir models through the evaluation of the representativeness of the model sub-set in reproducing the uncertainty of the original dataset. Eventually, the existence of a strong correlation between channel amalgamation and production performance was proved. From a practical perspective, the possibility to include channel amalgamation in the assessment of the geological models can considerably improve the representativeness of the selected models for uncertainty propagation thus reducing significantly the number of geological models to be considered.     

温岭市台风风暴潮灾害风险评估和区划研究

文章选取对温岭市最不利的台风路径,采用SWAN和MIKE21模型计算台风风暴潮淹没深度,对淹没深度进行分类并划分危险性等级;根据温岭市土地利用类型进行脆弱性等级划分;建立台风风暴潮和承灾体致灾因子指标体系,得出风险水平等级区划。结果表明,温岭市台风风暴潮灾害风险最大的区域在东部产业聚集区、松门镇沿海、乐清湾温峤镇西南角和坞根镇西北角,其次在隘顽湾顶部分区域,再次在滨海镇和松门镇部分区域,其他地区风险相对较小。