洪水灾害风险分析的系统理论

从系统论的观点出发 ,提出了洪水灾害复杂大系统的概念 ,并以这一概念为基础 ,探讨了洪水灾害风险特征及洪水灾害风险评价的基本内容 ,提出并系统地阐述了以洪水危险性分析、承灾体易损性分析和洪水灾害灾情评估为核心内容的洪水灾害风险分析的系统理论     

Assessing social vulnerability and identifying spatial hotspots of flood risk to inform socially just flood management policy

This study presents the first nationwide spatial assessment of flood risk to identify social vulnerability and flood exposure hotspots that support policies aimed at protecting high-risk populations and geographical regions of Canada. The study used a national-scale flood hazard dataset (pluvial, fluvial, and coastal) to estimate a 1-in-100-year flood exposure of all residential properties across 5721 census tracts. Residential flood exposure data were spatially integrated with a census-based multidimensional social vulnerability index (SoVI) that included demographic, racial/ethnic, and socioeconomic indicators influencing vulnerability. Using Bivariate Local Indicators of Spatial Association (BiLISA) cluster maps, the study identified geographic concentration of flood risk hotspots where high vulnerability coincided with high flood exposure. The results revealed considerable spatial variations in tract-level social vulnerability and flood exposure. Flood risk hotspots belonged to 410 census tracts, 21 census metropolitan areas, and eight provinces comprising about 1.7 million of the total population and 51% of half-a-million residential properties in Canada. Results identify populations and the geographic regions near the core and dense urban areas predominantly occupying those hotspots. Recognizing priority locations is critically important for government interventions and risk mitigation initiatives considering socio-physical aspects of vulnerability to flooding. Findings reinforce a better understanding of geographic flood-disadvantaged neighborhoods across Canada, where interventions are required to target preparedness, response, and recovery resources that foster socially just flood management strategies.     

The informed society: an analysis of the public's information-seeking behavior regarding coastal flood risks

Recent flood risk management puts an increasing emphasis on the public's risk perception and its preferences. It is now widely recognized that a better knowledge of the public's awareness and concern about risks is of vital importance to outline effective risk communication strategies. Models such as Risk Information Seeking and Processing address this evolution by considering the public's needs and its information-seeking behavior with regard to risk information. This study builds upon earlier information-seeking models and focuses on the empirical relationships between information-seeking behavior and the constructs of risk perception, perceived hazard knowledge, response efficacy, and information need in the context of coastal flood risks. Specific focus is given to the mediating role of information need in the model and to the differences in information-seeking behavior between permanent and temporary residents. By means of a structured on-line questionnaire, a cross-sectional survey was carried out in the city of Ostend, one of the most vulnerable places to coastal flooding on the Belgian coast. Three hundred thirteen respondents participated in the survey. Path analysis reveals that information need does not act as a mediator in contrast to risk perception and perceived knowledge. In addition, it is shown that risk perception and perceived hazard knowledge are higher for permanent than temporary residents, leading to increased information-seeking behavior among the former group. Implications for risk communication are discussed.     

Flood Hazard and Flood Risk Assessment Using a Time Series of Satellite Images: A Case Study in Namibia

In this article, the use of time series of satellite imagery to flood hazard mapping and flood risk assessment is presented. Flooded areas are extracted from satellite images for the flood‐prone territory, and a maximum flood extent image for each flood event is produced. These maps are further fused to determine relative frequency of inundation (RFI). The study shows that RFI values and relative water depth exhibit the same probabilistic distribution, which is confirmed by Kolmogorov‐Smirnov test. The produced RFI map can be used as a flood hazard map, especially in cases when flood modeling is complicated by lack of available data and high uncertainties. The derived RFI map is further used for flood risk assessment. Efficiency of the presented approach is demonstrated for the Katima Mulilo region (Namibia). A time series of Landsat‐5/7 satellite images acquired from 1989 to 2012 is processed to derive RFI map using the presented approach. The following direct damage categories are considered in the study for flood risk assessment: dwelling units, roads, health facilities, and schools. The produced flood risk map shows that the risk is distributed uniformly all over the region. The cities and villages with the highest risk are identified. The proposed approach has minimum data requirements, and RFI maps can be generated rapidly to assist rescuers and decisionmakers in case of emergencies. On the other hand, limitations include: strong dependence on the available data sets, and limitations in simulations with extrapolated water depth values.     

Sensitivity Analysis of a Two-Dimensional Probabilistic Risk Assessment Model Using Analysis of Variance

This article demonstrates application of sensitivity analysis to risk assessment models with two-dimensional probabilistic frameworks that distinguish between variability and uncertainty. A microbial food safety process risk (MFSPR) model is used as a test bed. The process of identifying key controllable inputs and key sources of uncertainty using sensitivity analysis is challenged by typical characteristics of MFSPR models such as nonlinearity, thresholds, interactions, and categorical inputs. Among many available sensitivity analysis methods, analysis of variance (ANOVA) is evaluated in comparison to commonly used methods based on correlation coefficients. In a two-dimensional risk model, the identification of key controllable inputs that can be prioritized with respect to risk management is confounded by uncertainty. However, as shown here, ANOVA provided robust insights regarding controllable inputs most likely to lead to effective risk reduction despite uncertainty. ANOVA appropriately selected the top six important inputs, while correlation-based methods provided misleading insights. Bootstrap simulation is used to quantify uncertainty in ranks of inputs due to sampling error. For the selected sample size, differences in F values of 60% or more were associated with clear differences in rank order between inputs. Sensitivity analysis results identified inputs related to the storage of ground beef servings at home as the most important. Risk management recommendations are suggested in the form of a consumer advisory for better handling and storage practices.     

Aging and Cardiometabolic Risk in European HEMS Pilots: An Assessment of Occupational Old‐Age Limits as a Regulatory Risk Management Strategy

Old‐age limits are imposed in some occupations in an effort to ensure public safety. In aviation, the “Age 60 Rule” limits permissible flight operations conducted by pilots aged 60 and over. Using a retrospective cohort design, we assessed this rule's validity by comparing age‐related change rates of cardiometabolic incapacitation risk markers in European helicopter emergency medical service (HEMS) pilots near age 60 with those in younger pilots. Specifically, individual clinical, laboratory, and electrocardiogram (ECG)‐based risk markers and an overall cardiovascular event risk score were determined from aeromedical examination records of 66 German, Austrian, Polish, and Czech HEMS pilots (average follow‐up 8.52 years). Risk marker change rates were assessed using linear mixed models and generalized additive models. Body mass index increases over time were slower in pilots near age 60 compared to younger pilots, and fasting glucose levels increased only in the latter. Whereas the lipid profile remained unchanged in the latter, it improved in the former. An ECG‐based arrhythmia risk marker increased in younger pilots, which persisted in the older pilots. Six‐month risk of a fatal cardiovascular event (in or out of cockpit) was estimated between 0% and 0.3%. Between 41% and 95% of risk marker variability was due to unexplained time‐stable between‐person differences. To conclude, the cardiometabolic risk marker profile of HEMS pilots appears to improve over time in pilots near age 60, compared to younger pilots. Given large stable interindividual differences, we recommend individualized risk assessment of HEMS pilots near age 60 instead of general grounding.     

Project risk management using multiple criteria decision-making technique and decision tree analysis: a case study of Indian oil refinery

This study proposes an integrated analytical framework for effective management of project risks using combined multiple criteria decision-making technique and decision tree analysis. First, a conceptual risk management model was developed through thorough literature review. The model was then applied through action research on a petroleum oil refinery construction project in the Central part of India in order to demonstrate its effectiveness. Oil refinery construction projects are risky because of technical complexity, resource unavailability, involvement of many stakeholders and strict environmental requirements. Although project risk management has been researched extensively, practical and easily adoptable framework is missing. In the proposed framework, risks are identified using cause and effect diagram, analysed using the analytic hierarchy process and responses are developed using the risk map. Additionally, decision tree analysis allows modelling various options for risk response development and optimises selection of risk mitigating strategy. The proposed risk management framework could be easily adopted and applied in any project and integrated with other project management knowledge areas.