Uncertainty Reduction Through Data Management in the Development, Validation, Calibration, and Operation of a Hurricane Vulnerability Model

Catastrophe models estimate risk at the intersection of hazard,exposure,and vulnerability.Each of these areas requires diverse sources of data,which are very often incomplete,inconsistent,or missing altogether.The poor quality of the data is a source of epistemic uncertainty,which affects the vulnerability models as well as the output of the catastrophe models.This article identifies the different sources of epistemic uncertainty in the data,and elaborates on strategies to reduce this uncertainty,in particular through identification,augmentation,and integration of the different types of data.The challenges are illustrated through the Florida Public Hurricane Loss Model(FPHLM),which estimates insured losses on residential buildings caused by hurricane events in Florida.To define the input exposure,and for model development,calibration,and validation purposes,the FPHLM teams accessed three main sources of data:county tax appraiser databases,National Flood Insurance Protection(NFIP)portfolios,and wind insurance portfolios.The data from these different sources were reformatted and processed,and the insurance databases were separately cross-referenced at the county level with tax appraiser databases.The FPHLM hazard teams assigned estimates of natural hazard intensity measure to each insurance claim.These efforts produced an integrated and more complete set of building descriptors for each policy in the NFIP and wind portfolios.The article describes the impact of these uncertainty reductions on the development and validation of the vulnerability models,and suggests avenues for data improvement.Lessons learned should be of interest to professionals involved in disaster risk assessment and management.

A Vulnerability Model Construction Method Based on Chemical Abstract Machine

It is difficult to formalize the causes of vulnerability, and there is no effective model to reveal the causes and characteristics of vulnerability. In this paper, a vulnerability model construction method is proposed to realize the description of vulnerability attribute and the construction of a vulnerability model. A vulnerability model based on chemical abstract machine（CHAM） is constructed to realize the CHAM description of vulnerability model, and the framework of vulnerability model is also discussed. Case study is carried out to verify the feasibility and effectiveness of the proposed model. In addition, a prototype system is also designed and implemented based on the proposed vulnerability model. Experimental results show that the proposed model is more effective than other methods in the detection of software vulnerabilities.

Application of fuzzy optimization model in the evaluationof urban flood-waterloggedvulnerabilitybased on the synthetic weight ofgame theory

The evaluation of urban flood-waterlogged vulnerability is very important to the safety of urban flood control. In this paper, the evaluation of consolidated index is used. Respectively, AHP and entropy method calculate the subjective and objective weight of the evaluation indicators, and combine them by game theory. So we can obtain synthetic weight based on objective and subjective weights. The evaluation of urban flood-waterlogged vulnerability as target layer, a single variable multi-objective fuzzy optimization model is established. We use the model to evaluate flood-waterlogged vulnerability of 13 prefecture-level city in Hunan, and compare it with other evaluation method. The results show that the evaluation method has certain adaptability and reliability, and it＇ s helpfid to the construction planning of urban flood control.

Comparison on Vulnerability of European and Chinese Air Transport Networks under Spatial Hazards

European air transport network(EATN)and Chinese air transport network(CATN),as two important air transport systems in the world,are facing increasingly spatial hazards,such as extreme weathers and natural disasters. In order to reflect and compare impact of spatial hazards on the two networks in a practical way,a new spatial vulnerability model(SVM)is proposed in this paper,which analyzes vulnerability of a network system under spatial hazards from the perspectives of network topology and characteristics of hazards. Before introduction of the SVM,two abstract networks for EATN and CATN are established with a simple topological analysis by traditional vulnerability method. Then,the process to study vulnerability of an air transport network under spatial hazards by SVM is presented. Based on it,a comparative case study on EATN and CATN under two representative spatial hazard scenarios,one with an even spatial distribution,named as spatially uniform hazard,and the other with an uneven spatial distribution that takes rainstorm hazard as an example,is conducted. The simulation results show that both of EATN and CATN are robust to spatially uniform hazard,but vulnerable to rainstorm hazard. In the comparison of the results of the two networks that only stands from the points of network topology and characteristics of hazard without considering certain unequal factors,including airspace openness and flight safety importance in Europe and China,EATN is more vulnerable than CATN under rainstorm hazard. This suggests that when the two networks grow to a similar developed level in future,EATN needs to pay more attention to the impact of rainstorm hazard.

Risk assessment of maize drought disaster in southwest China using the Environmental Policy Integrated Climate model

The East Asian monsoon has a tremendous impact on agricultural production in China. An assessment of the risk of drought disaster in maize-producing regions is therefore important in ensuring a reduction in such disasters and an increase in food security. A risk assessment model, EPIC（Environmental Policy Integrated Climate） model, for maize drought disasters based on the Erosion Productivity Impact Calculator crop model is proposed for areas with the topographic characteristics of the mountainous karst region in southwest China. This region has one of the highest levels of environmental degradation in China. The results showed that the hazard risk level for the maize zone of southwest China is generally high. Most hazard index values were between 0.4 and 0.5,accounting for 47.32% of total study area. However,the risk level for drought loss was low. Most of the loss rate was ＆lt;0.1, accounting for 96.24% of the total study area. The three high-risk areas were mainlydistributed in the parallel ridge–valley areas in the east of Sichuan Province, the West Mountain area of Guizhou Province, and the south of Yunnan Province.These results provide a scientific basis and support for the reduction of agricultural drought disasters and an increase in food security in the southwest China maize zone.