Development of vulnerability curves of buildings to windstorms using insurance data: An empirical study in South Korea

Development of Empirical Wind Vulnerability Curves of School Buildings Damaged by the 2016 Typhoon Nina

Introducing loss transfer functions to model seismic financial loss: A case study of Iran

Development of structural type-based physical vulnerability curves to debris flow using numerical analysis and regression model

The Northwestern Pacific Ocean Basin is home to the strongest tropical cyclones in the world, called typhoons. The Philippines is situated as the gateway for the typhoons developing in the Northwestern Pacific Basin. As a result, the country is being exposed to the risk brought by significantly strong typhoons that occur more than once annually. Lightweight buildings, particularly wooden buildings, and their structural components are the most vulnerable to severe winds. This study aims to perform vulnerability analysis on wooden buildings, by developing vulnerability curves that relate the magnitude of severe winds to the variation of damages and by establishing the probabilities of identified damage states of the buildings at certain wind speeds - which are called fragility curves. This study employs an improved framework from a heuristic-empirical-computational methodology previously used in determining GMMA-RAP vulnerability curves. This enhanced framework uses a component-based Monte Carlo vulnerability analysis to determine the improved vulnerability curve to account for the statistical variations of documented building damage from severe winds. A maximum, average, and minimum vulnerability curve were developed by fitting a cumulative lognormal distribution function wherein the mean parameters are 250.92, 425.89, 148.80, and the variance parameters are 0.579, 0.257, 0.433, respectively—the functions used an offset of 72 kph for all the developed curves. The developed curves were then compared to empirical field survey data, wherein 71.43% of the empirical data was within the developed envelope.

Few empirical seismic vulnerability curves exist for non-engineered reinforced concrete buildings in developing countries, and this is particularly true for the South Asian countries. This category of buildings is widespread and is highly vulnerable, since the buildings suffer from serious problems due to poor design and construction and are prone to collapse in moderate earthquakes. In this paper, building damage data from the Kashmir earthquake (2005), Pakistan are utilized to develop empirical vulnerability curves for the non-engineered reinforced concrete structures in the region. In order to develop empirical vulnerability curves, a damage probability matrix was defined and its elements corresponding to damage ratio of different damage states are used to evaluate the mean damage ratio. The developed curve show abrupt damage accumulation at relatively small values of peak ground acceleration. The findings of mean damage ratio as a function of peak ground acceleration are compared with the most relevant existing empirical and judgmental vulnerability curves to show the severity of damage in non-engineered reinforced concrete structures of that region and to validate for use in risk assessment studies.

Catastrophe risk models require the damage functions of each vulnerable item in inventory to estimate volcanic ash losses. The damage functions are used to represent the relation between damage factors and damage and also widely used in engineering and natural hazard studies to calculate the vulnerability. In most cases, damage functions are constructed as fragility or vulnerability curves, and researchers are confused by the similarities between them particularly when they perform interdisciplinary research. Thus, we aim to explain the similarities and differences between fragility and vulnerability curves and their relationship by providing case studies to construct them. In addition, we suggest a simple method to construct the damage functions between damage ratio and volcanic ash thickness using limited damage data. This study comes from the fact that damage functions are generally constructed using damage data. However, there is no available volcanic ash damage data in Korea, and not even enough volcanic disaster data to construct damage functions in the world, compared to other hazards. Using the method suggested in the study and the limited damage data from Japan and New Zealand, we construct Weibull-type functions or linear functions dependent of available data to calculate volcanic ash loss estimation, which we think need to be corrected to make it more suitable for inventory characteristics and environmental conditions in Korea.

A vulnerability curve (VC) describes the extent of xylem cavitation resistance. Centrifuges have been used to generate VCs for decades via static- and flow-centrifuge methods. Recently, the validity of the centrifuge techniques has been questioned. Researchers have hypothesized that the centrifuge techniques might yield unreliable VCs due to the open-vessel artifact. However, other researchers reject this hypothesis. The focus of the dispute is centered on whether exponential VCs are more reliable when the static-centrifuge method is used rather than the flow-centrifuge method. To further test the reliability of the centrifuge technique, two centrifuges were manufactured to simulate the static- and flow-centrifuge methods. VCs of three species with open vessels of known lengths were constructed using the two centrifuges. The results showed that both centrifuge techniques produced invalid VCs for Robinia because the water flow through stems under mild tension in centrifuges led to an increasing loss of water conductivity. In addition, the injection of water in the flow-centrifuge exacerbated the loss of water conductivity. However, both centrifuge techniques yielded reliable VCs for Prunus, regardless of the presence of open vessels in the tested samples. We conclude that centrifuge techniques can be used in species with open vessels only when the centrifuge produces a VC that matches the bench-dehydration VC.

یکی از مهم ترین چالش‌های جهانی، مخصوصا در منطقه خاورمیانه، طوفان‌های گرد و غبار است. با توجه به افزایش روز افزون طوفان‌های گرد و غبار و خطرات ناشی از آن، لزوم بررسی و تجزیه و تحلیل داده‌های بادسنجی به منظور شناخت این پدیدۀ مخرب زیست محیطی مشخص است. موقعیت ویژه ایستگاه سرپل ذهاب به دلیل بروز پی در پی طوفان های گرد و غبار، موجب انتخاب این ایستگاه برای مطالعه گردید. از ترسیم گلغبارهای سالانه و ماهانه و نیز تجزیه و تحلیل داده‌های هواشناسی مربوط به سال های 1986 تا 2009 مشخص شد وقوع طوفان ها سیر صعودی داشته است. در سال هایی که با افزایش وقوع طوفان مواجه بوده‌ایم جهت بادها میل به غربی شدن پیدا می‌کند و لزوما بادهای گرد و غبارزا بادهایی نبوده‌اند که سرعت بیشتری داشته باشند،که این نتیجه در مورد بررسی‌های ماهانه و سالانه صادق است. بررسی میزان همبستگی عناصر اقلیمی نشان می‌دهد که کاهش میدان دید با سرعت پایین باد همراه است و طوفان های گرد و غبار لزوما با سرعت بیشتر باد همراه نبوده‌اند. با توجه به ابعاد وسیع این پدیده و فرا ایستگاهی بودن آن لزوم یک طرح جامع برای شناسایی این پدیده در بلند مدت در کل منطقه تحت تاثیر احساس می‌شود.

Tunnel construction, a common byproduct of rapid economic growth and transportation-system development, carries inherent risks to life and various kinds of property that operations and management professionals must take into account. Due to various and complicated geological conditions, tunnel construction projects can produce unexpected collapses, landslides, avalanches, and water-related hazards. Moreover, damage from such events can be intensified by other factors, including geological hazards caused by natural disasters, such as heavy rainfall and earthquakes, resulting in huge social, economic, and environmental losses. Therefore, the present research conducted multiple linear regression analyses on financial-loss data arising from tunnel construction in Korea to develop a novel tunnel-focused method of natural-hazard risk assessment. More specifically, the total insured value and actual value of damage to 277 tunnel-construction projects were utilized to identify significant natural-disaster indicators linked to unexpected construction-budget overruns and construction-scheduling delays. Damage ratios (i.e., actual losses over total insured project value) were used as objective, quantitative indices of the extent of damage that can be usefully applied irrespective of project size. Natural-hazard impact data—specifically wind speed, rainfall, and flood occurrences—were applied as the independent variables in the regression model. In the regression model, maximum wind speed was found to be correlated with tunnel projects’ financial losses across all three of the natural-hazard indicators. The present research results can serve as important baseline references for natural disaster-related risk assessments of tunnel-construction projects, and thus serve the wider purpose of balanced and sustainable development.

ABSTRACTThe aim of this study is to develop regional vulnerability functions of buildings to estimate the loss from windstorms. Windstorms trigger critical financial damage to assets around the world. Insurance companies assess the financial risk of their exposures by employing windstorm risk assessment models. The vulnerability function in the risk assessment model is generally based on the analysis of actual damage records from insurance companies. However, the absence of detailed loss data is an obstacle to developing vulnerability functions. To fill this gap, this study provides a methodology to develop a function using an insurance company's loss data associated with windstorms. Vulnerability functions are generated based on the wind speed, line of business, and value of the property. The findings and methodology of this study offer a practical way of reflecting the real economic losses and regional vulnerability of buildings and help to develop vulnerability functions for insurance companies and emergency planners.

Effects of forcing scale and intensity on the emergence and maintenance of polar vortices on Saturn and Ice Giants

Event Abstract Back to Event Identification of highly pathogenic avian influenza suitable areas for wild birds using species distribution models in South Korea. Lee Kyuyoung1*, Dae-sung Yu2*, Beatriz Martínez-López1, Jaber A. Belkhiria1, Sung-il Kang2, Hachung Yoon2, Seong-Keun Hong2, ILSEOB LEE2, Han-Mo Son2 and Kwangnyeong Lee2 1 Department of Medicine & Epidemiology, School of Veterinary Medicine, University of California, Davis, United States 2 Animal and Plant Quarantine Agency (South Korea), Republic of Korea Highly pathogenic avian influenza (HPAI) virus is influenza A type virus with high mortality and morbidity in the broad range of host species domestic and wild birds to humans. HPAI infection has been a high-priority concern in global poultry industry because of consistent generation and circulation of novel HPAI strains, and consequent tremendous financial losses. Wild birds are considered one of the most important sources of novel HPAI introductions in poultry farms due to the experimental evidence of their asymptomatic infection with viral shedding, genetic closeness of HPAI virus identified in domestic poultry and wild birds, and spatial and temporal coincidence of identification of HPAI in wild birds and domestic poultry. The poultry industry in South Korea has annually suffered from the introduction of novel HPAI strains since early 2000s. HPAI infection in annually migrated wild birds has been carefully monitored to rapidly establish preventive measures of HPAI introduction into poultry farms in South Korea. However, current understanding of highly risk areas or suitable areas for HPAI in wild birds and contribution of other geographical and environmental factors contributing to HPAI vírus suitability is limited. Application of species distribution models based on digitalized geographical and environmental information facilitates our understanding about suitability of wild species’ habitat and its association with environmental and geographical factors. Furthermore, species distribution modelling can be applied to identify high-risk areas of potential disease transmission at the interface between wild species and domestic animals. Our study aimed to evaluate the areas with higher suitability/risk for HPAI identification in wild birds in South Korea and to describe what is the influence or association with the different environmental and geographical factors. Our results will help to not only have a better understanding of the ecology of HPAI in wild birds but also to establish more effective, risk-based, surveillance to prevent novel HPAI introductions into domestic poultry farms in South Korea We obtained land cover, monthly climate (precipitation, temperature and wind speed) and ecological preservation area (Level 1-3) data of South Korea in digitalized form as environmental and geographical data. The observation records of 7 species of wild birds (Baikal teal, white-front goose, common teal, mandarin duck, mallard, bean goose, spot-billed duck) in 206 habitats in South Korea from 1999 to 2017 were used to estimate the suitability map for the wild bird distribution in South Korea. The geographical records of wild bird HPAI surveillance from 2014 to 2018 was combined with 7 wild birds species distribution and environmental and geographical data to estimate the suitability map of HPAI identification in wild birds. Each suitability maps was estimated by maximum entropy approach (Maxent model) via the “dismo” package in R studio. 3. Results and Discussion Our study presents the suitability map of HPAI identification in wild birds and how geographical, environmental factors and 7 wild birds species distributions are contributing to the prediction. These results will not only provide a high-resolution map for the target allocation of surveillance and rapid detection of HPAI in wild birds but also will allow the improvement of the cost-effectiveness of risk-based surveillance of HPAI introduction into domestic poultry farms in South Korea. Acknowledgements This study was supported by the 2019-20 cooperative research grant from the veterinary epidemiology Division in the Animal and Plant Quarantine Agency (APQA) in South Korea and the fellowship of the graduate student support program (GSSP) at UC Davis

Vulnerability to cavitation curves describe the decrease in xylem hydraulic conductivity as xylem pressure declines. Several techniques for constructing vulnerability curves use centrifugal force to induce negative xylem pressure in stem or root segments. Centrifuge vulnerability curves constructed for long-vesselled species have been hypothesised to overestimate xylem vulnerability to cavitation due to increased vulnerability of vessels cut open at stem ends that extend to the middle or entirely through segments. We tested two key predictions of this hypothesis: (i) centrifugation induces greater embolism than dehydration in long-vesselled species, and (ii) the proportion of open vessels changes centrifuge vulnerability curves. Centrifuge and dehydration vulnerability curves were compared for a long- and short-vesselled species. The effect of open vessels was tested in four species by comparing centrifuge vulnerability curves for stems of two lengths. Centrifuge and dehydration vulnerability curves agreed well for the long- and short-vesselled species. Centrifuge vulnerability curves constructed using two stem lengths were similar. Also, the distribution of embolism along the length of centrifuged stems matched the theoretical pressure profile induced by centrifugation. We conclude that vulnerability to cavitation can be accurately characterised with vulnerability curves constructed using a centrifuge technique, even in long-vesselled species.

Risk Analysis of Three-storey Reinforced Concrete Moment-resisting Frame Structures Using Performance-based Wind Engineering

Present days and future coastal flooding is a key concern for Europe due to sea-level rise, storm surges and the importance of infrastructure at risk in low-lying areas. To support adaptation, information on future risks such as people exposed and economic damages are required. The CoCliCo project aims to contribute responding to this need by informing users about coastal risks via an open-source web platform. This platform aspires to improve decision-making on coastal risk management and adaptation in Europe. Here, we present the methods used in CoCliCo to compute risks and provide early results of risk calculations at the European scale. The results take the form of costs calculated for different flooding scenarios on different infrastructures (residential buildings, roads...) as a function of flood water levels. Flood water levels are determined for each infrastructure based on flood modelling. Then, using vulnerability curves, a damage associated with the type of infrastructure as a function of the water level is assigned. The damage ratio then is used to calculate the cost of flooding. Coastal risk can also be presented in social terms, by assessing the number of people potentially affected by flooding. The results are illustrated for two case studies: Dieppe and Hyère in France using detailed flood modelling and complemented by preliminary results for Europe. Our results are compared results from with previous studies. Finally, flood risk projections will be presented for several return periods at different scales and for different integrated scenarios considering climate change and associated socio-economic pathways as well as different adaptation options. These results will be made available on the CoCliCo platform.