Damage assessment of water supply networks due to seismic events using vulnerability functions

The paper presents commonly used methodology for assessing damage of water supply networks after a seismic event. The methodology relies on deriving and applying so-called vulnerability function. An overview of the existing vulnerability functions is given together with parameters, primarily related to soil deformations, which are influencing the assessment. Also, a critical review of the possibility of their use is given. Finally, by using two approaches, the estimated number of damages, with associated repair costs, is given for the water supply network of the City of Petrinja after the earthquake on December 29, 2020. With a total of 3 800 new damages, it is estimated that the total repair costs are around HRK 28 million. The accuracy of these estimates should be verified after detailed collection and processing of relevant data in accordance with the given guidelines.

Evaluating synthetic vulnerability functions in flood risk modelling – a case study from Switzerland

<p>The selection of vulnerability models has a significant influence on the overall uncertainty when quantifying flood loss. Several scholars reported a limited spatial transferability of available vulnerability functions to case studies other than those they have been empirically deduced from. As a result, there is a need for computation and validation of regionally specific vulnerability functions. As in many data-scarce regions this option is not feasible, the physical processes of flood impact model chains can be developed using synthetic vulnerability function and validating them by expert opinion. The function presented in our study is based on expert heuristics using a small sample of representative buildings. We applied the vulnerability function in a meso-scale river basin and evaluated the new function by comparing the resulting flood damage with the damage computed by other approaches, (1) an ensemble of vulnerability functions available from the literature, (2) an individual vulnerability function calibrated with region-specific data, and (3) the vulnerability function used in flood risk management by the Swiss government. The results show that synthetic information can be a valuable alternative for developing flood vulnerability models in regions without any data or only few data on flood loss.</p>

Calibration Of Regional Vulnerability Functions By Applying Earthquake Events Database

The paper describes the structure and content of the Information System database containing information on earthquake events, which is developed and supported within the framework of computer support for the EMERCOM of the Russian Federation. The database is assigned to provide analytical support for decision making in case of an emergency situation, including tools for mathematical simulation of hazardous excitation, the response of elements at risk to excitation and loss generation. The calibration procedure of the earthquake vulnerability functions for buildings and structures using the database with descriptions of events is presented. The calibrated functions of earthquake vulnerability for buildings of different types are applied to provide an acceptable accuracy of situational assessments for the case of a strong earthquake. The examples of earthquake damage estimations for the test site in Siberia showed that region-specific parameters in the vulnerability functions yield more reliable results to estimate possible damage and losses due to a large earthquake. For Irkutsk City, the estimates of the numbers of heavily damaged and completely collapsed buildings obtained when using different sets of parameters for vulnerability functions differ by 30%. Such difference in damage estimates can significantly affect the plans for rescue and recovery operations. The conclusion is made about the advantage of the calibrated functions application for near real-time damage and loss assessment due to strong earthquakes in order to ensure population safety and territory sustainable development.

Typhoon Vulnerability Analysis in South Korea Utilizing Damage Record of Typhoon Maemi

The purpose of this research is to identify the indicators of typhoon damage and develop a metric for typhoon vulnerability functions employing the losses associated with Typhoon Maemi. Typhoons cause significant financial damages worldwide every year. Federal and local governments, insurance companies, and construction companies strive to develop typhoon risk assessment models and use them to quantify the risks so that they can avoid, mitigate, or transfer the financial risks. Therefore, typhoon risk assessment modeling is becoming increasingly important, and in order to achieve a sophisticated evaluation, it is also important to reflect more specified and local vulnerabilities. Although several previous studies on economic loss associated with natural catastrophe have identified essential risk indicators, there has been a shortage of more specific research studies focusing on the correlation between vulnerability and economic loss caused by typhoons. In order to fill this gap, this study collected and analyzed the actual loss record of Typhoon Maemi collected and accumulated by a major insurance company in Korea. In order to create the vulnerability functions and to identify the natural hazard indicators and basic building information indicators, information from the insurance record was used in the analysis. The results and metric of this research provide a pragmatic approach that helps create vulnerability functions for abovementioned sectors and like estimating local vulnerabilities and predicting and coping with the possible damage and loss from typhoons.

Patterns in US flood vulnerability revealed from flood insurance "big data"

<p>Vulnerability functions are applied in flood risk models to calculate the losses incurred when a flood interacts with the built environment. Typically, these take the form of relative depth–damage relationships: flood depths at the location of a particular asset translate to a damage expressed as a certain percentage of its value. Vulnerability functions are a core component of risk and insurance industry catastrophe (CAT) models, permitting physical models of flood inundation under different scenarios (e.g. certain probabilities) to be translated to more tangible and useful estimates of loss. Much attention is devoted to the physical hazard component of flood risk models, but the final vulnerability component has historically received less attention — despite quantifications of risk being highly sensitive to these uncertain depth–damage functions. For the case of US flood risk models, ‘off-the-shelf’ functions from the US Army Corps of Engineers (USACE) are commonly used. In an analysis of roughly 2 million flood claims under the US National Flood Insurance Programme (NFIP), we find these ubiquitous USACE functions are not reflective of real damages at specified flood depths experienced by policy holders of the NFIP. Particularly for smaller flood depths (<1m), the majority of structural damages are of <10% of the building value compared to the 30–50% stipulated by the USACE functions. A deterministic relationship between depth and damage is shown to be invalid, with the claims data indicating damages at a certain depth form a beta distribution. Most reported damages are either <10% or >90% of building values, with the proportion of >90% damages increasing with water depth. The NFIP data also reveal that newer buildings tend to be more resilient (lower damages for a given depth), surface water flooding to be more damaging than fluvial flooding for a given depth, vulnerability to vary dramatically across space, and even the concept of a relative damage to be untenable in its application to expensive properties (e.g. even for depths >1m, properties worth >$250k rarely experience losses >20% of their value). The findings of this study have significant implications for developers of flood risk models, suggesting current estimates of US flood risk (in $ terms) may be substantial over-estimates.</p>

Development of a global seismic risk model

Since 2015, the Global Earthquake Model (GEM) Foundation and its partners have been supporting regional programs and bilateral collaborations to develop an open global earthquake risk model. These efforts led to the development of a repository of probabilistic seismic hazard models, a global exposure dataset comprising structural and occupancy information regarding the residential, commercial and industrial buildings, and a comprehensive set of fragility and vulnerability functions for the most common building classes. These components were used to estimate probabilistic earthquake risk globally using the OpenQuake-engine, an open-source software for seismic hazard and risk analysis. This model allows estimating a number of risk metrics such as annualized average losses or aggregated losses for particular return periods, which are fundamental to the development and implementation of earthquake risk mitigation measures.