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Current CEDIM-Projects

Rapid Earthquake Impact Modelling

Earthquakes are felt every daily all around the globe. In some cases, damaging effects cannot be avoided and it is difficult, especially during bigger disasters, to estimate the actual impact. But first estimates of the earthquake intensity are important to estimate potential losses and the number of affected population. For this task, a system for disaster cartography has been developed to provide potential disaster impact maps within minutes after an event occurred. Such data can then be used e.g. for loss estimates or mitigation measures.
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 Effects of Extreme Events on EMI-Systems



Facing the increasing probability of extreme events and their tremendous possible impacts on societies, it is inevitable to investigate their impacts on current and future energy, mobility and information systems. This is also more than valid, facing the aspect that through the network character of those systems, extreme events lead to cascading effects along its system-parts. That is why, natural disasters can have also severe impacts far away from their place of origin. The current globalization and strong interconnectedness around the world is also increasing this aspect. To assess the indirect impacts of natural events, two subprojects were implemented, dealing with supply chain vulnerability under consideration of global interconnectedness and changed consumer mobility requests in the aftermath of a disaster.
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In case of natural disasters, modern sensor networks provide high quality data. These measurements, however, are only mapping disjoint values from their respective locations for a limited amount of parameters. Using observations of witnesses represents one approach to enhance measured values from sensors ("humans as sensors"). These observations are increasingly disseminated via social media platforms such as Facebook, Twitter, Youtube and Flickr. Every user of these social networks can be regarded as a mobile, virtual sensor ("social sensor"). These "social sensors" offer several advantages over common sensors, e.g. high mobility, high versatility of captured parameters as well as rapid distribution of information. Moreover, the amount of data offered by social media platforms is quite extensive. On the other hand these data are often subjectively influenced by the observer and of varying quality and quantity. Methods and techniques, which identify appropriate information, need to be developed to enable the usage of social media data for applications in disaster management. The project's goal is to gather data from social media platforms that can be applied for rapid damage estimation in combination with common sensors.
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Energy risks toward 2025: Disaster risk and resilience assessment of renewable and traditional systems


Energy systems are key to the recovery of a location post-disaster. Connectivity to internet, telephone systems, heat, cool, cooking, and many other processes are energy-system driven. Evacuation, business downtime and direct losses are all associated with energy systems. A change to the system, whether from natural disaster, terrorism or other effects can cause major delays and follow-on consequences for social and economic systems as seen through Tohoku 2011. With the world becoming increasingly reliant on electricity through use of the internet, a potential major outage during a disaster is a risk that will become more and more important to countries in the future.
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Forensic Disaster Analysis


In late 2011, CEDIM embarked on a new style of disaster research known as Forensic Disaster Analysis. In the new research program CEDIM Forensic Disaster Analysis (CEDIM FDA), CEDIM researchers will analyse disasters and their impact in near real-time. The core of CEDIM’s new style of analysis is to examine disasters in an interdisciplinary manner with a focus on the complex interactions between
(1) the natural hazard,
(2) the technical installations, facilities, and infrastructures, and
(3) the societal structures, institutions and capacities.

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Global Tsunami Risk Modeling

Since the devastating events of Sumatra in 2004 and Japan in 2011, tsunamis returned into the global memory and perception of natural disasters. Quantification of tsunami risk is difficult and many-faceted. During the last 20 years, various, mostly local models have been developed for the assessment of tsunami hazards and risk. But most of them show massive differences in terms of methodology, data assessment and interpretation. Thus, this project targets to develop a globally uniform and comparative tsunami risk assessment model.
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Indicator system for assessing the hazard to infrastructure against extreme flooding

As a consequence of climate change, occurrence of heavy rainfalls increases, leading to inevitable flooding. Considering the devastating effects of floods, their assessment is essential in order to mitigate the hazard. The main goal of the project is to develop the relevant indicators for large scale hazard and risk analyses based on a deepened knowledge of the dynamic processes and impacts of extreme events.
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Resilience of urban infrastructures in the course of time

The welfare of modern societies highly depends on the functioning of Critical Infrastructures (CIs) like power and water supply, transport and distribution systems. Thus it is desirable to gain a profound understanding on how disruptions of CIs for example caused by extreme weather events or terrorist attacks affect the vulnerability of a city - today and in the future. Detecting hidden or a priori underestimated interdependencies could help to identify enhanced strategies for crisis management and design patterns concerning robust future CI developments. For this purpose an Agent Based Modelling (ABM) approach, where CIs or CI components are modelled as agents, seems to be most promising. 
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Loss Assessment for Earthquakes

Based on the huge flow of information via internet (focussing on earthquake-report.com) and building on the largest earthquake loss database available (CATDAT) and using indicator based evaluation methods, a structured picture of losses for earthquakes will emerge. They will be compared with other events based on tectonic, regional, and socio-economic characteristics such as Human Development Index (HDI) and other relevant parameters.
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Vulnerability and resilience of the critical infrastructure as exemplified by Chile


Natural hazards, such as earthquakes and floods, threaten road infrastructure and thus the society depending on them. On the one hand, the CEDIM-funded joint research project KRITIS investigates the evacuation behaviour of an affected society using qualitative and quantitative empirical social research. Therefore, specific local data of selected study areas in central Chile is collected using standardised questionnaires, expert interviews and focus group interviews. On the other hand, a generic, multi-scale concept is developed to analyse the vulnerability of critical road infrastructure. This concept follows a modular approach and evaluates the accessibility of emergency facilities by calculating an index as its basic module. The socio-scientific parameters gained in the field research are integrated with additional modules to the regional conditions in more detail.
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Early Warning of Hazardous Weather

Feasible and routinely available techniques will be used to give an advance or real-time estimation of possible damage (amount of loss) before and during a winter storm event over Europe. With accurate station data (wind gusts) at representative locations weighted or unweighted storm indices will be calculated for past storm events. All this calculations eventually lead into a kind of “storm-MOS” (Model Output Statistics) that describes a storm event with reasonable certainty and precision and that allows to evolve a storm damage function. Once the storm occurs, the wind measurements at representative locations on the one hand and the model predicted wind gusts on the other hand provide the storm indices and the appropriate damage index. The data of all past and future storm events will be fed into a database and the parameters are: name, date, regions affected, model data, measurement data and loss data.
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Willis Hail Hazard Assessment

A stochastic model for the frequency, extent and severity of hail events has been developed for Europe, and a version covering the Australian continent is currently under development. Research at KIT is focusing on the hazard component of the risk model. European METEOSAT Second Generation (MSG) and Japanese MT-SAT satellite data is used to identify major convective storms associated with hail. The method leads to unique, spatially homogeneous event data set covering entire continents for time periods of more than a decade. Stochastic modelling of the frequency, length, width, and severity of hail events then allows to generate a large event set for hailstorms expected to occur in several thousand years. This event set can in turn be combined with insurance portfolios in order to estimate loss events for certain return periods. The aim of the project is also to improve the understanding of the relationship between the strength of convection and the formation of hail, and more generally the prevailing atmospheric conditions at the formation of hail events. Several other data sources including climate model data are considered in this context.
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