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Abstract/Summary
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<jats:p>Abstract. Different risk management activities, such as land-use planning, preparedness, and emergency response, utilize scenarios of earthquake events. A systematic selection of such scenarios should aim at finding those that are representative of a certain severity, which can be measured by consequences to the exposed assets. For this reason, defining a representative scenario as the most likely one leading to a loss with a specific return period, e.g., the 100-year loss, has been proposed. We adopt this definition and develop enhanced algorithms for determining such scenarios for multiple return periods. With this approach, we identify representative earthquake scenarios for the return periods of 50, 100, 500, and 1000 years in the Chilean communes of Valparaíso and Viña del Mar, based on a synthetic earthquake catalog of 20 000 scenarios on the subduction zone with a magnitude of Mw≥5.0. We separately consider the residential-building stock and the electrical-power network and identify and compare earthquake scenarios that are representative of these systems. Because the representative earthquake scenarios are defined in terms of the annual loss exceedance rates, they vary in function of the exposed system. The identified representative scenarios for the building stock have epicenters located not further than 30 km from the two communes, with magnitudes ranging between 6.0 and 7.0. The epicenter locations of the earthquake scenarios representative of the electrical-power network are more spread out but not further than 100 km away from the two communes, with magnitudes ranging between 7.0 and 9.0. For risk management activities, we recommend considering the identified scenarios together with historical events.
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1000
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Hinweis
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DeepGreen-ID: de9a867802db4cab9b1085ca4a5991c5 ; metadata provieded by: DeepGreen (https://www.oa-deepgreen.de/api/v1/), LIVIVO search scope life sciences (http://z3950.zbmed.de:6210/livivo), Crossref Unified Resource API (https://api.crossref.org/swagger-ui/index.html), to.science.api (https://frl.publisso.de/), ZDB JSON-API (beta) (https://zeitschriftendatenbank.de/api/), lobid - Dateninfrastruktur für Bibliotheken (https://lobid.org/resources/search)
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