Impact Forecasting to Support Emergency Management of Natural Hazards

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Version: Final published version
License: CC BY 4.0
Serval ID
serval:BIB_30D298CE99AD
Type
Article: article from journal or magazin.
Collection
Publications
Title
Impact Forecasting to Support Emergency Management of Natural Hazards
Journal
Reviews of Geophysics
Author(s)
Merz Bruno, Kuhlicke Christian, Kunz Michael, Pittore Massimiliano, Babeyko Andrey, Bresch David N., Domeisen Daniela I. V., Feser Frauke, Koszalka Inga, Kreibich Heidi, Pantillon Florian, Parolai Stefano, Pinto Joaquim G., Punge Heinz Jürgen, Rivalta Eleonora, Schröter Kai, Strehlow Karen, Weisse Ralf, Wurpts Andreas
ISSN
8755-1209
1944-9208
Publication state
Published
Issued date
12/2020
Peer-reviewed
Oui
Volume
58
Number
4
Language
english
Abstract
Forecasting and early warning systems are important investments to protect lives, properties, and livelihood. While early warning systems are frequently used to predict the magnitude, location, and timing of potentially damaging events, these systems rarely provide impact estimates, such as the expected amount and distribution of physical damage, human consequences, disruption of services, or financial loss. Complementing early warning systems with impact forecasts has a twofold advantage: It would provide decision makers with richer information to take informed decisions about emergency measures and focus the attention of different disciplines on a common target. This would allow capitalizing on synergies between different disciplines and boosting the development of multihazard early warning systems. This review discusses the state of the art in impact forecasting for a wide range of natural hazards. We outline the added value of impact-based warnings compared to hazard forecasting for the emergency phase, indicate challenges and pitfalls, and synthesize the review results across hazard types most relevant for Europe.
Keywords
impact forecasting, natural hazards, early warning
Web of science
Open Access
Yes
Funding(s)
Swiss National Science Foundation / 170523
Create date
08/03/2022 14:13
Last modification date
11/07/2024 9:32
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