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  • AGU (American Geophysical Union)  (1)
  • Copernicus Publications  (1)
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  • 1
    Publication Date: 2023-02-08
    Description: 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 two‐fold 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 multi‐hazard 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. Plain language summary Forecasting and early warning systems are important investments to protect lives, properties and livelihood. While such systems are frequently used to predict the magnitude, location and timing of potentially damaging events, they rarely provide impact estimates, such as the expected physical damage, human consequences, disruption of services or financial loss. Extending hazard forecast systems to include impact estimates promises many benefits for the emergency phase, for instance, for organising evacuations. We review and compare the state‐of‐the‐art of impact forcasting across a wide range of natural hazards, and outline opportunities and key challenges for research and development of impact forecasting.
    Type: Article , PeerReviewed , info:eu-repo/semantics/article
    Format: text
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  • 2
    Publication Date: 2024-04-22
    Description: As the adverse impacts of hydrological extremes increase in many regions of the world, a better understanding of the drivers of changes in risk and impacts is essential for effective flood and drought risk management and climate adaptation. However, there is currently a lack of comprehensive, empirical data about the processes, interactions, and feedbacks in complex human-water systems leading to flood and drought impacts. Here we present a benchmark dataset containing socio-hydrological data of paired events, i.e. two floods or two droughts that occurred in the same area. The 45 paired events occurred in 42 different study areas and cover a wide range of socio-economic and hydro-climatic conditions. The dataset is unique in covering both floods and droughts, in the number of cases assessed and in the quantity of socio-hydrological data. The benchmark dataset comprises (1) detailed review-style reports about the events and key processes between the two events of a pair; (2) the key data table containing variables that assess the indicators which characterize management shortcomings, hazard, exposure, vulnerability, and impacts of all events; and (3) a table of the indicators of change that indicate the differences between the first and second event of a pair. The advantages of the dataset are that it enables comparative analyses across all the paired events based on the indicators of change and allows for detailed context- and location-specific assessments based on the extensive data and reports of the individual study areas. The dataset can be used by the scientific community for exploratory data analyses, e.g. focused on causal links between risk management; changes in hazard, exposure and vulnerability; and flood or drought impacts. The data can also be used for the development, calibration, and validation of socio-hydrological models. The dataset is available to the public through the GFZ Data Services (Kreibich et al., 2023, 10.5880/GFZ.4.4.2023.001).
    Repository Name: EPIC Alfred Wegener Institut
    Type: Article , isiRev
    Format: application/pdf
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