European Drought Risk Atlas

Rossi, Lauro, Wens, Marthe, de Moel, Hans, Cotti, Davide, Sabino Siemons, Anne-Sophie, Toreti, Andrea, Maetens, Willem, Masante, Dario, Van Loon, Anne, Hagenlocher, Michael, Rudari, Roberto, Naumann, Gustavo, Meroni, Michelle, Avanzi, Francesco, Isabellon, Michel and Barbosa, Paulo (2023). European Drought Risk Atlas. European Commission.

Document type:

  • Sub-type Research report
    Author Rossi, Lauro
    Wens, Marthe
    de Moel, Hans
    Cotti, Davide
    Sabino Siemons, Anne-Sophie
    Toreti, Andrea
    Maetens, Willem
    Masante, Dario
    Van Loon, Anne
    Hagenlocher, Michael
    Rudari, Roberto
    Naumann, Gustavo
    Meroni, Michelle
    Avanzi, Francesco
    Isabellon, Michel
    Barbosa, Paulo
    Title European Drought Risk Atlas
    Publication Date 2023-10-10
    Place of Publication Luxembourg
    Publisher European Commission
    Pages 108
    Language eng
    Abstract English In recent years, droughts have had substantial impacts on nearly all regions of the EU, affecting several critical systems such as agriculture, water supply, energy, river transport, and ecosystems. These impacts are projected to further increase due to climate change. While some of the drivers of drought risk are well known for some systems and regions, drought risks and impacts remain hard to assess and quantify. The European Drought Risk Atlas is a step towards impact-based drought assessment and can support the development and implementation of drought management and adaptation policies and actions. It characterises how drought hazard, exposure and vulnerability interact and affect different but interconnected systems: agriculture, public water supply, energy, riverine transport, freshwater and terrestrial ecosystems. The Atlas presents both a conceptual and quantitative approach to drought risk for these systems. The conceptual drought risk models (impact chains) are the result of a review of the literature in Europe and consultations with experts to construct visualisations of the most relevant drivers and how they interact to determine risk and impacts. The quantitative estimate of drought risk is based on machine learning techniques and maps drought risk at the sub-national level in terms of annual average loss and probable maximum losses at specific return periods, both for present climate conditions, and for projections under different levels of global warming (+1.5 °C, +2 °C, +3 °C).
    Keyword Impact chains
    Conceptual models
    Future risks
    Copyright Holder European Union
    Copyright Year 2023
    Copyright type Creative commons
    ISBN 9789268080
    DOI 10.2760/33211
  • Versions
    Version Filter Type
  • Citation counts
    Google Scholar Search Google Scholar
    Access Statistics: 162 Abstract Views  -  Detailed Statistics
    Created: Fri, 13 Oct 2023, 01:00:23 JST by Aarti Basnyat on behalf of UNU EHS