Articles | Volume 24, issue 6
https://doi.org/10.5194/nhess-24-2071-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/nhess-24-2071-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Hyper-resolution flood hazard mapping at the national scale
Günter Blöschl
CORRESPONDING AUTHOR
TU Wien, Institute of Hydraulic Engineering and Water Resources Management, Karlsplatz 13, 1040 Vienna, Austria
Andreas Buttinger-Kreuzhuber
TU Wien, Institute of Hydraulic Engineering and Water Resources Management, Karlsplatz 13, 1040 Vienna, Austria
VRVis Zentrum für Virtual Reality und Visualisierung Forschungs-GmbH, Donau-City-Strasse 11, 1220 Vienna, Austria
Daniel Cornel
VRVis Zentrum für Virtual Reality und Visualisierung Forschungs-GmbH, Donau-City-Strasse 11, 1220 Vienna, Austria
Julia Eisl
Ingenieurbüro Dipl.- Ing. Günter Humer GmbH – Ingenieurbüro für Kulturtechnik und Wasserwirtschaft, Geboltskirchen and Gmunden, Austria
Michael Hofer
Ingenieurbüro Dipl.- Ing. Günter Humer GmbH – Ingenieurbüro für Kulturtechnik und Wasserwirtschaft, Geboltskirchen and Gmunden, Austria
Markus Hollaus
TU Wien, Department of Geodesy and Geoinformation, Research Area Photogrammetry, Wiedner Hauptstraße 8-10, 1040 Vienna, Austria
Zsolt Horváth
TU Wien, Institute of Hydraulic Engineering and Water Resources Management, Karlsplatz 13, 1040 Vienna, Austria
VRVis Zentrum für Virtual Reality und Visualisierung Forschungs-GmbH, Donau-City-Strasse 11, 1220 Vienna, Austria
Jürgen Komma
TU Wien, Institute of Hydraulic Engineering and Water Resources Management, Karlsplatz 13, 1040 Vienna, Austria
Artem Konev
VRVis Zentrum für Virtual Reality und Visualisierung Forschungs-GmbH, Donau-City-Strasse 11, 1220 Vienna, Austria
Juraj Parajka
TU Wien, Institute of Hydraulic Engineering and Water Resources Management, Karlsplatz 13, 1040 Vienna, Austria
Norbert Pfeifer
TU Wien, Department of Geodesy and Geoinformation, Research Area Photogrammetry, Wiedner Hauptstraße 8-10, 1040 Vienna, Austria
Andreas Reithofer
Ingenieurbüro Dipl.- Ing. Günter Humer GmbH – Ingenieurbüro für Kulturtechnik und Wasserwirtschaft, Geboltskirchen and Gmunden, Austria
José Salinas
TU Wien, Institute of Hydraulic Engineering and Water Resources Management, Karlsplatz 13, 1040 Vienna, Austria
Moody's RMS, Inland Flood Model Development, 21 Mincing Lane, London, EC3R 7AG, UK
Peter Valent
TU Wien, Institute of Hydraulic Engineering and Water Resources Management, Karlsplatz 13, 1040 Vienna, Austria
Roman Výleta
STU Bratislava, Faculty of Civil Engineering, Department of Land and Water Resources Management, Radlinského 11, 810 05 Bratislava, Slovakia
Jürgen Waser
VRVis Zentrum für Virtual Reality und Visualisierung Forschungs-GmbH, Donau-City-Strasse 11, 1220 Vienna, Austria
Michael H. Wimmer
TU Wien, Department of Geodesy and Geoinformation, Research Area Photogrammetry, Wiedner Hauptstraße 8-10, 1040 Vienna, Austria
Heinz Stiefelmeyer
Federal Ministry of Agriculture, Forestry, Regions and Water Management, Stubenring 1, 1010 Vienna, Austria
Data sets
Flood peak data and discharge data eHYD https://ehyd.gv.at
Local flood hazard maps Amt der Tiroler Landesregierung https://data-tiris.opendata.arcgis.com/datasets/ueberflutungsflaechen-1
Model code and software
rtop package J. Skoien and D. Koffler https://r-forge.r-project.org/projects/rtop
Short summary
A methodology of regional flood hazard mapping is proposed, based on data in Austria, which combines automatic methods with manual interventions to maximise efficiency and to obtain estimation accuracy similar to that of local studies. Flood discharge records from 781 stations are used to estimate flood hazard patterns of a given return period at a resolution of 2 m over a total stream length of 38 000 km. The hazard maps are used for civil protection, risk awareness and insurance purposes.
A methodology of regional flood hazard mapping is proposed, based on data in Austria, which...
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