HOchwasserRisikozonierung Austria 3.0 (HORA 3.0)

Blöschl, Günter; Waser, Jürgen; Buttinger‐Kreuzhuber, Andreas; Cornel, Daniel; Eisl, Julia; Hofer, Michael; Hollaus, Markus; Horváth, Zsolt; Komma, Jürgen; Konev, Artem; Parajka, Juraj; Pfeifer, Norbert; Reithofer, Andreas; Salinas, José Luis; Valent, Peter; Viglione, Alberto; Wimmer, Michael; Stiefelmeyer, Heinz

doi:10.1007/s00506-022-00848-7

Cited by 3 publications

(1 citation statement)

References 21 publications

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“…Our web service provides detailed information about different risk factors for a whole country, involving data larger than 6 TB. The data basis is derived from the hora 3.0 project [BKWC*22, BWBK*22], where a high‐resolution digital twin of the whole of Austria with an area of about 84000 km 2 and a river network of 33880 km length was created for hydrodynamic simulations. In this project, four river flood scenarios have been simulated, from which we derive individual risk factors and visualize them via hora 3D.…”

Section: Introductionmentioning

confidence: 99%

HORA 3D: Personalized Flood Risk Visualization as an Interactive Web Service

Rauer‐Zechmeister,

Cornel,

Sadransky

et al. 2024

Computer Graphics Forum

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We propose an interactive web‐based application to inform the general public about personal flood risks. Flooding is the natural hazard affecting most people worldwide. Protection against flooding is not limited to mitigation measures, but also includes communicating its risks to affected individuals to raise awareness and preparedness for its adverse effects. Until now, this is mostly done with static and indiscriminate 2D maps of the water depth. These flood hazard maps can be difficult to interpret and the user has to derive a personal flood risk based on prior knowledge. In addition to the hazard, the flood risk has to consider the exposure of the own house and premises to high water depths and flow velocities as well as the vulnerability of particular parts. Our application is centered around an interactive personalized visualization to raise awareness of these risk factors for an object of interest. We carefully extract and show only the relevant information from large precomputed flood simulation and geospatial data to keep the visualization simple and comprehensible. To achieve this goal, we extend various existing approaches and combine them with new real‐time visualization and interaction techniques in 3D. A new view‐dependent focus+context design guides user attention and supports an intuitive interpretation of the visualization to perform predefined exploration tasks. HORA 3D enables users to individually inform themselves about their flood risks. We evaluated the user experience through a broad online survey with 87 participants of different levels of expertise, who rated the helpfulness of the application with 4.7 out of 5 on average.

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Section: Introductionmentioning

confidence: 99%

HORA 3D: Personalized Flood Risk Visualization as an Interactive Web Service

Rauer‐Zechmeister,

Cornel,

Sadransky

et al. 2024

Computer Graphics Forum

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Vorhersage von hydrologischen Abflusskennwerten in unbeobachteten Einzugsgebieten mit Machine Learning

Klingler

Feigl

Borgwardt

et al. 2022

Österr Wasser- und Abfallw

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ZusammenfassungIm Rahmen dieser Arbeit wurden Abflusskennwerte für Hochwasser (MJHQ), Mittelwasser (MQ) sowie Niederwasser (MJNQ, MJNQ7, Q95, Q98) für alle topografischen Einzugsgebiete der österreichischen Oberflächenwasserkörper inklusive der ausländischen hydrologischen Oberlieger-Regionen vorhergesagt. Die Regionalisierung der Abflusskennwerte wurde mit dem Machine-Learning-Modell XGBoost durchgeführt. Zentrale Grundlage für das Training von XGBoost war der LamaH-Datensatz, welcher für 859 beobachtete Einzugsgebiete in Zentraleuropa über 70 aggregierte Einzugsgebietseigenschaften und 15 meteorologische Zeitreihen umfasst. Anthropogene Beeinflussungen wie z. B. Jahresspeicher oder Überleitungen wurden durch zusätzlich erstellte Attribute bei der Vorhersage berücksichtigt. Die Testergebnisse haben gezeigt, dass bei der Vorhersage der Abflusskennwerte in unbeobachteten Einzugsgebieten mit einer Abweichung von rund 20 % zu rechnen ist, wobei diese Schätzung auch stark anthropogen beeinflusste Gebiete beinhaltet. Darüber hinaus wurden auch 90-%-Konfidenzintervalle der Vorhersagen mit einem Quantile-Random-Forest-Modell geschätzt und klassifiziert. Die Ergebnisse werden der Öffentlichkeit in Form von Shapefiles unter https://doi.org/10.5281/zenodo.6523372 kostenlos zur Verfügung gestellt.

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Three hypotheses on changing river flood hazards

Blöschl¹

2022

Hydrol. Earth Syst. Sci.

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Abstract. There is serious concern that the hazard, or probability, of river floods is increasing over time. Starting from narratives that are sometimes discussed in public, the article addresses three hypotheses. The first suggests that land-use changes, such as deforestation, urbanisation and soil compaction by agriculture, increase flood hazards. This review finds that land-use effects on floods are particularly pronounced in small catchments since soil permeability plays an important role in infiltration at this scale. For regional floods, and the most extreme events, land use is usually not the most important control, since areas of soil saturation play a greater role in runoff generation, which are less dependent on soil permeability. The second hypothesis suggests that hydraulic interventions and structures, such as river training, levees and dams, increase flood hazards. This review finds that hydraulic structures have the greatest impact on events of medium magnitude, associated with return periods of tens to hundreds of years, and that their effects are usually local. Long-term interactions between humans and floods must be taken into account when predicting future flood hazards. The third hypothesis suggests that climate change increases flood hazard. This review finds that, in small catchments of a few hectares, flood hazards may increase due to convective storms. In large catchments, where regional floods occur, changes are not necessarily directly related to precipitation, nor are they directly related to rising air temperatures, but are determined by the seasonal interplay of soil moisture, snow and extreme precipitation via runoff generation. Increases and decreases in flood hazards have been observed worldwide. It is concluded that significant progress has been made in recent years in understanding the role of land use, hydraulic structures and climate in changing river flood hazards. It is crucial to consider all three factors of change in flood risk management and communicate them to the general public in a nuanced way.

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HOchwasserRisikozonierung Austria 3.0 (HORA 3.0)

Cited by 3 publications

References 21 publications

HORA 3D: Personalized Flood Risk Visualization as an Interactive Web Service

HORA 3D: Personalized Flood Risk Visualization as an Interactive Web Service

Vorhersage von hydrologischen Abflusskennwerten in unbeobachteten Einzugsgebieten mit Machine Learning

Three hypotheses on changing river flood hazards

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