Articles | Volume 26, issue 19
https://doi.org/10.5194/hess-26-5015-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-26-5015-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Review article
| 
11 Oct 2022
Review article |
| 11 Oct 2022
| 11 Oct 2022
Three hypotheses on changing river flood hazards
Günter Blöschl
CORRESPONDING AUTHOR
Institute of Hydraulic Engineering and Water Resources Management,
Vienna University of Technology, Karlsplatz 13/223, 1040 Vienna, Austria
Invited contribution by Günter Blöschl, recipient of the EGU Alfred Wegener Medal 2022.
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30 citations as recorded by crossref.
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- The impacts of rainfall and soil moisture to flood hazards in a humid mountainous catchment: a modeling investigation T. Yu et al. 10.3389/feart.2023.1285766
- HESS Opinions: The sword of Damocles of the impossible flood A. Montanari et al. 10.5194/hess-28-2603-2024
- Identifying changes in flood characteristics and their causes from an event-based perspective in the Central Taihu Basin S. Luo et al. 10.1016/j.scitotenv.2023.167131
- Abflusstrends in Österreichs Fließgewässern 1977–2020 G. Laaha et al. 10.1007/s00506-024-01106-8
- Global river water quality under climate change and hydroclimatic extremes M. van Vliet et al. 10.1038/s43017-023-00472-3
- A tracer‐aided 2D numerical framework to define fluvial and pluvial hazard mapping P. Perrini et al. 10.1111/jfr3.13039
- Palynological approaches to forest restoration in Southeast Asia: Challenges and opportunities for Thailand—A systematic review T. Sattraburut et al. 10.1016/j.tfp.2024.100714
- Effects of forest disturbance on water yield and peak flow in low‐relief glaciated catchments assessed with Bayesian parameter estimation Z. McEachran et al. 10.1002/hyp.14956
- Mega Forest Fires Intensify Flood Magnitudes in Southeast Australia Z. Xu et al. 10.1029/2023GL103812
- Hyper-resolution flood hazard mapping at the national scale G. Blöschl et al. 10.5194/nhess-24-2071-2024
- A Simple Model of Flood Peak Attenuation R. Paiva & S. Lima 10.1029/2023WR034692
- Study of flooding hazards in highly urbanized area based on a coupled one- and two-dimensional hydrological-hydrodynamic model W. Yin et al. 10.1016/j.dwt.2024.100933
- Normalization of Suak Ujong Kalak estuary as a flood reduction effort for Meulaboh city M. Safriani et al. 10.1088/1742-6596/2916/1/012007
- Use of Soil Infiltration Capacity and Stream Flow Velocity to Estimate Physical Flood Vulnerability under Land-Use Change Scenarios Y. Hernández-Atencia et al. 10.3390/w15061214
- On the Performance of Sentinel-3 Altimetry over High Mountain and Cascade Reservoirs Basins: Case of the Lancang and Nu River Basins Y. Cheng et al. 10.3390/rs15071769
- Drivers, changes, and impacts of hydrological extremes in India: A review V. Mishra et al. 10.1002/wat2.1742
- Why structural solutions for flood control should be adapted to climate change? M. Hosseinipoor et al. 10.1007/s11069-024-06969-4
- Future Changes in Hydro-Climatic Extremes across Vietnam: Evidence from a Semi-Distributed Hydrological Model Forced by Downscaled CMIP6 Climate Data H. Do et al. 10.3390/w16050674
- Quantifying the relative contributions of rainfall and antecedent soil moisture to flood generation: Analysis of 963 Iranian catchments A. Jahanshahi & M. Booij 10.1016/j.jaridenv.2025.105328
- Climate impact on flood changes – an Austrian-Ukrainian comparison S. Snizhko et al. 10.2478/johh-2023-0017
- Assessing multi-source random forest classification and robustness of predictor variables in flooded areas mapping C. Albertini et al. 10.1016/j.rsase.2024.101239
- Large-scale flood mapping using Sentinel-1 and Sentinel-2 imagery: Spatio-temporal analysis of the 23·7 Haihe basin-wide extreme flood L. Lan & X. Wang 10.1016/j.jhydrol.2025.132777
- Unprecedented April-May 2024 rainfall in South Brazil sets new record W. Collischonn et al. 10.1590/2318-0331.292420240088
- A hydrologic similarity-based parameters dynamic matching framework: Application to enhance the real-time flood forecasting H. Wu et al. 10.1016/j.scitotenv.2023.167767
- Advancing real-time error correction of flood forecasting based on the hydrologic similarity theory and machine learning techniques P. Shi et al. 10.1016/j.envres.2024.118533
- Advancing river flood forecasting with a collaborative integrated modeling method Y. He et al. 10.1016/j.jenvman.2024.123677
Latest update: 21 Feb 2025
Short summary
There is serious concern that river floods are increasing. Starting from explanations discussed in public, the article addresses three hypotheses: land-use change, hydraulic structures, and climate change increase floods. This review finds that all three changes have the potential to not only increase floods, but also to reduce them. 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.
There is serious concern that river floods are increasing. Starting from explanations discussed...
