Articles | Volume 14, issue 6
https://doi.org/10.5194/nhess-14-1579-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/nhess-14-1579-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
23 Jun 2014
Research article |
| 23 Jun 2014
Projecting flood hazard under climate change: an alternative approach to model chains
J. M. Delgado
University of Potsdam, Institute of Earth and Environmental Science, Karl-Liebknecht-Str. 24–25, 14476 Potsdam-Golm, Germany
GFZ German Research Centre for Geosciences, Section 5.4, Hydrology, Telegrafenberg, 14473 Potsdam, Germany
GFZ German Research Centre for Geosciences, Section 5.4, Hydrology, Telegrafenberg, 14473 Potsdam, Germany
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Cited
31 citations as recorded by crossref.
- Can PDSI inform extreme precipitation?: An exploration with a 500 year long paleoclimate reconstruction over the U.S. S. Steinschneider et al. https://doi.org/10.1002/2016WR018712
- Comparing Flood Projection Approaches Across Hydro‐Climatologically Diverse United States River Basins K. Schlef et al. https://doi.org/10.1029/2019WR025861
- Floods and climate: emerging perspectives for flood risk assessment and management B. Merz et al. https://doi.org/10.5194/nhess-14-1921-2014
- Comparison of time trend- and precipitation-informed models for assessing design discharges in variable climate M. Šraj & N. Bezak https://doi.org/10.1016/j.jhydrol.2020.125374
- A deep learning synthetic likelihood approximation of a non-stationary spatial model for extreme streamflow forecasting R. Majumder & B. Reich https://doi.org/10.1016/j.spasta.2023.100755
- Using Climate-Flood Links and CMIP5 Projections to Assess Flood Design Levels Under Climate Change Scenarios: A Case Study in Southern Brazil A. Silva & M. Portela https://doi.org/10.1007/s11269-018-2058-6
- A new flood type classification method for use in climate change impact studies T. Turkington et al. https://doi.org/10.1016/j.wace.2016.10.001
- Non Stationary Analysis of Extreme Events A. Cancelliere https://doi.org/10.1007/s11269-017-1724-4
- Season-Ahead Flood Quantile Forecasting with Climate-Informed Models for Indian Catchments A. Ganapathy et al. https://doi.org/10.1061/JHYEFF.HEENG-6750
- A risk-based analytical framework for quantifying non-stationary flood risks and establishing infrastructure design standards in a changing environment K. Byun & A. Hamlet https://doi.org/10.1016/j.jhydrol.2020.124575
- Identifying drivers of streamflow extremes in West Africa to inform a nonstationary prediction model K. Chun et al. https://doi.org/10.1016/j.wace.2021.100346
- Urgency and importance of local-scale modeling tools to support climate adaptation and sustainable development H. Ouyang et al. https://doi.org/10.1007/s11783-025-2091-7
- Hydroclimatic scenario generation using two-stage stochastic simulation framework C. Awasthi et al. https://doi.org/10.1016/j.advwatres.2024.104739
- Customized sea‐surface temperature indicators linking to streamflow at different timescales A. Ganapathy & A. Agarwal https://doi.org/10.1002/joc.7853
- Governance challenges of flood-prone delta cities: Integrating flood risk management and climate change in spatial planning M. Francesch-Huidobro et al. https://doi.org/10.1016/j.progress.2015.11.001
- Multidecadal variability of the Tonle Sap Lake flood pulse regime A. Chen et al. https://doi.org/10.1002/hyp.14327
- Auswirkungen der Klimaänderung auf Österreichs Wasserwirtschaft – ein aktualisierter Statusbericht G. Blöschl et al. https://doi.org/10.1007/s00506-018-0498-0
- Attribution of regional flood changes based on scaling fingerprints A. Viglione et al. https://doi.org/10.1002/2016WR019036
- Identifying hotspots of hydro-hazards under global change: A worldwide review L. Beevers et al. https://doi.org/10.3389/frwa.2022.879536
- Future high- and low-flow estimations for Central Vietnam: a hydro-meteorological modelling chain approach Q. Dang et al. https://doi.org/10.1080/02626667.2017.1353696
- Robust Adaptation to Multiscale Climate Variability J. Doss‐Gollin et al. https://doi.org/10.1029/2019EF001154
- Assessing flood hazard changes using climate model forcing D. Callaghan & M. Hughes https://doi.org/10.5194/nhess-22-2459-2022
- Understanding flood regime changes in Europe: a state-of-the-art assessment J. Hall et al. https://doi.org/10.5194/hess-18-2735-2014
- Design considerations for riverine floods in a changing climate – A review B. François et al. https://doi.org/10.1016/j.jhydrol.2019.04.068
- Hydrological extremes across the Commonwealth of Massachusetts in a changing climate R. Siddique et al. https://doi.org/10.1016/j.ejrh.2020.100733
- Predicting nonstationary flood frequencies: Evidence supports an updated stationarity thesis in the United States A. Luke et al. https://doi.org/10.1002/2016WR019676
- Non-stationary frequency analysis of extreme precipitation in South Korea using peaks-over-threshold and annual maxima S. Wi et al. https://doi.org/10.1007/s00477-015-1180-8
- Climate influences on flood probabilities across Europe E. Steirou et al. https://doi.org/10.5194/hess-23-1305-2019
- Updating urban design floods for changes in central tendency and variability using regression J. Hecht & R. Vogel https://doi.org/10.1016/j.advwatres.2019.103484
- Changing Seasonality of Annual Maximum Floods over the Conterminous US: Potential Drivers and Regional Synthesis B. Basu et al. https://doi.org/10.1061/JHYEFF.HEENG-5768
- The influence of non-stationarity in extreme hydrological events on flood frequency estimation M. Šraj et al. https://doi.org/10.1515/johh-2016-0032
31 citations as recorded by crossref.
- Can PDSI inform extreme precipitation?: An exploration with a 500 year long paleoclimate reconstruction over the U.S. S. Steinschneider et al. https://doi.org/10.1002/2016WR018712
- Comparing Flood Projection Approaches Across Hydro‐Climatologically Diverse United States River Basins K. Schlef et al. https://doi.org/10.1029/2019WR025861
- Floods and climate: emerging perspectives for flood risk assessment and management B. Merz et al. https://doi.org/10.5194/nhess-14-1921-2014
- Comparison of time trend- and precipitation-informed models for assessing design discharges in variable climate M. Šraj & N. Bezak https://doi.org/10.1016/j.jhydrol.2020.125374
- A deep learning synthetic likelihood approximation of a non-stationary spatial model for extreme streamflow forecasting R. Majumder & B. Reich https://doi.org/10.1016/j.spasta.2023.100755
- Using Climate-Flood Links and CMIP5 Projections to Assess Flood Design Levels Under Climate Change Scenarios: A Case Study in Southern Brazil A. Silva & M. Portela https://doi.org/10.1007/s11269-018-2058-6
- A new flood type classification method for use in climate change impact studies T. Turkington et al. https://doi.org/10.1016/j.wace.2016.10.001
- Non Stationary Analysis of Extreme Events A. Cancelliere https://doi.org/10.1007/s11269-017-1724-4
- Season-Ahead Flood Quantile Forecasting with Climate-Informed Models for Indian Catchments A. Ganapathy et al. https://doi.org/10.1061/JHYEFF.HEENG-6750
- A risk-based analytical framework for quantifying non-stationary flood risks and establishing infrastructure design standards in a changing environment K. Byun & A. Hamlet https://doi.org/10.1016/j.jhydrol.2020.124575
- Identifying drivers of streamflow extremes in West Africa to inform a nonstationary prediction model K. Chun et al. https://doi.org/10.1016/j.wace.2021.100346
- Urgency and importance of local-scale modeling tools to support climate adaptation and sustainable development H. Ouyang et al. https://doi.org/10.1007/s11783-025-2091-7
- Hydroclimatic scenario generation using two-stage stochastic simulation framework C. Awasthi et al. https://doi.org/10.1016/j.advwatres.2024.104739
- Customized sea‐surface temperature indicators linking to streamflow at different timescales A. Ganapathy & A. Agarwal https://doi.org/10.1002/joc.7853
- Governance challenges of flood-prone delta cities: Integrating flood risk management and climate change in spatial planning M. Francesch-Huidobro et al. https://doi.org/10.1016/j.progress.2015.11.001
- Multidecadal variability of the Tonle Sap Lake flood pulse regime A. Chen et al. https://doi.org/10.1002/hyp.14327
- Auswirkungen der Klimaänderung auf Österreichs Wasserwirtschaft – ein aktualisierter Statusbericht G. Blöschl et al. https://doi.org/10.1007/s00506-018-0498-0
- Attribution of regional flood changes based on scaling fingerprints A. Viglione et al. https://doi.org/10.1002/2016WR019036
- Identifying hotspots of hydro-hazards under global change: A worldwide review L. Beevers et al. https://doi.org/10.3389/frwa.2022.879536
- Future high- and low-flow estimations for Central Vietnam: a hydro-meteorological modelling chain approach Q. Dang et al. https://doi.org/10.1080/02626667.2017.1353696
- Robust Adaptation to Multiscale Climate Variability J. Doss‐Gollin et al. https://doi.org/10.1029/2019EF001154
- Assessing flood hazard changes using climate model forcing D. Callaghan & M. Hughes https://doi.org/10.5194/nhess-22-2459-2022
- Understanding flood regime changes in Europe: a state-of-the-art assessment J. Hall et al. https://doi.org/10.5194/hess-18-2735-2014
- Design considerations for riverine floods in a changing climate – A review B. François et al. https://doi.org/10.1016/j.jhydrol.2019.04.068
- Hydrological extremes across the Commonwealth of Massachusetts in a changing climate R. Siddique et al. https://doi.org/10.1016/j.ejrh.2020.100733
- Predicting nonstationary flood frequencies: Evidence supports an updated stationarity thesis in the United States A. Luke et al. https://doi.org/10.1002/2016WR019676
- Non-stationary frequency analysis of extreme precipitation in South Korea using peaks-over-threshold and annual maxima S. Wi et al. https://doi.org/10.1007/s00477-015-1180-8
- Climate influences on flood probabilities across Europe E. Steirou et al. https://doi.org/10.5194/hess-23-1305-2019
- Updating urban design floods for changes in central tendency and variability using regression J. Hecht & R. Vogel https://doi.org/10.1016/j.advwatres.2019.103484
- Changing Seasonality of Annual Maximum Floods over the Conterminous US: Potential Drivers and Regional Synthesis B. Basu et al. https://doi.org/10.1061/JHYEFF.HEENG-5768
- The influence of non-stationarity in extreme hydrological events on flood frequency estimation M. Šraj et al. https://doi.org/10.1515/johh-2016-0032
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