Articles | Volume 17, issue 11
https://doi.org/10.5194/hess-17-4389-2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Special issue:
https://doi.org/10.5194/hess-17-4389-2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
HESS Opinions "Forecaster priorities for improving probabilistic flood forecasts"
F. Wetterhall
European Centre for Medium Range Weather Forecasts, Reading, UK
F. Pappenberger
European Centre for Medium Range Weather Forecasts, Reading, UK
L. Alfieri
European Centre for Medium Range Weather Forecasts, Reading, UK
H. L. Cloke
University of Reading, Reading, UK
J. Thielen-del Pozo
European Commission, Joint Research Centre, Ispra, Italy
S. Balabanova
National Institute of Meteorology and Hydrology, Sofia, Bulgaria
J. Daňhelka
Czech Hydrometeorological Institute, Prague, Czech Republic
A. Vogelbacher
Bayerisches Landesamt für Umwelt, Augsburg, Germany
P. Salamon
European Commission, Joint Research Centre, Ispra, Italy
I. Carrasco
Confederación Hidrográfica del Ebro, Zaragoza, Spain
A. J. Cabrera-Tordera
Environmental Information Network of Andalusia, Cuenca, Spain
M. Corzo-Toscano
Environmental Information Network of Andalusia, Cuenca, Spain
M. Garcia-Padilla
Environmental Information Network of Andalusia, Cuenca, Spain
R. J. Garcia-Sanchez
Environmental Information Network of Andalusia, Cuenca, Spain
C. Ardilouze
Service Central d'Hydrométéorologie et d'Appui à la Prévision des Inondations, Toulouse, France
S. Jurela
Hydrological and Meteorological Service Croatia, Zagreb, Croatia
B. Terek
Hydrological and Meteorological Service Croatia, Zagreb, Croatia
A. Csik
Environmental Protection and Water Management Research Centre, Budapest, Hungary
J. Casey
Office of Public Works, Dublin, Ireland
G. Stankūnavičius
Department of Hydrology and Climatology, Vilnius University, Vilnius, Lithuania
V. Ceres
State Hydrometeorological Service, Ghimet, Moldova
E. Sprokkereef
Rijkswaterstaat, Lelystad, the Netherlands
J. Stam
Rijkswaterstaat, Lelystad, the Netherlands
E. Anghel
National Institute of Hydrology and Water Management, Bucharest, Romania
D. Vladikovic
Republic Hydrometeorological Service of Serbia, Belgrade, Serbia
C. Alionte Eklund
Swedish Meteorological and Hydrological Institute, Norrköping, Sweden
N. Hjerdt
Swedish Meteorological and Hydrological Institute, Norrköping, Sweden
H. Djerv
Swedish Meteorological and Hydrological Institute, Norrköping, Sweden
F. Holmberg
Swedish Meteorological and Hydrological Institute, Norrköping, Sweden
J. Nilsson
Swedish Meteorological and Hydrological Institute, Norrköping, Sweden
K. Nyström
Swedish Meteorological and Hydrological Institute, Norrköping, Sweden
M. Sušnik
Slovenian Environment Agency, Ljubljana, Slovenia
M. Hazlinger
Slovak Hydrometeorological Institute, Bratislava, Slovakia
M. Holubecka
Slovak Hydrometeorological Institute, Bratislava, Slovakia
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Cited
39 citations as recorded by crossref.
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- Improving the Reliability of Probabilistic Multi-Step-Ahead Flood Forecasting by Fusing Unscented Kalman Filter with Recurrent Neural Network Y. Zhou et al. 10.3390/w12020578
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- Evaluation of the Impact of Multi-Source Uncertainties on Meteorological and Hydrological Ensemble Forecasting Z. Shu et al. 10.1016/j.eng.2022.06.007
- Using bias correction and ensemble modelling for predictive mapping and related uncertainty: A case study in digital soil mapping J. Sylvain et al. 10.1016/j.geoderma.2021.115153
- Generating Ensemble Streamflow Forecasts: A Review of Methods and Approaches Over the Past 40 Years M. Troin et al. 10.1029/2020WR028392
- Improved error modelling for streamflow forecasting at hourly time steps by splitting hydrographs into rising and falling limbs M. Li et al. 10.1016/j.jhydrol.2017.10.057
- Assessing time, cost and quality trade-offs in forecast-based action for floods K. Bischiniotis et al. 10.1016/j.ijdrr.2019.101252
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- On the assessment of reliability in probabilistic hydrometeorological event forecasting C. DeChant & H. Moradkhani 10.1002/2014WR016617
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- Understanding Future Water Challenges in a Highly Regulated Indian River Basin—Modelling the Impact of Climate Change on the Hydrology of the Upper Narmada N. Rickards et al. 10.3390/w12061762
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- River basin flood potential inferred using GRACE gravity observations at several months lead time J. Reager et al. 10.1038/ngeo2203
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34 citations as recorded by crossref.
- Challenges, Opportunities, and Pitfalls for Global Coupled Hydrologic‐Hydraulic Modeling of Floods S. Grimaldi et al. 10.1029/2018WR024289
- Streamflow forecast sensitivity to air temperature forecast calibration for 139 Norwegian catchments T. Hegdahl et al. 10.5194/hess-23-723-2019
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- Quantifying the effectiveness of early warning systems for natural hazards M. Sättele et al. 10.5194/nhess-16-149-2016
- Evaluation of a global ensemble flood prediction system in Peru K. Bischiniotis et al. 10.1080/02626667.2019.1617868
- Trivariate joint frequency analysis of water resources deficiency signatures using vine copulas M. Nazeri Tahroudi et al. 10.1007/s13201-022-01589-4
- Ensemble Streamflow Forecasting across the U.S. Mid-Atlantic Region with a Distributed Hydrological Model Forced by GEFS Reforecasts R. Siddique & A. Mejia 10.1175/JHM-D-16-0243.1
- Improving the Reliability of Probabilistic Multi-Step-Ahead Flood Forecasting by Fusing Unscented Kalman Filter with Recurrent Neural Network Y. Zhou et al. 10.3390/w12020578
- On the implementation of post-processing of runoff forecast ensembles J. Skøien et al. 10.1175/JHM-D-21-0008.1
- Reliable hourly streamflow forecasting with emphasis on ephemeral rivers M. Li et al. 10.1016/j.jhydrol.2020.125739
- Evaluation of the Impact of Multi-Source Uncertainties on Meteorological and Hydrological Ensemble Forecasting Z. Shu et al. 10.1016/j.eng.2022.06.007
- Using bias correction and ensemble modelling for predictive mapping and related uncertainty: A case study in digital soil mapping J. Sylvain et al. 10.1016/j.geoderma.2021.115153
- Generating Ensemble Streamflow Forecasts: A Review of Methods and Approaches Over the Past 40 Years M. Troin et al. 10.1029/2020WR028392
- Improved error modelling for streamflow forecasting at hourly time steps by splitting hydrographs into rising and falling limbs M. Li et al. 10.1016/j.jhydrol.2017.10.057
- Assessing time, cost and quality trade-offs in forecast-based action for floods K. Bischiniotis et al. 10.1016/j.ijdrr.2019.101252
- A national flood awareness system for ungauged catchments in complex topography: The case of development, communication and evaluation in New Zealand C. Cattoën et al. 10.1111/jfr3.12864
- Ensemble forecasting system for the management of the Senegal River discharge: application upstream the Manantali dam D. Ndione et al. 10.1007/s13201-020-01199-y
- A global network for operational flood risk reduction L. Alfieri et al. 10.1016/j.envsci.2018.03.014
- On the assessment of reliability in probabilistic hydrometeorological event forecasting C. DeChant & H. Moradkhani 10.1002/2014WR016617
- How do I know if I’ve improved my continental scale flood early warning system? H. Cloke et al. 10.1088/1748-9326/aa625a
- Understanding Future Water Challenges in a Highly Regulated Indian River Basin—Modelling the Impact of Climate Change on the Hydrology of the Upper Narmada N. Rickards et al. 10.3390/w12061762
- Exploring hydrologic post-processing of ensemble streamflow forecasts based on affine kernel dressing and non-dominated sorting genetic algorithm II J. Xu et al. 10.5194/hess-26-1001-2022
- Hyperresolution information and hyperresolution ignorance in modelling the hydrology of the land surface K. Beven et al. 10.1007/s11430-014-5003-4
- Pre- and postprocessing flood forecasts using Bayesian model averaging T. Hegdahl et al. 10.2166/nh.2023.024
- Technical review of large-scale hydrological models for implementation in operational flood forecasting schemes on continental level A. Kauffeldt et al. 10.1016/j.envsoft.2015.09.009
- Skill of short- to medium-range monsoon rainfall forecasts from two global models over India for hydro-meteorological applications S. Prakash et al. 10.1002/met.1579
- Discharge Interval method for uncertain flood forecasts using a flood model chain: city of Kulmbach M. Beg et al. 10.2166/hydro.2019.131
- Evaluation of ensemble streamflow predictions in Europe L. Alfieri et al. 10.1016/j.jhydrol.2014.06.035
- Improving flood forecasts for better flood preparedness in the UK (and beyond) E. Stephens & H. Cloke 10.1111/geoj.12103
- Toward Systematic Literature Reviews in Hydrological Sciences D. De León Pérez et al. 10.3390/w16030436
- Accounting for three sources of uncertainty in ensemble hydrological forecasting A. Thiboult et al. 10.5194/hess-20-1809-2016
- From calibration to real‐time operations: an assessment of three precipitation benchmarks for a Swiss river system N. Andres et al. 10.1002/met.1569
- Forecasting upper and lower uncertainty bands of river flood discharges with high predictive skill J. Leandro et al. 10.1016/j.jhydrol.2019.06.052
5 citations as recorded by crossref.
- Challenges of Operational River Forecasting T. Pagano et al. 10.1175/JHM-D-13-0188.1
- How do I know if my forecasts are better? Using benchmarks in hydrological ensemble prediction F. Pappenberger et al. 10.1016/j.jhydrol.2015.01.024
- Hydrological uncertainty processor based on a copula function Z. Liu et al. 10.1080/02626667.2017.1410278
- River basin flood potential inferred using GRACE gravity observations at several months lead time J. Reager et al. 10.1038/ngeo2203
- Characterized Flood Potential in the Yangtze River Basin from GRACE Gravity Observation, Hydrological Model, and In-Situ Hydrological Station N. Chao & Z. Wang 10.1061/(ASCE)HE.1943-5584.0001547
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