Articles | Volume 13, issue 10
https://doi.org/10.5194/gmd-13-4943-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-13-4943-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model description paper
| 
16 Oct 2020
Model description paper |
| 16 Oct 2020
| 16 Oct 2020
The Ensemble Framework For Flash Flood Forecasting (EF5) v1.2: description and case study
Zachary L. Flamig
Cooperative Institute for Mesoscale Meteorological Studies, University of Oklahoma, 120 David L Boren Blvd, Norman, OK 73072, USA
National Oceanic and Atmospheric Administration's National Severe Storms Laboratory, 120 David L Boren Blvd, Norman, OK 73072, USA
School of Meteorology, University of Oklahoma, Norman, OK, USA
Humberto Vergara
Cooperative Institute for Mesoscale Meteorological Studies, University of Oklahoma, 120 David L Boren Blvd, Norman, OK 73072, USA
National Oceanic and Atmospheric Administration's National Severe Storms Laboratory, 120 David L Boren Blvd, Norman, OK 73072, USA
National Oceanic and Atmospheric Administration's National Severe Storms Laboratory, 120 David L Boren Blvd, Norman, OK 73072, USA
School of Meteorology, University of Oklahoma, Norman, OK, USA
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- Can re-infiltration process be ignored for flood inundation mapping and prediction during extreme storms? A case study in Texas Gulf Coast region Z. Li et al. https://doi.org/10.1016/j.envsoft.2022.105450
- Hydrologic evaluation of the global precipitation measurement mission over the U.S.: Flood peak discharge and duration D. Woods et al. https://doi.org/10.1016/j.jhydrol.2023.129124
- A prototype adaptive mesh generator for enhancing computational efficiency and accuracy in physically-based modeling of flood-landslide hazards G. Chen et al. https://doi.org/10.1016/j.envsoft.2025.106458
- Coupling hydrological, geotechnical and machine learning models to enhance landslide prediction for an early warning system: application to Upper Garonne River Basin, Pyrenees, Spain F. Asurza et al. https://doi.org/10.1007/s10346-025-02685-7
- Spatiotemporal Characteristics of US Floods: Current Status and Forecast Under a Future Warmer Climate Z. Li et al. https://doi.org/10.1029/2022EF002700
- Does a convection-permitting regional climate model bring new perspectives on the projection of Mediterranean floods? N. Poncet et al. https://doi.org/10.5194/nhess-24-1163-2024
- An Adaptive Ensemble Framework for Flood Forecasting and Its Application in a Small Watershed Using Distinct Rainfall Interpolation Methods Y. Xu et al. https://doi.org/10.1007/s11269-023-03489-x
- A data-driven global flood forecasting system for medium to large rivers W. Palash et al. https://doi.org/10.1038/s41598-024-59145-w
- PHyL v1.0: A parallel, flexible, and advanced software for hydrological and slope stability modeling at a regional scale G. Chen et al. https://doi.org/10.1016/j.envsoft.2023.105882
- Towards Predicting Flood Event Peak Discharge in Ungauged Basins by Learning Universal Hydrological Behaviors with Machine Learning A. Sanjay Potdar et al. https://doi.org/10.1175/JHM-D-20-0302.1
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- Is there differential engagement in urban flooding prevention in Detroit? T. Tran et al. https://doi.org/10.1080/07352166.2026.2642133
- Enhancing Flood Risk Management: A Comprehensive Review on Flood Early Warning Systems with Emphasis on Numerical Modeling D. Fernández-Nóvoa et al. https://doi.org/10.3390/w16101408
- Assessing the impact of migration activities on flood exposure and evaluating sustainable development areas based on hydrodynamic simulations and gridded migration data K. Fei et al. https://doi.org/10.1016/j.jhydrol.2025.133425
- CREST-iMAP v1.0: A fully coupled hydrologic-hydraulic modeling framework dedicated to flood inundation mapping and prediction Z. Li et al. https://doi.org/10.1016/j.envsoft.2021.105051
- Historical memory in remotely sensed soil moisture can enhance flash flood modeling for headwater catchments in Germany Y. Liu et al. https://doi.org/10.1016/j.jhydrol.2024.132395
Saved (final revised paper)
Latest update: 09 Jun 2026
Short summary
The Ensemble Framework For Flash Flood Forecasting (EF5) is used in the US National Weather Service for operational monitoring and short-term forecasting of flash floods. This article describes the hydrologic models supported by the framework and evaluates their accuracy by comparing simulations of streamflow from 2001 to 2011 at 4 366 observation sites with catchments less than 1000 km2. Overall, the uncalibrated models reasonably simulate flash flooding events.
The Ensemble Framework For Flash Flood Forecasting (EF5) is used in the US National Weather...
