Articles | Volume 13, issue 10
https://doi.org/10.5194/gmd-13-4943-2020
https://doi.org/10.5194/gmd-13-4943-2020
Model description paper
 | 
16 Oct 2020
Model description paper |  | 16 Oct 2020

The Ensemble Framework For Flash Flood Forecasting (EF5) v1.2: description and case study

Zachary L. Flamig, Humberto Vergara, and Jonathan J. Gourley

Related authors

Does a convection-permitting regional climate model bring new perspectives on the projection of Mediterranean floods?
Nils Poncet, Philippe Lucas-Picher, Yves Tramblay, Guillaume Thirel, Humberto Vergara, Jonathan Gourley, and Antoinette Alias
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2023-82,https://doi.org/10.5194/nhess-2023-82, 2023
Preprint under review for NHESS
Short summary
MGP: a new 1-hourly 0.25° global precipitation product (2000–2020) based on multi-source precipitation data fusion
Hanqing Chen, Debao Wen, Bin Yong, Jonathan J. Gourley, Leyang Wang, and Yang Hong
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2023-42,https://doi.org/10.5194/essd-2023-42, 2023
Manuscript not accepted for further review
Short summary
CREST-VEC: a framework towards more accurate and realistic flood simulation across scales
Zhi Li, Shang Gao, Mengye Chen, Jonathan Gourley, Naoki Mizukami, and Yang Hong
Geosci. Model Dev., 15, 6181–6196, https://doi.org/10.5194/gmd-15-6181-2022,https://doi.org/10.5194/gmd-15-6181-2022, 2022
Short summary
A multi-source 120-year US flood database with a unified common format and public access
Zhi Li, Mengye Chen, Shang Gao, Jonathan J. Gourley, Tiantian Yang, Xinyi Shen, Randall Kolar, and Yang Hong
Earth Syst. Sci. Data, 13, 3755–3766, https://doi.org/10.5194/essd-13-3755-2021,https://doi.org/10.5194/essd-13-3755-2021, 2021
Short summary
iCRESTRIGRS: a coupled modeling system for cascading flood–landslide disaster forecasting
Ke Zhang, Xianwu Xue, Yang Hong, Jonathan J. Gourley, Ning Lu, Zhanming Wan, Zhen Hong, and Rick Wooten
Hydrol. Earth Syst. Sci., 20, 5035–5048, https://doi.org/10.5194/hess-20-5035-2016,https://doi.org/10.5194/hess-20-5035-2016, 2016
Short summary

Related subject area

Hydrology
Enhancing the representation of water management in global hydrological models
Guta Wakbulcho Abeshu, Fuqiang Tian, Thomas Wild, Mengqi Zhao, Sean Turner, A. F. M. Kamal Chowdhury, Chris R. Vernon, Hongchang Hu, Yuan Zhuang, Mohamad Hejazi, and Hong-Yi Li
Geosci. Model Dev., 16, 5449–5472, https://doi.org/10.5194/gmd-16-5449-2023,https://doi.org/10.5194/gmd-16-5449-2023, 2023
Short summary
NEOPRENE v1.0.1: a Python library for generating spatial rainfall based on the Neyman–Scott process
Javier Diez-Sierra, Salvador Navas, and Manuel del Jesus
Geosci. Model Dev., 16, 5035–5048, https://doi.org/10.5194/gmd-16-5035-2023,https://doi.org/10.5194/gmd-16-5035-2023, 2023
Short summary
Uncertainty estimation for a new exponential-filter-based long-term root-zone soil moisture dataset from Copernicus Climate Change Service (C3S) surface observations
Adam Pasik, Alexander Gruber, Wolfgang Preimesberger, Domenico De Santis, and Wouter Dorigo
Geosci. Model Dev., 16, 4957–4976, https://doi.org/10.5194/gmd-16-4957-2023,https://doi.org/10.5194/gmd-16-4957-2023, 2023
Short summary
Validating the Nernst–Planck transport model under reaction-driven flow conditions using RetroPy v1.0
Po-Wei Huang, Bernd Flemisch, Chao-Zhong Qin, Martin O. Saar, and Anozie Ebigbo
Geosci. Model Dev., 16, 4767–4791, https://doi.org/10.5194/gmd-16-4767-2023,https://doi.org/10.5194/gmd-16-4767-2023, 2023
Short summary
DynQual v1.0: a high-resolution global surface water quality model
Edward R. Jones, Marc F. P. Bierkens, Niko Wanders, Edwin H. Sutanudjaja, Ludovicus P. H. van Beek, and Michelle T. H. van Vliet
Geosci. Model Dev., 16, 4481–4500, https://doi.org/10.5194/gmd-16-4481-2023,https://doi.org/10.5194/gmd-16-4481-2023, 2023
Short summary

Cited articles

AMS: Prediction and Mitigation of Flash Floods, B. Am. Meteorol. Soc., 81, 1338–1340, https://doi.org/10.1175/1520-0477(2000)081<1338:pspamo>2.3.co;2, 2000. a
AMS: Flash Floods: The Role of Science, Forecasting, and Communications in Reducing Loss of Life and Economic Disruptions, available at: https://www.ametsoc.org/index.cfm/ams/about-ams/ams-statements/statements-of-the-ams-in-force/flash-floods-the-role-of-science-forecasting-and-communications-in-reducing-loss-of-life-and-economic-disruptions/ (last access: 3 September 2020), 2017. a
Anderson, E. A.: A Point Energy and Mass Balance Model of a Snow Cover, NOAA Technical Report, NWS 19, 1976. a
Argyle, E. M., Gourley, J. J., Flamig, Z. L., Hansen, T., and Manross, K.: Toward a User-Centered Design of a Weather Forecasting Decision-Support Tool, B. Am. Meteorol. Soc., 98, 373–382, https://doi.org/10.1175/bams-d-16-0031.1, 2017. a
Ashley, S. T. and Ashley, W. S.: Flood Fatalities in the United States, J. Appl. Meteorol. Climatol., 47, 805–818, https://doi.org/10.1175/2007jamc1611.1, 2008. a
Download
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.