A flood predictability study for Hurricane Harvey with the CREST-iMAP model using high-resolution quantitative precipitation forecasts and U-Net deep learning precipitation nowcasts-Reference-Cited by-同舟云学术

A flood predictability study for Hurricane Harvey with the CREST-iMAP model using high-resolution quantitative precipitation forecasts and U-Net deep learning precipitation nowcasts

Published:2022-09 Issue: Volume:612 Page:128168
ISSN:0022-1694
Container-title:Journal of Hydrology
language:en
Short-container-title:Journal of Hydrology

Author:

Chen Mengye,Li Zhi,Gao Shang^ORCID,Xue Ming,Gourley Jonathan J.,Kolar Randall L.,Hong Yang

Funder

University of Oklahoma

Publisher

Elsevier BV

Subject

Water Science and Technology

Reference65 articles.

1. Flood forecasting: a global perspective,2016

2. Agrawal, S., Barrington, L., Bromberg, C., Burge, J., Gazen, C., Hickey, J., 2019. Machine Learning for Precipitation Nowcasting from Radar Images. arXiv:1912.12132 [cs, stat].

3. Flood Fatalities in the United States;Ashley;J. Appl. Meteorol. Climatol.,2008

4. Major flood disasters in Europe: 1950–2005;Barredo;Nat. Hazards,2007

5. A simple raster-based model for flood inundation simulation;Bates;J. Hydrol.,2000

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