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Title: A Novel Modeling Framework for Computationally Efficient and Accurate Real‐Time Ensemble Flood Forecasting With Uncertainty Quantification

ORCiD logo [1];  [2]; ORCiD logo [3]; ORCiD logo [2]; ORCiD logo [1]
  1. School of Civil and Environmental EngineeringUniversity of Ulsan South Korea
  2. Department of Civil and Environmental EngineeringUniversity of Michigan Ann Arbor MI USA
  3. Sandia National Laboratories Livermore CA USA
Publication Date:
Sponsoring Org.:
OSTI Identifier:
Grant/Contract Number:  
Resource Type:
Publisher's Accepted Manuscript
Journal Name:
Water Resources Research
Additional Journal Information:
[Journal Name: Water Resources Research Journal Volume: 56 Journal Issue: 3]; Journal ID: ISSN 0043-1397
American Geophysical Union (AGU)
Country of Publication:
United States

Citation Formats

Tran, Vinh Ngoc, Dwelle, M. Chase, Sargsyan, Khachik, Ivanov, Valeriy Y., and Kim, Jongho. A Novel Modeling Framework for Computationally Efficient and Accurate Real‐Time Ensemble Flood Forecasting With Uncertainty Quantification. United States: N. p., 2020. Web. doi:10.1029/2019WR025727.
Tran, Vinh Ngoc, Dwelle, M. Chase, Sargsyan, Khachik, Ivanov, Valeriy Y., & Kim, Jongho. A Novel Modeling Framework for Computationally Efficient and Accurate Real‐Time Ensemble Flood Forecasting With Uncertainty Quantification. United States. doi:10.1029/2019WR025727.
Tran, Vinh Ngoc, Dwelle, M. Chase, Sargsyan, Khachik, Ivanov, Valeriy Y., and Kim, Jongho. Sun . "A Novel Modeling Framework for Computationally Efficient and Accurate Real‐Time Ensemble Flood Forecasting With Uncertainty Quantification". United States. doi:10.1029/2019WR025727.
title = {A Novel Modeling Framework for Computationally Efficient and Accurate Real‐Time Ensemble Flood Forecasting With Uncertainty Quantification},
author = {Tran, Vinh Ngoc and Dwelle, M. Chase and Sargsyan, Khachik and Ivanov, Valeriy Y. and Kim, Jongho},
abstractNote = {},
doi = {10.1029/2019WR025727},
journal = {Water Resources Research},
number = [3],
volume = [56],
place = {United States},
year = {2020},
month = {3}

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