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Title: Enhancing Streamflow Forecast and Extracting Insights Using Long‐Short Term Memory Networks With Data Integration at Continental Scales

Authors:
ORCiD logo [1]; ORCiD logo [2]; ORCiD logo [1]
  1. Civil and Environmental Engineering Pennsylvania State University State College PA USA
  2. Civil and Environmental Engineering Pennsylvania State University State College PA USA, Now at: Earth System Science Stanford University Stanford CA USA
Publication Date:
Sponsoring Org.:
USDOE
OSTI Identifier:
1664500
Grant/Contract Number:  
DE‐SC0016605
Resource Type:
Publisher's Accepted Manuscript
Journal Name:
Water Resources Research
Additional Journal Information:
Journal Name: Water Resources Research Journal Volume: 56 Journal Issue: 9; Journal ID: ISSN 0043-1397
Publisher:
American Geophysical Union (AGU)
Country of Publication:
United States
Language:
English

Citation Formats

Feng, Dapeng, Fang, Kuai, and Shen, Chaopeng. Enhancing Streamflow Forecast and Extracting Insights Using Long‐Short Term Memory Networks With Data Integration at Continental Scales. United States: N. p., 2020. Web. https://doi.org/10.1029/2019WR026793.
Feng, Dapeng, Fang, Kuai, & Shen, Chaopeng. Enhancing Streamflow Forecast and Extracting Insights Using Long‐Short Term Memory Networks With Data Integration at Continental Scales. United States. https://doi.org/10.1029/2019WR026793
Feng, Dapeng, Fang, Kuai, and Shen, Chaopeng. Wed . "Enhancing Streamflow Forecast and Extracting Insights Using Long‐Short Term Memory Networks With Data Integration at Continental Scales". United States. https://doi.org/10.1029/2019WR026793.
@article{osti_1664500,
title = {Enhancing Streamflow Forecast and Extracting Insights Using Long‐Short Term Memory Networks With Data Integration at Continental Scales},
author = {Feng, Dapeng and Fang, Kuai and Shen, Chaopeng},
abstractNote = {},
doi = {10.1029/2019WR026793},
journal = {Water Resources Research},
number = 9,
volume = 56,
place = {United States},
year = {2020},
month = {9}
}

Journal Article:
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