Dayflow: CONUS Daily Streamflow Reanalysis, Version 1 (V1)

Kao, Shih-Chieh; Ghimire, Ganesh R.; Hansen, Carly; Gangrade, Sudershan; Thornton, Peter E.; Singh, Debjani

doi:10.21951/Dayflow/1847639

Title: Dayflow: CONUS Daily Streamflow Reanalysis, Version 1 (V1)

Dataset
Other Related Research

Abstract

Dayflow V1 is a historical streamflow reanalysis dataset reconstructed for a 36-year period (1980-2015). The dataset provides both daily and monthly scale streamflow information at about 2.7 million NHDPlusV2 stream reaches in the conterminous US (CONUS). Dayflow is the result of a nationally scalable modeling framework that integrates the simulated runoff from the Variable Infiltration Capacity (VIC) model with the Routing Application for Parallel computatIon of Discharge (RAPID) routing model. Two types of streamflow products, simulated streamflow with or without assimilation of historic US Geological Survey (USGS) streamflow observations, are provided in Dayflow V1. A comprehensive evaluation at 7,526 USGS National Water Information System (NWIS) gauges is performed for both types of streamflow products. The resulting key evaluation metrics are also included in the Dayflow V1 Dataset.

Authors:

Kao, Shih-Chieh; Ghimire, Ganesh R.; Hansen, Carly; Gangrade, Sudershan; Thornton, Peter E.; Singh, Debjani

Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Oak Ridge National Laboratory
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)

Publication Date:: Mon Feb 28 23:00:00 EST 2022

Other Number(s):: 1

DOE Contract Number:: AC05-00OR22725

Research Org.:: Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)

Sponsoring Org.:: USDOE Office of Energy Efficiency and Renewable Energy (EERE), Renewable Power Office. Water Power Technologies Office

Subject:: 13 HYDRO ENERGY

OSTI Identifier:: 1847639

DOI:: https://doi.org/10.21951/Dayflow/1847639

Citation Formats


                    Kao, Shih-Chieh, Ghimire, Ganesh R., Hansen, Carly, Gangrade, Sudershan, Thornton, Peter E., and Singh, Debjani. Dayflow: CONUS Daily Streamflow Reanalysis, Version 1 (V1).  United States: N. p., 2022. 
        Web.  doi:10.21951/Dayflow/1847639.

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                    Kao, Shih-Chieh, Ghimire, Ganesh R., Hansen, Carly, Gangrade, Sudershan, Thornton, Peter E., & Singh, Debjani. Dayflow: CONUS Daily Streamflow Reanalysis, Version 1 (V1).  United States.  doi:https://doi.org/10.21951/Dayflow/1847639

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                    Kao, Shih-Chieh, Ghimire, Ganesh R., Hansen, Carly, Gangrade, Sudershan, Thornton, Peter E., and Singh, Debjani. 2022.  
"Dayflow: CONUS Daily Streamflow Reanalysis, Version 1 (V1)".  United States.  doi:https://doi.org/10.21951/Dayflow/1847639.  https://www.osti.gov/servlets/purl/1847639. Pub date:Mon Feb 28 23:00:00 EST 2022

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@article{osti_1847639,

  title        = {Dayflow: CONUS Daily Streamflow Reanalysis, Version 1 (V1)},

  author       = {Kao, Shih-Chieh and Ghimire, Ganesh R. and Hansen, Carly and Gangrade, Sudershan and Thornton, Peter E. and Singh, Debjani},

  abstractNote = {Dayflow V1 is a historical streamflow reanalysis dataset reconstructed for a 36-year period (1980-2015). The dataset provides both daily and monthly scale streamflow information at about 2.7 million NHDPlusV2 stream reaches in the conterminous US (CONUS). Dayflow is the result of a nationally scalable modeling framework that integrates the simulated runoff from the Variable Infiltration Capacity (VIC) model with the Routing Application for Parallel computatIon of Discharge (RAPID) routing model. Two types of streamflow products, simulated streamflow with or without assimilation of historic US Geological Survey (USGS) streamflow observations, are provided in Dayflow V1. A comprehensive evaluation at 7,526 USGS National Water Information System (NWIS) gauges is performed for both types of streamflow products. The resulting key evaluation metrics are also included in the Dayflow V1 Dataset.},

  doi          = {10.21951/Dayflow/1847639},

  journal      = {},

  number       = ,

  volume       = ,

  place        = {United States},

  year         = {Mon Feb 28 23:00:00 EST 2022},

  month        = {Mon Feb 28 23:00:00 EST 2022}

}

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DOI: https://doi.org/10.21951/Dayflow/1847639

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