Articles | Volume 26, issue 23
https://doi.org/10.5194/hess-26-6121-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-26-6121-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
06 Dec 2022
Research article |
| 06 Dec 2022
| 06 Dec 2022
Evaluation of a new observationally based channel parameterization for the National Water Model
Department of Civil, Environmental, and Architectural Engineering,
University of Colorado Boulder, Boulder, CO 80309, USA
Ben Livneh
Department of Civil, Environmental, and Architectural Engineering,
University of Colorado Boulder, Boulder, CO 80309, USA
Cooperative Institute for Research in Environmental Sciences,
University of Colorado Boulder, Boulder, CO 80309, USA
James McCreight
National Center for Atmospheric Research, Boulder, CO 80305, USA
Laura Read
National Center for Atmospheric Research, Boulder, CO 80305, USA
Joseph Kasprzyk
Department of Civil, Environmental, and Architectural Engineering,
University of Colorado Boulder, Boulder, CO 80309, USA
Toby Minear
Cooperative Institute for Research in Environmental Sciences,
University of Colorado Boulder, Boulder, CO 80309, USA
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Short summary
Measurements of channel characteristics are important for accurate forecasting in the NOAA National Water Model (NWM) but are scarcely available. We seek to improve channel representativeness in the NWM by updating channel geometry and roughness parameters using a large, previously unpublished, dataset of approximately 48 000 gauges. We find that the updated channel parameterization from this new dataset leads to improvements in simulated streamflow performance and channel representation.
Measurements of channel characteristics are important for accurate forecasting in the NOAA...
