Articles | Volume 21, issue 1
https://doi.org/10.5194/hess-21-635-2017
https://doi.org/10.5194/hess-21-635-2017
Research article
 | 
31 Jan 2017
Research article |  | 31 Jan 2017

Evaluation of snow data assimilation using the ensemble Kalman filter for seasonal streamflow prediction in the western United States

Chengcheng Huang, Andrew J. Newman, Martyn P. Clark, Andrew W. Wood, and Xiaogu Zheng

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Cited articles

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Short summary
This study examined the potential of snow water equivalent data assimilation to improve seasonal streamflow predictions. We examined aspects of the data assimilation system over basins with varying climates across the western US. We found that varying how the data assimilation system is implemented impacts forecast performance, and basins with good initial calibrations see less benefit. This implies that basin-specific configurations and benefits should be expected given this modeling system.