Journal cover Journal topic
Hydrology and Earth System Sciences An interactive open-access journal of the European Geosciences Union
Journal topic

Journal metrics

IF value: 5.153
IF5.153
IF 5-year value: 5.460
IF 5-year
5.460
CiteScore value: 7.8
CiteScore
7.8
SNIP value: 1.623
SNIP1.623
IPP value: 4.91
IPP4.91
SJR value: 2.092
SJR2.092
Scimago H <br class='widget-line-break'>index value: 123
Scimago H
index
123
h5-index value: 65
h5-index65
Download
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.
Articles | Volume 21, issue 1
Hydrol. Earth Syst. Sci., 21, 635–650, 2017
https://doi.org/10.5194/hess-21-635-2017

Special issue: Sub-seasonal to seasonal hydrological forecasting

Hydrol. Earth Syst. Sci., 21, 635–650, 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 et al.

Viewed

Total article views: 2,056 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
1,175 814 67 2,056 172 66 86
  • HTML: 1,175
  • PDF: 814
  • XML: 67
  • Total: 2,056
  • Supplement: 172
  • BibTeX: 66
  • EndNote: 86
Views and downloads (calculated since 04 May 2016)
Cumulative views and downloads (calculated since 04 May 2016)

Cited

Latest update: 22 Jan 2021
Publications Copernicus
Download
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.
Citation