An intercomparison of approaches for improving operational seasonal streamflow forecasts

Mendoza, Pablo A.; Wood, Andrew W.; Clark, Elizabeth; Rothwell, Eric; Clark, Martyn P.; Nijssen, Bart; Brekke, Levi D.; Arnold, Jeffrey R.

doi:https://doi.org/10.5194/hess-21-3915-2017

Articles | Volume 21, issue 7

https://doi.org/10.5194/hess-21-3915-2017

© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.

Special issue:

Sub-seasonal to seasonal hydrological forecasting

https://doi.org/10.5194/hess-21-3915-2017

© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.

Articles | Volume 21, issue 7

Research article

| Highlight paper

|

31 Jul 2017

Research article | Highlight paper |

| 31 Jul 2017

An intercomparison of approaches for improving operational seasonal streamflow forecasts

Pablo A. Mendoza, Andrew W. Wood, Elizabeth Clark, Eric Rothwell, Martyn P. Clark, Bart Nijssen, Levi D. Brekke, and Jeffrey R. Arnold

Data sets

2010 Modified Streamflows Bonneville Power Administration https://www.bpa.gov/power/streamflow/default.aspx

Global Historical Climatology Network - Daily (GHCN-Daily), Version 3 M. J. Menne, I. Durre, B. Korzeniewski, S. McNeal, K. Thomas, X. Yin, S. Anthony, R. Ray, R. S. Vose, B. E. Gleason, and T. G. Houston https://doi.org/10.7289/V5D21VHZ

Climate Indices: Monthly Atmospheric and Ocean Time Series Earth System Research Laboratory https://www.esrl.noaa.gov/psd/data/climateindices/list/

Climate Forecast System (CFS) NOAA - National Centers for Environmental Information https://www.ncdc.noaa.gov/data-access/model-data/model-datasets/climate-forecast-system-version2-cfsv2

Short summary

Water supply forecasts are critical to support water resources operations and planning. The skill of such forecasts depends on our knowledge of (i) future meteorological conditions and (ii) the amount of water stored in a basin. We address this problem by testing several approaches that make use of these sources of predictability, either separately or in a combined fashion. The main goal is to understand the marginal benefits of both information and methodological complexity in forecast skill.