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Generation of ensemble streamflow forecasts using an enhanced version of the snowmelt runoff model

Author:
Harshburger, Brian J., Walden, Von P., Humes, Karen S., Moore, Brandon C., Blandford, Troy R., Rango, Albert
Source:
Journal of the American Water Resources Association 2012 v.48 no.4 pp. 643
ISSN:
1752-1688
Subject:
Snowmelt Runoff Model, basins, image analysis, model validation, snowpack, stream flow, telemetry, watershed hydrology, watersheds, Idaho
Abstract:
As water demand increases in the western United States, so does the need for accurate streamflow forecasts. We describe a method for generating ensemble streamflow forecasts (1-15 days) using an enhanced version of the snowmelt runoff model (SRM). Forecasts are produced for three snowmelt-dominated basins in Idaho. Model inputs are derived from meteorological forecasts, snow cover imagery, and surface observations from Snowpack Telemetry stations. The model performed well at lead times up to 7 days, but has significant predictability out to 15 days. The timing of peak flow and the streamflow volume are captured well by the model, but the peak-flow value is typically low. The model performance was assessed by computing the coefficient of determination (R2), percentage of volume difference (Dv%), and a skill score that quantifies the usefulness of the forecasts relative to climatology. The average R2 value for the mean ensemble is >0.8 for all three basins for lead times up to seven days. The Dv% is fairly unbiased (within ±10%) out to seven days in two of the basins, but the model underpredicts Dv% in the third. The average skill scores for all basins are >0.6 for lead times up to seven days, indicating that the ensemble model outperforms climatology. These results validate the usefulness of the ensemble forecasting approach for basins of this type, suggesting that the ensemble version of SRM might be applied successfully to other basins in the Intermountain West.
Agid:
57179
Handle:
10113/57179