Premium
Reducing Streamflow Forecast Uncertainty: Application and Qualitative Assessment of the Upper Klamath River Basin, Oregon 1
Author(s) -
Hay Lauren E.,
McCabe Gregory J.,
Clark Martyn P.,
Risley John C.
Publication year - 2009
Publication title -
jawra journal of the american water resources association
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.957
H-Index - 105
eISSN - 1752-1688
pISSN - 1093-474X
DOI - 10.1111/j.1752-1688.2009.00307.x
Subject(s) - streamflow , geopotential height , environmental science , snowmelt , climatology , structural basin , drainage basin , hydrology (agriculture) , meteorology , geology , snow , precipitation , geography , paleontology , cartography , geotechnical engineering
The accuracy of streamflow forecasts depends on the uncertainty associated with future weather and the accuracy of the hydrologic model that is used to produce the forecasts. We present a method for streamflow forecasting where hydrologic model parameters are selected based on the climate state. Parameter sets for a hydrologic model are conditioned on an atmospheric pressure index defined using mean November through February (NDJF) 700‐hectoPascal geopotential heights over northwestern North America [Pressure Index from Geopotential heights (PIG)]. The hydrologic model is applied in the Sprague River basin (SRB), a snowmelt‐dominated basin located in the Upper Klamath basin in Oregon. In the SRB, the majority of streamflow occurs during March through May (MAM). Water years (WYs) 1980‐2004 were divided into three groups based on their respective PIG values (high, medium, and low PIG). Low (high) PIG years tend to have higher (lower) than average MAM streamflow. Four parameter sets were calibrated for the SRB, each using a different set of WYs. The initial set used WYs 1995‐2004 and the remaining three used WYs defined as high‐, medium‐, and low‐PIG years. Two sets of March, April, and May streamflow volume forecasts were made using Ensemble Streamflow Prediction (ESP). The first set of ESP simulations used the initial parameter set. Because the PIG is defined using NDJF pressure heights, forecasts starting in March can be made using the PIG parameter set that corresponds with the year being forecasted. The second set of ESP simulations used the parameter set associated with the given PIG year. Comparison of the ESP sets indicates that more accuracy and less variability in volume forecasts may be possible when the ESP is conditioned using the PIG. This is especially true during the high‐PIG years (low‐flow years).