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Riley C. Hales, Robert B. Sowby, Gustavious P. Williams, E. James Nelson, Daniel P. Ames, Jonah B. Dundas and Josh Ogden
Hydrologic modeling is trending toward larger spatial and temporal domains, higher resolutions, and less extensive local calibration and validation. Thorough calibration and validation are difficult because the quantity of observations needed for such sc...
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Vanessa Wörner, Phillip Kreye and Günter Meon
Bias-correction methods are commonly applied to climate model data in hydrological climate impact studies. This is due to the often large deviations between simulated and observed climate variables. These biases may cause unrealistic simulation results w...
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Yilu Li, Yunzhong Jiang, Xiaohui Lei, Fuqiang Tian, Hao Duan and Hui Lu
Meteorological centers constantly make efforts to provide more skillful seasonal climate forecast, which has the potential to improve streamflow forecasts. A common approach is to bias-correct the general circulation model (GCM) forecasts prior to genera...
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Alexander J. Koutsouris, Jan Seibert and Steve W. Lyon
This study explored the potential for bias correction of global precipitation datasets (GPD) to support streamflow simulation for water resource management in data limited regions. Two catchments, 580 km2 and 2530 km2, in the Kilombero Valley of central ...
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Peter Berg, Thomas Bosshard and Wei Yang
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