Rainfall characteristics define the value of streamflow observations for distributed watershed model identification

Physics

Scientific paper

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Hydrology: Modeling, Hydrology: Streamflow, Hydrology: Watershed, Hydrology: Model Calibration (3333), Hydrology: Precipitation (3354)

Scientific paper

We present evidence that the characteristics of rainfall events strongly control the value of streamflow observations for the identification of distributed watershed models. A series of synthetic rainfall events with different spatio-temporal extents and dynamics are used to investigate spatially-distributed global parameter sensitivities for a typical watershed model. The model's parametric sensitivities vary greatly with rainfall distribution characteristics, location of the model cell in relation to the watershed's gauged outlet, and, to a lesser degree, the initial model states. This study demonstrates that the information content of streamflow is a dynamic property and that distributed model identification methodologies should consider the impact of spatio-temporal rainfall dynamics.

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