Does model structure limit the use of satellite data as hydrologic forcing for distributed operational models?

Abstract:

We are investigating the implications for use of satellite data in operational streamflow prediction. Specifically, the consequence of potential hydrologic model structure deficiencies on the ability to achieve improved forecast accuracy through the use of satellite data. We want to understand why advanced data do not lead to improved streamflow simulations by exploring how various fluxes and states differ among models of increasing complexity. In a series of prior studies, we investigated the use of a daily satellite-derived potential evapotranspiration (PET) estimate as input to the National Weather Service (NWS) streamflow forecast models for watersheds in the Upper Mississippi and Red river basins. Although the spatial PET product appears to represent the day-to-day variability in PET more realistically than current climatological methods used by the NWS, the impact of the satellite data on streamflow simulations results in slightly poorer model efficiency overall. Analysis of the model states indicates the model progresses differently between simulations with baseline PET and the satellite-derived PET input, though variation in streamflow simulations overall is negligible. For instance, the upper zone states, responsible for the high flows of a hydrograph, show a profound difference, while simulation of the peak flows tend to show little variation in the timing and magnitude. Using the spatial PET input, the lower zone states show improvement with simulating the recession limb and baseflow portion of the hydrograph. We anticipate that through a better understanding of the relationship between model structure, model states, and simulated streamflow we will be able to diagnose why simulations of discharge from the forecast model have failed to improve when provided seemingly more representative input data. Identifying model limitations are critical to demonstrating the full benefit of a satellite data for operational use.