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Seminar Abstract

Ed Maurer - May 7, 2002

 

Hydrologic Predictability in the Mississippi River Basin

Climatic phenomena, such as the El Nino/Southern Oscillation, have been shown to be related to local patterns of land surface hydrologic variables, such as streamflow. Persistence of the climate signal can be exploited to make seasonal forecasts of precipitation and temperature, which in turn can be used to predict runoff and streamflow. For seasonal forecast lead times, the predictability of runoff, and ultimately streamflow, is derived both from predictability of the climatic forcing signal and persistence in the initial moisture conditions of the land surface, specifically hydrologic storage as soil moisture and snow water equivalent. Identification of the importance of the space-time distribution of hydrologic storage has important implications for observation networks and for validation of remotely sensed products of snow and soil moisture. Relationships are evaluated among surface hydrologic variables, and their implications for hydrologic forecasting, using a derived data set of soil moisture, snow water equivalent, and runoff generated using a macroscale hydrologic model forced with gridded surface observations. Statistical analysis of the data set provides insights into the predictability of runoff over the Mississippi River basin, for forecast lead times up to one year.

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