Real-Time Variational Assimilation of Hydrologic and Hydrometeorological Data into Operational Hydrologic Forecasting

Abstract

Variational assimilation (VAR) of hydrologic and hydrometeorological data into operational hydrologic forecasting is explored. The data assimilated are the hourly real-time observations of streamflow and precipitation, and climatological estimates of potential evaporation (PE). The hydrologic system considered is a single headwater basin for which soil moisture accounting and routing are carried out in a lumped fashion via the Sacramento model (SAC) and the unit hydrograph (UH), respectively. The control variables in the VAR formulation are the fast-varying SAC soil moisture states at the beginning of the assimilation window and the multiplicative adjustment factors to the estimates of mean areal precipitation (MAP) and mean areal potential evaporation (MAPE) for each hour in the assimilation window. In a separate application of VAR as a parameter estimation tool, the estimation of empirical UH is also explored by treating its ordinates as the control variables. To evaluate the assimilation procedure thus developed, streamflow was forecast with and without the aid of VAR for three basins in the southern plains under the assumption of perfectly forecast future mean areal precipitation (FMAP). The streamflow forecasts were then compared with each other and with those based on persistence and the state space-based state-updating procedure, the state-space Sacramento model (SS-SAC). The results indicate that the VAR procedure significantly improves the accuracy of the basic forecast at short lead times and compares favorably with SS-SAC.