State and parameter update in a coupled energy/hydrologic balance model using ensemble Kalman filtering

The capability to accurately monitor and describe daily evapotranspiration (ET) in a cost effective manneris generally attributed to hydrological models. However, continuous solution of energy and water balanceprovides precise estimations only when a detailed knowledge of sub-surface characteristics is available.On the other hand, residual surface energy balance models, based on remote observation of land surfacetemperature, are characterised by sufficient accuracy, but their applicability is limited by the lack of highfrequency and high resolution thermal data. A compromise between these two methodologies is representedby the use of data assimilation scheme to include sparse remote estimates of surface fluxes intocontinuous modelling. This paper aims to test the combined use of coupled energy/water budget modeland data assimilation schemes to assess daily evapotranspiration at field scale in a typical Mediterraneanenvironment characterised by sparse olive trees. The continuous model was applied at hourly scale usingremote multispectral images in the short-wave and standard meteorological information. The model wasvalidated by means of contextual micro-meteorological information adopting the best available parameterisation(including root zone depth). The validation suggests an accuracy of about 35Wm 2 for thehourly turbulent fluxes and of about 0.3–0.4 mm/d for the daily ET. Successively, two data assimilationschemes based on the ensemble version of the Kalman filter were tested under the hypothesis of absenceof information about the root zone depth. The application of a dual state-parameter filter (2EnKF) allowsto obtain results very close to the ‘optimal’ ones independently from the value adopted as initial of rootzone depth. Moreover, these results were obtained both by assimilating synthetic ‘perfect’ observationsand ‘real’ remotely-derived estimations of latent heat flux. The methodology, which combines a coupledenergy/water budget model and a dual state-parameter assimilation scheme, seems to be suitable to provideprecise estimations of daily ET also when information on root zone depth are absent or not enoughaccurate.