Satellite-based evapotranspiration in hydrological model calibration

Hydrological models are usually calibrated against observed streamflow (Q_obs), which is not applicable for ungauged river basins. Afew studies have exploited remotely sensed evapotranspiration (ET_RS) for model calibration but their effectiveness on streamflow simulation remains uncertain. This paper investigates the use of ET_RS in the hydrological calibration of a widely used land surface model coupled with a source-sink routing scheme and global optimization algorithm for 28 natural river basins. A baseline simulation is a setup based on the latest model developments and inputs. Sensitive parameters are determined for Q_obs and ET_RS-based model calibrations, respectively, through comprehensive sensitivity tests. The ET_RS-based model calibration results in a mean Kling-Gupta Efficiency (KGE) value of 0.54 for streamflow simulation; 61% of the river basins have KGE > 0.5 in the validation period, which is consistent with the calibration period and provides a significant improvement over the baseline. Compared to Q_obs, the ET_RS calibration produces better or similar streamflow simulations in 29% of the basins, while further significant improvements are achieved when either better ET or precipitation observations are used. Furthermore, the model results show better or similar performance in 68% of the basins and outperform the baseline simulations in 90% of the river basins using model parameters from the best ET_RS calibration runs. This study confirms that with reasonable precipitation input, the ET_RS-based spatially distributed calibration can efficiently tune parameters for better ET and streamflow simulations. The application of ET_RS for global scale hydrological model calibration promises even better streamflow accuracy as the satellite-based ET_RS observations continue to improve.