Evaluation of a satellite-derived model parameterized by three soil moisture constraints to estimate terrestrial latent heat flux in the Heihe River basin of Northwest China.

Satellite-derived terrestrial latent heat flux (LE) models are useful tools to understand regional surface energy and water cycle processes for terrestrial ecosystems in the Heihe River basin (HRB) of Northwest China. This study developed a satellite-derived hybrid LE model parameterized by three soil moisture (SM) constraints: SM, relative humidity (RH), and diurnal air temperature range (DT); and assessed model performance and sensitivity. We used MODerate Resolution Imaging Spectroradiometer (MODIS) and eddy covariance (EC) data from 12 EC flux tower sites across the HRB. The hybrid model was trained using observed LE over 2012/2013-2014, and validated using observed LE for 2015 and leave-one-out cross-validation. The results show that the three SM constraints schemes exhibited some modeling differences at the flux tower site scale. LE estimation using SM achieved the highest correlation (R ²  = 0.87, p < 0.01) and lowest root mean square error (RMSE = 20.1 W/m ² ) compared to schemes using RH or DT schemes. We then produced regional daily LE maps at 1 km × 1 km across the HRB for 2013-2015. Regional analysis shows that our LE estimates from all three constraint models exhibited large spatial variability and strong seasonal and annual variations, attributed to differences in parameterizing the model water constraints. This study provides data and model based evidence to improve satellite-derived hybrid LE models with regard to water constraints.
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