School of Earth, Environmental, and Marine Sciences Faculty Publications and Presentations

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  • We developed an algorithm to estimate evapotranspiration based solely on satellite data.

  • Our model is able to track the seasonal changes in the flux tower observations.

  • The errors in the model ET output were lower than the MODIS ET product.

  • The modeled and observed ET strong relationship implies that our model has the potential to be applied to different ecosystems.


We introduce a different operational approach to estimate 8-day average daily evapotranspiration (ET) using both routinely available data and the Penman-Monteith (P-M) equation for canopy transpiration and evaporation of intercepted water and Priestley and Taylor for soil evaporation. Our algorithm considered the environmental constraints on canopy resistance and ET by (1) including vapor pressure deficit (VPD), incoming solar radiation, soil moisture, and temperature constraints on stomatal conductance; (2) using leaf area index (LAI) to scale from the leaf to canopy conductance; and (3) calculating canopy resistance as a function of environmental variables such as net radiation and VPD. Remote sensing data from the Moderate Resolution Spectroradiometer (MODIS) and satellite soil moisture data were used to derive the ET model. The algorithm was calibrated and evaluated using measured ET data from 20 AmeriFlux Eddy covariance flux sites for the period of 2003–2012. We found good agreements between our 8-day ET estimates and observations with mean absolute error (MAE) ranges from 0.17 mm/day to 0.94 mm/day compared with MAE ranging from 0.28 mm/day to 1.50 mm/day for MODIS ET. Compared to MODIS ET, our proposed algorithm has higher correlations and higher Willmott’s index of agreement with observations for the majority of the Ameriflux sites. The strong relationship between the model estimated ET and the flux tower observations implies that our model has the potential to be applied to different ecosystems and at different temporal scales.


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Publication Title

Agricultural and Forest Meteorology





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