Abstract
Satellite-based actual evapotranspiration (ETa) is becoming increasingly reliable and available for various water management and agricultural applications from water budget studies to crop performance monitoring. The Operational Simplified Surface Energy Balance (SSEBop) model is currently used by the US Geological Survey (USGS) Famine Early Warning System Network (FEWS NET) to routinely produce and post multitemporal ETa and ETa anomalies online for drought monitoring and early warning purposes. Implementation of the global SSEBop using the Aqua satellite’s Moderate Resolution Imaging Spectroradiometer (MODIS) land surface temperature and global gridded weather datasets is presented. Evaluation of the SSEBop ETa data using 12 eddy covariance (EC) flux tower sites over six continents indicated reasonable performance in capturing seasonality with a correlation coefficient up to 0.87. However, the modeled ETa seemed to show regional biases whose natures and magnitudes require a comprehensive investigation using complete water budgets and more quality-controlled EC station datasets. While the absolute magnitude of SSEBop ETa would require a one-time bias correction for use in water budget studies to address local or regional conditions, the ETa anomalies can be used without further modifications for drought monitoring. All ETa products are freely available for download from the USGS FEWS NET website.
Highlights
The estimation of actual evapotranspiration (ETa) is an important activity in crop and water management
The main objectives of this study are: (1) to present the methods used in creating the global SSEBop ETa product, (2) to conduct a first-order evaluation using flux tower eddy covariance ETa and precipitation data, and (3) to introduce the SSEBop ETa anomaly as a drought monitoring tool
Model outputs were created for every dekad
Summary
The estimation of actual evapotranspiration (ETa) is an important activity in crop and water management. The two most common principles in estimating ETa are water balance and energy balance approaches [3]. ETa is estimated as a function of soil moisture by tracking precipitation and other contributions (e.g., irrigation) in a controlled volume (e.g., root-zone storage). This is the physics-based simulation of ETa as implemented by prognostic hydrologic models, commonly described as land surface models (LSM) such as the Global Land
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