Abstract. The operational Simplified Surface Energy Balance (SSEBop) approach was applied on 14 Landsat 5 thermal infrared images for mapping daily actual evapotranspiration (ETa) fluxes during the spring and summer seasons (March–October) in 2006 and 2007. Data from four large lysimeters, managed by the USDA-ARS Conservation and Production Research Laboratory were used for evaluating the SSEBop estimated ETa. Lysimeter fields are arranged in a 2 × 2 block pattern with two fields each managed under irrigated and dryland cropping systems. The modeled and observed daily ETa values were grouped as "irrigated" and "dryland" at four different aggregation periods (1-day, 2-day, 3 day and "seasonal") for evaluation. There was a strong linear relationship between observed and modeled ETa with R2 values ranging from 0.87 to 0.97. The root mean square error (RMSE), as percent of their respective mean values, were reduced progressively with 28, 24, 16 and 12% at 1-day, 2-day, 3-day, and seasonal aggregation periods, respectively. With a further correction of the underestimation bias (−11%), the seasonal RMSE reduced from 12 to 6%. The random error contribution to the total error was reduced from 86 to 20% while the bias' contribution increased from 14 to 80% when aggregated from daily to seasonal scale, respectively. This study shows the reliable performance of the SSEBop approach on the Landsat data stream with a transferable approach for use with the recently launched LDCM (Landsat Data Continuity Mission) Thermal InfraRed Sensor (TIRS) data. Thus, SSEBop can produce quick, reliable and useful ET estimations at various time scales with higher seasonal accuracy for use in regional water management decisions.
Calibration of the Thermal Infrared Sensor on the Landsat Data Continuity Mission
