Hourly and Daytime Evapotranspiration from Grassland Using Radiometric Surface Temperatures

Abstract

Determination of evapotranspiration (E) is needed for many applications in agriculture, hydrology, and meteorology. The spatial variability of leaf area index (LAI) and soil water availability makes it impractical to model E over heterogeneous lands using ground-based techniques. Remote sensing can be a good source for both LAI and radiometric surface temperature (Ts) estimates. However, remotely sensed soil moisture content is not suitable for E prediction. In this study, we propose a procedure to estimate E using Ts. The method uses a dimensionless temperature ΔT, defined as (Ts – Ta)/(Tmax – Ta), where Ta is the air temperature and Tmax is the surface temperature that would occur if all the net radiation (Rn) was converted to sensible heat flux and no evaporation occurred. This approach has been tested on data from two grassland sites in Oklahoma and Kansas. Root mean square differences between hourly predicted and measured E ranged from 30 to 50 W m−2. The slope and r2 for the zero-intercept linear regression between hourly estimated and measured E ranged from 1.01 to 1.37 and 78 to 0.94, respectively. Daytime conservation of evaporative fraction (EF = E/Rn) was used to extrapolate from hourly to daytime E. The slope and r2 of the linear regression between daytime estimated and measured E ranged from 0.89 to 1.07 and 0.69 to 0.9, respectively. These results demonstrate that, for grassland, the model may give good estimates of E when Ta and Ts are available.