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Hourly and Daytime Evapotranspiration from Grassland Using Radiometric Surface Temperatures
Author(s) -
Suleiman Ayman,
Crago Richard
Publication year - 2004
Publication title -
agronomy journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.752
H-Index - 131
eISSN - 1435-0645
pISSN - 0002-1962
DOI - 10.2134/agronj2004.3840
Subject(s) - evapotranspiration , daytime , environmental science , grassland , sensible heat , linear regression , bowen ratio , hydrology (agriculture) , water content , flux (metallurgy) , transpiration , soil water , latent heat , atmospheric sciences , soil science , meteorology , mathematics , geography , agronomy , statistics , materials science , geotechnical engineering , engineering , metallurgy , biology , geology , ecology , photosynthesis , botany
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 ( T s ) estimates. However, remotely sensed soil moisture content is not suitable for E prediction. In this study, we propose a procedure to estimate E using T s . The method uses a dimensionless temperature Δ T , defined as ( T s – T a )/( T max – T a ), where T a is the air temperature and T max is the surface temperature that would occur if all the net radiation ( R n ) 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 r 2 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 / R n ) was used to extrapolate from hourly to daytime E . The slope and r 2 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 T a and T s are available.