Evaluating Methods to Estimate Corn Evapotranspiration from Short-time Interval Weather Data
Sensors and dataloggers routinely provide weather data at hourly or shorter intervals. These data may be used with models to estimate daily evapotranspiration (ET) by integration of the short-time interval measurements. Three such models were compared—one a canopy temperature energy balance approach (CTEB) and two variations of the Penman-Monteith equation (P-Ms and P-Mw). In the P-Ms approach, a canopy resistance term based on sunlit stomatal resistance and canopy leaf area index was used. The P-Mw model used a weighted canopy resistance term based on stomatal resistance and leaf area index of sunlit and shaded foliage fractions. Bowen ratio energy balance (BREB) measurements of ET from a corn crop were compared to ET estimated by each model. On the average, model estimates were 10 to 13% higher than BREB values. As indicated by several indices, the performance of CTEB was better than the P-M models for 20-min intervals and daily ET rates. Results of the application of atmospheric stability corrections on the overall performance of the models were inconsistent. All models tracked the diurnal fluctuation of ET except under moderate to high wind conditions. All models agreed more closely with BREB when intervals with wind speed greater than 2 m s–1 were excluded. Possible explanations for this effect are discussed. No difference was found between P-Ms and P-Mw to justify the extra input data and calculation requirements of the latter approach.