|PORTER, DANA - Texas Agrilife Extension|
|MAREK, THOMAS - Agrilife Research|
|IRMAK, SUAT - University Of Nebraska|
Submitted to: Applied Engineering in Agriculture
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 12/1/2011
Publication Date: 8/14/2012
Citation: Porter, D.O., Gowda, P., Marek, T.H., Howell, T.A., Irmak, S., Moorhead, J.E. 2012. Sensitivity of grass and alfalfa reference evapotranspiration to weather station sensor accuracy. Applied Engineering in Agriculture. 28(4):543-549.
Interpretive Summary: Evapotranspiration (ET) is defined as a measure of the total water demand through evaporation from soil and transpiration of plants to the atmosphere. It is said to equal potential ET (maximum ET for a given set of atmospheric conditions) when there is ample water available. It is the preferred term for use in estimating the potential ET of a crop. Reference ET can be accurately computed from meteorological data recorded from weather stations that are properly sited and instrumented with calibrated sensors. In this study, we conducted a sensitivity analysis to determine the relative effects of measurement errors in climate data input parameters on the accuracy of calculated reference crop ET using the standardized reference ET equation. Results indicated that reference crop ET was most sensitive to measurement errors in wind speed and air temperature followed by solar radiation. Further, data sensitivity was found greater during the mid-summer growing season.
Technical Abstract: A sensitivity analysis was conducted to determine the relative effects of measurement errors in climate data input parameters on the accuracy of calculated reference crop evapotranspiration (ET) using the ASCE-EWRI Standardized Reference ET Equation. Data for the period of 1991 to 2008 from an automated weather station located at the USDA-ARS Conservation and Production Research Laboratory at Bushland, Texas was used for the analysis. Results indicated that grass (ETos) and alfalfa (ETrs) reference crop ET, were most sensitive to measurement errors in wind speed and air temperature followed by solar radiation, that data sensitivity was greater during the mid-summer growing season.