Submitted to: Decennial National Irrigation Symposium
Publication Type: Proceedings
Publication Acceptance Date: August 30, 2010
Publication Date: December 5, 2010
Citation: Colaizzi, P.D., Evett, S.R., Howell, T.A., Gowda, P., Oshaughnessy, S.A., Tolk, J.A., Kustas, W.P., Anderson, M.C. 2010. Two source energy balance model-refinements and lysimeter tests in the Southern High Plains. In: Proceedings of the 5th Decennial National Irrigation Symposium, December 5-8, 2010, Phoenix, Arizona. Paper No:IRR10-9701.2010 CDROM. Interpretive Summary: Irrigation of crops is important to maintain abundant food for a growing population. However, crop irrigation requires large amounts of water and energy. Both water and energy are becoming less available and more expensive. Therefore, it is important for farmers to conserve water and energy when irrigating crops. Conserving water and energy requires good irrigation management methods. One way to manage irrigation is by sensing crop temperature using infrared thermometers. The crop temperature is related to the rate of crop water use, which in turn is related to need for irrigation. When the crop does not completely cover the soil, which commonly occurs for row crops, the soil temperature beneath the crop will influence the crop temperature that is measured by the infrared thermometer. In order to get accurate estimates of the rate of crop water use, the influence of the soil temperature must be accounted for. We developed a new mathematical model that more accurately accounts for the influence of soil temperature on the infrared thermometer. This model was tested against actual measurements of crop water use, and the model greatly improved the accuracy of crop water use estimated with the infrared thermometer. This improved the usefulness of using crop temperature for irrigation management. This will help farmers continue to produce crops for a growing population while using less water and energy.
Technical Abstract: A thermal two-source energy balance model (TSM) was evaluated for predicting daily evapotranspiration (ET) of alfalfa, corn, cotton, grain sorghum, soybean, and wheat in a semiarid, advective environment. Crop ET was measured with large, monolythic weighing lysimeters. The TSM solved the energy budget of soil and vegetation using a series resistance network, and one-time-of-day latent heat flux estimates were scaled to daily ET using the ASCE Standardized Reference ET equation for a short crop. The TSM included several refinements, including an improved method to account for the nonrandom spatial distribution of vegetation for row crops with partial canopy cover. Root mean squared error, mean absolute error, and mean bias error were 1.1 (27%), 0.82 (21%), and -0.031 (-0.78%) mm d-1, respectively, between measured and modeled daily ET for all crops. The TSM refinements will improve the accuracy of remote sensing-based ET maps, which is imperative for water resource management.