|Kustas, William - Bill|
|Evett, Steven - Steve|
Submitted to: Advances in Water Resources
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 6/7/2012
Publication Date: N/A
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 the 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 taken into account. 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: The two source energy balance model (TSM) can estimate evapotranspiration (ET) of vegetated surfaces, which has important applications in water resources management for irrigated crops. The TSM uses soil (TS) and canopy (TC) surface temperatures to solve the energy budgets of these layers separately, and combines estimates of instantaneous latent heat flux, which can be scaled to daily ET. Operationally, usually only composite surface temperature (TR) measurements are available. For surfaces with non-random spatial distribution of vegetation such as row crops, TR often includes both soil and vegetation, which may have vastly different temperatures. Therefore, TS and TC must be derived from a single TR measurement using simple linear mixing, where an initial estimate of TC is calculated, and the temperature–resistant network is solved iteratively until energy balance closure is reached. Two versions of the TSM were compared, where a single TR measurement was used (TSM-TR) and separate measurements of TS and TC were used (TSM-TS-TC), where TSM-TS-TC did not require an iterative solution. Using stationary infrared thermometers viewing an irrigated cotton crop, ET estimates using two versions of the TSM were compared with ET measured by large, monolythic lysimeters. The TSM-TR version resulted in calculated vs. measured root mean square error (RMSE), mean absolute error (MAE) and mean bias error (MBE) of ET of 0.76, 0.58, and 0.07 mm/d, respectively. The TSM-TS-TC version resulted in larger error rates, where respective RSME, MAE, and MBE were 1.2, 1.1, and 0.16 mm/d. Also, the TSM-TS-TC appeared to incorrectly partition energy fluxes to the soil and canopy to a greater extent compared with the TSM-TR version. This may have resulted from over-estimates of soil and canopy boundary layer resistances, which are fixed in the TSM-TS-TC version but allowed to vary in the TSM-TR version.