The two source energy balance model (TSEB) can estimate evaporation (E), transpiration (T), and evapotranspiration (ET) of vegetated surfaces, which has important applications in water resources management for irrigated crops. The TSEB requires soil (T S) and canopy (T C) surface temperatures to solve the energy budgets of these layers separately. Operationally, usually only composite surface temperature (T R) measurements are available at a single view angle. For surfaces with nonrandom spatial distribution of vegetation such as row crops, T R often includes both soil and vegetation, which may have vastly different temperatures. Therefore, T S and T C must be derived from a single T R measurement using simple linear mixing, where an initial estimate of T C is calculated, and the temperature-resistance network is solved iteratively until energy balance closure is reached. Two versions of the TSEB were evaluated, where a single T R measurement was used (TSEB-T R) and separate measurements of T S and T C were used (TSEB-T C-T S). All surface temperatures (T S , T C , and T R) were measured by stationary infrared thermometers that viewed an irrigated cotton (Gossypium hirsutum L.) crop. The TSEB-T R version used a Penman-Monteith approximation for T C , rather than the Priestley-Taylor-based formulation used in the original TSEB version, because this has been found to result in more accurate partitioning of E and T under conditions of strong advection. Calculations of E, T, and ET by both model versions were compared with measurements using microlysimeters, sap flow gauges, and large monolythic weighing lysimeters, respectively. The TSEB-T R version resulted in similar overall agreement with the TSEB-T C-T S version for calculated and measured E (RMSE = 0.7 mm d À1) and better overall agreement for T (RMSE = 0.9 vs. 1.9 mm d À1), and ET (RMSE = 0.6 vs. 1.1 mm d À1). The TSEB-T C-T S version calculated daily ET up to 1.6 mm d À1 (15%) less early in the season and up to 2.0 mm d À1 (44%) greater later in the season compared with lysimeter measurements. The TSEB-T R also calculated larger ET later in the season but only up to 1.4 mm d À1 (20%). ET underestimates by the TSEB-T C-T S version may have been related to limitations in measuring T C early in the season when the canopy was sparse. ET overestimates later in the season by both versions may have been related to a greater proportion of non-transpiring canopy elements (flowers, bolls, and senesced leaves) being out of the T C and T R measurement view.

a b s t r a c tVariations of the crop water stress index (CWSI) have been used to characterize plant water stress and schedule irrigations. Usually, this thermal-based stress index has been calculated from measurements taken once daily or over a short period of time, near solar noon or after and in cloud free conditions. A method of integrating the CWSI over a day was developed to avoid the noise that may occur if weather prevents a clear CWSI signal near solar noon. This CWSI and time threshold (CWSI-TT) was the accumulated time that the CWSI was greater than a threshold value (0.45); and it was compared with a time threshold (CWSI-TT) based on a well-watered crop. We investigated the effectiveness of the CWSI-TT to automatically control irrigation of short and long season grain sorghum hybrids (Sorghum bicolor (L.) Moench, NC+ 5C35 and Pioneer 84G62); and to examine crop response to deficit irrigation treatments (i.e. 80%, 55%, 30% and 0% of full replenishment of soil water depletion to 1.5-m depth). Results from automated irrigation scheduling were compared to those from manual irrigation based on weekly neutron probe readings. In 2009, results from the Automatic irrigation were mixed; biomass yields in the 55% and 0% treatments, dry grain yields in the 80% and 0% treatments, and WUE in the 80%, 55%, and 0% treatments were not significantly different from those in the corresponding Manual treatments. However, dry grain yields in the 55% and 30% treatments were significantly less than those in the Manual control plots. These differences were due mainly to soil water variability in the beginning of the growing season. This conclusion is reinforced by the fact that IWUE for dry grain yield was not significantly different for 30% and 55% treatments, and was significantly greater for Automatic control at 80%. In 2010, there were no significant differences in biomass, dry grain yield, WUE, or IWUE for irrigation control methods when compared across the same amount treatments. Similar results between irrigation methods for at least the highest irrigation rate (80% of soil water depletion) in 2009 and among all irrigation treatment amounts in 2010 indicate that the CWSI-TT method can be an effective trigger for automatically scheduling either full or deficit irrigations for grain sorghum in a semi-arid region.Published by Elsevier B.V.

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