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Apparent thermal conductivities of loamy sand, loam, and silty clay loam soils were measured with a cylindrical heat probe at several water contents and temperatures. Values of λ were also calculated with the de Vries model. Results show that the model may be used satisfactorily to calculate λ. However, improvements may be needed to account for the enhancement of vapor transfer at high temperatures (45° C) in medium to fine textured soils. The heat probe method of measuring the thermal conductivity requires a correction factor to allow for errors due to the entrapment of air at the surface of the heat probe, when used at water contents ranging from 0 to about 30% of saturation.The contribution of vapor distillation to thermal conductivity was analyzed by comparing λ at 25 and 45° C. The ratios λ45/λ25 were nearly equal to unity when < 5% of total pore space was filled with water. The ratios increased, due to vapor distillation, as water filled the pores and reached maximum values of 2.17, 2.71, and 2.96 when 22, 27, and 35% of total pore space was filled with water, corresponding to soil water potentials of −0.8, −9.0, and −8.0 bars for loamy sand, loam, and silty clay loam, respectively. As the water content increased further, the ratios decreased and approached unity when > 50% of total space was filled with water.The apparent thermal conductivity was independent of water content at very low water contents. The water molecules are in layers only a few molecules thick. The water content below which the apparent thermal conductivity is not affected by water content is a function of the soil temperature and the clay content. In our experiments these water contents were 0.03 and 0.05 cm3/cm3 at 45° C and 0.13 and 0.18 cm3/cm3 at 25° C for the loam and silty clay loam respectively.

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The AquaCrop model was used to simulate maize growth and soil water content under full and deficit irrigation managements as 1.2, 1, 0.8, and 0.6 of the potential crop water requirement. Generally, the RMSEs in simulating soil water content in calibration and validation were 0.01-0.039 and 0.012-0.037 m 3 m −3 , respectively, that overall corresponds to 3-14 % error. For the in-season biomass development, the RMSEs in calibration varied between 2.16 and 2.73 Mg ha −1 , while they varied between 1.97 and 5.19 Mg ha −1 in validation for the four irrigation managements. The model showed poor performance for simulating biomass late in the season under deficit irrigation managements. The RMSEs of final grain yield simulation were 0.71 and 1.77 Mg ha −1 that corresponded to 7 and 18 % error in calibration and validation, respectively. Likewise, the RMSEs for simulating the final biomass in calibration and validation were 1.29 and 2.21 Mg ha −1 that equals to 6 and 10 % error, respectively. Results demonstrated that AquaCrop is a useful decision-making tool for investigating deficit irrigations and maize growth in the region. However, in agreement with the findings in earlier studies on AquaCrop, the model showed insufficient accuracy in simulating final grain yield and biomass under moderate to severe water stresses. It is suggested that AquaCrop would benefit of including some calibrating parameters about the root distribution pattern in the soil because it is a water-driven model and highly depends on the accurately simulated water uptake from the soil profile.

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