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A model is presented for calculating the daily evaporation rate from a crop sur• face. It applies to a row crop canopy situation in which the soil water supply to the• plant roots is not limited and the crop has not come into an advanced stage of maturation or senescence. The crop evaporation rate is calculated by adding the soil surface and plant surface components (each of these requiring daily numbers for the leaf area index), the potential evaporation, the rainfall, and the net radiation above the canopy. The evaporation from the soil surface E8 is calculated in two stages: (1) the constant rate stage in which E, is limited only by the supply of energy to the surface and (2) the falling rate stage in which water movement to the evaporating sites near the surface is controlled by the hydraulic properties of the soil. The evaporation from the plant surfaces Ep is predicted by using an empirical relation based on local data, which shows how Ep is related to Eo through the leaf area index. The model was used to obtain the total evaporation rate E ----E8 q-Ep of a developing grain sorghum (Sorghum bicolor L.) canopy in central Texas. The results agreed well with values for E measured directly with a weighing lysimeter. 1958; Blaney, 1959; Jensen and Haise, 1963]. Recently, Jensen et al. [1969] developed an improved plant factor used in predicting evaporation that can be adjusted to reflect changes in surface wetness caused by irrigation or rainfall.

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Accurate evaluation of the soil water reserves available for plant use is vital in developing optimum water management for crop production in marginally dry regions. Laboratory estimates of the upper and lower limits of soil water availability used to calculate the soil water reservoir often deviate significantly from the limits measured in the field. To make a unified and broad assessment of the accuracy of laboratory measurements for estimating field soil water, we obtained and evaluated a comprehensive data base of field‐measured upper and lower limits of the soil water reservoir. The field‐measured upper limit was taken as the water content at which drainage from a prewetted soil had practically ceased. The lower limit was taken as the water content of the soil at which plants were practically dead or dormant as a result of the soil water deficit. These field‐measured limits were compared to laboratory measurements at −0.33 and −15 bar made on samples removed from each field site. A total of 401 observations were available for the comparisons of −15 bar measurements to the field‐measured lower limits and 282 observations of −0.33 bar measurements were available for comparison with the field‐measured upper limit. Variation often existed within a soil series at a particular site for the field‐measured upper and lower limits. However, the differences between the field‐measured limits, the total available water reservoir, were relatively constant. Crop species caused only minor differences in the lower limit water content for the upper part of the soil profile where root length density was apparently above some critical limit. However, some annuals extracted water to greater depths than others. The laboratory estimates of the upper limit obtained by −0.33 bar water contents were significantly less than the field‐measured drained upper limit for sands, sandy loams, and sandy clay loams and were significantly more than field measurements for silt loams, silty clay loams, and silty clays. The laboratory estimates of the lower limit obtained by −15 bar water content measurements were significantly less than field lower limit measurements for sands, silt loams, and sandy clay loams and significantly more than field observations for loams, silty clays, and clays. Because our study included relatively few measurements of loamy sands, silts, sandy clays, and clays, it was difficult to generalize about differences in field‐measured and laboratory‐estimated water limits for those textures. The results suggest that if absolute accuracy is necessary in water balance calculations, laboratory‐estimated soil water limits should be used with caution and field‐measured limits, if available, would be preferred.

Exposure of plants to low temperature (LT) produces a myriad of measurable changes in morphological, biochemical, and physiological characters that are often highly correlated with plant cold tolerance. These complicated responses have made it difficult to separate cause‐and‐effect adjustments to LT, emphasizing the need for a descriptive framework for the integration of current knowledge so that research efforts can be better focused. The objective of this study was to construct a functional model that complies with the known LT responses of cereals so production risks, cause‐and‐effect processes, and genetic theories can be systematically investigated. In the model, a series of equations describe acclimation, dehardening, and damage due to LT stress. A modular design permits modification and allows the model to be interfaced with other simulation models that input or compute daily measurements of soil temperature and phonological development. LT tolerance is estimated on a daily basis relative to phenological stage and the input of a genetic coefficient is required. Operation of the model is consistent with recent interpretation of LT‐gene regulation and it is especially sensitive to the switching signals that down‐regulate LT‐gene expression in plants maintained for long periods of time in the optimum temperature range for cold acclimation. Simulation studies have also shown that small differences in cultivar genetic potential translate into large differences in LT tolerance when the cumulative effects of LT stress enter the critical range for overwinter survival. The model has been field validated for cereals overwintered in Saskatchewan, Canada, but it also has potential application in the simulation of LT responses of a wide range of species and climates.