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Soil water assessment model for several crops in the high plains

Robinson, J.M., Hubbard, K.G.
Agronomy journal 1990 v.82 no.6 pp. 1141-1148
Zea mays, Triticum aestivum, Sorghum bicolor, Glycine max, prediction, soil water content, soil water balance, mathematical models, meteorological data, precipitation, evapotranspiration, Nebraska, Wyoming, South Dakota
Soil properties, soil water content and precipitation vary widely within the High Plains of the USA. Reliable estimates of crop water status have been hampered by a general sparsity of soil water monitoring. This study examined the feasibility of determining soil water status using a soil water balance model. Soil water content was measured under corn (Zea mays L.), wheat (Triticum aestivum L.), sorghum (Sorghum vulgare L.) and soybean (Glycine max L.) at different sites in the High Plains during 1986 and 1987. Surface weather data collected from the High Plains Automated Weather Data Network (AWDN) served as input to a model that estimates evapotranspiration (ET) and soil water content on a daily time step. Atmospheric demand was represented by potential evapotranspiration (ETp) calculated from the Penman method. Model estimates of total water in the root zone were compared to measured values using statistical measures including the D index of agreement. Comparison at one site between measured and estimated soil water by individual soil layers beneath a corn indicated that water content was slightly underestimated in the upper layers and overestimated in the lower layers. The performance of the model in estimating total soil water over a range of soil types, crops and weather was satisfactory, with the majority of D index values exceeding 0.75. Based on the results of this study, we conclude that it is now possible to accurately estimate soil water conditions in a timely fashion under reasonably flat terrain, provided near-real time weather data are available.