Modeling Spring Wheat Production as Influenced by Climate and Irrigation

• Main Author: Rasmussen, V. Philip, Jr.
• Format: Others
• Published: DigitalCommons@USU 1976
• Subjects: modeling; spring; wheat; production; influence; climate; irrigation; Soil Science
• Online Access: https://digitalcommons.usu.edu/etd/3579; https://digitalcommons.usu.edu/cgi/viewcontent.cgi?article=4585&context=etd

A model has been developed that predicts spring wheat grain and dry matter yield. Preliminary tests show very favorable results when predicting grain yield in two different climatic regimes, one being a dryland and another being an irrigated area. The strenghts of the model lie in its simplicity, relatively available input data, and low computer processing time cost. Weakness of the model stem from the assumptions that allow its simplicity. The basic assumption in the model is that grain and dry matter yield can be related to the ratio of actual to potential transpiration, computed for each of five phenological stages. Actual and potential evapotranspiration, transpiration, and soil evaporation are obtained in the model by numerical operations on a potential evapotranspiration/potential soil evaporation array obtained by empirical formulae or pan data, and a modified crop coefficient. Soil water status is monitored in the model by taking into account the balance of irrigation, drainage, precipitation, soil water storage and evapotranspiration. Phenological data is computed by a simple numerical formula utilizing maximum and minimum temperatures during the season. Good agreement was found in comparing predicted versus actual heading date for four varieties over four different years. A field study was carried out to aid in model calibration and testing. A continuous variable plot design, with two replications of each of five spring wheat varieties (two soft whit spring wheats and three hard red spring wheats)> This allowed a large number of data points to be measured that related yield to many water levels within the soil. Although this design leads to difficulties in classical statistical analysis, it was shown to be especially useful in calibration of a model of the type shown herein.