Model for Predicting Plant Yield as Influenced by Water Use¹

TLDR

The ratio of actual to potential dry matter yield is assumed to be directly related to the ratio of actual to potential transpiration. The study devised a model to predict plant yield, both total dry matter and grain, as a function of water use. The model is a simple, inexpensive computer simulation that estimates seasonal yields from irrigation, rainfall, and soil water storage, assuming soil evaporation decreases with the square root of time after wetting and with growth stage. The model achieved a good fit between predicted and measured dry matter yields for sorghum in Colorado, corn dry matter and grain yields in Israel, and corn grain yields in Nebraska, and the relative yield‑water use curve was sensitive to evaporation and transpiration assumptions but not to the soil water status–transpiration relationship.

Abstract

Abstract A model has been devised to predict plant yield, both total dry matter and grain, as a function of water use. The model is simple and inexpensive to run on a computer to determine seasonal yields as influenced by irrigation frequency and amount, rainfall, and soil water storage. A good fit of predicted vs measured dry matter yield of sorghum ( Sorghum vulgate L.) in Colorado, corn ( Zea mays L.) dry matter and grain yields in Israel, and corn grain yields in Nebraska, with various water application treatments, was found. A basic assumption is that the ratio of actual to potential dry matter yield is directly related to the ratio of actual to potential transpiration. Evaporation from the soil is assumed to decrease with the square root of time after wetting as well as with the stage of growth. The shape of the relative yield‐water use curve was found to be sensitive to the evaporation and transpiration assumptions made, but insensitive to the relation used to describe the influence of soil water status on transpiration.