Estimating Plant‐Available Water Across a Field with an Inverse Yield Model

The variability of crop yield in dryland production is primarily affected by the spatial distribution of plant‐available water even for seemingly uniform fields. The most productive midwestern soils, which are loess caps over glacial till or outwash, can have a wide range of water‐holding capacities in individual fields because of landscape processes and management. An inverse yield model was created as a robust method to quantify the spatial and temporal role of plant‐available water on large agricultural fields to improve management options in precision agriculture. Plant‐available water maps for a field were estimated from yield maps using inverse water‐budget modeling based on measurements of solar radiation, temperature, precipitation, and vapor pressure deficit. The model presented in this paper was applied to 5 yr of corn ( Zea mays L.) yield‐monitor data from a field in Waunakee, WI, having three soil mapping units, Plano silt loam (fine‐silty, mixed, mesic Typic Argiudoll), St. Charles silt loam (fine‐silty, mixed, mesic Typic Hapludalf), and Griswold loam (Fine‐loamy, mixed, mesic Typic Argiudoll). The comparison of measured and inverse‐modeled plant‐available water suggests that the simple inverse yield model produces reasonable results in drier years with uncertainties of about 28 mm of plant‐available water. The model helped to quantify the role of plant‐available water in determining crop yield. Because of limited input requirements, the model shows promise as a practical tool for using precision farming to improve management decisions, and as a tool to obtain input for landscape‐based models.