Grain yield response to consumptive water use a.k.a. evapotranspiration (ET c ) is a critical dimension of food‐water nexus in irrigated agroecosystems. With the largest water footprint, irrigated corn production in the U.S. must be assessed for its ET c and water use efficiency (WUE) at a scale meaningful for producers and water managers. Field experiments significantly inform our understanding of how corn yield responds to ET c at the field/plot‐level, but their collective synergism remains untapped. This analysis uses a literature synthesis of existing measured data from nationwide experiments that measured corn ET c , to build models that elucidate and predict corn ET c and WUE under diverse environment and on‐farm management. The resulting synthesis ( n = 1,362) captured wide ranging conditions of mean aridity, environmental variability, management, and crop outcomes, providing an unprecedented opportunity to train data‐driven models. Random forest models effectively predicted seasonal total ET c and seasonal mean WUE using a handful of environmental and management‐based predictors, demonstrating RMSEs of 33 mm (5.1%) and 0.28 kg m −3 (10.4%), respectively. Irrigation depth was the most important followed by total precipitation received during the growing season in determining ET c and WUE. Trained on the largest compilation of experimental data sets of corn ET c , these data‐driven models represent nuanced corn water production functions that also account for weather and agronomy besides describing economic yield‐ET c response.
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Meetpal S. Kukal (2024) studied this question.
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