Modeling tree responses to soil water variability guides irrigation to account for soil winter reserves

Abstract High‐yield almond ( Prunus amygdalus ) production requires irrigation to support soil water availability throughout the summer. We aimed to develop tools that project almond trees’ water requirements and then integrate them into irrigation management. We postulated that deficit irrigation would limit root allocation and reduce irrigation efficiency. Thus, we monitored soil water availability (soil water content and potential evapotranspiration) and tree physiology (transpiration and trunk circumference) under 600, 900, or 1250 mm summer irrigations. A soil‐tree model was trained to predict trees’ transpiration as the soil dried between irrigation events. The model included an empirical function for tree transpiration at variable soil water potentials (50% loss by −1 MPa). Field records corroborated the soil‐tree model projections that 600 mm irrigation reduces soil water potential to −1 MPa and limits transpiration after winter soil water reserves deplete. Trees at deficit irrigation did grow deep roots to extract soil winter reserves, thus disputing our original notion. A 900 mm irrigation matched transpiration and maintained soil at −0.6 MPa. The 1250 mm irrigation exceeded transpiration and narrowed trees’ water uptake to the upper 50 cm. The reciprocity between soil water and transpiration dictates that predetermined irrigation would limit or exceed transpiration. The soil‐tree model could project transpiration responses to soil water variability, thereby supporting irrigation by trees’ transpiration. The model uses soil water dynamics, rather than insular water potential measures, to account for spatial discrepancies between water application and uptake depths. Hence, the soil‐tree model lays a computational framework for precision irrigation by automated sensory.