Understanding plant water stress (PWS) in the soil-plant-atmosphere-continuum (SPAC) that connects water supply from soil, water demand from atmosphere, and plant self-regulation is a prerequisite for efficient irrigation in response to water scarcity. Currently, PWS can be defined in various ways, for example, based on environmental factors and/or plant-centric metrics. The environment-based metrics usually do not take plants into consideration. Regarding the existing plant-centric metrics, their interconnections and abilities to capture the physical water constraints from both soil water supply and atmospheric water demand are still unclear. This research investigates the theoretical foundations behind different PWS metrics, and assesses their efficacy and potentials for irrigation scheduling. This study first investigated the interconnections among different PWS metrics and the co-regulation of soil moisture and vapor pressure deficit (VPD) on the plant-centric metrics through an advanced process-based model, ecosys. We then use ecosys to test different PWS metrics’ performance in guiding irrigation in terms of water use, maize yield, and economic profits. The case study was conducted at sites across a dramatic rainfall gradient in Nebraska, the largest irrigation state in the United States Corn Belt. The ecosys simulation indicates that canopy water potential and stomatal conductance (gs) are the most effective plant-centric metrics in the SPAC system in indicating PWS. In addition, our findings show that using the plant-centric metrics-based irrigation schemes, which capture the co-regulation of soil moisture and VPD, can improve producers’ economic profits through water savings
