ContextAgriculture is the major consumer of fresh water globally. However, climate change-induced water scarcity is challenging the freshwater resources to meet global crop water demands. Consequently, utilizing limited water resources efficiently is increasingly important in agriculture. Accurate diagnosis of crop water status and in-season demand is imperative for precision irrigation, as it allows growers to make informed decisions about fine-tuning in-season irrigation scheduling. Plant-based diagnostic approaches such as the critical saturated water accumulation (SWA) curve have been employed to diagnose the in-season crop water status in maize. However, it remains uncertain if this indicator applies to other crops including wheat. ObjectiveThe study aimed to develop and validate a model for quantifying the in-season water status of winter wheat using SWA curves and water diagnosis index (WDI). MethodsA four-year study was carried out by employing four water and two nitrogen rate treatments from 2019 to 2023 to establish the relationship between dry mass (DM) and SWA during the vegetative growth period of winter wheat. The effects of different water and nitrogen conditions on DM-SWA allometry were also analyzed. Besides, WDI was also derived as the ratio of the observed SWA value to the critical SWA value. ResultsThe allometric relationships between SWA and DM were used to construct critical SWA curves under sub-optimal and optimal nitrogen nutrition (N1: SWA = 5.34DM0.77; N2: SWA = 7.37DM0.83). The decrease in plant stem ratio and indirect soil nitrogen deficiency caused by water stress were the two main factors contributing to the decrease in plant WDI. However, uncertainties of observation and input data, model assumptions, model structure, and parameters led to a high degree of uncertainty in WDI, which affected its practical application. ConclusionsThe allometric relationships between SWA and DM can potentially be used as a diagnostic tool for assessing crop water status. Nitrogen deficiency would reduce the SWA without affecting its accumulation rate. Further research is required to employ WDI for plant water status diagnosis under field conditions. Significance/ImplicationsThe findings would assist in developing precision irrigation indicators for monitoring in-season plant water status, optimizing irrigation scheduling, selecting water-efficient cultivars, and enhancing wheat productivity.