Accurately simulating crop photosynthate allocation under water stress is critical for predicting both food security and ecosystem carbon sequestration (SOC inputs). Current crop models often rely on static or growth-stage-fixed partitioning coefficients, which limits their ability to capture the physiological plasticity of crops responding to fluctuating environmental conditions. This study develops a water-driven, stage-dependent carbon allocation scheme within the Agro-C model to better represent crop responses to soil moisture variability. The scheme dynamically adjusts photosynthate partitioning coefficients for roots (PR) and leaves (PL), integrates the yellow-to-green leaf ratio (YGR), and incorporates a water stress–induced leaf senescence module. By linking carbon allocation to both soil moisture and crop development, the approach improves the representation of physiologically regulated allocation processes and enhances the realism of crop simulations. Model evaluation using extensive datasets for maize and wheat demonstrates substantial improvements in simulation accuracy, with R<sup>2</sup> values reaching 0.77–0.95 for aboveground biomass (AGB) and 0.62–0.83 for belowground biomass (BGB). These results underscore the importance of dynamically representing carbon allocation under water stress and offer an improved framework for simulating carbon–water interactions in agroecosystems.