The photosynthetic light–response (P_n/I) curve is a crucial tool for accurately estimating photosynthetic parameters. However, selecting the most suitable model from numerous available light–response models is still difficult because of the complex canopy structure. This study aimed to evaluate the performance of different models, including the rectangular hyperbolic model (RHM), non-rectangular hyperbolic model (NRHM), exponential model (EM), and modified rectangular hyperbolic model (MRHM), in modeling P_n/I curves and estimating photosynthetic parameters for rice leaves at various canopy positions. The results showed that the NRHM demonstrated the highest accuracy, and the EM was identified as the most ideal in estimating P_n. The RHM consistently overestimated the maximum net photosynthetic rate (P_nmax), apparent quantum efficiency (α), dark respiration rate (R_d), and light compensation point (LCP) while underestimating light saturation point (LSP) for all rice leaves. The NRHM overestimated P_nmax, underestimated LSP, and accurately estimated LCP for all leaves, and overestimated α and R_d for top leaves but performed well for lower leaves. The EM excelled in estimating P_nmax and LSP for all leaves and performed well in estimating α for the top third and fourth leaves, R_d for the top four leaves, and LCP for the top six leaves. The MRHM was effective in estimating P_nmax but consistently overestimated α, R_d, and LSP for all leaves.

The distinct co-occurrence of soil water content (SWC) and vapor pressure deficit (VPD) influences ecosystem water use efficiency (WUE) by modifying the synergistic relationship between gross primary productivity (GPP) and evapotranspiration (ET), yet how they impact each other remains unclear in agricultural ecosystems. Based on long-term eddy covariance flux data (2005–2014) observed at a rainfed maize site in Northeast China, we examined how SWC and VPD affect WUE by decomposing it into gross primary productivity to transpiration ratio (GPP/T) and transpiration to evapotranspiration ratio (T/ET). Results showed that WUE was more sensitive to VPD than SWC. Increasing VPD directly suppressed WUE under all soil moisture conditions, whereas SWC had a context-dependent effect: higher SWC reduced WUE under low VPD but enhanced WUE under high VPD. The underlying mechanism was that changes in GPP/T (plant physiological regulation) dominated the WUE responses to both SWC and VPD (contributing 70.25–83.30% and 67.89–87.96%, respectively), while T/ET (evapotranspiration partitioning) played a minor role (<18%). Therefore, to improve WUE under future drier climates, agronomic practices should focus on enhancing photosynthetic capacity and stomatal regulation (e.g., selecting drought-tolerant varieties, optimizing nitrogen supply) rather than solely reducing soil evaporation. Furthermore, supplemental irrigation applied specifically during periods of high VPD (when atmospheric demand is strong) can effectively enhance WUE, as soil moisture becomes critically beneficial under such conditions. These findings provide a mechanistic basis for improving water use efficiency in rainfed maize systems under climate change.