Water use efficiency (WUE), a key ecohydrological indicator linking carbon assimilation and vegetation water loss, is critical for understanding ecosystem responses under changing hydro-climatic conditions. Process-based land surface models (LSMs) are widely used to represent carbon-water interactions; however, their ability to simulate ecosystem-scale WUE across contrasting climates remains limited. This study evaluates the performance of the Interactions between Soil-Biosphere-Atmosphere model with A-g_s photosynthesis scheme (ISBA-A-g_s) implemented within the SURFEX land surface modelling platform in simulating gross primary productivity (GPP), evapotranspiration (ET), and WUE (GPP/ET) for maize grown under temperate (France, FR-Lam) and tropical semi-arid (India, Ind-IITH) climates. The model was driven by site-specific meteorological and vegetation variables across six growing seasons under sprinkler irrigation at FR-Lam, and two seasons (monsoon and winter) under alternate furrow irrigation (AFI) at Ind-IITH. Model calibration revealed that FR-Lam is characterized by relatively higher cuticular conductance and pronounced atmospheric control on stomatal behaviour, whereas at Ind-IITH, AFI-induced adjustments in mesophyll conductance and soil moisture stress thresholds. At FR-Lam, ISBA-A-g_s simulated the seasonal mean cumulative GPP, ET, and WUE of 1039 ± 20 gC m^-2, 610 ± 31 kg H₂O m^-2, and 1.70 ± 0.10 gC kg^-1 H₂O, respectively, as compared to measured values of 1026 ± 30 gC m^-2, 562 ± 42 kg H₂O m^-2, and 1.82 ± 0.11 gC kg^-1 H₂O correspondingly. At Ind-IITH, the model simulated the seasonal mean cumulative GPP, ET, and WUE of 766 ± 15 gC m^-2, 567 ± 30 kg H₂O m^-2, and 1.35 ± 0.11 gC kg^-1 H₂O, respectively, as compared to measured values of 793 ± 11 gC m^-2, 522 ± 20 kg H₂O m^-2, and 1.51 ± 0.12 gC kg^-1 H₂O correspondingly. Further, the diagnostic analysis using the GPP·VPD^0.5-ET relationship revealed that ISBA-A-g_s realistically captures the coupling between carbon assimilation and transpiration-driven water loss. Overall, ISBA-A-g_s demonstrates strong capability in simulating carbon and water fluxes of maize, particularly in representing WUE dynamics under contrasting climate regimes.