Mustard (Brassica spp.) grown as a cover crop retains root-zone soil water; however, if terminated late, it may lead to excessive water uptake. We calibrated and evaluated the decision support system for agrotechnology transfer (DSSAT) using field data from 2019 to 20 to simulate soil water content (SWC), leaf area index (LAI), aboveground biomass (AGB), and grain yield for maize (Zea mays L.) in southwest Texas. We applied DSSAT with climate projections from seven global climate models (GCMs) to assess soil water dynamics and crop responses under projected climate scenarios. The model accurately calibrated and evaluated LAI for maize (RMSE = 0.28) and mustard (RMSE = 1.42), and AGB for maize (RMSE = 1092.51 kg ha-1) and mustard (RMSE = 772.54 kg ha-1). Simulated SWC matched observed values in 2019 and closely followed field observations at 10 cm depth in 2020, confirming the model's sensitivity to root-zone moisture dynamics. Future climate impacts were assessed using Seasonal Analysis tool with bias-corrected projections from seven GCMs under RCP 4.5 and RCP 8.5. Results showed that maize yield is projected to peak in 2050 under RCP 4.5 and declined under RCP 8.5. Mustard cover cropping improved SWC (0.29 m3 m-3) and subsequently maize yield under moderate to high rainfall scenarios, but had neutral effects under drier conditions (SWC as 0.13 m3 m-3). It is critical to maintain SWC above 0.27 m3 m-3 for maize yield stability in this region. Maize irrigation demand is projected to increase 20 % by 2100. Sensitivity analysis showed that maize yield is strongly influenced by genetic parameters such as P1, P5, and G2 that regulate phenology and grain filling duration. Our study recommends targeted irrigation at flowering and physiological maturity in maize to optimize WUE, while demonstrating that projected warming and altered rainfall patterns are expected to intensify soil moisture deficits in mustard-maize rotation.