In arid regions, water scarcity and soil potassium destruction are major constraints on the sustainable development of the jujube industry. In this regard, the use of crop models can compensate for time-consuming and costly field trials to screen for better irrigation regimes, but their predictive accuracy is often compromised by parameter uncertainty. To address this issue, we utilized data from a three-year (2022–2024) field trial (with irrigation at 50%, 75%, and 100% of evapotranspiration and potassium applications of 120, 180, and 240 kg/ha) to simulate the growth process of jujube trees in arid regions using the WOFOST model. In this study, parameter sensitivity analyses were conducted to determine that photosynthetic capacity maximization (A_max), the potassium nutrition index (K_status), the water stress factor (SWF), the water–potassium photosynthetic coefficient of synergy (α), and potassium partitioning weight coefficients (β_i) were the important parameters affecting the simulated growth process of the crop. Path analysis using segmented structural equations also showed that water stress factor (SWF) and potassium nutrition index (K_status) indirectly controlled yield by significantly affecting photosynthesis (path coefficients: 0.72 and 0.75, respectively). The ability of the crop model to simulate the growth process and yield of jujube trees was improved by the introduction of water and potassium parameters (R² = 0.94–0.96, NRMSE = 4.1–12.2%). The subsequent multi-objective optimization of yield and crop water productivity of dates under different combinations of water and potassium treatments under a bi-objective optimization model based on the NSGA-II algorithm showed that the optimal strategy was irrigation at 80% ET_c combined with 300 kg/ha of potassium application. This management model ensures yield and maximizes crop water use efficiency (CWP), thus providing a scientific and efficient irrigation and fertilization regime for jujube trees in arid zones.