The AquaCrop model is used to predict rice yield in response to different irrigation management in the Yanyun irrigation area in Yangzhou, China, and the constraints to rice production were identified to maximize water productivity based on model simulations. The model was calibrated by comparing measured and predicted canopy cover (CC), yield, and soil water content during the growing season in 2018. The results showed that, for CC simulations, R² was 0.99, RMSE was 3.6%, and NRMSE was 5.3%; for Biomass simulation, RMSE was 0.50 t/ha, and NRMSE was 5.3%. Different irrigation strategies were analyzed for a long-term simulation period from 1955 to 2014. The simulated rice yield increased rapidly as irrigation demand increased initially, and then gradually stabilized. The simulated rice yield fluctuated in the different years. The Pearson type-III model method was used to identify different hydrological years of wet, normal, and dry years. The analysis identified the wet year as 1991, normal year as 1981, and dry year as 1966. In the different rainfall years (1991, 1981, and 1966) water use efficiency (WUE), water productivity (WPet), and irrigation water productivity (IWP) were utilized to determine the irrigation strategy. The predicted highest WPet in the wet year was 1.77kg m⁻³, while the lowest WPet in the dry year was 1.13 kg m⁻³. The highest IWP was 19.78 kg m⁻³ in the wet year, and 9.32 kg m⁻³ in the normal year; while the lowest IWP in the dry year was 1.90 kg m⁻³. IWP was significantly higher in the rainy year, while WUE was significantly lower. On the other hand, WPet was more extensive in the wet year because the yield was higher, and the Evapotranspiration (ET) was smaller in comparison to the dry year.

Simulations using the Crop Water and Irrigation Requirements model (CROPWAT), show that the projected climatic changes over the period from 2026 to 2050 in the Yanyun irrigation district, Yangzhou, China, will cause the paddy lands there to lose about 12.4% to 37.4%, and 1.6% to 45.6%, of their future seasonal rainwater in runoff under the Representative Concentration Pathways (RCP45 and RCP85), respectively. This may increase future irrigation requirements (IRs), alongside threatening the quality of adjacent water bodies. The CROPWAT simulations were re-run after increasing the Surface Storage Capacity (SSC) of the land by 50% and 100% of its baseline value. The results state that future rainwater runoff will be reduced by up to 76% and 100%, and 53% and 100% when the SSC is increased by 50% and 100%, under RCP45 and RCP85, respectively. This mitigates the future increase in IRs (e.g., under RCP45, up to about 11% and 16% of future IRs will be saved when increasing the SSC by 50% and 100%, respectively), thus saving the adjacent water bodies from the contaminated runoff from these lands. Adjusting the SSC of farmlands is an easy physical approach that can be practiced by farmers, and therefore educating them on how to follow up the rainfall forecast and then adjust the level of their farmlands’ boundaries according to these forecasts may help in the self-adaptation of vast areas of farmlands to climate change. These findings will help water users conserve agricultural water resources (by mitigating the future increase in IRs) alongside ensuring better quality for adjacent water bodies (by decreasing future runoff from these farmlands). Increasing farmers’ awareness, an underutilized approach, is a potential tool for ensuring improved agricultural circumstances amid projected climate changes and preserving the available water resources.