Optimal water supply and irrigation indicators for winter wheat in the main producing regions of China: Insights from the WMAIP integrated model

The significant spatial variability of precipitation in China's main producing regions of winter wheat is a major factor determining irrigation water supply. Previous research on determining optimal irrigation for winter wheat in the main producing regions of China (MPC) based on crop models has primarily relied on single-model approaches, with limited discussion on growth-stage-specific water supply and inherent model uncertainties. This study systematically evaluated region-specific irrigation indicators for winter wheat under different precipitation patterns across the MPC sub-regions by establishing a Wheat Model Algorithm Integration Platform (WMAIP) and employing a composite indicator that integrates high stability coefficients for yield and water productivity (WP). Irrigation significantly enhanced winter wheat yields throughout the MPC. The highest improvements were observed in the northern region under dry conditions, where yields increased by up to 90 %, compared to less than 20 % in the south. During dry years, the highest WP values under irrigation were achieved in the northern and central regions, ranging from 1.56 to 1.85 kg·m⁻³ . In contrast, rainfed conditions in the southern region resulted in the highest WP across the MPC, reaching 1.88–2.06 kg·m⁻³ . By integrating a high-yield stability coefficient (Y-HSC) and a high-WP stability coefficient (WP-HSC), the optimal total water supply was determined to be 237–416 mm (mean 319 mm), 231–393 mm (mean 309 mm), and 214–388 mm (mean 299 mm) for dry, normal, and wet years, respectively. The corresponding irrigation indicators ranged from 6 to 335 mm (mean 191 mm), 0 to 257 mm (mean 126 mm), and 0 to 176 mm (mean 57 mm) for dry, normal, and wet years, respectively. Moreover, the optimal water supply was strongly correlated (R² = 0.96) with the gap between potential evapotranspiration and available soil water, underscoring its value as a predictive indicator for water management. These findings underscore the critical importance of developing differentiated irrigation strategies tailored to regional and precipitation-specific conditions.