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In this study, a numerical procedure to determine RRWD thresholds was developed through coupling AquaCrop software with genetic-simplex algorithms. Using a two-year field lysimetric experiment for winter wheat conducted in the North China Plain (NCP), AquaCrop adequately simulated canopy cover, final aboveground biomass, grain yield, seasonal evapotranspiration, and soil water storage, with the normalized root mean squared error (NRMSE) smaller than 15 % and determination coefficient (R2) larger than 0.84. The global optimum range of RRWD thresholds was preliminarily determined using the genetic algorithm, and subsequently final RRWD thresholds were optimized by fine tuning using the simplex algorithm. The RRWD threshold combinations (composed of the RRWD thresholds to trigger different sequential irrigation events) for varying number of irrigation events (i.e.1\u20134) were optimized based on 39 years of historical meteorological data, and the effects of climate change on the optimal crop yield (Ya, opt), water productivity (WPopt), and the combinations of optimized RRWD threshold (RRWDopt) were investigated. The results indicated that both Ya, opt and WPopt generally increased with time showing a tendency of gradually elevated annual CO2 concentration and seasonal average effective temperature. Irrespective of the number of irrigation events during the winter wheat growing season, the differences of RRWDopt for different combinations of irrigation sequence and event in the same kind of hydrological year were relatively small, with a coefficient of variation consistently less than 23 % and a mean of 8 %. When combinations of mean RRWDopt were applied into AquaCrop to trigger irrigation for winter wheat in various hydrological years, the simulated yield (Ya, sim) and water productivity (WPsim) under 1\u20134 irrigation events were found to be comparable to their respective optimums (Ya, opt and WPopt), with all the values of Ya, sim (WPsim) falling in the range of 92 %Ya, opt (90 %WPopt). Therefore, the mean RRWDopt should be helpful to formulate rational irrigation management strategies of winter wheat under changing climatic conditions in the NCP.", "keywords": ["HD9000-9495", "2. Zero hunger", "0106 biological sciences", "Evapotranspiration", "Agriculture (General)", "04 agricultural and veterinary sciences", "Agricultural industries", "15. Life on land", "01 natural sciences", "Irrigation scheduling", "6. Clean water", "S1-972", "Optimization algorithm", "13. 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