Climate change is affecting the productivity of crops and their regional distribution. Strategies to enhance local adaptation capacity are needed to mitigate climate change impacts and to maintain regional stability of food production. The objectives of this study were to simulate the climate change effects on phonological stages, Leaf Area Index (LAI), biomass and grain yield of maize (Zea mays L.) in the future and to explore the possibilities of employing irrigation water and planting dates as adaptation strategies to decrease the climate change impacts on maize production in Khorasan Razavi province, Iran. For this purpose, we employed two types of General Circulation Models ((United Kingdom Met. Office Hadley Center: HadCM3) and (Institute Pierre Simon Laplace: IPCM4)) and three scenarios (A1B, A2 and B1). Long Ashton Research Station-Weather Generator (LARS-WG) was used to produce daily climatic parameters as one stochastic growing season for each projection period. Also, crop growth under projected climate conditions was simulated based on the Cropping System Model (CSM)-CERES-Maize. The results of model evaluation showed that LARS-WG had appropriate prediction for climatic parameters. Time period from cultivation until anthesis and maturity were reduced in majority of scenarios as affected by climate change. The results indicated that the grain yield of maize may be reduced (11 % to 38 %) as affected by climate change based on common planting date in baseline and changed (−61 % to 48%) in response to different irrigation regimes in the future climate change, under all scenarios and times. In general, earlier planting date (1 May) and decreasing irrigation intervals in the anthesis stage (11 applications) caused higher yield compared with other planting dates due to adaption to high temperature. Based on our findings, it seems that management of irrigation water and planting dates can be beneficial for adaptation of maize to climate change in this region.

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