Simulating the Impact of Climate Change on Rice Phenology and Grain Yield in Irrigated Drylands of Central Asia

Abstract, Journal of Applied Meteorology and Climatology, 2013

Rice is the second major food crop in central Asia. Climate change may greatly affect the rice production in the region. This study quantifies the effects of projected increases in temperature and atmospheric CO₂concentration on the phenological development and grain yield of rice using the “ORYZA2000” simulation model. The model was parameterized and validated on the basis of datasets from three field experiments with three widely cultivated rice varieties under various seeding dates in the 2008–09 growing seasons in the Khorezm region of Uzbekistan. The selected rice varieties represent short-duration (SD), medium-duration (MD), and long-duration (LD) maturity types. The model was linked with historical climate data (1970–99) and temperatures and CO₂ concentrations projected by the Intergovernmental Panel on Climate Change for the B1 and A1F1 scenarios for the period 2040–69 to explore rice growth and yield formation at eight emergence dates from early May to mid-July. Simulation results with historical daily weather data reveal a close relationship between seeding date and rice grain yield. Optimal emergence dates were 25 June for SD, 5 June for MD, and 26 May for LD varieties. Under both climate change scenarios, the seeding dates could be delayed by 10 days. Increased temperature and CO₂ concentration resulted in higher rice grain yields. However, seeding rice before and after the optimal seeding dates reduced crop yield and yield stability significantly because of spikelet sterility induced by both high and low temperatures. As the grain yield of SD varieties could be adversely affected by climate change, rice breeding programs for central Asia should focus on developing appropriate heat-tolerant MD and LD varieties.

Keywords: Hazardous release modeling; Model evaluation/performance; Model output statistics; Agriculture; Crop growth; Ecological models