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Simulation of the impacts of climate change on phenology, growth, and yield of various rice genotypes in humid sub-tropical environments using AquaCrop-Rice

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Abstract

In the light of continuing anthropogenic climate change, it is important to gain a deep understanding of rice genotypic behavior under climate change. Most efforts on modeling rice performance under climate change focused on studying some aspects of climate change only such as CO2 concentration ([CO2]) or temperature. A comprehensive study on the role of genotypic variability in rice under diverse [CO2] × temperature × rainfall × representative concentration pathway (RCP) × environment is rare. The objective of the present study was to use AquaCrop-Rice model to study the impact of climate change on different rice cultivars in northern Iran. Three common improved and local rice cultivars were chosen, and their growth and yield behavior were simulated under three environments, three RCPs (2.6, 4.5 and 8.5), four temperature (+ 1 °C, + 2 °C, + 3 °C, + 4 °C), and two rainfall (± 20%) scenarios under two future timeframes (2020–2051 and 2052–2083). Results indicated different responses of rice cultivars under climate change. In general, improved cultivars acted better than the local cultivar although interaction with environment was also observed. Increase in [CO2] and temperature most often favored rice yield. However, RCP8.5 along with temperature scenario + 1 °C resulted in the highest aboveground biomass and yield. Rainfall variation was not of considerable importance. Phenology (flowering and physiological maturity) was accelerated especially by temperature. The length of the vegetative phase was more influenced by temperature than the length of the generative phase. Our simulations also indicated a potential for adaptation of improved cultivars under increasing [CO2] through their reduced stomatal conductance.

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Raoufi, R.S., Soufizadeh, S. Simulation of the impacts of climate change on phenology, growth, and yield of various rice genotypes in humid sub-tropical environments using AquaCrop-Rice. Int J Biometeorol 64, 1657–1673 (2020). https://doi.org/10.1007/s00484-020-01946-5

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