Future Rainfall Change Trend in Yangtze River Basin Based on CanESM5 Model

OUYANG Shuo; HU Zhi-dan; SHAO Jun; GONG Li; DU Tao

doi:10.11988/ckyyb.20221144

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Journal of Changjiang River Scientific Research Institute ›› 2024, Vol. 41 ›› Issue (1) : 36-43. DOI: 10.11988/ckyyb.20221144

Water Resources

Future Rainfall Change Trend in Yangtze River Basin Based on CanESM5 Model

OUYANG Shuo¹, HU Zhi-dan², SHAO Jun¹, GONG Li³, DU Tao¹

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Abstract

Situated in the eastern monsoon region of China, Yangtze River Basin is highly vulnerable to the impacts of climate change and prone to be stricken by frequent and severe flood and drought disasters. It is crucial to analyze the future spatiotemporal trends of hydrological and meteorological elements in the Yangtze River Basin. Based on the precipitation prediction results of the CanESM5 model released by CMIP6 under low, medium, and high forcing scenarios, namely SSP1-2.6, SSP2-4.5, and SSP5-8.5, respectively, we employed the daily bias correction method to examine the spatiotemporal evolution of precipitation over the next four decades. In spatial scale, the annual average precipitation across the Yangtze River Basin remains a pattern of increasing from northwest to southeast; and in temporal scale, future precipitation trends in the upstream basins of Pingshan and Yichang, which are key control stations, exhibit significantly higher mean and extreme values over the next four decades than those in historical period. In particular, precipitation levels in the SSP5-8.5 scenario are notably higher than those observed in the SSP1-2.6 and SSP2-4.5 scenarios. Moreover, we observed a significant linear correlation between annual precipitation and time in the upstream of Pingshan section under the SSP1-2.6 and SSP5-8.5 scenarios, but no significant correlation for the Yichang section. However, under the SSP2-4.5 scenario, the correlation between annual precipitation and time in the upstream of both sections remains significant.

Key words

spatiotemporal evolution trend of precipitation / CMIP6 / CanESM5 model / quantile-based daily bias correction / Yangtze River Basin

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OUYANG Shuo, HU Zhi-dan, SHAO Jun, GONG Li, DU Tao. Future Rainfall Change Trend in Yangtze River Basin Based on CanESM5 Model[J]. Journal of Changjiang River Scientific Research Institute. 2024, 41(1): 36-43 https://doi.org/10.11988/ckyyb.20221144

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