Evolution characteristics of the interannual and intra-annual precipitation in the Yangtze River Basin from 1901 to 2022
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Abstract
To evaluate the long-term spatiotemporal patterns of precipitation and their influence on drought-flood disasters, this study employs the precipitation concentration index (PCI) and the rainfall anomaly index (RAI) to analyze the intra-annual distribution and drought-flood characteristics in the Yangtze River Basin (YRB) from 1901 to 2022. The key findings are as follows: (1) During 1901-2022, the multi-year average PCI in the YRB ranged between 11 and 26, indicating that the intra-annual distribution of precipitation was moderately to highly concentrated. Spatially, PCI exhibited a northwest-high, southeast-low pattern, reflecting stronger seasonal precipitation variability in the northwestern regions. (2) Over the entire study period, the inter-annual change rate of the PCI in the study area was 0.029/10a, suggesting enhanced precipitation concentration. However, distinct differences were observed between sub-periods (1901-1960 and 1961-2022), highlighting the temporal complexity of precipitation changes. (3) RAI analysis revealed a general wetting trend (0.021/decade) across the basin. However, significant spatiotemporal variations existed—some regions transitioned from dry to wet conditions, while others shifted toward increased aridity, demonstrating the climatic diversity and dynamism of the YRB. (4) The mutation analysis of PCI and SPCI reveals asynchronous abrupt changes across different study periods, though both indices exhibited significant mutations around the 1950s and 1990s. Specifically, three major PCI mutations were identified in the YRB during 1901-2022 (1953, 1988, and 2002). Seasonal analysis shows earlier SPCI mutations in spring, autumn and winter (1931, 1920, and 1937 respectively), followed by secondary mutations in spring, summer and winter around 1953 and 1989. These spatiotemporal variations in PCI and RAI demonstrate fundamental shifts in precipitation patterns across the basin. The findings provide a scientific basis for drought-flood disaster forecasting and contribute to understanding regional climate response mechanisms under global climate change.
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