Spatiotemporal evolution of intra-annual precipitation distribution in Changjiang River Basin from 1901 to 2022

To assess the long-term spatiotemporal evolution of precipitation and its impacts on drought and flood disasters, this study employs the Precipitation Concentration Index (PCI), Seasonal Precipitation Concentration Index (SPCI), and Rainfall Anomaly Index (RAI) to characterize the intra-annual precipitation distribution and associated drought-flood variations in the Changjiang River Basin from 1901 to 2022. The main findings are as follows: ① Over the study period, the multi-year average PCI ranges from 11 to 26 across the basin, indicating a moderate to exceptionally concentrated intra-annual precipitation regime. Spatially, PCI values exhibit a northwest-high, southeast-low pattern. ② On an interannual timescale, PCI shows an overall increasing trend (0.029 per decade), suggesting a strengthening of intra-annual precipitation concentration. Notably, the trend differs markedly between the sub-periods 1901~1960 and 1961~2022, highlighting the temporal complexity of precipitation changes. ③ RAI analysis reveals a general wetting trend across the Changjiang River Basin (0.021 per decade) from 1901 to 2022. However, pronounced variations exist among different sub-periods and sub-regions. Some areas have transitioned from dry to wet conditions, whereas others have shifted from wet to dry, reflecting the diversity and dynamic nature of the basin′s climate. ④ Abrupt change analysis shows that while the timing of abrupt changes in PCI and SPCI varies across study sub-periods, both indices experienced abrupt changes around the 1950s and 1990s. For the entire 1901~2022 period, PCI experienced three abrupt changes (in 1953, 1988, and 2002). Abrupt changes in spring, autumn, and winter occurred earlier (1931, 1920, and 1937, respectively), whereas another cluster of abrupt changes occurred around 1953 and 1989 in spring, summer, and winter. These findings reveal a shift in the precipitation regime of the Changjiang River Basin. The identified spatiotemporal evolution characteristics provide a scientific basis for predicting drought and flood disasters and contribute to a better understanding of regional climate responses to global change.