Analysing non-stationarity in runoff and sediment load is crucial for effective water resource management in the Dongting Lake basin amid climate change and human impacts. Using the Mann-Kendall test, Generalized Additive Models for Location, Scale, and Shape framework, and Random Forest models, we evaluated non-stationarity and its drivers in the annual runoff and annual sediment load series at eight hydrological stations from 1961 to 2021. These stations include three inflow sites at the Jingjiang Three Outlets (Ouchi, Songzi, and Hudu Rivers), four inflow sites in the Four Rivers basin (Xiang, Zi, Yuan, and Li Rivers), and one outflow site at Chenglingji. Results revealed a significant decrease in annual runoff at the Three Outlets and Chenglingji, while the Four Rivers basin showed no significant trend. The non-stationary models with multiple physically-based covariates better captured non-stationarity compared to single covariate models. Annual rainfall was a key contributor to annual runoff in the Four Rivers basin, while reservoir storage capacity played a more dominant role in the Three Outlets. At Chenglingji station, both factors significantly influenced annual runoff. For annual sediment load, reservoir storage capacity emerged as the most critical factor across all regions. These findings provide a basis for improving runoff and sediment regulation in the Dongting Lake basin.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11487199PMC
http://dx.doi.org/10.1038/s41598-024-74952-xDOI Listing

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