Non-stationarity of runoff and sediment load and its drivers under climate change and anthropogenic activities in Dongting Lake Basin

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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Publication Details

Journal
Scientific Reports
Published
2024-10-17
DOI
https://doi.org/10.1038/s41598-024-74952-x
Citations
6
Primary Topic
Hydrology and Watershed Management Studies
Type
article
Field-Weighted Citation Impact
1.21

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article

Non-stationarity of runoff and sediment load and its drivers under climate change and anthropogenic activities in Dongting Lake Basin

Peiliang Liu, Dehua Mao, Enguang Li, Yishu Li et al.
6 citations
Scientific Reports
Hydrology and Watershed Management Studies
1.21
article

Non-stationarity of runoff and sediment load and its drivers under climate change and anthropogenic activities in Dongting Lake Basin

Peiliang Liu, Dehua Mao, Enguang Li, Yishu Li, Min Yang, Guangwei Hu, Meirong Deng, Chang Feng, Ting Wang
article en
6 citations

Abstract

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.

Scientific ReportsVol. 14(1)
Hengyang Normal University (CN), Sun Yat-sen University (CN), Hunan Normal University (CN), Huawei Technologies (China) (CN), Changsha Normal University (CN), Ministry of Education (KR), Nanjing Surveying and Mapping Research Institute (China) (CN), Nano Carbon (Poland) (PL), Dali University (CN)
Education Department of Hunan Province, National Natural Science Foundation of China
Climate action
Openalex Percentile: Top 22%
Hydrology and Watershed Management Studies
1.21
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