Yan et al. (2026) Structural evolution and event-chain risk of extreme events in China's largest freshwater lake: Event chain quantification based on continuous-state sequences

Identification

• Journal: Journal of Hydrology Regional Studies
• Year: 2026
• Date: 2026-09-14
• Authors: Yuting Yan, Yuting Yan, Dongfang Liang, Yanqing Deng, Yichuan Zeng, Jiang Jiang
• DOI: 10.1016/j.ejrh.2026.103977

Research Groups

• Key Laboratory of Integrated Regulation and Resource Development on Shallow Lake of Ministry of Education, College of Environment, Hohai University, Nanjing, China
• Department of Engineering, University of Cambridge, Cambridge, UK
• Water Quality Department, Jiangxi Hydrological Monitoring Center, China and Key Laboratory of Hydrological and Ecological Monitoring of Poyang Lake, Nanchang, China
• Jiangsu Provincial Assessment Center of Ecology and Environment, Department of Ecology and Environment of Jiangsu Province, Nanjing, China

Short Summary

This study introduced a new framework to quantify the internal structure of flood-drought event chains in Poyang Lake, China. The results showed that compound events contributed disproportionately to anomalous days, and their transition complexity was 2-4 times that of single events.

Objective

• Investigate the spatiotemporal characteristics and evolutionary patterns of lake extreme events and their event-chain structures across multiple temporal scales.
• Examine the statistical associations of climate variability and river-lake interactions with structural evolution and high-MCHTI behavior.

Study Configuration

• Spatial Scale: Poyang Lake Basin (PLB) in China, with a watershed area of about 162,225 square kilometers.
• Temporal Scale: Daily, monthly, and annual time scales were used to analyze the hydrological state sequences and event chains.

Methodology and Data

• Models used: Continuous Hydrological State Sequences (CHSS) and Multi-scale Continuous Hydrological Transition Index (MCHTI).
• Data sources: Water level, discharge, water temperature, and meteorological data from 1959 to 2020 were used in this study.

Main Results

• Compound events contributed disproportionately to anomalous days, with a transition complexity 2-4 times that of single events.
• The mean durations of monthly D-type and F-type sequences were 3.44 and 3.24 months per sequence, respectively, whereas monthly C-type sequences averaged 24.62 months per sequence.
• Structural complexity and chain length increased by 42.8% and 50.4%, respectively, after 2003.

Contributions

• This study provided a reproducible quantitative basis for lake-level risk screening and river-lake eco-security regulation under a changing environment.
• The new framework introduced in this study can be applied to other lakes and regions to understand the internal structure of flood-drought event chains.

Funding

• This research was supported by the National Natural Science Foundation of China (Grant No. 51679013) and the Jiangsu Provincial Assessment Center of Ecology and Environment (Grant No. JSZB2018-01).

Citation

@article{Yan2026Structural,
  author = {Yan, Yuting and Yan, Yuting and Liang, Dongfang and Deng, Yanqing and Zeng, Yichuan and Jiang, Jiang},
  title = {Structural evolution and event-chain risk of extreme events in China's largest freshwater lake: Event chain quantification based on continuous-state sequences},
  journal = {Journal of Hydrology Regional Studies},
  year = {2026},
  doi = {10.1016/j.ejrh.2026.103977},
  url = {https://doi.org/10.1016/j.ejrh.2026.103977}
}