Xu et al. (2026) A network-based framework for deciphering extreme precipitation propagation across China

Identification

• Journal: Journal of Hydrology
• Year: 2026
• Date: 2026-08-24
• Authors: Yingying Xu, Zhiyong Liu, Yifan Huang, Yu Liu, Caihong Hu
• DOI: 10.1016/j.jhydrol.2026.136303

Research Groups

• Center for Water Resources and Environment, School of Civil Engineering, Sun Yat-sen University, China
• Key Laboratory of Water Security Guarantee in Guangdong-Hong Kong-Macao, Greater Bay Area of Ministry of Water Resources, China
• College of Water Conservancy and Transportation, Zhengzhou University, China

Short Summary

The study develops a network-based framework to analyze the propagation of extreme precipitation across China, identifying key propagation hubs and the role of geomorphological features in facilitating hydroclimatic connectivity.

Objective

• To characterize the spatiotemporal dynamics, propagation pathways, and community structures of extreme precipitation events across China to improve early-warning capabilities and cross-basin flood risk management.

Study Configuration

• Spatial Scale: National (China)
• Temporal Scale: Eleven consecutive 5-year windows

Methodology and Data

• Models used: Dual-threshold approach (for event identification), Louvain algorithm combined with K-means correction (for spatially constrained community detection).
• Data sources: Not explicitly detailed in the provided text, though the framework utilizes regional and seasonal precipitation data to identify extremes.

Main Results

• Propagation Patterns: A pronounced southeast-northwest precipitation gradient exists, with coastal monsoon regions and the middle-lower Yangtze Basin serving as core propagation hubs.
• Connectivity: Arid inland and high-altitude regions exhibit weak connectivity, while river valleys and mountain passes act as critical relay corridors for long-distance signal propagation.
• Community Structure: Approximately 68% of propagation events occur within delineated communities, with boundaries aligning with terrain and river basins.
• Temporal Evolution: Extreme precipitation propagation shows nonstationary evolution, characterized by a trend toward intensified propagation with shorter time lags.

Contributions

• Moves beyond traditional site-specific intensity analysis to capture directional propagation and system-scale cascading processes.
• Provides a quantitative framework for diagnosing regional hydroclimatic connectivity and cross-basin propagation.

Funding

• Not specified in the provided text.

Citation

@article{Xu2026networkbased,
  author = {Xu, Yingying and Liu, Zhiyong and Huang, Yifan and Liu, Yu and Hu, Caihong},
  title = {A network-based framework for deciphering extreme precipitation propagation across China},
  journal = {Journal of Hydrology},
  year = {2026},
  doi = {10.1016/j.jhydrol.2026.136303},
  url = {https://doi.org/10.1016/j.jhydrol.2026.136303}
}