Jin et al. (2026) Spatiotemporal evolution and hyetograph changes of global extreme precipitation

Identification

• Journal: Journal of Hydrology
• Year: 2026
• Date: 2026-03-19
• Authors: Haoyu Jin, Ke Zhang, Moyang Liu, Xuan Yu, Xu Yang, Lijun Chao, Pengfei Zhang, Guoyan Liu
• DOI: 10.1016/j.jhydrol.2026.135325

Research Groups

• State Key Laboratory of Water Disaster Prevention, Hohai University, Nanjing, Jiangsu 210024, China
• Key Laboratory of Transportation Meteorology of China Meteorological Administration, Nanjing Joint Institute for Atmospheric Sciences, Nanjing 210041, China
• Yangtze Institute for Conservation and Development, Nanjing, Jiangsu 210024, China
• College of Hydrology and Water Resources, Hohai University, Nanjing, Jiangsu 210024, China
• China Meteorological Administration Hydro-Meteorology Key Laboratory, Hohai University, Nanjing, Jiangsu 210024, China
• Key Laboratory of Water Big Data Technology of Ministry of Water Resources, Hohai University, Nanjing, Jiangsu 210024, China
• The Fenner School of Environment and Society, The Australian National University (ANU), Canberra ACT 0200, Australia
• State Key Laboratory of Soil and Sustainable Agriculture, Institute of Soil Science, Chinese Academy of Sciences, Nanjing 210008, China

Short Summary

This study systematically analyzes the global spatiotemporal evolution of annual maximum 3-hour precipitation events and their hyetograph changes, revealing a global decline in peak intensity but an increase in total event precipitation due to more temporally distributed rainfall, which is likely to exacerbate flood risk.

Objective

• To systematically analyze the global spatiotemporal evolution of annual maximum 3-hour precipitation events, with a particular emphasis on changes in precipitation hyetograph characteristics.

Study Configuration

• Spatial Scale: Global
• Temporal Scale: Annual maximum 3-hour precipitation events, analyzed over multi-decadal periods (implied by "evolution" and "recent years").

Methodology and Data

• Models used: Precipitation type classification based on a similarity index.
• Data sources: High-resolution MSWEP (Multi-Source Weighted-Ensemble Precipitation) dataset.

Main Results

• The intensity of annual maximum 3-hour precipitation is declining in 57.81% of global regions (14.76% significantly).
• Precipitation occurring within a 9-hour window before and after peak events is increasing across 56.15% and 56.60% of the globe, respectively (6.18% and 5.50% significantly).
• Total precipitation per event is increasing in 52.23% of regions (6.68% significantly).
• Precipitation concentration is decreasing in many regions, indicating a more evenly distributed precipitation process over time.
• The average similarity index for precipitation type classification exceeds 0.9.
• Precipitation Types 3 and 5 are the most frequently observed hyetographs globally.
• The proportion of Type 3 events (more intense and temporally concentrated) has declined, while Types 4 and 5 (more approximately uniform distribution) have increased.
• The increase in Types 4 and 5, combined with rising total event precipitation (63.22% and 71.75% respectively, with 6.28% and 8.65% significant), is likely to exacerbate the risk of severe flooding.

Contributions

• Enhances the understanding of changing extreme precipitation hyetographs globally.
• Provides valuable insights for improving flood risk management and disaster preparedness under evolving precipitation regimes.
• Addresses a gap in the literature by systematically analyzing the evolution of extreme precipitation hyetographs at a global scale.

Funding

• Not specified in the provided text.

Citation

@article{Jin2026Spatiotemporal,
  author = {Jin, Haoyu and Zhang, Ke and Liu, Moyang and Yu, Xuan and Yang, Xu and Chao, Lijun and Zhang, Pengfei and Liu, Guoyan},
  title = {Spatiotemporal evolution and hyetograph changes of global extreme precipitation},
  journal = {Journal of Hydrology},
  year = {2026},
  doi = {10.1016/j.jhydrol.2026.135325},
  url = {https://doi.org/10.1016/j.jhydrol.2026.135325}
}