Hu et al. (2025) Long-term changes in the drought propagation characteristics in the Yangtze River Basin

Identification

• Journal: Journal of Hydrology Regional Studies
• Year: 2025
• Date: 2025-12-11
• Authors: R. Hu, Shanshui Yuan, Junliang Jin, Liujun Zhu, Yi Liu
• DOI: 10.1016/j.ejrh.2025.103014

Research Groups

• State Key Laboratory of Water Disaster Prevention, Hohai University, Nanjing, China
• Yangtze Institute for Conservation and Development, Hohai University, Nanjing, China
• College of Hydrology and Water Resources, Hohai University, Nanjing, China

Short Summary

This study systematically assesses the long-term evolution of drought propagation characteristics in the Yangtze River Basin (1950–2022) using a dynamic sliding-window framework and copula-based joint probability analysis. It reveals significant spatiotemporal changes in drought propagation time and risk, highlighting the influence of vegetation type and hydrological interventions.

Objective

• To systematically quantify the long-term evolutionary trends of drought propagation time and risk from meteorological to agricultural and hydrological droughts in the Yangtze River Basin over the past decades.
• To identify the spatial patterns of these trends and explore potential climatic or anthropogenic factors associated with these changes.

Study Configuration

• Spatial Scale: Yangtze River Basin, covering approximately 1.8 million square kilometers (24°27’ - 35°54’ N, 90°33’ - 122°19’ E).
• Temporal Scale: 1950–2022 (73 years), analyzed using a 30-year sliding-window framework.

Methodology and Data

• Models used:
  • Standardized Precipitation Index (SPI)
  • Standardized Soil Moisture Index (SSI)
  • Standardized Runoff Index (SRI)
  • Pearson Correlation Coefficient (PCC) for Drought Propagation Time (DPT)
  • Copula functions (Gaussian, Gumbel, Frank) for joint probability analysis of drought duration and severity
  • Drought Hazard Propagation Ratio (DHPR)
  • Mann-Kendall trend test for temporal trends
• Data sources: ERA5-Land dataset (precipitation, soil moisture, runoff) with a spatial resolution of 0.1° from 1950 to 2022.

Main Results

• Drought propagation from meteorological drought (MD) to agricultural drought (AD) is predominantly characterized by a 2-month lag across 64.5 % of the basin.
• MD to hydrological drought (HD) propagation typically exhibits a 4-month lag, with approximately 25 % of the basin experiencing lags exceeding 6 months.
• Sliding-window analysis reveals significant decreases in DPT in parts of the upper basin, but widespread increases in drought propagation risk, particularly in the Sichuan Basin.
• Areas dominated by cultivated vegetation show longer propagation times and higher risks, with more pronounced upward trends compared to natural vegetation regions.
• For MD-AD propagation, the DHPR for severity tends to decrease with increasing return periods (e.g., 61.5 % of the basin has DHPR < 1.0 at a 100-year return period), while the DHPR for duration increases.
• For MD-HD propagation, both severity and duration DHPR exhibit a clear increasing trend across nearly the entire basin, with amplification becoming more pronounced at longer return periods (e.g., DHPR (Severity) > 2.0 rises to 14.1 % at a 100-year return period).
• DPT trends for MD-AD are spatially scattered, with significant lengthening in the high-altitude source region (+0.08 month/year) and shortening downstream (-0.10 month/year).
• DPT trends for MD-HD are more spatially coherent, showing widespread significant shortening in the upper reaches (-0.04 to -0.10 month/year) and lengthening in the source region and parts of the middle reaches (+0.04 to +0.08 month/year).

Contributions

• Provides a novel dynamic assessment of long-term evolutionary trends in drought propagation characteristics (time and risk) in a large river basin, moving beyond static analyses.
• Systematically quantifies these trends using a 30-year sliding-window framework combined with copula-based joint probability analysis.
• Clarifies the spatiotemporal patterns and the role of vegetation types in controlling drought propagation dynamics.
• Offers critical regional knowledge for developing proactive and adaptive drought early warning systems and water resource management strategies.
• Highlights the non-linear response of drought propagation to extreme events and the distinct propagation mechanisms between agricultural and hydrological pathways.

Funding

• National Key Research and Development Program of China (2023YFC3209800)
• Basic Research Project of Jiangsu Province (BK20250090)
• National Natural Science Foundation of China (52279011)

Citation

@article{Hu2025Longterm,
  author = {Hu, R. and Yuan, Shanshui and Jin, Junliang and Zhu, Liujun and Liu, Yi},
  title = {Long-term changes in the drought propagation characteristics in the Yangtze River Basin},
  journal = {Journal of Hydrology Regional Studies},
  year = {2025},
  doi = {10.1016/j.ejrh.2025.103014},
  url = {https://doi.org/10.1016/j.ejrh.2025.103014}
}