Liu et al. (2025) Hydrological drought dynamic using copula functions and drought center migration in the Ganjiang river basin

Identification

• Journal: Scientific Reports
• Year: 2025
• Date: 2025-11-10
• Authors: Weilin Liu, Jingrong Zhang, Zhanxiong Zhou, Siyu Zhu, Lina Liu, Jianzhu Li
• DOI: 10.1038/s41598-025-18331-0

Research Groups

• Jiangxi Provincial Key Laboratory of Water Resources Allocation and Efficient Utilization, Jiangxi University of Water Resources and Electric Power, Nanchang, China
• College of Hydrology and Water Resources, Hohai University, Nanjing, China
• State Key Laboratory of Hydraulic Engineering Simulation and Safety, Tianjin University, Tianjin, China

Short Summary

This study investigated the spatiotemporal evolution and risk of hydrological drought in China's Ganjiang River Basin (1959–2019) using observed and SWAT-simulated runoff data, the Standardized Runoff Index (SRI), run theory, a gravity center model, and Copula functions. The findings revealed an intensification of droughts after the 1990s, a concentration of drought centers in the central basin with prominent north-south migration, and the Gumbel copula as the best model for interdependent drought characteristics (duration, severity, and peak intensity) to enhance risk assessment.

Objective

• To explore the spatiotemporal dynamics and risk of hydrological drought events in the Ganjiang River Basin (GRB), China, from 1959 to 2019.

Study Configuration

• Spatial Scale: Ganjiang River Basin (GRB), China (113.58°–116.63°E, 24.52°–28.75°N), with a drainage area of 83,500 km², divided into 81 sub-basins.
• Temporal Scale: 1959–2019 (61 years) using monthly runoff data; analysis of drought characteristics across decadal periods.

Methodology and Data

• Models used:
  • Soil and Water Assessment Tool (SWAT) for hydrological simulation.
  • Standardized Runoff Index (SRI-3) with a threshold of -0.5 for drought identification and classification.
  • Run theory for extracting drought duration (D), severity (S), and intensity peak (P).
  • Gravity center model for analyzing spatial migration patterns of drought barycenters.
  • Copula functions (Gumbel, Clayton, Frank, t, Gaussian, Joe, BB1, BB6) for modeling bivariate and trivariate joint distributions of drought characteristics and estimating return periods.
• Data sources:
  • Observed monthly runoff data (1959–2019) from six hydrological stations in the GRB, provided by the Hydrology and Water Resource Survey Bureau of Jiangxi Province.
  • Daily meteorological data (1959–2019) from 13 national stations (maximum/minimum air temperature, precipitation, sunshine duration, wind speed, relative humidity) from the National Meteorological Information Center of China (CMA).
  • Geographical data: 30 m resolution Digital Elevation Model (DEM), 1 km resolution FAO soil data, and University of Maryland’s Global Land Cover dataset.

Main Results

• Drought conditions in the GRB showed a weakening trend from the 1960s to the 1990s, but have intensified since the 1990s. Regions with longer drought durations generally experienced greater severity.
• The gravity center of drought events was primarily concentrated in the central GRB, exhibiting more pronounced north-south migration than east-west movement. The migration distance increased with drought severity, with the extreme drought center migrating up to 109.72 km between the 1970s and 1980s.
• Significant dependence was observed among drought characteristics (D, S, P), with the strongest correlation between D and S. The Gumbel copula was identified as the best-fitting model for both bivariate (D–S, S–P, D–P) and trivariate (D–S–P) joint distributions.
• The joint return period (Tα) and co-occurrence return period (To) effectively bounded the univariate return period (T) (Tα < T < To). For example, a 50-year univariate extreme drought event (duration 18.08 months, severity 23.84, peak intensity 2.71) had an estimated co-occurrence return period of approximately 148 years, indicating that extreme droughts occur less frequently.

Contributions

• Provides a quantitative basis for understanding the spatiotemporal dynamics of hydrological drought in the Ganjiang River Basin, addressing previous research gaps focused mainly on meteorological drought and limited detailed investigations.
• Introduces a comprehensive approach combining the SWAT model, SRI, run theory, gravity center analysis, and multivariate copula functions for a detailed spatiotemporal and frequency analysis of hydrological drought.
• Offers improved drought risk assessment by accurately modeling the interdependent nature of drought characteristics (duration, severity, and peak intensity) and providing more reliable return period estimations.
• Supports the development of regional drought mitigation strategies and water resource planning by identifying vulnerable areas and revealing drought movement trends.

Funding

• National Natural Science Foundation of China (No. 52069015)
• Jiangxi High level - High skilled Leading Talent Training Project (2023)

Citation

@article{Liu2025Hydrological,
  author = {Liu, Weilin and Zhang, Jingrong and Zhou, Zhanxiong and Zhu, Siyu and Liu, Lina and Li, Jianzhu},
  title = {Hydrological drought dynamic using copula functions and drought center migration in the Ganjiang river basin},
  journal = {Scientific Reports},
  year = {2025},
  doi = {10.1038/s41598-025-18331-0},
  url = {https://doi.org/10.1038/s41598-025-18331-0}
}