Feng et al. (2026) A framework for analyzing spatial hydrological drought dependence based on extreme value theory and nonstationary copulas

Identification

• Journal: Journal of Hydrology
• Year: 2026
• Date: 2026-07-21
• Authors: Yuqing Feng, Zhiyong Wu, Hai He, Zhenchen Liu, Yue Zhuo, Yangqian Li, Sergio M. Vicente‐Serrano
• DOI: 10.1016/j.jhydrol.2026.136076

Research Groups

• College of Hydrology and Water Resources, Hohai University, China
• Instituto Pirenaico de Ecología, Consejo Superior de Investigaciones Científicas (IPE–CSIC), Spain
• Yangtze Institute for Conservation and Development, China

Short Summary

The study proposes an integrated framework combining event-scale extreme value theory and nonstationary copulas to analyze the spatial dependence and concurrence risk of hydrological droughts within river networks.

Objective

• To investigate the spatiotemporal variation of hydrological drought dependence and concurrent drought probability by characterizing the joint probability structure of upstream–downstream drought durations while explicitly accounting for temporal nonstationarity.

Study Configuration

• Spatial Scale: River network scale, specifically applied to the Yangtze River basin.
• Temporal Scale: Not explicitly specified in the provided text (analyzes temporal evolution/nonstationarity).

Methodology and Data

• Models used: Nonstationary copulas, Extreme Value Theory (EVT), and the Peaks Over Threshold (POT) approach.
• Data sources: Hydrological drought event data from the Yangtze River basin.

Main Results

• Both the joint distribution structure and concurrent drought risk at the river network scale exhibit significant spatial heterogeneity and temporal nonstationarity.
• There is no uniform evolutionary pattern of drought dependence across different river reaches.
• The nonstationary framework provides a more accurate representation of changes in dependence structures and the temporal redistribution of joint probability during upstream-to-downstream drought propagation compared to stationary models.

Contributions

• Provides a statistically consistent and physically interpretable analytical framework for assessing concurrent hydrological drought risk in large river networks under nonstationary conditions.

Funding

• Not mentioned in the provided text.

Citation

@article{Feng2026framework,
  author = {Feng, Yuqing and Wu, Zhiyong and He, Hai and Liu, Zhenchen and Zhuo, Yue and Li, Yangqian and Vicente‐Serrano, Sergio M.},
  title = {A framework for analyzing spatial hydrological drought dependence based on extreme value theory and nonstationary copulas},
  journal = {Journal of Hydrology},
  year = {2026},
  doi = {10.1016/j.jhydrol.2026.136076},
  url = {https://doi.org/10.1016/j.jhydrol.2026.136076}
}