Zhang et al. (2025) A multi-element coupled drought index for drought characterization in seasonal shallow lake basins

Identification

• Journal: Journal of Hydrology
• Year: 2025
• Date: 2025-12-08
• Authors: Zhen Zhang, Wen Zhang, Zhe Wang, Yi Bao, Yangyang Ma, Xi Wang, Qianyu Wang, Bingquan Chen, Huiqi Wang, Linguang Miao, Linyi Li, Lingkui Meng
• DOI: 10.1016/j.jhydrol.2025.134760

Research Groups

• School of Remote Sensing and Information Engineering, Wuhan University, China
• HeiLongJiang University of Technology, China

Short Summary

This study develops a Multi-element Coupled Drought Index (MCDI) by integrating six key water cycle elements and their lag times using vine copula, specifically for seasonal shallow lake basins. The MCDI demonstrates superior performance in drought characterization, offering more prompt and accurate detection of drought occurrence and grades compared to traditional indices.

Objective

• To construct a Multi-element Coupled Drought Index (MCDI) by integrating six key water cycle elements (precipitation, potential evaporation, runoff, surface water area, soil moisture, and ground water storage) using vine copula, accounting for their lag times.
• To evaluate the performance of MCDI through correlation analysis with typical drought indices and its ability to characterize major droughts quantitatively and qualitatively.
• To quantify the spatiotemporal characteristics of drought in nine seasonal shallow lake basins over the past 20 years using MCDI combined with a three-dimensional clustering method.

Study Configuration

• Spatial Scale: Nine seasonal shallow lake basins, including the Poyang Lake Basin.
• Temporal Scale: Past 20 years.

Methodology and Data

• Models used: Vine copula, three-dimensional clustering method.
• Data sources: Precipitation, potential evaporation, runoff, surface water area, soil moisture, and ground water storage.

Main Results

• MCDI exhibits high correlations (concentrated at 0.6–0.9, with most basin’s average correlation coefficients exceeding or approaching 0.7) with typical drought indices such as SPI, SPEI, and MSDI.
• Compared with existing drought indices, MCDI generally demonstrates a superior ability to capture drought occurrence more promptly, detect drought grades more accurately, and provide a more complete characterization of the drought lifecycle and evolution process.
• Surface water plays an important role in the advantages of MCDI for drought monitoring.
• Most basins exhibit significant dynamic fluctuations in drought-affected area, reflecting the instability of their drought conditions.

Contributions

• Addresses the limitations of traditional univariate drought indices and existing composite drought indices by fully integrating six comprehensive water cycle elements and accounting for their lag times.
• Introduces a novel Multi-element Coupled Drought Index (MCDI) that offers enhanced capabilities for comprehensive drought monitoring and assessment in seasonal shallow lake basins.
• Provides a methodological framework for more prompt, accurate, and complete characterization of drought lifecycle and evolution, which can support regional drought prevention and mitigation.

Funding

No funding information was provided in the paper text.

Citation

@article{Zhang2025multielement,
  author = {Zhang, Zhen and Zhang, Wen and Wang, Zhe and Bao, Yi and Ma, Yangyang and Wang, Xi and Wang, Qianyu and Chen, Bingquan and Wang, Huiqi and Miao, Linguang and Li, Linyi and Meng, Lingkui},
  title = {A multi-element coupled drought index for drought characterization in seasonal shallow lake basins},
  journal = {Journal of Hydrology},
  year = {2025},
  doi = {10.1016/j.jhydrol.2025.134760},
  url = {https://doi.org/10.1016/j.jhydrol.2025.134760}
}