Bai et al. (2025) Tracking drought-flood abrupt alternations: Event identification, path analysis, and ecological impacts on vegetation

Identification

• Journal: Journal of Hydrology
• Year: 2025
• Date: 2025-12-25
• Authors: Xiaoyan Bai, Yue Yao, Jiefeng Wu, Yulei Xie, Zhenxing Zhang
• DOI: 10.1016/j.jhydrol.2025.134858

Research Groups

• Guangzhou Key Laboratory of Environmental Catalysis and Pollution Control, Guangdong Key Laboratory of Environmental Catalysis and Health Risk Control, School of Environmental Science and Engineering, Institute of Environmental Health and Pollution Control, Guangdong University of Technology, Guangzhou, China
• College of Civil Engineering, Hefei University of Technology, Hefei, China
• School of Ecology, Environment and Resources, Guangdong University of Technology, Guangzhou, China
• Illinois State Water Survey, Prairie Research Institute, University of Illinois at Urbana-Champaign, Champaign, IL, USA

Short Summary

This study introduces a novel three-dimensional method to identify drought-to-flood and flood-to-drought abrupt alternation events in the Pearl River Basin, quantifying their spatiotemporal characteristics and evaluating their distinct ecological impacts on vegetation.

Objective

• To propose and apply a novel three-dimensional identification method for drought-to-flood (DTF) and flood-to-drought (FTD) abrupt alternation events.
• To quantify key spatiotemporal features (duration, area, intensity, centroid, and migration direction) of identified DTF and FTD events.
• To evaluate the ecological responses of vegetation, using anomalies in fractional vegetation cover (FVC), normalized difference vegetation index (NDVI), and net primary productivity (NPP), to these abrupt alternation events.

Study Configuration

• Spatial Scale: Pearl River Basin, China.
• Temporal Scale: 1979–2018 (40 years).

Methodology and Data

• Models used: A novel three-dimensional identification method for drought-to-flood (DTF) and flood-to-drought (FTD) events.
• Data sources: Anomalies in fractional vegetation cover (FVC), normalized difference vegetation index (NDVI), and net primary productivity (NPP), likely derived from satellite observations or reanalysis products.

Main Results

• The method successfully identified 47 drought-to-flood (DTF) and 52 flood-to-drought (FTD) events during the 1979–2018 period.
• A majority of events, 41 DTF and 39 FTD, exhibited a predominant westward migration.
• DTF events had longer migration durations (mean: 4.7 months) and larger affected areas (mean coverage: 66%) compared to FTD events (4.0 months; 57% coverage).
• Spatiotemporal centroids for DTF events were concentrated in the central basin from February to April, while for FTD events they were from July to September.
• Vegetation FVC/NDVI showed a rapid response to DTF events (1–2 months lag) but a delayed response to FTD events (6–8 months lag).
• Net primary productivity (NPP) consistently displayed low sensitivity with a 7-month lag to both DTF and FTD events.
• DTF events initially exerted stronger inhibition on vegetation than FTD events; however, FVC/NDVI suppression weakened over time, and NPP showed increasingly positive responses.

Contributions

• Introduces a novel three-dimensional identification method for drought-flood abrupt alternation (DFAA) events, addressing their inherent spatiotemporal continuity previously overlooked in isolated temporal or spatial analyses.
• Provides a comprehensive quantification of key spatiotemporal features (duration, area, intensity, centroid, migration direction) for both drought-to-flood and flood-to-drought events.
• Reveals distinct and complex ecological response mechanisms of vegetation (FVC, NDVI, NPP) to different types of DFAA events, including varying lag times and long-term trends in suppression or positive response.

Funding

Not specified in the provided text.

Citation

@article{Bai2025Tracking,
  author = {Bai, Xiaoyan and Yao, Yue and Wu, Jiefeng and Xie, Yulei and Zhang, Zhenxing},
  title = {Tracking drought-flood abrupt alternations: Event identification, path analysis, and ecological impacts on vegetation},
  journal = {Journal of Hydrology},
  year = {2025},
  doi = {10.1016/j.jhydrol.2025.134858},
  url = {https://doi.org/10.1016/j.jhydrol.2025.134858}
}