Wang et al. (2026) Seasonal variation patterns and drivers of baseflow recession dynamics across Australia

Identification

• Journal: Journal of Hydrology
• Year: 2026
• Date: 2026-03-21
• Authors: Tianmei Wang, Lei Cheng, Xuxin Lei, Yunfan Zhang, Shujie Cheng, Chenhao Fu, Yao Lai, Lu Zhang
• DOI: 10.1016/j.jhydrol.2026.135347

Research Groups

• State Key Laboratory of Water Resources Engineering and Management, Wuhan University
• School of Water Resources and Hydropower Engineering, Wuhan University
• Sichuan Hydrological and Water Resources Survey Center
• Hubei Key Laboratory of Water Resources & Eco-Environmental Sciences, Changjiang River Scientific Research Institute

Short Summary

This study quantifies the event-scale seasonal variation of the baseflow recession parameter 'a' across 596 Australian catchments and identifies vegetation, temperature, and evaporative demand as key drivers using machine learning.

Objective

• To quantify event-scale temporal variation in the baseflow recession parameter 'a' and investigate its governing drivers across Australian catchments.

Study Configuration

• Spatial Scale: 596 Australian catchments, stratified into temperate, grassland, and tropical hydro-climatic regions.
• Temporal Scale: Event-scale, with a focus on seasonal variation patterns.

Methodology and Data

• Models used: Periodic and seasonal analysis, Boosted Regression Trees (BRT) machine learning method, post-hoc interpretation technique.
• Data sources: Recession events from 596 Australian catchments.

Main Results

• Temporal variation of the recession parameter 'a' is predominantly seasonal, contributing over 50% of the total variation, and exhibits a consistent cosine-like pattern across all regions.
• Vegetation, temperature, and evaporative demand factors are identified as primary influences on parameter 'a', accounting for over 90% of the variation in the three hydro-climatic regions.
• Parameter 'a' is interactively modulated by meteorological factors and vegetation dynamics, showing a universal negative correlation with vegetation cover and a positive relationship with temperature in temperate and grassland regions.

Contributions

• Advances the mechanistic understanding of baseflow dynamics by revealing the seasonal pattern of event-scale recession parameter 'a' and its modulation by meteorological and vegetation factors.
• Offers critical insights for water resource management under climate change by quantifying the drivers of baseflow recession.

Funding

• Not available in the provided text.

Citation

@article{Wang2026Seasonal,
  author = {Wang, Tianmei and Cheng, Lei and Lei, Xuxin and Zhang, Yunfan and Cheng, Shujie and Fu, Chenhao and Lai, Yao and Zhang, Lu},
  title = {Seasonal variation patterns and drivers of baseflow recession dynamics across Australia},
  journal = {Journal of Hydrology},
  year = {2026},
  doi = {10.1016/j.jhydrol.2026.135347},
  url = {https://doi.org/10.1016/j.jhydrol.2026.135347}
}