Zhou et al. (2025) Detecting time-varying characteristics of the integrated parameter in the generalized complementary principle based on long-term flux data

Identification

• Journal: Journal of Hydrology
• Year: 2025
• Date: 2025-12-09
• Authors: Lihao Zhou, Lei Cheng, Xiao‐Jing Zhang, Xiao Wang, Shuai Wang, Lei Xiong, Lu Zhang
• DOI: 10.1016/j.jhydrol.2025.134751

Research Groups

• State Key Laboratory of Water Resources Engineering and Management, Wuhan University, Wuhan, China
• School of Water Resources and Hydropower Engineering, Wuhan University, Wuhan, China

Short Summary

This study investigated the temporal variability of the integrated parameter αc in the generalized complementary relationship (GCR) using long-term flux data from seven sites, revealing that incorporating its temporal dynamics significantly improves regional evaporation estimation across various time scales.

Objective

• To evaluate the temporal variability and transferability of the integrated parameter αc in the generalized complementary relationship (GCR) across daily, monthly, and annual scales.
• To identify the key climatic drivers influencing the temporal dynamics of αc.

Study Configuration

• Spatial Scale: Seven flux tower sites.
• Temporal Scale: Long-term data (>10 years) analyzed at daily, monthly, and annual scales.

Methodology and Data

• Models used: Generalized complementary relationship (GCR), Sliding Window Divided Sample Calibration (SWD-SSC) method, Stepwise regression analysis.
• Data sources: Long-term flux data from seven flux tower sites, meteorological variables (shortwave radiation, air temperature, vapor pressure deficit).

Main Results

• Incorporating temporal variation of yearly αc improved evaporation estimation in 3 of 7 sites, with Kling-Gupta Efficiency (KGE) improvements exceeding 0.1 (up to 0.27).
• αc exhibited greater non-transferability during winter months, indicated by broader KGE ranges.
• The majority (95%) of inverted αc values ranged from 0.38 to 3.44 (daily), 0.52 to 1.70 (monthly), and 0.72 to 1.22 (annual).
• Daily αc showed consistent seasonal variation inter-annually but substantial differences spatially.
• Monthly αc values demonstrated stronger correlations with meteorological variables compared to daily values.
• Stepwise regression identified shortwave radiation, air temperature, and vapor pressure deficit as dominant drivers of αc dynamics across all time scales.

Contributions

• First study to systematically evaluate the temporal variability and transferability of the GCR's integrated parameter αc across multiple time scales using long-term flux data.
• Provides quantitative evidence for the necessity of incorporating temporal variability of αc to improve GCR-based evaporation estimation.
• Identifies key climatic drivers of αc's temporal dynamics, enhancing understanding of its physical basis.

Funding

Not specified in the provided text.

Citation

@article{Zhou2025Detecting,
  author = {Zhou, Lihao and Cheng, Lei and Zhang, Xiao‐Jing and Wang, Xiao and Wang, Shuai and Xiong, Lei and Zhang, Lu},
  title = {Detecting time-varying characteristics of the integrated parameter in the generalized complementary principle based on long-term flux data},
  journal = {Journal of Hydrology},
  year = {2025},
  doi = {10.1016/j.jhydrol.2025.134751},
  url = {https://doi.org/10.1016/j.jhydrol.2025.134751}
}