Gao et al. (2025) Dynamics and Drivers of Suprapermafrost Groundwater on the Qinghai–Tibet Plateau Under Climate Change

⚠️ Warning: This summary was generated from the abstract only, as the full text was not available.

Identification

• Journal: Water Resources Research
• Year: 2025
• Date: 2025-11-01
• Authors: Zeyong Gao, Guoan Yin, Fujun Niu, Yibo Wang, Jing Luo, Zhanju Lin, Yunhu Shang, C. X. Zhang, Wenyan Liu
• DOI: 10.1029/2025wr040246

Research Groups

Not specified in the abstract.

Short Summary

This study investigated the seasonal dynamics, drivers, and future projections of suprapermafrost groundwater (SPG) in alpine meadow and alpine wet meadow ecosystems on the Qinghai–Tibet Plateau. It found that SPG fluctuations are primarily driven by thaw depth and rainfall infiltration, with climate warming projected to significantly deepen SPG tables by the 2090s.

Objective

• To investigate the seasonal variation, drivers, and projections of suprapermafrost groundwater (SPG) dynamics in alpine meadow (AM) and alpine wet meadow (AWM) ecosystems on the Qinghai–Tibet Plateau.

Study Configuration

• Spatial Scale: Qinghai–Tibet Plateau (QTP), specifically focusing on alpine meadow and alpine wet meadow ecosystems.
• Temporal Scale: Warm season (for observations), seasonal (for dynamics), and projections for the 2090s.

Methodology and Data

• Models used: XGBoost, LightGBM, RandomForest (Machine Learning models).
• Data sources: In situ observations, geophysical surveys.

Main Results

• Suprapermafrost groundwater (SPG) tables ranged from -1.1 to -0.1 m in alpine meadow and from -1.3 to -0.2 m in alpine wet meadow during the warm season.
• SPG fluctuations were primarily driven by thaw depth (TD) and rainfall infiltration, exhibiting similar seasonal patterns across both ecosystems.
• A greater thaw depth was associated with a deeper SPG table, indicating an exponential relationship between TD and SPG table position, and a linear relationship with aquifer thickness.
• Rainfall infiltration increased shallow soil moisture and elevated SPG tables, with responses influenced by rainfall intensity, duration, and infiltration pathways.
• Spatial heterogeneity in SPG distribution was further shaped by vegetation structure and microtopographic variation.
• Machine learning models projected that mean summer SPG table depths in the 2090s would increase by 0.06 m under SSP126 and 0.64 m under SSP585 in alpine wet meadow ecosystems.
• For alpine meadow ecosystems, projections indicated an increase of 0.37 m under SSP126 and 0.87 m under SSP585 by the 2090s.

Contributions

• Provides new insights into how climate warming affects hydrological processes in permafrost regions of the Qinghai–Tibet Plateau.
• Integrates in situ observations, geophysical surveys, and machine learning models to comprehensively analyze SPG dynamics.
• Quantifies the primary drivers (thaw depth and rainfall infiltration) of SPG fluctuations and their relationships.
• Offers future projections of SPG table depths under different climate change scenarios (SSP126, SSP585).

Funding

Not specified in the abstract.

Citation

@article{Gao2025Dynamics,
  author = {Gao, Zeyong and Yin, Guoan and Niu, Fujun and Wang, Yibo and Luo, Jing and Lin, Zhanju and Shang, Yunhu and Zhang, C. X. and Liu, Wenyan},
  title = {Dynamics and Drivers of Suprapermafrost Groundwater on the Qinghai–Tibet Plateau Under Climate Change},
  journal = {Water Resources Research},
  year = {2025},
  doi = {10.1029/2025wr040246},
  url = {https://doi.org/10.1029/2025wr040246}
}