Song et al. (2026) Temporal Lag and Response Characteristics of Runoff and Its Components in a Glacial Basin

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Identification

• Journal: Remote Sensing
• Year: 2026
• Date: 2026-09-20
• Authors: Mengwei Song, Hailong Liu, Guoqing Tang, Xuhong Gong, Xi Chen, Tie Liu, Manuchekhr Gulakhmadov, Aminjon Gulakhmadov, Firdavs Shaimuradov
• DOI: 10.3390/rs18183235

Research Groups

• Institute of Mountain Hazards and Environment, Chinese Academy of Sciences
• Key Laboratory of Mountain Hazards and Environment
• University of the Chinese Academy of Sciences

Short Summary

This paper investigates the driving factors of runoff and its components in the Vakhsh River basin of Tajikistan using a combination of baseflow separation methods and machine learning approaches. The study reveals significant effects of snow-related variables and vegetation index on runoff and its components, with varying time lags between dry and wet seasons.

Objective

• Identify the driving factors of runoff and its components in glacial basins
• Quantitatively evaluate the impacts of hydroclimatic variables on runoff and its components

Study Configuration

• Spatial Scale: The Vakhsh River basin in Tajikistan, a mountainous region with glaciers
• Temporal Scale: Daily to seasonal time scales for data analysis

Methodology and Data

• Models used:
  • Chapman–Maxwell baseflow separation method
  • Categorical Boosting (CatBoost) machine learning algorithm
  • SHapley Additive exPlanations (SHAP) analysis
• Data sources: Satellite remote-sensing products, reanalysis datasets, and in-situ observations

Main Results

• The Chapman–Maxwell baseflow separation method demonstrates superior performance among nine evaluated methods.
• Snow-related variables and Normalized Difference Vegetation Index (NDVI) have significant effects on runoff and its components in both dry and wet seasons.
• Time lags of surface runoff, total runoff, and baseflow vary between dry and wet seasons, with shorter time lags in the wet season.

Contributions

This study provides a comprehensive understanding of the driving factors of runoff and its components in glacial basins, filling the knowledge gap in this research area. The results can be used to inform climate change mitigation and adaptation strategies for glacial regions.

Funding

• National Natural Science Foundation of China (Grant No. 41971045)
• Key Research Program of Frontier Sciences, Chinese Academy of Sciences (Grant No. QYZDY-SSW-DQC001)

Citation

@article{Song2026Temporal,
  author = {Song, Mengwei and Liu, Hailong and Tang, Guoqing and Gong, Xuhong and Chen, Xi and Liu, Tie and Gulakhmadov, Manuchekhr and Gulakhmadov, Aminjon and Shaimuradov, Firdavs},
  title = {Temporal Lag and Response Characteristics of Runoff and Its Components in a Glacial Basin},
  journal = {Remote Sensing},
  year = {2026},
  doi = {10.3390/rs18183235},
  url = {https://doi.org/10.3390/rs18183235}
}