Luo et al. (2025) Runoff components’ changes and their driving mechanism in a typical cryosphere basin, northeast Tibetan Plateau

Identification

• Journal: Journal of Hydrology Regional Studies
• Year: 2025
• Date: 2025-10-10
• Authors: Yan Luo, Qi Feng, Jiali Xie, Haiyang Xi, Zhenliang Yin, Jinkui Wu, Hongyuan Li
• DOI: 10.1016/j.ejrh.2025.102844

Research Groups

• State Key Laboratory of Ecological Safety and Sustainable Development in Arid Lands, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou, Gansu, China
• University of Chinese Academy of Sciences, Beijing, China
• College of Resources and Environment, Linyi University, Linyi, Shandong, China

Short Summary

This study partitioned runoff components (glacier, snow, rainfall, baseflow) in the Upper Shule River basin (Tibetan Plateau) from 1975 to 2022 using the SPHY model, identifying abrupt changes and their driving mechanisms. It found a significant increase in total runoff, glacier runoff, rainfall runoff, and baseflow, with a declining contribution from snow runoff, primarily driven by combinations of temperature, precipitation, evapotranspiration, vegetation, and snow cover extent.

Objective

• To quantitatively partition the runoff components of the Upper Shule River (USR) from 1975 to 2022 using the SPHY model and analyze the abrupt change year of the climatic and hydrological factors.
• To quantify the differences and changes in spatiotemporal contributions of runoff components to total runoff, and clarify their response patterns to climate change.
• To identify the driving factors (single/multiple factor combinations) of runoff components’ changes at different time scales.

Study Configuration

• Spatial Scale: Upper Shule River (USR) basin, northeast Tibetan Plateau, China. The basin covers approximately 10,946 square kilometers, with elevations ranging from 2038 meters to 5780 meters above sea level. Glaciers cover about 421 square kilometers.
• Temporal Scale: 1975–2022 (48 years). The study identified an abrupt change year in 1998, dividing the period into a baseline (1975–1998) and a changing period (1999–2022).

Methodology and Data

• Models used: Spatial Processes in Hydrology (SPHY) model, Mann-Kendall test (M-K), Pettitt test, Moving T test (MTT), Linear regression, Wavelet Transform Coherence (WTC), Multiple Wavelet Coherence (MWC), Budyko hypothesis (Choudhury-Yang equation).
• Data sources:
  • Meteorological data (daily maximum, average, minimum temperature, and precipitation) from 1975–2022 (China Meteorological Administration).
  • Potential evapotranspiration (ERA5-Land) from 1981–2018 (Copernicus Climate Change Service).
  • Digital Elevation Model (SRTM DEM) at 90 meters resolution (USGS Earth Explorer).
  • Soil physical parameters (HiHydroSoil) at 800 meters resolution (FutureWater).
  • Land cover (CNLUCC) for 1990, 2000, 2010, 2020 at 30 meters resolution (Resource and Environment Science and Data Center).
  • Glacier data (Second glacial catalogue data set of China (v1.0), Glacier outlines over the Qilian Mountain area (1980–2015)) for 1990, 2010 (Tibetan Plateau Data Center).
  • Daily runoff data from 1975–2022 (Gansu Provincial Department of Water Resources).
  • Vegetation (NDVI) and Snow Cover Extent (SCE) from 1981–2018 (Tibetan Plateau Data Center).
  • Snow Cover Area (MOD10A1) from 2001–2018 (MODIS).

Main Results

• Most climatic and hydrological factors in the USR exhibited an abrupt change around 1998.
• Total runoff showed an extremely significant increasing trend at a rate of 5.46 cubic meters per second per decade (p < 0.001) from 1975 to 2022.
• Glacier runoff significantly increased at a rate of 1.0 cubic meter per second per decade (Z = 3), but its trend shifted to a decrease after the abrupt change in 1995.
• Baseflow exhibited an extremely significant increasing trend at a rate of 1.40 cubic meters per second per decade (Z = 4.36*), shifting from a decreasing to an increasing trend after 1997.
• Rainfall runoff also showed an extremely significant increase at a rate of 1.79 cubic meters per second per decade (Z = 3.62*), accelerating after 2007.
• Snow runoff displayed no statistically significant change in magnitude (0.55 cubic meters per second per decade, Z = 1.36), but its contribution to total runoff exhibited an extremely significant declining trend (Z = -2.82**), decreasing from 19% before to 15% after the abrupt change.
• The average contributions to total runoff (1975–2022) were: baseflow (30%), glacier runoff (30%), rainfall runoff (23%), and snow runoff (17%).
• Monthly, glacier and rainfall runoff predominantly occur from June to August, while snow runoff peaks in May. Baseflow peaks in August and September due to recharge lag.
• Spatially, glacier meltwater yield exceeded 1500 millimeters in alpine glacier areas, contributing 60%-70% to total runoff in headwater tributaries. Baseflow constituted over 50% of total runoff in the main stream.
• The dominant driving factor combinations for runoff components were:
  • Total runoff: Temperature (TEM) – Normalized Difference Vegetation Index (NDVI)
  • Glacier runoff: Precipitation (PCP) – TEM – Potential Evapotranspiration (ETp)
  • Baseflow: PCP – NDVI – Snow Cover Extent (SCE)
  • Rainfall runoff: PCP – TEM – ETp
  • Snow runoff: PCP – NDVI
• Single factors alone could not adequately explain runoff changes; synergies of multiple factors showed more robust impacts.
• Attribution analysis based on the Budyko hypothesis indicated that runoff changes were mainly driven by climate change (54.8% total contribution), with precipitation changes being a significant factor (56.1%). Underlying surface changes (45.2%) were also largely influenced by climate.

Contributions

• First study to quantitatively partition runoff components (glacier, snow, rainfall, baseflow) in the Upper Shule River basin from 1975 to 2022 using the SPHY model.
• Provided a comprehensive analysis of abrupt change years for various climatic and hydrological factors in the region.
• Quantified the spatiotemporal contributions of different runoff components to total runoff and clarified their response patterns to climate change.
• Identified the complex driving factors (single and multiple factor combinations) of runoff component changes at different time scales using advanced wavelet analysis (WTC and MWC), addressing a critical gap in existing literature.
• Offers crucial insights for predicting future hydrological changes and formulating adaptive water resource management strategies in cryosphere basins.

Funding

• Strategic Priority Research Program of the Chinese Academy of Sciences (Project No. XDB0720200)
• “Light of West China” Program of CAS (Project Nos. xbzglzb2022020, 23JR6KA008)
• Gansu Provincial Science and Technology Planning Project (Project No. 23ZDFA018)
• Inter-institute Youth Joint Fund project of Lanzhou Branch, Chinese Academy of Sciences (Project No. E4400404)

Citation

@article{Luo2025Runoff,
  author = {Luo, Yan and Lu, Zhixiang and Feng, Qi and Xie, Jiali and Zhang, Jinbo and Xi, Haiyang and Yin, Zhenliang and Wu, Jinkui and Li, Hongyuan},
  title = {Runoff components’ changes and their driving mechanism in a typical cryosphere basin, northeast Tibetan Plateau},
  journal = {Journal of Hydrology Regional Studies},
  year = {2025},
  doi = {10.1016/j.ejrh.2025.102844},
  url = {https://doi.org/10.1016/j.ejrh.2025.102844}
}