Zhao et al. (2025) Integrating topographic characteristics to construct lake and catchment topology on the Tibetan Plateau

Identification

• Journal: Journal of Hydrology Regional Studies
• Year: 2025
• Date: 2025-11-25
• Authors: Fei Zhao, Hong Wei, Guoan Tang, Liyang Xiong
• DOI: 10.1016/j.ejrh.2025.102975

Research Groups

• State Key Laboratory of Climate System Prediction and Risk Management, Nanjing Normal University, Nanjing, China
• School of Geography, Nanjing Normal University, Nanjing, China
• Key Laboratory of Virtual Geographic Environment (Nanjing Normal University), Ministry of Education, Nanjing, China
• Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing, China
• School of Geographic Information and Tourism, Chuzhou University, Chuzhou, China

Short Summary

This study developed a novel lake-oriented algorithm to construct the first temporally consistent lake–catchment topological network for the Tibetan Plateau as of 2000, significantly improving accuracy by preserving true endorheic basins and ensuring data consistency between lake extents and topography.

Objective

• Develop a lake-oriented depression-filling algorithm that distinguishes fake depressions from true endorheic basins.
• Extract temporally consistent lake topological relationships directly from Digital Elevation Models (DEMs), ensuring coherence with the acquisition time of the terrain data.
• Construct a comprehensive, time-specific dataset of lake topological relationships for the Tibetan Plateau around the year 2000.

Study Configuration

• Spatial Scale: Tibetan Plateau (primary study region); Inner Mongolia Plateau (for universality validation).
• Temporal Scale: Circa 2000, reflecting the acquisition time of the Shuttle Radar Topography Mission (SRTM) DEM.

Methodology and Data

• Models used:
  • Novel lake-oriented depression-filling algorithm.
  • D8 algorithm for flow direction calculation.
  • Workflow for lake extraction, monomerization, outlet identification, and catchment delineation.
• Data sources:
  • Shuttle Radar Topography Mission (SRTM) Digital Elevation Model (DEM) (3 arcseconds resolution, collected in 2000).
  • HydroLAKES (as prior knowledge for lake locations).
  • Global Surface Water Dynamics (GSWD) dataset (30 meters resolution, 1984–2020, used for visual validation).

Main Results

• A temporally consistent lake–catchment network for the Tibetan Plateau as of 2000 was produced, containing 3985 lakes.
• Of these, 3743 lakes are endorheic and 242 are exorheic.
• Lakes are categorized as 3764 starting, 19 middle, and 3673 terminal nodes, with 3471 lakes having neither upstream nor downstream connections (simultaneously starting and terminal).
• The average number of upstream lakes (NUL) is 0.09 for inland lakes and 0.14 for outflow lakes.
• The average area of upstream catchments (AUC) is 447.7 square kilometers for inland lakes and 303.1 square kilometers for outflow lakes.
• Validation showed a 95.26% overlap between LCTopo lake polygons and HydroLAKES, with over 73.63% of individual lake pairs having an overlap rate above 80%.
• Over 76% of identified outlet pairs in LCTopo and Lake-TopoCat datasets had a geodesic distance of less than 2 kilometers.
• The algorithm successfully extracted 1915 lakes and their topological relationships from the Inner Mongolia Plateau, demonstrating universality.

Contributions

• Developed a novel lake-oriented depression-filling algorithm that accurately distinguishes true endorheic basins from fake depressions, preserving terrain integrity.
• Created the first temporally consistent lake–catchment topological network (LCTopo dataset) for the Tibetan Plateau as of 2000, directly extracted from DEMs to ensure coherence.
• Introduced an improved approach for identifying lake outlet locations by analyzing elevation gradients, minimizing misidentification errors.
• The LCTopo dataset provides a robust baseline for tracking post-2000 hydrological changes and offers a transferable framework for studying water system evolution in high-altitude regions.
• The method reduces reliance on external lake datasets by mining information directly from DEMs, avoiding temporal mismatch issues prevalent in traditional approaches.
• The algorithm prevents unreasonable situations such as outlets inside terminal lakes or flow paths crossing lake polygons, enhancing hydrological realism.

Funding

• National Nature Science Foundation of China (Grant No. 42371407)
• Foundation of Key Lab of Virtual Geographic Environment (Nanjing Normal University), Ministry of Education (Grant No. 2022VGE03)

Citation

@article{Zhao2025Integrating,
  author = {Zhao, Fei and Wei, Hong and Tang, Guoan and Xiong, Liyang},
  title = {Integrating topographic characteristics to construct lake and catchment topology on the Tibetan Plateau},
  journal = {Journal of Hydrology Regional Studies},
  year = {2025},
  doi = {10.1016/j.ejrh.2025.102975},
  url = {https://doi.org/10.1016/j.ejrh.2025.102975}
}