Enhanced understanding of hydrological connectivity among lakes on the Qiangtang Plateau

Accurate catchment delineation and lake connectivity assessment are crucial for understanding hydrological conditions and managing water resources. However, the accuracy and timeliness of Digital Elevation Models (DEM) constrain existing catchment datasets. Temporal mismatches between DEM acquisitio...

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Bibliographic Details
Main Authors: Yunmei Li, Chang Huang, Ninglian Wang, Yun Chen, Shiqiang Zhang, Hongtao Duan
Format: Article
Language:English
Published: Taylor & Francis Group 2025-12-01
Series:International Journal of Digital Earth
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Online Access:https://www.tandfonline.com/doi/10.1080/17538947.2025.2450845
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Summary:Accurate catchment delineation and lake connectivity assessment are crucial for understanding hydrological conditions and managing water resources. However, the accuracy and timeliness of Digital Elevation Models (DEM) constrain existing catchment datasets. Temporal mismatches between DEM acquisition and lake datasets further undermine the reliability of analyses. By employing the Forest And Buildings removed Copernicus DEM (FABDEM) and a 2015 lake dataset, this study has updated the delineations of 798 lake catchments on the Qiangtang Plateau. From these lake catchments, 434 whole catchments are identified based on inter-lake connectivity, with 144 encompassing multiple lakes. The multi-lake whole catchments are further categorized into three types: 89 single-linkage, 30 dendritic, and 25 convergent based on the cascading structures of them using graph theory. This provides a refined understanding of the hierarchical organization within the lake networks. Furthermore, projected reductions to 408 whole catchments by 2030 and 391 by 2050 due to global warming underscore the dynamic impacts of climate change on lake connectivity. This research is crucial for understanding lake system hydrodynamics, enhancing water quality, flood control, and resource management, and for developing strategies and models to mitigate climate change impacts.
ISSN:1753-8947
1753-8955