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Retrospective Assessment of Urban Flooding Susceptibility on the Qinghai–Tibet Plateau Under Data Scarcity

Datos Bibliográficos

ID22034404
AutoresYanjie Liu (0000-0003-3948-1246, Tibet University), YuHeng Liu (0000-0002-6645-4772, College of Water Conservancy and Civil Engineering, Xizang Agricultural and Animal Husbandry University, Nyingchi 860000, China), Libin Su (0009-0007-1017-9883, Tibet University, autor de correspondencia), Yongtao Yang (0000-0001-6508-0804, Kun Shan University), Yonggang Guo (0000-0001-5303-4886, Tibet University), Tongliang Gong (Tibet University)
Año2026
Volumen15
Número7
Páginas309
Fecha de publicación2026-07-07
Peer ReviewedSí
Open AccessSí
TipoARTICLE
RevistaISPRS International Journal of Geo-Information (JOURNAL)
Identificadores de la revistaISSN: 2220-9964 • E-ISSN: 2220-9964
EditorialMDPI AG (PUBLISHER • IT)
DOI10.3390/ijgi15070309
OpenAlexW7167580999
IdiomaEN
Referencias citadas36

Quantitative assessment of historical urban waterlogging on the Qinghai–Tibet Plateau (QTP) is severely hindered by the lack of early instrumental records. To bridge this data gap during the initial rapid urbanization period (1985–2003), this study proposes an integrated retrospective framework combining Large Language Models (LLMs)-based semantic mining, spatial reconstruction, and Extreme Gradient Boosting (XGBoost)- SHapley Additive exPlanations (SHAP) modeling under a Spatial Block Cross-Validation (SBCV) strategy. Historical disaster archives were transformed into spatially explicit training samples, enabling the reconstruction of a high-resolution urban waterlogging susceptibility atlas across the QTP. The results indicate that high-susceptibility areas are predominantly concentrated within urbanized river valleys and account for approximately 45% of the total urban built-up area across the QTP. The proposed framework achieved an Area Under the Receiver Operating Characteristic Curve (AUC) of 0.9793 under the SBCV strategy, indicating good spatial transferability within the study area. SHAP analysis revealed that geomorphic variables contributed more strongly than most climatic variables, highlighting the important role of a geomorphic confinement effect in shaping susceptibility patterns. Comparative analyses further suggest a spatial transition from basin-dominated accumulation patterns to increasingly valley-confined susceptibility distributions under stronger topographic constraints. In addition, surface albedo and land surface temperature were identified as influential predictors, likely reflecting integrated thermal-hydrological conditions associated with antecedent soil moisture and local urban thermal dynamics. This study establishes a historical risk baseline for the QTP and provides a reproducible and cost-effective framework for historical hazard assessment in other data-scarce mountainous and high-altitude regions

Hazard · Hazard analysis · Land cover · Land use · Spatial analysis · Urbanization · Flood Risk Assessment and Management · Groundwater and Watershed Analysis · Tropical and Extratropical Cyclones Research

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