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Optimizing a prediction model for engineering disturbance hazard susceptibility along the China-Nepal highway in the Qinghai-Tibet plateau

  • 01-01-2026
  • Original Paper
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Abstract

The article delves into the types and susceptibility of engineering disturbance hazards (HEDH) along the China-Nepal Highway in the Qinghai-Tibet Plateau. Through extensive field investigations, the study identifies six primary types of HEDH, including earth slides, debris-bedrock binary slides, rock topples, earth-rock mixture slides, earth-rock mixture falls, and rock falls. The research highlights the significant impact of human engineering activities on geologic hazards, particularly in regions with complex geological conditions. The study introduces an optimized Convolutional Neural Network (CNN) framework to predict hazard susceptibility, demonstrating superior performance compared to traditional machine learning models. By incorporating Tobler's First Law of Geography, the optimized model effectively captures the spatial context of hazard points, leading to more accurate susceptibility assessments. The findings provide valuable insights for hazard prevention and mitigation along the China-Nepal transport corridor and offer broader implications for similar research in other regions.

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Title
Optimizing a prediction model for engineering disturbance hazard susceptibility along the China-Nepal highway in the Qinghai-Tibet plateau
Authors
Lei Li
Zhiqing Li
Shuangjiao Wang
Kai Sun
Ruilin Hu
Publication date
01-01-2026
Publisher
Springer Berlin Heidelberg
Published in
Bulletin of Engineering Geology and the Environment / Issue 1/2026
Print ISSN: 1435-9529
Electronic ISSN: 1435-9537
DOI
https://doi.org/10.1007/s10064-025-04669-2
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