An integrated simulation-learning framework for rapid prediction of regional snow avalanche runout and hazard metrics
文献类型：期刊论文
| 作者 | Guo, Jian2; Li, Yao1; Hao, Jiansheng2; Zhang, Zhao3 |
| 刊名 | ENGINEERING GEOLOGY
 |
| 出版日期 | 2025-10-01 |
| 卷号 | 357页码:108373 |
| 关键词 | Snow avalanche Deep neural networks (DNN) Dynamic simulations Machine learning Hazard mapping Early warning |
| ISSN号 | 0013-7952 |
| DOI | 10.1016/j.enggeo.2025.108373 |
| 产权排序 | 1 |
| 文献子类 | Article |
| 英文摘要 | Snow avalanches pose significant and growing risks in the southeastern Tibetan Plateau, where steep terrain and limited data availability challenge effective hazard assessment. This study proposes a hybrid modeling framework (ADS-DNN), which integrates a limited set of physically based avalanche simulations with deep neural networks to enable rapid prediction of key hazard metrics at a regional scale. A total of 206 simulations were conducted using real terrain and snow parameters across diverse avalanche-prone basins. The simulation results serve as training data for the neural network, which uses terrain and snow features, such as slope, elevation, depth, and density, to predict four key indicators: the maximum runout distance, velocity, flow depth, and deposition area. Field photos were used to validate the simulation reliability and support model calibration. Applied to the Nyingchi region, the ADS-DNN model achieves high predictive performance while reducing computation time from four days to a few minutes. This framework provides a scalable and transferable solution for avalanche hazard mapping and early warning in mountainous regions with limited monitoring data. While the approach demonstrates good performance, its accuracy depends on the representativeness of the simulated scenarios and is constrained by the limited availability of detailed field observations. |
| URL标识 | 查看原文 |
| WOS关键词 | LANDSLIDE ; MODEL |
| WOS研究方向 | Engineering ; Geology |
| 语种 | 英语 |
| WOS记录号 | WOS:001583997700001 |
| 出版者 | ELSEVIER |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/217531]  |
| 专题 | 陆地表层格局与模拟院重点实验室_外文论文 |
| 通讯作者 | Li, Yao |
| 作者单位 | 1.Tsinghua Univ, State Key Lab Hydrosci & Engn, Beijing 100084, Peoples R China; 2.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Land Surface Pattern & Simulat, Beijing 100101, Peoples R China; 3.Cent South Univ, Sch Geosci & Infophys, Changsha 410083, Peoples R China |
| 推荐引用方式 GB/T 7714 | Guo, Jian,Li, Yao,Hao, Jiansheng,et al. An integrated simulation-learning framework for rapid prediction of regional snow avalanche runout and hazard metrics[J]. ENGINEERING GEOLOGY,2025,357:108373. |
| APA | Guo, Jian,Li, Yao,Hao, Jiansheng,&Zhang, Zhao.(2025).An integrated simulation-learning framework for rapid prediction of regional snow avalanche runout and hazard metrics.ENGINEERING GEOLOGY,357,108373. |
| MLA | Guo, Jian,et al."An integrated simulation-learning framework for rapid prediction of regional snow avalanche runout and hazard metrics".ENGINEERING GEOLOGY 357(2025):108373. |
入库方式： OAI收割
来源：地理科学与资源研究所
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