Robustness evaluation of the probability-based HTCA model for simulating debris-flow run-out extent: Case study of the 2010 Hongchun event, China
Robustness evaluation of the probability-based HTCA model for simulating debris-flow run-out extent: Case study of the 2010 Hongchun event, China
复制标题
基于概率的 HTCA 泥石流跳动范围模拟模型的鲁棒性评估：以 2010 年中国红春事件为例
DOI：
10.1016/j.enggeo.2022.106918
复制
发表时间：
2023
影响因子：
7.4
通讯作者：
Dou Jie
中科院分区：
文献类型：
--
作者：
Ma Yangfan;Han Zheng;Li Yange;Chen Guangqi;Wang Weidong;Chen Ningsheng;Hu Guisheng;Zhao Lianheng;Dou Jie
基于概率的元胞自动机（CA）模型是模拟泥石流溃决程度的有用工具。尽管CA模型具有很高的计算效率，但模拟结果往往对几个关键参数敏感，特别是蒙特-卡罗迭代（MCI）的步骤和数字地形模型（DTM）数据的空间分辨率。这些信息是评估CA模型在处理各种情况下的鲁棒性的基础。该研究改进了现有的基于流体力学和地形学的元胞自动机（HTCA）模型。简要回顾了该模型的基本原理，并分析了MCI值和DTM空间分辨率的敏感性。探讨了河床挟沙和淤地坝影响的各种实际情况，这有利于评估HTCA模型处理复杂条件的能力。以2010年8月14日发生在汶川东部洪春流域的震后泥石流为例，分析了关键参数对模拟结果的影响。结果表明，该模型的鲁棒性，在处理特定的场景。敏感性分析表明，MCI值和DTM的空间分辨率对模拟结果有明显的影响。根据输入DTM数据的分辨率选择MCI值，可以改善HTCA模型的模拟结果。
Probability-based cellular automaton (CA) models are useful alternative tools for simulating the extent of debris flow run-out. Despite that CA models have high computational efficiency, the simulation results are often sensitive to several key parameters, in particular, the steps of Monte-Carlo iterations (MCI), and the spatial resolution of the digital terrain model (DTM) data. This information is fundamental for evaluating the robustness of the CA model in dealing with various cases. This study improves upon the existing hydrodynamic and topography-based cellular automaton (HTCA) model. The basics of the model are briefly reviewed, and the sensitivity of the MCI value and the DTM spatial resolution are analyzed. Various practical scenarios regarding the effects of bed sediment entrainment and check dams are explored, which is beneficial for assessing the capability of the HTCA model in dealing with complex conditions. The August 14, 2010, post-seismic debris-flow event in the Hongchun catchment in the eastern Wenchuan area of China is selected as a case study to demonstrate the influence of key parameters on the simulation. The results illustrate the model's robustness in dealing with specific scenarios. Sensitivity analysis suggests that the MCI value and the DTM spatial resolution have obvious influences on the simulation results. The simulation results of the HTCA model can be improved if the MCI value is chosen based on the resolution of the input DTM data.