Abstract Rockfall is a dangerous hazard on steep and susceptible slope. However, it is not easy to identify potential rockfalls on cliff mountains. Traditionally, rockfall risk analysis ignores the temporal evolution of risk due to the changes of the elements at risk, or changes in the annual probability. This may lead to an underestimation of risk in time. In this paper, we present an innovative approach for a dynamic risk analysis, and we demonstrate this approach for the ShenXianjJu scenic area case study, where rockfall represent a threat for thousands of tourists each year. Moreover, we studied the role of rock mass quality in controlling the rockfall potential and rockfall volume, since this may lead to significant changes of rockfall risk in space. We describe the use of Unmanned Aerial Vehicle, Terrestrial LiDAR and detailed field surveys to identify 34 potential rockfalls on slopes where historical rockfalls have occurred. Within ignimbrite and rhyolite rock masses rockfall blocks range in size between large and very large. Andesite derived rockfalls are characterized by medium-size to large block size. Faulted and fractured ignimbrite and rhyolite rock masses within the fault damage zone exhibit small-very small rockfall block sizes. Based on the identified potential rockfalls in the study area, we quantified the dynamic risk by considering the temporal–spatial changes of tourist activity. To demonstrate the methodology, two potential rockfalls on two heavily-used tourist routes were selected. For these scenarios we quantified the annual probability of occurrence, the reach probability, the dynamic temporal-spatial probability, and the vulnerability of tourists. The dynamic temporal probability was also calculated considering different visiting periods (e.g., working days, weekends, holidays), showing significant changes in the risk level among the different visiting periods and with time. Some of the investigated scenarios were within the ALARP zone in the first years (i.e. PLL on workday in 2017–2019), and subsequently became unacceptable (i.e. PLL on workday in 2020). As a conclusion, the research demonstrates that the traditional static risk analysis would lead to a significant rockfall risk underestimation.

中文翻译：

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动态落石风险分析

摘要 落石是陡坡易感边坡上的一种危险灾害。然而，在悬崖山上识别潜在的落石并不容易。传统上，落石风险分析忽略了由于风险要素的变化或年度概率的变化而导致的风险的时间演变。这可能会导致对时间风险的低估。在本文中，我们提出了一种动态风险分析的创新方法，并在神仙居风景区案例研究中展示了这种方法，这里的落石对每年成千上万的游客构成威胁。此外，我们研究了岩体质量在控制落石潜力和落石量中的作用，因为这可能会导致空间落石风险的显着变化。我们描述了无人机的使用，地面 LiDAR 和详细的实地调查，以确定发生历史落石的斜坡上的 34 处潜在落石。在熔凝灰岩和流纹岩岩体中，落石块的大小介于大和非常大之间。安山岩衍生的落石具有中到大块大小的特点。断层破坏带内的断层和断裂的熔凝灰岩和流纹岩岩体表现出小到非常小的落石块尺寸。基于在研究区识别出的潜在落石，我们通过考虑旅游活动的时空变化来量化动态风险。为了演示该方法，在两条经常使用的旅游路线上选择了两个潜在的落石点。对于这些场景，我们量化了年度发生概率、到达概率、动态时空概率、以及游客的脆弱性。还考虑了不同的访问时段（例如工作日、周末、节假日）计算了动态时间概率，显示了不同访问时段之间的风险水平以及随时间的显着变化。一些调查的情景在最初几年处于 ALARP 区域内（即 2017-2019 年工作日的 PLL），随后变得不可接受（即 2020 年工作日的 PLL）。总之，研究表明，传统的静态风险分析会导致严重的落石风险低估。一些调查的情景在最初几年处于 ALARP 区域内（即 2017-2019 年工作日的 PLL），随后变得不可接受（即 2020 年工作日的 PLL）。总之，研究表明，传统的静态风险分析会导致严重的落石风险低估。一些调查的情景在最初几年处于 ALARP 区域内（即 2017-2019 年工作日的 PLL），随后变得不可接受（即 2020 年工作日的 PLL）。总之，研究表明，传统的静态风险分析会导致严重的落石风险低估。