RAPID: Investigating the Triggers of the 2023 Wrangell, Alaska Landslides

2023年11月20日晚上，阿拉斯加州兰格尔的社区经历了两次山体滑坡，当时暴风雨伴随着高海拔地区的大风(约每小时70英里)。两次山体滑坡都是在陡峭的森林斜坡上开始的；11英里的山体滑坡造成6人死亡，切断了电力、固定电话和大约75户家庭的通道；而中岭山体滑坡始于一条碎石路的转弯处。这个快速项目的调查团队假设：1)2023年11月风暴的强风和中等降雨量引发了兰格尔山体滑坡，2)碎石路的存在影响了中脊滑坡的范围和轨迹。该团队的主要目标是捕捉这些山体滑坡的短暂数据，以确定它们的启动机制和过程、土壤厚度以及树木和基础设施所起的作用。对数据的分析将为阿拉斯加东南部社区早期预警系统的发展提供信息。数据收集后研讨会将为Wrangell社区提供对当地地质和滑坡机制的更多了解，并有机会指导未来预警系统和/或滑坡事件响应的方向。调查人员将捕获可纳入滑坡模型的现场数据，从而通过现场测量限制输入参数，以便对这些滑坡事件进行反向分析。虽然以前的研究已经建立了滑坡、森林覆盖、坡角和天气事件之间的相关性，但这项工作是在较低的空间分辨率下完成的；这项快速研究将收集特定地点的数据(包括地表和基岩地质、森林特征、滑坡几何和风暴特征)，这些数据是必要的：评估现有的滑坡模型；了解形成机制；以及确定是否应该将风变量与降水和水文观测结合起来，用于滑坡预测模型。现场工作的结果将被纳入全州范围的山体滑坡清单，并提供关于当地地表和基岩地质的高分辨率数据。有关应对这些山体滑坡的成本数据将与2020年12月阿拉斯加海恩斯山体滑坡期间获得的类似数据结合在一起，为阿拉斯加东南部小型社区的应急管理人员提供必要的信息。该奖项反映了NSF的法定使命，并已通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

The community of Wrangell, Alaska experienced two landslides on the night of November 20, 2023, during a storm event accompanied by high winds (~70 mph) at higher elevations. Both landslides initiated on steep, forested slopes; the 11-Mile Slide killed six people and cut off power, telephone landlines, and access to about 75 homes, while the Middle Ridge Slide initiated at a switchback of a gravel road. The team of investigators on this RAPID project hypothesize that 1) the high winds combined with moderate rainfall of the November 2023 storm triggered the Wrangell landslides, and 2) the presence of a gravel road affected the extent and trajectory of the Middle Ridge Slide. The team's primary objective is to capture the ephemeral data from these landslides to determine their initiation mechanisms and processes, soil thickness, and the role that trees and infrastructure played. What is learned from analysis of the data will inform the development of early warning systems for communities throughout Southeast Alaska. A post-data collection workshop will provide the Wrangell community with a greater understanding of local geology and landslide mechanisms, and an opportunity to guide the direction of future early warning systems and/or landslide event response.The investigators will capture field data that can be incorporated into landslide models, thereby constraining input parameters with on-the-ground measurements to allow for back analysis of these landslide events. While previous research has established correlations among landslides, forest cover, slope angle, and weather events, the work was done at lower spatial resolution; this RAPID research will collect site-specific data (including surficial and bedrock geology, forest characteristics, landslide geometry, and storm characteristics) necessary to: evaluate existing landslide models; understand initiation mechanisms; and determine if wind variables should be incorporated with precipitation and hydrologic observations for landslide prediction models. Results from field work will be incorporated into a statewide landslide inventory, and provide high-resolution data on local surficial and bedrock geology. Cost data on the response to these landslides will be combined with similar data obtained during the December 2020 landslides in Haines, Alaska, providing necessary information for emergency managers in small communities throughout Southeast Alaska.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.