Collaborative Research: Lahar dynamics and Monitoring: A multiparametric approach grounded in infrasound

合作研究：拉哈尔动力学和监测：基于次声的多参数方法

• 批准号: 1914526
• 负责人: Gregory Waite
• 金额: $ 29.47万
• 依托单位: Michigan Technological University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-08-01 至 2024-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1914526&HistoricalAwards=false
• 关键词: Collaborative; Research; Lahar; dynamics; Monitoring

Lahars, or volcanic mud flows, produce infrasound (low-frequency acoustic energy) that can be detected from distances of many kilometers. As such, it is possible to remotely characterize these hazardous mud flows by tracking their flow positions and energetics through time. This work seeks to develop infrasound analytical tools to locate where lahars initiate, how far and fast they move, and estimate their mass flow. Toward these goals the project will deploy and maintain seismic and infrasonic instruments at Fuego Volcano (Guatemala), where lahars are common during the rainy season (April through September). Rain gauges and time lapse cameras will be installed at locations along the lahar paths to understand how lahars initiate and to validate flow characteristics through direct observation. Fuego volcano is an ideal candidate for this study because of its frequent lahars and relatively easy access and because information learned will be applicable for mitigating risks. Lessons learned at Fuego may then be applied to dozens of volcanoes in the US and around the world where lahar activity is common. The project aims to train several graduate and undergraduate students from the US and result in scientific publication. Important capacity building in Guatemala will result from the training of Guatemalan scientists and technology transfer to observatory staff. This project will improve our understanding of the seismo-acoustic source mechanisms associated with lahars, and to develop methods that can be used to track such sources and other rapid gravity-driven mass movements. Through multi-parametric observations this study will contribute to our fundamental understanding of how lahars are triggered during precipitation events and where material is incorporated along the lahar flow path. Infra-acoustic arrays and broadband seismic sensors will be deployed at Fuego Volcano (Guatemala) with the intent to remotely monitor the most frequent channels that carry lahars during the rainy season. Signal processing techniques using data from an integrated network of arrays will be used to track and quantify flow energetics. Fuego provides an ideal field site where seismo-acoustic data will be combined with contemporaneous rainfall and geomorphologic (terrain and channel slope) observations. Computer vision techniques will be used to quantify timing, mass flow, and velocities of lahars at various positions along channels. This work merges geomorphology and geophysical approaches to study hazardous lahar phenomena. Broader impacts include development of applied technology for hazard mitigation and training of both US-based and Guatemala-based students and professionals. This award is cofunded by the PredicMon of and Resilience against Extreme Events (PREEVENTS) program.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.

火山泥流产生的次声（低频声能）可以在数公里外被探测到。 因此，可以通过随时间跟踪这些危险泥浆流的流动位置和能量来远程表征这些危险泥浆流。 这项工作旨在开发次声分析工具，以确定火山泥流的起始位置，它们移动的距离和速度，并估计它们的质量流量。为了实现这些目标，该项目将在Fuego火山（危地马拉）部署和维护地震和次声仪器，那里的火山泥流在雨季（4月至9月）很常见。 将在拉哈尔路径的沿着位置安装雨量计和延时摄像机，以了解拉哈尔是如何形成的，并通过直接观察验证流动特性。富埃戈火山是这项研究的理想候选者，因为它经常有火山泥流，相对容易进入，而且所了解的信息将适用于减轻风险。 在富埃戈学到的教训可能会应用到美国和世界各地的几十个火山，那里的拉哈尔活动是常见的。 该项目旨在培训来自美国的几名研究生和本科生，并发表科学论文。培训危地马拉科学家和向观测站工作人员转让技术将有助于危地马拉的重要能力建设。该项目将提高我们对与火山泥流相关的地震-声学震源机制的理解，并开发可用于跟踪此类震源和其他快速重力驱动的物质运动的方法。 通过多参数观测，这项研究将有助于我们从根本上了解如何触发火山泥流在降水过程中，并在沿着的拉哈尔流动路径的材料被纳入。声波阵列和宽带地震传感器将被部署在Fuego火山（危地马拉），目的是远程监测最频繁的渠道，在雨季携带火山泥流。 信号处理技术使用的数据从一个集成的网络阵列将被用来跟踪和量化流能量。 Fuego提供了一个理想的现场，地震声学数据将与同期降雨和地貌（地形和河道坡度）观测相结合。 计算机视觉技术将被用来量化时间，质量流量，并在沿着通道的不同位置的火山泥流的速度。 这项工作融合了地貌学和地球物理学的方法来研究危险的拉哈尔现象。 更广泛的影响包括开发减轻灾害的应用技术以及培训美国和危地马拉的学生和专业人员。该奖项由极端事件预测和复原力（PREEVENTS）计划共同资助。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。