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: 1914491
• 负责人: Jeffrey Johnson
• 金额: $ 29.25万
• 依托单位: Boise State 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=1914491&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.

火山泥流或火山泥流会产生次声（低频声能），可以在数公里之外检测到。 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来定位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，该项目将在富埃戈火山（危地马拉）部署和维护地震和次声仪器，该火山在雨季（四月至九月）期间火山泥流很常见。 雨量计和延时摄影机将安装在火山泥流路径沿线的位置，以了解火山泥流如何引发并通过直接观察验证流动特征。富埃戈火山是这项研究的理想候选者，因为它频繁发生火山灰，相对容易进入，而且所学到的信息将适用于减轻风险。 富埃戈火山的经验教训可能会应用于美国和世界各地火山泥流活动频繁的数十座火山。 该项目旨在培训几名来自美国的研究生和本科生并发表科学论文。危地马拉重要的能力建设将通过对危地马拉科学家的培训和向天文台工作人员的技术转让来实现。该项目将增进我们对与火山泥流相关的地震声源机制的理解，并开发可用于跟踪此类源和其他快速重力驱动的质量运动的方法。 通过多参数观测，这项研究将有助于我们基本了解降水事件期间如何触发火山灰以及物质沿着火山灰流动路径的位置。 次声阵列和宽带地震传感器将部署在富埃戈火山（危地马拉），目的是远程监测雨季期间携带火山泥流最频繁的通道。 使用来自集成阵列网络的数据的信号处理技术将用于跟踪和量化流动能量。 富埃戈提供了一个理想的现场地点，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。 计算机视觉技术将用于量化沿通道不同位置的火山泥流的时间、质量流量和速度。 这项工作融合了地貌学和地球物理方法来研究危险的火山泥流现象。 更广泛的影响包括开发减灾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 PredicMon of and Resilience against Extreme Events (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智力优点和更广泛的影响审查标准进行评估，被认为值得支持。

项目成果

UAV-Based Quantification of Dynamic Lahar Channel Morphology at Volcán de Fuego, Guatemala

基于无人机的危地马拉火地火山动态泥浆通道形态量化

• DOI: 10.3390/rs15153713
• 发表时间: 2023
• 期刊: Remote Sensing
• 影响因子: 5
• 作者: Mock, Jerry C.;Johnson, Jeffrey B.;Pineda, Armando;Bejar, Gustavo;Roca, Amilcar
• 通讯作者: Roca, Amilcar

Snow Avalanche Detection and Source Constraints Made Using a Networked Array of Infrasound Sensors

• DOI: 10.1029/2020jf005741
• 发表时间: 2021-03-01
• 期刊: JOURNAL OF GEOPHYSICAL RESEARCH-EARTH SURFACE
• 影响因子: 3.9
• 作者: Johnson, J. B.;Anderson, J. F.;Watson, L. M.
• 通讯作者: Watson, L. M.