EAR-PF: Closing the gap between analogue studies and numerical lava flow models using insights from the 2018 Kilauea eruption

Elisabeth Gallant博士获得了美国国家科学基金会EAR博士后奖学金，与英国利物浦大学的Matt Patrick博士、Hannah Dietterich博士和Janine Kavanagh博士一起在夏威夷火山观测站、美国地质调查局阿拉斯加火山观测站开展研究和教育活动。该项目旨在通过使用2018年基拉韦厄火山喷发期间收集的数据和新的模拟建模技术来推进数值熔岩流模型，以更好地了解对熔岩流就位的控制。熔岩流，虽然通常不像其他火山灾害那样致命，但可能具有极大的破坏性，因为它们会使人口流离失所，破坏财产，破坏重要的基础设施。2018年，夏威夷基拉韦厄火山下东部裂谷区（LERZ）爆发，覆盖了三分之二曼哈顿大小的居民区，在四个月的时间里摧毁了716座建筑，耗资8亿美元进行恢复。帮助减轻熔岩流负面影响的一种方法是预测未来喷发的潜在路径，以帮助指导疏散计划和土地使用决策。计算建模已成为预测熔岩流灾害影响的常用方法。在这次合作中开发的计算机模型将考虑到我们所知道的对确定淹没模式至关重要的因素，特别是随着时间的推移，在喷口喷发的熔岩数量的变化（渗出率）如何决定水流进一步向下发生的事情（例如，熔岩流通过沟渠化或向上流动形成新的淹没路径的能力）。由于广泛的监测和数据收集，2018年的LERZ火山喷发为我们提供了一个前所未有的机会，可以提高我们对渗出速率、水流通道化和爆发之间关系的认识。利物浦大学开发的模拟建模新技术将量化这些关系，并帮助解决实验室模型与现实世界之间的比例问题。从这些模拟模型中获得的见解将用于改进计算熔岩流模型。该项目将通过使用多尺度模型来调查危险，从而提高对熔岩淹没的基本认识，解决由美国国家科学院建立的火山科学中的一个重大挑战。这项工作也与美国火山科学中心的目标一致。该项目的产出将用于帮助设计易于使用的教育材料，通过美国地质勘探局的火山灾害项目增加对危险的宣传，并补充美国地质勘探局现有的火山景观地理叙述。本研究将利用新的模拟建模技术和2018年LERZ火山喷发的高分辨率数据，推动熔岩流预测工具的发展，进一步量化动态喷发源参数（ESPs）对熔岩流就位模式的影响。2018年基拉韦厄火山的LERZ喷发为我们提供了一个前所未有的机会，可以提高我们对控制熔岩流就位过程的认识，并提高我们模拟流场演化的能力。具体来说，它将侧重于esp变化对渠道演变和爆发的影响，这在当前的计算预测领域中明显缺失。通道有助于控制熔岩的流向和到达的速度，这是评估洪水危害的重要因素。从问题的模拟、数值和现实尺度来探讨这一问题，为推进熔岩流淹没预测领域提供了坚实的基础。这项工作将结合美国地质勘探局在2018年LERZ火山喷发期间获得的强大数据集的见解，以及利物浦大学MagmaLab首创的新技术，该技术允许对模拟流动模型进行4D成像，以开发开放获取的数值熔岩流动模型。将开发教育材料，以增加美国地质勘探局火山灾害计划的灾害宣传材料。该奖项反映了美国国家科学基金会的法定使命，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。

Dr. Elisabeth Gallant has been granted an NSF EAR Postdoctoral Fellowship to carry out research and educational activities at the Hawaiian Volcano Observatory, USGS Alaska Volcano Observatory, alongside Dr Matt Patrick, Dr Hannah Dietterich, and Dr Janine Kavanagh at the University of Liverpool (UK). This project seeks to advance numerical lava flow models by using data collected during the 2018 eruption of Kilauea and novel analogue modeling techniques to better understand controls on lava flow emplacement. Lava flows, although generally less deadly than other volcanic hazards, can be extremely disruptive because they displace populations, destroy property, and damage vital infrastructure. The 2018 lower East Rift Zone (LERZ) eruption of Kilauea Volcano, Hawaii, covered a residential area two-thirds the size of Manhattan, destroyed 716 structures over a period of four months, and cost $800 million to recover from. One way to help mitigate negative impacts of lava flows is by forecasting the potential paths of future eruptions to help guide evacuation planning and land use decisions. Computational modeling has become the established method to forecast the impact of lava flow hazards. The computer models developed during this fellowship will take into account factors we know are critical for determining inundation patterns, specifically how changes in the amount of lava erupting at the vent over time (effusion rate) determines what happens further down in the flow (e.g., the ability of the lava flow to forge a new inundation path by channelizing or breaking out up-flow). The 2018 LERZ eruption provides an unprecedented opportunity to improve our knowledge of the relationships between effusion rate, flow channelization, and breakouts due to extensive monitoring and data collection. New techniques in analogue modeling, developed at the University of Liverpool, will quantify these relationships and help address problems of scaling between laboratory models and the real world. Insights from these analogue models will then be used to improve computational lava flow models. This project will advance the fundamental understanding of lava inundation through the use of multi-scale models to investigate hazards, addressing one of the grand challenges in volcano science established by the National Academy of Science. This work also aligns with the goals of the US Volcano Science Center. Outputs from this project will be used to help design accessible educational materials to increase hazard communication through the USGS Volcanic Hazards Program and would complement existing USGS Geonarratives for volcanic landscapes.This study will advance the development of lava flow forecasting tools by using new analogue modeling techniques and high-resolution data from the 2018 LERZ eruption to further quantify the impact of dynamic eruption source parameters (ESPs) on lava flow emplacement patterns. The 2018 LERZ eruption of Kilauea Volcano provides an unprecedented opportunity to improve our knowledge of the processes that govern lava flow emplacement and advance our ability to model flow field evolution. Specifically, it will focus on the impact that variations in ESPs have on channel evolution and breakouts, which is notably absent in the current computational forecasting landscape. Channels help control where the lava goes and how fast it arrives, which are important factors in assessing inundation hazards. Approaching this problem from the analogue, numerical, and real world scale of the problem provides a robust foundation for advancing the field of lava flow inundation forecasting. This work will combine insights from the robust suite of data acquired by the USGS during the 2018 LERZ eruption and new techniques pioneered by the MagmaLab at the University of Liverpool that allow for 4D imaging of analogue flow models to develop open-access numerical lava flow models. Educational materials will be developed to augment hazard communication materials at the USGS Volcano Hazards 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.