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

Elisabeth Gallant博士已获得NSF博士后奖学金，在夏威夷火山天文台，美国地质勘探局阿拉斯加火山天文台开展研究和教育活动，与Matt帕特里克博士，Hannah Dietterich博士和Janine Kavanagh博士一起在利物浦大学（英国）。该项目旨在通过使用2018年基拉韦厄喷发期间收集的数据和新的模拟建模技术来推进熔岩流数值模型，以更好地了解对熔岩流就位的控制。熔岩流虽然通常没有其他火山灾害那么致命，但也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，并破坏重要的基础设施。2018年，夏威夷基拉韦厄火山的下东裂谷带（LERZ）喷发，覆盖了曼哈顿三分之二大小的住宅区，在四个月内摧毁了716座建筑物，并花费了8亿美元来恢复。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，以帮助指导疏散规划和土地使用决策。计算建模已成为预测熔岩流灾害影响的既定方法。在这次研究期间开发的计算机模型将考虑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量的变化（渗出率）如何决定流动中进一步发生的事情（例如，熔岩流的能力，以锻造一个新的淹没路径，通过渠道或打破上升流）。2018年的LERZ喷发提供了一个前所未有的机会，可以通过广泛的监测和数据收集来提高我们对渗出率，流动通道化和突破之间关系的认识。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和真实的世界之间的缩放问题。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害，促进对熔岩泛滥的基本理解，解决国家科学院确定的火山科学的重大挑战之一。这项工作也符合美国火山科学中心的目标。该项目的产出将用于帮助设计可访问的教育材料，以通过美国地质勘探局火山灾害计划增加灾害沟通，并将补充现有的美国地质勘探局火山景观地质资料。2018年LERZ喷发的分辨率数据，以进一步量化动态喷发源参数（ESP）对熔岩流就位模式的影响。2018年基拉韦厄基拉韦厄火山的LERZ喷发提供了一个前所未有的机会，可以提高我们对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，它将集中在ESP的变化对通道演变和突破的影响，这是在目前的计算预测景观明显缺乏。通道有助于控制熔岩的流向和到达速度，这是评估洪水危害的重要因素。从问题的模拟、数值和真实的世界尺度来处理这个问题，为推进熔岩流淹没预测领域提供了坚实的基础。这项工作将结合联合收割机的见解，从USGS在2018年LERZ喷发期间获得的强大数据集和利物浦大学MagmaLab开创的新技术中获得的见解，这些新技术允许模拟流模型的4D成像，以开发开放访问的数值熔岩流模型。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沟通材料。该奖项反映了NSF的法定使命，并已被认为是值得通过使用基金会的智力价值和更广泛的影响审查标准进行评估的支持。

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.