Physics-Based Volcano Geodesy with Application to Effusive Eruptions at Mount St Helens

基于物理的火山大地测量及其在圣海伦斯火山喷发中的应用

• 批准号: 1358607
• 负责人: Paul Segall
• 金额: $ 39.42万
• 依托单位: Stanford University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-07-01 至 2020-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1358607&HistoricalAwards=false
• 关键词: Physics; Based; Volcano; Geodesy; Application

Non-technical summaryPrior to volcanic eruptions magma accumulates in shallow reservoirs in Earth?s crust. As a result, pressure increases in these magma chambers, which deforms or ?inflates? the Earth?s surface; in contrast, during eruptions, magma leaves these reservoirs, decreasing pressure and causing the Earth?s surface to ?deflate?. Better understanding of these signals could help improve societal responses to volcanic eruptions, such as possible evacuations and changes to airline routes near volcanoes like following the 2010 Icelandic eruption. This project is developing new physics-based models of volcano deformation, which can be coupled with deformation measurements from the EarthScope Plate Boundary to improve forecasts of the duration of an eruption and the volume of material that may be erupted. The project is investigating a data assimilation approach in which available data are used to develop probabilistic estimates for parameters that describe the state of the magmatic system. These are then used to initialize an ensemble of forward models that predict future behavior, including eruption duration and total erupted volume. Given improved forward models, this approach has the advantage of being consistent with both available data and realistic physics-based eruption models. Physics-based volcano eruption forecasts are similar in concept to numerical weather forecasts that assimilate satellite and other data into sophisticated weather models. Technical summaryThis project employs Markov Chain Monte Carlo (MCMC) inversion of continuous GPS positions, magma efflux, and other data using a physics-based forward model of an effusive eruption. Including a physically consistent eruption model allows the estimation procedure to constrain parameters of interest that are not resolved by traditional approaches, including the volume of the crustal magma chamber and the initial water content of the magma. These parameters influence the size and potential explosive potential of eruptions. Ongoing work is increasing the realism of the forward model by including: 1) equilibrium crystallization of the magma as it ascends and pressure decreases; 2) explicit consideration of the rheological transition from distributed viscous flow to solid plug flow with slip on bounding faults, based on a Bingham fluid model and 3) explicit consideration of gas loss (both H2O and CO2) through both lateral and vertical diffusion. Other goals include better models of the eruption onset and cessation. The method is being applied to the 2004-2008 dome forming eruption of Mount St. Helens (MSH), including GPS data from the Plate Boundary Observatory (PBO) and could be applied to other volcanoes, including Augustine in Alaska, Unzen in Japan, and the Soufriere Hills on Montserrat.

火山喷发的非技术摘要岩浆积聚在地壳的浅水库中。 结果，这些岩浆腔的压力增加，哪些变形或膨胀？地球表面；相反，在喷发过程中，岩浆留下了这些储层，降低压力并导致地面表面降低？ 更好地了解这些信号可以帮助改善对火山喷发的社会反应，例如撤离和对火山附近航空公司的变化，例如遵循2010年冰岛爆发。该项目正在开发新的基于物理的火山变形模型，该模型可以与来自Earthscope板边界的变形测量​​相结合，以改善喷发持续时间的预测和可能爆发的材料体积。 该项目正在研究一种数据同化方法，其中使用可用数据来开发描述岩浆系统状态的参数的概率估计。 然后，这些用于初始化一个预测未来行为的正向模型的集合，包括喷发持续时间和总量爆发。 鉴于改进的远期模型，这种方法具有与可用数据和基于物理学的喷发模型一致的优点。 基于物理学的火山喷发预测在概念上与数值天气预测相似，这些天气预测将卫星和其他数据吸收到复杂的天气模型中。技术摘要项目使用Markov Chain Monte Carlo（MCMC）反转连续的GPS位置，岩浆外排和其他基于物理学的前向爆发模型。 包括物理上一致的喷发模型允许估计程序约束感兴趣的参数，这些参数无法通过传统方法解决，包括地壳岩浆腔室的体积和岩浆的初始水含量。 这些参数会影响喷发的大小和潜在爆炸潜力。持续的工作是通过包括：1）岩浆上升和压力降低的岩浆的平衡结晶来增加正向模型的现实主义； 2）基于宾厄姆流体模型和3）通过横向扩散和垂直扩散的明确考虑对气体损失（H2O和CO2）的明确考虑。 其他目标包括更好的喷发开始和停止模型。该方法应用于2004-2008的圆顶形成圣海伦斯山（MSH），包括来自板边界天文台（PBO）的GPS数据，可以应用于其他火山，包括阿拉斯加的奥古斯丁，日本Unezen，以及蒙特塞拉特的Soufriere Hills。