Opening and reestablishment of Kilauea's lower east rift zone magma plumbing system during the 2018 eruption

该项目的重点是对夏威夷基拉韦厄火山地下岩浆流动的计算机模拟。在基拉韦厄火山长达4个月的2018年喷发期间，岩浆在地面下流动，距离基拉韦厄火山山顶约15英里，然后喷发到地面上。一旦喷发，岩浆形成的熔岩流覆盖了大约875英亩的土地，摧毁了大约700所房屋，造成了近10亿美元的损失。火山通常覆盖数千平方英里的区域，但岩浆突破地表的实际位置很难预测，并取决于地表下数千英尺处的岩浆流动。可以通过卫星和地球物理观测探测到地下岩浆的迁移，但火山活动的潜在预测和喷发灾害的评估取决于对地下岩浆流动和围岩变形的预测计算机模拟，特别是岩浆为向地表推进而破坏岩石的能力。该项目将在一个案例研究中利用2018年基拉韦厄火山喷发的异常多样和广泛的一组观测数据，目的是促进喷发前和喷发期间计算机建模和预测的最新水平。该项目将通过提高社会抵御自然灾害的能力，造福于国家健康、繁荣和福利。该项目的一个重要组成部分是在休斯顿独立学区内对高中教师进行教育，休斯顿独立学区是得克萨斯州最大的学区，服务于高度多样化的城市学生群体，约有80%的经济困难学生。除了在科学和工业研究中的重要性外，作为现代制造过程的一部分，计算建模已经成为一项宝贵的技能，其目标是促进高中水平的计算建模教学。拟议的项目的目标是增进对火山系统岩浆和构造成分之间相互作用的理解。它的重点是对2018年夏威夷基拉韦厄火山喷发期间的岩浆运输进行基于物理的建模。有人提出，基拉韦厄火山南侧的突然向海运动，就像2018年6.9级地震期间那样，可以通过侵入的岩浆迁移来促进。在2018年喷发之前的几年里，基拉韦厄火山探测到了岩浆压力的积累，最终导致岩浆沿着基拉韦厄火山东部裂谷带侵入15英里，然后喷发。该项目的一个关键目标是量化基拉韦厄东部裂谷带内岩浆压力的时空演变，以便对可能导致基拉韦厄南侧在6.9级地震期间突然位移的应力条件提供约束。拟议的方法包括对2018年喷发前和喷发期间岩浆运移的数值模拟，与岩浆-构造系统的弹性变形建模相结合，使用广泛的观测(GPS、InSAR、倾斜、重力、地震、喷发速率、岩浆化学)作为约束。火山系统预报能力的提高取决于可靠预报观测数据的基于物理的模型。拟议项目的智力价值在于，通过利用有史以来监测最好的火山喷发之一，促进了基于物理学的计算机模拟的进步。这一奖项反映了NSF的法定使命，并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，被认为值得支持。

The project is focused on computer modeling of magma flow in the subsurface beneath Kilauea volcano, Hawaii. During Kilauea's 4-months long 2018 eruption magma flowed beneath the ground surface over a distance of approximately 15 miles from Kilauea's summit before erupting onto the surface. Once erupted, the magma formed lava flows that covered approximately 875 acres of land, destroyed approximately 700 houses, and resulted in close to 1 billion dollars of damage. Volcanoes typically encompass areas of thousands of square miles, but the actual location where magma breaches the surface is difficult to predict and contingent upon the flow of magma at thousands of feet beneath the surface. Subsurface magma migration can be detected by satellite and geophysical observations, but potential forecasting of volcanic activity and assessment of eruption hazards are contingent upon predictive computer modeling of subsurface magma flow and deformation of the surrounding rock, in particular the magma's ability to break rock in order to advance toward the surface. This project will leverage the exceptionally diverse and extensive set of observational data from the 2018 eruption of Kilauea in a case study with the goal of advancing the state of the art in computer modeling and forecasting prior to and during an eruption. The project will benefit national health, prosperity and welfare by advancing societal resilience against natural disasters. A substantial component of the project involves the education of high-school teachers within the Houston Independent School District, the largest school district in Texas and serving a highly diverse urban student population with approximately 80% economically disadvantaged students. Beyond it importance in scientific and industrial research, computational modeling has become a valuable skill as part of the modern manufacturing process and the goal is to promote the teaching of computational modeling at the high-school level.The objective of the proposed project is to advance understanding about the interaction between magmatic and tectonic components of volcanic systems. It is focused on physics-­based modeling of magma transport during the 2018 eruption of Kilauea volcano, Hawaii. It has been suggested that abrupt seaward movement of Kilauea’s south flank, as during the 2018 M6.9 earthquake, can be facilitated by intrusive magma migration. Buildup of magma pressure at Kilauea was detected for several years prior to the 2018 eruption, eventually causing magma to intrude for 15 miles down Kilauea’s east rift zone before erupting. A key objective of the project is to quantify the spatiotemporal evolution of magma pressure within Kilauea’s east rift zone in order to provide constraints on stress conditions that may have led to the abrupt displacement of Kilauea’s south flank during the M6.9 earthquake. The proposed approach includes numerical simulation of magma transport prior to and during the 2018 eruption, integrated with elastic deformation modeling of the magmatic-­tectonic system, using a wide range of observations (GPS, InSAR, tilt, gravity, earthquakes, eruption rate, magma chemistry) as constraints. Advancement of forecasting capabilities in volcanic systems is contingent upon physics­-based models to reliably predict observational data. The intellectual merit of the proposed project lies in the advancement of physics-based computer modeling through leveraging one of the best­-monitored volcanic eruptions of all time.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.