NSF Award
2326785
This award is funded in whole or in part under the American Rescue Plan Act of 2021 (Public Law 117-2). Subduction zones, known for parallel chains of towering volcanoes and deep oceanic trenches, host Earth's most geologically complex and heavily populated regions. Subduction zones represent the continuous convergence of two tectonic plates, one of which subducts (“dives”) into the mantle while the other rides over the top of the subducting plate. Stress in this converging system continuously builds until it exceeds the frictional strength of the boundary separating the two plates. At this point, the pent-up stress is released in the form of an earthquake and warps the seafloor. This warping seafloor shifts the overlying ocean surface, a process known as tsunami genesis. Only subduction zones can generate mega-earthquakes, which can warp the seafloor over tremendously vast areas and trigger devastating tsunamis. Predicting tsunamis is a challenging problem because it requires an understanding of the inaccessible details of the stress release along the plate boundary and how it deforms the structure of the entire subduction zone. This research presents a new approach that brings the combined power of mathematics and statistics to bear on this problem. Mathematics describes the physical processes of earthquakes and tsunamis and the statistics account for what is known, or more importantly, what is unknown about the subduction zone system. Results of this research could provide the tools to evaluate risks for coastal locations that are prone to tsunamis. Numerical modeling is the key to this approach and demand for numerical modeling skills is increasing in parallel with expanding data collection initiatives and advances in computational capabilities. This project includes an educational component that will engage students from underrepresented groups in science, technology, engineering, and mathematics in formalized training in numerical modeling. <br/><br/>This research will develop numerical tools with a probabilistic perspective to investigate the coupling of seafloor deformation from megathrust earthquakes and tsunamis. These tools will address the challenging problem of embedding sophisticated finite element models of earthquake deformation into automated Monte Carlo sampling strategies. The deformation models will have geodetically-informed slip distributions over curved fault surfaces embedded in domains having the geometric irregularities of topography and bathymetry. Domains will simultaneously account for seismic tomography and reflection models, submarine-based seafloor observations, and tsunami observations. These models will propagate uncertainties from geodetic data into probability density functions for tsunami run-up behavior along coastal locations. This research will, for the first time, quantify how the larger uncertainties for near-trench slip propagate into tsunami predictions. Finite element models are necessary to simulate the complex mechanical behavior of subduction zones and Monte Carlo sampling will reveal how uncertainties in the data and model configurations propagate into deformation and tsunami predictions. These objectives will be achieved using the well-documented 2004 Sumatra megathrust earthquake and tsunami as a case study. A short course on finite element models of earthquake deformation will be developed and delivered. The curriculum will comprise Protocol-based Modeling, Forward Modeling, Inverse Modeling, and discussions of Target Applications. Graduate students from U.S. institutions will be recruited by the Graduate Women In Science chapter and the Women in Science and Engineering program at the South Dakota School of Mines to promote participation of underrepresented students.<br/><br/>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.
