# Quantifying Uncertainties in Fault Slip Distribution during the T=ohoku Tsunami using Polynomial Chaos

arXiv: https://arxiv.org/abs/1607.07414 · HTML: https://mlsanity.com/paper/1607.07414/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 25 Jul 2016.

## Built on by (most cited first, 2 of 2)

- [Construction of a Surrogate Model: Multivariate Time Series Prediction with a Hybrid Model](https://mlsanity.com/paper/2212.07918/) (2022)
- [Nonintrusive Uncertainty Quantification for automotive crash problems with VPS/Pamcrash](https://mlsanity.com/paper/2102.07673/) (2021)

## Abstract (arXiv)

An efficient method for inferring Manning's n coefficients using water surface elevation data was presented in Sraj et al. (2014) focusing on a test case based on data collected during the T=ohoku earthquake and tsunami. Polynomial chaos expansions were used to build an inexpensive surrogate for the numerical model Geoclaw, which were then used to perform a sensitivity analysis in addition to the inversion. In this paper, a new analysis is performed with the goal of inferring the fault slip distribution of the T=ohoku earthquake using a similar problem setup. The same approach to constructing the PC surrogate did not lead to a converging expansion, however an alternative approach based on Basis-Pursuit DeNoising was found to be suitable. Our result shows that the fault slip distribution can be inferred using water surface elevation data whereas the inferred values minimizes the error between observations and the numerical model. The numerical approach and the resulting inversion are presented in this work.