UW Tsunami Modeling Group Modeling Projects and Reports

This page contains a summary of some past, present, and potential projects on tsunami modeling and hazard assessment by the UW Tsunami Modeling Group. Most of this work is done using the GeoClaw software developed by this group and our collaborators, which is distributed as part of the open source Clawpack software.

See also:

The tsunami modeling collection of the UW ResearchWorks repository lists archived versions of many recent reports, and other papers and theses from UW tsunami researchers.
The GeoClaw page contains links to some other applications of GeoClaw to tsunamis, storm surge, and overland flooding.
The M9 Project, whose goal is to reduce catastrophic potential effects of a Cascadia megathrust earthquake on social, built, and natural environments.
The Cascadia Coastlines and People Hazards Research Hub: September 2021 press releases from UW and OSU.

Projects for Washington State

The projects listed below were performed for the Washington State Emergency Management Division (EMD), Division of Natural Resources (DNR), and/or other local jurisdictions.

Some of the recent Tsunami Hazard Maps and Maritime Guidance brochures produced by DNR and EMD have been created from GeoClaw simulations.
Links to some recent work can also be found on the WA EMD Tsunami Resources page.
Tsunami Simulations produced for the Tsunami Roadshow of 2018 and other public presentations.
Modeling for Ocosta Elementary School (2013):
- Report and various links
- Simulations and data
Modeling for Long Beach berm (2013):
- Report
- Simulations and data
Modeling for Long Beach berm (2018):
- Report
- Simulations and data
Modeling for inundation maps on Olympic Peninsula coast (2014):
- Simulations
- Superceded by 2020 modeling
Modeling for inundation maps on Strait of Juan de Fuca:
- Report
- Simulations
- Superceded by 2021 modeling
Modeling for Port Angeles and Port Townsend:
- Maps published by DNR based on our modeling.
Modeling for Snohomish County (2018):
- Updated in 2020, Results and draft report
Modeling for Northern Whatcom County (2019):
- Report
- (Except Point Roberts due to lack of DEMs, in progress in 2021)
Modeling for Bainbridge Island (2018):
- Report, including comparisons with the MOST model, in colaboration with the NOAA Center for Tsunami Research
Modeling for Island and Skagit Counties (2019):
- Report and simulations
Issues Encountered with ASCE Compatibility Criteria (2019):
- Report
Modeling for Aberdeen School District (2020):
- Report
Modeling of Northwestern Coast of Washington (2020):
- Report and simulations
Modeling of the Strait of Juan de Fuca (2021):
- Report and simulations
Modeling of maritime hazards around the Port of Bellingham (2021):
- Report and other links
Modeling of Point Roberts (2021):
- In progress
Modeling for Shoalwater Bay Tribe (2020):
- To support development of a vertical evacuation structure in Tokeland
- Report and other links
Modeling of maritime hazards around Westport Marina, Port of Grays Harbor (2022):
- Guidance

NTHMP Benchmarking

2009 Workshop:
- Results and report
2015 Workshop on Currents:
- Results

Projects on Probabilistic Tsunami Hazard Assessment (PTHA)

PTHA study of Crescent City (for Baker/AECOM, funded by FEMA IX)
- Report
- Simulations and data
- The pattern method for incorporating tidal uncertainty into probabilistic tsunami hazard assessment (PTHA) by L. M. Adams, R. J. LeVeque and F. I. Gonzalez, Natural Hazards 76(2015), pp. 19-39.
PTHA methodology for source filtering (funded by FEMA Region IX)
- project website with simulations and data
- Project Final Report, March, 2017.
More recent work on source filtering and clustering
- A Source Clustering Approach for Efficient Inundation Modeling and Regional Scale PTHA, by A.L. Williamson, D. Rim, L.M. Adams, R.J. LeVeque, D. Melgar, and F.I. Gonzalez, Frontiers in Earth Science, 8 (2020) p. 442.

Comparisons of GeoClaw and observations for historical events

Comparison of earthquake source models for the 2011 Tohoku event using tsunami simulations and near field observations, by Breanyn T MacInnes, Aditya Riadi Gusman, Randall J LeVeque, Yuichiro Tanioka. Bulletin of the Seismological Society of America, 103(2013), pp. 1256-1274.
Observations and Modelling of Tsunami Currents at the Port of Tauranga, New Zealand, by J. C. Borerro, R. J. LeVeque, S. D. Greer, S. O'Neill, and B. N. Davis, Australasian Coasts & Ports Conference 2015: 22nd Australasian Coastal and Ocean Engineering Conference and the 15th Australasian Port and Harbour Conference.
GeoClaw Model Tsunamis Compared to Tide Gauge Results Project funded by NOAA/PMEL/JISAO to compare results at numerous DART and tide gauges with observations from four past events.

Flow around buildings

Wave tank model of Seaside, OR [Video]
- NTHMP Currents workshop benchmark problem 4: GeoClaw results, in particular this animation
- 3d simulation using OpenFOAM
- A comparison of a two-dimensional depth averaged flow model and a three-dimensional RANS model for predicting tsunami inundation, by X. Qin, M. R. Motley, R. J. LeVeque, F. I. Gonzalez, and K. Mueller, Nat. Hazards Earth Syst. Sci., 18 (2018) , pp. 2489-2506, DOI 10.5194/nhess-18-2489-2018
GeoClaw simulation of Aberdeen with buildings
Proof of concept with 1-meter grid and initial column of water
- Aberdeen.kmz Open in Google Earth [Screen shot]

Earthquake/Tsunami Early Warning

We are developing a coupled seismic/tsunami modeling code with some funding from the Moore Foundation grant to explore the potential benefits of an off-shore cabled network for early warning. See the Early Warning Offshore Cascadia Project webpage for more details.

Earthquake and Tsunami Early Warning on the Cascadia Subduction Zone: A Feasibility Study for an Offshore Geophysical Monitoring Network. , by D.W. Schmidt, D.W. Wilcock, R. LeVeque, F. Gonzalez, G. Gram, D. Manalang, M. Harrington, E. Roland, and P. Bodin, Project White Paper, University of Washington, 2019, 81 pp.,
Developing a Warning System for Inbound Tsunamis from the Cascadia Subduction Zone, by R.J. LeVeque, P. Boden, G. Cram, B.W. Crowell, F.I. Gonzalez, M. Harrington, D. Manalang, D. Melgar, D.A. Schmidt, J.E. Vidale, C.J. Vogl, and W.S.D. Wilcock, Oceans 2018 conference.
Designing an offshore geophysical network in the Pacific Northwest for earthquake and tsunami early warning and hazard research, by W. S. D. Wilcock, D. A. Schmidt, J. E. Vidale, et al. Oceans 2016 Conference.
Sustained Offshore Geophysical Monitoring in Cascadia, by William S. D. Wilcock, David A. Schmidt, John E. Vidale, Michael J. Harrington, Paul Bodin, Geoffrey S. Cram, John R. Delaney, Frank I. Gonzalez, Heidi Houston, Deborah S. Kelley, Randall J. LeVeque, Dana A. Manalang, Chuck McGuire, Emily C. Roland, Mark W. Stoermer, James W. Tilley, and Christopher J. Vogl, from the The Subduction Zone Observatory Workshop, Boise, 2016.
Animation of seismic waves and resulting sea floor deformation and sea surface disturbance from coupled model, comparing to Okada solution often used as the tsunami source (the static displacement of an elastic half space after the seismic waves have propagated away). Note that the gravity wave (tsunami) propagates over a much longer time scale than the seismic waves. (Work in progress with Chris Vogl.)

We are also interested in studying the potential for better real-time warning at points on the Strait and in Puget Sound, where there are several hours between the earthquake and the arrival of the tsunami. In particular, we believe that ocean bottom pressure sensors near the entrance to the Strait might be extremely effective in determining the in-coming tsunami.

Tsunami Forecasting and Machine Learning

Recent work on these topics has been funded in part by Tohoku University in Sendai, Japan for collaboration with researchers at IRIDeS, and by a CICOES Fellowship for collaboration with the NOAA Center for Tsunami Research.

Comparison of Machine Learning Approaches for Tsunami Forecasting from Sparse Observations, by C.M. Liu, D. Rim, R. Baraldi, and R.J. LeVeque, to appear in Pure and Applied Geophysics, 2021.
Sequential Bayesian Update to Detect the Most Likely Tsunami Scenario Using Observational Wave Sequences, by R. Nomura, S. Fujita, J. M. Galbreath, Y. Otake, S. Moriguchi, S. Koshimura, R. J. LeVeque, and K. Terada J. Geophys. Res. Oceans 2022. DOI 10.1029/2021JC018324
Tsunami Early Warning from Global Navigation Satellite System Data using Convolutional Neural Networks, by D. Rim, R. Baraldi, C.M. Liu, R.J. LeVeque, and K. Terada Geophysical Research Letters (2022), DOI 10.1029/2022GL099511

Student theses

Finite volume methods for Tsunamis genereated by submarine landslides, by Jihwan Kim, PhD thesis, 2014. hdl.handle.net/1773/25374
Uncertainty Quantification Problems in Tsunami Modeling and Reduced Order Models for Hyperbolic Partial Differential Equations, by Donsub Rim, PhD thesis, 2017. hdl.handle.net/1773/39933
Adjoint-Guided Adaptive Mesh Refinement for Hyperbolic Systems of Equations, by Brisa Davis, PhD thesis, 2018. hdl.handle.net/1773/42950
Tsunami Inundation Modeling of Sequim Bay Area, Washington, USA from a Mw 9.0 Cascadia Subduction Zone Earthquake, by Chun-Juei Lee, UW Master's Capstone Report, 2017. hdl.handle.net/1773/44994
Modeled tsunami in Lake Washington from hypothetical ruptures on the Seattle Fault, by Kathryn Richwine, UW Master's Capstone Report, 2020. hdl.handle.net/1773/45565