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.
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
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 produced by DNR have been created from GeoClaw simulations.
- Tsunami Simulations
produced for the Tsunami Roadshow of 2018 and other public presentations.
- Modeling for Ocosta Elementary School (2013):
- Modeling for Long Beach berm (2013):
- Modeling for Long Beach berm (2018):
- Modeling for inundation maps on Olympic Peninsula coast (2014):
- Modeling for inundation maps on Strait of Juan de Fuca:
- Modeling for Port Angeles and Port Townsend:
- Modeling for Snohomish County (2018):
- Modeling for Northern Whatcom County (2019):
- (Except Point Roberts due to lack of DEMs, in progress in 2021)
- Modeling for Bainbridge Island (2018):
- Modeling for Island and Skagit Counties (2019):
- Issues Encountered with ASCE Compatibility Criteria (2019):
- Modeling for Aberdeen School District (2020):
- Modeling of Northwestern Coast of Washington (2020):
- Modeling of the Strait of Juan de Fuca (2021):
- Modeling of maritime hazards around the Port of Bellingham (2021):
- Modeling of Point Roberts (2021):
- Modeling for Shoalwater Bay Tribe (2020):
- 2009 Workshop:
- 2015 Workshop on Currents:
Projects on Probabilistic Tsunami Hazard Assessment (PTHA)
- PTHA study of Crescent City (for Baker/AECOM, funded by FEMA IX)
- PTHA methodology for source filtering (funded by FEMA Region IX)
- More recent work on source filtering and clustering
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.
- Observations and Modelling of Tsunami Currents at the Port of Tauranga,
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
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
Flow around buildings
- Wave tank model of Seaside, OR
- NTHMP Currents workshop benchmark problem 4:
results, in particular
- 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.
- GeoClaw simulation of Aberdeen with buildings
Proof of concept with 1-meter grid and initial column of water
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.
Early Warning Offshore Cascadia Project webpage
for more details.
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.
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
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
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
Zone Observatory Workshop, Boise, 2016.
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.)
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
and by a
CICOES Fellowship for collaboration
with the NOAA Center for Tsunami
Comparison of Machine Learning Approaches for Tsunami Forecasting from Sparse
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
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
- Finite volume methods for Tsunamis genereated by submarine landslides,
by Jihwan Kim, PhD thesis, 2014.
- Uncertainty Quantification Problems in Tsunami Modeling and Reduced
Order Models for Hyperbolic Partial Differential Equations,
by Donsub Rim, PhD thesis, 2017.
- Adjoint-Guided Adaptive Mesh Refinement for Hyperbolic Systems of
Equations, by Brisa Davis, PhD thesis, 2018.
- 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.
Modeled tsunami in Lake Washington from hypothetical ruptures on the
by Kathryn Richwine, UW Master's Capstone Report, 2020.