Articles | Volume 12, issue 6
https://doi.org/10.5194/nhess-12-2003-2012
© Author(s) 2012. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/nhess-12-2003-2012
© Author(s) 2012. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
25 Jun 2012
Research article |
| 25 Jun 2012
Statistical emulation of a tsunami model for sensitivity analysis and uncertainty quantification
A. Sarri
Institute for Risk and Disaster Reduction, University College London, UK
S. Guillas
Institute for Risk and Disaster Reduction, University College London, UK
Department of Statistical Science, University College London, UK
F. Dias
School of Mathematical Sciences, University College Dublin, Ireland
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Cited
40 citations as recorded by crossref.
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- Uncertainty quantification and inference of Manning’s friction coefficients using DART buoy data during the Tōhoku tsunami I. Sraj et al. https://doi.org/10.1016/j.ocemod.2014.09.001
- Uncertainties in the 2004 Sumatra–Andaman source through nonlinear stochastic inversion of tsunami waves D. Gopinathan et al. https://doi.org/10.1098/rspa.2017.0353
- Rapid tsunami force prediction by mode-decomposition-based surrogate modeling K. Tozato et al. https://doi.org/10.5194/nhess-22-1267-2022
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- Discriminating the occurrence of inundation in tsunami early warning with one-dimensional convolutional neural networks J. Núñez et al. https://doi.org/10.1038/s41598-022-13788-9
- A review of approaches for submarine landslide-tsunami hazard identification and assessment J. Roger et al. https://doi.org/10.1016/j.marpetgeo.2024.106729
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- Multi-level emulation of a volcanic ash transport and dispersion model to quantify sensitivity to uncertain parameters N. Harvey et al. https://doi.org/10.5194/nhess-18-41-2018
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- Generating Random Earthquake Events for Probabilistic Tsunami Hazard Assessment R. LeVeque et al. https://doi.org/10.1007/s00024-016-1357-1
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- Quantifying uncertainties in fault slip distribution during the Tōhoku tsunami using polynomial chaos I. Sraj et al. https://doi.org/10.1007/s10236-017-1105-9
- APPLICATION OF GAUSSIAN PROCESS REGRESSION TO IMPROVE THE EFFICIENCY OF TSUNAMI PREDICTIONS IN PROBABILISTIC TSUNAMI HAZARD ANALYSIS T. KURITA et al. https://doi.org/10.2208/jscejj.25-17193
- Statistical analysis of three-dimensional run-up heights using Gaussian process emulator of particle method Y. Mizuno et al. https://doi.org/10.1007/s40571-021-00426-w
- Bayesian inference of earthquake parameters from buoy data using a polynomial chaos-based surrogate L. Giraldi et al. https://doi.org/10.1007/s10596-017-9646-z
- Machine Learning for Tsunami Waves Forecasting Using Regression Trees E. Cesario et al. https://doi.org/10.1016/j.bdr.2024.100452
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- Physics-based simulations of multiple natural hazards for risk-sensitive planning and decision making in expanding urban regions L. Jenkins et al. https://doi.org/10.1016/j.ijdrr.2022.103338
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- The hydrodynamics of landslide tsunamis: current analytical models and future research directions E. Renzi & P. Sammarco https://doi.org/10.1007/s10346-016-0680-z
- Efficient probabilistic prediction of tsunami inundation considering random tsunami sources and the failure probability of seawalls Y. Fukutani et al. https://doi.org/10.1007/s00477-023-02379-3
- Rheological considerations for the modelling of submarine sliding at Rockall Bank, NE Atlantic Ocean D. Salmanidou et al. https://doi.org/10.1063/1.5009552
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- Prediction of wind loading on masked angle members in lattice tower structures A. Hadane et al. https://doi.org/10.1016/j.euromechflu.2024.10.008
- Probabilistic Tsunami Hazard and Risk Analysis: A Review of Research Gaps J. Behrens et al. https://doi.org/10.3389/feart.2021.628772
- Bayesian calibration of the constants of thek–εturbulence model for a CFD model of street canyon flow S. Guillas et al. https://doi.org/10.1016/j.cma.2014.06.008
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