Laboratory data
Significance
Tsunamis are ocean waves triggered by large earthquakes that occur near or under the ocean, volcanic eruptions, submarine landslides, onshore landslides in which large volumes of debris fall into the water. Over the years, tsunami simulation models have been well validated against wave height and runup; nonetheless, comparisons with speed data are less common. The impact caused by the strong currents that typically accompany a tsunami is of key importance in ports, bays, and harbors. As model results are increasingly used to estimate damage to coastal infrastructure, understanding the accuracy and precision of speed predictions becomes of undeniable importance. In order to produce accurate and consistent maritime hazard products, the National Tsunami Hazard Mitigation Program (NTHMP) in its FY13-17 Strategic Plan included the requirement of the Mapping and Modeling Subcommittee (MMS) to evaluate NTHMP-benchmarked models for current predictions. Since then, several models have been probed both using laboratory experimental data and field observations. In particular, the model Tsunami-HySEA has undertaken this benchmarked approach together with a, pioneering in tsunami modelling, implementation in multi-GPU architectures. This has led to the development of a code which is about two orders of magnitude faster in comparison with the same model coded for a single CPU. This hardware/software combination is a game changer that has captured the attention of tsunami researchers and warning centers worldwide.
Tsunami-HySEA model has enabled low budget centers to compute with their own computational resources. In fact, up until now, there were no real-time computational approaches applied to TEWS; therefore, Tsunami-HySEA model represents a completely novel approach in this field. Nevertheless, the new numerical model implemented has to be validated and verified. On this account, researchers from the University of Malaga in Spain: Professor Jorge Macías, Professor Manuel Castro and Dr. Cipriano Escalante performed the five numerical benchmarks proposed in the “NTHMP/MMS Benchmarking Workshop: Tsunami currents”, using the novel Tsunami-HySEA model. Their work is currently published in the research journal, Coastal Engineering.
In their approach, the benchmarks considered were those proposed by the NTHMP. The team presented the most exhaustive numerical study with a NLSW model for the BP1 as different numerical schemes, boundary conditions, friction parameterization, and sensitivity to the friction coefficient were evaluated. Overall, the team presented the first implementation of dispersion in the Tsunami-HySEA model.
The authors reported that benchmark 1 appeared to be the most difficult one of all for non-linear shallow water (NLSW) models due to its high sensitivity to parameters and the very complex wake structure occurring behind the submerged island. Remarkably, for the rest of the benchmark problems, a good fit was obtained with measured data. The recently implemented dispersive version of the Tsunami-HySEA code have been fully benchmarked for propagation and inundation, first, and now for tsunami currents, representing a new operational tool for tsunami modeling and hazard assessment.
In summary, the study included three benchmark problems dealing with laboratory data, namely: BP1 (truncated submerged circular cone), BP4 (Seaside, Oregon, city building model), and BP5 (solitary wave over a complex shelf) when using the Tsunami-HySEA model to perform numerical benchmarks proposed in the “NTHMP/MMS Benchmarking Workshop: Tsunami currents”. In a statement to Advances in Engineering, Professor Jorge Macías mentioned that based on their validation exercise, the Tsunami-HySEA model performed well in all benchmark problems proposed, with the most difficult one being the first test.
Reference
Jorge Macías, Manuel J. Castro, Cipriano Escalante. Performance assessment of the Tsunami-HySEA model for NTHMP tsunami currents benchmarking: Laboratory data. Coastal Engineering: volume 158 (2020) 103667