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Developing a Virtual Reality Video Game to Simulate Rip Currents

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Probabilistic quantification of tsunami current hazard using statistical emulation.

Devaraj Gopinathan¹, Mohammad Heidarzadeh², Serge Guillas¹

¹Department of Statistical Science, University College London, Gower Street, London WC1E 6BT, UK.

Proceedings. Mathematical, Physical, and Engineering Sciences

|February 14, 2022

Summary

Statistical emulation is a powerful tool for tsunami impact modeling, enabling millions of predictions to quantify high-risk, low-probability hazards. This leap in tsunami science provides detailed insights into tsunami velocities and heights.

Keywords:

Karachi port Makran subduction zone coastal engineering hazard assessment sediment amplification unstructured mesh

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Area of Science:

Earth Sciences
Computational Science
Oceanography

Background:

Tsunami impact modeling is computationally intensive, limiting the scope of hazard assessments.
Understanding local tsunami effects requires detailed simulations from source to impact.

Purpose of the Study:

To demonstrate statistical emulation as an efficient tool for end-to-end tsunami impact modeling.
To quantify high-risk, low-probability tsunami hazard thresholds.
To map probabilistic tsunami velocities and heights for specific coastal areas.

Main Methods:

Constructed an emulator using 300 training simulations from a validated tsunami code.
Generated 1 million predictions to overcome computational cost barriers.
Utilized detailed geological data (Slab2, fault segmentation) and sediment enhancements for seabed deformation modeling.
Employed a bespoke unstructured meshing algorithm for refined numerical modeling.

Main Results:

Achieved a record number of predictions (1 million) for a realistic tsunami code.
Successfully mapped probabilistic tsunami velocities and heights at approximately 200 locations near Karachi port.
Quantified hazard thresholds for high-risk, low-probability tsunami events originating from the Makran Subduction Zone (MSZ).
Discovered substantial local variations in tsunami currents and heights due to the synthesis of emulation and meticulous modeling.

Conclusions:

Statistical emulation is an essential and effective tool for comprehensive local tsunami impact assessment.
The study provides unprecedented insights into potential tsunami hazards for the Karachi port region.
Advanced numerical modeling techniques, including sediment enhancements, significantly improve the accuracy of tsunami impact predictions.