Computationally efficient surrogate-based optimization of coastal storm waves heights and run-ups

TL;DR

This paper introduces a novel surrogate-based optimization method to efficiently estimate maximum storm wave heights and run-up, significantly reducing computational effort for coastal risk assessment.

Contribution

The paper presents the first surrogate-based optimization approach for modeling storm waves, enabling efficient identification of extreme wave conditions with minimal simulations.

Findings

Successfully identified conditions for largest storm waves using few simulations

Demonstrated efficiency of the surrogate-based method in idealized settings

Paves the way for advanced coastal risk assessments

Abstract

Storm surges cause coastal inundations due to the setup of the water surface resulting from atmospheric pressure, surface winds and breaking waves. The latter is particularly difficult to be accounted for. For instance, it was observed that during Typhoon Haiyan (2013, Philippines), a stretch of coral reef near the coast, which was expected to protect the coastal communities, actually amplified the waves. The propagation and breaking process of such large nearshore waves can be successfully captured by a phase-resolving wave model. Building defences requires estimating not only the maximum storm surge height, but also maxima of breaking wave height and run-up on land, under consideration of a variety of storm characteristics. However, the computational complexity of the simulator makes optimization tasks impractical. To find the maximum breaking wave (bore) height and the maximum run-up, we employ optim-MICE, a new surrogate-based optimization scheme based on Gaussian Process emulation and information theory. In two idealised settings, we efficiently identify the conditions that create the largest storm waves at the coast using a minimal number of simulations. This is the first surrogate-based optimization of storm waves. It opens the door to previously inconceivable coastal risk assessments.