A survey on tidal analysis and forecasting methods for Tsunami detection

TL;DR

This survey reviews various tidal analysis and forecasting methods, emphasizing their importance for tsunami detection and highlighting classical and novel approaches, including harmonic analysis, filtering, neural networks, and wavelets.

Contribution

It provides a comprehensive, systematic review of both traditional and recent tidal analysis and forecasting techniques, comparing their effectiveness and applicability.

Findings

Harmonic analysis requires extensive data and parameters.

Machine learning methods like neural networks show promise in complex scenarios.

Wavelet transforms effectively handle non-stationary tidal signals.

Abstract

Accurate analysis and forecasting of tidal level are very important tasks for human activities in oceanic and coastal areas. They can be crucial in catastrophic situations like occurrences of Tsunamis in order to provide a rapid alerting to the human population involved and to save lives. Conventional tidal forecasting methods are based on harmonic analysis using the least squares method to determine harmonic parameters. However, a large number of parameters and long-term measured data are required for precise tidal level predictions with harmonic analysis. Furthermore, traditional harmonic methods rely on models based on the analysis of astronomical components and they can be inadequate when the contribution of non-astronomical components, such as the weather, is significant. Other alternative approaches have been developed in the literature in order to deal with these situations and provide predictions with the desired accuracy, with respect also to the length of the available tidal record. These methods include standard high or band pass filtering techniques, although the relatively deterministic character and large amplitude of tidal signals make special techniques, like artificial neural networks and wavelets transform analysis methods, more effective. This paper is intended to provide the communities of both researchers and practitioners with a broadly applicable, up to date coverage of tidal analysis and forecasting methodologies that have proven to be successful in a variety of circumstances, and that hold particular promise for success in the future. Classical and novel methods are reviewed in a systematic and consistent way, outlining their main concepts and components, similarities and differences, advantages and disadvantages.