Beach-Scale Tidal Variations Observed From Satellite-Derived Shoreline Time Series

Why It Matters

Accurate, high‑resolution tidal data improve flood risk assessments and sediment transport models, especially where traditional gauges are sparse. Satellite shoreline observations provide a scalable solution for coastal managers worldwide.

Key Takeaways

• Shoreline imagery captures tidal cycles at meter scale
• Harmonic analysis matches in‑situ tide gauge data
• Bayesian estimator reveals M2 trends around New Zealand
• Satellite shoreline data validates coastal tide models
• Phase‑locked S2 constituent detected from optical imagery

Pulse Analysis

Coastal tidal dynamics influence flooding, erosion, and ecosystem health, yet conventional satellite altimetry struggles near shorelines due to signal contamination and coarse resolution. Recent advances in processing optical satellite imagery now generate continuous shoreline positions, creating a dense, beach‑scale dataset that fills the observational gap left by sparse tide‑gauge networks. This new data stream enables researchers to monitor tidal fluctuations with meter‑level precision across extensive coastlines.

The study applies both classic harmonic analysis and response‑based techniques to the shoreline time series, extracting major constituents such as M₂, S₂, and higher‑order terms. A variational Bayesian harmonic estimator further quantifies long‑term trends, revealing statistically significant changes in the M₂ amplitude around New Zealand that align with independent tide‑gauge and altimetry records. Validation against in‑situ measurements confirms that shoreline‑derived tides retain phase and amplitude fidelity, establishing confidence in the method for scientific and operational use.

Beyond validation, satellite‑derived shoreline observations offer a scalable, cost‑effective tool for coastal managers and modelers. They can be integrated into flood‑risk frameworks, sediment‑transport simulations, and climate‑impact assessments, especially in regions lacking dense gauge networks. As global optical constellations expand, the temporal and spatial coverage of shoreline datasets will improve, positioning them as a cornerstone for next‑generation coastal tide monitoring and model calibration.