A Probabilistic Framework for Estimating Present and Future Extreme Total Water Levels in Tidal-Dominated Regions

Estimating extreme total water levels is critical for understanding future flood risks and designing resilient coastal and offshore infrastructure. Traditional methods often rely on a deterministic approach that sums specified high tide values, storm surge levels with certain return periods, and selected sea level rise projections scenarios. However, this approach can overlook the joint probability of these events occurring simultaneously, potentially leading to conservative or inaccurate estimates. Alternatively, extreme value analysis of total water levels may overestimate risk in tidal-dominated settings due to the incorporation of tidal variations. This paper addresses these limitations for a study case in the Arafura Sea, by using Monte Carlo simulations to generate synthetic water level time series for the period from 2024 to 2060, integrating deterministic tide predictions with stochastic storm surge, long period oceanic water level variation, and sea level rise projections. The study finds that in the Arafura Sea the total water level exceedance probabilities are strongly influenced by tidal epochs and sea level rise, with the most extreme conditions anticipated around 2045. By aligning design conditions more closely with actual risk tolerance, this methodology provides more accurate estimates of extreme water levels and future flood risks, offering valuable insights for the design of coastal and offshore facilities in tidal-dominated regions.