Intercomparison of statistical and machine-learning methods for sea-level trend estimation at the Hon Dau tide gauge (1960–2024)

This paper presents an intercomparison of statistical, machine-learning, and signal decomposition methods for estimating sea-level trends using the long-term tide-gauge record at Hon Dau tide gauge (northern Vietnam) during 1960–2024. Classical statistical approaches (Mann–Kendall, Ordinary Least Squares), machine-learning models (Random Forest, Support Vector Regression, Artificial Neural Network, Long Short-Term Memory), and signal decomposition techniques (Empirical Mode Decomposition, and Co