Abstract:
Tidal analysis using the harmonic method has been recognized as more accurate compared to non-harmonic methods, as it leverages precise knowledge of astronomic tidal constituents to comprehensively analyze tidal behavior. While the Ordinary Least Squares technique (OLS) has traditionally been employed for tidal harmonic analysis, the Iteratively Re-weighted Least Squares (IRLS) method is gaining prominence due to improved performance speed, computational effectiveness, and fewer operational limitations related to confidence intervals.
In this study, we conduct a comparative analysis of both tidal harmonic analysis methods using 12 months of sea level observational data collected at 10-minute intervals from the Dockyard Tide Gauge in Lagos state. The data is categorized into four types: short-term data without gaps (5 months), short-term data with gaps (4% missing data), multi-months data without gaps (12 months), and multi-months data with gaps (5% missing data). We compute harmonic constants for each tidal constituent in all four scenarios using both OLS and IRLS methods. Furthermore, we determine the confidence intervals and Signal-to-Noise Ratio (SNR) for each method using the UT-tidal analysis hydrographic tool in MATLAB, designed by Codiga (2012). Subsequently, tidal values at specific times based on the determined constituent values are predicted.
Our findings reveal that there is no significant difference in tidal prediction when using either the OLS or the IRLS method for data not exceeding five months, at a 95% confidence interval. However, the OLS method outperforms the IRLS method for short-term data periods. Conversely, for multi-months data periods, the IRLS method performs better than the OLS method in both scenarios (complete data and data sets with omissions).
In conclusion, long-term data may be more suitable for determining river tidal characteristics, with values of 1.457m and 1.6495m for the Mean Low Water Springs (MLWS) and Mean High Water Springs (MHWS), respectively. On the other hand, short-term data proves to be more effective for tidal prediction.
Analyzing and Predicting Tidal Harmonics in Apapa Dockyard, Lagos, Nigeria. GET MORE, ACTUARIAL SCIENCE PROJECT TOPICS AND MATERIALS
