Date Log
This work is licensed under a Creative Commons Attribution 4.0 International License.
Presentation of a Wavelet‑Based Harmonic Model for Tidal Level Forecasting at Sabah and Sarawak
Corresponding Author(s) : Auwal Garba Abubakar
Geomatics and Environmental Engineering,
Vol. 14 No. 4 (2020): Geomatics and Environmental Engineering
Abstract
The world´s tides are a result of the combined forces of celestial forces and centrifugal force exerted by the Earth‑Moon and the Sun acting on the water body, earth tides and the atmospheric tides. Harmonic analysis is the most popular and widely accepted method used for the processing and expression of tidal behavior as well as its characteristics. Despite its strengths, harmonic analysis has a few drawbacks when short data are involved for long term‑prediction. However, to enhance the accuracy of the popular methodology of harmonic analysis (HA), this study presents a wavelet‑based harmonic model for tidal analysis and prediction. Six months of water level heights at four tide gauge stations in Sabah and Sarawak of Malaysia were employed. The results obtained agrees with the original data when a comparison was made. The root mean square error (RMSE) and Pearson correlation coefficient (r) are the statistical index tools applied to test the functioning of the model. The residual error is the deviation between the original data and the predicted data which was also computed in this study. The new wavelet‑based harmonic model improves the accuracy of prediction. Moreover, the model is efficient and feasible for tidal analysis and prediction.
Keywords
Download Citation
Endnote/Zotero/Mendeley (RIS)BibTeX
- Li S., Liu L., Cai S., Wang G.: Tidal harmonic analysis and prediction with least‑squares estimation and inaction method. Estuarine, Coastal and Shelf Science, vol. 220, 2019, pp. 196–208. https://doi.org/10.1016/j.ecss.2019.02.047.
- Liu J., Shi G., Zhu K.: High‑Precision Combined Tidal Forecasting Model. Algorithms, vol. 12, no. 3, 2019, pp. 65 (1–17).
- Zeguo Z., Jianchuan Y.I.N., Nini W., Jiangqiang H.U., Ning W.: A precise tidal prediction mechanism based on the combination of harmonic analysis and adaptive network‑based fuzzy inference system model. Acta Oceanologica Sinica, vol. 36, no. 11, 2017, pp. 94–105. https://doi.org/10.1007/s13131-017-1140-x.
- Darwin G.H.: Oceanic Tides and Lunar Disturbances of Gravity. Scientific papers, vol. 1, University Press, 1907.
- Chen B.-F., Wang H.-D., Chu C.-C.: Wavelet and artificial neural network analyses of tide forecasting and supplement of tides around Taiwan and South China Sea. Ocean Engineering, vol. 34, no. 16, 2007, pp. 2161–2175.
- El‑Diasty M., Al‑Harbi S.: Development of wavelet network model for accurate water levels prediction with meteorological effects. Applied Ocean Research, vol. 53, 2015, pp. 228–235. https://doi.org/10.1016/j.apor.2015.09.008.
- Abubakar A.G., Mahmud M.R., Tang K.K.W., Hussaini A., Md Yusuf N.H.: A review of modelling approaches on tidal analysis and prediction. International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol. 42, no. 4/W16, 2019, pp. 23–34. https://doi.org/10.5194/isprs-archives-XLII-4-W16-23-2019.
- Rossiter J.R.: The History of Tidal Predictions in the United Kingdom before the Twentieth Century. Proceedings of the Royal Society of Edinburgh, Section B: Biological Sciences, vol. 73, 1972, pp. 13–23.
- Presentation of a Wavelet‑Based Harmonic Model for Tidal Level Forecasting... 23
- Agnew D.C.: Earth Tides: An Introduction, University of California, San Diego 2005.
- Munk W.H., Cartwright D.E.: Tidal spectroscopy and prediction. Philosophical Transactions of the Royal Society of London. Series A, Mathematical and Physical Sciences, vol. 259, 1966, pp. 533–581.
- Flinchem E.P., Jay D.A.: An introduction to wavelet transform tidal analysis methods. Estuarine, Coastal and Shelf Science, vol. 51, no. 2, 2000, pp. 177–200. https://doi.org/10.1006/ecss.2000.0586.
- Zhang Z., Yin J., Wang N., Hu J., Wang N.: A precise tidal prediction mechanism based on the combination of harmonic analysis and adaptive network‑based fuzzy inference system model. Acta Oceanologica Sinica, vol. 36, no. 11, 2017, pp. 94–105. https://doi.org/10.1007/s13131-017-1140-x.
- Yin J., Perakis A.N., Wang N., Member S.: An Ensemble Real‑Time Tidal Level Prediction Mechanism Using Multiresolution Wavelet Decomposition Method. IEEE Transactions on Geoscience and Remote Sensing, vol. 56, issue 8, 2018, pp. 4856–4865. https://doi.org/10.1109/TGRS.2018.2841204.
- El‑Diasty M., Al‑Harbi S., Pagiatakis S.: Hybrid harmonic analysis and wavelet network model for sea water level prediction. Applied Ocean Research, 2018, vol. 70, pp. 14–21.
- Cai S., Liu L., Wang G.: Short‑term tidal level prediction using normal time‑frequency transform. Ocean Engineering, vol. 156, 2018, pp. 489–499. https://doi.org/10.1016/j.oceaneng.2018.03.021.
- Egbert G.D., Ray R.D.: Tidal prediction. Journal of Marine Research, vol. 75, no. 3, 2017, pp. 189–237.
- Daubechies I.: Ten Lectures on Wavelets. Society for Industrial and Applied Mathematics, 1992.
- Chan Y.T.: Wavelet Basics. Springer Science & Business Media, 1994.
- Meyers O.S.D, Kelly B.G., O’Brien J.J.: An Introduction to Wavelet Analysis in Oceaonography and Meteorology with Application to the Dispersion of Yanai Waves. Monthly Weather Review, vol. 121, 1993, pp. 2858–2866.
- Barford L.A., Fazzio R.S., Smith D.R.: An Introduction to Wavelets. Hewlett‑Packard Laboratories, Technical Publications Department, 1992.
- Singh C., Singh J.: ECG Signal Denoising & Detection Using Digital, Adaptive Filter & Wavelet Transform. Lovely Professional University, 2017 [Ph.D. thesis].
- Mallat S.G.: A theory for multiresolution signal decomposition: The wavelet representation. [in:] Heil Ch., Walnut D.F. (eds.), Fundamental Papers in Wavelet Theory, Princeton University Press, 2006, pp. 494–513. https://doi.org/10.1515/9781400827268.494.
References
Li S., Liu L., Cai S., Wang G.: Tidal harmonic analysis and prediction with least‑squares estimation and inaction method. Estuarine, Coastal and Shelf Science, vol. 220, 2019, pp. 196–208. https://doi.org/10.1016/j.ecss.2019.02.047.
Liu J., Shi G., Zhu K.: High‑Precision Combined Tidal Forecasting Model. Algorithms, vol. 12, no. 3, 2019, pp. 65 (1–17).
Zeguo Z., Jianchuan Y.I.N., Nini W., Jiangqiang H.U., Ning W.: A precise tidal prediction mechanism based on the combination of harmonic analysis and adaptive network‑based fuzzy inference system model. Acta Oceanologica Sinica, vol. 36, no. 11, 2017, pp. 94–105. https://doi.org/10.1007/s13131-017-1140-x.
Darwin G.H.: Oceanic Tides and Lunar Disturbances of Gravity. Scientific papers, vol. 1, University Press, 1907.
Chen B.-F., Wang H.-D., Chu C.-C.: Wavelet and artificial neural network analyses of tide forecasting and supplement of tides around Taiwan and South China Sea. Ocean Engineering, vol. 34, no. 16, 2007, pp. 2161–2175.
El‑Diasty M., Al‑Harbi S.: Development of wavelet network model for accurate water levels prediction with meteorological effects. Applied Ocean Research, vol. 53, 2015, pp. 228–235. https://doi.org/10.1016/j.apor.2015.09.008.
Abubakar A.G., Mahmud M.R., Tang K.K.W., Hussaini A., Md Yusuf N.H.: A review of modelling approaches on tidal analysis and prediction. International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol. 42, no. 4/W16, 2019, pp. 23–34. https://doi.org/10.5194/isprs-archives-XLII-4-W16-23-2019.
Rossiter J.R.: The History of Tidal Predictions in the United Kingdom before the Twentieth Century. Proceedings of the Royal Society of Edinburgh, Section B: Biological Sciences, vol. 73, 1972, pp. 13–23.
Presentation of a Wavelet‑Based Harmonic Model for Tidal Level Forecasting... 23
Agnew D.C.: Earth Tides: An Introduction, University of California, San Diego 2005.
Munk W.H., Cartwright D.E.: Tidal spectroscopy and prediction. Philosophical Transactions of the Royal Society of London. Series A, Mathematical and Physical Sciences, vol. 259, 1966, pp. 533–581.
Flinchem E.P., Jay D.A.: An introduction to wavelet transform tidal analysis methods. Estuarine, Coastal and Shelf Science, vol. 51, no. 2, 2000, pp. 177–200. https://doi.org/10.1006/ecss.2000.0586.
Zhang Z., Yin J., Wang N., Hu J., Wang N.: A precise tidal prediction mechanism based on the combination of harmonic analysis and adaptive network‑based fuzzy inference system model. Acta Oceanologica Sinica, vol. 36, no. 11, 2017, pp. 94–105. https://doi.org/10.1007/s13131-017-1140-x.
Yin J., Perakis A.N., Wang N., Member S.: An Ensemble Real‑Time Tidal Level Prediction Mechanism Using Multiresolution Wavelet Decomposition Method. IEEE Transactions on Geoscience and Remote Sensing, vol. 56, issue 8, 2018, pp. 4856–4865. https://doi.org/10.1109/TGRS.2018.2841204.
El‑Diasty M., Al‑Harbi S., Pagiatakis S.: Hybrid harmonic analysis and wavelet network model for sea water level prediction. Applied Ocean Research, 2018, vol. 70, pp. 14–21.
Cai S., Liu L., Wang G.: Short‑term tidal level prediction using normal time‑frequency transform. Ocean Engineering, vol. 156, 2018, pp. 489–499. https://doi.org/10.1016/j.oceaneng.2018.03.021.
Egbert G.D., Ray R.D.: Tidal prediction. Journal of Marine Research, vol. 75, no. 3, 2017, pp. 189–237.
Daubechies I.: Ten Lectures on Wavelets. Society for Industrial and Applied Mathematics, 1992.
Chan Y.T.: Wavelet Basics. Springer Science & Business Media, 1994.
Meyers O.S.D, Kelly B.G., O’Brien J.J.: An Introduction to Wavelet Analysis in Oceaonography and Meteorology with Application to the Dispersion of Yanai Waves. Monthly Weather Review, vol. 121, 1993, pp. 2858–2866.
Barford L.A., Fazzio R.S., Smith D.R.: An Introduction to Wavelets. Hewlett‑Packard Laboratories, Technical Publications Department, 1992.
Singh C., Singh J.: ECG Signal Denoising & Detection Using Digital, Adaptive Filter & Wavelet Transform. Lovely Professional University, 2017 [Ph.D. thesis].
Mallat S.G.: A theory for multiresolution signal decomposition: The wavelet representation. [in:] Heil Ch., Walnut D.F. (eds.), Fundamental Papers in Wavelet Theory, Princeton University Press, 2006, pp. 494–513. https://doi.org/10.1515/9781400827268.494.