Using Modified Harmonic Analysis to Estimate the Trend of Sea-Level Rise around Taiwan

Chih-Min Hsieh, Dean Chou and Tai-Wen Hsu
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Chih-Min Hsieh: Department of Maritime Information and Technology, National Kaohsiung University of Science and Technology, Kaohsiung 805006, Taiwan
Dean Chou: Department of Biomedical Engineering, National Cheng Kung University, Tainan 70101, Taiwan
Tai-Wen Hsu: Department of Harbor and River Engineering, National Taiwan Ocean University, Keelung 202301, Taiwan

Sustainability, 2022, vol. 14, issue 12, 1-17

Abstract: Sea-level rise (SLR) has become an essential global environmental problem and great importance is attached by all sectors of society. This study aims to estimate the trends of SLR from the tide-gauge measurements located in different sites of Taiwan. Different methods of analysis, such as the linear-regression method (LRM), Hilbert–Huang transform (HHT), and modified harmonic analysis (MHA) are used to estimate SLR and their applicability is discussed. Limitations of these methods are also compared and discussed via the analyzed results. MHA is the focus of the present paper. It has the advantage of representing tidal harmonic motion as well as the long-term trend of SLR more accurately, even in the condition of data loss caused by mechanical failures or anomaly. The analyzing results reveal that MHA is more applicable for estimating SLR than the above traditional methods. The most important analyzed results indicate that the recent 20-year SLR rate is within the range of −0.9 mm/yr and 18.1 mm/yr, using the tidal database observed at 17 stations along the Taiwanese coast. SLR is also compared with analyzed results from different databases or scenarios. The value of SLR is modified by adding the vertical-change rate of the benchmark. It is interesting to note that correction tends to reduce the bias of the variation trend of SLR.

Keywords: sea-level rise (SLR); modified harmonic analysis (MHA); linear regression method (LRM); empirical mode decomposition (EMD) (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
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