Quantitative and Qualitative Error Re-analysis of Tidal Datasets

<p>Tidal data forms the basis for understanding and quantifying sea-level rise and tidal statistics. While quality assurance methods based upon spectral and harmonic analysis have been applied to individual tidal records, these methods have not been used to assess global tidal datasets. In this thesis, four west coast tidal records were examined using harmonic analysis methods to investigate uncertainty on a monthly averaged basis. Uncertainty was identified using a method that quantifies time lag as a linear regression of height difference between a predicted and measured tidal height and the predicted rate of change of tidal height. Errors identified through this method were validated by visual inspection of qualitative records and digitization of daily staff/gauge comparisons. Of the 1188 total months investigated using the time-lag based estimates, 41 months of high uncertainty were identified validated through comparison with staff/gauge comparisons. Six additional months of high uncertainty were identified by the time-lag based method but were not apparent in staff-gauge comparisons. An additional 55 months of possibly inadequate data were only identified by staff/gauge comparisons. These 55 cases were shown to relate to either staff measurement error or short-term gauge issues. For problems that persisted over a month, a binning approach was used to create a statistically significant relationship between estimated time lag and the uncertainty in the water level measurement. In the future, this regression could be applied to assess uncertainty in other tidal datasets.</p>

Name thesis:degree_name

MS in Civil and Environmental Engineering

Discipline thesis:degree_discipline

Civil and Environmental Engineering

Year dc:date.available

2020

Author dc:creator

• Ledezma, Ernesto Andrew

Contributors dc:contributor

• Stefan Talke
• Civil and Environmental Engineering
• College of Engineering

• Error Re-Analysis
• Tide Gauge
• Historic Tide Records
• Civil Engineering
• Environmental Engineering
• Other Civil and Environmental Engineering

Identifier

10.15368/theses.2020.115

OAI identifier oai:identifier

oai:digitalcommons.calpoly.edu:theses-3675