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Publicado el: 2022-06-23
Tiempo de estudio aproximado: .75 - 1.00 h
Incluye sonido: no
Áreas temáticas
Geospatial
Oceanography/Marine/Tsunami
Descripción:
Having accurate water level data ensures that the resulting data products, such as tidal datums, are also accurate. Poor data quality can affect the derived water level products and impact applications such as marsh restoration or coastal engineering. In this lesson, we examine the origins of bad data, how to recognize bad data, how to discriminate between bad data and anomalous, but very real data, and when and how to remediate bad data. This lesson is intended for those interested in examining water level data that has been collected and saved, as opposed to real-time data. Saved data is useful for applications like the determination of tidal datums and inundation analysis.
Objetivos:
After completing this lesson, the learner will be able to:
- Describe the origins of bad water level data,
- Recognize bad water level data,
- Discriminate between bad water level data and anomalous, but real water level data,
- Remediate bad water level data.
Palabras clave
water levels, QA, QC, quality assurance, quality control, data spikes, data gaps, data flats, rapid datum shifts, attenuated tide range, instrument malfunction, stability and drift, statistical tests, standard deviation, tsunami, storm surge, meteotsunami