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Time Series Analysis

For data collected in the field, time series analysis is a valuable method for examining a wide range of variables and how they vary in time and with respect to each other. Often, a pattern or trend can be detected on the basis of one variable that can lead to a hypothesis about a certain process. The hypothesis can then be tested or verified through examination of a range of related variables. Such methodology is, here, being used to examine the role of internal waves in fluid mud entrainment dynamics in an estuarine system.

Current Projects


Bryna Flaim

Time series analysis is undertaken on a dataset acquired in 2010 in the Ems Estuary in Germany by Dr. Christian Winter and colleagues for the purposes of investigating the role on internal waves at lutocline on the overall fluid mud dynamics. Such variables as current speed (m/s) and acoustic backscatter (dB), recorded by Acoustic Doppler Current Profilers, are examined alongside changes in acoustic impedance (AI), recorded by Sediment Echosounder, to identify the timing of fluid mud entrainment, internal wave characteristics, and changes in water column stability. Additional variables, such as temperature, suspended sediment concentration, and salinity are used to enhance and complement the findings. In March 2013, a second dataset was collected in the Waihou River near the Firth of Thames in New Zealand with the aim of examining similar processes, but in a different setting. The findings from the two surveys will provide an improved perspective on the role of internal waves in a fluid mud system; a phenomenon that has been, until now, not extensively observed in situ.
More details about the project on INTERCOAST