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Welcome to our wiki page, offering supplementary explanations and guidance to our data platform.


Beach profiles are 2D measurements of elevation and distance (chainage) along a pre-determined line. The beach profile is measured from the back of the beach such as a sea wall and extend seaward until the Mean Low Water Spring (MLWS) elevation is reached (this is known as a vertical datum).  You can find detailed instructions for profile surveys in the documents section for more information.

Over time beach profiles are repeated and their changes can be compared in a graph.

We use the 4 vertical datums and the 'back of beach' chainage shown here to calculate cross sectional area.

Profile Graph3.png

Cross Sectional Area (CSA)

CSA is the area underneath the profile line from the back of the mobile beach to a specific vertical datum e.g. MLWS. Four examples of CSA are shown for the four datums below.


CSA is a single value to represent each profile. The time series chart displays a MLWN CSA. 

This allows us to see how that CSA trends over time.

CSA over time.png

Sigma Value


In statistics the standard deviation is a measure of the amount of variation of a variable expected about its mean. This is represented by 'Sigma'.

The box and whisker displays the CSA Sigma values which describes the distribution or natural variability of the profile. Values >2 or <-2 Sigma would be considered extreme. There are no extreme values shown in this plot.

CSA box and whisker.png

Survey Unit Status

Our 'survey unit status' averages profile Sigma values from the most recent survey. In the Survey Unit 8c15.1 shown in the satellite image below, the average Sigma is calculated across 17 profiles.  The scale is 'absolute' which means the negatives Sigmas have been transformed to positives. This is to allow for alongshore variability within a survey unit where positive and negative profile sigma values could average to zero. That would be a misleading score for a beach where a lot of change is occurring. 

Alongshore Distribution.png

Normal status;  1 Standard Deviation from the mean (68% of all results fall within this range) 
Moderate status;  between 1-2 SD from the mean (95% of all results fall within 0-2)
Extreme;  is more than 2 SD from the mean (5% remaining)  


Wave power data demonstrates the short term antecedent hydrodynamic conditions.  Long term seasonal wave events are also shown to provide context. The graphs are generated using E.U. Copernicus Marine Service Information.

Wave Power Equation

The return period of extreme wave height events has been calculated using extreme value analysis in python using the pyextremes package. The 'storm' threshold value was selected as the 95th percentile value (the top 5% of significant wave height values were classified as 'storm'). The peaks over threshold (POT) method was used, classifying any top 5% value within 16hrs of another to be one storm event to avoid capturing the same event multiple times. A return period of 1 year (365.2425 days) was used with a Weibull distribution in order to give the return period of each significant wave height 'storm' event. The return periods were then grouped by size of the event and the numer of events in each year (from September to August to include an entire storm season) was counted e.g. a 2.568 return period value was grouped as a 1 in 1 year event, a 11.450 return period value is grouped as a 1 in 10 year event. 
More details

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