hydroEvents (version 0.12.0)

eventMaxima: Event identification (using local maxima as a basis)

Description

Events are identified on the basis of local maxima with an "event" considered to have occurred if the maxima is above a tolerable threshold of the neighbouring troughs/valleys.

Usage

eventMaxima(
  data,
  delta.y = 200,
  delta.x = 1,
  threshold = -1,
  out.style = "summary"
)

Value

By default, the out.style returns the indices of the maximum in each event, as well as the value of the maximum and the sum of the data in each event, alongside the start and end of the events. Otherwise just the indices of start and end of events as a two column dataframe are returned.

Arguments

data

The data vector

delta.y

Minimum allowable difference from a peak to a trough

delta.x

Minimum spacing between peaks

threshold

Value above which an event is considered to have occurred

out.style

The type of output (currently either "summary" or "none")

Details

If delta.y is negative it is applied a fractional decrease from the peak, otherwise it is treated as an absolute value. The threshold is applied after the event separation meaning that if a trough goes below the threshold but was originally considered one event it will continue to be considered one event. This makes this method distinct from the peaks over threshold algorithm in eventPOT. The threshold here should be thought of as a filter to remove trace amounts that are not part of an event rather than event separation metric.

See Also

calcStats eventBaseflow eventMaxima eventPOT

Examples

# Example extracting events from quickflow
bf = baseflowB(dataBassRiver, alpha = 0.925)
qf = dataBassRiver - bf$bf
events = eventMaxima(qf, delta.y = 200, delta.x = 1, threshold = 0)
print(events)
plotEvents(qf, dates = NULL, events = events, type = "lineover", main = "")
# Other examples to try
# delta.y = 200; delta.x = 1 # 5 events identified
# delta.y = 500; delta.x = 1 # 3 events identified
# delta.y = 10;  delta.x = 7 # 2 events identified