hydroEvents (version 0.12.0)

eventMinima: Event identification (using local minima as a basis)

Description

Events are identified on the basis of local minima with an "event" considered to have occurred once the data has returned to within a threshold level of the start of the event.

Usage

eventMinima(
  data,
  delta.y = 20,
  delta.x = 5,
  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

Maximum allowable difference between troughs

delta.x

Minimum length for an event

threshold

Value above which an event is considered to have occurred

out.style

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

Details

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.

References

Tang, W., & Carey, S. K. (2017) HydRun: A MATLAB toolbox for rainfall-runoff analysis, Hydrological Processes (31) 2670-2682

See Also

calcStats eventBaseflow eventMaxima eventPOT

Examples

# Example extracting events from quickflow
bf = baseflowB(dataBassRiver, alpha = 0.925)
qf = dataBassRiver - bf$bf
events = eventMinima(qf, delta.x = 5, delta.y = 20)
print(events)
plotEvents(qf, dates = NULL, events = events, type = "lineover", main = "")
# delta.x = 5, delta.y = 20 # 5 events identified
# delta.x = 5, delta.y = 10 # 4 events identified
# delta.x = 1, delta.y = 20 # 6 events identified