drawre: Extraction of independent rainfall events from a sub-daily...
In IETD: Inter-Event Time Definition

Description Usage Arguments Details Value Note Author(s) References Examples

View source: R/drawre.R

This function draws rainfall events from a sub-daily rainfall time series based on the inter-event time definition (IETD) method and computes the event characteristics such as duration, total rainfall depth, and intensity. The function allows slight rainfall events to be characterized, which are, in turn, not considered in the extraction of rainfall events.

1	drawre(Time_series,IETD,Thres)

`Time_series`	A dataframe. The first column contains the time and day of a rainfall pulse and the second one the depth of rainfall in each time step. The date must be as POSIXct class.
`IETD`	The minimum rainless period or dry period (hours) to be considered between two independent rainfall events.
`Thres`	A rainfall depth threshold to define slight rainfall events (default value 0.5).

IETD is defined as the minimum dry or rainless period between two independent events. This time interval is applied to a continuous time series: if two groups of consecutive pulses of rainfall are separated by a rainless period longer than or equal to IETD, they are considered as two independent rainfall events; otherwise, these two groups are categorized as belonging to the same event \insertCiteRestrepo-Posada1982,Adams2000IETD. A rainless period between two independent events is known as inter-event time (b) and by definition b>= IETD. A rainfall event whose rainfall pulses are lower than the threshold Thres is characterized as a slight rainfall event.

A list with a dataframe, named Rainfall_Characteristics, and a sublist, named Rainfall_Events, is provided. Rainfall_Characteristics contains the main information of each extracted rainfall event such as event number, the beginning and end of the event, duration (in hours), total rainfall depth, and average intensity (total rainfall depth/duration). Rainfall_Events contains several dataframes with the values of rainfall pulses of each extracted rainfall event. The first dataframe in Rainfall_Events corresponds to the first event in Rainfall_Characteristics, the second dataframe in Rainfall_Events corresponds to the second event in Rainfall_Characteristics, and so on.

This function does not accept missing values in the sub-daily rainfall time series.

Luis F. Duque <lfduquey@gmail.com> <l.f.duque-yaguache2@newcastle.ac.uk>

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