getRainEventData: Get rain event of a landslide

In ggRaver/Lslide: Functions for object-oriented image analysis in landslide science

Get rain event of a landslide

Description

This function calcuates different precipitation characteristics for a specific time-series: total precipitation, number of rainfall events, weighted mean intensitiy of rainfall events (normalized by MAP, RD or RDN), cumulative critical event rainfall (normalized by MAP, RD or RDN), maximum rainfall during critical rainfall event, duration of critical rainfall event, critical rainfall intensitiy (normalized by MAP, RD or RDN), rainfall at day of failure (start date), rainfall intensity at day of failure (start date), maximum rainfall at day of failure (start date).

Usage

getRainEventData(x, dates = NULL, timesteps = NULL,
  date.of.failure = NULL, sub.RainEvent = TRUE,
  all.RainEvent = FALSE, cumu.RainFall = NULL,
  return.DataFrame = FALSE, S1.rainThresh = 0.2, S3.rainThresh = 1,
  S1.rainOffLength = c(3, 6), S2.rainOffLength = c(6, 12),
  S4.rainOffLength = c(48, 96), RD = NULL, MAP = NULL,
  RDN = MAP/RD, index.month.warm.season = c(4, 10),
  force.limit = NULL)

Arguments

x	vector containing precipitation
dates	vector containing dates. The length of dates must be similar to the length of x. Default: NULL
timesteps	time period or length of observation. The rev(x) and rev(dates) are subsetted to this length according to date.of.failure if set. I.e. 24 for hourly or 1 for daily data. Default: NULL
date.of.failure	date of failure. If set data is subsetted to this date. Must be of class "POSIXct" or "POSIXt". Default: NULL
sub.RainEvent	examine potential sub-rain-events of critical rainfall event. Default: TRUE
all.RainEvent	if TRUE, all rain events in data are extracted. By setting this option, no critival rain event metrics are computed. Default: FALSE
cumu.RainFall	vector containing time intervals for cumulative rainfall. I.e. c(24, 48, 96) for 1, 2 and 4 days aggregation. Default: NULL
return.DataFrame	only the rain events are returned as a data.frame. Default: FALSE
S1.rainThresh	isolated rainfall measurements below this thresholds are removed in the first step. Default: 0.2
S3.rainThresh	exclusion of irrelevant rainfall sub-events under and equal to this threshold (third step). Default: 1 [mm]
S1.rainOffLength	dry periods between isolated rain events in the first step. Default: c(3, 6) (hours). When dates is NULL, then the smallest values is used for separation.
S2.rainOffLength	dry periods between rainfall sub-events in the second step. Default: c(6, 12) (hours). When dates is NULL, then the smallest values is used for separation.
S4.rainOffLength	dry periods between rainfall sub-events in the second step. Default: c(48, 96) (hours). When dates is NULL, then the smallest values is used for separation.
RD	average number of rainy days in a year, proxy for locate climate conditions. Default: NULL
MAP	mean annual precipitation, the long-term yearly average precipitation, see CRU - climate research units for number. Default: NULL
RDN	a climatic index that provides better description (or proxy) than the MAP for the occurence of extreme storm events (Guzzetti et al. 2006: 247). Default: MAP/RD
index.month.warm.season	month indices of the warm season. First element is start, and second element represents the end (all including). Only relevant when dates are set. Default: c(4, 10) (including April, including Ocotober)
force.limit	Usefull for standard output, if result is type list. Must be integer number of specific size. If result is smaller, than results gets filled with NA, otherwise cut to this size. Default: NULL

Value

vector containing rainfall metrics (see description). If return.DataFrame is TRUE a data.frame is returned containing similar rain metrics for all rain events.

Note

• thresholds are oriented at hourly data

• timesteps with precipitation equal 0 are included (see Melillo et al. 2015: 314)

• Guzzetti, F., Peruccacci, S., Rossi, M., & Stark, C. P. (2007). Rainfall thresholds for the initiation of landslides in central and southern Europe. Meteorology and atmospheric physics, 98(3-4), 239-267.

• Rossi, M., Luciani, S., Valigi, D., Kirschbaum, D., Brunetti, M. T., Peruccacci, S., & Guzzetti, F. (2017). Statistical approaches for the definition of landslide rainfall thresholds and their uncertainty using rain gauge and satellite data. Geomorphology, 285, 16-27.

• Melillo, M., Brunetti, M. T., Peruccacci, S., Gariano, S. L., & Guzzetti, F. (2015). An algorithm for the objective reconstruction of rainfall events responsible for landslides. Landslides, 12(2), 311-320.

ggRaver/Lslide documentation built on April 8, 2022, 7:14 a.m.