get_drought {SEI}

Get drought characteristics

Description

Extract characteristics of droughts from a time series of values. Drought characteristics include the occurrence, intensity, magnitude, and duration of the drought.

Usage

get_drought(x, thresholds = c(1.28, 1.64, 1.96), exceed = TRUE, lag = FALSE)

Arguments

x

vector or xts object.

thresholds

numeric vector containing thresholds to use when defining droughts.

exceed

logical; TRUE if a drought is defined when x is above the thresholds, FALSE otherwise.

lag

logical; TRUE if the drought should end when the value changes sign.

Details

A drought is assumed to be defined as an instance when the vector x exceeds (if exceed = TRUE) or falls below (if exceed = FALSE) the specified thresholds in thresholds.

thresholds can be a single value, or a vector of values. In the latter case, each threshold is assumed to be a different level or intensity of the drought. For example, if thresholds = c(1, 1.5, 2), then a level 1 drought occurs whenever x exceeds 1 but is lower than 1.5, a level 2 drought occurs whenever x exceeds 1.5 but is lower than 2, and a level 3 drought occurs whenever x exceeds 2.

By default, thresholds = c(1.28, 1.64, 1.96), which correspond to the 90th, 95th, and 97.5th percentiles of the standard normal distribution.

In meteorology, droughts are typically defined in terms of standardised indices, such as the standardised precipitation index (SPI). It is sometimes the case that a drought event ends not when the variable of interest no longer exceeds (or falls below) the relevant thresholds, but rather when the index changes sign. This can help to account for fluctuations around the threshold values, classing it as one long drought rather than several shorter droughts. This definition can be used by specifying lag = TRUE.

get_drought() currently does not use the time series information in the xts input, thereby assuming that the time series is complete, without missing time periods. If x is a vector, rather than an xts object, then this is also implicitly assumed.

The output is a dataframe containing the vector x, a logical vector specifying whether each value of x corresponds to a drought event, and the magnitude of the drought. The magnitude of the drought is only shown on the last day of the drought. This makes it easier to compute statistics about the drought magnitude, such as the average drought magnitude. If thresholds is a vector, the intensity or level of the drought is also returned.

Value

A data frame containing the original values x and the corresponding drought characteristics.

Author(s)

Sam Allen, Noelia Otero

References

Allen, S. and N. Otero (2023): ‘Standardised indices to monitor energy droughts’, Renewable Energy doi:10.1016/j.renene.2023.119206

McKee, T. B., Doesken, N. J., & Kleist, J. (1993): ‘The relationship of drought frequency and duration to time scales’, In Proceedings of the 8th Conference on Applied Climatology 17, 179-183.

Examples

data(data_supply)
# consider hourly German energy supply data in 2019
supply_de <- subset(data_supply, country == "Germany", select = c("date", "PWS"))
supply_de <- xts::xts(supply_de$PWS, order.by = supply_de$date)
supply_de_std <- std_index(supply_de, timescale = "hours")

get_drought(supply_de_std, thresholds = c(-1, -1.5, -2), exceed = FALSE)