sigmaLowFlows: Estimate catastrophic flow variability

In discharge: Fourier Analysis of Discharge Data

Description

Calculates catastrophic variability for low flow events. Negative residuals from the seasonal signal are used to calculate σ.lf , the standard deviation of low-flow events.

Usage

sigmaLowFlows(x, resid.column)

Arguments

x	An object of class data.frame or streamflow. If a data.frame is used, one column should contain residuals.
resid.column	Optional numeric specifiying which column contains residuals. Required if x is a data frame.

Value

An object of class list with items

n.droughts	Number of independent events with negative residuals.
sigma.lfa	Estimated sigma using the y-intercept.
sigma.lfb	Estimated sigma using the slope (σ.lf).
drought.line	Matrix containing fitted, observed, and residual values from regression of log counts on bin midpoints.
onesigma.events	matrix containing information for all events below σ.lf (as calculated using the slope). Columns will contain the same data as the output from the independentEvents function.
twosigma.events	matrix containing information for all events below 2σ.lf. Columns will contain the same data as the output from the independentEvents function.

See Also

independentEvents sigmaHighFlows

Examples

# load data
data(sycamore)

# get streamflow object
sf = asStreamflow(sycamore)

# estimate catastrophic low flow variability
sigmaLowFlows(sf)

discharge documentation built on May 2, 2019, 5:54 a.m.