discharge (version 1.0.0)

sigmaHighFlows: Estimate catastrophic flow variability

Description

Calculates catastrophic variability for high flow events. Positive residuals from the seasonal signal are used to calculate \(\sigma.hf\) , the standard deviation of high-flow events.

Usage

sigmaHighFlows(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.floods

Number of independent events with positive residuals.

sigma.hfa

Estimated sigma using the y-intercept.

sigma.hfb

Estimated sigma using the slope (\(\sigma.hf\)).

flood.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 \(\sigma.hf\) (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 \(2\sigma.hf\). Columns will contain the same data as the output from the independentEvents function.

See Also

independentEvents sigmaLowFlows

Examples

# NOT RUN {
# load data
data(sycamore)

# get streamflow object
sf = asStreamflow(sycamore)

# estimate catastrophic high flow variability
sigmaHighFlows(sf)
# }