sigmaHighFlows function

Estimate catastrophic flow variability

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.

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.

Returns

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.

Examples

# load data
data(sycamore)

# get streamflow object
sf = asStreamflow(sycamore)

# estimate catastrophic high flow variability
sigmaHighFlows(sf)

See Also

independentEvents

sigmaLowFlows