screen.summary {FlowScreen}

Create a screening plot

Description

Produces summary screening plots of high flow, low flow, or baseflow metrics. Each plot shows significant temporal trends and step changes. Intended for use as a data quality screening tool aimed at identifying streamflow records with anthropogenic impacts or data inhomogeneities.

Usage

screen.summary(metrics, type = "h", language = "English", StnInfo = NULL)

Arguments

metrics

output from metrics.all

type

Character indicating the set of metrics to plot. Options are "h" for high flow metrics, "l" for low flow metrics, or "b" for baseflow metrics.

language

Language for plot labels. Choice of either "English" or "French". Default is "English".

StnInfo

Optional data.frame containing user-supplied station info for plot. data.frame must have 7 columns containing station info in the following order: Station ID, Station Name, Prov/State, Country, Latitude, Longitude, Catchment Area If any of the information is unavailabe, fill with NA. The Station ID column must match the Station ID in column 1 of the data.frame input from create.ts.

Details

For the center of volume (COV) plots on the high flow and baseflow screening plots, the correlation coefficients for COV and years and for mean annual flow (MAF) and years are added to the plot. The ratio of the correlation coefficients (r COV-years / r COV-MAF) is included as a rudimentary indication of whether or not the temporal trend in COV is meaningful. See Whitfield (2013) for a discussion of COV.

Drought metrics for the low flow plot may not be applicable to intermittent streams, and plots will be empty in this case.

Important note: If "French" is the language wanted for the plot labels, the language option must also be specified in metrics.all, as this plotting function pulls the metric names from the output metrics.all output.

Author(s)

Jennifer Dierauer

References

Whitfield, P.H. 2013. Is 'Center of Volume' a robust indicator of changes in snowmelt timing? Hydrological Processes 27:2691-8.

Examples

# load results from metrics.all function for the Caniapiscau River
data(caniapiscau.res)

# create a summary flow screening plot of the high flow metrics
screen.summary(caniapiscau.res, type="l")