calcLakeMetrics {lakemorpho}

Calculate all Lake Morphometry Metrics

Description

This function is a wrapper function for all of the metrics. It calculates each metric for an input lakeMorphoClass. This returns a list of all metrics

Usage

calcLakeMetrics(
  inLakeMorpho,
  bearing,
  pointDens,
  slope_quant = 0.5,
  correctFactor = 1,
  zmax = NULL
)

Arguments

inLakeMorpho

an object of lakeMorphoClass. Output of the lakeSurroundTopo function would be appropriate as input

bearing

Numeric that indicates the bearing of the desired fetch.

pointDens

Number of points to place equidistant along shoreline for lakeMaxLength or density of lines to test for lakeMaxWidth and lakeFetch.

slope_quant

The slope quantile to use to estimate maximum depth. Defaults to the median as described in (Hollister et. al, 2011).

correctFactor

Value used to correct the predicted maximum lake depth. Defaults to 1. Corrections are simply accomplished by multiplying estimated max depth by correction factor. Correction factors can be determined empirically by regressing the predicted depth against a known maximum depth while forcing the intercept through zero. The slope of the line would then be used as the correction factor(Hollister et. al, 2011).

zmax

Maximum depth of the lake. If none entered and elevation dataset is inlcuded in inLakeMorpho, lakeMaxDepth is used to estimate a maximum depth.

Value

Returns a list with all lake metrics calculated for a given input lakemorpho object

References

Florida LAKEWATCH (2001). A Beginner's guide to water management - Lake Morphometry (2nd ed.). Gainesville: Florida LAKEWATCH, Department of Fisheries and Aquatic Sciences. Link

Hollister, J. W., W.B. Milstead (2010). Using GIS to Estimate Lake Volume from Limited Data. Lake and Reservoir Management. 26(3)194-199. doi:10.1080/07438141.2010.504321

Hollister, J. W., W.B. Milstead, M.A. Urrutia (2011). Predicting Maximum Lake Depth from Surrounding Topography. PLoS ONE 6(9). doi:10.1371/journal.pone.0025764

Examples

data(lakes)
calcLakeMetrics(inputLM, bearing = 45, pointDens = 25)