Calculate predicted environmental concentrations in surface water due to drift

This is a basic, vectorised form of a simple calculation of a contaminant concentration in surface water based on complete, instantaneous mixing with input via spray drift.

PEC_sw_drift(
  rate,
  applications = 1,
  water_depth = 30,
  drift_percentages = NULL,
  drift_data = c("JKI", "RF"),
  crop = "Ackerbau",
  distances = c(1, 5, 10, 20),
  rate_units = "g/ha",
  PEC_units = "µg/L"
)

Arguments

rate	Application rate in units specified below
applications	Number of applications for selection of drift percentile
water_depth	Depth of the water body in cm
drift_percentages	Percentage drift values for which to calculate PECsw. 'drift_data' and 'distances' if not NULL.
drift_data	Source of drift percentage data. If 'JKI', the [drift_data_JKI] included in the package is used. If 'RF', the Rautmann formula is used, if implemented for the crop type and number of applications
crop	Crop name (use German names for JKI data), defaults to "Ackerbau"
distances	The distances in m for which to get PEC values
rate_units	Defaults to g/ha
PEC_units	Requested units for the calculated PEC. Only µg/L currently supported

Value

The predicted concentration in surface water

Examples

PEC_sw_drift(100)
#>        1 m        5 m       10 m       20 m 
#> 0.92333333 0.19000000 0.09666667 0.05000000 
# Alternatively, we can use the formula for a single application to "Ackerbau" from the paper
PEC_sw_drift(100, drift_data = "RF")
#>        1 m        5 m       10 m       20 m 
#> 0.92350000 0.19114149 0.09699222 0.04921742 

# This makes it possible to also use different substances
PEC_sw_drift(100, distances = c(1, 3, 5, 6, 10, 20, 50, 100), drift_data = "RF")
#>        1 m        3 m        5 m        6 m       10 m       20 m       50 m 
#> 0.92350000 0.31512171 0.19114149 0.15990435 0.09699222 0.04921742 0.02007497 
#>      100 m 
#> 0.01018678 

# Using custom drift percentages is also supported
PEC_sw_drift(100, drift_percentages = c(2.77, 0.95, 0.57, 0.48, 0.29, 0.15, 0.06, 0.03))
#>     2.77 %     0.95 %     0.57 %     0.48 %     0.29 %     0.15 %     0.06 % 
#> 0.92333333 0.31666667 0.19000000 0.16000000 0.09666667 0.05000000 0.02000000 
#>     0.03 % 
#> 0.01000000