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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.

Usage

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

Author

Johannes Ranke

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