1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
|
# Calculate drift percentages based on Rautmann data
Calculate drift percentages based on Rautmann data
## Usage
``` r
drift_percentages_rautmann(
distances,
applications = 1,
crop_group_RF = "arable",
formula = c("Rautmann", "FOCUS"),
widths = 1
)
```
## Arguments
- distances:
The distances in m for which to get PEC values
- applications:
Number of applications for selection of drift percentile
- crop_group_RF:
Crop group(s) as used in
[drift_parameters_focus](https://pkgdown.jrwb.de/pfm/reference/drift_parameters_focus.md),
i.e. "arable", "hops", "vines, late", "vines, early", "fruit, late",
"fruit, early" or "aerial".
- formula:
By default, the original Rautmann formula is used. If you specify
"FOCUS", mean drift input over the width of the water body is
calculated as described in Chapter 5.4.5 of the FOCUS surface water
guidance
- widths:
The widths of the water bodies (only used in the FOCUS formula)
## References
FOCUS (2014) Generic guidance for Surface Water Scenarios (version 1.4).
FOrum for the Co-ordination of pesticde fate models and their USe.
<http://esdac.jrc.ec.europa.eu/public_path/projects_data/focus/sw/docs/Generic%20FOCUS_SWS_vc1.4.pdf>
## See also
[drift_parameters_focus](https://pkgdown.jrwb.de/pfm/reference/drift_parameters_focus.md),
[PEC_sw_drift](https://pkgdown.jrwb.de/pfm/reference/PEC_sw_drift.md)
## Examples
``` r
# Compare JKI data with Rautmann and FOCUS formulas for arable crops (default)
# One application on field crops, for 1 m, 3 m and 5 m distance
drift_data_JKI[[1]][as.character(c(1, 3, 5)), "Ackerbau"]
#> 1 3 5
#> 2.77 0.95 0.57
drift_percentages_rautmann(c(1, 3, 5))
#> [1] 2.7593000 0.9424748 0.5719342
drift_percentages_rautmann(c(1, 3, 5), formula = "FOCUS")
#> [1] 1.9273922 0.8160023 0.5224362
# Since pfm 0.6.5, the function can also take a vector of crop groups
drift_percentages_rautmann(
distances = c(1, 5, 5),
crop_group_RF = c("fruit, early", "fruit, early", "fruit, late"))
#> [1] 66.702000 19.884442 8.410849
# Two applications, all else equal
drift_data_JKI[[2]][as.character(c(1, 3, 5)), "Ackerbau"]
#> 1 3 5
#> 2.38 0.79 0.47
drift_percentages_rautmann(c(1, 3, 5), applications = 2)
#> [1] 2.4376000 0.8036556 0.4797365
drift_percentages_rautmann(c(1, 3, 5), formula = "FOCUS", app = 2)
#> [1] 1.6837733 0.6925952 0.4369331
# One application to early or late fruit crops
drift_data_JKI[[1]][as.character(c(3, 5, 20, 50)), "Obstbau frueh"]
#> 3 5 20 50
#> 29.20 19.89 2.77 0.30
drift_percentages_rautmann(c(3, 5, 20, 50), crop_group_RF = "fruit, early")
#> [1] 29.1973659 19.8844422 2.7618138 0.3012008
drift_percentages_rautmann(c(3, 5, 20, 50), crop_group_RF = "fruit, early",
formula = "FOCUS")
#> [1] 26.1193421 18.5428680 2.6038558 0.2940792
drift_data_JKI[[1]][as.character(c(3, 5, 20, 50)), "Obstbau spaet"]
#> 3 5 20 50
#> 15.73 8.41 1.09 0.22
drift_percentages_rautmann(c(3, 5, 20, 50), crop_group_RF = "fruit, late")
#> [1] 15.7246994 8.4108487 1.0813887 0.2155992
drift_percentages_rautmann(c(3, 5, 20, 50), crop_group_RF = "fruit, late",
formula = "FOCUS")
#> [1] 13.1414350 7.5123244 1.0359007 0.2118734
# We get a continuum if the waterbody covers the hinge distance
# (11.4 m for 1 early app to fruit)
x <- seq(3, 30, by = 0.1)
d <- drift_percentages_rautmann(x, crop_group_RF = "fruit, early", formula = "FOCUS")
plot(x, d, type = "l",
xlab = "Distance of near edge [m]",
ylab = "Mean drift percentage over waterbody width",
main = "One application to fruit, early")
abline(v = 11.4, lty = 2)
```
|
