Fill missing point source data with annual average
Value
Input data frame as is if no missing values, otherwise missing data filled as described above.
Details
Missing concentration data are replaced with the average for the outfall in a given year. All flow data are also floored at zero. Rows with missing flow data are assigned 0 for all data. Rows with zero flow are assigned concentration of zero.
Examples
pth <- system.file('extdata/ps_dom_hillsco_falkenburg_2019.txt', package = 'tbeploads')
dat <- read.table(pth, skip = 0, sep = '\t', header = TRUE)
dat <- util_ps_checkuni(dat)
util_ps_fillmis(dat)
#> Year Month outfall flow_mgd tn_mgl tp_mgl tss_mgl bod_mgl
#> 1 2019 1 D-001 5.296512 1.756881 0.2001634 0.4167875 0.8280425
#> 2 2019 2 D-001 2.696663 2.120932 0.2656919 0.5553969 1.5441635
#> 3 2019 3 D-001 5.689358 2.158781 0.2425811 0.3740764 1.3241451
#> 4 2019 4 D-001 4.749738 2.054544 0.3550630 0.3821190 1.2910567
#> 5 2019 5 D-001 4.396303 2.105568 0.2370389 0.3274173 1.3266714
#> 6 2019 6 D-001 5.838083 1.931209 0.2070870 0.5313604 1.3973229
#> 7 2019 7 D-001 5.194401 2.164595 0.3276313 0.3039208 1.1665574
#> 8 2019 8 D-001 3.346228 2.259220 0.2472752 0.2890792 1.2809236
#> 9 2019 9 D-001 4.748794 1.974068 0.1277325 0.6515675 1.1685260
#> 10 2019 10 D-001 6.461638 1.708387 0.1556450 0.2632500 1.3609233
#> 11 2019 11 D-001 4.240126 1.692041 0.2045273 0.3768561 1.0848231
#> 12 2019 12 D-001 4.010090 2.204548 0.1839178 0.4708175 1.6361168
#> 13 2019 1 R-001 3.698012 2.310801 0.2337734 0.3704153 1.6188011
#> 14 2019 2 R-001 3.180484 1.840923 0.2520314 0.1775579 1.8374191
#> 15 2019 3 R-001 2.761142 2.143444 0.1868349 0.3195870 1.6904981
#> 16 2019 4 R-001 5.189126 2.118240 0.2528620 0.5491718 1.4536160
#> 17 2019 5 R-001 4.454835 1.455411 0.2666154 0.3321027 1.7107790
#> 18 2019 6 R-001 6.892169 2.038263 0.3230197 0.3735168 1.2470248
#> 19 2019 7 R-001 4.239362 1.645825 0.2404983 0.3679821 1.0699091
#> 20 2019 8 R-001 6.473536 2.181010 0.2483830 0.3191815 1.2001535
#> 21 2019 9 R-001 4.167933 2.063323 0.1998192 0.3823141 1.7882855
#> 22 2019 10 R-001 3.516200 1.992785 0.2163667 0.4136695 1.2712782
#> 23 2019 11 R-001 5.407001 2.210327 0.2491462 0.3610934 1.4497958
#> 24 2019 12 R-001 5.236846 1.895703 0.1697065 0.4747824 1.8571717