Install R package
# Enable repository from kwb-r
options(repos = c(
kwbr = 'https://kwb-r.r-universe.dev',
CRAN = 'https://cloud.r-project.org'))
# Download and install kwb.swmm in R
install.packages('kwb.swmm')Download SWMM Executable
library(kwb.swmm)
#> SWMM executable not found.
swmm_exe <- kwb.swmm::download_swmm_executable(tdir = getwd(),
swmm_version = "5.2.0")
#> Downloading and extracting SWMM folder to 'D:/a/kwb.swmm/kwb.swmm/vignettes' ... ok. (0.57 secs)Define Paths
paths_list <- list(
model_dir = kwb.swmm::extdata_file("models/lid"),
model_name = "zone-1_bioretention-cell_lidshare-1.00",
model_inp = "<model_dir>/<model_name>.inp",
model_out = "<model_dir>/<model_name>.out",
model_rpt = "<model_dir>/<model_name>.rpt",
swmm_exe = swmm_exe
)
paths <- kwb.utils::resolve(paths_list)Read Input
inp <- swmmr::read_inp(paths$model_inp)
## print some inputs
inp$options
#> # A tibble: 34 × 2
#> Option Value
#> <chr> <chr>
#> 1 FLOW_UNITS LPS
#> 2 INFILTRATION HORTON
#> 3 FLOW_ROUTING KINWAVE
#> 4 LINK_OFFSETS DEPTH
#> 5 MIN_SLOPE 0
#> 6 ALLOW_PONDING NO
#> 7 SKIP_STEADY_STATE NO
#> 8 IGNORE_SNOWMELT YES
#> 9 START_DATE 04/30/2008
#> 10 START_TIME 00:00:00
#> # ℹ 24 more rows
inp$lid_controls
#> # A tibble: 3 × 9
#> Name `Type/Layer` Par1 Par2 Par3 Par4 Par5 Par6 Par7
#> <chr> <chr> <int> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 bioretention_cell.… BC NA NA NA NA NA NA NA
#> 2 bioretention_cell.… SURFACE 300 0.05 0.3 4 5 NA NA
#> 3 bioretention_cell.… SOIL 500 0.437 0.105 0.047 3.6 0.5 0.047
inp$lid_usage
#> # A tibble: 1 × 10
#> Subcatchment `LID Process` Number Area Width InitSat FromImp ToPerv RptFile
#> <chr> <chr> <int> <int> <int> <int> <int> <int> <chr>
#> 1 S1 bioretention_c… 1 1000 6 0 0 0 *
#> # ℹ 1 more variable: DrainTo <chr>Run SWMM
kwb.swmm::run_swmm(model_dir = paths$model_dir,
model_inp = paths$model_inp,
exe = paths$swmm_exe)Read Output
results <- kwb.swmm::get_results(path_out = paths$model_out)
#> File D:/a/_temp/Library/kwb.swmm/extdata/models/lid/zone-1_bioretention-cell_lidshare-1.00.out opened.
#> InputStartPos: 42
#> OutputStartPos: 270
#> SWMM_Nperiods: 100463
#> errCode: 0
#> magic2: 516114522
#> 1 subcatchments read.
#> 1 nodes read.
#> 0 links read.
#> 0 pollutants read.
#> n_variables[SUBCATCH]: 8
#> n_variables[NODE]: 6
#> n_variables[LINK]: 5
#> n_variables[SYS]: 15
#> SWMM_StartDate: 39568.000000
#> SWMM_ReportStep: 3600
#> File D:/a/_temp/Library/kwb.swmm/extdata/models/lid/zone-1_bioretention-cell_lidshare-1.00.out opened.
#> InputStartPos: 42
#> OutputStartPos: 270
#> SWMM_Nperiods: 100463
#> errCode: 0
#> magic2: 516114522
#> 1 subcatchments read.
#> 1 nodes read.
#> 0 links read.
#> 0 pollutants read.
#> n_variables[SUBCATCH]: 8
#> n_variables[NODE]: 6
#> n_variables[LINK]: 5
#> n_variables[SYS]: 15
#> SWMM_StartDate: 39568.000000
#> SWMM_ReportStep: 3600
#> File D:/a/_temp/Library/kwb.swmm/extdata/models/lid/zone-1_bioretention-cell_lidshare-1.00.out opened.
#> InputStartPos: 42
#> OutputStartPos: 270
#> SWMM_Nperiods: 100463
#> errCode: 0
#> magic2: 516114522
#> 1 subcatchments read.
#> 1 nodes read.
#> 0 links read.
#> 0 pollutants read.
#> n_variables[SUBCATCH]: 8
#> n_variables[NODE]: 6
#> n_variables[LINK]: 5
#> n_variables[SYS]: 15
#> SWMM_StartDate: 39568.000000
#> SWMM_ReportStep: 3600
#> Reading time series 1/14 ... ok.
#> Reading time series 2/14 ... ok.
#> Reading time series 3/14 ... ok.
#> Reading time series 4/14 ... ok.
#> Reading time series 5/14 ... ok.
#> Reading time series 6/14 ... ok.
#> Reading time series 7/14 ... ok.
#> Reading time series 8/14 ... ok.
#> Reading time series 9/14 ... ok.
#> Reading time series 10/14 ... ok.
#> Reading time series 11/14 ... ok.
#> Reading time series 12/14 ... ok.
#> Reading time series 13/14 ... ok.
#> Reading time series 14/14 ... ok.
results
#> # A tibble: 100,463 × 15
#> datetime total_rainfall total_snow_depth average_losses
#> <dttm> <dbl> <dbl> <dbl>
#> 1 2008-04-30 01:00:00 0 0 0
#> 2 2008-04-30 02:00:00 0 0 0
#> 3 2008-04-30 03:00:00 0 0 0
#> 4 2008-04-30 04:00:00 0 0 0
#> 5 2008-04-30 05:00:00 0 0 0
#> 6 2008-04-30 06:00:00 0 0 0
#> 7 2008-04-30 07:00:00 0.789 0 0
#> 8 2008-04-30 08:00:00 0 0 0
#> 9 2008-04-30 09:00:00 0 0 0
#> 10 2008-04-30 10:00:00 0 0 0
#> # ℹ 100,453 more rows
#> # ℹ 11 more variables: total_runoff <dbl>, total_dry_weather_inflow <dbl>,
#> # total_groundwater_inflow <dbl>, total_RDII_inflow <dbl>,
#> # total_external_inflow <dbl>, total_direct_inflow <dbl>,
#> # total_external_flooding <dbl>, total_outflow_from_outfalls <dbl>,
#> # total_nodal_storage_volume <dbl>, potential_evaporation <dbl>,
#> # actual_evaporation <dbl>Calculate Rainstats
results_system <- kwb.swmm::get_results(path_out = paths$model_out,
vIndex = c(1, 4)) %>%
dplyr::rename(
total_rainfall_mmPerHour = .data$total_rainfall,
total_runoff_litrePerSecond = .data$total_runoff
) %>%
dplyr::mutate(total_runoff_mmPerHour = kwb.swmm::lps_to_mmPerHour(.data$total_runoff_litrePerSecond)) %>%
dplyr::select(-.data$total_runoff_litrePerSecond)
#> File D:/a/_temp/Library/kwb.swmm/extdata/models/lid/zone-1_bioretention-cell_lidshare-1.00.out opened.
#> InputStartPos: 42
#> OutputStartPos: 270
#> SWMM_Nperiods: 100463
#> errCode: 0
#> magic2: 516114522
#> 1 subcatchments read.
#> 1 nodes read.
#> 0 links read.
#> 0 pollutants read.
#> n_variables[SUBCATCH]: 8
#> n_variables[NODE]: 6
#> n_variables[LINK]: 5
#> n_variables[SYS]: 15
#> SWMM_StartDate: 39568.000000
#> SWMM_ReportStep: 3600
#> File D:/a/_temp/Library/kwb.swmm/extdata/models/lid/zone-1_bioretention-cell_lidshare-1.00.out opened.
#> InputStartPos: 42
#> OutputStartPos: 270
#> SWMM_Nperiods: 100463
#> errCode: 0
#> magic2: 516114522
#> 1 subcatchments read.
#> 1 nodes read.
#> 0 links read.
#> 0 pollutants read.
#> n_variables[SUBCATCH]: 8
#> n_variables[NODE]: 6
#> n_variables[LINK]: 5
#> n_variables[SYS]: 15
#> SWMM_StartDate: 39568.000000
#> SWMM_ReportStep: 3600
#> File D:/a/_temp/Library/kwb.swmm/extdata/models/lid/zone-1_bioretention-cell_lidshare-1.00.out opened.
#> InputStartPos: 42
#> OutputStartPos: 270
#> SWMM_Nperiods: 100463
#> errCode: 0
#> magic2: 516114522
#> 1 subcatchments read.
#> 1 nodes read.
#> 0 links read.
#> 0 pollutants read.
#> n_variables[SUBCATCH]: 8
#> n_variables[NODE]: 6
#> n_variables[LINK]: 5
#> n_variables[SYS]: 15
#> SWMM_StartDate: 39568.000000
#> SWMM_ReportStep: 3600
#> Reading time series 1/2 ... ok.
#> Reading time series 2/2 ... ok.
#> Warning: Use of .data in tidyselect expressions was deprecated in tidyselect 1.2.0.
#> ℹ Please use `"total_rainfall"` instead of `.data$total_rainfall`
#> This warning is displayed once every 8 hours.
#> Call `lifecycle::last_lifecycle_warnings()` to see where this warning was
#> generated.
#> Warning: Use of .data in tidyselect expressions was deprecated in tidyselect 1.2.0.
#> ℹ Please use `"total_runoff"` instead of `.data$total_runoff`
#> This warning is displayed once every 8 hours.
#> Call `lifecycle::last_lifecycle_warnings()` to see where this warning was
#> generated.
#> Warning: Use of .data in tidyselect expressions was deprecated in tidyselect 1.2.0.
#> ℹ Please use `"total_runoff_litrePerSecond"` instead of
#> `.data$total_runoff_litrePerSecond`
#> This warning is displayed once every 8 hours.
#> Call `lifecycle::last_lifecycle_warnings()` to see where this warning was
#> generated.
results_system
#> # A tibble: 100,463 × 3
#> datetime total_rainfall_mmPerHour total_runoff_mmPerHour
#> <dttm> <dbl> <dbl>
#> 1 2008-04-30 01:00:00 0 0
#> 2 2008-04-30 02:00:00 0 0
#> 3 2008-04-30 03:00:00 0 0
#> 4 2008-04-30 04:00:00 0 0
#> 5 2008-04-30 05:00:00 0 0
#> 6 2008-04-30 06:00:00 0 0
#> 7 2008-04-30 07:00:00 0.789 0
#> 8 2008-04-30 08:00:00 0 0
#> 9 2008-04-30 09:00:00 0 0
#> 10 2008-04-30 10:00:00 0 0
#> # ℹ 100,453 more rows
results_vrr <- results_system %>%
dplyr::mutate(year = lubridate::year(.data$datetime)) %>%
dplyr::group_by(.data$year) %>%
dplyr::summarise(vrr = 1 - (
sum(.data$total_runoff_mmPerHour) / sum(.data$total_rainfall_mmPerHour)
))
results_vrr
#> # A tibble: 12 × 2
#> year vrr
#> <dbl> <dbl>
#> 1 2008 1
#> 2 2009 1
#> 3 2010 1
#> 4 2011 1
#> 5 2012 1
#> 6 2013 1
#> 7 2014 1
#> 8 2015 1
#> 9 2016 1
#> 10 2017 1
#> 11 2018 1
#> 12 2019 1
col_eventsep <- "total_rainfall_mmPerHour"
rainevent_stats_mean <-
kwb.swmm::calculate_rainevent_stats(results_system,
col_eventsep = col_eventsep,
aggregation_function = "mean") %>%
dplyr::mutate(
rainfall_cbm = .data$dur * .data$mean_total_rainfall_mmPerHour / 3600 /
1000,
runoff_cbm = .data$dur * .data$mean_total_runoff_mmPerHour /
3600 / 1000,
vrr = 1 - runoff_cbm / rainfall_cbm
) %>%
dplyr::arrange(dplyr::desc(.data$mean_total_rainfall_mmPerHour))
#> Calculating `mean` event stats for parameter `total_rainfall_mmPerHour` ... ok. (3.18 secs)
#> Calculating `mean` event stats for parameter `total_runoff_mmPerHour` ... ok. (2.98 secs)
head(rainevent_stats_mean)
#> iBeg iEnd tBeg tEnd dur pBefore pAfter event
#> 1 5034 5034 2016-08-21 13:00:00 2016-08-21 13:00:00 3600 86400 162000 995
#> 2 3024 3035 2013-06-23 15:00:00 2013-06-24 04:00:00 50400 36000 25200 599
#> 3 5230 5238 2017-06-21 15:00:00 2017-06-21 23:00:00 32400 43200 259200 1046
#> 4 3224 3233 2013-08-06 14:00:00 2013-08-06 23:00:00 36000 280800 32400 642
#> 5 6062 6068 2019-08-07 15:00:00 2019-08-07 21:00:00 25200 68400 72000 1201
#> 6 5445 5447 2018-06-28 12:00:00 2018-06-28 14:00:00 10800 86400 72000 1092
#> mean_total_rainfall_mmPerHour mean_total_runoff_mmPerHour rainfall_cbm
#> 1 8.605081 0 0.008605081
#> 2 6.654423 0 0.093161928
#> 3 5.424497 0 0.048820477
#> 4 5.153533 0 0.051535330
#> 5 4.868611 0 0.034080276
#> 6 4.771171 0 0.014313512
#> runoff_cbm vrr
#> 1 0 1
#> 2 0 1
#> 3 0 1
#> 4 0 1
#> 5 0 1
#> 6 0 1
rainevent_stats_max <-
kwb.swmm::calculate_rainevent_stats(results_system,
col_eventsep = col_eventsep,
aggregation_function = "max") %>%
dplyr::arrange(dplyr::desc(.data$max_total_rainfall_mmPerHour))
#> Calculating `max` event stats for parameter `total_rainfall_mmPerHour` ... ok. (3.01 secs)
#> Calculating `max` event stats for parameter `total_runoff_mmPerHour` ... ok. (2.45 secs)
head(rainevent_stats_max)
#> iBeg iEnd tBeg tEnd dur pBefore pAfter event
#> 1 911 953 2009-07-26 12:00:00 2009-07-28 20:00:00 205200 61200 36000 193
#> 2 5230 5238 2017-06-21 15:00:00 2017-06-21 23:00:00 32400 43200 259200 1046
#> 3 3224 3233 2013-08-06 14:00:00 2013-08-06 23:00:00 36000 280800 32400 642
#> 4 3024 3035 2013-06-23 15:00:00 2013-06-24 04:00:00 50400 36000 25200 599
#> 5 2554 2559 2012-07-17 16:00:00 2012-07-17 21:00:00 21600 72000 21600 502
#> 6 5994 6002 2019-07-29 16:00:00 2019-07-30 03:00:00 43200 212400 43200 1192
#> max_total_rainfall_mmPerHour max_total_runoff_mmPerHour
#> 1 21.09241 0
#> 2 17.84431 0
#> 3 16.58891 0
#> 4 15.38480 0
#> 5 15.36419 0
#> 6 15.04827 0