This function is an addition to the swmmr package. The function inp_to_files is used to convert SWMM projects saved as .inp to several independent files. While geographical informations are stored in .shp files, informations of the sections options, report, raingages, evaporation, pollutants, landuses, buildup, washoff and coverages are stored in one .txt file named ‘options.txt’. Furthermore timeseries are converted to SWMM’s timeseries format and saved in .dat files.
The usage of swmmr’s function inp_to_files is explained with Example1 shipped with the SWMM executable:
# in case your operating system is Windows, the examples are saved in the following directory:
# "C:/Users/.../Documents/EPA SWMM Projects/Examples/"
# please change the path to:
# "C:/Users/.../Documents/EPA_SWMM_Projects/Examples/"
# substitute '...' with your user name# set path to inp
# If your operating system is Windows, the Example1.inp model is usually
# located at "C:\Users\your user name\Documents\EPA SWMM Projects\Examples".
# For convenience the Example1.inp model is also included in the swmmr package.
# Feel free to change this to your path of choice.
inp_file <- system.file("extdata", "Example1.inp", package = "swmmr", mustWork = TRUE)# set the path to the output directory for the example files (here, we use a temp directory)
# Feel free to change this to your path of choice.
out_dir <- tempdir()# read the "Example1.inp" using read_inp
Example1 <- read_inp(x = inp_file)
# glance the structure of Example1
summary(Example1)##
## ** summary of swmm model structure **
## infiltration : horton
## flow_units : cfs
## flow_routing : kinwave
## start_date : 01/01/1998
## end_date : 01/02/1998
## raingages : 1
## subcatchments : 8
## aquifers : 0
## snowpacks : 0
## junctions : 13
## outfalls : 1
## dividers : 0
## storage : 0
## conduits : 13
## pumps : 0
## orifices : 0
## weirs : 0
## outlets : 0
## controls : 0
## pollutants : 2
## landuses : 2
## lid_controls : 0
## treatment : 0
## *************************************# convert .inp file into independent .shp and .txt files
inp_to_files(x = Example1, name = "Example1", path_out = out_dir)## Warning in abbreviate_shapefile_names(obj): Field names abbreviated for ESRI
## Shapefile driver## Writing layer `Example1_polygon' to data source
## `/tmp/RtmprqkDMA/shp/Example1_polygon.shp' using driver `ESRI Shapefile'
## Writing 8 features with 22 fields and geometry type Polygon.
## Writing layer `Example1_link' to data source
## `/tmp/RtmprqkDMA/shp/Example1_link.shp' using driver `ESRI Shapefile'
## Writing 13 features with 16 fields and geometry type Line String.
## Writing layer `Example1_point' to data source
## `/tmp/RtmprqkDMA/shp/Example1_point.shp' using driver `ESRI Shapefile'
## Writing 13 features with 6 fields and geometry type Point.
## Writing layer `Example1_outfall' to data source
## `/tmp/RtmprqkDMA/shp/Example1_outfall.shp' using driver `ESRI Shapefile'
## Writing 1 features with 6 fields and geometry type Point.## section weirs is missing## section orifices is missing## section pumps is missing## section storage is missing## *.shp files were written to /tmp/RtmprqkDMA/shp## *.txt file was written to /tmp/RtmprqkDMA/txt## section curves is missing## timeseries.dat files were written to /tmp/RtmprqkDMA/dat## [1] "dat" "shp" "txt"# check existence of shape, text and dat files:
c("shp", "txt", "dat") %>%
map( ~ file.path(out_dir, .)) %>%
map(list.files)## [[1]]
## [1] "Example1_link.dbf" "Example1_link.prj" "Example1_link.shp"
## [4] "Example1_link.shx" "Example1_outfall.dbf" "Example1_outfall.prj"
## [7] "Example1_outfall.shp" "Example1_outfall.shx" "Example1_point.dbf"
## [10] "Example1_point.prj" "Example1_point.shp" "Example1_point.shx"
## [13] "Example1_polygon.dbf" "Example1_polygon.prj" "Example1_polygon.shp"
## [16] "Example1_polygon.shx"
##
## [[2]]
## [1] "Example1_options.txt"
##
## [[3]]
## [1] "Example1_timeseries_TS1.dat"This is the counterpart to inp_to_files. Geographical informations stored in .shp files are converted to the input file format ‘.inp’ of SWMM using R. Informations on simulation settings, rain timeseries etc., stored in .txt or .dat files, complete these geographical informations.
Based on the converted files of Example1, the usage of swmmr’s function shp_to_inp is explained:
# convert shp and txt files to inp object:
Example1_con <- shp_to_inp(
path_options = file.path(out_dir,"txt/Example1_options.txt"),
path_timeseries = file.path(out_dir,"dat/Example1_timeseries_TS1.dat"),
path_polygon = file.path(out_dir,"shp/Example1_polygon.shp"),
path_line = file.path(out_dir,"shp/Example1_link.shp"),
path_point = file.path(out_dir,"shp/Example1_point.shp"),
path_outfall = file.path(out_dir,"shp/Example1_outfall.shp")
)## Warning: `as.tibble()` was deprecated in tibble 2.0.0.
## ℹ Please use `as_tibble()` instead.
## ℹ The signature and semantics have changed, see `?as_tibble`.
## ℹ The deprecated feature was likely used in the swmmr package.
## Please report the issue at <https://github.com/dleutnant/swmmr/issues>.
## This warning is displayed once every 8 hours.
## Call `lifecycle::last_lifecycle_warnings()` to see where this warning was
## generated.## Warning: `spread_()` was deprecated in tidyr 1.2.0.
## ℹ Please use `spread()` instead.
## ℹ The deprecated feature was likely used in the swmmr package.
## Please report the issue at <https://github.com/dleutnant/swmmr/issues>.
## This warning is displayed once every 8 hours.
## Call `lifecycle::last_lifecycle_warnings()` to see where this warning was
## generated.##
## ** summary of swmm model structure **
## infiltration : horton
## flow_units : cfs
## flow_routing : kinwave
## start_date : 01/01/1998
## end_date : 01/02/1998
## raingages : 1
## subcatchments : 8
## aquifers : 0
## snowpacks : 0
## junctions : 13
## outfalls : 1
## dividers : 0
## storage : 0
## conduits : 13
## pumps : 0
## orifices : 0
## weirs : 0
## outlets : 0
## controls : 0
## pollutants : 2
## landuses : 2
## lid_controls : 0
## treatment : 0
## *************************************# save the input file to a new folder in the output directory:
dir.create(file.path(out_dir, "inp_new"))
write_inp(Example1_con, file.path(out_dir, "inp_new", "Example1_con.inp"))Now simulation runs can be initiated…
There are three different ways to define the parameters of the different SWMM sections:
Here examples for the structure of supplementary R objects are given:
# ... assuming infiltration parameters are not given in the .shp file, an R object (tibble or data.frame) called infiltration can be added. Additionally a column 'Soil' must be added to polygon shp file.
infiltration <- tibble(
Soil = c("A", "B"), # or: unique(polygon$Soil)
MaxRate = c(76.2, 127),
MinRate = c(3.81, 7.62),
Decay = c(0.069, 0.069),
DryTime = c(1,1),
MaxInf = c(0,0)
)
# ... assuming not all subcatchment related parameters are given in the polygon .shp-file, an R object (tibble or data.frame) called subcatchment_typologies can be added. Additionally a column 'Type' must be added to the polygon .shp file.
subcatchment_typologies <- tibble(
Type = c("Street", "Park"), # or: unique(polygon$Type)
Perc_Imperv = c(100, 10),
Width = c(9, 30),
Slope = c(0.57, 1),
CurbLen = 0,
Snowpack = ' ',
Rain_Gage = "Test_rain",
N_Imperv = c(0.01, 0.025),
N_Perv = c(0.01, 0.2),
S_Imperv = c(1.5, 0.58),
S_Perv = c(1.5, 0.58),
Pct_Zero = 0,
PctRouted = 100
)
#...assuming roughness is not given in the line .shp file, an R object (tibble or data.frame) called conduit_material can be added. Additionally a column 'Material' must be added to the line .shp file
conduit_material <- tibble(
Material = "B", # or: unique(lines$Material)
Roughness = 0.018
)
#... assuming surcharge of junctions should be added later:
junction_parameters <- tibble(
Y = 0,
Ysur = 1,
Apond = 1
)The shp_to_inp function relies on the correct naming of the column names given in the .shp files: either you use the original swmm encoding (also given in swmmr::read_inp) or the swmm encoding abbreviated to seven characters (which is coerced when storing shp files, e.g. with sf::st_write).
In the moment, inp_to_files and shp_to_inp support the following SWMM inp sections:
The following sections are implemented with restrictions: