The R package is used to define a tolerable pollutant input into small surface waters via rainwater runoff. It assigns a maximal connectable urban area to the surface water. For planning areas, different scenarios regarding the connection of surfaces to the separate sewer system and runoff water treatment can be calculated.
For details on how to install KWB-R packages checkout our installation tutorial.
### Optionally: specify GitHub Personal Access Token (GITHUB_PAT)
### See here why this might be important for you:
### https://kwb-r.github.io/kwb.pkgbuild/articles/install.html#set-your-github_pat
# Sys.setenv(GITHUB_PAT = "mysecret_access_token")
# Install package "remotes" from CRAN
if (! require("remotes")) {
install.packages("remotes", repos = "https://cloud.r-project.org")
}
# Install KWB package 'r2q' from GitHub
remotes::install_github("KWB-R/r2q")Example for using the Excel input mask
path <- file.path(system.file(package = "r2q"), "extdata", "Example")
fileName <- "Herne_Baukau.xlsx"
# checkout the example excel file (only works on windows with excel installed)
shell.exec(file.path(path, fileName))
# load Example -----------------------------------------------------------
siteData <- r2q::load_site_data(
data.dir = path,
filename = fileName
)
c_river <- r2q::load_background_data(
data.dir = path,
filename = fileName,
default_for_na = TRUE
)
# load package data ---------------------------------------------------------
c_storm <- r2q::get_stormwaterRunoff(
runoff_effective_mix = list(
siteData$landuse$Mix_flow_connected[c(2,1,3,4)],
siteData$landuse$Mix_flow_connectable[c(2,1,3,4)]),
mix_names = c("is", "pot"))
c_threshold <- r2q::get_thresholds(LAWA_type = siteData$LAWA_type$Value)
# yearly rain event
rain <- r2q::get_rain(
area_catch = siteData$area_catch$Value,
river_cross_section = siteData$river_cross_section$Value,
river_length = siteData$river_length$Value,
river_mean_flow = siteData$Q_mean$Value,
x_coordinate = siteData$x_coordinate$Value,
y_coordinate = siteData$y_coordinate$Value
)
# combine data ---------------------------------------------------------
c_table <- r2q::combine_concentration_tables(
threshold_table = c_threshold,
storm_table = c_storm,
background_table = c_river
)
# process -----------------------------------------------------------------
r2q_h <- r2q::hydrology_assessment(site_data = siteData, q_rain = rain[2])
c_type <- "average" # --> median or "worstcase" -> 95th Quantile
# which substance poses a high risk?
checked <- r2q::check_all_substances(
c_table = c_table,
c_type = c_type)
# Assessment of one substance
r2q::immission_assessment(
site_data = siteData,
c_table = c_table,
q_rain = rain[2],
t_rain = rain[1] * 60, substance = "Zink_geloest",
hazard_list = checked)
# Assessment of all substances of potentially high risk
r2q_out <- r2q::assess_all_hazards(
hazard_list = checked,
site_data = siteData,
c_table = c_table,
q_rain = rain[2], t_rain = rain[1] * 60,
c_type = c_type)
# plot the results
r2q::plot_hazards(hazards = checked) # substances that might pose a high risk
r2q::plot_connectable_urban_area(
r2q_substance = r2q_out,
r2q_hydrology = r2q_h,
site_data = siteData,
x_type = "percent",
language = "de"
)
# detailed planning (excel sheet: "planning_area_details") ------------------
planningData <- r2q::load_planning_details(
data.dir = path,
filename = fileName,
scenario_name = "planning_area_details" # excel sheet name of planning details
)
pl_out <- r2q::planning_area_discharge(
planning_data = planningData,
q_rain = rain[2],
t_rain = rain[1] * 60,
y_rain = siteData$rain_year$Value,
thresholdTable = c_threshold)
# comparison with tolerable discharge
isPlan <- data.frame(
"loadPlan_is" = pl_out$sum)
isPlan$substance <- rownames(isPlan)
df_compare <- merge(
x = isPlan,
y = as.data.frame(lapply(r2q_out$general, unlist)),
by = "substance",
all.y = TRUE)
df_compareRelease: https://kwb-r.github.io/r2q
Development: https://kwb-r.github.io/r2q/dev
Release: https://kwb-r.github.io/r2q
Development: https://kwb-r.github.io/r2q/dev