Compute construction costs for an infiltration-swale parameter grid

Given a parameter grid that drives the simulation, attach a per-scenario breakdown of construction costs plus a cost_total column suitable for filtering / sorting in the results datatable.

Usage

compute_costs(
  param_grid,
  storage_type = c("infiltration_box", "gravel_trench"),
  cost_rates = default_cost_rates()
)

Arguments

param_grid: data.frame / tibble — must contain the four geometry columns listed above. Other columns are passed through unchanged.
storage_type: character(1) — "infiltration_box" (default; ~95% porosity, the Austrian "Sickerbox") or "gravel_trench" (~30% porosity, the Austrian "Schotterrigol"). Only used when param_grid does not have a storage_type column.
cost_rates: list — unit costs as returned by default_cost_rates(). Override individual entries to run cost sensitivity analyses.

Value

The input param_grid with the columns storage_type, cost_excavation, cost_profiling, cost_filter, cost_storage, cost_total (all in EUR) appended.

Details

Required columns in param_grid:

mulde_area — element footprint area in m²
mulde_height — surface depression depth in mm
filter_height — soil-filter layer thickness in mm
storage_height — storage layer thickness in mm

Optional column storage_type (character: "infiltration_box" or "gravel_trench") selects the per-scenario storage rate. If absent, the value of the storage_type argument is used for every row.

Cost formulas (Leimgruber, 2026-03-27):


  cost_excavation = mulde_area * (mulde_h + filter_h + storage_h)/1000 * 70
  cost_profiling  = mulde_area * 10
  cost_filter     = mulde_area * filter_h/1000 * 200
  cost_storage    = mulde_area * storage_h/1000 * <350 | 50>
  cost_total      = sum of the four above

Examples

grid <- tibble::tibble(
  scenario_name = c("s00001", "s00002"),
  mulde_area = c(50, 50),
  mulde_height = c(300, 300),
  filter_height = c(300, 300),
  storage_height = c(600, 600)
)

# Infiltration box (default)
compute_costs(grid)
#> # A tibble: 2 × 11
#>   scenario_name mulde_area mulde_height filter_height storage_height
#>   <chr>              <dbl>        <dbl>         <dbl>          <dbl>
#> 1 s00001                50          300           300            600
#> 2 s00002                50          300           300            600
#> # ℹ 6 more variables: storage_type <chr>, cost_excavation <dbl>,
#> #   cost_profiling <dbl>, cost_filter <dbl>, cost_storage <dbl>,
#> #   cost_total <dbl>

# Gravel trench
compute_costs(grid, storage_type = "gravel_trench")
#> # A tibble: 2 × 11
#>   scenario_name mulde_area mulde_height filter_height storage_height
#>   <chr>              <dbl>        <dbl>         <dbl>          <dbl>
#> 1 s00001                50          300           300            600
#> 2 s00002                50          300           300            600
#> # ℹ 6 more variables: storage_type <chr>, cost_excavation <dbl>,
#> #   cost_profiling <dbl>, cost_filter <dbl>, cost_storage <dbl>,
#> #   cost_total <dbl>

# Per-scenario storage type
compute_costs(dplyr::mutate(grid,
                            storage_type = c("infiltration_box",
                                             "gravel_trench")))
#> # A tibble: 2 × 11
#>   scenario_name mulde_area mulde_height filter_height storage_height
#>   <chr>              <dbl>        <dbl>         <dbl>          <dbl>
#> 1 s00001                50          300           300            600
#> 2 s00002                50          300           300            600
#> # ℹ 6 more variables: storage_type <chr>, cost_excavation <dbl>,
#> #   cost_profiling <dbl>, cost_filter <dbl>, cost_storage <dbl>,
#> #   cost_total <dbl>