Synthetic leachate-impacted water-quality data (demo)

Returns a small, fictional long-format water-quality dataset used in the examples and vignettes. It is not real monitoring data — concentrations are generated from a simple two-component mixing model so the worked examples are reproducible and self-contained.

Usage

leachate_demo()

Value

A tibble with one row per sample x analyte and the columns:

sample_id: Character. Unique sample identifier.
site_id: Character. One of "downstream", "reference", "leachate".
datetime: Date. Sampling date.
analyte: Character. Analyte name.
value: Numeric. Concentration in units.analyte.
detected: Logical. FALSE marks a below-detection-limit result.
units.analyte: Character. Concentration units: major ions in "mg/L"; Cu/Zn/NH3-N in "ug/L" (the SSD scale); pH unitless; temperature in "degC"; hardness in "mg/L CaCO3".
valence.analyte: Numeric. Ionic charge (for the meq conversion in to_meq()); NA for non-ionic analytes.
atomic_mass.analyte: Numeric. Molar/atomic mass in g/mol (for the meq conversion); NA for non-ionic analytes.

Details

The data are bundled in the qs2 qdata format under inst/extdata (qs2 is already a dependency) and read on demand by this accessor, rather than being lazy-loaded R data.

Three sites are included:

downstream: A leachate-impacted site, ~15% leachate mixing fraction relative to the reference.
reference: Clean background / upstream chemistry.
leachate: The leachate end-member.

Each site has six bi-monthly samples through 2024. The analyte panel carries the major ions used by add_lmf() / to_meq() (Na, K, Ca, Mg, Cl, sulfate, F, NO3-N, NO2-N, CO3-CaCO3, HCO3-CaCO3), the toxicants assessed by ssd_paf() / add_mspaf() (Cu, Zn, NH3-N), and the co-analytes needed for the ammonia and bioavailability normalisations (pH, temperature, DOC, hardness).

Examples

demo <- leachate_demo()
table(demo$site_id, demo$analyte == "Cu")
#>             
#>              FALSE TRUE
#>   downstream   102    6
#>   leachate     102    6
#>   reference    102    6
head(subset(demo, site_id == "downstream"), 4)
#> # A tibble: 4 × 9
#>   sample_id site_id    datetime   analyte value detected units.analyte
#>   <chr>     <chr>      <date>     <chr>   <dbl> <lgl>    <chr>        
#> 1 DS-01     downstream 2024-01-15 Na      149.  TRUE     mg/L         
#> 2 DS-01     downstream 2024-01-15 K        30.0 TRUE     mg/L         
#> 3 DS-01     downstream 2024-01-15 Ca       75.5 TRUE     mg/L         
#> 4 DS-01     downstream 2024-01-15 Mg       25.9 TRUE     mg/L         
#> # ℹ 2 more variables: valence.analyte <dbl>, atomic_mass.analyte <dbl>