Overview
Tidywater incorporates published water chemistry and empirical models in a standard format. The modular functions allow for building custom, comprehensive drinking water treatment processes. Functions are designed to work in a tidyverse workflow.
Installation
# Install tidywater from CRAN:
install.packages("tidywater")
# Alternatively, install the development version from GitHub:
# install.packages("devtools")
devtools::install_github("BrownandCaldwell-Public/tidywater")Examples
In this first example, acid-base chemistry and TOC removal models are demonstrated. This example uses tidywater base functions to model a single water quality scenario.
library(tidywater)
library(tidyverse)
## Use base tidywater functions to model water quality for a single scenario.
base_coagulation <- define_water(ph = 8, alk = 90, tds = 50, toc = 3, doc = 2.8, uv254 = 0.08) %>%
# note that we get a warning about sulfate from this code because we didn't specify sulfate in the define_water
chemdose_ph(alum = 30) %>%
chemdose_toc(alum = 30)
#> Warning in chemdose_ph(., alum = 30): Sulfate-containing chemical dosed, but
#> so4 water slot is NA. Slot not updated because background so4 unknown.To model multiple water quality scenarios, use tidywater’s helper functions (x_df) to apply the models to a dataframe. The pluck_cols argument can be added to return the parameters impacted by the model as separate columns. The pluck_water function can pull any parameter from a water into a separate column.
coagulation <- water_df %>%
define_water_df(output_water = "raw") %>%
mutate(alum = 30) %>%
chemdose_ph_df(input_water = "raw", output_water = "phchange") %>% # return "phchange" water
chemdose_toc_df(input_water = "phchange", output_water = "coag", pluck_cols = TRUE) # return "coag" water and coag_doc, coag_toc, coag_uv254 as columns
## To get individual parameters, use `pluck_water`
coagulation <- coagulation %>%
pluck_water(input_waters = c("raw", "coag"), parameter = c("ph", "doc"))Note that these functions use a “water” class. The “water” class is the foundation of the package; it provides a mechanism for linking models in any order while maintaining water quality information. The define_water function takes water quality inputs, but define_water_df may be used to convert a dataframe to a list of “waters”.
For more detailed examples on tidywater functions and how to use “water” class data, please see the tidywater vignettes: browseVignettes("tidywater")