calculate_corrosion: Calculate six corrosion and scaling indices (AI, RI, LSI, LI,...

In tidywater: Water Quality Models for Drinking Water Treatment Processes

Calculate six corrosion and scaling indices (AI, RI, LSI, LI, CSMR, CCPP)

Description

This function takes an object created by define_water and calculates corrosion and scaling indices. For a single water, use calculate_corrosion; to apply the calculations to a dataframe, use calculate_corrosion_once.

Usage

calculate_corrosion(
  water,
  index = c("aggressive", "ryznar", "langelier", "ccpp", "larsonskold", "csmr"),
  form = "calcite"
)

calculate_corrosion_once(
  df,
  input_water = "defined_water",
  index = c("aggressive", "ryznar", "langelier", "ccpp", "larsonskold", "csmr"),
  form = "calcite"
)

Arguments

water	Source water of class "water" created by define_water
index	The indices to be calculated. Default calculates all six indices: "aggressive", "ryznar", "langelier", "ccpp", "larsonskold", "csmr" CCPP may not be able to be calculated sometimes, so it may be advantageous to leave this out of the function to avoid errors
form	Form of calcium carbonate mineral to use for modelling solubility: "calcite" (default), "aragonite", or "vaterite"
df	a data frame containing a water class column, created using define_water
input_water	name of the column of water class data to be used as the input. Default is "defined_water".

Details

Aggressiveness Index (AI), unitless - the corrosive tendency of water and its effect on asbestos cement pipe.

Ryznar Index (RI), unitless - a measure of scaling potential.

Langelier Saturation Index (LSI), unitless - describes the potential for calcium carbonate scale formation. Equations use empirical calcium carbonate solubilities from Plummer and Busenberg (1982) and Crittenden et al. (2012) rather than calculated from the concentrations of calcium and carbonate in the water.

Larson-skold Index (LI), unitless - describes the corrosivity towards mild steel.

Chloride-to-sulfate mass ratio (CSMR), mg Cl/mg SO4 - indicator of galvanic corrosion for lead solder pipe joints.

Calcium carbonate precipitation potential (CCPP), mg/L as CaCO3 - a prediction of the mass of calcium carbonate that will precipitate at equilibrium. A positive CCPP value indicates the amount of CaCO3 (mg/L as CaCO3) that will precipitate. A negative CCPP indicates how much CaCO3 can be dissolved in the water.

For large datasets, using fn_once or fn_chain may take many minutes to run. These types of functions use the furrr package for the option to use parallel processing and speed things up. To initialize parallel processing, use plan(multisession) or plan(multicore) (depending on your operating system) prior to your piped code with the fn_once or fn_chain functions. Note, parallel processing is best used when your code block takes more than a minute to run, shorter run times will not benefit from parallel processing.

Value

calculate_corrosion returns a data frame with corrosion and scaling indices as individual columns.

calculate_corrosion_once returns the a data frame containing specified corrosion and scaling indices as columns.

Source

AWWA (1977)

Crittenden et al. (2012)

Langelier (1936)

Larson and Skold (1958)

Merrill and Sanks (1977a)

Merrill and Sanks (1977b)

Merrill and Sanks (1978)

Nguyen et al. (2011)

Plummer and Busenberg (1982)

Ryznar (1944)

Schock (1984)

Trussell (1998)

U.S. EPA (1980)

See reference list at https://github.com/BrownandCaldwell-Public/tidywater/wiki/References

Examples

water <- define_water(
  ph = 8, temp = 25, alk = 200, tot_hard = 200,
  tds = 576, cl = 150, so4 = 200
)
corrosion_indices <- calculate_corrosion(water)

water <- define_water(ph = 8, temp = 25, alk = 100, tot_hard = 50, tds = 200)
corrosion_indices <- calculate_corrosion(water, index = c("aggressive", "ccpp"))


library(dplyr)

example_df <- water_df %>%
  slice_head(n = 2) %>% # used to make example run faster
  define_water_chain() %>%
  calculate_corrosion_once(index = c("aggressive", "ccpp"))

tidywater documentation built on Aug. 8, 2025, 7:15 p.m.