Skip to contents

Durov Diagram

Source: R/plotting.R
durov_plot.Rd

Creates a Durov diagram for interpretation of hydrochemical facies, mixing processes, ion exchange, and geochemical evolution.

Usage

durov_plot(df, ...)

# S3 method for class 'data.frame'
durov_plot(df, location, analyte, result, unit, date, ...)

# S3 method for class 'env_schema'
durov_plot(
  df,
  analyte_matching = c("normalized", "strict", "exact"),
  title = NULL
)

Arguments

df

A data frame or `env_schema` object.

...

Additional arguments passed to methods.

location

Location identifier column.

analyte

Analyte column.

result

Analytical result column.

unit

Reporting unit column.

date

Sample date column.

analyte_matching

Analyte matching strategy. One of `"exact"`, `"strict"`, or `"normalized"`.

title

Optional plot title.

Value

A ggplot object.

Details

`durov_plot()` is an S3 generic that supports both raw data frames and `env_schema` objects.

For data frames, environmental column mappings must be supplied. For `env_schema` objects, mapped schema fields are used automatically.

For data frames, `durov_plot()` first converts the supplied data to an `env_schema` object using the specified column mappings and then dispatches to [durov_plot.env_schema()].

Durov diagrams combine cation and anion ternary plots with a central projection field to aid interpretation of hydrochemical facies, mixing trends, ion exchange processes, and geochemical evolution.

Major-ion concentrations are converted to milliequivalents per liter (meq/L), normalized to ionic percentages, and transformed into Durov coordinates before plotting.

The central Durov field may be used to evaluate:

  • groundwater recharge processes;

  • mixing between water types;

  • ion exchange reactions;

  • salinization trends;

  • hydrochemical evolution.

For `env_schema` objects, analyte, result, unit, date, and location fields are obtained directly from schema mappings.

Analyte Matching

exact

Uses analyte names exactly as reported.

strict

Applies text normalization while preserving analytical distinctions such as dissolved versus total fractions.

normalized

Resolves analyte aliases to canonical analyte names using package analyte metadata.

Interpretation

The Durov projection field is divided into nine regions representing characteristic hydrochemical facies and geochemical processes.

These fields should be interpreted as general hydrochemical indicators and evaluated alongside site-specific geological, hydrological, and geochemical information.

Validation

Input data are validated for:

  • major-ion chemistry availability;

  • analyte resolution;

  • supported analytical units;

  • successful conversion to milliequivalents;

  • completeness of major-ion chemistry.

Examples

data(gw)

durov_plot(gw)
#> Error in tibble::tibble(source_analyte = source_analyte, alias = normalized) %>%     dplyr::left_join(alias_lookup, by = "alias", relationship = "many-to-one") %>%     dplyr::mutate(fraction = dplyr::coalesce(fraction, .extract_fraction(source_analyte))) %>%     dplyr::transmute(source_analyte, normalized_input = normalized,         is_known_analyte = !is.na(analyte_id), analyte_id = dplyr::coalesce(analyte_id,             normalized), analyte = dplyr::coalesce(analyte, source_analyte),         normalized_analyte = dplyr::coalesce(normalized_analyte,             analyte_id, normalized), fraction): could not find function "%>%"

durov_plot(
  gw,
  analyte_matching = "normalized"
)
#> Error in tibble::tibble(source_analyte = source_analyte, alias = normalized) %>%     dplyr::left_join(alias_lookup, by = "alias", relationship = "many-to-one") %>%     dplyr::mutate(fraction = dplyr::coalesce(fraction, .extract_fraction(source_analyte))) %>%     dplyr::transmute(source_analyte, normalized_input = normalized,         is_known_analyte = !is.na(analyte_id), analyte_id = dplyr::coalesce(analyte_id,             normalized), analyte = dplyr::coalesce(analyte, source_analyte),         normalized_analyte = dplyr::coalesce(normalized_analyte,             analyte_id, normalized), fraction): could not find function "%>%"

durov_plot(
  gw,
  title = "Hydrochemical Facies"
)
#> Error in tibble::tibble(source_analyte = source_analyte, alias = normalized) %>%     dplyr::left_join(alias_lookup, by = "alias", relationship = "many-to-one") %>%     dplyr::mutate(fraction = dplyr::coalesce(fraction, .extract_fraction(source_analyte))) %>%     dplyr::transmute(source_analyte, normalized_input = normalized,         is_known_analyte = !is.na(analyte_id), analyte_id = dplyr::coalesce(analyte_id,             normalized), analyte = dplyr::coalesce(analyte, source_analyte),         normalized_analyte = dplyr::coalesce(normalized_analyte,             analyte_id, normalized), fraction): could not find function "%>%"