This function applies the Nutrient Aggregation logic from ECHO's Water Pollutant Loading Tool to add nitrogen subspecies together to approximate a total nitrogen value on a single day at a single site. Additional rows are added with the total nitrogen and total phosphorous estimations. Before summing subspecies, this function runs TADA_AggregateMeasurements to obtain the max value of a characteristic-fraction-speciation-unit-media combination at a given site and date. Where necessary, it uses conversion factors to convert nitrogen subspecies expressed as nitrate, nitrite, ammonia, ammonium, etc. to as nitrogen based on the atomic weights of the different elements in the compound. Similarly, phosphate and other phosphorus forms are converted to AS P where applicable. The reference table is contained within the package but may be edited/customized by users.
Usage
TADA_CalculateTotalNP(.data, sum_ref, daily_agg = c("max", "min", "mean"))Arguments
- .data
TADA dataframe. TADA_AutoClean() must have been run (and the TADA.ResultMeasureValueDataTypes.Flag added) before this TM/TP summation function can be used. This function runs required flag functions (TADA_FindQCActivities, TADA_FlagResultUnit, TADA_FlagFraction, TADA_FlagSpeciation) if they have not yet been run. Suspect and invalid combinations are not included in TN and TP summation. While not required for this function to run, ideally, users should also run TADA_SimpleCensoredMethods and TADA_HarmonizeSynonyms before this function. If user wants to consider grouping N or P subspecies across multiple organizations, user should have also run TADA_FindNearbySites and grouped all nearby sites to one common TADA.MonitoringLocationIdentifier, TADA.LatitudeMeasure, TADA.LongitudeMeasure, etc.
- sum_ref
Optional. A custom summation reference dataframe the user has loaded into the R environment. Dataframe must have same columns as default TADA.summation reference table.
- daily_agg
If there are multiple measurements for the same characteristic-unit-fraction-speciation-media combination at the same location (TADA.MonitoringLocationIdentifier) on the same day (ActivityStartDate), this will select a single measurement to use in the Total N or Total P summation. Defaults to 'max', but can be set to 'min' or 'mean'.
Value
TADA dataframe with additional rows representing total N and P summation values from adding up subspecies. Note that for total phosphorus, these additional rows are simply a re-classification of phosphorus or phosphate into the total phosphorus as P format. These new rows share the same date and monitoring location as the subspecies, but an additional note is added in the TADA.NutrientSummation.Flag column describing how the total was derived. Also adds TADA.NutrientSummationGroup and TADA.NutrientSummationEquation columns, which can be used to trace how the total was calculated and from which subspecies.
Details
Nutrient equations are as follows:
NITROGEN:
TOTAL N (UNFILTERED)
TOTAL N (FILTERED) + TOTAL N (PARTICULATE)
TOTAL KJELDAHL NITROGEN + NITRATE + NITRITE
ORGANIC N + AMMONIA + NITRATE + NITRITE
OTHER NITROGEN FORMS
PHOSPHORUS:
TOTAL PHOSPHORUS
PHOSPHATE
OTHER PHOSPHORUS FORMS
Equations are applied in the order above. The function looks for groups of nutrients that exactly match each equation before looking for every combination within each equation (for example, a group of nitrogen subspecies including AMMONIA and NITRATE will be passed over in an initial sweep of groups of subspecies containing ORGANIC N, AMMONIA, NITRATE, and NITRITE, but will be caught as the function moves down the hierarchy of equations to fewer and fewer subspecies). Eventually, even groups with only one subspecies will be used to represent a TOTAL N value for that site/day/depth.
Examples
df <- TADA_DataRetrieval(statecode = "UT", startDate = "2024-06-01",
endDate = "2024-07-01", characteristicType = "Nutrient", applyautoclean = TRUE,
ask = FALSE)
#> Checking what data is available. This may take a moment.
#> The number of sites and/or records matched by the query terms is large, so the download may take some time.
#> [1] "Downloading data from sites with fewer than 350000 results by grouping them together."
#>
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|===================================================== | 76%
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|======================================================================| 100%
#> [1] "Data successfully downloaded. Running TADA_AutoClean function."
#> [1] "TADA_Autoclean: creating TADA-specific columns."
#> [1] "TADA_Autoclean: handling special characters and coverting TADA.ResultMeasureValue and TADA.DetectionQuantitationLimitMeasure.MeasureValue value fields to numeric."
#> [1] "TADA_Autoclean: converting TADA.LatitudeMeasure and TADA.LongitudeMeasure fields to numeric."
#> [1] "TADA_Autoclean: harmonizing synonymous unit names (m and meters) to m."
#> [1] "TADA_Autoclean: updating deprecated (i.e. retired) characteristic names."
#> [1] "No deprecated characteristic names found in dataset."
#> [1] "TADA_Autoclean: harmonizing result and depth units."
#> [1] "TADA_Autoclean: creating TADA.ComparableDataIdentifier field for use when generating visualizations and analyses."
#> [1] "NOTE: This version of the TADA package is designed to work with numeric data with media name: 'WATER'. TADA_AutoClean does not currently remove (filter) data with non-water media types. If desired, the user must make this specification on their own outside of package functions. Example: dplyr::filter(.data, TADA.ActivityMediaName == 'WATER')"
df2 <- TADA_SimpleCensoredMethods(df, nd_method = "multiplier",
nd_multiplier = 0.5, od_method = "as-is", od_multiplier = "null")
#> [1] "TADA_IDCensoredData: There are 2 results in your dataframe that are missing ResultDetectionConditionText. TADA requires BOTH ResultDetectionConditionText and DetectionQuantitationLimitTypeName fields to be populated in order to categorize censored data."
df2 <- TADA_RunKeyFlagFunctions(df2, clean = TRUE)
#> [1] "TADA_FlagResultUnit: All characteristic/unit combinations are valid in your dataframe. Returning input dataframe with TADA.ResultUnit.Flag column for tracking."
#> [1] "TADA_FindQCActivities: Quality control samples have been removed or were not present in the input dataframe. Returning dataframe with TADA.ActivityType.Flag column for tracking."
df2 <- TADA_HarmonizeSynonyms(df2)
df3 <- TADA_CalculateTotalNP(df2, daily_agg = "max")
#> [1] "Aggregation results:"
#>
#> Considered in max aggregation function but not selected
#> 461
#> No aggregation needed
#> 1413
#> Selected as max aggregate value
#> 313