Review and Apply Any Site-specific Criteria to Monitoring Location Sites or Assessment Units

This function will pull in all unique MonitoringLocationName, MonitoringLocationType, and MonitoringLocationIdentifier from the TADA dataframe and join it to TADA_CreateUseParamRef. Users are not required to provide a crosswalk between WQP Monitoring locations and Assessment units if they are only interested in summarizing assessments on a monitoring location level.

Usage

TADA_CreateMLSummaryRef(
  .data,
  org_id = NULL,
  useParamRef = NULL,
  displayNA = FALSE,
  AUMLRef = NULL,
  useAURef = NULL,
  MLSummaryRef = NULL,
  excel = FALSE,
  overwrite = FALSE
)

Arguments

.data

A TADA dataframe. The user should run all desired data cleaning, processing, harmonization, filtering, and handling of censored data functions prior to running this function.

org_id

The ATTAINS organization identifier must be supplied by the user. A list of organization identifiers can be found by downloading the ATTAINS Domains Excel file: https://www.epa.gov/system/files/other-files/2025-02/domains_2025-02-25.xlsx. organization identifiers are listed in the "OrgName" tab. The "code" column contains the organization identifiers that should be used for this param. If a user does not provide an org_id argument, the function attempts to identify which organization identifier(s) to include based on the unique ATTAINS organization identifiers found in the dataframe.

useParamRef

A required data frame which contains a completed crosswalk of organization specific ATTAINS.UseName(s) for each ATTAINS.ParameterName. Users will need to ensure this crosswalk contains the appropriate column names in order to run the function. Users who have previously completed this crosswalk table can re-use it and review this output for accuracy.

displayNA

A boolean value. If TRUE, this allows user to view MLSummaryRef for all uses and parameter assigned to a ML or AU regardless if that site contains WQP data for that parameter. This is useful if a user is interested in an explicit list of everything that will be analyzed. Default is FALSE.

An optional data frame input. If provided, this data frame should contain a completed crosswalk of use names associated with a water type. Users will need to ensure this crosswalk contains the appropriate column names in order to run the function.

AUMLRef

An optional data frame input. If provided, this data frame should contain a completed crosswalk of monitoring location sites associated with an assessment unit. Users will need to ensure this crosswalk contains the appropriate column names in order to run the function. See module 2 vignette and sample output of TADA_CreateAUMLCrosswalk().

useAURef

An optional data frame input. If provided, this data frame should contain a completed crosswalk of use names associated with an assessment unit. Users will need to ensure this crosswalk contains the appropriate column names in order to run the function. See output of TADA_CreateUseAURef() for column names.

MLSummaryRef

An optional data frame which contains the completed spatial crosswalk to assign any unique spatial criteria to a parameter, use, waterbody or monitoring site/assessment unit.

excel

A Boolean value that returns an excel spreadsheet if excel = TRUE. This spreadsheet is created in the user's downloads folder path. If you have any trouble locating the file, please type the following into your R console to locate it: file.path(Sys.getenv("USERPROFILE"), "Downloads"). The file will be named "myfileRef.xlsx". The excel spreadsheet will highlight the cells in which users should input information.

overwrite

A Boolean value that ensures the function will not overwrite the user supplied crosswalk entered into this function via the paramRef function input. This helps prevent users from overwriting their progress.

Value

A data frame with any unique spatial descriptions defined for

Details

If users are interested in summarizing water quality data results by Assessment Units, users will need to provide an AUMLRef and useAURef file which (see TADA Module 2 tools) to assist in their monitoring location to assessment unit crosswalk (see TADA_GetATTAINSAUMLCrosswalk, TADA_CreateAUMLCrosswalk, and TADA_GetATTAINSByAUID) and uses to assessment unit crosswalk (see TADA_CreateWaterUseParamRef and TADA_CreateUseAURef) prior to this step.

Users can apply any unique site-specific criteria (for example, warm waters, cold waters, water classifications, species-based waters, ecoregions etc.) to any monitoring location sites or assessment units as needed. Users are recommended to utilize the excel file for easy filtering across columns to apply any site specific criteria as needed.

Examples

if (FALSE) { # \dontrun{
# First, generate and fill out a parameter crosswalk (see TADA_CreateParamRef()):
paramRef_UT <- TADA_CreateParamRef(Data_Nutrients_UT, org_id = "UTAHDWQ", excel = FALSE)
paramRef_UT2 <- dplyr::mutate(paramRef_UT, ATTAINS.ParameterName = dplyr::case_when(
  grepl("AMMONIA", TADA.ComparableDataIdentifier) ~ "AMMONIA, TOTAL",
  grepl("NITRATE", TADA.ComparableDataIdentifier) ~ "NITRATE",
  grepl("NITROGEN", TADA.ComparableDataIdentifier) ~ "NITRATE/NITRITE (NITRITE + NITRATE AS N)"
))
paramRef_UT3 <- TADA_CreateParamRef(
  Data_Nutrients_UT,
  paramRef = paramRef_UT2, org_id = "UTAHDWQ", excel = FALSE
)

# Next, enter the crosswalk generated above as the paramRef function input
# for TADA_CreateUseParamRef():
UseParamRef_UT <- TADA_CreateUseParamRef(
  Data_Nutrients_UT,
  paramRef = paramRef_UT3, org_id = c("UTAHDWQ"), excel = FALSE
)

# Now, run TADA_CreateMLSummaryRef()
MLSummaryRef_UT <- TADA_CreateMLSummaryRef(
  Data_Nutrients_UT,
  org_id = c("UTAHDWQ"),
  useAURef = NULL, AUMLRef = NULL,
  useParamRef = UseParamRef_UT,
  excel = FALSE
)
} # }