Skip to contents

The quality control functions in MassWateR can be used once the required data are successfully imported into R (see the data input and checks vignette for an overview). The required data includes the results data file that describe the monitoring data and the data quality objective files for accuracy, frequency, and completeness. The example data files included with the package are imported here to demonstrate how to use the quality control functions:

library(MassWateR)

# import results data
respth <- system.file("extdata/ExampleResults.xlsx", package = "MassWateR")
resdat <- readMWRresults(respth)
#> Running checks on results data...
#>  Checking column names... OK
#>  Checking all required columns are present... OK
#>  Checking valid Activity Types... OK
#>  Checking Activity Start Date formats... OK
#>  Checking depth data present... OK
#>  Checking for non-numeric values in Activity Depth/Height Measure... OK
#>  Checking Activity Depth/Height Unit... OK
#>  Checking Activity Relative Depth Name formats... OK
#>  Checking values in Activity Depth/Height Measure > 1 m / 3.3 ft... OK
#>  Checking Characteristic Name formats... OK
#>  Checking Result Values... OK
#>  Checking for non-numeric values in Quantitation Limit... OK
#>  Checking QC Reference Values... OK
#>  Checking for missing entries for Result Unit... OK
#>  Checking if more than one unit per Characteristic Name... OK
#>  Checking acceptable units for each entry in Characteristic Name... OK
#> 
#> All checks passed!

# import data quality objectives for accuracy
accpth <- system.file("extdata/ExampleDQOAccuracy.xlsx", package = "MassWateR")
accdat <- readMWRacc(accpth)
#> Running checks on data quality objectives for accuracy...
#>  Checking column names... OK
#>  Checking all required columns are present... OK
#>  Checking column types... OK
#>  Checking no "na" in Value Range... OK
#>  Checking for text other than <=, ≤, <, >=, ≥, >, ±, %, AQL, BQL, log, or all... OK
#>  Checking overlaps in Value Range... OK
#>  Checking gaps in Value Range... OK
#>  Checking Parameter formats... OK
#>  Checking for missing entries for unit (uom)... OK
#>  Checking if more than one unit (uom) per Parameter... OK
#>  Checking acceptable units (uom) for each entry in Parameter... OK
#>  Checking empty columns... OK
#> 
#> All checks passed!

# import data quality objectives for frequency and completeness
frecompth <- system.file("extdata/ExampleDQOFrequencyCompleteness.xlsx", package = "MassWateR")
frecomdat <- readMWRfrecom(frecompth)
#> Running checks on data quality objectives for frequency and completeness...
#>  Checking column names... OK
#>  Checking all required columns are present... OK
#>  Checking for non-numeric values... OK
#>  Checking for values outside of 0 and 100... OK
#>  Checking Parameter formats... OK
#>  Checking empty columns... OK
#> 
#> All checks passed!

Creating the review report

The qcMWRreview() function compiles a review report as a Word document for all quality control checks included in the MassWateR package. The report shows several tables, including the data quality objectives files for accuracy, frequency, and completeness, summary results for all accuracy checks, summary results for all frequency checks, summary results for all completeness checks, and individual results for all accuracy checks. The report uses individual table functions described in the sections below to return the results, which include tabMWRacc(), tabMWRfre(), and tabMWRcom().

The workflow for using this function is to import the required data (results and data quality objective files, as above) and to fix any errors noted on import prior to creating the review report. The function can be used with inputs as paths to the relevant files or as data frames returned by readMWRresults(), readMWRacc(), and readMWRfrecom(). For the former, the full suite of data checks can be evaluated with runkchk = T (default) or suppressed with runchk = F, as explained in the relevant help files. In the latter case, downstream analyses may not work if data are formatted incorrectly.

The report can be created as follows by including the required files and specifying an output directory where the Word document is saved (a temporary directory is used here). Once the function is done running, a message indicating success and where the file is located is returned. The Word file can be further edited by hand as needed.

qcMWRreview(res = resdat, acc = accdat, frecom = frecomdat, warn = FALSE, output_dir = tempdir())
#> Report created successfully! File located at /tmp/Rtmps88vvh/qcreview.docx

As a convenience, the input files can also be passed to the qcMWRreview() function as a named list using the fset argument. This eliminates the need to individually specify the input arguments.

# names list of inputs
fsetls <- list(
  res = resdat, 
  acc = accdat, 
  frecom = frecomdat
)

qcMWRreview(fset = fsetls, output_dir = tempdir())

Note that the warnings are suppressed above with warn = FALSE. By default, this argument is set to TRUE to view the warnings in the R console after the report is created. The warnings indicate notable concerns to consider for the input data that may need to be addressed. Details on these warnings are described in the sections below for each quality control table.

Optional arguments for qcMWRreview() that can be changed as needed include specifying the file name with output_file, suppressing the raw data summaries at the end of the report with rawdata = FALSE, and changing the table font sizes (dqofontsize for the data quality objectives on the first page, tabfontsize for the remainder).

Quality control for accuracy

The quality control checks for accuracy assess several characteristics of the data in the results file by referencing appropriate values in the data quality objectives file for accuracy. In short, the accuracy checks evaluate field blanks, lab blanks, field duplicates, lab duplicates, lab spikes, and instrument checks. The accuracy checks require results data (as in resdat above) and data quality objectives files for accuracy (accdat) and frequency and completeness (frecomdat).

The tabMWRacc() function is used to create tabular results for the accuracy checks for each parameter. The function can be used with inputs as paths to the relevant files or as data frames returned by readMWRresults(), readMWRacc(), and readMWRfrecom. For the former, the full suite of data checks can be evaluated with runkchk = T (default) or suppressed with runchk = F, as explained in the data inputs and checks vignette. In the latter case, downstream analyses may not work if data are formatted incorrectly. Also note that accuracy is only evaluated on parameters that are shared between the results file and the data quality objectives accuracy file. A warning is returned if there are parameters that do not match. The warnings can be suppressed by setting warn = FALSE.

The tabMWRacc() function can return three types of tables as specified with the type argument: "individual", "summary", or "percent". The individual tables are specific to each type of accuracy check for each parameter (e.g., field blanks, lab blanks, etc.). The summary table summarizes all accuracy checks by the number of checks and how many hit/misses are returned for each across all parameters. The percent table is similar to the summary table, but showing only percentages with appropriate color-coding for hit/misses. The data quality objectives file for frequency and completeness is also required if type = "summary" or type = "percent".

For type = "individual", the quality control tables for accuracy are retrieved by specifying the check with the accchk argument. The accchk argument can be used to specify one of the following values to retrieve the relevant tables: "Field Blanks", "Lab Blanks", "Field Duplicates", "Lab Duplicates", or "Lab Spikes / Instrument Checks". Below shows how to retrieve each table using the data frames from above for the results and quality objectives file for accuracy. The warnings are suppressed with warn = FALSE.

tabMWRacc(res = resdat, acc = accdat, frecom = frecomdat, type = "individual", accchk = "Field Blanks", warn = FALSE)
Field Blanks

Parameter

Date

Site

Result

Threshold

Hit/Miss

Ammonia

2022-05-15

BDL

0.1 mg/l

2022-06-12

BDL

0.1 mg/l

2022-07-17

BDL

0.1 mg/l

2022-07-17

BDL

0.1 mg/l

2022-08-14

BDL

0.1 mg/l

2022-08-14

BDL

0.1 mg/l

2022-09-11

BDL

0.1 mg/l

E.coli

2022-06-13

BDL

1 MPN/100ml

2022-07-18

BDL

1 MPN/100ml

2022-08-01

BDL

1 MPN/100ml

2022-08-29

BDL

1 MPN/100ml

Nitrate

2022-05-15

BDL

0.05 mg/l

2022-06-12

BDL

0.05 mg/l

2022-06-12

BDL

0.05 mg/l

2022-07-17

BDL

0.05 mg/l

2022-07-17

BDL

0.05 mg/l

2022-08-14

BDL

0.05 mg/l

2022-09-11

BDL

0.05 mg/l

TP

2022-05-15

BDL

0.01 mg/l

2022-05-15

BDL

0.01 mg/l

2022-06-12

BDL

0.01 mg/l

2022-06-12

BDL

0.01 mg/l

2022-07-17

BDL

0.01 mg/l

2022-07-17

BDL

0.01 mg/l

2022-07-17

0.01 mg/l

0.01 mg/l

MISS

2022-08-14

BDL

0.01 mg/l

2022-08-14

BDL

0.01 mg/l

2022-09-11

BDL

0.01 mg/l

2022-09-11

BDL

0.01 mg/l

tabMWRacc(res = resdat, acc = accdat, frecom = frecomdat,type = "individual", accchk = "Lab Blanks", warn = FALSE)
Lab Blanks

Parameter

Date

Sample ID

Result

Threshold

Hit/Miss

Ammonia

2022-05-15

BDL

0.1 mg/l

2022-06-12

BDL

0.1 mg/l

2022-07-17

BDL

0.1 mg/l

2022-07-17

0.1 mg/l

0.1 mg/l

MISS

2022-08-14

BDL

0.1 mg/l

2022-08-14

BDL

0.1 mg/l

2022-09-11

BDL

0.1 mg/l

Nitrate

2022-05-15

BDL

0.05 mg/l

2022-06-12

BDL

0.05 mg/l

2022-07-17

BDL

0.05 mg/l

2022-08-14

BDL

0.05 mg/l

2022-09-11

BDL

0.05 mg/l

Sp Conductance

2022-05-15

7 uS/cm

50 uS/cm

2022-05-15

7.4 uS/cm

50 uS/cm

2022-05-15

7.7 uS/cm

50 uS/cm

2022-05-15

8.6 uS/cm

50 uS/cm

2022-06-12

8.9 uS/cm

50 uS/cm

2022-06-12

9 uS/cm

50 uS/cm

2022-06-12

10.1 uS/cm

50 uS/cm

2022-06-12

10.9 uS/cm

50 uS/cm

2022-06-12

13 uS/cm

50 uS/cm

2022-07-17

4 uS/cm

50 uS/cm

2022-07-17

4 uS/cm

50 uS/cm

2022-07-17

5.8 uS/cm

50 uS/cm

2022-07-17

6 uS/cm

50 uS/cm

2022-08-14

2.5 uS/cm

50 uS/cm

2022-08-14

3 uS/cm

50 uS/cm

2022-08-14

80 uS/cm

50 uS/cm

MISS

2022-08-14

3.9 uS/cm

50 uS/cm

2022-09-11

4 uS/cm

50 uS/cm

2022-09-11

4.1 uS/cm

50 uS/cm

2022-09-11

4.7 uS/cm

50 uS/cm

2022-09-11

5.9 uS/cm

50 uS/cm

TP

2022-05-15

BDL

0.01 mg/l

2022-06-12

BDL

0.01 mg/l

2022-07-17

BDL

0.01 mg/l

2022-08-14

BDL

0.01 mg/l

2022-09-11

BDL

0.01 mg/l

tabMWRacc(res = resdat, acc = accdat, frecom = frecomdat, type = "individual", accchk = "Field Duplicates", warn = FALSE)
Field Duplicates

Parameter

Date

Site

Initial Result

Dup. Result

Diff./RPD

Hit/Miss

Ammonia

2022-05-15

ABT-312

BDL

BDL

0% RPD

2022-05-15

DAN-013

BDL

BDL

0% RPD

2022-06-12

ABT-301

BDL

0.2 mg/l

67% RPD

MISS

2022-09-11

ABT-301

BDL

BDL

0% RPD

DO

2022-05-15

ABT-026

7.58 mg/l

7.6 mg/l

0% RPD

2022-05-15

ELZ-004

5.81 mg/l

5.94 mg/l

2% RPD

2022-05-15

NSH-002

8.32 mg/l

8.33 mg/l

0% RPD

2022-06-12

ABT-062

8.56 mg/l

8.56 mg/l

0% RPD

2022-06-12

ABT-237

7.81 mg/l

8.1 mg/l

4% RPD

2022-06-12

HOP-011

7.8 mg/l

7.79 mg/l

0% RPD

2022-07-17

ABT-062

7.59 mg/l

7.59 mg/l

0% RPD

2022-07-17

ABT-237

5.92 mg/l

5.92 mg/l

0% RPD

2022-08-14

ABT-237

5.89 mg/l

5.9 mg/l

0% RPD

2022-09-11

ABT-026

7.7 mg/l

7.7 mg/l

0% RPD

2022-09-11

HOP-011

8.36 mg/l

8.35 mg/l

0% RPD

E.coli

2022-07-18

ABT-162

276 MPN/100ml

276 MPN/100ml

0% logRPD

2022-08-15

ABT-077

231 MPN/100ml

276 MPN/100ml

3% logRPD

Nitrate

2022-06-12

ABT-301

3.65 mg/l

3.35 mg/l

9% RPD

2022-07-17

ABT-077

0.72 mg/l

0.73 mg/l

1% RPD

pH

2022-05-15

ABT-026

7.19 s.u.

7.2 s.u.

0.01 s.u.

2022-05-15

ELZ-004

6.95 s.u.

7.08 s.u.

0.13 s.u.

2022-05-15

NSH-002

7.23 s.u.

7.25 s.u.

0.02 s.u.

2022-06-12

ABT-062

7.26 s.u.

7.26 s.u.

0 s.u.

2022-06-12

ABT-237

7.1 s.u.

7.11 s.u.

0.01 s.u.

2022-06-12

HOP-011

6.86 s.u.

6.82 s.u.

0.04 s.u.

2022-07-17

ABT-062

8.02 s.u.

8.01 s.u.

0.01 s.u.

2022-07-17

ABT-237

7.28 s.u.

7.28 s.u.

0 s.u.

2022-08-14

ABT-237

7.28 s.u.

7.28 s.u.

0 s.u.

2022-09-11

ABT-026

7.13 s.u.

7.14 s.u.

0.01 s.u.

2022-09-11

HOP-011

6.92 s.u.

6.84 s.u.

0.08 s.u.

Sp Conductance

2022-05-15

ABT-026

585 uS/cm

586 uS/cm

0% RPD

2022-05-15

ELZ-004

375 uS/cm

375 uS/cm

0% RPD

2022-05-15

NSH-002

524 uS/cm

525 uS/cm

0% RPD

2022-06-12

ABT-062

579 uS/cm

579 uS/cm

0% RPD

2022-06-12

ABT-237

740 uS/cm

740 uS/cm

0% RPD

2022-06-12

HOP-011

731 uS/cm

731 uS/cm

0% RPD

2022-07-17

ABT-062

831 uS/cm

831 uS/cm

0% RPD

2022-07-17

ABT-237

1222 uS/cm

1221 uS/cm

0% RPD

2022-08-14

ABT-237

1497 uS/cm

1489 uS/cm

1% RPD

2022-09-11

ABT-026

738 uS/cm

675 uS/cm

9% RPD

2022-09-11

HOP-011

865 uS/cm

865 uS/cm

0% RPD

TP

2022-05-15

ABT-312

0.03 mg/l

0.03 mg/l

0 mg/l

2022-05-15

DAN-013

0.04 mg/l

0.04 mg/l

0 mg/l

2022-06-12

ABT-301

0.03 mg/l

0.03 mg/l

0 mg/l

2022-07-17

ABT-077

0.04 mg/l

0.02 mg/l

0.02 mg/l

MISS

2022-09-11

ABT-301

0.03 mg/l

0.03 mg/l

0 mg/l

Water Temp

2022-05-15

ABT-026

22.4 deg C

22.4 deg C

0 deg C

2022-05-15

ELZ-004

22.2 deg C

22.2 deg C

0 deg C

2022-05-15

NSH-002

23.3 deg C

23.3 deg C

0 deg C

2022-06-12

ABT-062

21.1 deg C

21.1 deg C

0 deg C

2022-06-12

ABT-237

18.7 deg C

18.7 deg C

0 deg C

2022-06-12

HOP-011

18.4 deg C

18.4 deg C

0 deg C

2022-07-17

ABT-062

25.6 deg C

25.6 deg C

0 deg C

2022-07-17

ABT-237

20.8 deg C

20.8 deg C

0 deg C

2022-08-14

ABT-237

18.8 deg C

18.8 deg C

0 deg C

2022-09-11

ABT-026

20.5 deg C

20.5 deg C

0 deg C

2022-09-11

HOP-011

19.3 deg C

19.3 deg C

0 deg C

tabMWRacc(res = resdat, acc = accdat, frecom = frecomdat, type = "individual", accchk = "Lab Duplicates", warn = FALSE)
Lab Duplicates

Parameter

Date

Sample ID

Initial Result

Dup. Result

Diff./RPD

Hit/Miss

Ammonia

2022-05-15

0.21 mg/l

0.21 mg/l

0% RPD

2022-05-15

BDL

BDL

0% RPD

2022-06-12

0.1 mg/l

0.1 mg/l

0% RPD

2022-06-12

0.19 mg/l

0.19 mg/l

0% RPD

2022-07-17

BDL

BDL

0% RPD

2022-07-17

BDL

BDL

0% RPD

2022-08-14

BDL

BDL

0% RPD

2022-08-14

BDL

BDL

0% RPD

2022-09-11

BDL

BDL

0% RPD

2022-09-11

BDL

BDL

0% RPD

E.coli

2022-06-13

547.5 MPN/100ml

579.4 MPN/100ml

1% logRPD

2022-07-18

88 MPN/100ml

167 MPN/100ml

13% logRPD

2022-08-01

114.5 MPN/100ml

160.7 MPN/100ml

7% logRPD

2022-08-29

42.8 MPN/100ml

40.4 MPN/100ml

2% logRPD

Nitrate

2022-05-15

0.37 mg/l

0.38 mg/l

3% RPD

2022-06-12

0.17 mg/l

0.17 mg/l

0% RPD

2022-06-12

3.65 mg/l

3.63 mg/l

1% RPD

2022-06-12

BDL

BDL

0% RPD

2022-07-17

1.29 mg/l

1.29 mg/l

0% RPD

2022-07-17

BDL

BDL

0% RPD

2022-07-17

BDL

BDL

0% RPD

2022-08-14

2.69 mg/l

2.69 mg/l

0% RPD

2022-08-14

5.22 mg/l

5.24 mg/l

0% RPD

2022-09-11

1.51 mg/l

1.5 mg/l

1% RPD

pH

2022-05-15

7.11 s.u.

7.09 s.u.

0.02 s.u.

2022-05-15

7.18 s.u.

7.09 s.u.

0.09 s.u.

2022-05-15

7.19 s.u.

7.09 s.u.

0.1 s.u.

2022-06-12

7.12 s.u.

7.19 s.u.

0.07 s.u.

2022-06-12

7.13 s.u.

7.19 s.u.

0.06 s.u.

2022-06-12

7.21 s.u.

7.19 s.u.

0.02 s.u.

2022-06-12

7.27 s.u.

7.19 s.u.

0.08 s.u.

2022-07-17

7.48 s.u.

7.37 s.u.

0.11 s.u.

2022-07-17

7.54 s.u.

7.37 s.u.

0.17 s.u.

2022-07-17

7.54 s.u.

7.37 s.u.

0.17 s.u.

2022-07-17

7.54 s.u.

7.37 s.u.

0.17 s.u.

2022-08-14

7.64 s.u.

7.32 s.u.

0.32 s.u.

2022-08-14

7.65 s.u.

7.32 s.u.

0.33 s.u.

2022-08-14

7.68 s.u.

7.32 s.u.

0.36 s.u.

2022-09-11

7.07 s.u.

6.74 s.u.

0.33 s.u.

2022-09-11

7.16 s.u.

6.74 s.u.

0.42 s.u.

2022-09-11

7.34 s.u.

6.74 s.u.

0.6 s.u.

MISS

Sp Conductance

2022-05-15

599 uS/cm

609 uS/cm

2% RPD

2022-05-15

605 uS/cm

609 uS/cm

1% RPD

2022-05-15

606 uS/cm

609 uS/cm

0% RPD

2022-06-12

600 uS/cm

608 uS/cm

1% RPD

2022-06-12

602 uS/cm

608 uS/cm

1% RPD

2022-06-12

606 uS/cm

608 uS/cm

0% RPD

2022-07-17

793 uS/cm

802 uS/cm

1% RPD

2022-07-17

900 uS/cm

802 uS/cm

12% RPD

2022-07-17

796 uS/cm

802 uS/cm

1% RPD

2022-07-17

801 uS/cm

802 uS/cm

0% RPD

2022-08-14

1062 uS/cm

1066 uS/cm

0% RPD

2022-08-14

1062 uS/cm

1066 uS/cm

0% RPD

2022-08-14

1063 uS/cm

1066 uS/cm

0% RPD

2022-08-14

1065 uS/cm

1066 uS/cm

0% RPD

2022-09-11

761 uS/cm

766 uS/cm

1% RPD

2022-09-11

765 uS/cm

766 uS/cm

0% RPD

2022-09-11

774 uS/cm

766 uS/cm

1% RPD

TP

2022-05-15

0.01 mg/l

0.01 mg/l

0 mg/l

2022-05-15

0.03 mg/l

0.02 mg/l

0.01 mg/l

2022-05-15

0.06 mg/l

0.06 mg/l

0% RPD

2022-06-12

0.04 mg/l

0.04 mg/l

0 mg/l

2022-06-12

0.04 mg/l

0.04 mg/l

0 mg/l

2022-06-12

0.06 mg/l

0.06 mg/l

0% RPD

2022-06-12

BDL

BDL

0 mg/l

2022-07-17

0.04 mg/l

0.04 mg/l

0 mg/l

2022-07-17

0.05 mg/l

0.05 mg/l

0% RPD

2022-07-17

BDL

BDL

0 mg/l

2022-08-14

0.03 mg/l

0.03 mg/l

0 mg/l

2022-08-14

0.05 mg/l

0.05 mg/l

0% RPD

2022-08-14

0.09 mg/l

0.09 mg/l

0% RPD

2022-09-11

0.04 mg/l

0.04 mg/l

0 mg/l

2022-09-11

0.04 mg/l

0.04 mg/l

0 mg/l

2022-09-11

0.05 mg/l

0.05 mg/l

0% RPD

Water Temp

2022-05-15

21.7 deg C

21.8 deg C

0.1 deg C

2022-05-15

21.8 deg C

21.8 deg C

0 deg C

2022-05-15

21.8 deg C

21.8 deg C

0 deg C

2022-06-12

20.2 deg C

20.2 deg C

0 deg C

2022-06-12

20.2 deg C

20.2 deg C

0 deg C

2022-06-12

20.3 deg C

20.2 deg C

0.1 deg C

2022-06-12

20.3 deg C

20.2 deg C

0.1 deg C

2022-07-17

23 deg C

22.9 deg C

0.1 deg C

2022-07-17

23 deg C

22.9 deg C

0.1 deg C

2022-07-17

23.1 deg C

22.9 deg C

0.2 deg C

2022-08-14

20.8 deg C

20.7 deg C

0.1 deg C

2022-08-14

20.8 deg C

20.7 deg C

0.1 deg C

2022-08-14

20.9 deg C

20.7 deg C

0.2 deg C

2022-08-14

20.9 deg C

20.7 deg C

0.2 deg C

2022-09-11

20.6 deg C

20.5 deg C

0.1 deg C

2022-09-11

20.7 deg C

20.5 deg C

0.2 deg C

2022-09-11

20.7 deg C

20.5 deg C

0.2 deg C

tabMWRacc(res = resdat, acc = accdat, frecom = frecomdat, type = "individual", accchk = "Lab Spikes / Instrument Checks", warn = FALSE)
Lab Spikes / Instrument Checks

Parameter

Date

Sample ID

Spike/Standard

Result

Diff./Accuracy

Hit/Miss

Ammonia

2022-05-15

100 % recovery

86 % recovery

86%

2022-06-12

100 % recovery

94 % recovery

94%

2022-06-12

100 % recovery

106 % recovery

106%

2022-07-17

100 % recovery

92 % recovery

92%

2022-07-17

100 % recovery

108 % recovery

108%

2022-08-14

100 % recovery

96 % recovery

96%

2022-08-14

100 % recovery

102 % recovery

102%

2022-09-11

100 % recovery

88 % recovery

88%

2022-09-11

100 % recovery

89 % recovery

89%

Nitrate

2022-05-15

100 % recovery

99 % recovery

99%

2022-06-12

100 % recovery

95 % recovery

95%

2022-06-12

100 % recovery

97 % recovery

97%

2022-06-12

100 % recovery

105 % recovery

105%

2022-07-17

100 % recovery

99 % recovery

99%

2022-07-17

100 % recovery

101 % recovery

101%

2022-07-17

100 % recovery

125 % recovery

125%

MISS

2022-08-14

100 % recovery

103 % recovery

103%

2022-08-14

100 % recovery

109 % recovery

109%

2022-09-11

100 % recovery

101 % recovery

101%

pH

2022-05-15

7.02 s.u.

7 s.u.

-0.02 s.u.

2022-05-15

7.02 s.u.

7.03 s.u.

+0.01 s.u.

2022-05-15

7.02 s.u.

7.09 s.u.

+0.07 s.u.

2022-05-15

7.02 s.u.

7.11 s.u.

+0.09 s.u.

2022-06-12

7 s.u.

7.01 s.u.

+0.01 s.u.

2022-06-12

7 s.u.

7.05 s.u.

+0.05 s.u.

2022-06-12

7 s.u.

7.06 s.u.

+0.06 s.u.

2022-06-12

7 s.u.

7.06 s.u.

+0.06 s.u.

2022-06-12

7 s.u.

7.07 s.u.

+0.07 s.u.

2022-07-17

7 s.u.

7.05 s.u.

+0.05 s.u.

2022-07-17

7 s.u.

7.06 s.u.

+0.06 s.u.

2022-07-17

7 s.u.

7.06 s.u.

+0.06 s.u.

2022-07-17

7 s.u.

7.06 s.u.

+0.06 s.u.

2022-07-17

7 s.u.

7.4 s.u.

+0.4 s.u.

MISS

2022-08-14

7 s.u.

6.99 s.u.

-0.01 s.u.

2022-08-14

7 s.u.

7.07 s.u.

+0.07 s.u.

2022-08-14

7 s.u.

7.09 s.u.

+0.09 s.u.

2022-09-11

7 s.u.

7.01 s.u.

+0.01 s.u.

2022-09-11

7 s.u.

7.06 s.u.

+0.06 s.u.

2022-09-11

7 s.u.

7.06 s.u.

+0.06 s.u.

Sp Conductance

2022-05-15

1000 uS/cm

975 uS/cm

-25 uS/cm

2022-05-15

1000 uS/cm

977 uS/cm

-23 uS/cm

2022-05-15

1000 uS/cm

985 uS/cm

-15 uS/cm

2022-05-15

1000 uS/cm

991 uS/cm

-9 uS/cm

2022-06-12

1000 uS/cm

978 uS/cm

-22 uS/cm

2022-06-12

1000 uS/cm

979 uS/cm

-21 uS/cm

2022-06-12

1000 uS/cm

979 uS/cm

-21 uS/cm

2022-06-12

1000 uS/cm

983 uS/cm

-17 uS/cm

2022-06-12

1000 uS/cm

987 uS/cm

-13 uS/cm

2022-07-17

1000 uS/cm

984 uS/cm

-16 uS/cm

2022-07-17

1000 uS/cm

988 uS/cm

-12 uS/cm

2022-07-17

1000 uS/cm

997 uS/cm

-3 uS/cm

2022-08-14

1000 uS/cm

991 uS/cm

-9 uS/cm

2022-08-14

1000 uS/cm

991 uS/cm

-9 uS/cm

2022-08-14

1000 uS/cm

992 uS/cm

-8 uS/cm

2022-08-14

1000 uS/cm

992 uS/cm

-8 uS/cm

2022-08-14

1000 uS/cm

996 uS/cm

-4 uS/cm

2022-09-11

1000 uS/cm

986 uS/cm

-14 uS/cm

2022-09-11

1000 uS/cm

989 uS/cm

-11 uS/cm

2022-09-11

1000 uS/cm

990 uS/cm

-10 uS/cm

2022-09-11

1000 uS/cm

993 uS/cm

-7 uS/cm

TP

2022-05-15

100 % recovery

100 % recovery

100%

2022-05-15

100 % recovery

101 % recovery

101%

2022-05-15

100 % recovery

103 % recovery

103%

2022-06-12

100 % recovery

100 % recovery

100%

2022-06-12

100 % recovery

104 % recovery

104%

2022-06-12

100 % recovery

104 % recovery

104%

2022-07-17

100 % recovery

105 % recovery

105%

2022-07-17

100 % recovery

105 % recovery

105%

2022-07-17

100 % recovery

110 % recovery

110%

2022-08-14

100 % recovery

99 % recovery

99%

2022-08-14

100 % recovery

99 % recovery

99%

2022-08-14

100 % recovery

101 % recovery

101%

2022-09-11

100 % recovery

97 % recovery

97%

2022-09-11

100 % recovery

99 % recovery

99%

2022-09-11

100 % recovery

99 % recovery

99%

Water Temp

2022-05-15

21.8 deg C

21.8 deg C

+0 deg C

2022-05-15

21.8 deg C

21.8 deg C

+0 deg C

2022-05-15

21.8 deg C

21.9 deg C

+0.1 deg C

2022-05-15

21.8 deg C

21.9 deg C

+0.1 deg C

2022-06-12

22.5 deg C

22.6 deg C

+0.1 deg C

2022-06-12

22.5 deg C

22.6 deg C

+0.1 deg C

2022-06-12

22.5 deg C

22.7 deg C

+0.2 deg C

2022-07-17

22.7 deg C

22.6 deg C

-0.1 deg C

2022-07-17

22.7 deg C

22.7 deg C

+0 deg C

2022-07-17

22.7 deg C

22.7 deg C

+0 deg C

2022-07-17

22.7 deg C

25 deg C

+2.3 deg C

MISS

2022-07-17

22.7 deg C

22.9 deg C

+0.2 deg C

2022-08-14

23.1 deg C

23.1 deg C

+0 deg C

2022-08-14

23.1 deg C

23.4 deg C

+0.3 deg C

2022-08-14

23.1 deg C

23.4 deg C

+0.3 deg C

2022-09-11

22.8 deg C

22.8 deg C

+0 deg C

2022-09-11

22.8 deg C

22.8 deg C

+0 deg C

2022-09-11

22.8 deg C

22.9 deg C

+0.1 deg C

2022-09-11

22.8 deg C

23 deg C

+0.2 deg C

For type = "summary", the function summarizes all accuracy checks by counting the number of quality control checks, number of misses, and percent acceptance for each parameter. All accuracy checks are used and the accchk argument does not apply.

tabMWRacc(res = resdat, acc = accdat, frecom = frecomdat, type = "summary", warn = FALSE)

Type

Parameter

Number of QC Checks

Number of Misses

% Acceptance

Field Duplicates

Ammonia

4

1

75 %

DO

11

0

100 %

E.coli

2

0

100 %

Nitrate

2

0

100 %

pH

11

0

100 %

Sp Conductance

11

0

100 %

TP

5

1

80 %

Water Temp

11

0

100 %

Lab Duplicates

Ammonia

10

0

100 %

E.coli

4

0

100 %

Nitrate

10

0

100 %

pH

17

1

94 %

Sp Conductance

17

0

100 %

TP

16

0

100 %

Water Temp

17

0

100 %

Field Blanks

Ammonia

7

0

100 %

E.coli

4

0

100 %

Nitrate

7

0

100 %

TP

11

1

91 %

Lab Blanks

Ammonia

7

1

86 %

E.coli

0

-

-

Nitrate

5

0

100 %

Sp Conductance

21

1

95 %

TP

5

0

100 %

Lab Spikes / Instrument Checks

Ammonia

9

0

100 %

Nitrate

10

1

90 %

pH

20

1

95 %

Sp Conductance

21

0

100 %

TP

15

0

100 %

Water Temp

19

1

95 %

For type = "percent", the function returns a similar table as for the summary option, except only the percentage of checks that pass for each parameter are shown in wide format. Cells are color-coded based on the percentage of checks that have passed using the percent thresholds from the % Completeness column of the data quality objectives file for frequency and completeness. Parameters without an entry for % Completeness are not color-coded and an appropriate warning is returned. All accuracy checks are used and the accchk argument does not apply.

tabMWRacc(res = resdat, acc = accdat, frecom = frecomdat, type = "percent", warn = FALSE)

Parameter

Field Duplicate

Lab Duplicate

Field Blank

Lab Blank

Spike/Check Accuracy

Ammonia

75%

100%

100%

86%

100%

DO

100%

-

-

-

-

E.coli

100%

100%

100%

-

-

Nitrate

100%

100%

100%

100%

90%

pH

100%

94%

-

-

95%

Sp Conductance

100%

100%

-

95%

100%

TP

80%

100%

91%

100%

100%

Water Temp

100%

100%

-

-

95%

The tabMWRacc() function uses the qcMWRacc() function internally to create the table. This function creates the raw summaries of accuracy from the input data. Typically, qcMWRacc() is not used by itself, but it is explained here to demonstrate how the raw summaries can be obtained.

Below, the qcMWRacc() function is executed with the data frames for the results and quality objectives file for accuracy. As with tabMWRacc, the accchk argument can be used to return one to all of the checks. The results are returned as a list, with each element of the list corresponding to a specific accuracy check. Here, the lab duplicate checks are returned. The warnings are also suppressed.

qcMWRacc(res = resdat, acc = accdat, frecom = frecomdat, accchk = "Lab Duplicates", warn = FALSE)
#> $`Lab Duplicates`
#> # A tibble: 91 × 7
#>    Parameter Date                `Sample ID` `Initial Result` `Dup. Result`
#>    <chr>     <dttm>              <chr>       <chr>            <chr>        
#>  1 Ammonia   2022-05-15 00:00:00 NA          0.21 mg/l        0.21 mg/l    
#>  2 Ammonia   2022-05-15 00:00:00 NA          BDL              BDL          
#>  3 Ammonia   2022-06-12 00:00:00 NA          0.1 mg/l         0.1 mg/l     
#>  4 Ammonia   2022-06-12 00:00:00 NA          0.19 mg/l        0.19 mg/l    
#>  5 Ammonia   2022-07-17 00:00:00 NA          BDL              BDL          
#>  6 Ammonia   2022-07-17 00:00:00 NA          BDL              BDL          
#>  7 Ammonia   2022-08-14 00:00:00 NA          BDL              BDL          
#>  8 Ammonia   2022-08-14 00:00:00 NA          BDL              BDL          
#>  9 Ammonia   2022-09-11 00:00:00 NA          BDL              BDL          
#> 10 Ammonia   2022-09-11 00:00:00 NA          BDL              BDL          
#> # ℹ 81 more rows
#> # ℹ 2 more variables: `Diff./RPD` <chr>, `Hit/Miss` <chr>

Quality control for frequency

The quality control checks for frequency are used to verify an appropriate number of quality control samples have been collected or analyzed for each parameter. These are checks on the quantity of samples and not the values, as for the accuracy checks. The frequency checks require results data (as in resdat above), a data quality objectives file for accuracy (as in accdat), and a data quality objectives file for frequency and completeness (as in frecomdat).

The tabMWRfre() function is used to create tabular results for the frequency checks for each parameter. The function can be used with inputs as paths to the relevant files or as data frames returned by readMWRresults(), readMWRacc(), and readMWRfrecom(). For the former, the full suite of data checks can be evaluated with runkchk = T (default) or suppressed with runchk = F, as explained in the data inputs and checks vignette. In the latter case, downstream analyses may not work if data are formatted incorrectly. Also note that completeness is only evaluated on parameters that are shared between the results file and the data quality objectives completeness file. A warning is returned if there are parameters that do not match. The warnings can be suppressed by setting warn = FALSE.

The quality control tables for frequency show the number of records that apply to a given check (e.g., Lab Blank, Field Blank, etc.) relative to the number of “regular” data records (e.g., field samples or measures) for each parameter. A summary of all frequency checks for each parameter is provided if type = "summary". The function is executed with the data frames for the results and quality objectives file for frequency.

tabMWRfre(res = resdat, acc = accdat, frecom = frecomdat, type = "summary", warn = FALSE)

Type

Parameter

Number of Data Records

Number of Dups/Blanks/Spikes

Frequency %

Hit/Miss

Field Duplicates

Ammonia

43

4

9%

MISS

DO

49

11

22%

E.coli

12

2

17%

Nitrate

20

2

10%

pH

49

11

22%

Sp Conductance

49

11

22%

TP

48

5

10%

Water Temp

49

11

22%

Lab Duplicates

Ammonia

43

10

23%

E.coli

12

4

33%

Nitrate

20

10

50%

pH

49

17

35%

Sp Conductance

49

17

35%

TP

48

16

33%

Water Temp

49

17

35%

Field Blanks

Ammonia

43

7

16%

E.coli

12

4

33%

Nitrate

20

7

35%

TP

48

11

23%

Lab Blanks

Ammonia

43

7

16%

E.coli

12

0

0%

MISS

Nitrate

20

5

25%

Sp Conductance

49

21

43%

TP

48

5

10%

Lab Spikes / Instrument Checks

Ammonia

43

9

21%

Nitrate

20

10

50%

pH

49

20

41%

Sp Conductance

49

21

43%

TP

48

15

31%

Water Temp

49

19

39%

A color-coded table showing similar information as percentages for each parameter is provided if type = "percent". Cells are shown as green or red if the required frequency checks are met as specified in the data quality objectives file.

tabMWRfre(res = resdat, acc = accdat, frecom = frecomdat, type = "percent", warn = FALSE)

Parameter

Field Duplicate

Lab Duplicate

Field Blank

Lab Blank

Spike/Check Accuracy

Ammonia

9%

23%

16%

16%

21%

DO

22%

-

-

-

-

E.coli

17%

33%

33%

0%

-

Nitrate

10%

50%

35%

25%

50%

pH

22%

35%

-

-

41%

Sp Conductance

22%

35%

-

43%

43%

TP

10%

33%

23%

10%

31%

Water Temp

22%

35%

-

-

39%

The tabMWRfre() function uses the qcMWRfre() function internally to create the table. This function creates the raw summaries of frequency from the input data. Typically, qcMWRfre() is not used by itself, but it is explained here to demonstrate how the raw summaries can be obtained.

Below, the qcMWRfre() function is executed with the data frames for the results and quality objectives file for frequency and completeness. The warnings are suppressed.

qcMWRfre(res = resdat, acc = accdat, frecom = frecomdat, warn = FALSE)
#> # A tibble: 40 × 7
#>    Parameter   obs check                count standard percent met  
#>    <chr>     <int> <chr>                <int>    <dbl>   <dbl> <lgl>
#>  1 Ammonia      43 Field Duplicate          4       10    9.30 FALSE
#>  2 Ammonia      43 Lab Duplicate           10        5   23.3  TRUE 
#>  3 Ammonia      43 Field Blank              7       10   16.3  TRUE 
#>  4 Ammonia      43 Lab Blank                7        5   16.3  TRUE 
#>  5 Ammonia      43 Spike/Check Accuracy     9        5   20.9  TRUE 
#>  6 DO           49 Field Duplicate         11       10   22.4  TRUE 
#>  7 DO           49 Lab Duplicate            0       NA   NA    NA   
#>  8 DO           49 Field Blank              0       NA   NA    NA   
#>  9 DO           49 Lab Blank                0       NA   NA    NA   
#> 10 DO           49 Spike/Check Accuracy     0       NA   NA    NA   
#> # ℹ 30 more rows

The output shows the frequency checks from the combined files. Each row applies to a frequency check for a parameter. The Parameter column shows the parameter, the obs column shows the total records that apply to regular activity types, the check column shows the relevant activity type for each frequency check, the count column shows the number of records that apply to a check, the standard column shows the relevant percentage required for the quality control check from the quality control objectives file, and the met column shows if the standard was met by comparing if percent is greater than or equal to standard.

Quality control for completeness

The quality control checks for completeness are used to assess the number of regular samples relative to qualified samples that apply to each parameter. Regular samples are those with Field Msr/Obs or Sample-Routine in the Activity Type column of the results file and qualified samples are those marked as Q in the Result Measure Qualifier column of the results file. The completeness checks require results data (as in resdat above) and a data quality objectives file for frequency and completeness (as in frecomdat).

The tabMWRcom() function is used to create a table that shows the completeness percentages for each parameter. As explained in the previous section, the function can be used with inputs as paths to the relevant files or as data frames returned by readMWRresults() and read_frecom().

A summary table showing the number of data records, number of qualified records, and percent completeness can be created with tabMWRcom(). The % Completeness column shows cells as green or red if the required percentage of observations for completeness are present as specified in the data quality objectives file. The Hit/Miss column shows similar information but in text format, i.e., MISS is shown if the quality control standard for completeness is not met. The function is also executed with the data frames from above, since they have already passed the internal checks.

tabMWRcom(res = resdat, frecom = frecomdat, warn = FALSE)

Parameter

Number of Data Records

Number of Qualified Records

% Completeness

Hit/ Miss

Number of Censored Records

Notes

Ammonia

43

0

100%

DO

49

0

100%

E.coli

12

0

100%

Nitrate

20

0

100%

pH

49

0

100%

Sp Conductance

49

0

100%

TP

48

5

90%

MISS

Water Temp

49

0

100%

The tabMWRcom() function uses the qcMWRcom() function internally to create the table. This function creates the raw summaries of completeness from the input data. Typically, qcMWRcom() is not used by itself, but it is explained here to demonstrate how the raw summaries can be obtained.

Below, the qcMWRcom() function is executed with the data frames for the results and quality objectives file for completeness. The warnings are suppressed.

qcMWRcom(res = resdat, frecom = frecomdat, warn = FALSE)
#> # A tibble: 8 × 6
#>   Parameter      datarec qualrec standard complete met  
#>   <chr>            <int>   <int>    <dbl>    <dbl> <lgl>
#> 1 Ammonia             43       0       90    100   TRUE 
#> 2 DO                  49       0       90    100   TRUE 
#> 3 E.coli              12       0       90    100   TRUE 
#> 4 Nitrate             20       0       90    100   TRUE 
#> 5 pH                  49       0       90    100   TRUE 
#> 6 Sp Conductance      49       0       90    100   TRUE 
#> 7 TP                  48       5       90     89.6 FALSE
#> 8 Water Temp          49       0       90    100   TRUE

The output shows the completeness checks from the combined files. Each row applies to a completeness check for a parameter. The datarec and qualrec columns show the number of data records and qualified records, respectively. The datarec column specifically shows only records not for quality control by excluding those as duplicates, blanks, or spikes in the count. The standard column shows the relevant percentage required for the quality control check from the quality control objectives file, the complete column shows the calculated completeness taken from the input data, and the met column shows if the standard was met by comparing if complete is greater than or equal to standard.