Read In Data

These functions read in concentration and flow data necessary for loads calculations. The two main functions for reading in data are ReadInData and ReadInDataFromR. The former function makes use of the internal ReadC and ReadQ functions for reading in external text files of concentration and flow respectively. The latter function assumes the data have already been read in as a dataframe with two columns (Date and concentration/flow) and will convert these into an object suitable for analysis with LRE.

ReadInData(dirnm = NULL, filenm, Cnames, OmitCzeros = FALSE, format)
ReadInDataFromR(x.C, x.Q)

ReadInDataFromR(x.C, x.Q)

Arguments

dirnm: The directory name where the files are stored, e.g. 'C:/Data/'
filenm: The name of the csv files where the concentration and flow data are stored. This should be a name common to both files with the extension _C and _Q representing the location of the concentration and flow data respectively. For example, filenm = "test" indicates that there is a test_C.csv and a test_Q.csv located in the specified dirnm directory.
Cnames: name of concentration variable
OmitCzeros: a logical value indicating whether zeros should be omitted in the concentration record. If missing, it is assumed that no zeros should be omitted from the record if they exist.
format: date format
x.C: concentration dataframe
x.Q: flow dataframe

Value

A list of class 'data' containing: Q Observed flow dataset Conc Observed concentration dataset Standard summary and plot functions apply.

Details

The ReadInData function reads in two comma delimited text files using the read.csv function. The first is a concentration dataset containing two columns: date and concentration measured in mg/L. The second is a flow dataset containing two columns: date and flow measured in cumecs.

The concentration and flow files will have a name common to both and are distinguished by a _C for concentration and a Q for flow. These need to be .csv files.

By default, if zeros exist in the concentration record, they will be left in the record. If they are to be removed then the OmitCzeros argument will need to be set to TRUE.

The ReadInDataFromR function reads in two R objects that are dataframes. The first is a concentration dataset containing two columns: date and concentration measured in mg/L. The second is a flow dataset containing two columns: date and flow measured in cumecs.

Note

Concentrations and flows measured in other formats will need to be converted prior to using this function and subsequent functions of the LRE package.

References

Kuhnert, P.M., Henderson, B.L., Lewis, S.E., Bainbridge, Z.T., Wilkinson, S.N. and Brodie, J.E. (2012) Quantifying total suspended sediment export from the Burdekin River catchment using the loads regression estimator tool, Water Resources Research, 48, W04533,doi:10.1029/2011WR011080.

Examples

# Reading in data from a file
# This function assumes you will have two csv files:
# burdR_Q.csv and burdR_C.csv representing
# flow and concentration files respectively
# The following script is not executed:
if (FALSE) { # \dontrun{
 # Reading in data from external files
 library(LRE)
 burdR <- ReadInData(dirnm = "C:/Files/", filenm = "burdR",
            Cnames = "TSS")
 } # }

# Reading in data already stored in R
library(LRE)
burdR <- ReadInDataFromR(x.C = burdRC, x.Q = burdRQ)
plot(burdR)
#> Warning: Removed 32 rows containing missing values or values outside the scale range
#> (`geom_point()`).

summary(burdR)
#> Flow Data:
#> ---------
#> Flow Collection Period: From  1973-12-02  to  2015-06-30 
#> No. of records:  15186   Average sampling frequency:  1 days 
#> Flow: 	 min=0 max=25482.8
#> 	 percentiles: 25th (10) 50th (22) 75th (74.17) 90th (451.99) 95th (1377.12) 97.5th (2906.43) 99th (6488.2)
#> 	 median=21.51
#> 	 mean=302.26
#> 
#> Concentration Data:
#> -------------------
#> Pollutant:  TSS
#> Concentration Collection Period: From  2006-01-26  to  2016-06-23 
#> No. of records:  461   Average sampling frequency:  713927 secs 
#> Concentration: 	 min=1 max=3060
#> 	 percentiles: 25th (28) 50th (135) 75th (313) 90th (451.99) 95th (812) 97.5th (1545) 99th (2304)
#> 	 median=135
#> 	 mean=264.49
#> 
hist(burdR)


 if (FALSE) { # \dontrun{
 # Reading in data from external files
 library(LRE)
 burdR <- ReadInData(dirnm = "C:/Files/", filenm = "burdR",
            Cnames = "TSS")


 } # }