EGRET (version 3.0.12)

populateDaily: Populate Daily data frame

Description

Using a data frame that has at least Date, Q, Qualifier, populates the rest of the basic Daily data frame used in EGRET analysis.

Usage

populateDaily(rawData, qConvert, verbose = TRUE, adjust = TRUE,
  fill = FALSE, maxgap = 21, fill_type = "interpolation")

Value

A data frame 'Daily' with the following columns:

Name	Type	Description
Q	numeric	Discharge in m^3/s
Julian	integer	Number of days since Jan. 1, 1850
Month	integer	Month of the year [1-12]
Day	integer	Day of the year [1-366]
DecYear	numeric	Decimal year
MonthSeq	integer	Number of months since January 1, 1850
Qualifier	character	Qualifying code
i	integer	Index of days, starting with 1
LogQ	numeric	Natural logarithm of Q
Q7	numeric	7 day running average of Q
Q30	numeric	30 day running average of Q

Arguments

rawData

dataframe contains at least Date, Q, Qualifier columns.

qConvert

numeric conversion to cubic meters per second.

verbose

logical specifying whether or not to display messages.

adjust

logical specifying whether or not to add a constant to zero values to allow log transformation. Defaults to TRUE.

fill

logical specifying whether to fill NA values by linear interpolation. Defaults to FALSE.

maxgap

Maximum number of NA days allowed for interpolating gaps. Default is 21. Only used if fill is set to TRUE.

fill_type

character to define what process to fill missing data. Options are "interpolation" - linear interpolation from the `zoo::na.approx`, or "log_interp" - linear interpolation in the log space. Only used if fill is set to TRUE.

Author

Robert M. Hirsch

See Also

readNWISDaily, readUserDaily

Examples

Date <- as.character(seq(from = as.Date("2001/1/1"),
                         to = as.Date("2002/1/2"),
                         by = "day"))
Q <- c(-1:365)
Qualifier <- rep("",367)
dataInput_complete <- data.frame(Date, Q, Qualifier)
dataInput <- dataInput_complete[-4:-5,]

# No fill, but with 0 and negative:
Daily <- populateDaily(dataInput, qConvert = 1)

# No negatives/zeros:
Q <- 2+sin(seq(from = 0, to = 2*pi, length.out = 367))
Q <- jitter(Q, factor = 500)
plot(Q, ylim = c(0, 3.2))
dataInput_complete <- data.frame(Date, Q, Qualifier)
# Remove some rows to test missing:
dataInput <- dataInput_complete[-4:-5,]
dataInput <- dataInput[-10:-20,]

# No fill:
Daily <- populateDaily(dataInput, qConvert = 1)
plot(Daily$Date[1:30], Daily$Q[1:30], type = "b", ylim = c(0, 3.2))

# Linear interpolation:
Daily_fill <- populateDaily(dataInput,
                            qConvert = 1,
                            fill = TRUE,
                            fill_type = "interpolation")
plot(Daily_fill$Date[1:30],
     Daily_fill$Q[1:30],
     col = as.factor(Daily_fill$Qualifier[1:30]),
     type = "b", pch = 16, ylim = c(0, 3.2),
     main = "Linear Interpolation")


# Add a gap that is too big do deal with:
dataInput <- dataInput_complete[-4:-20,]
dataInput <- dataInput[-200:-255,]

Daily_interp <- populateDaily(dataInput,
                              qConvert = 1,
                              fill = TRUE,
                              fill_type = "interpolation")
plot(Daily_interp$Date, Daily_interp$Q,
     col = as.factor(Daily_interp$Qualifier),
     main = "Linear Interpolation",
     type = "b", pch = 16, ylim = c(0, 3.2))
plot(Daily_interp$Date[1:50], Daily_interp$Q[1:50],
     col = as.factor(Daily_interp$Qualifier[1:50]),
     main = "Linear Interpolation",
     type = "b", pch = 16, ylim = c(0, 3.2))

Daily_log_interp <- populateDaily(dataInput,
                              qConvert = 1,
                              fill = TRUE,
                              fill_type = "log_interp")
plot(Daily_log_interp$Date, Daily_log_interp$Q,
     col = as.factor(Daily_log_interp$Qualifier),
     main = "Linear Interpolation in Log Scale",
     type = "b", pch = 16, ylim = c(0, 3.2))
plot(Daily_log_interp$Date[1:50], Daily_log_interp$Q[1:50],
     col = as.factor(Daily_log_interp$Qualifier[1:50]),
     main = "Linear Interpolation in Log Scale",
     type = "b", pch = 16, ylim = c(0, 3.2))


# Real data:
eList <- Choptank_eList
Daily_chop <- eList$Daily
df <- Daily_chop[,c("Date", "Q")]
df <- df[-2:-5, ]
df <- df[-100:-200,]
D2 <- populateDaily(df, 1, fill = TRUE)
plot(D2$Date[1:20], D2$Q[1:20],
     col = as.factor(D2$Qualifier[1:20]),
     main = "Linear Interpolation",
     type = "b", pch = 16)
plot(D2$Date[1:110], D2$Q[1:110],
     col = as.factor(D2$Qualifier[1:110]),
     main = "Linear Interpolation",
     type = "b", pch = 16)