`R/screen_flow_data.R`

`screen_flow_data.Rd`

Calculates means, medians, maximums, minimums, standard deviations of annual flows and data availability and missing data statistics, and symbol counts (if column exists) for each year and month of each year. Calculates the statistics from all daily discharge values from all years, unless specified. Returns a tibble with statistics.

```
screen_flow_data(
data,
dates = Date,
values = Value,
groups = STATION_NUMBER,
symbols = "Symbol",
station_number,
roll_days = 1,
roll_align = "right",
water_year_start = 1,
start_year,
end_year,
months = 1:12,
transpose = FALSE,
include_symbols = TRUE
)
```

- data
Data frame of daily data that contains columns of dates, flow values, and (optional) groups (e.g. station numbers). Leave blank or set to

`NULL`

if using`station_number`

argument.- dates
Name of column in

`data`

that contains dates formatted YYYY-MM-DD. Only required if dates column name is not 'Date' (default). Leave blank or set to`NULL`

if using`station_number`

argument.- values
Name of column in

`data`

that contains numeric flow values, in units of cubic metres per second. Only required if values column name is not 'Value' (default). Leave blank if using`station_number`

argument.- groups
Name of column in

`data`

that contains unique identifiers for different data sets, if applicable. Only required if groups column name is not 'STATION_NUMBER'. Function will automatically group by a column named 'STATION_NUMBER' if present. Remove the 'STATION_NUMBER' column beforehand to remove this grouping. Leave blank if using`station_number`

argument.- symbols
Name of column in

`data`

that contains symbols. Only required if symbols column name is not 'Symbol' (default). Leave blank or set to`NULL`

if using`station_number`

argument.- station_number
Character string vector of seven digit Water Survey of Canada station numbers (e.g.

`"08NM116"`

) of which to extract daily streamflow data from a HYDAT database. Requires`tidyhydat`

package and a HYDAT database. Leave blank if using`data`

argument.- roll_days
Numeric value of the number of days to apply a rolling mean. Default

`1`

.- roll_align
Character string identifying the direction of the rolling mean from the specified date, either by the first (

`'left'`

), last (`'right'`

), or middle (`'center'`

) day of the rolling n-day group of observations. Default`'right'`

.- water_year_start
Numeric value indicating the month (

`1`

through`12`

) of the start of water year for analysis. Default`1`

.- start_year
Numeric value of the first year to consider for analysis. Leave blank or set well before start date (i.e.

`1800`

) to use from the first year of the source data.- end_year
Numeric value of the last year to consider for analysis. Leave blank or set well after end date (i.e.

`2100`

) to use up to the last year of the source data.- months
Numeric vector of months to include in analysis. For example,

`3`

for March,`6:8`

for Jun-Aug or`c(10:12,1)`

for first four months (Oct-Jan) when`water_year_start = 10`

(Oct). Default summarizes all months (`1:12`

).- transpose
Logical value indicating whether to transpose rows and columns of results. Default

`FALSE`

.- include_symbols
Logical. Include columns of counts of symbol categories from the symbols column.

A tibble data frame with the following columns:

- Year
calendar or water year selected

- n_days
number of days per year

- n_Q
number of days per year with flow data

- n_missing_Q
number of days per year with no flow data

- No_Symbol
number of days with no symbol category, if include_symbol=TRUE

- x_Symbol
number of days with a specific symbol category (x) from symbols column, if include_symbol=TRUE

- Maximum
annual maximum of all daily flows for a given year

- Mean
annual mean of all daily flows for a given year

- Median
annual median of all daily flows for a given year

- StandardDeviation
annual 1 standard deviation of all daily flows for a given year

and the following monthly missing columns (order will depend on water_year_month):

- Jan_missing_Q
number of Jan days per year with no flow data

- Feb_missing_Q
number of Feb days per year with no flow data

- Mar_missing_Q
number of Mar days per year with no flow data

- Apr_missing_Q
number of Apr days per year with no flow data

- May_missing_Q
number of May days per year with no flow data

- Jun_missing_Q
number of Jun days per year with no flow data

- Jul_missing_Q
number of Jul days per year with no flow data

- Aug_missing_Q
number of Aug days per year with no flow data

- Sep_missing_Q
number of Sep days per year with no flow data

- Oct_missing_Q
number of Oct days per year with no flow data

- Nov_missing_Q
number of Nov days per year with no flow data

- Dec_missing_Q
number of Dec days per year with no flow data

Transposing data creates a column of "Statistics" and subsequent columns for each year selected.

```
# Run if HYDAT database has been downloaded (using tidyhydat::download_hydat())
if (file.exists(tidyhydat::hy_downloaded_db())) {
# Calculate screening statistics using data frame and data argument with defaults
flow_data <- tidyhydat::hy_daily_flows(station_number = "08NM116")
screen_flow_data(data = flow_data)
# Calculate screening statistics using station_number argument with defaults
screen_flow_data(station_number = "08NM116")
# Calculate screening statistics for water years starting in October
screen_flow_data(station_number = "08NM116",
water_year_start = 9)
# Calculate screening statistics for 7-day flows for July-September months only
screen_flow_data(station_number = "08NM116",
roll_days = 7,
months = 7:9)
}
#> # A tibble: 72 × 16
#> STATION_…¹ Year n_days n_Q n_mis…² E_Sym…³ No_Sy…⁴ A_Sym…⁵ Minimum Maximum
#> <chr> <dbl> <int> <int> <int> <int> <int> <int> <dbl> <dbl>
#> 1 08NM116 1949 92 92 0 5 87 0 0.838 4.29
#> 2 08NM116 1950 92 92 0 0 92 0 0.714 16.6
#> 3 08NM116 1951 92 92 0 0 92 0 0.629 8.80
#> 4 08NM116 1952 92 92 0 0 92 0 1.11 12.9
#> 5 08NM116 1953 92 92 0 0 92 0 0.821 24.1
#> 6 08NM116 1954 92 92 0 0 92 0 1.98 30.5
#> 7 08NM116 1955 92 92 0 0 92 0 0.396 19.9
#> 8 08NM116 1956 92 92 0 0 92 0 0.784 8.21
#> 9 08NM116 1957 92 92 0 0 92 0 0.916 6.23
#> 10 08NM116 1958 92 92 0 0 92 0 0.578 5.51
#> # … with 62 more rows, 6 more variables: Mean <dbl>, Median <dbl>,
#> # StandardDeviation <dbl>, Jul_missing_Q <int>, Aug_missing_Q <int>,
#> # Sep_missing_Q <int>, and abbreviated variable names ¹STATION_NUMBER,
#> # ²n_missing_Q, ³E_Symbol, ⁴No_Symbol, ⁵A_Symbol
```