Hourly precipitation data downloaded from DWD for monitoring station Braunschweig (id = 662) between 1997-10-22 and 2021-12-31, which were aggregated to daily values within R
Format
A data.frame with 8835 rows and 3 variables:
- year
year
- month
month
- days_in_month
days in month
- date_start
date start
- date_end
date end
- irrigation_area_sqm
irrigation area in squaremeter
- "groundwater.mmPerDay
irrigation using "groundwater" (mm/sqm)
- "clearwater.mmPerDay
irrigation using "clearwater" (mm/sqm)
)
Examples
if (FALSE) { # \dontrun{
install.packages(c("dplyr", "rdwd"))
library(dplyr)
rdwd::updateRdwd()
rdwd::findID("Braunschweig")
rdwd::selectDWD(name = "Braunschweig", res = "daily")
url_bs_rain <- rdwd::selectDWD(name = "Braunschweig",
res = "hourly",
var = "precipitation",
per = "historical" )
bs_rain <- rdwd::dataDWD(url_bs_rain)
precipitation_hourly <- rdwd::dataDWD(url_bs_rain) %>%
dplyr::select(.data$MESS_DATUM, .data$R1) %>%
dplyr::rename("datetime" = "MESS_DATUM",
"precipitation_mm" = "R1")
precipitation_daily <- precipitation_hourly %>%
dplyr::mutate("date" = as.Date(datetime)) %>%
dplyr::group_by(date) %>%
dplyr::summarise(rain_mm = sum(precipitation_mm))
} # }
head(flextreat.hydrus1d::precipitation_daily)
#> # A tibble: 6 × 2
#> date rain_mm
#> <date> <dbl>
#> 1 1997-10-22 0
#> 2 1997-10-23 0.1
#> 3 1997-10-24 0.5
#> 4 1997-10-25 0.3
#> 5 1997-10-26 0
#> 6 1997-10-27 0