select rainfall events and calculate rainfall event total from time series data

1library(dplyr)
2
3# Set data column as POSIXct, important for calculating duration afterwards
4data <- data %>% mutate(DateTime = as.POSIXct(DateTime, format = '%m/%d/%Y %H:%M'))
5
6flags <- data %>% 
7  # Set a rain flag if there is rain registered on the gauge
8  mutate(rainflag = ifelse(Precip_in > 0, 1, 0)) %>% 
9  # Create a column that contains the number of consecutive times there was rain or not.
10  # Use `rle`` which indicates how many times consecutive values happen, and `rep`` to repeat it for each row.
11  mutate(rainlength = rep(rle(rainflag)$lengths, rle(rainflag)$lengths)) %>% 
12  # Set a flag for an event happening, when there is rain there is a rain event, 
13  # when it is 0 but not for six consecutive times, it is still a rain event
14  mutate(
15    eventflag = ifelse(
16      rainflag == 1, 
17      1, 
18      ifelse(
19        rainflag == 0 & rainlength < 6, 
20        1, 
21        0
22      )
23    )
24  ) %>% 
25  # Correct for the case when the dataset starts with no rain for less than six consecutive times
26  # If within the first six rows there is no rain registered, then the event flag should change to 0
27  mutate(eventflag = ifelse(row_number() < 6 & rainflag == 0, 0, eventflag)) %>% 
28  # Add an id to each event (rain or not), to group by on the pivot table
29  mutate(eventid = rep(seq(1,length(rle(eventflag)$lengths)), rle(eventflag)$lengths))
30
31rain_pivot <- flags %>% 
32  # Select only the rain events
33  filter(eventflag == 1) %>% 
34  # Group by id
35  group_by(eventid) %>% 
36  summarize(
37    precipitation = sum(Precip_in),
38    eventStart = first(DateTime),
39    eventEnd = last(DateTime)
40  ) %>% 
41  # Compute time difference as duration of event, add 1 hour, knowing that the timestamp is the time when the rain record ends
42  mutate(time = as.numeric(difftime(eventEnd,eventStart, units = 'h')) + 1)
43
44rain_pivot
45#> # A tibble: 2 x 5
46#>   eventid precipitation eventStart          eventEnd             time
47#>     <int>         <dbl> <dttm>              <dttm>              <dbl>
48#> 1       2          0.07 2017-10-06 17:00:00 2017-10-06 22:00:00     6
49#> 2       4          0.01 2017-10-07 15:00:00 2017-10-07 15:00:00     1
50