This is a follow-up to my previous post Identifying and Determining the Average Rainfall Intensity of Precipitation Events and Associated Increases in Streamflow Part 1 - General - Posit Community.
From the previous post, I created a new tibble table with 227,455 observations, the first 100 of which are shown below.
observation Date Time Precipitation Discharge in_dry_spell rain_event
<int> <chr> <chr> <dbl> <dbl> <lgl> <dbl>
1 1 2010-05-01 0:00:00 0 0.299 TRUE NA
2 2 2010-05-01 0:15:00 0 0.302 TRUE NA
3 3 2010-05-01 0:30:00 0 0.305 TRUE NA
4 4 2010-05-01 0:45:00 0.2 0.308 FALSE 1
5 5 2010-05-01 1:00:00 0.2 0.312 FALSE 1
6 6 2010-05-01 1:15:00 0 0.317 FALSE 1
7 7 2010-05-01 1:30:00 0 0.321 FALSE 1
8 8 2010-05-01 1:45:00 0.2 0.326 FALSE 1
9 9 2010-05-01 2:00:00 0.4 0.33 FALSE 1
10 10 2010-05-01 2:15:00 0 0.339 FALSE 1
11 11 2010-05-01 2:30:00 0 0.352 FALSE 1
12 12 2010-05-01 2:45:00 0.2 0.38 FALSE 1
13 13 2010-05-01 3:00:00 0 0.41 FALSE 1
14 14 2010-05-01 3:15:00 0 0.428 FALSE 1
15 15 2010-05-01 3:30:00 0 0.424 FALSE 1
16 16 2010-05-01 3:45:00 0 0.419 FALSE 1
17 17 2010-05-01 4:00:00 0.2 0.415 FALSE 1
18 18 2010-05-01 4:15:00 0 0.41 FALSE 1
19 19 2010-05-01 4:30:00 0 0.411 FALSE 1
20 20 2010-05-01 4:45:00 0.6 0.412 FALSE 1
21 21 2010-05-01 5:00:00 0.4 0.414 FALSE 1
22 22 2010-05-01 5:15:00 0.2 0.415 FALSE 1
23 23 2010-05-01 5:30:00 0 0.416 FALSE 1
24 24 2010-05-01 5:45:00 0 0.44 FALSE 1
25 25 2010-05-01 6:00:00 0 0.459 FALSE 1
26 26 2010-05-01 6:15:00 0 0.465 FALSE 1
27 27 2010-05-01 6:30:00 0 0.495 FALSE 1
28 28 2010-05-01 6:45:00 0 0.495 FALSE 1
29 29 2010-05-01 7:00:00 0 0.495 FALSE 1
30 30 2010-05-01 7:15:00 0 0.495 FALSE 1
31 31 2010-05-01 7:30:00 0.2 0.495 FALSE 1
32 32 2010-05-01 7:45:00 0 0.495 TRUE NA
33 33 2010-05-01 8:00:00 0 0.471 TRUE NA
34 34 2010-05-01 8:15:00 0 0.453 TRUE NA
35 35 2010-05-01 8:30:00 0 0.44 TRUE NA
36 36 2010-05-01 8:45:00 0 0.431 TRUE NA
37 37 2010-05-01 9:00:00 0 0.422 TRUE NA
38 38 2010-05-01 9:15:00 0 0.423 TRUE NA
39 39 2010-05-01 9:30:00 0 0.423 TRUE NA
40 40 2010-05-01 9:45:00 0 0.424 TRUE NA
41 41 2010-05-01 10:00:00 0 0.424 TRUE NA
42 42 2010-05-01 10:15:00 0 0.425 TRUE NA
43 43 2010-05-01 10:30:00 0 0.425 TRUE NA
44 44 2010-05-01 10:45:00 0 0.426 TRUE NA
45 45 2010-05-01 11:00:00 0 0.427 TRUE NA
46 46 2010-05-01 11:15:00 0 0.427 TRUE NA
47 47 2010-05-01 11:30:00 0 0.428 TRUE NA
48 48 2010-05-01 11:45:00 0 0.428 TRUE NA
49 49 2010-05-01 12:00:00 0 0.429 TRUE NA
50 50 2010-05-01 12:15:00 0 0.429 TRUE NA
51 51 2010-05-01 12:30:00 0 0.43 TRUE NA
52 52 2010-05-01 12:45:00 0 0.43 TRUE NA
53 53 2010-05-01 13:00:00 0 0.431 TRUE NA
54 54 2010-05-01 13:15:00 0 0.431 TRUE NA
55 55 2010-05-01 13:30:00 0 0.432 TRUE NA
56 56 2010-05-01 13:45:00 0 0.432 TRUE NA
57 57 2010-05-01 14:00:00 0 0.433 TRUE NA
58 58 2010-05-01 14:15:00 0 0.433 TRUE NA
59 59 2010-05-01 14:30:00 0 0.434 TRUE NA
60 60 2010-05-01 14:45:00 0 0.434 TRUE NA
61 61 2010-05-01 15:00:00 0 0.435 TRUE NA
62 62 2010-05-01 15:15:00 0 0.441 TRUE NA
63 63 2010-05-01 15:30:00 0 0.471 TRUE NA
64 64 2010-05-01 15:45:00 0 0.527 TRUE NA
65 65 2010-05-01 16:00:00 0 0.565 TRUE NA
66 66 2010-05-01 16:15:00 0 0.562 TRUE NA
67 67 2010-05-01 16:30:00 0 0.559 TRUE NA
68 68 2010-05-01 16:45:00 0 0.556 TRUE NA
69 69 2010-05-01 17:00:00 0 0.552 TRUE NA
70 70 2010-05-01 17:15:00 0 0.665 TRUE NA
71 71 2010-05-01 17:30:00 0 0.892 TRUE NA
72 72 2010-05-01 17:45:00 0 0.941 TRUE NA
73 73 2010-05-01 18:00:00 0 0.937 TRUE NA
74 74 2010-05-01 18:15:00 0 0.933 TRUE NA
75 75 2010-05-01 18:30:00 0 0.928 TRUE NA
76 76 2010-05-01 18:45:00 0 0.924 TRUE NA
77 77 2010-05-01 19:00:00 0 0.843 TRUE NA
78 78 2010-05-01 19:15:00 0 0.812 TRUE NA
79 79 2010-05-01 19:30:00 0 0.765 TRUE NA
80 80 2010-05-01 19:45:00 0 0.729 TRUE NA
81 81 2010-05-01 20:00:00 0 0.693 TRUE NA
82 82 2010-05-01 20:15:00 0 0.672 TRUE NA
83 83 2010-05-01 20:30:00 0 0.644 TRUE NA
84 84 2010-05-01 20:45:00 0 0.617 TRUE NA
85 85 2010-05-01 21:00:00 0 0.611 TRUE NA
86 86 2010-05-01 21:15:00 0 0.591 TRUE NA
87 87 2010-05-01 21:30:00 0 0.578 TRUE NA
88 88 2010-05-01 21:45:00 0 0.569 TRUE NA
89 89 2010-05-01 22:00:00 0 0.559 TRUE NA
90 90 2010-05-01 22:15:00 0 0.55 TRUE NA
91 91 2010-05-01 22:30:00 0 0.54 TRUE NA
92 92 2010-05-01 22:45:00 0 0.538 TRUE NA
93 93 2010-05-01 23:00:00 0 0.536 TRUE NA
94 94 2010-05-01 23:15:00 0 0.534 TRUE NA
95 95 2010-05-01 23:30:00 0 0.532 TRUE NA
96 96 2010-05-01 23:45:00 0 0.53 TRUE NA
97 97 2010-05-02 0:00:00 0 0.528 TRUE NA
98 98 2010-05-02 0:15:00 0 0.526 TRUE NA
99 99 2010-05-02 0:30:00 3 0.524 FALSE 2
100 100 2010-05-02 0:45:00 0 0.521 TRUE NA```
In the table above, I have precipitation and discharge data in 15-minute intervals from 2010 until 2022. I used the precipitation data to identify individual rainfall events using a 4-hour intermittent dry period (i.e., any precipitation that fell within 4 hours of a previous event was considered the same event and any precipitation that fell with more than 4 hours since the previous event was considered a unique event. Using this criteria, I created a new column in the table called "rain_event" which numbered each unique event chronologically.
For each rainfall event, I now want to pull out the start date and time, end date and time, the total precipitation that had accumulated between the start date and time and the end date and time, the maximum discharge and the minimum discharge between the start date and time and the end date and time. I then want to put this data in a new table with the format
Rain_Event, StartDateTime, EndDateTime, TotalPrecipitation, MinimumDischarge, MaximumDischarge
Does anyone have any suggestions as to how to achieve this?
TIA