NWM data is extracted as hourly values.
To aggregate hourly data to different time chunks the nwmHistoric package offers a family of aggregate functions.
Each of these begins with the prefix 'aggregate_' and is followed by the date symbol to aggregate to.
| Symbol | Aggregate |
| y | year |
| m | month |
| d | day |
| j | julien day |
| s | season |
| wy | water year |
aggregate_m(rawData, fun = "mean", na.rm = TRUE)
| rawData | data extracted with |
|---|---|
| fun | function to be applied to the flows column default = 'mean' |
| na.rm | a logical value indicating whether NA values should be stripped before the computation proceeds. |
Other aggregate functions:
aggregate_dowy(),
aggregate_j(),
aggregate_record(),
aggregate_s(),
aggregate_wymd(),
aggregate_wym(),
aggregate_wys(),
aggregate_wy(),
aggregate_yj(),
aggregate_ymd(),
aggregate_ym(),
aggregate_ys(),
aggregate_y()
if (FALSE) { # Get flow record for COMID 101 flows = readNWMdata(comid = 101) # Aggregate to yearly average (y) yearly = aggregate_y(flows, fun = 'mean') # Aggregate to monthly # minimum and maximum per year (ym) ym = aggregate_ym(flows, fun = list(min, max)) # Aggregate to seasonal 95th percetile # with using custom function s95 = aggregate_s(flows, fun = function(x){quantile(x,.95)}) }