Parallel

With {wildlandhydRo} it is really easy to get station data in parallel. The functions use the {furrr} framework and will work by planning a session prior to calling the function. Below is a quick benchmark between the options; regular (np) or parallel (para).

library(wildlandhydRo)
library(microbenchmark)
library(dataRetrieval)

sites <- dataRetrieval::whatNWISsites(stateCd='MT', parameterCd = '00060') %>% 
  filter(nchar(site_no) <= 8)

tm <- microbenchmark(
 'np' = {
   batch_USGSdv(sites = sites[1:50,]$site_no, parallel = FALSE)},
 'para' = {
   future::plan('multisession')
   batch_USGSdv(sites = sites[1:50,]$site_no, parallel = TRUE)},
 times = 10
)

tm

autoplot(tm)

You can do this for most functions in the package, e.g. batch_*(), wym*(), ym*(), get_Basin(), etc.

Annual and Monthly Stats

With the package you can get monthly, annual and monthly-annual statistics for a snotel or usgs sites. You can provide a previously create batch_*() data.frame or the station id. This creates/mungs the results of the daily values to generate mean, maximum, median and standard deviation per water year or per water year per month. It also includes peaks from dataRetrieval::readNWISpeak(); annual base-flow (tp = 0.9, window = 5) and Base-flow Index (BFI) (total-flow/base-flow) from baseflow; annual coefficient of variance (sd of flow/mean of flow); and normalization methods Flow/drainage area, Flow/(all time mean flow) and Flow/log(standard deviation). The window for all the methods are annual, e.g. 1. This leaves it up to the user to explore different windows if inclined. Monthly stats

water_year <- wyUSGS(sites = '12304500')
ggplot(water_year, aes(peak_dt, Peak)) + 
  geom_line() +
  labs(title = 'Peak Flow per Water Year', 
       subtitle = paste0(water_year %>% slice(n=1) %>% .$Station))

monthly <- wymUSGS(sites = '12304500')
ggplot(monthly, aes(year_month, coef_var)) +
  geom_line() +
  labs(title = 'Monthly Coefficient of Variance', 
       subtitle = paste0(monthly %>% slice(n=1) %>% .$Station))

Get Percentiles for Reporting

You can also just generate percentiles for daily values or months.

• Daily

yaak_dv <- batch_USGSdv(sites = '12304500')

usgs_rep <- reportUSGSdv(procDV = yaak_dv, days = 60)

plot_reportUSGS(usgs_rep)

• Monthly

usgs_rep_month <- reportUSGSmv(procDV = yaak_dv)

plot_reportUSGS(usgs_rep_month %>% filter(year_nu >2020), time = 'month')

Get a Drain Point

Sometimes you just want to get the drainage area above a point and then do some other things. With get_Basin() function you just have to provide a sf point and it will return the basin. If you want zonal stats associated with that drainage area then just use get_BasinStats().

• Basin

pt <- tibble(lon = -114.36, lat = 48.92)
pt <- sf::st_as_sf(pt, coords = c('lon', 'lat'))

basin <- get_Basin(pt)

ggplot() + geom_sf(data = basin)

• Basin Stats

basin_stats <- get_BasinStats(basin)

basin_stats %>% sf::st_drop_geometry() %>% 
  pivot_longer(cols = c('TOT_PET', 'TOT_BFI', 'TOT_TWI')) %>% 
  select(name, value, comid) %>% 
  right_join(basin_stats, by ='comid') %>% sf::st_as_sf() %>% 
  ggplot() + 
  geom_sf(aes(fill = value)) +
    facet_wrap(~name, nrow = 3) + theme_void()