Purpose: view EcoDrought stream temperature and flow data and download Daymet climate data (modeled air temperature).

2.1 Site information

Code 
siteinfo <- read_csv("data/EcoDrought_SiteInformation.csv")
datatable(siteinfo)
Code 
siteinfo_sp <- st_as_sf(siteinfo, coords = c("long", "lat"), crs = 4326)
mapview(siteinfo_sp, zcol = "designation")

2.2 Flow and temp data

Load data

Code 
dat <- read_csv("data/EcoDrought_FlowTempData_DailyWeekly.csv")
dat
# A tibble: 202,014 × 31
   station_no site_name      site_id basin   subbasin region   lat  long elev_ft
   <chr>      <chr>          <chr>   <chr>   <chr>    <chr>  <dbl> <dbl>   <dbl>
 1 12355347   Big Creek NWIS BIG     Flathe… Big Cre… Flat    48.6 -114.   3528.
 2 12355347   Big Creek NWIS BIG     Flathe… Big Cre… Flat    48.6 -114.   3528.
 3 12355347   Big Creek NWIS BIG     Flathe… Big Cre… Flat    48.6 -114.   3528.
 4 12355347   Big Creek NWIS BIG     Flathe… Big Cre… Flat    48.6 -114.   3528.
 5 12355347   Big Creek NWIS BIG     Flathe… Big Cre… Flat    48.6 -114.   3528.
 6 12355347   Big Creek NWIS BIG     Flathe… Big Cre… Flat    48.6 -114.   3528.
 7 12355347   Big Creek NWIS BIG     Flathe… Big Cre… Flat    48.6 -114.   3528.
 8 12355347   Big Creek NWIS BIG     Flathe… Big Cre… Flat    48.6 -114.   3528.
 9 12355347   Big Creek NWIS BIG     Flathe… Big Cre… Flat    48.6 -114.   3528.
10 12355347   Big Creek NWIS BIG     Flathe… Big Cre… Flat    48.6 -114.   3528.
# ℹ 202,004 more rows
# ℹ 22 more variables: area_sqmi <dbl>, designation <chr>, date <date>,
#   DischargeReliability <dbl>, TempReliability <dbl>, flow_mean <dbl>,
#   flow_min <dbl>, flow_max <dbl>, tempc_mean <dbl>, tempc_min <dbl>,
#   tempc_max <dbl>, flow_mean_filled <dbl>, flow_mean_cms <dbl>,
#   flow_mean_filled_cms <dbl>, area_sqkm <dbl>, Yield_mm <dbl>,
#   Yield_filled_mm <dbl>, flow_mean_7 <dbl>, flow_mean_filled_7 <dbl>, …

Unique basins

Code 
unique(dat$basin)
[1] "Flathead"       "West Brook"     "Donner Blitzen" "Paine Run"     
[5] "Piney River"    "Staunton River" "Shields River"  "Snake River"

2.2.1 View daily temp

2.2.2 View daily flow

2.3 Daymet data

Trim siteinfo to sites with temp/flow data

Code 
siteinfo_sub <- siteinfo %>% filter(site_name %in% unique(dat$site_name))

Download Daymet daily air temperature data for each site (point locations)

Code 
climlist <- vector("list", length = dim(siteinfo_sub)[1])
for (i in 1:dim(siteinfo_sub)[1]) {
  clim <- download_daymet(site = siteinfo_sub$site_name[i], lat = siteinfo_sub$lat[i], lon = siteinfo_sub$long[i], start = 2010, end = 2024, internal = T)
  climlist[[i]] <- tibble(clim$data) %>% 
    mutate(air_temp_mean = (tmax..deg.c. + tmin..deg.c.)/2, 
           date = as.Date(paste(year, yday, sep = "-"), "%Y-%j"),
           site_name = siteinfo_sub$site_name[i]) %>%
    select(12,2,11,10,4,6,3,5) %>% rename(precip_mmday = 5, swe_kgm2 = 6, daylength_sec = 7, shortrad_wm2 = 8)
  print(i)
}
climdf <- do.call(rbind, climlist)
write_csv(climdf, "data/Daymet_daily.csv")

Re-load Daymet climate data

Code 
climdf <- read_csv("data/Daymet_daily.csv")

Plot example Daymet time series data (2020-2025, Avery Brook, MA)

Code 
ggarrange(climdf %>% filter(site_name == "Avery Brook", year(date) >= 2020) %>% ggplot(aes(x = date, y = air_temp_mean)) + geom_line(),
          climdf %>% filter(site_name == "Avery Brook", year(date) >= 2020) %>% ggplot(aes(x = date, y = precip_mmday)) + geom_line(),
          climdf %>% filter(site_name == "Avery Brook", year(date) >= 2020) %>% ggplot(aes(x = date, y = swe_kgm2)) + geom_line(),
          climdf %>% filter(site_name == "Avery Brook", year(date) >= 2020) %>% ggplot(aes(x = date, y = daylength_sec)) + geom_line(),
          climdf %>% filter(site_name == "Avery Brook", year(date) >= 2020) %>% ggplot(aes(x = date, y = shortrad_wm2)) + geom_line(),
          ncol = 1)