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snowtellllllr.R
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library(snotelr)
library(tidyverse)
meta <-snotel_info()
NV <-filter(meta, state == "NV")
elko <-filter(NV, county == "Elko")
CA <-filter(meta, state == "CA")
lam <-as.data.frame(snotel_download(site_id = 570, path = tempdir(), internal = TRUE))
lam_wy2018 <-filter(lam, date > "2017-09-30" & date < "2028-10-01")
lam_wy2019 <-filter(lam, date > "2018-09-30" & date < "2029-10-01")
lam_wy2020 <-filter(lam, date > "2019-09-30" & date < "2020-10-01")
lam_wy2021 <-filter(lam, date > "2020-09-30" & date < "2021-10-01")
ggplot()+
geom_point(lam_wy2020, mapping = aes(x = date, y = snow_water_equivalent,))+
geom_point(lam_wy2021, mapping = aes(x = date, y = snow_water_equivalent,))+
geom_point(lam_wy2019, mapping = aes(x = date, y = snow_water_equivalent,))+
geom_point(lam_wy2018, mapping = aes(x = date, y = snow_water_equivalent,))
# downloading snotel data, SWE[mm] and temp[Degrees C]
indy_camp <- snotel_download(site_id = 539, internal = TRUE)
indy_creek <- snotel_download(site_id = 540, internal = TRUE)
indy_lake <- snotel_download(site_id = 541, internal = TRUE)
css_lab <- snotel_download(site_id = 428, internal = TRUE)
### seperating out the data for a specific time
ilake_wy2020 <- filter(indy_lake, date > "2019-09-30", date < "2020-10-30")
icamp_wy2020 <- filter(indy_camp, date > "2019-09-30", date < "2020-10-30")
icreek_wy2020 <- filter(indy_creek, date > "2019-09-30", date < "2020-10-30")
css_wy2020 <- filter(css_lab, date > "2019-09-30", date < "2020-10-30")
theme_set(theme_light(base_size =11))
wy2020<- ggplot() +
geom_line(ilake_wy2020, color="blue", mapping = aes(x = as.Date(date), y = snow_water_equivalent)) +
geom_line(icamp_wy2020, color="red", mapping = aes(x = as.Date(date), y = snow_water_equivalent)) +
geom_line(icreek_wy2020, color="purple", mapping = aes(x = as.Date(date), y = snow_water_equivalent)) +
geom_line(css_wy2020, color="green", mapping = aes(x = as.Date(date),y = snow_water_equivalent)) +
labs(title="Independence SNOTELs 2019-20 SWE", y="SWE (mm)", x="Date")
print(wy2020)
# so far this year
### seperating out the data for a specific time
ilake_wy2021 <- filter(indy_lake, date > "2020-09-30", date < "2021-10-30")
icamp_wy2021 <- filter(indy_camp, date > "2020-09-30", date < "2021-10-30")
icreek_wy2021 <- filter(indy_creek, date > "2020-09-30", date < "2021-10-30")
css_wy2021 <- filter(css_lab, date > "2020-09-30", date < "2021-10-30")
theme_set(theme_light(base_size =11))
wy2021<- ggplot() +
geom_line(ilake_wy2021, color="goldenrod", mapping = aes(x = as.Date(date), y = snow_water_equivalent)) +
geom_line(icamp_wy2021, color="firebrick", mapping = aes(x = as.Date(date), y = snow_water_equivalent)) +
geom_line(icreek_wy2021, color="purple", mapping = aes(x = as.Date(date), y = snow_water_equivalent)) +
geom_line(css_wy2021, color="black", mapping = aes(x = as.Date(date),y = snow_water_equivalent)) +
labs(title="north lake SNOTELs wy2021 SWE", y="SWE (mm)", x="Date")
print(wy2021)