Inflow and outflow
Sam Bashevkin
2023-07-31
library(tidyverse)
library(here)Display R and package versions:
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## setting value
## version R version 4.2.3 (2023-03-15 ucrt)
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## language (EN)
## collate English_United States.utf8
## ctype English_United States.utf8
## tz America/Los_Angeles
## date 2023-07-31
## pandoc 3.1.1 @ C:/Program Files/RStudio/resources/app/bin/quarto/bin/tools/ (via rmarkdown)
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## ──────────────────────────────────────────────────────────────────────────────Data prep
# Import Delta Inflow and Outflow data from Dayflow
dayflow <- readRDS(here("data/processed/hydrology/dayflow.rds"))
# Prepare Dayflow data for plots
dayflow_c <- dayflow %>%
mutate(
Period_year_cat = factor(Period_year_cat, levels = c("1", "2", "3+")),
Drought = factor(
Drought,
levels = c("D", "N", "W"),
labels = c("Drought", "Neutral", "Wet")
)
)Inflow plots
Total inflow seasonal hydrograph by year
dayflow_c %>%
ggplot(aes(x = WYday, y = InflowTotal, color = Period_year_cat, group = WaterYear)) +
geom_smooth(method = "gam", formula = y ~ s(x, bs = "cs", k = 25)) +
facet_grid(rows = vars(Drought), scales = "free_y") +
scale_color_viridis_d(name = "Period-year") +
coord_cartesian(ylim = c(0, NA), expand = FALSE) +
theme_bw()
Total inflow seasonal hydrograph by Period_year
dayflow_c %>%
ggplot(aes(x = WYday, y = InflowTotal, color = Period_year_cat, group = Period_year_cat)) +
geom_smooth(method = "gam", formula = y ~ s(x, bs = "cs", k = 25)) +
facet_grid(rows = vars(Drought), scales = "free_y") +
scale_color_viridis_d(name = "Period-year") +
scale_x_continuous(
name = "Day of Water Year",
breaks = seq.int(0, 360, by = 60),
expand = expansion(mult = 0.005)
) +
scale_y_continuous(limits = c(0, NA), expand = expansion()) +
theme_bw()
Total inflow seasonal hydrograph by Period_year, scaled by summed inflow over the year
dayflow_c %>%
ggplot(aes(x = WYday, y = InflowTotal / InflowTotal_sum, color = Period_year_cat)) +
geom_smooth(method = "gam", formula = y ~ s(x, bs = "cs", k = 25)) +
facet_grid(rows = vars(Drought)) +
scale_color_viridis_d(name = "Period-year") +
scale_x_continuous(
name = "Day of Water Year",
breaks = seq.int(0, 360, by = 60),
expand = expansion(mult = 0.005)
) +
scale_y_continuous(limits = c(0, NA), expand = expansion()) +
theme_bw()
Total cumulative inflow seasonal hydrograph by Period_year
plt_inflow_wyday <- dayflow_c %>%
ggplot(
aes(
x = WYday,
y = InflowTotal_cum / InflowTotal_sum,
color = Period_year_cat,
group = WaterYear,
linetype = Period_year_cat
)
) +
geom_line() +
facet_grid(rows = vars(Drought), scales = "free_y") +
scale_color_viridis_d(name = "Period-year") +
scale_linetype(name = "Period-year") +
scale_x_continuous(
name = "Day of Water Year",
breaks = seq.int(0, 360, by = 60),
expand = expansion(mult = 0.005)
) +
scale_y_continuous(
name = "Cumulative proportional inflow",
limits = c(0, NA),
expand = expansion()
) +
theme_bw() +
theme(panel.spacing = unit(1, "lines"))
plt_inflow_wyday
This shows most clearly how in dry years, after 2+ years of a drought, water managers are more conservative early in the water year, saving up whatever rainfall they can. But in wet years after 2+ years of a wet period, the reservoirs are full and much more water is released earlier in the water year. Neutral years show no pattern, as expected since they represent flip-flopping among year types.
Same plot as above, but smoothed for each Period_year and drought category combo
dayflow_c %>%
ggplot(
aes(
x = WYday,
y = InflowTotal_cum / InflowTotal_sum,
color = Period_year_cat,
fill = Period_year_cat,
linetype = Period_year_cat
)
) +
geom_smooth(method = "gam", formula = y ~ s(x, bs = "cs", k = 25), alpha = 0.5) +
facet_grid(rows = vars(Drought), scales = "free_y") +
scale_color_viridis_d(aesthetics = c("color", "fill"), name = "Period-year") +
scale_linetype(name = "Period-year") +
scale_x_continuous(
name = "Day of Water Year",
breaks = seq.int(0, 360, by = 60),
expand = expansion(mult = 0.005)
) +
scale_y_continuous(
name = "Cumulative proportional inflow",
limits = c(0, NA),
expand = expansion()
) +
theme_bw()
Outflow plots
Total cumulative outflow seasonal hydrograph by Period_year
plt_outflow_wyday <- dayflow_c %>%
ggplot(
aes(
x = WYday,
y = Outflow_cum / Outflow_sum,
color = Period_year_cat,
group = WaterYear,
linetype = Period_year_cat
)
) +
geom_line() +
facet_grid(rows = vars(Drought), scales = "free_y") +
ylab("Cumulative proportional outflow") +
scale_color_viridis_d(name = "Period-year") +
scale_linetype(name = "Period-year") +
scale_x_continuous(
name = "Day of Water Year",
breaks = seq.int(0, 360, by = 60),
expand = expansion(mult = 0.005)
) +
scale_y_continuous(
name = "Cumulative proportional outflow",
limits = c(0, NA),
expand = expansion()
) +
theme_bw() +
theme(panel.spacing = unit(1, "lines"))
plt_outflow_wyday
Export Figures
# Define file path for manuscript figures
fp_plots <- here("results/figures")
# Cumulative inflow figure
ggsave(
file.path(fp_plots, "cumul_inflow_wyday.jpg"),
plot = plt_inflow_wyday,
width = 6,
height = 4,
units = "in",
dpi = 300
)
# Cumulative outflow figure
ggsave(
file.path(fp_plots, "cumul_outflow_wyday.jpg"),
plot = plt_outflow_wyday,
width = 6,
height = 4,
units = "in",
dpi = 300
)