In goertler/inundation: Calculate Delta Inundation Metrics

knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)

library(inundation)
library(ggplot2)
library(patchwork)
library(scales)

These plots show annual inundation data, including the Fremont weir height, Yolo bypass dayflow, and the number of inundation days.

Note that strange Sacramento River height values in 1989, 1990 and 1991 (39.98 & 39.91) are ~4 ft higher than any other starting inundation day in the time series. We leave these in the dataset, but users may want to check with CDEC FRE or look into water operations in those years for a possible water transfer.

#load data
all_flows <- calc_inundation()

# add year
head(all_flows)
all_flows <- within(all_flows, year <- format(all_flows$date, "%Y"))

colors_yolo <- c("#469990","#f032e6")
breaks_yolo <- c(0, 4000, 500000)
limits_yolo <- c(0, 500000)
values_yolo <- scales::rescale(c(0, 4000, 500000), 
                               from = c(0, 500000))

# sac weir

colors_sac <- c('#dcbeff','#42d4f4','#3cb44b')
breaks_sac <- c(2, 32, 33.5)
limits_sac <- c(2, 42)
values_sac <- scales::rescale(c(2, 32, 42), 
                              from = c(2, 42))

theme_border <- theme_gray() + 
  theme(plot.background = element_rect(fill = NA, colour = 'black', size = 3))

for (i in unique(all_flows$year)){
    temp_dat <- all_flows[all_flows$year == i,]


    p1 <- ggplot() +
        geom_point(data = temp_dat, mapping = aes(x = date, y = height_sac, color = height_sac)) +
        scale_color_stepsn(colours = colors_sac,
                           breaks = breaks_sac,
                           limits = limits_sac,
                           values = values_sac) +
        geom_point(data = temp_dat, mapping = aes(x = date, y = inund_days + 10, size = inund_days)) +
        scale_size(range = c(0,1), guide = "none") +
        scale_y_continuous("Fremont Weir Height", sec.axis = sec_axis(~ . -10, name = "Number of Inundation Days")) +
        labs(x = "", title = i, color = "Yolo Bypass Dayflow") +
        theme_classic()


    p2 <- ggplot() +
        geom_point(data = temp_dat, mapping = aes(x = date, y = yolo_dayflow, color = yolo_dayflow)) +
        scale_color_stepsn(colours = colors_yolo,
                           breaks = breaks_yolo,
                           limits = limits_yolo,
                           values = values_yolo) +
        ylim(c(0, 10000)) +
        theme_classic() +
        labs(x = "", y = "Yolo Bypass Dayflow", color = "Yolo Bypass Dayflow")

    print(p1 + p2 + plot_layout(ncol=1) + plot_annotation(theme = theme_border))
}