Chlorophyll attainment

library(tidyverse)
library(here)
library(tbeptools)
library(patchwork)

data(epcdata)
epcdata$epchc_station <- as.character(epcdata$epchc_station)

pinchldat <- read.table(here('data-raw/_WIN_WAVES_GUEST_20250613105203_93062.txt'), sep = '|', header = TRUE, skip = 9) |> 
  mutate(
    date = as.Date(lubridate::mdy_hms(Activity.Start.Date.Time)),
    yr = year(date),
    mo = month(date),
    bay_segment = 'OTB',
    strata = gsub('(^E\\d)\\-.*$', '\\1', Monitoring.Location.ID), 
    var = case_when(
      DEP.Analyte.Name == 'Chlorophyll a- uncorrected' ~ 'chla_uncorr', 
      DEP.Analyte.Name == 'Chlorophyll a- corrected' ~ 'chla_corr'
    )
  ) |> 
  select(
    date,
    yr,
    mo,
    bay_segment,
    strata,
    station = Monitoring.Location.ID,
    lat = DEP.Latitude,
    lon = DEP.Longitude,
    var,
    val = DEP.Result.Value.Number
  ) |> 
  pivot_wider(names_from = var, values_from = val)

Chlorophyll target attainment

trgattain <- targets |> 
  mutate(chla_thresh = 8.5)

# chlorophyll epc only target attainment

p1 <- show_wqmatrix(epcdata, bay_segment = 'OTB', yrrng = c(2018, 2024), param = 'chla', trgs = trgattain) + 
  labs(
    subtitle = 'EPCHC'
  )

# chlorophyll target attainment, pinellas uncorrected

tocmb <- pinchldat |>
  select(-chla_corr) |>
  rename(
    chla = chla_uncorr,
    epchc_station = station
  ) |>
  mutate(sd_m = 1)

p2 <- show_wqmatrix(tocmb, bay_segment = 'OTB', yrrng = c(2018, 2024), param = 'chla', trgs = trgattain) +
  labs(
    subtitle = 'PDEM uncorrected'
  )

# chlorophyll target attainment, pinellas corrected

tocmb <- pinchldat |>
  select(-chla_uncorr) |>
  rename(
    chla = chla_corr,
    epchc_station = station
  ) |>
  mutate(sd_m = 1)

p3 <- show_wqmatrix(tocmb, bay_segment = 'OTB', yrrng = c(2018, 2024), param = 'chla', trgs = trgattain) +
  labs(
    subtitle = 'PDEM corrected'
  )

# chlorophyll target attainment, epc, pinellas uncorrected

tocmb <- pinchldat |> 
  select(-chla_corr) |> 
  rename(
    chla = chla_uncorr, 
    epchc_station = station
  ) |> 
  mutate(sd_m = 1)

cmbdat <- bind_rows(epcdata, tocmb)

p4 <- show_wqmatrix(cmbdat, bay_segment = 'OTB', yrrng = c(2018, 2024), param = 'chla', trgs = trgattain) + 
  labs(
    subtitle = 'EPCHC,\nPDEM uncorrected'
  )

# chlorophyll target attainment, epc, pinellas corrected

tocmb <- pinchldat |> 
  select(-chla_uncorr) |> 
  rename(
    chla = chla_corr, 
    epchc_station = station
  ) |> 
  mutate(sd_m = 1)

cmbdat <- bind_rows(epcdata, tocmb)

p5 <- show_wqmatrix(cmbdat, bay_segment = 'OTB', yrrng = c(2018, 2024), param = 'chla', trgs = trgattain) + 
  labs(
    subtitle = 'EPCHC,\nPDEM corrected'
  )

p <- p1 + p2 + p3 + p4 + p5 + plot_layout(ncol = 5) & theme(plot.subtitle = element_text(size = 10))
p

Chlorophyll threshold attainment

# chlorophyll epc only threshold attainment

p1 <- show_wqmatrix(epcdata, bay_segment = 'OTB', yrrng = c(2018, 2024), param = 'chla') + 
  labs(
    subtitle = 'EPCHC'
  )
# chlorophyll threshold attainment, pinellas uncorrected

tocmb <- pinchldat |> 
  select(-chla_corr) |> 
  rename(
    chla = chla_uncorr, 
    epchc_station = station
  ) |> 
  mutate(sd_m = 1)

p2 <- show_wqmatrix(tocmb, bay_segment = 'OTB', yrrng = c(2018, 2024), param = 'chla') + 
  labs(
    subtitle = 'PDEM uncorrected'
  )

# chlorophyll thresold attainment, pinellas corrected

tocmb <- pinchldat |> 
  select(-chla_uncorr) |> 
  rename(
    chla = chla_corr, 
    epchc_station = station
  ) |> 
  mutate(sd_m = 1)

p3 <- show_wqmatrix(tocmb, bay_segment = 'OTB', yrrng = c(2018, 2024), param = 'chla') + 
  labs(
    subtitle = 'PDEM corrected'
  )

# chlorophyll threshold attainment, epc, pinellas uncorrected

tocmb <- pinchldat |> 
  select(-chla_corr) |> 
  rename(
    chla = chla_uncorr, 
    epchc_station = station
  ) |> 
  mutate(sd_m = 1)

cmbdat <- bind_rows(epcdata, tocmb)

p4 <- show_wqmatrix(cmbdat, bay_segment = 'OTB', yrrng = c(2018, 2024), param = 'chla') + 
  labs(
    subtitle = 'EPCHC,\nPDEM uncorrected'
  )

# chlorophyll thresold attainment, epc, pinellas corrected

tocmb <- pinchldat |> 
  select(-chla_uncorr) |> 
  rename(
    chla = chla_corr, 
    epchc_station = station
  ) |> 
  mutate(sd_m = 1)

cmbdat <- bind_rows(epcdata, tocmb)

p5 <- show_wqmatrix(cmbdat, bay_segment = 'OTB', yrrng = c(2018, 2024), param = 'chla') + 
  labs(
    subtitle = 'EPCHC,\nPDEM corrected'
  )

p <- p1 + p2 + p3 + p4 + p5 + plot_layout(ncol = 5) & theme(plot.subtitle = element_text(size = 10))
p