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updated_aq600_rmd
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Data/aquifer_well/well_test_202509/TEMPEST_Aquifer_WellTest_202509_Data.Rmd

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title: "TEMPEST_Aquifer_WellTest_202509"
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author: "Stephanie J. Wilson"
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date: "2025-09-05"
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output: pdf_document
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output:
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pdf_document:
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latex_engine: xelatex
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---
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```{r setup, include=FALSE}
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library(lubridate)
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library(knitr)
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library(tibble)
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library(patchwork)
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```
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## Aquatroll (AQ600) Well Data
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```{r, echo=FALSE}
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cat("In Situ AQ600 was put in a bucket with the well outflow.
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Data was recorded every minute for the duration of the test.
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Missing points are from removing the AQ600 from the bucket to check transmission.")
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well_dat <- read.csv("COMPASS_TEMPEST_WellTest_AQ600_Data.csv")
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head(well_dat)
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#head(well_dat)
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#change column names in well_dat
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colnames(well_dat) <- c("Date_Time","pH", "pH_mV" ,"ORP_mV", "DO_mgL", "DO_Sat", "DO_pp", "Actual_Conductivity_µScm" ,
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filter(DO_mgL < 1) %>%
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filter(TDS_ppt > 0.10)
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#create a table of average concentrations:
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summary_stats <- well_dat_filtered %>%
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summarise(
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Salinity_psu_mean = mean(Salinity_psu, na.rm = TRUE),
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Salinity_psu_sd = sd(Salinity_psu, na.rm = TRUE),
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Sp_Conductivity_µScm_mean = mean(Specific_Conductivity_µScm, na.rm = TRUE),
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Sp_Conductivity_µScm_sd = sd(Specific_Conductivity_µScm, na.rm = TRUE),
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DO_mgL_mean = mean(DO_mgL, na.rm = TRUE),
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DO_mgL_sd = sd(DO_mgL, na.rm = TRUE),
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TDS_ppt_mean = mean(TDS_ppt, na.rm = TRUE),
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TDS_ppt_sd = sd(TDS_ppt, na.rm = TRUE)
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) %>%
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pivot_longer(
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everything(),
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names_to = c("Measurement", ".value"),
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names_sep = "_(?=[^_]+$)" # Split at last underscore
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) %>%
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mutate(mean = round(mean, 3),
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sd = round(sd, 3))
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kable(summary_stats)
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#plot Salinity
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sal <- ggplot()+
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geom_point(data=well_dat_filtered, aes(x=Date_Time, y=Salinity_psu), size=2, color="blue")+
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theme_bw()+ labs(x="Time", y="Salinity (psu)", title="Aquifer Salinity") + theme(legend.title = element_blank())
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sal
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#plot Conductivity
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cond <- ggplot()+
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geom_point(data=well_dat_filtered, aes(x=Date_Time, y=Specific_Conductivity_µScm), size=2, color="darkblue")+
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theme_bw()+ labs(x="Time", y="Specific Conductivity (µScm)", title="Aquifer Conductivity") + theme(legend.title = element_blank())
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cond
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sal + cond
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#plot DO
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do <- ggplot()+
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geom_point(data=well_dat_filtered, aes(x=Date_Time, y=DO_mgL), size=2, color="darkred")+
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theme_bw()+ labs(x="Time", y="Dissolved Oxygen (mg/L)", title="Aquifer Dissolved Oxygen") + theme(legend.title = element_blank())
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do
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#plot TDS
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tds <- ggplot()+
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geom_point(data=well_dat_filtered, aes(x=Date_Time, y=TDS_ppt), size=2, color="darkgreen")+
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theme_bw()+ labs(x="Time", y="Total Dissolved Solids (ppt))", title="Aquifer TDS") + theme(legend.title = element_blank())
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tds
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do + tds
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#create a table of average concentrations:
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summary_stats <- well_dat_filtered %>%
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summarise(
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Salinity_psu_mean = mean(Salinity_psu, na.rm = TRUE),
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Salinity_psu_sd = sd(Salinity_psu, na.rm = TRUE),
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Sp_Conductivity_µScm_mean = mean(Specific_Conductivity_µScm, na.rm = TRUE),
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Sp_Conductivity_µScm_sd = sd(Specific_Conductivity_µScm, na.rm = TRUE),
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DO_mgL_mean = mean(DO_mgL, na.rm = TRUE),
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DO_mgL_sd = sd(DO_mgL, na.rm = TRUE),
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TDS_ppt_mean = mean(TDS_ppt, na.rm = TRUE),
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TDS_ppt_sd = sd(TDS_ppt, na.rm = TRUE)
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) %>%
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pivot_longer(
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everything(),
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names_to = c("Measurement", ".value"),
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names_sep = "_(?=[^_]+$)" # Split at last underscore
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) %>%
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mutate(mean = round(mean, 3),
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sd = round(sd, 3))
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kable(summary_stats)
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```
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