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app.R
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###############################################################################.
# TITLE: app.R (WAVE SHINY APP)
# DESCRIPTION: This Shiny App contains the "master" script for the app. The app contains a ui and server component
# and sources R scripts from the App folder
# AUTHOR(S): Dan Crocker and Nick Zinck
# DATE LAST UPDATED: 2022-01-20
# GIT REPO: dancrocker/DCR-WAVE
# R version 4.1.1 (2021-08-10) x86_64
##############################################################################.
### Notes:
### 1_
###
### To-Do List:
### 1_
### Load Libraries and Script (Sources, Modules, and Functions) ####
print(paste0("WAVE App lauched at ", Sys.time()))
ipak <- function(pkg){
new.pkg <- pkg[!(pkg %in% installed.packages(lib.loc = r_lib)[, "Package"])]
if (length(new.pkg))
install.packages(new.pkg, lib = r_lib, dependencies = TRUE, repos="https://cloud.r-project.org")
sapply(pkg, require, character.only = TRUE)
}
### Package List ####
### NOTE - Shiny must be installed and loaded in the LaunchAppGitHub.R script - any other packages requred should be listed below
packages <- c("shiny","shinyjs", "shinyFiles", "shinyWidgets","rmarkdown", "knitr", "tidyverse", "tidyselect", "lubridate", "plotly", "leaflet", "RColorBrewer", "devtools",
"DT", "akima", "scales", "stringr", "cowplot", "shinythemes", "reshape2", "dataRetrieval", "pryr", "broom",
"ggthemes", "visreg", "lattice", "httr", "glue", "sf", "sp") # Took out odbc and dbi since app no longer connects to databases directly
# Removed chron - was conflicting with lubridate
suppressPackageStartupMessages(ipak(packages))
options("sp_evolution_status" = 2) # use sf instead of rgdal and rgeos in sp
### Removed rcmodel (that module will not work now - This install fails if tried within R Script.exe)
# if("rcmodel" %in% rownames(installed.packages()) == FALSE) {
# print("rcmodel package not installed, installing now")
# install_github("markwh/rcmodel")
# }
# library(rcmodel)
### Set any system environmental variables ####
# Sys.setenv(RSTUDIO_PANDOC= paste0(config[21],"/bin/pandoc")) ### need to resolve issue that users have different install locations
### Set Location Dependent Variables - datatsets and distro
### Specify User information ####
user <- Sys.getenv("USERNAME") %>% toupper()
if (config[["App Location"]] == "DCR") {
rootdir <- user_root
} else {
rootdir <- NULL
}
userdata <- readxl::read_xlsx(path = paste0(rootdir, config[["Users"]]))
userdata$Username <- userdata$Username %>% toupper()
if(user %in% userdata$Username){
username <- paste(userdata$FirstName[userdata$Username %in% user], userdata$LastName[userdata$Username %in% user], sep = " ")
useremail <- userdata$Email[userdata$Username %in% user]
userlocation <- userdata$Location[userdata$Username %in% user]
} else {
username <- "non-DCR"
useremail <- "other"
userlocation <- "non-DCR"
}
### Tab Default ####
if(userlocation == "Quabbin"){
tab_selected <- "Quabbin"
} else {
tab_selected <- "Wachusett"
}
### Specify data source
datadir <- config[["DataCache"]]
### Load rds files ####
### Make a list of all the .rds files using full path
rds_files <- list.files(paste0(rootdir, datadir), full.names = TRUE ,pattern = "\\.rds$")
### create an object that contains all of the rds files
data <- lapply(rds_files, readRDS)
### Make a list of the df names by eliminating extension from files
df_names <- gsub(".rds", "", list.files(paste0(rootdir, datadir), pattern = "\\.rds$"))
# name each df in the data object appropriately
names(data) <- df_names
### Extract each element of the data object into the global environment
list2env(data ,.GlobalEnv)
### Remove data
rm(data)
#
# ### SOURCE OTHER DATA ####
# gam_models_wach <- readxl::read_xlsx(path = paste0(datadir,"/GAM_loading_models_wach.xlsx"))
### SOURCE MODULES ####
### Filter - Filter Related Modules
source("modules/filter/filter_wq.R")
source("modules/filter/filter_flow.R")
### source("modules/filter/filter_precip.R")
source("modules/filter/site_checkbox.R")
source("modules/filter/station_level_checkbox.R")
source("modules/filter/param_select.R")
source("modules/filter/param_checkbox.R") # Eventually delete
source("modules/filter/date_select.R")
source("modules/filter/checkbox_select_all.R")
source("modules/filter/select_select_all.R")
### Plots - Modules that generate plots
source("modules/plots/plot_time_wq.R")
source("modules/plots/plot_time_depth_wq.R") ### Merge with Plot_Time_wq (with differeing facetting schemes)
source("modules/plots/plot_corr_wq.R")
source("modules/plots/plot_corr_depth_wq.R") ### Merge with Plot_Corr_wq (with differeing facetting schemes)
source("modules/plots/plot_corr_matrix_wq.R")
source("modules/plots/plot_profline_custom.R") ### look at Dan's script - faceting - Bring in actual function?
source("modules/plots/distribution_wq.R")
source("modules/plots/profile_heatmap.R")
source("modules/plots/profile_line.R")
source("modules/plots/phyto.R")
source("modules/plots/plot_flow.R")
source("modules/plots/plot_gw_percentile.R")
### Plot Options - Modules containing plot options
source("modules/plot_options/plot_theme_and_hlines.R")
source("modules/plot_options/plot_text_and_vlines_time.R")
source("modules/plot_options/plot_text_and_vlines_corr.R")
source("modules/plot_options/plot_title_and_labels.R")
source("modules/plot_options/plot_save.R")
### Statistics - Modules that generate Statistics
### Make into One file
source("modules/stats/stats_summary.R")
source("modules/stats/stats_time_depth_wq.R") # Merge into stats_sumamry
source("modules/stats/profile_table_stats.R") # Merge into stats_summary
### Hydro
source("modules/precip/precip_current.R")
source("modules/precip/precip_historical.R")
### Modeling
source("modules/modeling/loading_rcmodel.R")
source("functions/RUNRCMODEL.R")
source("functions/Prep_rcmodelData.R")
### Metadata - Modules for Metadata
source("modules/metadata/metadata.R") # Seperate into multiple Modules
### Maps - Modules that use Leaflet Map generation
source("modules/maps/home.R")
source("modules/maps/geospatial_plot.R")
source("modules/maps/site_map.R")
source("modules/maps/site_map_single.R")
source("modules/maps/precip_map.R")
### Reports - Modules for report and document generation
source("modules/reports/report_AWQ.R")
source("modules/reports/report_MWQ.R")
source("modules/reports/report_custom.R")
### Load Functions
source("functions/stat_functions.R")
source("functions/phyto_plots.R")
source("functions/flow_plots2.R")
### UI ####
### font-family: 'Lobster', cursive;
ui <- tagList(
### Creates padding at top for navBar space due to "fixed-top" position
tags$style(type='text/css',
'body {padding-top: 70px;}',
'h2 {
font-family: "Arial Black";
font-weight: 500;
line-height: 1.1;
color: #0C4B91;
}'
),
### Use ShinyJS for reset buttons in Filter Tab and in Modeling module
useShinyjs(),
### Create the Top Navigation Bar as well as define aesthetics
navbarPage(NULL, position = "fixed-top", inverse = TRUE, collapsible = TRUE, theme = shinytheme("cerulean"), windowTitle = "WAVE",
footer = tagList(hr(),
column(4,strong(paste("Data last updated:", last_update)),br()),
column(8,tags$div(tags$em("Created by Nick Zinck, University of Massachusetts; and Dan Crocker,
Massachusetts Department of Conservation and Recreation"), align = "right"), br())
),
### HOME PAGE ####
tabPanel("Home",
fluidRow(
column(3, imageOutput("dcr_image", height = 80), align = "left"),
column(6, imageOutput("wave_image1", height = 80), align = "center"),
column(3, imageOutput("umass_image", height = 80), align = "right")
),
HOME_UI("home")
),
### TRIBUTARY ####
tabPanel("Tributary",
### Title
fluidRow(
column(3, imageOutput("wave_image3", height = 50), align = "left"),
column(6, h2("Tributary Water Quality Data", align = "center")),
column(3, imageOutput("DCR_BlueLeaf1", height = 50), align = "right")
),
### Qb Tribs ####
tabsetPanel(
tabPanel("Quabbin",
navlistPanel(widths = c(2, 10),
tabPanel("Select / Filter Data", icon=icon("filter"), FILTER_WQ_UI("mod_trib_quab_filter")),
tabPanel("--- Plots", icon = icon("line-chart"),
br(),
wellPanel(em('Plots use data from the "Select / Filter Data" tab.Each plot may have additional selections, filters, and options.')),
tabsetPanel(
tabPanel("Time-Series Scatter", PLOT_TIME_WQ_UI("mod_trib_quab_plot_time")),
tabPanel("Correlation Scatter", PLOT_CORR_WQ_UI("mod_trib_quab_plot_corr")),
tabPanel("Distribution Charts", DISTRIBUTION_WQ_UI("mod_trib_quab_plot_dist"))
)
),
tabPanel("--- Statistics", icon = icon("calculator"),
br(),
wellPanel(em('Statistics use data from the "Select / Filter Data" tab')),
tabsetPanel(
tabPanel("Summary Statistics", STAT_TIME_WQ_UI("mod_trib_quab_stat_sum")),
tabPanel("Temporal Statistics", fluidRow(h5("Mann-Kendall Stats to come"))),
tabPanel("Correlation Matrix", PLOT_CORR_MATRIX_WQ_UI("mod_trib_quab_stat_cormat"))
)
),
tabPanel("Geospatial", icon = icon("map-marker"), MAP_PLOT_UI("mod_trib_quab_map", df = df_trib_quab)),
tabPanel("Metadata", icon = icon("table"), METADATA_UI("mod_trib_quab_meta"))
) ### end navlist panel
),
### Ware Tribs ####
tabPanel("Ware",
navlistPanel(widths = c(2, 10),
tabPanel("Select / Filter Data", icon = icon("filter"), FILTER_WQ_UI("mod_trib_ware_filter")),
tabPanel("--- Plots", icon = icon("line-chart"),
br(),
wellPanel(em('Plots use data from the "Select / Filter Data" tab')),
tabsetPanel(
tabPanel("Time-Series Scatter", PLOT_TIME_WQ_UI("mod_trib_ware_plot_time")),
tabPanel("Correlation Scatter", PLOT_CORR_WQ_UI("mod_trib_ware_plot_corr")),
tabPanel("Distribution Charts", DISTRIBUTION_WQ_UI("mod_trib_ware_plot_dist"))
)
),
tabPanel("--- Statistics", icon = icon("calculator"),
br(),
wellPanel(em('Statistics use data from the "Select / Filter Data" tab')),
tabsetPanel(
tabPanel("Summary Statistics", STAT_TIME_WQ_UI("mod_trib_ware_stat_sum")),
tabPanel("Temporal Statistics", fluidRow(h5("Mann-Kendall Stats to come"))),
tabPanel("Correlation Matrix", PLOT_CORR_MATRIX_WQ_UI("mod_trib_ware_stat_cormat"))
)
),
tabPanel("Geospatial", icon = icon("map-marker"), MAP_PLOT_UI("mod_trib_ware_map", df = df_trib_ware)),
tabPanel("Metadata", icon = icon("table"), fluidRow(h5("See Quabbin Tab. Can add data here in future")))
) ### end navlist panel
),
### Wach Tribs ####
tabPanel("Wachusett",
navlistPanel(widths = c(2, 10),
tabPanel("Select / Filter Data", icon = icon("filter"), FILTER_WQ_UI("mod_trib_wach_filter")),
tabPanel("--- Plots", icon = icon("line-chart"),
br(),
wellPanel(em('Plots use data from the "Select / Filter Data" tab')),
tabsetPanel(
tabPanel("Time-Series Scatter", PLOT_TIME_WQ_UI("mod_trib_wach_plot_time")),
tabPanel("Correlation Scatter", PLOT_CORR_WQ_UI("mod_trib_wach_plot_corr")),
tabPanel("Distribution Charts", DISTRIBUTION_WQ_UI("mod_trib_wach_plot_dist"))
)
),
tabPanel("--- Statistics", icon = icon("calculator"),
br(),
wellPanel(em('Statistics use data from the "Select / Filter Data" tab')),
tabsetPanel(
tabPanel("Summary Statistics", STAT_TIME_WQ_UI("mod_trib_wach_stat_sum")),
tabPanel("Temporal Statistics", fluidRow(h5("Mann-Kendall Stats to come"))),
tabPanel("Correlation Matrix", PLOT_CORR_MATRIX_WQ_UI("mod_trib_wach_stat_cormat"))
)
),
tabPanel("Geospatial", icon = icon("map-marker"), MAP_PLOT_UI("mod_trib_wach_map", df = df_trib_wach)),
tabPanel("Metadata", icon = icon("table"), METADATA_UI("mod_trib_wach_meta"))
) ### end navlist panel
),
selected = tab_selected
)
), ### end Tributary Tabpanel (tributary)
### RESERVOIR ####
tabPanel("Reservoir",
###Title
fluidRow(
column(3, imageOutput("wave_image4", height = 50), align = "left"),
column(6, h2("Reservoir Water Quality Data", align = "center")),
column(3, imageOutput("DCR_BlueLeaf2", height = 50), align = "right")
),
### Qb res ####
tabsetPanel(
tabPanel("Quabbin",
navlistPanel(widths = c(2, 10),
"Biological",
tabPanel("Phytoplankton", PHYTO_UI("mod_phyto_quab_plots", df_phyto_quab)),
"Chemical",
tabPanel("Select / Filter data", icon=icon("filter"), FILTER_WQ_UI("mod_chem_quab_filter")),
tabPanel("--- Plots", icon = icon("line-chart"),
br(), wellPanel(em('Plots use data from the "Select / Filter Data" tab')),
tabsetPanel(
tabPanel("Time-Series Scatter", PLOT_TIME_WQ_UI("mod_chem_quab_plot_time")),
tabPanel("Correlation Scatter", PLOT_CORR_WQ_UI("mod_chem_quab_plot_corr")),
tabPanel("Distribution Charts", DISTRIBUTION_WQ_UI("mod_chem_quab_plot_dist"))
)
),
tabPanel("--- Statistics", icon = icon("calculator"),
br(), wellPanel(em('Statistics use data from the "Select / Filter Data" tab')),
tabsetPanel(
tabPanel("Summary Statistics", STAT_TIME_DEPTH_WQ_UI("mod_chem_quab_stat_sum")),
tabPanel("Temporal Statistics", fluidRow(h5("Mann-Kendall Stats to come"))),
tabPanel("Correlation Matrix", PLOT_CORR_MATRIX_WQ_UI("mod_chem_quab_stat_cormat"))
)
),
tabPanel("Metadata", icon = icon("table"), METADATA_UI("mod_chem_quab_meta")),
"Profile",
tabPanel("Select / Filter Data", icon=icon("filter"), FILTER_WQ_UI("mod_prof_quab_filter")),
tabPanel("--- Plots", icon = icon("line-chart"),
br(), wellPanel(em('Plots use data from the "Select / Filter Data" tab')),
tabsetPanel(
tabPanel("Heat Map", PROF_HEATMAP_UI("mod_prof_quab_heat")),
tabPanel("Scatter Plot", PLOT_TIME_WQ_UI("mod_prof_quab_plot_time")),
tabPanel("Line Plot", PROF_LINE_UI("mod_prof_quab_line", df_prof_quab)),
tabPanel("Distribution Charts", DISTRIBUTION_WQ_UI("mod_prof_quab_plot_dist"))
)
),
tabPanel("Table and Summary", PROF_TABLE_STAT_UI("mod_prof_quab_sum", df_prof_quab)),
tabPanel("Metadata", icon=icon("table"), METADATA_UI("mod_prof_quab_meta"))
) ### end navlist panel
),
### Wach res ####
tabPanel("Wachusett",
navlistPanel(widths = c(2, 10),
"Biological",
tabPanel("Phytoplankton", PHYTO_UI("mod_phyto_wach_plots", df_phyto_wach)),
"Profile",
tabPanel("Select / Filter Data", icon=icon("filter"), FILTER_WQ_UI("mod_prof_wach_filter")),
tabPanel("--- Plots", icon=icon("line-chart"),
br(),
wellPanel(em('Plots use data from the "Select / Filter Data" tab')),
tabsetPanel(
tabPanel("Heat Map", PROF_HEATMAP_UI("mod_prof_wach_heat")),
tabPanel("Scatter Plot", PLOT_TIME_WQ_UI("mod_prof_wach_plot_time")),
tabPanel("Line Plot", PROF_LINE_UI("mod_prof_wach_line", df_prof_wach)),
tabPanel("Distribution Charts", DISTRIBUTION_WQ_UI("mod_prof_wach_plot_dist"))
)
),
tabPanel("Table and Summary", PROF_TABLE_STAT_UI("mod_prof_wach_sum", df_prof_wach)),
tabPanel("Metadata", icon=icon("table"), METADATA_UI("mod_prof_wach_meta")),
"Chemical",
tabPanel("Select / Filter Data", icon=icon("filter"), FILTER_WQ_UI("mod_chem_wach_filter")),
tabPanel("--- Plots", icon=icon("line-chart"),
br(),wellPanel(em('Plots use data from the "Select / Filter Data" tab')),
tabsetPanel(
tabPanel("Time-Series Scatter", PLOT_TIME_WQ_UI("mod_chem_wach_plot_time")),
tabPanel("Correlation Scatter", PLOT_CORR_WQ_UI("mod_chem_wach_plot_corr")),
tabPanel("Distribution Charts", DISTRIBUTION_WQ_UI("mod_chem_wach_plot_dist"))
)
),
tabPanel("--- Statistics", icon=icon("calculator"),
br(),wellPanel(em('Statistics use data from the "Select / Filter Data" tab')),
tabsetPanel(
tabPanel("Summary Statistics", STAT_TIME_DEPTH_WQ_UI("mod_chem_wach_stat_sum")),
tabPanel("Temporal Statistics", fluidRow(h5("Mann-Kendall Stats to come"))),
tabPanel("Correlation Matrix", PLOT_CORR_MATRIX_WQ_UI("mod_chem_wach_stat_cormat"))
)
),
tabPanel("Metadata", icon=icon("table"), METADATA_UI("mod_chem_wach_meta")),
"Bacteria",
tabPanel("Select / Filter Data", icon=icon("filter"), FILTER_WQ_UI("mod_bact_wach_filter")),
tabPanel("--- Plots", icon=icon("line-chart"),
br(),wellPanel(em('Plots use data from the "Select / Filter Data" tab')),
tabsetPanel(
tabPanel("Time-Series Scatter", PLOT_TIME_WQ_UI("mod_bact_wach_plot_time")),
tabPanel("Correlation Scatter", PLOT_CORR_WQ_UI("mod_bact_wach_plot_corr")),
tabPanel("Distribution Charts", DISTRIBUTION_WQ_UI("mod_bact_wach_plot_dist"))
)
),
tabPanel("--- Statistics", icon=icon("calculator"),
br(),wellPanel(em('Statistics use data from the "Select / Filter Data" tab')),
tabsetPanel(
tabPanel("Summary Statistics", STAT_TIME_WQ_UI("mod_bact_wach_stat_sum")),
tabPanel("Temporal Statistics", fluidRow(h5("Mann-Kendall Stats to come"))),
tabPanel("Correlation Matrix", PLOT_CORR_MATRIX_WQ_UI("mod_bact_wach_stat_cormat"))
)
),
tabPanel("Geospatial", icon=icon("map-marker"), MAP_PLOT_UI("mod_bact_wach_map", df = df_bact_wach)),
tabPanel("Metadata", icon=icon("table"), METADATA_UI("mod_bact_wach_meta"))
) ### end navlist panel
), ### End TabPanel Watersheds
selected = tab_selected
)
), ### end Tabpanel (reservoir)
### HYDRO-MET-MODELING ####
tabPanel("Hydro/Met",
### Header
fluidRow(
column(3, imageOutput("wave_image6", height = 50), align = "left"),
column(6, h2("Hydrology and Meteorology Data", align = "center")),
column(3, imageOutput("DCR_BlueLeaf3", height = 50), align = "right")
),
### Qb Hydro ####
tabsetPanel(
tabPanel("Quabbin",
navlistPanel(widths = c(2, 10),
"Streamflow",
tabPanel("Select / Filter Data", icon = icon("filter"), FILTER_WQ_UI("mod_flow_quab_filter")),
tabPanel("--- Plot Streamflow", icon = icon("line-chart"),
br(),
wellPanel(em('Plots use data from the "Select / Filter Data" tab')),
tabsetPanel(
# tabPanel("Hydrographs", PLOT_FLOW_UI("mod_flow_quab_hydrographs")),
# tabPanel("Flow Duration", PLOT_CORR_WQ_UI("mod_flow_quab_flowdur")),
# tabPanel("Boxplots", PLOT_CORR_WQ_UI("mod_flow_quab_boxplots")),
# tabPanel("Ratings", PLOT_CORR_WQ_UI("mod_flow_quab_ratings"))
)
),
tabPanel("--- Streamflow Stats", icon = icon("calculator"),
br(),
wellPanel(em('Statistics use data from the "Select / Filter Data" tab')),
tabsetPanel(
tabPanel("Summary Statistics", STAT_TIME_DEPTH_WQ_UI("mod_flow_quab_stat_sum")),
tabPanel("Historical Statistics", PLOT_CORR_MATRIX_WQ_UI("mod_flow_quab_stat_hist"))
)
),
tabPanel("--- Modeling", icon = icon("calculator"),
br(),
wellPanel(em('Run Tributary Loading Models')),
tabsetPanel(
# tabPanel("flux", FLUX_WQ_UI("mod_trib_loads_flux")),
# tabPanel("rcmodel", LOADING_RCMODEL_UI("mod_quab_rcmodel"))
# tabPanel("loadflex", LOADFLEX_WQ_UI("mod_trib_loads_loadflex"))
)
),
# tabPanel("Ratings", icon = icon("calculator"),
# tabsetPanel(
# tabPanel("Rating Curves", STAT_TIME_DEPTH_WQ_UI("mod_flow_quab_ratcurve")),
# tabPanel("Rating Tables", PLOT_CORR_MATRIX_WQ_UI("mod_chem_quab_rattable"))
# )
# ),
"Precipitation",
tabPanel("Current Conditions", icon = icon("line-chart"), PRECIP_CURRENT_UI("mod_precip_quab_current")),
tabPanel("Historical Precip", icon = icon("line-chart"), PRECIP_HISTORICAL_UI("mod_precip_quab_hist")),
# tabPanel("Select / Filter Data", icon=icon("filter"), FILTER_WQ_UI("mod_precip_quab_filter")),
# tabPanel("--- Plots", icon = icon("line-chart"),
# br(),
# wellPanel(em('Plots use data from the "Select / Filter Data" tab')),
# tabsetPanel(
# # tabPanel("Current Conditions", PROF_HEATMAP_UI("mod_precip_quab_current")),
# # tabPanel("Historical Precip", PROF_LINE_UI("mod_precip_quab_hist", df_prof_quab)),
# # tabPanel("Distribution Charts", DISTRIBUTION_WQ_UI("mod_precip_quab_plot_dist"))
# )
# ),
# tabPanel("--- Stats/Tables", icon = icon("calculator"),
# br(),
# wellPanel(em('Statistics use data from the "Select / Filter Data" tab')),
# tabsetPanel(
# # tabPanel("Summary Statistics", STAT_TIME_DEPTH_WQ_UI("mod_precip_quab_stat_sum")),
# # tabPanel("Historical Statistics", PLOT_CORR_MATRIX_WQ_UI("mod_precip_quab_stat_hist"))
# )
# ),
"Water Supply",
tabPanel("Reservoirs/Transfers", icon=icon("calculator"),
br(),
wellPanel(em('Plots use data from the "Select / Filter Data" tab')),
tabsetPanel(
# tabPanel("Flows/Transfers", PLOT_TIME_WQ_UI("mod_ws_quab_flowtrans")),
# tabPanel("Historical Elevation/Storage ", PLOT_CORR_WQ_UI("mod_ws_quab_elev_stor"))
)
),
tabPanel("Snowpack", icon = icon("calculator"),
tabsetPanel(
# tabPanel("Map Overview", icon=icon("map-marker"), FILTER_WQ_UI("mod_snow_quab_map")),
# tabPanel("Summary Statistics", STAT_TIME_DEPTH_WQ_UI("mod_snow_quab_stat_sum"))
)
),
tabPanel("Groundwater", icon=icon("calculator"),
tabsetPanel(
# tabPanel("Map Overview", icon=icon("map-marker"), FILTER_WQ_UI("mod_gw_quab_map")),
# tabPanel("Plots", STAT_TIME_DEPTH_WQ_UI("mod_gw_quab_plots")),
# tabPanel("Stats/Tables", STAT_TIME_DEPTH_WQ_UI("mod_gw_quab_stats"))
)
)
) ### end navlist panel
), ### End Tab Panel Quabbin
### Wach Hydro ####
tabPanel("Wachusett",
navlistPanel(widths = c(2, 10),
"Streamflow",
tabPanel("Select / Filter Data", icon = icon("filter"), FILTER_FLOW_UI("mod_flow_wach_filter")),
tabPanel("--- Plot Streamflow", icon = icon("line-chart"),
br(),
wellPanel(em('Plots use data from the "Select / Filter Data" tab')),
tabsetPanel(
tabPanel("Hydrographs", PLOT_FLOW_UI("mod_flow_wach_hydrograph"))
# tabPanel("Flow Duration", PLOT_DURATION_UI("mod_flow_wach_flowdur")),
# tabPanel("Boxplots", PLOT_BOX_UI("mod_flow_wach_boxplots")),
# tabPanel("Ratings", RATINGS_UI("mod_flow_wach_ratings"))
)
),
tabPanel("--- Streamflow Stats", icon = icon("calculator"),
br(),
wellPanel(em('Statistics use data from the "Select / Filter Data" tab')),
tabsetPanel(
tabPanel("Summary Statistics", STAT_TIME_DEPTH_WQ_UI("mod_flow_wach_stat_sum")),
tabPanel("Historical Statistics", PLOT_CORR_MATRIX_WQ_UI("mod_flow_wach_stat_hist"))
)
),
tabPanel("--- Modeling", icon = icon("calculator"),
br(),
wellPanel(em('Run Tributary Loading Models')),
tabsetPanel(
# tabPanel("flux", FLUX_WQ_UI("mod_trib_loads_flux")),
tabPanel("rcmodel", LOADING_RCMODEL_UI("mod_wach_rcmodel"))
# tabPanel("loadflex", LOADFLEX_WQ_UI("mod_trib_loads_loadflex"))
)
),
# tabPanel("Ratings", icon = icon("calculator"),
# tabsetPanel(
# tabPanel("Rating Curves", STAT_TIME_DEPTH_WQ_UI("mod_flow_wach_ratcurve")),
# tabPanel("Rating Tables", PLOT_CORR_MATRIX_WQ_UI("mod_chem_wach_rattable"))
# )
# ),
"Precipitation",
tabPanel("Current Conditions", icon = icon("line-chart"), PRECIP_CURRENT_UI("mod_precip_wach_current")),
tabPanel("Historical Precip", icon = icon("line-chart"), PRECIP_HISTORICAL_UI("mod_precip_wach_hist")),
# tabPanel("Statistics", icon = icon("filter"), PRECIP_STATS_UI("mod_precip_wach_stats")),
# tabPanel("Filter/Export Precip Data ", PRECIP_FILTER_UI("mod_precip_wach_filter")),
"Water Supply",
tabPanel("Reservoirs/Transfers", icon=icon("calculator"),
br(),
wellPanel(em('Plots use data from the "Select / Filter Data" tab')),
tabsetPanel(
# tabPanel("Flows/Transfers", PLOT_TIME_WQ_UI("mod_ws_wach_flowtrans")),
# tabPanel("Historical Elevation/Storage ", PLOT_CORR_WQ_UI("mod_ws_wach_elev_stor"))
)
),
tabPanel("Snowpack", icon = icon("calculator"),
tabsetPanel(
# tabPanel("Map Overview", icon=icon("map-marker"), FILTER_WQ_UI("mod_snow_wach_map")),
# tabPanel("Summary Statistics", STAT_TIME_DEPTH_WQ_UI("mod_snow_wach_stat_sum"))
)
)
) ### end navlist panel
), ### End TabPanel Watersheds
selected = tab_selected
)
), ### end Tabpanel (HydroMet)
## Groundwater Plots ####
tabPanel("Groundwater",
### Header
fluidRow(
column(3, imageOutput("wave_image9", height = 50), align = "left"),
column(6, h2("Groundwater Data", align = "center")),
column(3, imageOutput("DCR_BlueLeaf6", height = 50), align = "right")
),
tabsetPanel(
tabPanel("Quabbin",
navlistPanel(widths = c(2, 10),
"Groundwater"
)
),
tabPanel("Wachusett",
navlistPanel(widths = c(2, 10),
"Groundwater",
tabPanel("Select / Filter Data", icon = icon("filter"), FILTER_WQ_UI("mod_well_wach_filter")),
tabPanel("--- Plot Groundwater", icon = icon("line-chart"),
br(),
wellPanel(em('Plots use data from the "Select / Filter Data" tab')),
tabsetPanel(
tabPanel("Time-Series Scatter", PLOT_TIME_WQ_UI("mod_well_wach_plot_time")),
tabPanel("Recent Groundwater Levels", PLOT_GW_PERCENTILE_UI("mod_well_wach_plot_percentile", well_sites = df_well_wach_site)),
tabPanel("Correlation Scatter", PLOT_CORR_WQ_UI("mod_well_wach_plot_corr")),
tabPanel("Distribution Charts", DISTRIBUTION_WQ_UI("mod_well_wach_plot_dist"))
)
),
tabPanel("--- Groundwater Stats", icon = icon("calculator"),
br(),
wellPanel(em('Statistics use data from the "Select / Filter Data" tab')),
tabsetPanel(
tabPanel("Summary Statistics", STAT_TIME_WQ_UI("mod_well_wach_stat_sum")),
tabPanel("Temporal Statistics", fluidRow(h5("Mann-Kendall Stats to come"))),
tabPanel("Correlation Matrix", PLOT_CORR_MATRIX_WQ_UI("mod_well_wach_stat_cormat"))
)
),
tabPanel("Geospatial", icon = icon("map-marker"), MAP_PLOT_UI("mod_well_wach_map", df = df_trib_wach)),
tabPanel("Metadata", icon = icon("table"), METADATA_UI("mod_well_wach_meta"))
) ### end navlist panel
), ### end tabpanel wachusett
selected = tab_selected
) ### end tabpanel watersheds
), ### end Tabpanel (Groundwater)
### FORESTRY ####
tabPanel("Forestry",
### Title
fluidRow(
column(3, imageOutput("wave_image7", height = 50), align = "left"),
column(6, h2("Forestry Data", align = "center")),
column(3, imageOutput("DCR_BlueLeaf4", height = 50), align = "right")
)
), ### End Tab Panel Forestry
### REPORTS ####
tabPanel("Report",
### Title
fluidRow(
column(3, imageOutput("wave_image8", height = 50), align = "left"),
column(6, h2("Report Generation", align = "center")),
column(3, imageOutput("DCR_BlueLeaf5", height = 50), align = "right")
),
navlistPanel(widths = c(2, 10),
"Preset Reports",
tabPanel("Annual WQ",
fluidRow(column(10, h4("Annual Water Quality Reports", align = "center")), column(2)),
tabsetPanel(
tabPanel("Quabbin", REPORT_AWQ_UI("mod_quab_awq", df_trib_quab)),
tabPanel("Wachusett", REPORT_AWQ_UI("mod_wach_awq", df_trib_wach))
) ### end tabset Panel
), ### end tabpanel
tabPanel("Monthly WQ",
fluidRow(column(10, h4("Monthly Water Quality Reports", align = "center")), column(2)),
tabsetPanel(
tabPanel("Quabbin", REPORT_MWQ_UI("mod_quab_mwq", df_trib_quab)),
tabPanel("Wachusett", REPORT_MWQ_UI("mod_wach_mwq", df_trib_wach))
) ### end tabset panel
), ### end tabpanel
"Custom Reports",
tabPanel("Tributary",
fluidRow(column(10, h4("Tributary Custom Reports", align = "center")), column(2)),
tabsetPanel(
tabPanel("Quabbin", REPORT_CUSTOM_UI("mod_trib_quab_rep", df_trib_quab)),
tabPanel("Ware River", REPORT_CUSTOM_UI("mod_trib_ware_rep", df_trib_ware)),
tabPanel("Wachusett", REPORT_CUSTOM_UI("mod_trib_wach_rep", df_trib_wach))
)
)
) ### end navlist
) ### End Tab Panel Reports
) ### end tagList
) ### END UI ####
### SERVER ####
server <- function(input, output, session) {
### HOME ####
callModule(HOME, "home", df_site = df_all_site, df_site_wells = df_well_wach_site)
### TRIBUTARY ####
### Quabbin ####
### Filter
Df_Trib_Quab <- callModule(FILTER_WQ, "mod_trib_quab_filter",
df = df_trib_quab,
df_site = df_trib_quab_site,
df_flags = df_flags,
df_precip = df_quabbin_prcp_daily,
df_flag_index = df_wq_quab_flag_sample,
type = "wq_trib")
### Plots
callModule(PLOT_TIME_WQ, "mod_trib_quab_plot_time", Df = Df_Trib_Quab$Long)
callModule(PLOT_CORR_WQ, "mod_trib_quab_plot_corr", Df = Df_Trib_Quab$Long)
callModule(DISTRIBUTION_WQ, "mod_trib_quab_plot_dist", Df = Df_Trib_Quab$Stat)
# Stats
callModule(STAT_TIME_WQ, "mod_trib_quab_stat_sum", Df = Df_Trib_Quab$Stat)
### temp stats
callModule(PLOT_CORR_MATRIX_WQ, "mod_trib_quab_stat_cormat", Df = Df_Trib_Quab$Wide)
### Geospatial
callModule(MAP_PLOT, "mod_trib_quab_map", df = df_trib_quab, df_site = df_trib_quab_site)
# MetaData
callModule(METADATA, "mod_trib_quab_meta", df = df_trib_quab, df_site = df_trib_quab_site, df_param = df_quab_param)
### Ware ####
### Filter
Df_Trib_Ware <- callModule(FILTER_WQ, "mod_trib_ware_filter",
df = df_trib_ware,
df_site = df_trib_ware_site,
df_flags = df_flags,
df_precip = df_quabbin_prcp_daily,
df_flag_index = df_wq_quab_flag_sample,
type = "wq_trib")
# Plots
callModule(PLOT_TIME_WQ, "mod_trib_ware_plot_time", Df = Df_Trib_Ware$Long)
callModule(PLOT_CORR_WQ, "mod_trib_ware_plot_corr", Df = Df_Trib_Ware$Long)
callModule(DISTRIBUTION_WQ, "mod_trib_ware_plot_dist", Df = Df_Trib_Ware$Stat)
### Stats
callModule(STAT_TIME_WQ, "mod_trib_ware_stat_sum", Df = Df_Trib_Ware$Stat)
### temp stats
callModule(PLOT_CORR_MATRIX_WQ, "mod_trib_ware_stat_cormat", Df = Df_Trib_Ware$Wide)
### Geospatial
callModule(MAP_PLOT, "mod_trib_ware_map", df = df_trib_ware, df_site = df_trib_ware_site)
### Precipitation ####
callModule(PRECIP_CURRENT, "mod_precip_quab_current", df = df_quabbin_prcp_daily, df_site = df_all_site, wshed = "Quabbin")
callModule(PRECIP_HISTORICAL, "mod_precip_quab_hist", df = df_quabbin_prcp_daily, wshed = "Quabbin")
### Wachusett ####
### Filter
Df_Trib_Wach <- callModule(FILTER_WQ, "mod_trib_wach_filter",
df = df_trib_wach,
df_site = df_trib_wach_site,
df_flags = df_flags,
df_precip = df_wach_prcp_daily,
df_flag_index = df_wach_flag_index[df_wach_flag_index$Dataset == "df_trib_bact_wach",],
type = "wq_trib")
### Plots
callModule(PLOT_TIME_WQ, "mod_trib_wach_plot_time", Df = Df_Trib_Wach$Long)
callModule(PLOT_CORR_WQ, "mod_trib_wach_plot_corr", Df = Df_Trib_Wach$Long)
callModule(DISTRIBUTION_WQ, "mod_trib_wach_plot_dist", Df = Df_Trib_Wach$Stat)
### Stats
callModule(STAT_TIME_WQ, "mod_trib_wach_stat_sum", Df = Df_Trib_Wach$Stat)
# temp stats
callModule(PLOT_CORR_MATRIX_WQ, "mod_trib_wach_stat_cormat", Df = Df_Trib_Wach$Wide)
### Geospatial
callModule(MAP_PLOT, "mod_trib_wach_map", df = df_trib_wach, df_site = df_trib_wach_site)
### MetaData
callModule(METADATA, "mod_trib_wach_meta", df = df_trib_wach, df_site = df_trib_wach_site, df_param = df_wach_param)
### RESERVOIR ####
##### Quabbin #####
### Chemical
### Filter
Df_Chem_Quab <- callModule(FILTER_WQ, "mod_chem_quab_filter",
df = df_chem_quab,
df_site = df_chem_quab_site,
df_flags = df_flags,
df_precip = df_quabbin_prcp_daily,
df_flag_index = df_wq_quab_flag_sample,
type = "wq_depth")
### Plots
callModule(PLOT_TIME_WQ, "mod_chem_quab_plot_time", Df = Df_Chem_Quab$Long) ### Update to Depth specific plot
callModule(PLOT_CORR_WQ, "mod_chem_quab_plot_corr", Df = Df_Chem_Quab$Long) ### Update to Depth Specific Plot
callModule(DISTRIBUTION_WQ, "mod_chem_quab_plot_dist", Df = Df_Chem_Quab$Stat) ### Depth Specific?
### Stats
callModule(STAT_TIME_DEPTH_WQ, "mod_chem_quab_stat_sum", Df = Df_Chem_Quab$Stat)
### temp stats
callModule(PLOT_CORR_MATRIX_WQ, "mod_chem_quab_stat_cormat", Df = Df_Chem_Quab$Wide)
### MetaData
callModule(METADATA, "mod_chem_quab_meta", df = df_chem_quab, df_site = df_chem_quab_site, df_param = df_quab_param)
### Profile
### Filter
Df_Prof_Quab <- callModule(FILTER_WQ,
"mod_prof_quab_filter",
df = df_prof_quab,
df_site = df_prof_quab_site,
df_flags = df_flags,
df_precip = df_quabbin_prcp_daily,
df_flag_index = df_wq_quab_flag_sample,
type = "profile")
### Plots
callModule(PROF_HEATMAP, "mod_prof_quab_heat", Df = Df_Prof_Quab$Long)
callModule(PLOT_TIME_WQ, "mod_prof_quab_plot_time", Df = Df_Prof_Quab$Long) ### Update to Depth specific plot
callModule(PROF_LINE, "mod_prof_quab_line", df = df_prof_quab)
callModule(DISTRIBUTION_WQ, "mod_prof_quab_plot_dist", Df = Df_Prof_Quab$Stat)
### Table and Stats
callModule(PROF_TABLE_STAT, "mod_prof_quab_sum", df = df_prof_quab)
### Change the Data Frames to Profile Data
callModule(METADATA, "mod_prof_quab_meta", df = df_prof_quab, df_site = df_prof_quab_site, df_param = df_quab_param)
### Phytoplankton
callModule(PHYTO, "mod_phyto_quab_plots", df = df_phyto_quab)
##### Wachusett #####
### Bacteria
### Filter
Df_Bact_Wach <- callModule(FILTER_WQ, "mod_bact_wach_filter",
df = df_bact_wach,
df_site = df_bact_wach_site,
df_flags = df_flags,
df_precip = df_wach_prcp_daily,
df_flag_index = df_wach_flag_index[df_wach_flag_index$DataTableName == "tblMWRAResults",],
type = "wq_res")
### Plots
callModule(PLOT_TIME_WQ, "mod_bact_wach_plot_time", Df = Df_Bact_Wach$Long)
callModule(PLOT_CORR_WQ, "mod_bact_wach_plot_corr", Df = Df_Bact_Wach$Long)
callModule(DISTRIBUTION_WQ, "mod_bact_wach_plot_dist", Df = Df_Bact_Wach$Stat)
### Stats
callModule(STAT_TIME_WQ, "mod_bact_wach_stat_sum", Df = Df_Bact_Wach$Stat)
### temp stats
callModule(PLOT_CORR_MATRIX_WQ, "mod_bact_wach_stat_cormat", Df = Df_Bact_Wach$Wide)
### Geospatial
callModule(MAP_PLOT, "mod_bact_wach_map", df = df_bact_wach, df_site = df_bact_wach_site)
### MetaData
callModule(METADATA, "mod_bact_wach_meta", df = df_bact_wach, df_site = df_bact_wach_site, df_param = df_wach_param)
### Chemical
### Filter
Df_Chem_Wach <- callModule(FILTER_WQ, "mod_chem_wach_filter",
df = df_chem_wach,
df_site = df_chem_wach_site,
df_flags = df_flags,
df_precip = df_wach_prcp_daily,
df_flag_index = df_wach_flag_index[df_wach_flag_index$DataTableName == "tbl_Nutrients",],
type = "wq_depth")
### Plots
callModule(PLOT_TIME_WQ, "mod_chem_wach_plot_time", Df = Df_Chem_Wach$Long) ### Update to Depth specific plot
callModule(PLOT_CORR_WQ, "mod_chem_wach_plot_corr", Df = Df_Chem_Wach$Long) ### Update to Depth Specific Plot
callModule(DISTRIBUTION_WQ, "mod_chem_wach_plot_dist", Df = Df_Chem_Wach$Stat) ### Depth Specific?
### Stats
callModule(STAT_TIME_DEPTH_WQ, "mod_chem_wach_stat_sum", Df = Df_Chem_Wach$Stat)
### temp stats
callModule(PLOT_CORR_MATRIX_WQ, "mod_chem_wach_stat_cormat", Df = Df_Chem_Wach$Wide)
### MetaData
callModule(METADATA, "mod_chem_wach_meta", df = df_chem_wach, df_site = df_chem_wach_site, df_param = df_chem_param)
### Profile
### Filter
Df_Prof_Wach <- callModule(FILTER_WQ,
"mod_prof_wach_filter",
df = df_prof_wach,
df_site = df_prof_wach_site,
df_flags = df_flags,
df_precip = df_wach_prcp_daily,
df_flag_index = df_wach_flag_index[df_wach_flag_index$Dataset == "tbl_Profiles",],
type = "profile")
### Plots
callModule(PLOT_TIME_WQ, "mod_prof_wach_plot_time", Df = Df_Prof_Wach$Long) ### Update to Depth specific plot
callModule(PROF_HEATMAP, "mod_prof_wach_heat", Df = Df_Prof_Wach$Long)
callModule(PROF_LINE, "mod_prof_wach_line", df = df_prof_wach)
callModule(DISTRIBUTION_WQ, "mod_prof_wach_plot_dist", Df = Df_Prof_Wach$Stat)
### Table and Stats
callModule(PROF_TABLE_STAT, "mod_prof_wach_sum", df = df_prof_wach)
### Change the Data Frames to Profile Data
callModule(METADATA, "mod_prof_wach_meta", df = df_prof_wach, df_site = df_prof_wach_site, df_param = df_wach_param)
### AquaBio
callModule(PHYTO, "mod_phyto_wach_plots", df = df_phyto_wach)
### HYDRO ####
### Wachusett ####
### Streamflow ####
# # Filter
Df_Flow_Wach <- callModule(FILTER_FLOW, "mod_flow_wach_filter",
df = df_wach_flow,
df_inst = df_wach_flow_inst,
df_site = df_trib_wach_site[!is.na(df_trib_wach_site$LocationFlow),],
df_flags = df_flags,
df_flag_index = df_wach_flag_index[df_wach_flag_index$DataTableName == "tbl_HOBO",],
type = "wq"
)
callModule(PLOT_FLOW, "mod_flow_wach_hydrograph",
Df = Df_Flow_Wach$Long, # This is a pre-filtered dataset from module Filter Flow
Df_inst = Df_Flow_Wach$Inst, # This is a pre-filtered dataset from module Filter Flow
df_wq = df_trib_wach,
df_site = df_trib_wach_site[!is.na(df_trib_wach_site$LocationFlow),],
df_precip = df_wach_prcp_daily)
# callModule(PLOT_DURATION, "mod_flow_wach_flowdur", Df = Df_Prof_Wach$Long)
# callModule(PLOT_BOX, "mod_flow_wach_boxplots", Df = Df_Prof_Wach$Long)
# callModule(FLOW_RATINGS, "mod_flow_wach_ratings", Df = Df_Prof_Wach$Long)
# callModule(RATINGS, "mod_prof_wach_plot_dist", Df = Df_Prof_Wach$Long)
# ### Groundwater ####
## Filter
Df_GW_Wach <- callModule(FILTER_WQ, "mod_well_wach_filter",
df = df_wach_wells,
df_site = df_well_wach_site,
df_flags = df_flags,
df_precip = df_wach_prcp_daily,
df_flag_index = df_wach_flag_index[df_wach_flag_index$DataTableName == "tblWellsManual",],
type = "wq_well")
### Plots
callModule(PLOT_TIME_WQ, "mod_well_wach_plot_time", Df = Df_GW_Wach$Long)
callModule(PLOT_GW_PERCENTILE, "mod_well_wach_plot_percentile", Df = df_wach_wells,
metadata = df_wach_wells_metadata,
df_flag_index = df_wach_flag_index[df_wach_flag_index$DataTableName == "tblWellsManual",])
callModule(PLOT_CORR_WQ, "mod_well_wach_plot_corr", Df = Df_GW_Wach$Long)
callModule(DISTRIBUTION_WQ, "mod_well_wach_plot_dist", Df = Df_GW_Wach$Stat)
### Stats
callModule(STAT_TIME_WQ, "mod_well_wach_stat_sum", Df = Df_GW_Wach$Stat)
# temp stats
callModule(PLOT_CORR_MATRIX_WQ, "mod_well_wach_stat_cormat", Df = Df_GW_Wach$Wide)
### Geospatial
callModule(MAP_PLOT, "mod_well_wach_map", df = df_wach_wells, df_site = df_well_wach_site)
### MetaData
callModule(METADATA, "mod_well_wach_meta", df = df_wach_wells, df_site = df_well_wach_site, df_param = df_wach_param)
# ### Precip ####
callModule(PRECIP_CURRENT, "mod_precip_wach_current", df = df_wach_prcp_daily, df_site = df_all_site, wshed = "Wachusett")
callModule(PRECIP_HISTORICAL, "mod_precip_wach_hist", df = df_wach_prcp_daily, wshed = "Wachusett")
# callModule(PRECIP_STATS, "mod_precip_wach_stats", df = df_wach_prcp_daily)
# callModule(PRECIP_FILTER, "mod_precip_wach_filter", df = df_wach_prcp_daily)
#
# # Water Supply ####
# # Filter
# Df_wSupply_Wach <- callModule(FILTER_WSUPPLY, "mod_wsupply_wach_filter",
# df_wsupply = df_wsupply_wach,
# type = "wq")
#
# callModule(WSUPPLY_RESTRANS, "mod_prof_wach_plot_dist", Df = Df_Prof_Wach$Long)
# callModule(WSUPPLY_SNOW, "mod_prof_wach_plot_dist", Df = Df_Prof_Wach$Long)
# callModule(WSUPPLY_GWATER, "mod_prof_wach_plot_dist", Df = Df_Prof_Wach$Long)
### Modeling ####
callModule(LOADING_RCMODEL, "mod_wach_rcmodel",
df_wq = df_trib_wach,
df_flow = df_wach_flow,
df_precip = df_wach_prcp_daily,
df_locs = df_trib_wach_site,
gam_models = gam_models_wach,
df_flags = df_flags,
df_flag_index = df_wach_flag_index[df_wach_flag_index$DataTableName == "tblWQALLDATA",])
# callModule(LOADING_FLUX, "mod_trib_loads_flux", Args)
# callModule(LOADING_LOADFLEX, "mod_trib_loads_loadflex", Args)
# Reports
callModule(REPORT_AWQ, "mod_quab_awq", df_trib = df_trib_quab, df_chem = df_chem_quab, df_prof = df_prof_quab, df_site = df_trib_quab_site)
callModule(REPORT_AWQ, "mod_wach_awq", df_trib = df_trib_wach, df_chem = df_chem_wach, df_prof = df_prof_wach, df_site = df_trib_wach_site)
callModule(REPORT_MWQ, "mod_quab_mwq", df_trib = df_trib_quab, df_chem = df_chem_quab, df_prof = df_prof_quab, df_site = df_trib_quab_site)