---
title: "Single Site Data Availability"
output: 
  rmarkdown::html_vignette
editor_options: 
  chunk_output_type: console
vignette: >
  %\VignetteIndexEntry{Single Site Data Availability}
  \usepackage[utf8]{inputenc}
  %\VignetteEngine{knitr::rmarkdown}
---

```{r setup, include=FALSE}
library(knitr)
opts_chunk$set(echo = TRUE,
               warning = FALSE,
               message = FALSE,
               fig.width = 6,
               fig.height = 5)

options(knitr.kable.NA = '')
library(dplyr)
```

<style>

body {
    max-width: 1600px;
    margin-left:10px;
    padding-left:10px;
}
</style>

This vignette shows how to use `HASP` and other R tools to reproduce:

https://fl.water.usgs.gov/mapper/site_info.php?site=263819081585801&stationType=gw

This page merges information from USGS Groundwater Watch website and USGS Water Science Centers.

## Site Information


```{r siteInfo, results='asis'}
library(HASP)

siteID <- "USGS-263819081585801"
site_metadata <- site_summary(siteID, markdown = TRUE)
```


```{r whatData}
data_info <- data_available(siteID)
kable(data_info)
```


## Get data using dataRetrieval

Using `dataRetrieval` code to get the data for this site:

```{r getData, eval=TRUE}
library(dataRetrieval)
siteID <- "USGS-263819081585801"
parameterCd <- "62610"
statCd <- "00001"
# Daily data:
gw_level_dv <- read_waterdata_daily(monitoring_location_id = siteID,
                                    parameter_code = parameterCd,
                                    statistic_id = statCd,
                                    skipGeometry = TRUE)

# Field measured:
gwl_data <- dataRetrieval::read_waterdata_field_measurements(monitoring_location_id = siteID,
                                                             skipGeometry = TRUE)

# Water quality data:
cl_sc <- c("Chloride", "Specific conductance")
qw_data <- readWQPqw(siteNumbers = siteID,
                     parameterCd = cl_sc)

plot_title <- "L -2701\n263819081585801"
y_label <- dataRetrieval::read_waterdata_parameter_codes(parameter_code = parameterCd)$parameter_name

```

## Groundwater Data

### Monthly Frequency


```{r monthlyFreqPlot}
monthly_frequency_plot(gw_level_dv,
                       gwl_data = gwl_data,
                       parameter_cd = parameterCd,
                       y_axis_label = y_label,
                       plot_title = plot_title,
                       plot_range = "Past year")
```


```{r monthlyFreqTable}
monthly_freq_table <- monthly_frequency_table(gw_level_dv,
                                              gwl_data,
                                              parameter_cd = parameterCd) 
kable(monthly_freq_table, digits = 1)
```

## Daily 2 year plot


```{r dailyPlotShow, fig.width=9}

daily_gwl_plot(gw_level_dv, 
               gwl_data,
               parameter_cd = parameterCd,
               plot_title = plot_title, 
               month_breaks = TRUE, 
               historical_stat = "median",
               y_axis_label = y_label)
```


```{r dailySummary}
daily_summary_table <- daily_gwl_summary(gw_level_dv, 
                                         gwl_data,
                                         parameter_cd = parameterCd) |> 
  select("Begin Date" = begin_date,
         "End Date" = end_date,
         "Days" = days,
         "% Complete" = percent_complete,
         "Lowest Level" = lowest_level,
         "25th" = p25,
         "50th" = p50,
         "75th" = p75,
         "Highest Level" = highest_level)
kable(t(daily_summary_table))
```


## Field Groundwater Level Data

```{r fieldPlot}
gwl_plot_field(gwl_data, 
               parameter_cd = parameterCd,
               plot_title = plot_title,
               flip = FALSE)
```


```{r fieldTable}
siteField <- gwl_data |> 
  site_data_summary(site_col = "monitoring_location_id") 

kable(siteField, digits = 1)

```



### Period of Record - All Data Types



```{r dvPlot}
y_label <- dataRetrieval::read_waterdata_parameter_codes(parameter_code = parameterCd)$parameter_name

gwl_plot_all(gw_level_dv, 
             gwl_data, 
             y_label = y_label,
             plot_title = plot_title,
             parameter_cd = parameterCd,
             flip = FALSE)

```


```{r dailyTable}
siteDaily <- gw_level_dv |> 
  site_data_summary() |> 
  select(Minimum = min_site, 	
         `1st` = p25, 
         Median = p50,
         Mean = mean_site,
         `3rd` = p75,
         Maximum = max_site)

kable(siteDaily, digits = 1)

```

## Salinity Data and Analysis


### Chloride


```{r chloride_plotSHOW}
qw_plot(qw_data, plot_title = plot_title)
```


```{r chloride_trend}
cl_trend <- trend_test(gw_level_dv = NULL,
                      gwl_data = dplyr::filter(qw_data, 
                   CharacteristicName == "Chloride"), 
                     approved_col = c(NA, "ResultStatusIdentifier"),
                     date_col = c(NA, "ActivityStartDateTime"),
                     value_col = c(NA, "ResultMeasureValue"))
kable(cl_trend, digits = 3)
```

```{r chloride_table}
chl_table <- qw_summary(qw_data, 
                        CharacteristicName = "Chloride",
                        norm_range = c(225,999))
kable(chl_table)

```


### Specific Conductance



```{r qwplotReal}
qw_plot(qw_data, "Specific Conductance", 
        CharacteristicName = "Specific conductance")
```

```{r sc_table}
sc_table <- qw_summary(qw_data, 
                       CharacteristicName = "Specific conductance",
                       norm_range = NA)
kable(sc_table)

```



### Specific Conductance vs Chloride


```{r salityPlotDisplay}
Sc_Cl_plot(qw_data, plot_title = plot_title)

```


```{r salityTable}
sc_cl <- Sc_Cl_table(qw_data)

# only show 10 row:
kable(head(sc_cl, 10), 
      col.names = c("Date",
                    "Chloride [mg/L]",
                    "Specific conductance [µS/L]"))
```