In USGS-R/HASP: Hydrologic AnalySis Package

library(knitr)
opts_chunk$set(echo = TRUE,
               warning = FALSE,
               message = FALSE,
               fig.width = 7,
               fig.height = 6)
library(dplyr)
library(tidyr)
library(ggplot2)
library(HASP)

options(knitr.kable.NA = '')

This vignette shows how to use R tools, primarily ggplot2, to modify and customize plots generated by HASP. To do this, we use data from site "295204099340201" which taps into the Edwards Aquifer in Texas.

Site Information

library(HASP)
siteID <- "295204099340201"
site_metadata <- site_summary(siteID, markdown = TRUE)
data_info <- data_available(siteID)
kable(data_info)

Get data using dataRetrieval

Using dataRetrieval code to get the data for this site:

library(dataRetrieval)
siteID <- "295204099340201"
parameterCd <- "62610"
statCd <- "00001"
# Daily data:
gw_level_dv <- readNWISdv(siteID, parameterCd, statCd = statCd)

# Field GWL measured:
gwl_data <- readNWISgwl(siteID)

Making and Customizing Plots

Default HASP Monthly Frequency Plot

Use the function HASP::monthly_frequency_plot() to generate a monthly statistics plot.

# set the site title
site_title <- "L -2701\n295204099340201"

# set the ylabel
y_label <- dataRetrieval::readNWISpCode(parameterCd)$parameter_nm 

# make the plot using the HASP function
monthly_frequency_plot(gw_level_dv, 
                      gwl_data = gwl_data,
                      parameter_cd = parameterCd,
                      plot_title = site_title,
                      y_axis_label = y_label)

Customize Color Palette

Use supported optional arguments to change the color palette used to generate the HASP::monthly_frequency_plot plot.

# remake the plot with a custom color palette
monthly_frequency_plot(gw_level_dv,
                       gwl_data = gwl_data,
                       parameter_cd = parameterCd,
                       plot_title = site_title,
                       y_axis_label = y_label,
                       percentile_colors = c(
                         "#d7191c", "#fdae61", "#ffffbf",
                         "#abdda4", "#2b83ba"
                         )
                       )

Further Customization of Multiple Plot Aspects

To fully customize the plot, it is necessary to define the plot object as a variable, which can then be passed to ggplot2 functions.

# define the plot as a variable
p_var <- monthly_frequency_plot(gw_level_dv,
                                gwl_data = gwl_data,
                                parameter_cd = parameterCd,
                                plot_title = site_title,
                                y_axis_label = y_label
                                )

p_var <- ggplot2::update_labels(p_var, list(x = "MONTH",
                                            y = "GWL")
                                )

p_var <- p_var + ggplot2::theme(
  # make the title font size 22 and boldface
  plot.title = ggplot2::element_text(size = 22, face="bold"),
  # make x-axis title size 16 and in italics
  axis.title.x = ggplot2::element_text(size = 16, face="italic"),
  # set y-axis title to size 14
  axis.title.y = ggplot2::element_text(size = 14),
  # make x-axis labels size 10 and dark green
  axis.text.x = ggplot2::element_text(size = 10, colour = "darkgreen"),
  # make y-axis labels size 14 and in italics
  axis.text.y = ggplot2::element_text(size = 14, face="italic"),
  # make the axis lines dark red with a line thickness of 1.2
  axis.line = ggplot2::element_line(colour = "darkred", size = 1.2),
  # make the axis ticks dark blue with a line thickness of 1.4
  axis.ticks = ggplot2::element_line(colour = "darkblue", size=1.4),
  # turn on major grid lines and make them gray and sized 0.1
  panel.grid.major = ggplot2::element_line(colour = "gray50", size = 0.1),
  # set the background color for the plot panel to a light gray
  panel.background = ggplot2::element_rect(fill = "gray90"),
  # set the legend background color to a light gray
  legend.background = ggplot2::element_rect(fill = "gray75"),
  # set the legend text to size 12 and make it italic
  legend.text = ggplot2::element_text(size = 12, face="italic"),
  # set the legend title to size 18
  legend.title = ggplot2::element_text(size = 18)
  )

p_var