# Lesson 4. Homework Challenge: Plot USGS Stream Discharge Data in R

In this data lesson, you explore and visualize stream discharge time series data collected by the United States Geological Survey (USGS). You will use everything that you learned in the previous lessons to create your plots. You will use these plots in the report that you submit for your homework.

Note: this page just shows you what the plots should look like. You will need to use your programming skills to create the plots!

## Learning Objectives

After completing this tutorial, you will be able to:

• Plot USGS Stream Discharge time series data in R

## What You Need

You need R and RStudio to complete this tutorial. Also you should have an earth-analytics directory set up on your computer with a /data directory with it.

### R Libraries to Install:

• ggplot2: install.packages("ggplot2")
• dplyr: install.packages("dplyr")

If you haven’t already downloaded this data (from the previous lesson), do so now.

## About the Data - USGS Stream Discharge Data

The USGS has a distributed network of aquatic sensors located in streams across the United States. This network monitors a suit of variables that are important to stream morphology and health. One of the metrics that this sensor network monitors is Stream Discharge, a metric which quantifies the volume of water moving down a stream. Discharge is an ideal metric to quantify flow, which increases significantly during a flood event.

As defined by USGS: Discharge is the volume of water moving down a stream or river per unit of time, commonly expressed in cubic feet per second or gallons per day. In general, river discharge is computed by multiplying the area of water in a channel cross section by the average velocity of the water in that cross section.

Read more about stream discharge data collected by USGS.

As you can imagine, stream gages can be sensitive to high flows and in the case of an extreme event like a flood are sometimes damaged. However, during the 2013 floods, one stream gage in Boulder, Colorado remained in tact. USGS stream gauge 06730200 located on Boulder Creek at North 75th St. collected data that you will use in the lesson below!

## Work with USGS Stream Gage Data

# set your working directory
# setwd("working-dir-path-here")

library(ggplot2) # create efficient, professional plots
library(dplyr) # data manipulation

# set strings as factors to false
options(stringsAsFactors = FALSE)


## Import USGS Stream Discharge Data into R

Let’s first import your data using the read.csv() function.

discharge <- read.csv("data/week-02/discharge/06730200-discharge-daily-1986-2013.csv",

# view first 6 lines of data
##   agency_cd site_no datetime disValue qualCode
## 1      USGS 6730200  10/1/86       30        A
## 2      USGS 6730200  10/2/86       30        A
## 3      USGS 6730200  10/3/86       30        A
## 4      USGS 6730200  10/4/86       30        A
## 5      USGS 6730200  10/5/86       30        A
## 6      USGS 6730200  10/6/86       30        A


## Challenge

Now that the data are imported, plot disValue (discharge value) over time. To do this, you will need to use everything that you learned in the previous lessons.

Hint: when converting the date, take a close look at the format of the date - is the year 4 digits (including the century) or just 2? Use ?strptime to figure out what format elements you’ll need to include to get the date right.

Your plot should look something like the one below:

## Challenge

Similar to the previous lesson, take the cleaned discharge data that you just plotted and subset it to the time span of 2013-08-15 to 2013-10-15. Use dplyr pipes and the filter() function to perform the subset.

Plot the data with ggplot(). Your plot should look like the one below.