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Abstract
Exploratory Data Visualization for the Physical Properties of Lakes
This lesson was adapted from educational material written by Dr. Kateri Salk for her Fall 2019 Hydrologic Data Analysis course at Duke University. This is the second part of a two-part exercise focusing on the physical properties of lakes.
Introduction
The field of limnology, the study of inland waters, uses a unique graph format to display relationships of variables by depth in a lake (the field of oceanography uses the same convention). Depth is placed on the y-axis in reverse order and the other variable(s) are placed on the x-axis. In this manner, the graph appears as if a cross section were taken from that point in the lake, with the surface at the top of the graph. This lesson introduces physical properties of lakes, namely stratification, and its visualization using the package ggplot2.
Learning Objectives
After successfully completing this notebook, you will be able to:
1. Investigate the concepts of lake stratification and mixing by analyzing monitoring data
2. Apply data analytics skills to applied questions about physical properties of lakes
3. Communicate findings with peers through oral, visual, and written modes
Subject Keywords
Coverage
Spatial
Temporal
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Content
README.md
Exploratory Data Visualization for the Physical Properties of Lakes
This lesson was adapted from educational material written by Dr. Kateri Salk for her Fall 2019 Hydrologic Data Analysis course at Duke University. This is the first part of a two-part exercise focusing on the physical properties of rivers.
Introduction
The field of limnology, the study of inland waters, uses a unique graph format to display relationships of variables by depth in a lake (the field of oceanography uses the same convention). Depth is placed on the y-axis in reverse order and the other variable(s) are placed on the x-axis. In this manner, the graph appears as if a cross section were taken from that point in the lake, with the surface at the top of the graph. This lesson introduces physical properties of lakes, namely stratification, and its visualization using the package ggplot2.
Learning Objectives
After successfully completing this exercise, you will be able to:
-
Investigate the concepts of lake stratification and mixing by analyzing monitoring data
-
Apply data analytics skills to applied questions about physical properties of lakes
-
Communicate findings with peers through oral, visual, and written modes
Requirements to Complete Lesson
Packages
This lesson requires the installation of the following R packages to run the provided script:
tidyverse- Version 1.3.0. A collection of R packages designed for data science.
lubridate- Version 1.7.9. Functions for working with dates/times.
ggplot2- Version 3.3.3. Creates elegant data visualisations using the Grammar of Graphics.
scales- Version 1.1.1. Graphical scales provide methods for automatically determining breaks and labels for axes and legends.
dataRetrieval- Version 2.7.6. Retrieval Functions for USGS and EPA Hydrologic and Water Quality Data.
Data and Code
This lesson will import daily discharge data for the Eno River near Durham, North Carolina for the entire period of record using the dataRetrieval package. The package was created to make querying and downloading hydrologic data from the USGS National Water Information System (NWIS) and the multi-agency database, Water Quality Portal (WQP). NWIS only contains data collected by or for the USGS. It should be noted that the databases are not static as data is constantly being added. For more in-depth information on the dataRetrieval package, please visit:
https://cran.r-project.org/web/packages/dataRetrieval/vignettes/dataRetrieval.html.
The code provided in this resource was developed using R version 3.6.1.
Related Resources
| The content of this resource is derived from | https://lter.limnology.wisc.edu/data |
How to Cite
This resource is shared under the Creative Commons Attribution CC BY.
http://creativecommons.org/licenses/by/4.0/
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