Watershed Analysis
1
Introduction
1.1
Course overview and objectives
1.2
Structure
1.3
Tentative schedule, subject to change
2
Intro to data visualization
2.1
Learning Objectives
2.2
Download and install tidyverse library
2.3
Reading data
2.4
Our first ggplot
2.5
Change point type
2.6
Set colors
2.7
Controlling color with a third variable and other functions
2.8
Plotting multiple groups (adding a third variable)
2.9
Facets
2.10
Two variable faceting
2.11
Boxplots
2.12
More about color, size, etc
2.13
Multiple geoms
2.14
Exit ticket
3
Data wrangling using tidyverse
3.1
Introduction
3.2
Learning objectives:
3.3
You can use R as a calculator
3.4
You can create new objects using <-
3.5
Using functions
3.6
Read in some data
3.7
What is a tibble?
3.8
Data wrangling in dplyr
3.9
Filter
3.9.1
Multiple conditions
3.10
Arrange
3.11
Select
3.12
Mutate
3.13
Summarize
3.14
Multiple operations with pipes
3.15
A final comment on NAs
3.16
That’s it for today
3.17
Exit ticket
4
Lab 1: Data vis, wrangling, and programming (12 pts)
4.1
Problem 1 (1 pts)
4.2
Problem 2 (1 pts)
4.3
Problem 3 (2 pts)
4.4
Problem 4 (2 pts)
4.5
Problem 5 (2 pts)
4.6
Problem 6 (2 pts)
4.7
Summary (2 pts)
4.8
Feeback
4.9
Deliverables
5
dataRetrieval
5.1
Goals
5.2
Exploring what dataRetrieval can do
5.3
First, let’s map these sites.
5.4
Joins
5.5
Join practice example
5.6
Now we know what is available so let’s download some data from the Gallatin site using “readNWISdata”.
6
Lab 2: dataRetrieval and area normalized flows (20 pts)
6.1
Intro
6.1.1
This is knitr settings. Knitr is a package that will turn this Rmd to an html.
6.1.2
Load the necessary packages.
6.1.3
Workflow
6.2
Summary (14 pts)
6.3
Deliverable (6 pts)
7
Statistics in hydrology
7.1
Learning objectives
7.2
Homework Q1 (2 pts)
7.3
What is the difference between a sample and a population?
7.4
Homework Q2 (2 pts)
7.5
Measuring our sample distribution: central tendency
7.6
So what’s a weighted average?
7.7
Measures of variability
7.8
Homework Q3 (2 pts)
7.9
What is a normal distribution and how can we determine if we have one?
7.10
Homework Q4 (2 pts)
7.11
Homework Q5 (2 pts)
7.12
Deliverable (10 pts, due Thursday 2/15 by 11:59 PM)
8
Lab 3: Statistics in hydrology (33 pts)
8.1
Problem 1 (5 pts)
8.2
Problem 2 (5 pts)
8.3
Problem 3 (5 pts)
8.4
Problem 4 (5 pts)
8.5
Problem 5 (5 pts)
8.6
Problem 6 (5 pts)
8.7
Deliverable
9
Hydrographs and rating curves (6 pts)
9.1
Overall Learning Objectives
9.2
Reading
9.3
Lecture
9.3.1
Hydrographs and Rating Curves
9.3.2
Rain versus Snow dominated systems
9.3.3
Making Stage Measurements
9.3.4
Applications of streamflow and stream gage
9.4
Optional activity to gain deeper understanding of rating curve
9.5
Summary questions (6 pts)
10
Lab 4 - Rating curve analysis
11
Flow Duration Curves
11.1
Get data
11.2
Review: describe the distribution
11.3
ECDFs
11.4
Calculate flow exceedence probabilities
11.5
Plot a Flow Duration Curve using the probabilities
11.6
Example use of an FDC
11.7
Compare to a boxplot of the same data
11.8
Challenge: Examining flow regime change at the Grand Canyon
11.9
That’s it! Next we will apply some of these principles to look at low-flow statistics.
12
Lab 5 - Low Flow Analysis
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Watershed Analysis: ENSC 445/LRES 545
Chapter 10
Lab 4 - Rating curve analysis
https://github.com/tpcovino/lab_4