tutorialhydrology

R tutorials for the 6th Workshop on Water Resources in Developing Countries at ICTP in Trieste, Italy.

You have three options to complete the tutorials. Regardless of the method you choose, you are expected to achieve the specified goals. Options 2 and 3 offer opportunities to delve deeper into the topics by working with the datasets in your own R scripts.

Goals

1. First steps in R
   • Simple operations
   • Functions
   • Assignment
   • Packages
2. A small hydrological sporadic dataset
   • Read from XLS
   • Exploring it with basic functions
3. A larger hydrological sporadic dataset
   • Exploring it with package dplyr
4. Plotting with package ggplot2
   • Time series
   • Facets
   • Box and whiskers plots
   • Scatter plots
   • Fit a curve
5. Reshaping the data with package tidyr
   • Long and wide tables
6. Fitting rating curves
   • Preliminary analysis
   • Package bdrc
   • Compare the rating curves
7. Stage hourly time series
   • Percentiles
   • Annual and daily courses
   • Changepoints detection
8. Estimating discharge with the rating curves

Option 1: Do the Tutorials Online

You can interactively engage with the tutorials directly in your browser without needing to download anything. This option is ideal for beginners.

1. Introduction to R and to the hydrological data
2. Plot the hydrological data
3. Fit the rating curve
4. Estimate the discharge using the fitted rating curve

Option 2: Install the Package and Do the Tutorials Locally

You can install the R package tutorialhydrology and run the tutorials locally in your RStudio session. This is recommended for those who are familiar with R or are keen to learn it.

Requirements

• R (≥ 3.5.2)
• RStudio
• R packages:
  • Mandatory: shiny (≥ 1.6.0), learnr, readxl, dplyr, ggplot2, tidyr, lubridate, bdrc, changepoint
  • Recommended: readr, remotes

You can install R packages directly from within R/RStudio with install.packages(<package-name>). To check if they are already installed and available, use library(<package-name>).

Instructions

Install the R package, load it and launch the tutorials.

library(learnr)
library(remotes)
install_github("jobonaf/tutorialhydrology")
library(tutorialhydrology)
run_tutorial(package = "tutorialhydrology", name = "intro")
run_tutorial(package = "tutorialhydrology", name = "plot")
run_tutorial(package = "tutorialhydrology", name = "fit")
run_tutorial(package = "tutorialhydrology", name = "estimate")

Option 3: Clone the Repository and Do the Tutorials Locally

You can also clone the repository tutorialhydrology from GitHub, build the package and then run the tutorials locally. This option is only possible for advanced R users.

Requirements

The same as option 2, plus git.

Instructions

1. Clone from GitHub
   • Use the command git clone https://github.com/jobonaf/tutorialhydrology.git in your shell, or
   • In RStudio: File > New Project > Version Control > Git, or
   • From GitHub: click Code > Download ZIP, then unzip the folder and create a new RStudio project in it with File > New Project > Existing Directory.
2. Open the new RStudio project and use the Build button to build the package.
3. Navigate the tutorials in the Tutorial pane and launch the one you are interested in.
4. If you want, you can modify them in the folder inst/tutorials and rebuild the package.

Work with the Datasets

If you choose options 2 or 3, you can view the dataset descriptions with the command

help(tutorialhydrology)

The package contains three datasets, accessible with the command data(<dataset-name>):

• hourly_n105: Hourly stage data at station N105. A data frame with 176034 rows and 2 columns:
  • datetime: Time of observation
  • H: Stage level (m)
• obs_discharge: Observed hydrological data. A data frame with 9768 rows and 20 columns:
  • Variable, Unit, Value, IdMeasure, Date, TimeStart, TimeEnd, NoBranches (Number of river's branches at the time of the measure), Instrument, Method, NotesMeasure, StationCode, Municipality, Province, Location, River, Basin, SubBasin, Description, NotesStation.
  • Includes variables measured in 19 stations: T_water, H, H_bridge, H_rod, H_select, Q, section_area, section_width, depth_ave, depth_max, speed_ave, speed_max.
• obs_n105: Observed discharge data at station N105 (Torre river in Tarcento). A data frame with 29 rows and 4 columns:
  • TimeStart: Begin of sampling time
  • StationCode: ID of the station
  • H: Stage level (cm)
  • Q: River discharge ($m^3/s$)

These datasets allow you to write your own scripts and perform further analyses. Enjoy exploring!

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Addendum: Publish Your Own Tutorial

To deploy/publish a tutorial on your shinyapps.io account, use the Publish button provided by the package rsconnect in RStudio. Alternatively, in an R session, try the following code:

rsconnect::setAccountInfo(
  name='<your-username>',
  token='<your-token>',
  secret='<your-secret>'
)
rsconnect::deployDoc(
  doc="<path-to-Rmd-file>",
  appName="<short-name>",
  appTitle="<webpage-title>"
)