Details / Topics / Slides / Check / Resources / R at EGU2019 / Citation
Conveners: Alexander Hurley, Louise Slater, Lucy Barker, Guillaume Thirel, Claudia Vitolo, Ilaria Prosdocimi
- Where? Monday 08 April, 16:15-18:00 in Room -2.16 (basement!);
- Using R in Hydrology (link to session)
- What? This session is aimed at hydrologists who are interested in hearing more about R as well as those who are advanced R programmers wanting to discuss recent developments in an open environment.
- The session is organised in cooperation with the Young Hydrologic Society (YHS) .
- Participants are invited to post and discuss questions in the Hydrology in R Facebook group
The detailed and time-tabled list of contributions, tutorials and discussion points will be here as soon it's ready.
All materials to reproduce the slides and analyses are available on this repository. To get everything (slides, data, code, etc.) onto your local machine, we recommend to download the whole github course repository. Individual presentations (.html or PDF files) can be downloaded from the presentations folder and viewed in a regular web browser.
Links to individual presentations (for direct view in browser) are below:
- Course intro and getting to grips with R in Hydrology // A. Hurley, I. Prosdocimi
- Obtaining, cleaning and visualizing hydrological data with R // A. Hurley
- Introduction to parallel and high performance computing for hydrologists // L. Slater
- Staying up-to date: automating tasks from downloading data to reporting // A. Hurley
- Using R Shiny to visualise and share your data: A UK drought story // L. Barker
- Modelling the hydrological cycle in snow-dominated catchments // G. Thirel
- Community-led initiatives: get involved! // C. Vitolo, A. Hurley
We will provide any relevant information you require to follow along during the course in due time. This includes software (versions) and any other materials. Stay tuned!
Update: We've chosen a presentation-style delivery of the course, rather than a hands-on workshop. You are more than welcome to follow along in the raw (if provided) or rendered versions of any materials. However, some operations, such as downloading and handling rasters, take multiple minutes. If you do want to execute code provided in the raw documents, we advise to give it a try in advance of the course, and ask questions where/if necessary during the session. Required packages are highlighted where necessary.
- CRAN Hydrology TaskView
- airGR - a description of the airGR package (IRSTEA GR Hydrological Models)
- R-Resources for Hydrology - a detailed list of R resources for hydrology (slightly outdated now)
- rnrfa - an R package to interact with the UK National River Flow Archive (GitHub repo)
- hddtools - an R package to facilitate access to a variety of online open data sources for hydrologists
We recommend the PICO presentation Using R in Hydrology: recent developments and future directions delivered by Louise Slater in the session Innovative methods to facilitate open science and data analysis in hydrology - from data collection in challenging environments to data sharing, visualization and modelling. This presentation is based on our discussion paper in HESS with the same title.
There are a number of other short courses using R that may be of interest to you:
- Building Bayesian Spatial Models to predict landslides by using R-INLA (co-organized)
- End-member modelling analysis of grain-size data in R (co-organized)
- Geocomputation with R (co-organized)
- Writing and maintaining R packages (co-organized)
Please refer to this course as:
- Alexander Hurley, Louise Slater, Guillaume Thirel, Lucy Barker, Claudia Vitolo, Ilaria Prosdocimi, & Shaun Harrigan. (2019, April). Using R in Hydrology at EGU2019 (Version v1.0.0). Zenodo. http://doi.org/10.5281/zenodo.3236979
BibTeX
@misc{alexander_hurley_2019_3236979,
author = {Alexander Hurley and
Louise Slater and
Guillaume Thirel and
Lucy Barker and
Claudia Vitolo and
Ilaria Prosdocimi and
Shaun Harrigan},
title = {Using R in Hydrology at EGU2019},
month = apr,
year = 2019,
doi = {10.5281/zenodo.3236979},
url = {https://doi.org/10.5281/zenodo.3236979}
}