Course description
R is a powerful data science tool. It provides a wide variety of statistical, data manipulation and visualisation packages. This course will focus on how to use R and its capabilities for hydrological modelling and climate change impact assessment using simple but robust approaches.
You will be implementing a workflow for hydrological modelling in R from data acquisition, pre-processing, modelling, visualisation, and reporting. The course is eminently practical and based on real world case studies (e.g. Thames catchment) and data (e.g. UKCP18, NRFA).
This is not a course on R programming, so a basic knowledge of R language is required to join the course (e.g. vectors and data types, variables and assignment, install packages, import/export various file formats, etc.).
Upcoming start dates
Suitability - Who should attend?
This training is suitable for professionals in water, hydrology and related sectors (e.g., energy, environment) that want to obtain knowledge on applied aspects of R programming in hydrological modelling.
Outcome / Qualification etc.
What you will learn
On successful completion of this short course you will be able to:
- Identify packages for data manipulation, modelling and visualisation relevant for hydrology and climate impact assessment,
- Process and analyse key input variables to implement a hydrological model,
- Select and setup an appropriate model and R package to simulate climate change impacts on hydrology in a given catchment,
- Report and visualise the modelling outcomes using various techniques tailored to specific audiences.
Training Course Content
Timetable
Day 1:
- Overview and good practice on R and project setup,
- R-packages - most common data manipulation packages relevant to hydrology,
- Hands-on 1: data collection, how to programmatically acquire input data for hydrological modelling from various data providers,
- Hands-on 2: data pre-processing and tidying (e.g., quality assessment, data cleaning and transformation, identify and handling missing data…),
- Hands-on 3: The power of Google Earth Engine and R for hydrological modelling: gridded hydrological data for any catchment globally
Day 2:
- Clinic: Q&A, Common issues (leap days in time series, hydrological year definition, daytime problems...) & practical tips,
- Introduction to R packages for hydrological modelling (pros-cons of each one, modelling process commonalities...),
- Hands-on 4: Set up and run selected hydrological models,
- Hands-on 5: Models calibration and validation. Model intercomparison (performance, purpose...),
- Hands-on 6 (group work): modelling analysis – Climate change (UKCP18) impacts on hydrology
Day 3:
- Group presentations and discussion,
- Introduction to visualization and plotting in R (hydrology focus),
- Hands-on 7: static plotting (2D plots, maps, rainfall runoff plot),
- Hands-on 8: interactive plotting (interactive maps, Shiny, interactive plots),
- Hands-on 9: Rmarkdown for reporting and presenting (pdfs, word, text +code, slides),
- Group presentations, Q&A and course feedback.
Course delivery details
Course structure
The course is organised into three days; 1) data pre-processing, 2) modelling and 3) visualisation. The course combines short introductory lectures, hands-on sessions and group work using real world case studies to provide a rich and effective learning experience.
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Cranfield University
Cranfield is a specialist postgraduate university that is a global leader for education and transformational research in technology and management. We have many world-class, large-scale facilities, including our own global research airport, which offers a unique environment for transformational education...