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.).

At a glance

  • Dates
    • 26 - 28 Mar 2024
  • Duration3 days
  • LocationCranfield campus
  • Cost£900

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.

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.


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.

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.

Accommodation options and prices

This is a non-residential course. If you would like to book accommodation on campus, please contact Mitchell Hall or Cranfield Management Development Centre directly. Further information regarding our accommodation on campus can be found here.

Alternatively you may wish to make your own arrangements at a nearby hotel.

Location and travel

Cranfield University is situated in Bedfordshire close to the border with Buckinghamshire. The University is located almost midway between the towns of Bedford and Milton Keynes and is conveniently situated between junctions 13 and 14 of the M1.

London Luton, Stansted and Heathrow airports are 30, 90 and 90 minutes respectively by car, offering superb connections to and from just about anywhere in the world.

Further location and travel details

Location address

Cranfield University
College Road
MK43 0AL

Read our Professional development (CPD) booking conditions.