Discover how to turn water-system data into reliable insights by selecting suitable analysis methods, interpreting results and communicating findings clearly.
Data Analysis in Water Engineering and Management (WEM) provides a practical introduction to the analysis of observational data from water systems. This course helps you develop both the analytical skills and the structured approach needed to investigate datasets.
Participants learn how to select suitable methods for a given dataset, how to interpret the results in context, and how to communicate findings clearly. The course covers commonly used data analysis techniques for spatial data and multivariate data, with specific attention to challenges and limitations that often arise in practice. The course is especially relevant for professionals who want to strengthen their ability to use data in (water) engineering.
With growing use of monitoring technologies, environmental sensors and data-driven approaches, professionals in water engineering and management are expected to work with larger and more complex datasets than before. Professionals therefore need more than technical software skills; they need to know how to assess data quality, choose appropriate analysis techniques, interpret results critically and communicate conclusions. These skills are essential for informed and reliable decision making.
This is a regular master-level course in which both students and professionals can participate. In the first part of the course, participants are introduced to a set of core analysis techniques, including dealing with missing data, interpreting outliers, assessing statistical significance, and applying methods to spatial and multivariate datasets. These techniques are practiced using Python or Matlab.
The second part of the course focuses on an assignment in which you will analyse a dataset linked to a water related question. You choose suitable methods, apply them to the dataset, and interpret the results in a structured and transparent way. Assignments are typically completed in self-selected groups of two, although individual work is also possible. Professionals may also bring in their own data problem where appropriate.
Details and assessment:
Lectures are not mandatory but strongly support in understanding the material. Tutorials can often be completed independently. Teaching is on campus, and recorded lectures may be available.
This course is intended for professionals who want to strengthen their data analysis skills in the context of water systems. Typical profiles include, but are not limited to, water managers, hydraulic engineers, environmental analysts, researchers, data-oriented engineers, consultants, and professionals working in monitoring, modelling or water-related policy support. Participants are expected to have prior knowledge of introductory statistics and basic programming skills in Python or Matlab.
Start date: November (Q2)
Total duration: lectures and tutorials in November and December, assignment phase in January - (timing is flexible in case of individual assignment) (140 hours study load)
Number of teaching days / sessions: Six lecture/tutorial blocks + Q&A during assignment phase
Total programme fee: €2067,15 (5 ECTS × €413,43)
Programme type: master course
Location: University of Twente, Enschede, NL
Language of instruction: English
Admission requirements: Prior knowledge of introductory-level statistics and basic programming skills in Matlab, Python, or a similar programming language. A BSc-level background in Civil Engineering, Environmental Engineering, or a related field is recommended.
Teachers: