Digitalization in the Water Sector

10 credits

Syllabus, Master's level, 1HY215

Code
1HY215
Education cycle
Second cycle
Main field(s) of study and in-depth level
Water Engineering A1F
Grading system
Fail (U), Pass (3), Pass with credit (4), Pass with distinction (5)
Finalised by
The Faculty Board of Science and Technology, 5 February 2024
Responsible department
Department of Earth Sciences

Entry requirements

120 credits including Computer Programming I. Field methods in Earth Sciences or Measurement methods in the water sector or Meteorology, Hydrology and Environmental Measurement Techniques. Participation in course Distribution and treatment of drinking water, or Municipal and industrial waste water treatment. Proficiency in English equivalent to the Swedish upper secondary course English 6.

Learning outcomes

Upon completion of the course, the student should be able to:

  • critically reflect on the historical development and current application of digitalization in the water sector, including the strengths, weaknesses, opportunities and threats with digitalization,
  • design and critically evaluate digitalization schemes in the water sector,
  • Identify the security risks and ethical implications associated with different data transfer and storage systems,
  • analyze time series for trends, periodic signals, and outliers using statistical methods,
  • Implement and interpret the results of process-based and data-driven models for relevant water sector applications,
  • plan and conduct projects related to digitalization in the water sector.

Content

The course covers driving forces and adaptation measures for digitalization in the water sector, which encompasses drinking water and wastewater utilities, stormwater management, and the interconnection of the water, food and energy sectors. Digitalization is considered within the contexts of water quality monitoring, treatment process control, and pipe network and reservoir operations through the application of real-time monitoring, automatic control, sensors, remote sensing, and Internet of Things. The digitalization tools included in the course are machine learning, artificial intelligence, and statistical and process-based mechanistic modelling. Special attention is given to data transfer and IT security, as well as ethics related to digitalization.

The course includes project work with digitalization case studies. Project work may be integrated with other educational programs.

Instruction

Lectures, seminars, computer exercises, project work in groups. Project work with other educational programs may be included.

Assessment

Seminars and exercises (5 credits), written and oral presentation of project work (5 credits).

Other directives

This course cannot be included in the same degree as 1HY850 Digital Water for Sustainable Cities due to content overlap.

No reading list found.

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