Urban Hydroinformatics


Prerequisite/Recommended prerequisite for participation in the module

The module adds to the knowledge obtained in Hydrodynamics and Analysis of Time Series, Ground Water Modelling, Hydraulics and Urban Drainage.

Content, progress and pedagogy of the module


Students who complete the module:

Learning objectives


  • Must have knowledge on complex hydrological, hydraulic, chemical, and biological processes in urban drainage systems.
  • Must have knowledge on different numerical models for simulation of relevant complex processes in drainage systems.


  • Must be able to apply commercial models for simulation of relevant processes in drainage systems.
  • Must be able to develop and code simple models for simulation of relevant processes in drainage systems.
  • Must be able to apply methods for calibration and validation of models.
  • Must be able to apply probabilistic methods in order to quantify uncertainties in urban drainage models.


  • Must be able read and understand scientific papers and apply novel methods within urban drainage modelling.
  • Be able to compare observations and simulation results and discuss validity of the latter.

Type of instruction

Lectures, etc. supplemented with project work, workshops, presentation seminars, lab tests.

Extent and expected workload

Since it is a 5 ECTS project module, the workload is expected to be 150 hours for the student.



Name of examUrban Hydroinformatics
Type of exam
Written or oral exam
Individual oral or written exam
AssessmentPassed/Not Passed
Type of gradingInternal examination
Criteria of assessmentThe criteria of assessment are stated in the Examination Policies and Procedures

Facts about the module

Danish titleUrban hydroinformatik
Module codeB-VM-K3G-15
Module typeCourse
Duration1 semester
Language of instructionEnglish
Location of the lectureCampus Aalborg
Responsible for the module


Study BoardStudy Board of the Build Environment
DepartmentDepartment of the Built Environment
FacultyFaculty of Engineering and Science