1. Course information

1.1. General information

Name of course: Land Surface Process Modelling

Course Code: GEO4-4406

ECTS: 7.5

Category / Level: M (Master)

Teaching period: 3

Contact hours: appr. 6 h / week

Language of instruction: English

1.2. Lecturers

Dr. Derek Karssenberg (coordinator)
Department of Physical Geography
Faculty of Geosciences
Utrecht University
PO Box 80.115
3508 TC Utrecht
the Netherlands
Room 103, Zonneveldvleugel
Phone: (+31) 30 2532768
Fax: (+31) 30 2531145
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Dr. Oliver Schmitz
Department of Physical Geography
Faculty of Geosciences
Utrecht University
Room 102, Zonneveldvleugel

1.3. Place in curriculum and entry requirements

The course provides a theoretical and practical basis of spatio-temporal (process-based) modelling of land surface processes, and is relevant for all disciplines related to land surface processes (hydrology, land degradation, geomorphology, natural hazards, ecology). In addition is provides a background in geoinformatics which is relevant for appropriate use of modelling tools and GIS.

Entry requirements: you must have study entrance permit.

1.4. Aims and content

Numerical simulation models of processes on the earth surface are essential tools in fundamental and applied research in the geosciences. They are used in almost all disciplines in the geosciences, for instance hydrology, geomorphology, land degradation, sedimentology, and most fields in ecology. They are important instruments in research for a number of reasons. First, they provide understanding of how systems work, in particular how system components interact, how systems react to changes in drivers, and how non-linear responses emerge. Also, simulation models can be used to forecast systems, which is essential in planning and decision making. Finally, land surface process models provide a means to evaluate theory of simulated processes against observational data.

In this course we will focus on generic principles of land surface modelling. You will study a number of different approaches to represent land surface processes in a simulation model, including differential equations, rule based modelling, cellular automata, individual (agent) based approaches, and probabilistic models. We will discuss how local interactions in large systems can lead to complexity and the impliction of this for forecasting. Also, you will learn how to combine information from observational data and simulation models using error propagation, calibration, and data assimilation techniques.

During the course you will learn how these principles can be applied in a number of different disciplines, in particular in the field of hydrology, geomorphology, sedimentology, and ecology. You will also learn how very similar approaches are used in other fields, for instance in urban geography and social sciences.

In addition to principles of land surface modelling, you will learn how to use software tools for land surface modelling. You will study theoretical concepts of software environments for land surface modelling, and you will learn how to program land surface models. In this part of the course we will use the Python programming language and PCRaster. These tools provide standard frameworks for model construction and techniques to combine a model with observational data. Other tools for model construction use similar concepts, so you will be able to apply your knowledge from this course to other software environments.

The course aims are:

  • To retrieve a theoretical basis of land surface modelling, including approaches to represent processes and approaches to combine data and models.
  • To retrieve an understanding of how various systems in the geosciences are represented with land surface models.
  • To learn principles of software environments for modelling and how to use these software environments.

1.5. Course outline (time table)

As shown in the outline of the course in the table below, the course consists of two blocks, Model Theory and Geoinformatics. These are run parallel in time. Model theory contains (web)lectures, working groups, and paper assignments. Geoinformatics is taught mainly using computer practicals. At the end of the course you will do a personal project, consisting of a case study model and a written report. The detailed course schedule below gives the date and location of lectures, working groups, and computer practicals. It also provides due dates for the computer practicals and other assignments.

Important: this course is taught following the blended learning model, which implies we combine e-learning and classical learning methods. Note that a large part of the lectures is provided as e-lectures instead of lectures in a classroom. It is strongly recommended to follow the general course outline below strictly, also during self study (e.g. watch e-lectures and read the text in the reader related to a topic in the week the topic is scheduled in the general course outline below). Of course you can allow yourself some flexibility regarding the e-lectures, it is not forbidden to work ahead of time, of course.

_images/courseOutline.jpg
_images/courseSchedule.jpg

time table

1.6. Calculation of final mark

For passing the course you need to:

  • Submit answers to the questions of all computer labs (before the deadline),
  • Active participation in working groups,
  • Hand-in short paper assignment and report on the personal project in time,
  • Get a final mark of 5.5 or higher.

The final mark M is calculated as:

M = 0.2A + 0.6B + 0.2C

with A, the average of the marks for the three short paper assignments, B, the mark for the closed book exam, and C, the mark for the written report on the personal project. A, B, and C are not rounded.

Absence (for instance as a result of illness or family circumstances) during the exam must be agreed with the coordinator of the course in advance by phone or email. You need to hand over a sick note (medical certificate from your doctor) afterwards to get access to a resit.

The course has been passed if the final grade is >=5.5 and all obligations have been fulfilled. If not, and only in case the final grade is 4.00 or higher a repair exam (supplementary test) could be attended. If the repair exam has been successfully passed and all other obligations have been fulfilled, the final grade of the course will be 6.

For details on the above and further information, see the OER (Education and Examination Regulations).

1.7. Study material

All study material needs to be studied for the written exam, except material explicitly indicated as reading material in this document. This information (reading material) is provided in the sections Model Theory content and Geoinformatics content of this document.

1.7.1. Study material: syllabus, book, practicals

Land Surface Process Modelling, syllabus. Available from blackboard.

Articles to be downloaded by yourself (as indicated in this document)

Think Python, An introduction to software design, A. Downey, 2008, Green Tea Press, Needham, 234 pp. Chapters 1, 2, 3, 5, 6, 7, 8, 10, and 14. Online at http://www.greenteapress.com/thinkpython/thinkpython.html or order a print from blackboard.

Computer practicals Map Algebra, available in Blackboard.

Computer practicals Python, available in Blackboard.

Computer practicals modelling with PCRaster Python.

Study material: lectures, powerpoints, and e-Lectures


All lectures, slides, and e-Lectures. For access or download, see the relevant sections in this document.

1.8. OSIRIS information on the course

Additional information is available at https://www.osiris.universiteitutrecht.nl/osistu_ospr/StartPagina.do

1.9. Tutor support

Tutor support: ask fellow students or email d.karssenberg@uu.nl