Uncertainty Propagation in Modelling

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Uncertainty Propagation in Spatial Environmental Modelling

10 - 14 December 2018


Picture UPSEM 2018.jpgDue to various causes errors can propagate through environmental models. Although users may be aware ofi t,they rarely pay attention to this problem. However, the accuracy of the data may be insufficient for the intended use, causing inaccurate model results, wrong conclusions and poor decisions. The purpose of this course is to familiarize participants with statistical methods to analyse uncertainty propagation in spatial modelling, such that they can apply these methods to their own models and data. Both attribute and positional errors are considered. Attention is also given to the effects of spatial auto- and cross-correlations on the results of an uncertainty propagation analysis and on methods to determine the relative contribution of individual sources of uncertainty to the accuracy of the final result. Quantification of model parameter uncertainty is covered using Bayesian calibration techniques. The methodology is illustrated with real-world examples. Computer practicals make use of the R language for statistical computing.
This course:

  • focuses on uncertainty propagation in spatial models, while SUADM concentrates on uncertainty analysis of dynamic models;
  • uses basic to intermediate statistical approaches and graphical tools to analyse uncertainty and uncertainty propagation, while SUADM uses more advanced statistical approaches;
  • dedicates one full day to the use of geostatistics for quantification of spatial uncertainty, while SUADM draws specific attention to stochastic sensitivity analysis.
  • Day 1, morning: Course overview; lectures and exercises probabilistic modelling of uncertainty; lecture and exercises Taylor series method.
  • Day 1, afternoon: Computer practical Taylor series method.
  • Day 1, evening: Group dinner in Wageningen town.
  • Day 2, morning: Lecture and exercises Monte Carlo method and quantification of uncertainty source contributions.
  • Day 2, afternoon: Computer practical Monte Carlo method and analysis of uncertainty source contributions.
  • Day 3, morning: Lecture and exercises geostatistics for spatial uncertainty quantification.
  • Day 3, afternoon: Computer practical geostatistics.
  • Day 4, morning: Lecture and exercises Bayesian calibration for quantification of model structural and model parameter uncertainty.
  • Day 4, afternoon: Computer practical Bayesian calibration.
  • Day 5, morning: Lecture, exercises and computer practical positional uncertainty propagation.
  • Day 5, afternoon: Guest lecture; course evaluation; uncertainty game; drinks and snacks.

The last 45 minutes of each afternoon (except for Friday) are reserved to either continue the scheduled computer practical or apply the methods learnt to your own models and data.

General information
Target Group The course is aimed at PhD candidates and other academics working with spatial models who want to know how errors in model inputs and parameters propagate to model outputs.
Group Size Min. 15, max. 25 participants
Course duration 5 days
Language of instruction English
Frequency of recurrence Once every two years
Number of credits 1.5 ECTS
Lecturers Prof.dr.ir. Gerard Heuvelink (Soil Geography and Landscape group, Wageningen University) and Dr.ir. Sytze de Bruin (Laboratory of Geo-information Science and Remote Sensing, Wageningen University)
Prior knowledge Intermediate knowledge of statistics, geo-information science and spatial modelling. Familiarity with the R programming language is preferred but not required.
Location Wageningen University Campus
Options for accommodation Accommodation is not included in the fee of the course, but there are several possibilities in Wageningen. For information on B&B's and hotels in Wageningen please visit proefwageningen.nl. Another option is Short Stay Wageningen. Furthermore Airbnb offers several rooms in the area. Note that besides the restaurants in Wageningen, there are also options to have dinner at Wageningen Campus.


Fees 1
PE&RC  / SENSE PhD candidates with an approved TSP € 360,- € 410,-
All other PhD candidates
Postdocs and staff of the above mentioned Graduate Schools
€ 760,- € 810,-
All others € 1.120,- € 1.170,-

1 The course fee includes a reader, coffee/tea, and lunches. It does not include accommodation (NB: options for accommodation are given above)
2 The Early-Bird Fee applies to anyone who REGISTERS ON OR BEFORE 12 NOVEMBER 2018


  • If you need an invoice to complete your payment, please send an email to office.pe@wur.nl, including ALL relevant details that should be mentioned on the invoice (e.g., purchase order no., specific addresses, attendees, etc.).
  • The Early-Bird policy is such that the moment of REGISTRATION (and not payment) is leading for determining the fee that applies to you.
  • Please make sure that your payment is arranged within two weeks after your registration.
  • It is the participant's responsibility to make sure that he/she (or his/her secretary) completes the payment correctly and in time.
PE&RC Cancellation Conditions
  • Up to 4 (four) weeks prior to the start of the course, cancellation is free of charge.
  • Up to 2 (two) weeks prior to the start of the course, a fee of € 360,- will be charged.
  • In case of cancellation within two weeks prior to the start of the course, a fee of € 760,- will be charged.
  • If you do not show at all, a fee of € 1.120,- will nevertheless be charged.

Note: If you would like to cancel your registration, ALWAYS inform us (and do note that you will be kept to the cancellation conditions)

More information

Dr. Gerard Heuvelink
Phone: +31 (0) 317 482716
Email: gerard.heuvelink@wur.nl

Dr. Lennart Suselbeek (PE&RC)
Phone: +31 (0) 317 485426
Email: lennart.suselbeek@wur.nl


To register, please enter your details below and click "Register".