EAWAG Summer School: Environmental Systems Analysis

The course provides an introduction to model-based data analysis in the environmental sciences. It covers model construction, sensitivity analysis, frequentist and Bayesian inference, and estimation of model prediction uncertainty. As prediction in the environmental sciences usually requires the combination of prior knowledge with measured data, there is an emphasis on Bayesian techniques.

The course is targeted at researchers who are interested in analyzing their data with mathematical models. This includes PhD students, post-doctoral researchers, and senior research scientists. The course consists of lectures, practice sessions based on didactical exercises, and discussion of problems of the participants. The participants are encouraged to bring their data sets and models to start working on their own problems during the course.

The course will be very intensive to optimize the benefit of the participants.

Objectives

• Provide an overview of systems analysis techniques relevant for model-based data analysis in the environmental sciences.


• Get practice in applying these techniques with the statistical and graphics software package R (www.r-project.org) and selected more specific data analysis programs.


• Get advice and do first steps in analyzing your own data set(s).


• Learn from the approaches chosen by the other participants for analyzing their data.

Topics

• Part I: Models in the Environmental Sciences
  Importance of models, causes of uncertainty in model predictions, description of uncertainty, mathematical representation of models.


• Part II: Identification of Models
  Construction of models, preliminary analysis, sensitivity analysis, frequentist inference (statistical tests, confidence regions, estimators, input uncertainty, model structure selection, numerical approaches), Bayesian inference (elicitatation and formulation of prior knowledge, combining prior knowledge with data, model averaging, input uncertainty, robust Bayesian analysis, numerical techniques such as importance sampling and Markov Chain Monte Carlo and simulation).


• Part III: Model Predictions
  Uncertainty of model predictions in the frequentist and Bayesian frameworks.

Lecturers

Peter Reichert and Carlo Albert, Eawag Dübendorf and ETH Zurich, Switzerland
Dmitri Kavetski, School of Engineering, University of Newcastle, Callaghan, Australia.
The practice sessions will be supported by Anne Dietzel and Simon-Lukas Rinderknecht.

Target Audience

PhD students, post-doctoral researchers and senior research scientists interested in applying statistical techniques of model-based data analysis.

Location

Eawag, Swiss Federal Institute of Aquatic Science and Technology, 8600 Dübendorf, Switzerland (hwww.eawag.ch). Eawag can be reached by a 10 minutes train ride and a 15 minutes walk from Zurich, Switzerland.

See www.eawag.ch/about/standorte/anreise_dd/index_EN for more details.

Course Organisation

The course will be split into four types of activities:

· Lectures will provide the basic underlying theory of all relevant techniques.

· Exercises will deepen the theoretical knowledge and demonstrate how the techniques can be applied using the statistics and graphics software package R (http://www.r-project.org) and selected more specific data analysis programs.

· Application sessions will give the participants the chance to start applying the techniques to their own data sets. The participants will be supported in choosing adequate techniques to address the needs for their own data analyses.

· Short presentations of problems of the participants for analyzing their data, and discussion of solution strategies.

· Outlook to techniques not dealt with in detail during the course.

Course Documentation

A comprehensive manuscript on Environmental Systems Analysis and selected more specific papers will be distributed to the participants.

Course Fee

The course fee is CHF 800.-- for participants not belonging to an institution of the ETH domain. It includes documentation, coffee and lunches, but it does not include accommodation.

Accommodation

It is the responsibility of the participants to book their hotel. Eawag can be reached by a 10 minutes walk from hotel Sonnental in Dübendorf (www.zuerich-hotels.ch/html/?20), but as Eawag can be reached by a 10 minutes train ride and a 15 minutes walk from Zurich, hotels in Zurich can also be chosen (www.zuerich.com/en/welcome.cfm).

Application

Please send your application by email to Karin Ghilardi by March, 31. Please include your affiliation, billing address, and a short description of your working area. The number of participants is limited to 30. The participants will be considered according to the time of their application.