The course provides an introduction to modelling of environmental processes in space and time, with emphasis on processes studied in the fields such as physical geography, ecology, (geo)hydrology, land degradation research, geodynamics of coastal and river systems, and geodynamics of soil and water systems. The course provides a theoretical background for constructing and using computer models to represent environmental processes. Using this theoretical background, the student will evaluate models using different types of software tools for spatio-temporal modelling. At the end of the course, each student works on his/her own modelling case study, dealing with all steps in model development and application.
The course provides an introduction to the theory of different approaches to represent spatio-temporal environmental systems with a computer model. Topics which will be covered are: position of models in the earth- and biosciences, concepts of spatial dynamic modelling, identification of the model structure, bottom-up and top-down modelling, deterministic and stochastic modelling, discretisation of the three dimensional space and time, numerical solution of differential equations, storage based modelling, modelling of plant growth and interaction, cellular automata, spatial interaction: flow and spatial friction networks. In addition, the course deals with concepts available for modelling of specific environmental systems, such as surface and groundwater flow models, plant growth models, sedimentological models and land degradation models. In addition, the course provides an introduction to the concepts and mathematical foundations for evaluating the quality and applicability of a certain model for a specific application. This part of the course covers theory of different methods for sensitivity analysis (local and global), calibration and validation of a model and the choice of the appropriate representation of environmental processes given a certain goal and data availability in a modelling case study.
Students apply the theory in model construction and evaluation of several environmental models. For construction and running the models, a programming language (Python) and an environmental modelling language (PCRaster) will be used, in addition to standard software for data management. The course provides an introduction to the use of the Python programming language (see http://www.python.org) for constructing models and management of spatial and temporal data. Topics dealt with are principles of programming languages, data types and operators, reading and writing files, control flow (loops, conditions) and functions. The concepts of the PCRaster modelling language (see http://pcraster.geo.uu.nl) for construction of spatial temporal models are explained, and applied in computer classes using on-line (interactive) course material. For other types of modelling procedures, it might be needed to use additional software tools, such as 'off the shelf' models, software for groundwater modelling (e.g. MODFLOW), or software for calibrating models (e.g. PEST). These tools are provided for students interested in these topics.
The course is concluded by a 2-3 weeks case study, whereby each student works on his or her own modelling study, dealing with all steps of modelling. Each student will compile a written report of this case study.
The course builds upon 1) the static spatial modelling (map algebra) component of the 2nd year bachelor course SAGIS1/RAGIS1 (Spatial Analysis and GIS1) by teaching spatial modelling through time and 2) a large number of Bachelor courses that include components related to earth systems modelling. It provides a general introduction to theory and practice of process based modelling required for MSc tracks in physical geography (e.g. coastal and fluvial systems, quaternary geology and climate change, natural hazards and earth observation), geology (in particular earth surface processes and sedimentology), ecology, and geocomputation.
You need to have a background at Bachelor level in one of the earth sciences, environmental sciences or ecology and basic knowledge of statistics and mathematics. In addition, it is desirable to have background in static spatial modelling, preferably SAGIS1 or another course that deals with spatial analysis (GIS course, introductionary modelling course). If you do not have a background in static spatial modelling, you can participate, but it is recommended you do some extra exercises at the start of the course (workload approximately 2 days). For additional information regarding required background knowledge, email the course coordinator.
The aim of the course is to understand the theory and practice of spatio-temporal modelling of environmental systems (i.e. earth systems with focus on earth surface processes). The course will teach you theory of modelling in space and time, how to construct a model and how to evaluate the quality of a model against real world data. In a case study, you will apply this knowledge and you will learn how to write a scientific paper reporting results of a modelling study. The course tries to be general in the sense that it does not focus on specific fields of the earth sciences.