Projects per year
Keywords: model structure, uncertainty, modularity, software design patterns, good modelling practices, crop growth and development.
This thesis is an account of the development and use of a framework to introduce flexibility in crop modelling. The construction of such a framework is supported by two main beams: the implementation and the modelling beam. Since the beginning of the 1990s, the implementation beam has gained increasing attention in the crop modelling field, notably with the development of APSIM (Agricultural Production Systems sIMulator) in Australia, OMS (Object Modelling System) in the United States, and APES (Agricultural Production and Externalities Simulator) in Europe. The main focus of this thesis is on the modelling beam and how to combine it with the implementation beam. I first explain how flexibility is adopted in crop modelling and what is required for the implementation beam of the framework, namely libraries of modules representing the basic crop growth and development processes and of crop models (i.e. modelling solutions). Then, I define how to deal with this flexibility (i.e. modelling beam) and more specifically I describe systematic approaches to facilitate the selection of the appropriate model structure (i.e. a combination of modules) for a specific simulation objective. While developing the framework, I stress the need for better documentation of the underlying assumptions of the modules and of the criteria applied in the selection of these modules for a particular simulation objective. Such documentation should help to point out the sources of uncertainties associated with the development of crop models and to reinforce the role of the crop modeller as an intermediary between the software engineer, coding the modules, and the end users, using the model for a specific objective. Finally, I draw conclusions for the prospects of such a framework in the crop modelling field. I see its main contribution to (i) a better understanding in crop physiology through easier testing of alternatives hypotheses, and (ii) integrated studies by facilitating model reuse.
|Qualification||Doctor of Philosophy|
|Award date||22 Oct 2010|
|Place of Publication||[S.l.|
|Publication status||Published - 2010|
- systems analysis
- computer simulation
- mathematical models
- computer software
- crop production
- crop yield
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