WP6: Model Integration


The goal of this work package is to build and analyze the hierarchy of models, which are developed and applied within this project, and, beyond. This WP will coordinate interaction between other project WPs to integrate models and knowledge generated in various case studies.

We will operate in a generalized 'socio-environmental model space', which will include empirical models, conceptual models, complex computer simulations, and data sets,and which can be characterized in several dimensions, such as model complexity, spatial and temporal resolution, disciplinary coverage, bias and focus, sensitivity and uncertainty, usability and relevance.

We will not restrict ourselves to conventional modelling tools, but will also integrate qualitative models of stakeholder knowledge, opinion and scenarios. We will explore the different models along the complexity continuum to understand how information from more aggregated qualitative models can be transmitted to more elaborated and detailed quantitative simulations, and vice versa.

The inputs from WP2-5 will come as models, data used in the case studies, including stakeholder analysis data, exogenous scenarios, and expert definitions of possible critical changes in the operation of the socio-environmental systems under consideration. Outputs to the other WPs will comprise appropriately adapted model integration methods and results of test applications of these methods in the case studies dealt with in these WPs and across WPs.

Additionally we will address model uncertainty, including sensitivity analysis, as well as the validation problem, the problem of making sure a model is realistic in a problem-domain where many, qualitatively dissimilar types of trajectories are possible, but we only have one to work with.

We will consider various levels of complexity in different geographical scales that should be used when modelling hierarchical systems. We will compare the output from more complex models to what can be generated by simpler models and study models for structural sensitivity to see what happens to system behaviour observed in some simpler models (loss of equilibrium, tipping points, emergent properties, attractors, etc.), when more details are  added to models and when some of these features become no longer evident in the model performance. We will analyze how complexity can be communicated to stakeholders and policy makers.  We will also explore how models can help integrate knowledge among stakeholders, actors, institutions, etc.

The project will span over a hierarchy of geographic scales, where models in one scale will inform models in other scales. For example, global models of climate and economy through disaggregation and downscaling will be used to provide inputs and define boundary conditions for regional and country level models. Reciprocally output from local and regional models will be aggregated and averaged to feed into higher level, global models.

We do realize that important problems related to incompatibility, uncertainty, sensitivity, mismatched resolution and spatio-temporal coverage will need to be resolved along the way. This includes development of innovative methods of communicating rapid, extreme change (shocks) that may be observed in short-term local models with fine temporal resolution, to more coarse resolution larger scale models (regional, global).

University of Twente Newcastle University Stockholm University nierscagora SLU iasa TNO


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