Keywords
system dynamics; Flanders; prospective studies; four-step plan; participatory modelling
Location
Session D10: The Role of Modelling in Sustainable Development
Start Date
11-7-2016 3:30 PM
End Date
11-7-2016 3:50 PM
Abstract
The development of energy prices, immigration, and other exogenous factors which are beyond control of the authorities add to the uncertainties in long-term environmental planning. Prospective studies such as the Nature Outlook and Environment Outlook are carried out to assess the existing status of nature and the environment in Flanders, to support the mid- and long-term planning, and to ensure that the environmental targets set by the EU are met. The supporting analyses are based on modelling and data for a wide range of social-economic sectors and thematic domains, including demography, economics, energy, mobility, land-use change, environment, agriculture and food production, waste, water, and air quality. The mutual consistency of these projections is limited due to the weak level of inter-thematic coupling and lack of consideration for feedback in the thematic models used. System dynamics (SD) models provide a natural framework to describe the time-dependent behavior of complex systems with feedback and support long-term policy analyses. Typical strengths of SD models are the high degree of transparency, computational efficiency and flexibility for changes to the model structure due to a modular design. A such, SD models are excellent tools to support the communication between model experts in different domains, environmental managers and stakeholders. Nevertheless, SD models describe systems at the outline level of analysis and more detailed modelling is sometimes needed. Therefore, a four-step approach is adopted to support the mid- and long-term environmental planning, with a central role for SD modelling. In this context, a ‘blueprint’ SD model of Flanders was developed in anticipation of the development of an operational version of the model. This blueprint can be run as stand-alone model to examine the impact of custom-selected combinations of driving factors and policy options on the development of environmental and social-economic indicators. We discuss the general architecture of the model and the design process, which was highly interactive.
Included in
Civil Engineering Commons, Data Storage Systems Commons, Environmental Engineering Commons, Hydraulic Engineering Commons, Other Civil and Environmental Engineering Commons
Blueprint of a System Dynamics Model for Flanders
Session D10: The Role of Modelling in Sustainable Development
The development of energy prices, immigration, and other exogenous factors which are beyond control of the authorities add to the uncertainties in long-term environmental planning. Prospective studies such as the Nature Outlook and Environment Outlook are carried out to assess the existing status of nature and the environment in Flanders, to support the mid- and long-term planning, and to ensure that the environmental targets set by the EU are met. The supporting analyses are based on modelling and data for a wide range of social-economic sectors and thematic domains, including demography, economics, energy, mobility, land-use change, environment, agriculture and food production, waste, water, and air quality. The mutual consistency of these projections is limited due to the weak level of inter-thematic coupling and lack of consideration for feedback in the thematic models used. System dynamics (SD) models provide a natural framework to describe the time-dependent behavior of complex systems with feedback and support long-term policy analyses. Typical strengths of SD models are the high degree of transparency, computational efficiency and flexibility for changes to the model structure due to a modular design. A such, SD models are excellent tools to support the communication between model experts in different domains, environmental managers and stakeholders. Nevertheless, SD models describe systems at the outline level of analysis and more detailed modelling is sometimes needed. Therefore, a four-step approach is adopted to support the mid- and long-term environmental planning, with a central role for SD modelling. In this context, a ‘blueprint’ SD model of Flanders was developed in anticipation of the development of an operational version of the model. This blueprint can be run as stand-alone model to examine the impact of custom-selected combinations of driving factors and policy options on the development of environmental and social-economic indicators. We discuss the general architecture of the model and the design process, which was highly interactive.
