On the design of computer-based models for integrated environmental science

• Published in: Environmental management (New York) 2005-06, Vol.35 (6), p.741-752
• Main Authors: McIntosh, Brian S, Jeffrey, Paul, Lemon, Mark, Winder, Nick
• Format: Article
• Language: English
• Subjects: Computer Simulation; Conservation of Natural Resources; Decision Making; Environment; Environmental management; Environmental science; Freshwater resources; Freshwater resources management; Policy and planning; Policy Making; Social Conditions; Water Supply
• ISSN: 0364-152X; 1432-1009
• DOI: 10.1007/s00267-004-0172-0

The current research agenda in environmental science is dominated by calls to integrate science and policy to better understand and manage links between social (human) and natural (nonhuman) processes. Freshwater resource management is one area where such calls can be heard. Designing computer-based models for integrated environmental science poses special challenges to the research community. At present it is not clear whether such tools, or their outputs, receive much practical policy or planning application. It is argued that this is a result of (1) a lack of appreciation within the research modeling community of the characteristics of different decision-making processes including policy, planning, and (2) participation, (3) a lack of appreciation of the characteristics of different decision-making contexts, (4) the technical difficulties in implementing the necessary support tool functionality, and (5) the socio-technical demands of designing tools to be of practical use. This article presents a critical synthesis of ideas from each of these areas and interprets them in terms of design requirements for computer-based models being developed to provide scientific information support for policy and planning. Illustrative examples are given from the field of freshwater resources management. Although computer-based diagramming and modeling tools can facilitate processes of dialogue, they lack adequate simulation capabilities. Component-based models and modeling frameworks provide such functionality and may be suited to supporting problematic or messy decision contexts. However, significant technical (implementation) and socio-technical (use) challenges need to be addressed before such ambition can be realized.