Decision support systems: experiences, lessons and recommendations

Integrated assessment (IA) models and Decision Support Systems (DSS) offer a framework for capturing, storing, and synthesising available knowledge and data to support effective management of complex environmental problems. The nature of DSS projects and the features and functionality of the delivered product vary according to the problem focus and selected modelling methodologies as well as the make-up of DSS development teams and stakeholder groups. Despite this, understanding both the positive outcomes and challenges from past environmental DSS projects can provide learnings for future DSS development. This paper draws on the experience of the authors in developing several DSS for environmental and stakeholder issues to provide recommendations for developing high quality and effective DSS. Introduction Decision Support Systems (DSS), and the inherent metadiscipline of Integrated Assessment (IA) and modelling, and are increasingly recognised as essential tools for understanding and managing complex environmental and resource management problems (McIntosh et al. 2011). These tools provide a framework for capturing, storing, and synthesising available knowledge and data for purposes like: strategic planning, impact assessment, and more generally for generating insights into management alternatives. Often DSS development projects constitute a large investment, typically involving a team of researchers, software developers, and end users. Each DSS project has a unique character, in terms of development purpose, modelling components and techniques, implementation platforms, the degree and extent of stakeholder involvement and needs, and the form and functionality of the final product. Yet, there are useful lessons that both researchers and users can learn from sharing and openly reflecting on development experiences. Whereas the DSS literature often focuses on documenting the DSS components and results, there is little attention given to reflecting on these projects, and what lessons can be gained from them. The aim of this paper is to articulate the role of DSS for supporting environmental management and to describe, and bring together, some general modelling experiences from several DSS developed by the authors for stakeholder problems. The types of DSS that we discuss here are ones that necessarily employ model-based techniques to address environmental problems that require improved system understanding and entail difficult decisions around the need to make multiple trade-offs, usually of a conflicting nature, between socioeconomic and environmental objectives. Jakeman et al. (2013). Decision support systems: experiences, lessons and recommendations. 22nd NSW Coastal Conference, 12-15 November 2013, Glasshouse, Port Macquarie, NSW 2 In the next section we describe the philosophy of integrated assessment and modelling inherent in the proper design of environmental DSS and follow this with a definition of DSS and the stages in their development. We then present an overview of a number of DSS to outline their type, problem focus, purpose, range of disciplines and models included, stakeholders involved and breadth or depth of issues. The paper draws on the results from this analysis to shed light on some of the key lessons, and their implications for future development and use of DSS in coastal management. The nature of integrated assessment and modelling Integrated assessment is a ‘whole of system’ approach which provides a framework for linking the complex, interacting processes that occur within a system. It recognizes both the individual components as well as the linkages between them, and that a disturbance at one point in the system might be translated to other parts of the system. It also recognizes that there can be multiple stakeholders with different (and often conflicting) aims. In particular, tradeoffs between economic, social and environmental outcomes must be considered to improve the sustainability of catchment systems. These types of complex interactions lend themselves to consideration by modelling approaches. In particular, integrated models are required to describe the links between economic, social and environmental system outcomes under various management and climatic regimes. The development and application of these models can enhance communication and interaction between different disciplinary teams and stakeholders. They can also provide a clearer perspective on the integrated nature of the problem. The development and use of models is a major activity of integrated assessment. This is because people think and communicate in terms of models as simplifications of reality. The types of models used include:  Data-driven models which represent measurements and experiments;  Qualitative conceptual models which describe systems and processes;  Quantitative numerical models that formalise qualitative models;  Decision making models that transform the values and knowledge into