Decision support systems: a framework for re-engaging end-users and improving model uptake

E. C. Heagney*, J. E. Ling, B. Alexander, N. Saintilan

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contributionpeer-review


The Rivers & Wetlands Unit of the NSW Office of Environment & Heritage recently commissioned 4 Environmental Decision Support Systems (DSSs) as the culmination of a 3-year $8.1M multi-disciplinary research program that focused on better use of environmental water in Australia's rivers and wetlands. The program also included a substantial knowledge & adoption component aimed at effecting uptake of scientific outputs, including a number of presentations and hands-on training workshops focused specifically on DSSs. However, subsequent evaluation indicated that uptake of DSSs remained low, as is typical of many DSSs, and identified significant potential for policy makers and water managers to become disengaged from ongoing model use and development. In the context of environmental water management in Australia, the critical state of river and wetland ecosystems requires that management is underpinned by the best available science, and large and controversial expenditures associated with the purchase of environmental water have brought increased public scrutiny and a heightened requirement for transparent and accountable decision-making. The DSSs produced under this program have been designed specifically to address some of these emerging policy and management requirements, but if they are to fulfill their intended function and feature in future decisions regarding the management of environmental water, it will be necessary to re-invent models and re-engage intended end-users around DSSs and the model development process. We undertook a social research program comprising in-depth interviews with 47 internal and external scientists, policy makers and water managers to identify characteristics of DSS models and the model development process that may present barriers to uptake and individuals' perceptions of science and scientific tools more generally. Primary barriers to uptake for our DSSs related to concerns regarding model accuracy - particularly where models did not adequately incorporate or simulate managers' experiential knowledge or where individuals feared that model outputs from scenario testing might become prescriptive for management - and poor model accessibility - particularly relating to slow data turnaround times that can mean that information is not available to managers when it is required. In order to address these concerns and re-engage stakeholders around DSS models and the model development process, we have developed a confidence-for-purpose framework - where models are required to demonstrate some pre-determined benchmark of data accuracy / reality, set in close consultation with the intended end-users, before they are applied to increasingly complex management functions. Ongoing dialogue established through the process of bench-marking would also allow decisions regarding future investments in next-generation models and/or simplified operational equivalents to be made jointly by model developers and end-users, to achieve a working balance between model accuracy and accessibility - a challenge inherent in all DSSs.

Original languageEnglish
Title of host publicationMODSIM 2011
Subtitle of host publication19th International Congress on Modelling and Simulation: proceedings
EditorsF. Chan, D. Marinova, R. S. Anderssen
Place of PublicationCanberra
PublisherModelling & Simulation Society Australia & New Zealand
Number of pages7
ISBN (Print)9780987214317
Publication statusPublished - 2011
Externally publishedYes
Event19th International Congress on Modelling and Simulation - Sustaining Our Future: Understanding and Living with Uncertainty, MODSIM2011 - Perth, WA, Australia
Duration: 12 Dec 201116 Dec 2011


Other19th International Congress on Modelling and Simulation - Sustaining Our Future: Understanding and Living with Uncertainty, MODSIM2011
CityPerth, WA


  • Decision Support Systems
  • End-user engagement
  • Knowledge and adoption
  • Model uptake


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