Case studies of scenario analysis for adaptive management of natural resource and infrastructure systems
- Authors:
-
- Hamilton, M.C. ;
- Thekdi, S.A. ;
- Jenicek, E.M. ;
- Harmon, R.S. ;
-
Goodsite, Michael Evan
;
Close
0000-0002-4565-6607
Department of Business Development and Technology, Aarhus BSS, Aarhus University - Case, M.P. ;
- Karvetski, C.W. ;
- Lambert, J.H.
- DOI:
- 10.1007/s10669-012-9424-3
- Abstract:
- Management of natural resources and infrastructure systems for sustainability is complicated by uncertainties in the human and natural environment. Moreover, decisions are further complicated by contradictory views, values, and concerns that are rarely made explicit. Scenario analysis can play a major role in addressing the challenges of sustainability management, especially the core question of how to scan the future in a structured, integrated, participatory, and policy-relevant manner. In a context of systems engineering, scenario analysis can provide an integrated and timely understanding of emergent conditions and help to avoid regret and belated action. The purpose of this paper is to present several case studies in natural resources and infrastructure systems management where scenario analysis has been used to aide decision making under uncertainty. The case studies include several resource and infrastructure systems: (1) water resources (2) land-use corridors (3) energy infrastructure, and (4) coastal climate change adaptation. The case studies emphasize a participatory approach, where scenario analysis becomes a means of incorporating diverse stakeholder concerns and experience. This approach to scenario analysis provides insight into both high-performing and robust initiatives/policies, and, perhaps more importantly, influential scenarios. Identifying the scenarios that are most influential to policy making helps to direct further investigative analysis, modeling, and data-collection efforts to support the learning process that is emphasized in adaptive management.
- Type:
- Journal article
- Language:
- English
- Published in:
- Environment Systems and Decisions, 2013, Vol 33, Issue 1, p. 89-103
- Main Research Area:
- Social science
- Publication Status:
- Published
- Review type:
- Peer Review
- Submission year:
- 2013
- Scientific Level:
- Scientific
- ID:
- 239965192
