Anticipating floodplain trajectories: a comparison of two alternative futures approaches

Authored by John P Bolte, David Hulse, Allan Branscomb, Chris Enright

Date Published: 2009-10

DOI: 10.1007/s10980-008-9255-2

Sponsors: United States Environmental Protection Agency (EPA) Oregon State University Pacific Northwest Ecosystem Research Consortium University of Oregon United States National Science Foundation (NSF)

Platforms: No platforms listed

Model Documentation: Other Narrative

Model Code URLs: Model code not found

Abstract

Scenario-based investigations explore alternative future courses of action in a widening array of situations. Anticipating landscape patterns and the values behind them are recurring needs in such investigations. While it is accepted that how scenario assumptions are framed and who frames them matters, the sensitivity of resulting trajectories to contrasting scenario framing and modeling processes is rarely tested. Using comparable scenarios we contrast landscape change trajectories produced from two distinct approaches to modeling scenario assumptions: the first uses lay citizen groups and deterministic land allocation modeling, the second uses experts from biophysical and social sciences and agent-based modeling. Scenarios are defined and mapped for the year 2050 in western Oregon's Willamette River Basin along a gradient of conservation oriented to development-oriented assumptions using first citizen-based and then expert-based approaches. The landscape variability and trajectories for the citizen-based Conservation 2050 and Development 2050 scenarios are then characterized and compared with those of the expert-based Conservation 2050 and Development 2050 scenarios. Results distinguish areas where trajectories always vary regardless of approach or scenario from those that never vary. Policy influence on trajectory is illustrated using agent-based model results where land conversion serves purposes of wealth production and ecosystem function. Results depict areas with strong coupling between policy and trajectory as those places experiencing the same pattern of change over time regardless of scenario. Results also indicate that the greater the variability of a given scenario's trajectories, the more successful the scenario is at avoiding scarcity of wealth and ecosystem function.

Tags

Agent-based modeling Alternative future scenarios Variant/invariant analysis