A project managed by the OSU Institute for Water and Watersheds.
The Willamette Water 2100 project will use Envision, a theoretical framework developed at OSU to evaluate how climate change, population growth, and economic growth will alter the availability and the use of water in the Willamette River Basin. Through Envision, we will investigate the impact of changes in the water budget on water quality, terrestrial ecosystems, aquatic ecosystems, and society’s ability to meet its future needs. Envision integrates these software subsystems:
- a geographic information system that manages data through space and time,
- a standard interface for plugging in hydrological, ecological, and socio-economic process models,
- a multi-agent-based modeling system that can represent human decision making on the landscape, and
- a system for visualizing the results of alternative scenarios.
Envision enables disciplinary models to communicate via a landscape, a shared data repository that represents instantaneous conditions at specific locations. Each time a model runs, it draws its inputs from the landscape and outputs its results to the landscape. From a system perspective, each time a model runs, it draws as its input the outputs from all the other state-of-the-art models running within the framework. Envision synchronizes models as they step through time on their own time scales. For example, it would run a hydrological model with a daily time step 30 times before running a socio-economic model with a monthly time step. Although the socio-economic model might represent hydrological events in a cursory manner, it takes advantage of the calculations that a state-of-the-art hydrological model made during the previous time interval. Envision thereby enables each disciplinary model to gain in predictive power.
Envision also contains a multi-agent-based modeling component that enables it to represent the impact of human decision-making on landscape change. Envision’s “agents” have specific decision-making authority over aspects of the landscape, such as land use and water use. Agents such as federal land managers, dam managers, or city governments can make public management decisions that reflect current and evolving management rules and public policies. Agents such as land owners, agricultural producers, or urban dwellers can make private choices based on opportunities, economic circumstances, and the current conditions of the evolving landscape as determined in the economic models. In many cases, institutional limits in the form of laws and regulations will also constrain these choices. A version of the model representing a different set of policies, management rules, public investments, or other boundary conditions constitutes a scenario.
Envision represents a new paradigm in water research in three respects. First, it achieves unprecedented integration of a range of state-of-the-art hydrological, ecological, and socio-economic models. Second, it incorporates the ability to consider changes in public policy and resource management. Third, it augments the traditional “predict-then-act” decision support paradigm with a novel “explore-then-test” paradigm. In the current “predict-then-act” paradigm, the decision maker selects the optimal outcome and takes the action most likely to realize it. The “predict-then-act” paradigm is poorly suited for problems that present high levels of uncertainty and risk, such as assuring the future availability of water resources. By comparison, the novel “explore-then-test” paradigm looks for resilient strategies that are unlikely to fail. It examines many possible outcomes and tries to identify strategies that produce successful or at least acceptable outcomes for a broad range of them. Envision is ideally suited for an “explore-then-test” paradigm; it can evaluate a range of social responses intended to avoid, mitigate, or adapt to costly future water scarcity.
The Envision website provides greater detail about the framework as well as examples of past projects.
Hulse, D., A. Branscomb, C. Enright, J. Bolte. 2008. Anticipating floodplain trajectories: a comparison of two alternative futures approaches. Landscape Ecology.
Guzy, M. R., C. L. Smith, J. P. Bolte, D. W. Hulse and S. V. Gregory. 2008. Policy research using agent based modeling to assess future impacts of urban expansion into farmlands and forests. Ecology and Society 13(1): 37.