Are watershed management plans selected and preferred by stakeholders considering current climate conditions robust against climate change scenarios? A sensitivity study of stakeholders spatially-explicit preferences

In the light of the changing climate, the importance of designing effective watershed management plans that are likely to be implemented is becoming ever more important. This research introduces a new concept, consensus, for incorporation into stakeholder-guided interactive optimization of watershed management plans. User preferences were mathematically simulated based upon scenarios of possible stakeholder attitudes in sub-basins of an agricultural watershed in Indiana, USA, and incorporated into an existing interactive genetic algorithm (GA) framework. These simulated users along with the watershed hydrologic model were used to evaluate overall preference for and performance of hundreds of different possible distributions of wetlands throughout the Eagle Creek Watershed, weighing cost and environmental concerns on and off of their property. Solutions generated using the interactive GA with the consensus measure performed at least as well as the non-interactively generated baseline solutions, and many out-performed the baseline solutions, with higher peak flow reductions for similar total wetland areas. This result is opposite of what was expected. Previous research has characterized adding stakeholders to the optimization process as a “tradeoff” process, where users sacrifice performance for certain intangible factors. In addition to adding a consensus measure to the interactive GA as an additional objective function, this research also developed a method to select short climate model realizations that best represent extreme flow events arising from climate extremes in the projected future. When the interactively and non-interactively generated solutions were subjected to these extreme climate years, their performance was reduced, even when adjusted for the different magnitudes of expected maximum peak flows. Data issues arising from an interruption to the interactive optimization at generation 30 likely led to some irregularities in the results of this research. Nevertheless, it appears that designing watershed management plans that perform well in the present does not necessarily lead to strong performance in the projected future. Any attempts to address climate change in management plans must do so explicitly.Keywords: flooding, interactive genetic algorithms, climate model ensemble, watershed management plans, human computation, stakeholders, wetlands, WRESTOR

Interactive Watershed Optimization in the Presence of Spatially-varying and Uncertain Stakeholder Preferences

Watershed planning over a geographic area is a difficult task primarily due to the presence of large number of stakeholders and decision makers whose intrinsic conflicting and/or subjective preferences often lead to uncertainty in perceived fitness of planning decisions. Deciding which watershed strategy should be implemented at what location requires a participatory approach to design and decision making, if adoption of landscape decisions is critical to success. Analytical participatory design (APD) approaches aim to enable farmers, environmentalists, government agencies, and other stakeholders to visualize the landscape, explore and design competitive scenarios of implementing certain management practices on the landscape. Since these approaches improve decision makers' awareness of opportunities and constraints in the co-existing physical and human systems, it is hypothesized that they can be used to generate acceptable decisions that are robust to uncertainties in stakeholder preferences. An APD method based on Interactive optimization is described in this paper and tested for design of wetlands in a study watershed site (Eagle Creek Watershed) in the state of Indiana. The method is then used to test research hypothesis by involving multiple virtual stakeholders as surrogates to diverse human users and their preferences. The results indicate that, while, as expected, the interactive optimization approach results in lower values of the financial and environmental objective criteria (which are being traded off against users' diverse subjective personal criteria), it also results in a relatively high degree of user consensus, indicating high likelihood of adoption of the generated solutions by the stakeholders