Exploration and Visualization of Patterns Underlying Multistakeholder Preferences in Watershed Conservation Decisions Generated by an Interactive Genetic Algorithm

Abstract

In multiple watershed planning and design problems, such as conservation planning, quantitative estimates of costs, and environmental benefits of proposed conservation decisions may not be the only criteria that influence stakeholders' preferences for those decisions. Their preferences may also be influenced by the conservation decision itself—specifically, the type of practice, where it is being proposed, existing biases, and previous experiences with the practice. While human-in-the-loop type search techniques, such as Interactive Genetic Algorithms (IGA), provide opportunities for stakeholders to incorporate their preferences in the design of alternatives, examination of user-preferred conservation design alternatives for patterns in Decision Space can provide insights into which local decisions have higher or lower agreement among stakeholders. In this paper, we explore and compare spatial patterns in conservation decisions (specifically involving cover crops and filter strips) within design alternatives generated by IGA and noninteractive GA. Methods for comparing patterns include nonvisual as well as visualization approaches, including a novel visual analytics technique. Results for the study site show that user-preferred designs generated by all participants had strong bias for cover crops in a majority (50%–83%) of the subbasins. Further, exploration with heat maps visualization indicate that IGA-based search yielded very different spatial patterns of user-preferred decisions in subbasins in comparison to decisions within design alternatives that were generated without the human-in-the-loop. Finally, the proposed coincident-nodes, multiedge graph visualization was helpful in visualizing disagreement among participants in local subbasin scale decisions, and for visualizing spatial patterns in local subbasin scale costs and benefits.