Title: Reduced Complexity Modeling of Eco-hydrologic Change in Intensively Managed Landscapes
Abstract: As climate changes and land is put to more intensive use, landscapes are pushed towards new eco-hydro-geomorphologic states that we cannot fully predict. Over-parameterized multi-physics based models are infeasible over large domains and periods of time, suffering also from lack of data to accurately parameterize them. On the other hand, reduced complexity models (RCMs) that capture the essential system dynamics have the ability to reveal emergent behavior and critical processes or interactions relevant to system behavior, prediction, and management. This talk will explore how blending mathematical formalisms and process-based knowledge can advance our predictive ability of complex environmental systems in response to perturbations and guide adaptation and mitigation actions. Examples will be presented on building RCMs to predict hot spots of river migration and synchronization of sediment fluxes, predict regime transitions in stream biota due to competing bio-physical processes, and explore efficacy of wetland connectivity within a river network perspective to optimize nitrogen removal in Midwestern agricultural landscapes.