Reduced Complexity Modeling of Linked Hydrological, Thermal Pollution, and Nitrogen Transportation Dynamics at the Regional Scale Using STELLA

Abstract:

The growing complexity among interdisciplinary studies of the food-energy-water systems (FEWS) nexus invites a greater need for communication among researchers and stakeholders regarding our most critical shared resources. While the objective is to achieve realism in modeling dynamic systems, balancing this with simplicity becomes important for analyzing and debugging simulation, but also for making them more understandable - and actionable - to policymakers. In this study, a suite of stand-alone models is built and coupled in STELLA to create a simplified adaptation of more complex hydrological and environmental models. Implementing this icon-based programming language offers clarity in tailoring many broad parameters needed to otherwise represent real geographic regions and integrated phenomena that include anthropogenic scenarios. This reduced complexity modeling effectively captures dynamic connections and interactions among multiple variables, such as precipitation, temperature, river discharge, physical properties of soil and waterways, agriculture, atmospheric deposition and fixation, livestock, industrial fertilizer, nitrogen flux, thermal pollution arising from power plants, and power station technologies. The modeling creates a visual interpretation to clearly communicate the functionalities and results of more comprehensive models, including WBM, TP2M, CTM, and SPARROW. This study is part of an NSF project to bolster understanding of climate-induced extremes on FEWS in the Northeast and Midwest of the US. The outcome of this study will not only be used in a charrette process uniting the NSF project with researchers and stakeholders but can also become a great tool for education and further quantitative analysis. The models have been part of a summer STEM effort in which undergraduate students performed essentially all of the computer modeling.