4.0 Article

Iowa Urban FEWS: Integrating Social and Biophysical Models for Exploration of Urban Food, Energy, and Water Systems

Journal

FRONTIERS IN BIG DATA
Volume 4, Issue -, Pages -

Publisher

FRONTIERS MEDIA SA
DOI: 10.3389/fdata.2021.662186

Keywords

urban FEWS; agent-based model (ABM); life cycle assessment (LCA); soil and water assessment tool (SWAT); building energy use (EnergyPlus); co-simulation

Funding

  1. NSF INFEWS Research grant [1855902]
  2. McIntire-Stennis funding

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Most people live in urban areas with high population densities, heavy reliance on external resources, and large waste production, leading to severe environmental impacts. Integrated study of urban areas involves social and biophysical data modeling, aiming to improve system function and sustainability. The research focuses on analyzing the urban food-energy-water systems (FEWS) nexus, using co-simulation to assess current and future conditions and enhance resilience.
Most people in the world live in urban areas, and their high population densities, heavy reliance on external sources of food, energy, and water, and disproportionately large waste production result in severe and cumulative negative environmental effects. Integrated study of urban areas requires a system-of-systems analytical framework that includes modeling with social and biophysical data. We describe preliminary work toward an integrated urban food-energy-water systems (FEWS) analysis using co-simulation for assessment of current and future conditions, with an emphasis on local (urban and urban-adjacent) food production. We create a framework to enable simultaneous analyses of climate dynamics, changes in land cover, built forms, energy use, and environmental outcomes associated with a set of drivers of system change related to policy, crop management, technology, social interaction, and market forces affecting food production. The ultimate goal of our research program is to enhance understanding of the urban FEWS nexus so as to improve system function and management, increase resilience, and enhance sustainability. Our approach involves data-driven co-simulation to enable coupling of disparate food, energy and water simulation models across a range of spatial and temporal scales. When complete, these models will quantify energy use and water quality outcomes for current systems, and determine if undesirable environmental effects are decreased and local food supply is increased with different configurations of socioeconomic and biophysical factors in urban and urban-adjacent areas. The effort emphasizes use of open-source simulation models and expert knowledge to guide modeling for individual and combined systems in the urban FEWS nexus.

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