Built-up urban areas use more food, water, and energy than they can produce themselves, making them reliant on external sources. The “Iowa UrbanFEWS” (Urban Food-Energy-Water Systems) project team is working to find new ways to help make cities more self-reliant.

With funding from the National Science Foundation, the project team is developing a framework with which to analyze food, energy and water systems for the greater Des Moines metro area, including the city and surrounding counties. A substantial amount of the team's work involves developing and analyzing “what if?” scenarios that could suggest how urban areas and the surrounding countryside can become more sustainable. The project team includes scientists from Iowa State University, the University of Northern Iowa, and University of Texas at Arlington. The team also works with community and local organization leaders who serve as an advisory board for the project.

Conducting experiments and research projects by making large-scale changes in the real world is not feasible. Consequently, investigating the impacts of changing land use, farming practices, consumer behavior, and diet in Des Moines and surrounding counties is best addressed by using models. Models can evaluate water use, energy use, temperature conditions, economic activity, food production and security, soil erosion, water quality, and other components of sustainability. The Iowa Urban FEWS project uses seven accessible platforms/simulation models guided by expert knowledge to assess current conditions and simulate future conditions as influenced by five drivers of change (policy, crop management, technology, social interaction, and market forces) and anticipated changes in climate.

Results of the project are intended to inform decisions by policy makers, farmers and land managers, and urban and rural citizens about food production and food availability, energy use, and environmental quality. We believe the results will apply to a large number of cities in rain-fed climates similar to Des Moines. We also believe that the project will provide an excellent opportunity to understand how urban and rural residents can work together or mutual benefit.

Project Goals

The majority of 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. The proposed work will create a system-of-systems analytical framework, integrating social and biophysical models for an urban FEWS via an innovative co-simulation approach to describe current and predict future conditions, with an emphasis on local (urban and urban-adjacent) food production. This framework will enable simultaneous analyses of climate dynamics, changes in land cover, built forms, energy use, and environmental outcomes associated with a set of five potential drivers of system change related to policy, crop management, technology, social interaction, and market forces affecting local food production. The goal is to use data-driven co-simulation to enable coupling of disparate (spatial/temporal scale) FEW system simulation models to quantify the environmental footprint (energy use and water quality outcomes) for current systems, and to  determine if environmental effects are decreased and local food supply increased as influenced by drivers that influence food production in urban and urban-adjacent areas. The Des Moines-West Des Moines Metropolitan Statistical Area (MSA) serves as a test bed to represent cities embedded in a rain-fed agricultural area. The transdisciplinary team will use accessible simulation models and expert knowledge to guide modeling for individual and combined systems in the urban FEWS nexus.

Intellectual Merit

An innovative process/framework will enable the effective integration of social and biophysical models for urban and urban-adjacent FEW systems. The use of empirical data to create an urban-agriculture ABM that describes current/predicts future decision-making by producers and consumers is a novel contribution that will further understanding of urban agriculture and use of local food production to increase city resiliency and sustainability. The unique approach to linked parameterization of a comprehensive set of single-system models allows for characterization of current and future conditions in individual systems as well as the urban FEW system-of-systems under predicted climate change.  Use of adaptive sampling strategies and creation of a functional mock-up interface framework will enable efficient co-simulations exploring the influence of individual drivers of system changes and allow analyses of critical system feedbacks, thresholds, and resiliency. Another novel contribution of this project is the evaluation of the five drivers for modeling that influence human decisions leading to FEW systems changes. These analyses will provide critical new knowledge about how negative environmental impacts of urban FEW systems can be decreased and local food supplies can be increased. The open source coupling standard created in this project will be made available to ensure the broader research community can use it to further analyze other FEW systems of systems.

Broader Impact

The proposed research was developed in collaboration with local stakeholder participants, who have expressed strong interest in improving local food systems as part of a larger set of sustainability strategies. This research will create scalable and transferable models that will support efforts to simultaneously improve local food production, reduce energy use, and protect surface water quality in urban and urban-adjacent landscapes and that will be shared widely through a project website and direct dissemination via workshops and professional presentations. It will support ongoing efforts in many urban areas to promote local food production, secure health and livelihoods, and preserve environmental resources. Knowledge gained from this project will also be directly integrated into undergraduate and graduate education in architecture, psychology, urban ecology, urban planning, sustainable agriculture, data science, and engineering courses, contributing to the development of the next generation workforce.


This work is supported by the National Science Foundation, Award # 1855902. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.