Award Abstract # 1855902
INFEWS / T1: Social and biophysical models to integrate local food systems, climate dynamics, built forms, and environmental impacts in the urban FEWS nexus

NSF Org: EAR
Division Of Earth Sciences
Recipient: IOWA STATE UNIVERSITY OF SCIENCE AND TECHNOLOGY
Initial Amendment Date: July 12, 2019
Latest Amendment Date: September 22, 2023
Award Number: 1855902
Award Instrument: Continuing Grant
Program Manager: Laura Lautz
llautz@nsf.gov
 (703)292-7775
EAR
 Division Of Earth Sciences
GEO
 Directorate for Geosciences
Start Date: July 15, 2019
End Date: December 31, 2024 (Estimated)
Total Intended Award Amount: $2,500,000.00
Total Awarded Amount to Date: $2,500,000.00
Funds Obligated to Date: FY 2019 = $1,386,810.00
FY 2020 = $1,113,190.00
History of Investigator:
  • Janette Thompson (Principal Investigator)
    jrrt@iastate.edu
  • Philip Gassman (Co-Principal Investigator)
  • Baskar Ganapathysubramanian (Co-Principal Investigator)
  • Ulrike Passe (Co-Principal Investigator)
  • Nicholas Terpstra-Schwab (Co-Principal Investigator)
  • Matthew Liebman (Former Co-Principal Investigator)
  • Yuyu Zhou (Former Co-Principal Investigator)
Recipient Sponsored Research Office: Iowa State University
1350 BEARDSHEAR HALL
AMES
IA  US  50011-2103
(515)294-5225
Sponsor Congressional District: 04
Primary Place of Performance: Iowa State University
1138 Pearson
Ames
IA  US  50011-2105
Primary Place of Performance
Congressional District:
04
Unique Entity Identifier (UEI): DQDBM7FGJPC5
Parent UEI: DQDBM7FGJPC5
NSF Program(s): Track 1 INFEWS,
Track 1 INFEWS,
EPSCoR Co-Funding
Primary Program Source: 01002021DB NSF RESEARCH & RELATED ACTIVIT
01001920DB NSF RESEARCH & RELATED ACTIVIT
Program Reference Code(s): 004Z, 9150
Program Element Code(s): 020Y00, 020y00, 915000
Award Agency Code: 4900
Fund Agency Code: 4900
Assistance Listing Number(s): 47.050

ABSTRACT

The majority of people in the world live in urban areas with high population densities, relying heavily on external sources of food, energy, and water, and producing disproportionately large amounts of waste. These phenomena, characteristic of many urban areas, result in serious and cumulative negative effects, such as increased energy consumption, greenhouse gas emissions and surface water pollution. The team will use simulation models and expert knowledge to guide assessment of current conditions for individual and combined systems in the urban food-energy-water (F-E-W) nexus, and to propose system improvements to increase local food production and simultaneously decrease environmental impacts. Investigators on this project will derive potential solutions by integrating social and biophysical models in a co-simulation approach to investigate these problems. The team will analyze current conditions and make future predictions focusing on local food production in urban and near-urban areas. The framework will include climate dynamics, land cover/land use changes, built forms, energy use, and environmental outcomes, with consideration of specific social, policy, crop management, technology, and market force scenarios. Project investigators will quantify environmental effects (energy use and water quality outcomes) for current food production systems. The team will then explore environmental effects and changes in local food supply under scenarios designed using data from producers and consumers in urban and near-urban areas. The Des Moines-West Des Moines Metropolitan Statistical Area will serve as a study area representative of cities in rain-fed agricultural regions. The team will collaborate with local stakeholders who are interested in improving local food systems as part of their sustainability strategies.

The team will develop an innovative approach to enable integration of social and biophysical models for urban and urban-adjacent food-energy-water (F-E-W) systems. The hypotheses guiding this research are: 1) data-driven co-simulation strategies will enable coupling of disparate F-E-W system simulation models across spatial and temporal scales; 2) the environmental footprint (energy use and water quality outcomes) for urban systems can be significantly reduced and food supply can be substantially increased through enhanced human food production in urban and urban-adjacent areas; and 3) the potential effects of changes (social, economic, and environmental) in urban areas and their adjacent landscapes will be synergistic. The team will create an empirical agent-based model that describes current actions and predicts the impacts of future decision-making by urban agricultural producers and consumers. This project will advance understanding of and enable projections to explore different scenarios for local food production to increase city resiliency and sustainability. The team will link parameterizations of single F-E-W system models that allow characterization of current and future conditions in individual systems as well as for the urban food-energy-water system-of-systems under predicted climate variability. The team will use co-simulations to explore the influence of individual drivers of system changes and allow analyses of critical system feedbacks, thresholds, and resiliency. This project will evaluate five specific drivers (related to policy, crop management, technology, social interactions and market forces) that influence human decisions leading to F-E-W systems changes. Local meteorological data for current conditions and predicted future conditions will drive modeling for building energy use, crop growth, and water dynamics. Changes in model outputs related to heat discharge from buildings and surfaces will be integrated as feedbacks for modeling future conditions and impacts on crop growth and urban water management. These analyses will provide critical new knowledge about how impacts of urban F-E-W systems can be reduced and local food supplies can be increased. The open-source coupling framework created in this project will be made available to ensure the broader research community can use it to analyze other F-E-W systems. This research will create scalable and transferable models that will support efforts to improve local food production, reduce energy use, and protect surface water quality in urban and urban-adjacent landscapes. This project is jointly funded by INFEWS Directorates (ENG, GEO and SBE and others) and the Established Program to Stimulate Competitive Research (EPSCoR); and managed by the GEOSCIENCES Directorate.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH

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(Showing: 1 - 10 of 20)
Hashemi, F and Najafian, P and Salahi, N and Ghiasi, S and Passe, U "The impact of the urban heat island and future climate on urban building energy use in a midwestern US neighborhood" Energies , 2025 Citation Details
Ghiasi, Sedigheh and Passe, Ulrike and Zhou, Yuyu and Thompson, Janette "A sensitivity analysis to investigate urban heat island impact on building energy consumption" Building Simulation Conference Proceedings , v.17 , 2021 https://doi.org/10.26868/25222708.2021.30873 Citation Details
Fagbule, O and Patel, R and Passe, U and Thompson, J "Utilizing a novel mobile diagnostics lab to validate the impact of vegetative wall coverings in building cooling load reduction" Journal of Physics: Conference Series , v.2069 , 2021 https://doi.org/10.1088/1742-6596/2069/1/012126 Citation Details
Dorneich, Michael C. and Krejci, Caroline C. and Schwab, Nicholas and Stone, Tiffanie F. and Huckins, Erin and Thompson, Janette R. and Passe, Ulrike "Producer and consumer perspectives on supporting and diversifying local food systems in central Iowa" Agriculture and Human Values , v.41 , 2023 https://doi.org/10.1007/s10460-023-10504-9 Citation Details
Chen, W and Zhou, Y and Passe, U and Zhang, T and Wang, C and Asrar, G and Li, H "Improving estimation of diurnal land surface temperatures by integrating weather modeling with satellite observations" Remote sensing of environment , v.315 , 2024 Citation Details
Brighenti, Tássia Mattos and Gassman, Philip W. and Schilling, Keith E. and Srinivasan, Raghavan and Liebman, Matt and Thompson, Jan R. "Determination of accurate baseline representation for three Central Iowa watersheds within a HAWQS-based SWAT analyses" Science of The Total Environment , v.839 , 2022 https://doi.org/10.1016/j.scitotenv.2022.156302 Citation Details
Brighenti, Tássia Mattos and Gassman, Philip W. and Gutowski, William J. and Thompson, Janette R. "Assessing the Influence of a Bias Correction Method on Future Climate Scenarios Using SWAT as an Impact Model Indicator" Water , v.15 , 2023 https://doi.org/10.3390/w15040750 Citation Details
Brighenti, T. and Gassman, P. and Gutowski, W. and Thompson, J. "Evaluation of bias correction methods for current and future RCM projections in hydrological regional applications" European Union General Assembly 2022 Abstracts , 2022 https://doi.org/10.5194/egusphere-egu22-10600 Citation Details
Xu, F and Xu, S and Passe, U and Ganapathysubramanian, B "Computational study of natural ventilation in a sustainable building complex geometry" Sustainable energy technologies and assessments , v.45 , 2021 https://doi.org/https://doi.org/10.1016/j.seta.2021.101153 Citation Details
Thompson, Jan and Ganapathysubramanian, Baskar and Chen, Wei and Dorneich, Michael and Gassman, Philip and Krejci, Caroline and Liebman, Matthew and Nair, Ajay and Passe, Ulrike and Schwab, Nicholas and Rosentrater, Kurt and Stone, Tiffanie and Wang, Yimi "Iowa Urban FEWS: Integrating Social and Biophysical Models for Exploration of Urban Food, Energy, and Water Systems" Frontiers in Big Data , v.4 , 2021 https://doi.org/10.3389/fdata.2021.662186 Citation Details
Stone, Tiffanie F and Thompson, Janette R and Zimmerman, Emily and Brighenti, Tassia M and Liebman, Matt "What would it look like? Visualizing a future US Corn Belt landscape with more table food production" Renewable Agriculture and Food Systems , v.39 , 2024 https://doi.org/10.1017/S1742170524000024 Citation Details
(Showing: 1 - 10 of 20)

PROJECT OUTCOMES REPORT

Disclaimer

This Project Outcomes Report for the General Public is displayed verbatim as submitted by the Principal Investigator (PI) for this award. Any opinions, findings, and conclusions or recommendations expressed in this Report are those of the PI and do not necessarily reflect the views of the National Science Foundation; NSF has not approved or endorsed its content.

Close to 80% of people in the U.S. live and work in urban areas. Food systems serving these areas cause large impacts on the environment due to high population densities, heavy reliance on external food sources, and failure to recycle nutrients. Approaches to analyze these systems are challenging because of disconnects among processes used for production, distribution, consumption and cycling of food, energy and water needed to support people living in urban settings.

The overall goal of this project was to develop a framework for analysis of urban food, energy, and water as integrated systems for the Des Moines, Iowa metropolitan region and the city itself (representative of mid-sized cities in rainfed agricultural landscapes). Because experiments using large-scale manipulation of the landscape are not feasible, this was explored using models to simulate effects of changes in land use, farming practices and consumer behavior on the environment (water quality, global warming potential). Investigators developed a set of what ifs? to test policies and decisions leading to increases in local table food production to supply 50% of the local population’s diet. Follow-on effects of energy and water use and environmental impacts for the metropolitan region and the city itself were quantified.

The land required to produce 50% of local diets in 2050 was determined for the metropolitan region (six counties surrounding the city) and the city itself.  For the region, approximately 18,000 hectares (2.5% of land zoned for agriculture) would meet this criterion, for the city approximately 1,450 hectares (about 6.4% of land within city boundaries) would meet it (for both this excludes pasture area for livestock). Information from focus groups and surveys of local producers were used to develop an agent-based model to predict farmer choices for land allocation to table food production (currently only about 1,500 ha for the region). If combined increases in interactions among farmers, technical assistance for them, improved policies (insurance for table food crops, zoning changes) and markets were considered, the model suggests that allocations for table food could reach 20,000 hectares.

A life-cycle assessment model used alone to quantify global warming potential (GWP), energy use and water use associated with increased local table food production for the region indicated decreases (15% less for both GWP and energy use, 25% less for water use) from 2020 to 2050 compared to current conditions (more than 90% of table food is currently produced outside the region). These effects were due to more intensive production practices used in locations producing the majority of food currently (2020) consumed, as well as transportation and food waste.  A hydrological model used alone indicated that land area changes greater than 30% would be necessary for measurable decreases in flow volumes, nitrogen, sediment and phosphorus loads in stream water draining the area. Combined models allowed better estimation of future crop yields influenced by changing climate and indicated that predicted change in local table food production from 2020 through 2040 would lead to decreases in GWP, energy and water use on a per capita basis, followed by increases in all three between 2040 and 2050 for scenarios that led to the greatest land use allocation changes.

At the city scale, additional models were used to assess effects of changes in the landscape on urban building energy use. An urban expansion map described future configurations of buildings based on population growth estimates and combined with a climate model to predict future surface temperatures. A framework was developed for building energy use models that included effects on heat transfer due to surrounding microclimate features (trees, urban agriculture production areas) and to allow scaling models from individual buildings to neighborhood and whole-city scales. These models are being integrated with life-cycle assessment and hydrological models to generate integrated analysis of food-energy-water dynamics for the city.

Stakeholder engagement in the study area included a formal 15-member stakeholder advisory board that met two to three times per year (to advise on research approaches, interpretation/presentation of results), local participants in focus groups and interviews (producers, consumers and distributors of local foods), collaboration with local food aggregators/distributors, and consultation with members of organizations involved in local food systems in Des Moines and throughout Iowa.  Stakeholders and collaborators have used research results from the project to support development of their strategic plans, address local food issues in their climate adaptation and community resilience plans, and have included project personnel in conference and local presentations in support of local foods and food systems.

The project also provided workforce development for undergraduate (15), graduate (14) and postdoctoral (2) scholars who engaged in this interdisciplinary research together and with project faculty. Students who have graduated have been successful in obtaining post-doctoral appointments at universities in Europe and Asia, with prestigious national laboratories in the US, and as practitioners and researchers in private industry.

 


Last Modified: 04/30/2025
Modified by: Janette R Thompson

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