Modeling cross-scale, cross-sector feedbacks to inform decision-making in food-energy-water systems


Feedbacks among water availability, irrigated agriculture, and electric power generation pose significant challenges for institutions and individuals who must make decisions subject to uncertain—and potentially cascading—risks from resource disruption.

For example, in California, snowpack fuels hydropower production and provides water for irrigation to the Central Valley, the most highly agriculturally productive area in the U.S., making this region one that is highly vulnerable to hydrologic drought. During drought, irrigators pump groundwater to recoup lost surface water, increasing electricity demand; at the same time, reduced hydropower production is replaced by more expensive natural gas generation, increasing electricity prices precisely when farmers’ pumping requirements are highest.

System dynamics among water, irrigated agriculture and electric power sectors in California.

It remains a fundamental challenge to understand how these feedbacks and their associated financial risks impact stakeholder decisions, particularly those involving irreversible capital investment (e.g., in new fruit and nut orchards, irrigation wells, and power plants)–  individual decisions that carry significant implications for regional water and energy sustainability.

As the recipient of two NSF Innovations at the Nexus of Food, Energy, and Water Systems (INFEWS) awards and a NSF Dynamics of Coupled Natural Human Systems (CNH2) award, the Kern Group is at the forefront of national efforts to better understand complex, interconnected FEW systems. These projects involve collaboration with researchers and public/private stakeholders across the U.S. We are also a co-PI in a DOE Office of Science project led by Pacific Northwest National Laboratory, focused on Integrated, Multi-scale, Multi-sector Modeling (IM3).

As part of these projects, one of our main research tasks is the development of computational models that accurately simulate the behavior of multi-zone bulk electric power systems under a wide range of different hydrologic, climate, and market conditions. These models will significantly improve our ability to study the current vulnerabilities of interconnected food-energy-water systems, and how these risks might change in the future.

Relevant Papers:

Kern, J.D., Su, Y., Hill, J. (2020). “A retrospective study of the 2012-2016 California drought and its impacts on the power sector.” Environmental Research Letters. 15 094008

Su, Y., Kern, J., Denaro, S., Hill, J., Reed, P., Sun, Y., Cohen, J., Characklis, G. (2020). “An open source model for quantifying risks in bulk electric power systems from spatially and temporally correlated hydrometeorological processes” Environmental Modelling and Software. Vol. 126.

Chowdhury, AFM K., Kern, J., Dang, T., Galelli, S. (2020) “PowNet: a power systems analysis model for large-scale water-energy nexus studies”. Journal of Open Research Software. September 2019.

Wang, X., Virguez, E., Kern, J., Chen, L., Patino-Echeverri, D., Wang, H. (2019) “Integrating wind, photovoltaic, and large hydropower during the reservoir refilling period.” Energy Conversion and Management. Volume 198, October 2019.