A Cornell-led research team has demonstrated that AI-driven modeling can significantly enhance the benefits of water infrastructure partnerships while reducing financial risks. The study, led by Professor Patrick Reed, focused on California’s Friant-Kern Canal and showed how AI algorithms can better balance the distribution of water supply benefits and financial risks among regional stakeholders.
The research, published in Nature Communications, revealed that while cooperative partnerships are often used to finance large-scale water projects, they can unfairly burden local partners. AI modeling, however, can help identify more equitable configurations, such as combining canal expansion with groundwater banking, to mitigate risks.
The findings have broader implications for water systems nationwide, especially as aging infrastructure faces new challenges from climate change and economic pressures. The research team hopes their freely available algorithm will guide more informed and equitable decision-making in water infrastructure projects across the U.S.
This work was supported by the National Science Foundation and the U.S. Department of Energy.
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