New NSF grant on "Stochastic Modeling for Sustainable Management of Water Rights"
Mike Ludkovski and Igor Cialenco (Illinois Tech) awarded a new NSF Applied Mathematics collaborative grant on stochastic modeling of groundwater management. The project started 9/1/2024 and will continue for 3 years.
Sustainable and equitable management of groundwater is one of the key aspects of adaptation to climate change in drought-affected regions nationwide. The rapid depletion of aquifers is spurring the creation of new groundwater management institutions to ensure conservation of groundwater supplies across generations. This project will provide new mathematical tools for designing efficient and fair water markets, that are free of predatory or exploitative behavior and flexibly respond to stakeholder needs, helping to build a water resilient future. The developed numerical algorithms would facilitate better market regulations and policies, supporting legislative mandates and their economic viability. The dissemination activities will enhance the exchange of ideas and knowledge between mathematicians, data scientists, resource economists and hydrologists. This award will also provide opportunities for student involvement in the research.
This project will address dynamic water allocation and equilibrium for tradeable water rights by establishing the foundations for an innovative mathematical framework for water management through the lens of stochastic games and market equilibria. The project will develop a tractable top-down stochastic model of groundwater levels to study the price formation of the groundwater rights as a Nash equilibrium of a non-cooperative game between the economic agents. In tandem, the project will characterize the Pareto optimal water rights allocation and water banking strategy from the perspective of a central planner. Modeling and pricing of groundwater rights and their fair distribution will articulate the benefits and dangers of potential management policies and quantify the efficiency of regulations. The project will also develop scalable computational schemes for multi-period equilibria with multiple stakeholders.