"MODELING CLIMATE CHANGE IMPACTS ON GROUNDWATER DEMAND IN EAST-CENTRAL " by Ryan Krakowiak

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Graduation Term

Spring 2025

Degree Name

Master of Science (MS)

Department

Department of Geography-Geology: Hydrogeology

Committee Chair

Wondwosen Seyoum

Committee Member

John Kostelnick

Committee Member

Jonathan Thayn

Abstract

Climate change threatens surface water reservoirs which increases reliance on groundwater reservoirs to sustain water demand in public supply and irrigation water demand sectors. East-central Illinois depends upon the Mahomet Aquifer and related shallow aquifer systems in the Mahomet Valley for their public supply and irrigation water use. A variety of machine learning regression models were trained and validated in two demand sectors used to make predictions of groundwater demand at the HUC12 watershed level under three different globally recognized and standardized socioeconomic-climate pathways (SSP245, SSP370, and SSP585). For both demand sectors, the random forest model explained the largest amount of variance with the least amount of error in the test dataset (public supply: R2 = 0.93, RMSE = 2.45; irrigation: R2 = 0.91, RMSE = 9.46) with different input variables for each demand sector. Average public supply groundwater demand projections show the greatest change in urban population dominated watersheds, with growth equal to 14% and 48% under SSP245 and SSP585, respectively, in the late century compared to the historical averages, while demand decreased by 35% under SSP370 scenario. The change in the average irrigation demand was greater than public supply demand, increasing by over 100% across all SSP-RCP scenarios. Climatic factors in July were most impactful on model predictions, suggesting heightened irrigation demand during dry periods. This modeling framework is a powerful tool in demand forecasting that facilitate groundwater management and sustainability policy by stakeholders that ensure the safeguard of east-central Illinois groundwater resources at a regional scale.

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