Expanding Croplands Threaten Future Access to Clean Water
Current land management practices and land use trends threaten the health of the Upper Mississippi River and, subsequently, drinking water quality. Recent research shows high rates of cropland expansion into the headwaters region, largely at the expense of forests, grasslands, and wetlands (Lark et al., 2015).
Over one million Minnesotans obtain drinking water from the Mississippi River, specifically in the Twin Cities Metropolitan Area and upstream in St. Cloud (Minnesota Department of Natural Resources, 2010). Millions more throughout the state receive drinking water from aquifers in the basin. Water utilities in the region have a financial interest in maintaining or improving the basin’s surface and groundwater quality to manage treatment costs. |
Our Approach
Targeted, high-impact conservation practices upstream can achieve measurable water quality improvements and help prevent future water quality deterioration.
This project will explore the numerous factors impacting that economic case and determine whether various water utilities in the basin can achieve a positive ROI through investment in the fund. The project’s findings will serve as a framework by which other utilities may evaluate the potential for green infrastructure investments to meet their specific water quality challenges.
Forecasting Agricultural ExpansionAgricultural expansion and land use change is expected to continue in the Upper Mississippi River Basin. Our project will incorporate multiple land use change scenarios to best inform future decision makers.
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Linking Land Use Change to Water Quality ImpactsThe direct impacts of land use change on nutrient pollution in surface waters is a complicated issue. Our analysis will take multiple factors into account in order to develop a comprehensive solution.
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Quantifying Increased Water Treatment CostsIncreased loadings of nutrients in surface waters will increase treatment costs for municipal drinking water facilities. Our ROI analysis will use data from small, medium, and large facilities to accurately forecast returns for utilities across multiple classes.
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