Institute of Water Research

Project Summary

Future climate projections for Michigan include higher temperatures, higher precipitation volume, and more intense precipitation events. The increased precipitation variability along with longer droughts leading into planting increases the uncertainty and risks associated with growing high value specialty crops. To offset those risks, producers are installing more high-capacity wells for irrigation, which can compete with groundwater discharge to nearby streams in many parts of the state. Additionally, greater storm intensity creates the potential for increased surface runoff, leading to greater soil and nutrient loss from agricultural fields and exacerbating the present-day challenge of nutrient-driven algal blooms in Lake Erie and Saginaw Bay. To help producers across Michigan implement the best practices for their specific operation in the context of more frequent climate extremes and increasing demand for groundwater, there is a need to quantify and predict how regenerative agriculture can enhance a farm’s soil and hydrology. The extent to which such practices can increase soil water holding capacity, improve soil nutrient cycling, recharge aquifers, reduce surface runoff, and retain soil and nutrients on the land will better prepare farms to withstand the climate extremes forecasted by current models. Through intensive field monitoring on a diverse sample of 10-20 Michigan farms (specialty crops and traditional row crops) and established modeling approaches, we will assess how improving soil health may increase crop resilience and improve water quality and quantity, including reducing nutrient loads, and increasing infiltration, particularly under projected climate scenarios. These results will enable producers to assess the costs of adapting their management strategies in the context of predicted short and long-term risks and benefits as weather patterns shift outside normal ranges. Additionally, we will include participating producers in developing, evaluating, and refining the crop models built for their respective farms to explore how such a collaborative approach may affect their trust in the model’s forecasted outcomes. Project findings will be shared with other producers through MSU Extension networks (workshops, field days, bulletins), with the broader scientific community through conference presentations and peer-reviewed publications, and through a web-based decision support tool