Collaborative Research: Exploring the Influence of Agricultural Tile Drainage on Streamflow and Water Temperature in the Midwestern US using a Stakeholder-driven Approach

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The upper Midwest is one of the most agriculturally productive regions in the world. To achieve this productivity, agricultural tile drainage was widely installed across the region to rapidly remove excess soil water after major precipitation events. The presence of tile drainage results in highly manipulated hydrology due to the rapid transport of water from the agricultural field to a nearby river or stream. While the effect of tile drainage on streamflow and water quality has been studied in individual watersheds, this project will assess how tile drainage alters streamflow at large spatial scales to make broader conclusions and recommendations to stakeholders. In addition, the impacts of tile drainage on water temperature regimes are largely unknown. Changes in water temperature in streams are particularly important, as they influence biological activity, gas solubility, and water evaporation rates. Using a large-scale network of streamflow and water-temperature observations in conjunction with an array of geospatial information (e.g., tile drainage, land use, climate data), this work will examine the effects of tile drainage on streamflow and water temperature at the scale of the entire agricultural Upper Midwest using statistical models. Throughout the project, stakeholders will be interviewed pre- and post-statistical modeling to ensure that the project results in actionable outcomes. The work will also provide valuable research experiences for undergraduate and graduate students. Workshops will be conducted that provide hands-on experience of the methods and approaches to be used in this project. Results will be disseminated in manuscripts, conference presentations, news releases, and public data portals.This research will develop quantile regression models at the scale of the entire agricultural portion of the Mississippi River Basin and at local watershed levels to provide better insight into the mechanisms that drive seasonal variations of sub-daily and daily streamflows and water temperatures. The use of quantile regression models will allow for the full distribution of streamflows and water temperatures to be examined. The stakeholder engagement throughout the modeling process will shape model results and output displays to user groups’ interests, extending model salience and utility to other groups. The results will improve the understanding of how tile drainage has altered local and regional hydrology and water temperature, thereby providing additional insight into major Midwestern concerns such as water quality, flooding, and drought effects.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.