In-stream nitrate responses integrate human and climate systems in an intensively managed landscape

Thursday, 18 December 2014: 10:35 AM
Adam S Ward1,2, Caroline A. Davis2, Amy J Burgin3, Terry Loecke3, Diego A Riveros-Iregui4, Doug J Schnoebelen2, Craig L Just2, Steven A Thomas3, Larry J Weber2, Martin A St. Clair5, Scott Spak2, Kajsa E Dalrymple2, Yuwei Li2 and Kara Prior2, (1)Indiana University Bloomington, School of Public and Environmental Affairs, Bloomington, IN, United States, (2)University of Iowa, Iowa City, IA, United States, (3)University of Nebraska Lincoln, Lincoln, NE, United States, (4)University of North Carolina at Chapel Hill, Chapel Hill, NC, United States, (5)Coe College, Cedar Rapids, IA, United States
Nitrogen (N) fertilization is a cornerstone of modern agriculture, but the practice also leads to eutrophication, hypoxia, and harmful algal blooms in both inland and coastal waters. Several studies identify Iowa, Illinois and Indiana as major source areas of N discharged by the Mississippi River to the Gulf of Mexico where large-scale hypoxia develops annually. Continental-scale management of nitrogen requires a comprehensive understanding of watershed-specific hydrologic dynamics and their consequences for nitrate flushing from agricultural landscapes. Spatiotemporal variation in nitrate fluxes is inherently complex due to the broad range of physicochemical and hydraulic properties that influence N movement through soils, groundwater, and rivers. In-stream N fluxes respond to both short- and long-term climactic forcing interacting with the cumulative human modification to both physical and biogeochemical systems in agricultural catchments.

Here, we synthesize results from three individual studies in the Iowa River watershed. First, we demonstrate significant inter- and intra-annual variability in stream responses to rainfall events as a function of antecedent moisture conditions in three nested catchments (first through third-order). This study highlights the use of in-situ, high temporal resolution sensor networks as an emerging tool. Next, we leverage a catchment-wide synoptic study repeated in 2013 to demonstrate the landscape-scale impact of climate dynamics interacting with management decisions on the landscape. This study highlights the role of changes in extreme event frequency on water quality in agricultural landscapes. Finally, we extend results onto the landscape, using a numerical model to quantify heterogeneity of key controlling variables within the landscape (e.g., soil texture) and N retention or mobilization. We compare variability in key controls with variability driven by climate over a 60-yr period of record.