E. Sinha and A.M. Michalak
Excessive nitrogen runoff into waterways can lead to the formation of harmful algal blooms as well as low-oxygen dead zones and other water quality problems. In this work we developed a modeling tool that provides the first comprehensive estimates of the amount of nitrogen entering U.S. waterways each year over a 21-year period. The spatial patterns of nitrogen entering waterways mimics the spatial patterns of nitrogen application by humans; however, the large year-to-year variability is instead due primarily to changes in precipitation, and the spatial occurrence of precipitation extremes. These results imply that reducing nitrogen inputs may not result in anticipated reduction in nitrogen runoff, and points to a fundamental challenge in managing nutrient loading.
Excessive nitrogen loading to waterways leads to increased eutrophication and associated water quality impacts. An understanding of the regional and interannual variability in nitrogen loading and associated drivers is necessary for the design of effective management strategies. Here we develop a parsimonious empirical model based on net anthropogenic nitrogen input, precipitation, and land use that explains 68% of the observed variability in annual total nitrogen flux (QTN) (76% of ln(QTN)) across 242 catchment years. We use this model to present the first spatially and temporally resolved estimates of QTN for all eight-digit hydrologic unit (HUC8) watersheds within the continental United States (CONUS), focusing on the period 1987–2007. Results reveal high spatial and temporal variability in loading, with spatial variability primarily driven by nitrogen inputs, but with interannual variability and the occurrence of extremes dominated by precipitation across over three-quarters of the CONUS. High interannual variability and its correlation with precipitation persist at large aggregated scales. These findings point to a fundamental challenge in managing regions with high nutrient loading, because these regions also exhibit the strongest interannual variability and because the impact of changes in management practices will be modulated by meteorological variability and climatic trends.
Sinha, E., A.M. Michalak (2016) "Precipitation Dominates Interannual Variability of Riverine Nitrogen Loading across the Continental United States", Environmental Science & Technology, 50 (23), 12874-12884, 10.1021/acs.est.6b04455.