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Factors influencing export of dissolved inorganic nitrogen by major rivers: A new, seasonal, spatially explicit, global model
McCrackin, M., J. Harrison, AND J. Compton. Factors influencing export of dissolved inorganic nitrogen by major rivers: A new, seasonal, spatially explicit, global model. Global Biogeochemical Cycles. American Geophysical Union, Washington, DC, 28(3):269-285, (2014).
Understanding seasonal patterns of sources and delivery of dissolved inorganic nitrogen (DIN) from rivers to coastal areas is critical to efforts to predict and mitigate the impacts of coastal eutrophication on communities and ecosystems. Algal blooms and hypoxic areas are often seasonal phenomena, and thus information on the seasonal patterns of nitrogen loading may be more relevant to communities and regions dealing with nutrient pollution issues. Most current large-scale models predict nutrient loading on an annual basis, thus this work represents the first large-scale attempt to predict the seasonal inputs of nitrogen to the landscape and exports of dissolved inorganic nitrogen to the coastal zone. The major uncertainties associated with predicting seasonal inputs lie within the N removal processes along the land to water flowpaths, thus better estimation of the location and magnitude of the ecosystem service of N removal is needed. Ultimately this work, conducted within EPA's Sustainable and Healthy Communities Research Program, will allow managers to identify key time periods and processes of importance for mitigating coastal zone impacts.
Substantial effort has focused on understanding spatial variation in dissolved inorganic nitrogen (DIN) export to the coastal zone and specific basins have been studied in depth. Much less is known, however, about seasonal patterns and controls of coastal DIN delivery across large spatial scales. Understanding sub-annual patterns of sources and delivery DIN export from rivers to coastal areas is critical to efforts to predict and mitigate impacts of coastal eutrophication, such as algal blooms and hypoxic areas, which are often seasonal phenomena. Here we describe, test, and apply NEWS2-DIN-S, the first global model capable of predicting seasonal DIN export to coastal regions for over 6,000 rivers for the contemporary period (2000). NEWS2-DIN-S used spatially explicit, seasonal N-inputs and was calibrated with measured DIN yield (kg N km-2 y-1) for 78 global rivers. Of the catchment characteristics considered, DIN export was positively related to runoff and negatively related to temperature across seasons (r2 = 0.32 to 0.49, p<0.0001), due likely to flushing effects and increased retention by plants and soils, respectively. NEWS2-DIN-S incorporated these insights and performed well in predicting DIN yield (Nash-Sutcliffe Efficiency = 0.54-0.69, depending on season). Model runs showed that catchments were effective in retaining DIN and average export rates were generally lower during the growing season (3-5%) compared to other seasons (6-10%) for major latitude bands. Model output was relatively insensitive to changes in the magnitude of N inputs, suggesting that further refinement of seasonal N budgets will not substantially improve predictive performance. Rather, better representation of land-to-river N transfers could improve the predictive capacity of future models because of the importance of landscape N-attenuation.