Estimating global river solids, nitrogen (N), and phosphorus (P), in both quantity and composition, is necessary for understanding the development and persistence of many harmful algal blooms and hypoxic events. This requires a comprehensive freshwater model that can resolve intertwined algae, solid, and nutrient dynamics, yet previous global watershed models do not mechanistically resolve instream biogeochemical processes. Here we develop a global, spatially explicit, process-based, Freshwater Algae, Nutrient, and Solid cycling and Yields (FANSY) model and incorporate it within the Land Model LM3. The resulting model, LM3-FANSY, explicitly resolves interactions between algae, N, P, and solid dynamics in rivers and lakes at 1 degree spatial and 30 minute temporal resolution. Simulated solids, N, and P in multiple forms (particulate/dissolved, organic/inorganic) agree well with measurement-based yield (kg km−2 yr−1), load (kt yr−1), and concentration (mg l−1) estimates across world major rivers. Furthermore, simulated global river loads of suspended solid, N, and P in different forms to the coastal ocean are consistent with published ranges. River N loads are estimated to be approximately equally distributed among forms with particulate organic, dissolved organic, and dissolved inorganic N accounting for 37 %, 34 %, and 30 % respectively. For river P load estimates, particulate P, which includes both organic and sorbed inorganic forms, is the most abundant form (58 %), followed by dissolved inorganic and organic P (32 % and 10 %). Analyses of model results and sensitivity to components, parameters, and inputs suggest that the fidelity of simulated river nutrient loads and N : P ratios with observation-based estimates could be improved markedly with better global estimates of nutrient inputs to rivers, including soil and litter runoff, wastewater, and weathering. Sensitivity analyses further demonstrate the role of algal dynamics in controlling the ratios of inorganic and organic nutrient forms. LM3-FANSY can serve as a baseline for linking global terrestrial and ocean biogeochemistry in next generation Earth System Models aimed at understanding the effects of terrestrial perturbations on coastal eutrophication under unprecedented socioeconomic and climate changes, where novel conditions challenge empirical approaches. Continued model enhancements will focus on the inclusion of terrestrial P dynamics, freshwater carbon and alkalinity dynamics, and anthropogenic hydraulic controls.
Enhanced riverine delivery of terrestrial nitrogen (N) has polluted many freshwater and coastal ecosystems, degrading drinking water and marine resources. An emerging view suggests a contribution of land N memory effects—impacts of antecedent dry conditions on land N accumulation that disproportionately increase subsequent river N loads. To date, however, such effects have only been explored for several relatively small rivers covering a few episodes. Here we introduce an index for quantifying land N memory effects and assess their prevalence using regional observations and global terrestrial-freshwater ecosystem model outputs. Model analyses imply that land N memory effects are globally prevalent but vary widely in strength. Strong effects reflect large soil dissolved inorganic N (DIN) surpluses by the end of dry years. During the subsequent wetter years, the surpluses are augmented by soil net mineralization pulses, which outpace plant uptake and soil denitrification, resulting in disproportionately increased soil leaching and eventual river loads. These mechanisms are most prominent in areas with high hydroclimate variability, warm climates, and ecosystem disturbances. In 48 of the 118 basins analyzed, strong memory effects produce 43% (21%–88%) higher DIN loads following drought years than following average years. Such a marked influence supports close consideration of prevalent land N memory effects in water-pollution management efforts.
Over the past century, human activities have resulted in substantial global changes that threaten the stability and functionality of coastal habitats. One of these impacts was through nutrient pollution of river runoffs, which have triggered harmful algal blooms and caused low-oxygen conditions in many coastal regions. However, it is challenging for models to simulate coastal impacts of increasing river nutrient loads, especially on a global scale and over a long period of time. Here we take advantage of some recent modeling advances to provide a global perspective on coastal ecosystem responses to increasing river nitrogen loads over the half-century between 1961 and 2010. Overall, we show that the global coastal ocean accumulated more nitrogen over time as river nitrogen loads increased. This caused the primary production of the global coastal system (i.e., the conversion of inorganic to organic materials through photosynthesis) to increase as well. However, we found that the sensitivity of each coastal ecosystem to comparable changes in nitrogen loads varied considerably. This variability was to a large extent related to two factors: the rate of exchange between coastal waters and the adjacent ocean waters, and whether nutrients are limited for phytoplankton to conduct photosynthesis in that system.
Nitrogen (N) pollution is shaped by multiple processes, the combined effects of which remain uncertain, particularly in the tropics. We use a global land biosphere model to analyze historical terrestrial-freshwater N budgets, considering the effects of anthropogenic N inputs, atmospheric CO2, land use, and climate. We estimate that globally, land currently sequesters 11 (10–13)% of annual N inputs. Some river basins, however, sequester >50% of their N inputs, buffering coastal waters against eutrophication and society against greenhouse gas-induced warming. Other basins, releasing >25% more than they receive, are mostly located in the tropics, where recent deforestation, agricultural intensification, and/or exports of land N storage can create large N pollution sources. The tropics produce 56 ± 6% of global land N pollution despite covering only 34% of global land area and receiving far lower amounts of fertilizers than the extratropics. Tropical land use should thus be thoroughly considered in managing global N pollution.
Lee, Minjin, C Jung, Elena Shevliakova, and Sergey Malyshev, et al., October 2018: Control of Nitrogen Exports From River Basins to the Coastal Ocean: Evaluation of Basin Management Strategies for Reducing Coastal Hypoxia. Journal of Geophysical Research: Biogeosciences, 123(10), DOI:10.1029/2018JG004436. Abstract
The spread of coastal hypoxia is a pressing global problem, largely caused by substantial nitrogen (N) exports from river basins to the coastal ocean. Most previous process‐based modeling studies for investigating basin management strategies to reduce river N exports focused on the impacts of different farming practices or land use, used watershed models that simplified many mechanisms that critically affect the state of N storage in land, were limited mainly to fairly small basins, and did not span multiple climate regimes. Here we use a process‐based land‐river model to simulate historical (1999–2010) river flows and nitrate‐N exports throughout the entire drainage network of South Korea (100,210 km2), which encompasses varying climate, land use, and hydrogeological characteristics. Based on projections by using multiple scenarios of N input reductions and climates, we explore the impacts of various ecosystem factors (i.e., N storage in basins, climate and its variability, anthropogenic N inputs, and basin location) on river nitrate‐N exports. Our findings have fundamental implications for reducing coastal hypoxia: (1) a small reduction of N inputs in basins, including intensively utilized human land use, can have a greater improvement on water quality; (2) heightening climate variability may not increase long‐term mean river N exports yet can significantly mask N input reduction effects by producing N export extremes associated with recurring coastal hypoxia; and (3) N exports to the coastal ocean can be most efficiently reduced by decreasing N inputs in subbasins, which are receiving high anthropogenic N inputs and are close to the coast.
Despite 30 years of basin-wide nutrient-reduction efforts, severe hypoxia continues to be observed in the Chesapeake Bay. Here we demonstrate the critical influence of climate variability, interacting with accumulated nitrogen (N) over multidecades, on Susquehanna River dissolved nitrogen (DN) loads, known precursors of the hypoxia in the Bay. We used the process model LM3-TAN (Terrestrial and Aquatic Nitrogen), which is capable of capturing both seasonal and decadal-to-century changes in vegetation-soil-river N storage, and produced nine scenarios of DN-load distributions under different short-term scenarios of climate variability and extremes. We illustrate that after 1 to 3 yearlong dry spells, the likelihood of exceeding a threshold DN load (56 kt yr−1) increases by 40 to 65% due to flushing of N accumulated throughout the dry spells and altered microbial processes. Our analyses suggest that possible future increases in climate variability/extremes—specifically, high precipitation occurring after multiyear dry spells—could likely lead to high DN-load anomalies and hypoxia.
We developed a~process model LM3-TAN to assess the combined effects of direct human influences and climate change on Terrestrial and Aquatic Nitrogen (TAN) cycling. The model was developed by expanding NOAA's Geophysical Fluid Dynamics Laboratory land model LM3V-N of coupled terrestrial carbon and nitrogen (C-N) cycling and including new N cycling processes and inputs such as a~soil denitrification, point N sources to streams (i.e. sewage), and stream transport and microbial processes. Because the model integrates ecological, hydrological, and biogeochemical processes, it captures key controls of transport and fate of N in the vegetation-soil-river system in a comprehensive and consistent framework which is responsive to climatic variations and land use changes. We applied the model at 1/8° resolution for a study of the Susquehanna River basin. We simulated with LM3-TAN stream dissolved organic-N, ammonium-N, and nitrate-N loads throughout the river network, and we evaluated the modeled loads for 1986–2005 using data from 15 monitoring stations as well as a reported budget for the entire basin. By accounting for inter-annual hydrologic variability, the model was able to capture inter-annual variations of stream N loadings. While the model was calibrated with the stream N loads only at the last downstream station Marietta (40.02° N, 76.32° W), it captured the N loads well at multiple locations within the basin with different climate regimes, land use types, and associated N sources and transformations in the sub-basins. Furthermore, the calculated and previously reported N budgets agreed well at the level of the whole Susquehanna watershed. Here we illustrate how point and non-point N sources contribute to the various ecosystems are stored, lost, and exported via the river. Local analysis for 6 sub-basins showed combined effects of land use and climate on the soil denitrification rates, with the highest rates in the Lower Susquehanna sub-basin (extensive agriculture; Atlantic coastal climate) and the lowest rates in the West Branch Susquehanna sub-basin (mostly forest; Great Lakes and Midwest climate). In the re-growing secondary forests, most of the N from non-point sources was stored in the vegetation and soil, but in the agricultural lands most N inputs were removed by soil denitrification indicating that anthropogenic N applications could drive substantial increase of N2O emission, an intermediate of the denitrification process.
