[1] An integrated modeling approach was used to connect socioeconomic factors and nutrient management to river export of nitrogen, phosphorus, silica and carbon based on an updated Global NEWS model. Past trends and four future scenarios were analyzed. Differences among the scenarios for nutrient management in agriculture were a key factor affecting the magnitude and direction of change of future DIN river export. In contrast, connectivity and level of sewage treatment and P detergent use were more important for differences in DIP river export. Global particulate nutrient export was calculated to decrease for all scenarios, in part due to increases in dams for hydropower. Small changes in dissolved silica and dissolved organics were calculated for all scenarios at the global scale. Population changes were an important underlying factor for river export of all nutrients in all scenarios. Substantial regional differences were calculated for all nutrient elements and forms. South Asia alone accounted for over half of the global increase in DIN and DIP river export between 1970 and 2000 and in the subsequent 30 years under the Global Orchestration scenario (globally connected with reactive approach to environmental problems); DIN river export decreased in the Adapting Mosaic (globally connected with proactive approach) scenario by 2030, although DIP continued to increase. Risks for coastal eutrophication will likely continue to increase in many world regions for the foreseeable future due to both increases in magnitude and changes in nutrient ratios in river export.Citation: Seitzinger, S. P., et al. (2010), Global river nutrient export: A scenario analysis of past and future trends, Global Biogeochem. Cycles, 24, GB0A08,

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An overview of the first spatially explicit, multielement (N, P, and C), multiform (dissolved inorganic: DIN, DIP; dissolved organic: DOC, DON, DOP; and particulate: POC, PN, PP) predictive model system of river nutrient export from watersheds (Global Nutrient Export from Watersheds (NEWS)) is presented. NEWS models estimate export from 5761 watersheds globally as a function of land use, nutrient inputs, hydrology, and other factors; regional and global scale patterns as of 1995 are presented here. Watershed sources and their relative magnitudes differ by element and form. For example, anthropogenic sources dominate the export of DIN and DIP at the global scale, although their anthropogenic sources differ significantly (diffuse and point, respectively). Natural sources dominate DON and DOP export globally, although diffuse anthropogenic sources dominate in several regions in Asia, Europe and N. America. “Hot spots” where yield (kg km−2 yr−1) is high for several elements and forms were identified, including parts of Indonesia, Japan, southern Asia, and Central America, due to anthropogenic N and P inputs in some regions and high water runoff in others. NEWS models provide a tool to examine past, current and future river export of nutrients, and how humans might impact element ratios and forms, and thereby affect estuaries and coastal seas.

[1] Here we describe, test, and apply a spatially explicit, global model for predicting dissolved inorganic nitrogen (DIN) export by rivers to coastal waters (NEWS-DIN). NEWS-DIN was developed as part of an internally consistent suite of global nutrient export models. Modeled and measured DIN export values agree well (calibration R 2 = 0.79), and NEWS-DIN is relatively free of bias. NEWS-DIN predicts: DIN yields ranging from 0.0004 to 5217 kg N km À2 yr À1 with the highest DIN yields occurring in Europe and South East Asia; global DIN export to coastal waters of 25 Tg N yr À1 , with 16 Tg N yr À1 from anthropogenic sources; biological N 2 fixation is the dominant source of exported DIN; and globally, and on every continent except Africa, N fertilizer is the largest anthropogenic source of DIN export to coastal waters.

Large-scale hydrological models describing the terrestrial water balance at continental and global scales are increasingly being used in earth system modeling and climate impact assessments. However, because of incomplete process understanding and limits of the forcing data, model simulations remain uncertain. To quantify this uncertainty a multimodel ensemble of nine large-scale hydrological models was compared to observed runoff from 426 small catchments in Europe. The ensemble was built within the framework of the European Union Water and Global Change (WATCH) project. The models were driven with the same atmospheric forcing data. Models were evaluated with respect to their ability to capture the interannual variability of spatially aggregated annual time series of five runoff percentiles-derived from daily time series-including annual low and high flows. Overall, the models capture the interannual variability of low, mean, and high flows well. However, errors in the mean and standard deviation, as well as differences in performance between the models, became increasingly pronounced for low runoff percentiles, reflecting the uncertainty associated with the representation of hydrological processes, such as the depletion of soil moisture stores. The large spread in model performance implies that any single model should be applied with caution as there is a great risk of biased conclusions. However, this large spread is contrasted by the good overall performance of the ensemble mean. It is concluded that the ensemble mean is a pragmatic and reliable estimator of spatially aggregated time series of annual low, mean, and high flows across Europe.

[1] The aim of this study is to produce future scenarios on the river inputs of water and nutrients (nitrate and phosphate) into the Mediterranean and Black Sea. They are based on the four contrasting scenarios that were developed by the Millenium Ecosystem Assessment (MEA) for the years 2030 and 2050 and implemented in a spatially explicit manner into the IMAGE model. We first identified the major drivers of the river fluxes by regression analyses, then tested the retained models against the past evolutions between 1970 and 2000, and finally applied the models to the MEA scenarios. For nutrients, the considered river data mainly refer to the large rivers for which long-term time series exist (Rhone, Po, Ebro, and Danube). Here, recent trends were principally driven by fertilizer spreads (NO 3 , PO 4 ), together with urban wastewater releases (PO 4 ). Future trends remain in the envelope of the observed variability during the last 40 years, both for the large rivers and, when extrapolated to the basin scales, also for the entire Mediterranean and Black Sea. At regional scales, however, the budgets considerably change. In the northern parts of the Mediterranean drainage basin, they uniformly tend to decrease, but they may strongly increase in the south and east. Water discharge is examined on a basis of 37 rivers, showing that this parameter is clearly linked to the evolution of climate. Because of the ongoing evolution toward dryer and warmer conditions, we predict a significant trend of decreasing freshwater fluxes for the future, which already started in the past. Regional hot spots for this decrease are the drainage basin of the Alboran Sea and, when also considering the inhabitant specific water fluxes, the basins of the Aegean and north Levantine seas.

Nano silver and nano zinc-oxide monthly concentrations in surface waters across Europe were modeled at ∼6 × 9 km spatial resolution. Nano-particle loadings from households to rivers were simulated considering household connectivity to sewerage, sewage treatment efficiency, the spatial distribution of sewage treatment plants, and their associated populations. These loadings were used to model temporally varying nano-particle concentrations in rivers, lakes and wetlands by considering dilution, downstream transport, water evaporation, water abstraction, and nano-particle sedimentation. Temporal variability in concentrations caused by weather variation was simulated using monthly weather data for a representative 31-year period. Modeled concentrations represent current levels of nano-particle production. Two scenarios were modeled. In the most likely scenario, half the river stretches had long-term average concentrations exceeding 0.002 ng L−1 nano silver and 1.5 ng L−1 nano zinc oxide. In 10% of the river stretches, these concentrations exceeded 0.18 ng L−1 and 150 ng L−1, respectively. Predicted concentrations were usually highest in July.