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Nitrous oxide (N2O) is a long-lived greenhouse gas that contributes to global warming. Emissions of N2O mainly stem from agricultural soils. This review highlights the principal factors from peer-reviewed literature affecting N2O emissions from agricultural soils, by grouping the factors into three categories: environmental, management and measurement. Within these categories, each impact factor is explained in detail and its influence on N2O emissions from the soil is summarized. It is also shown how each impact factor influences other impact factors. Process-based simulation models used for estimating N2O emissions are reviewed regarding their ability to consider the impact factors in simulating N2O. The model strengths and weaknesses in simulating N2O emissions from managed soils are summarized. Finally, three selected process-based simulation models (Daily Century (DAYCENT), DeNitrification-DeComposition (DNDC), and Soil and Water Assessment Tool (SWAT)) are discussed that are widely used to simulate N2O emissions from cropping systems. Their ability to simulate N2O emissions is evaluated by describing the model components that are relevant to N2O processes and their representation in the model.

Highlights We present scenarios for European agriculture and food systems: the Eur-Agri-SSPs. The five Eur-Agri-SSPs describe plausible and consistent developments until 2050. We followed a nine-step protocol to ensure a systematic and transparent process. European stakeholders provided regional and thematic details and valuable feedback. The Eur-Agri-SSPs can inform integrated assessments, education, and policy making.

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Abstract. The main objective of this study was to calibrate and validate the eco-hydrological model Soil and Water Assessment Tool (SWAT) with satellite-based actual evapotranspiration (AET) data from the Global Land Evaporation Amsterdam Model (GLEAM_v3.0a) and from the Moderate Resolution Imaging Spectroradiometer Global Evaporation (MOD16) for the Ogun River Basin (20 292 km2) located in southwestern Nigeria. Three potential evapotranspiration (PET) equations (Hargreaves, Priestley–Taylor and Penman–Monteith) were used for the SWAT simulation of AET. The reference simulations were the three AET variables simulated with SWAT before model calibration took place. The sequential uncertainty fitting technique (SUFI-2) was used for the SWAT model sensitivity analysis, calibration, validation and uncertainty analysis. The GLEAM_v3.0a and MOD16 products were subsequently used to calibrate the three SWAT-simulated AET variables, thereby obtaining six calibrations–validations at a monthly timescale. The model performance for the three SWAT model runs was evaluated for each of the 53 subbasins against the GLEAM_v3.0a and MOD16 products, which enabled the best model run with the highest-performing satellite-based AET product to be chosen. A verification of the simulated AET variable was carried out by (i) comparing the simulated AET of the calibrated model to GLEAM_v3.0b AET, which is a product that has different forcing data than the version of GLEAM used for the calibration, and (ii) assessing the long-term average annual and average monthly water balances at the outlet of the watershed. Overall, the SWAT model, composed of the Hargreaves PET equation and calibrated using the GLEAM_v3.0a data (GS1), performed well for the simulation of AET and provided a good level of confidence for using the SWAT model as a decision support tool. The 95 % uncertainty of the SWAT-simulated variable bracketed most of the satellite-based AET data in each subbasin. A validation of the simulated soil moisture dynamics for GS1 was carried out using satellite-retrieved soil moisture data, which revealed good agreement. The SWAT model (GS1) also captured the seasonal variability of the water balance components at the outlet of the watershed. This study demonstrated the potential to use remotely sensed evapotranspiration data for hydrological model calibration and validation in a sparsely gauged large river basin with reasonable accuracy. The novelty of the study is the use of these freely available satellite-derived AET datasets to effectively calibrate and validate an eco-hydrological model for a data-scarce catchment.

Furthermore, tillage practices cause soil disturbance, which may contribute to a decline in available soil N The objective of the study was to determine whether tillage and (Stevenson, 1965; McCarthy et al., 1995) due to mineralresidue practices have a significant effect on the yield and N content of corn (Zea mays L.) under nonlimiting soil N conditions. Nitrate ization of organic matter, which is vulnerable to oxileaching has been identified as a source of non-point-source pollution. dation.By identifying tillage practices which maximize corn N uptake, recom-Soil N content is affected by tillage and residue pracmendations can be based on how to minimize N loss. A 2-year field tices, which subsequently influence crop N concentrastudy was conducted in southwestern Quebec on a 2.4-ha site of a tions. Changes in crop N may influence yield and plant Typic Endoaquent (Humic Gleysol) cropped to corn. Three types of growth. This study examines corn grain and stover N tillage practice (conventional tillage, reduced tillage, and no-till) were content after harvest, and corn yield, as influenced by combined with two residue levels (with and without) in a randomized three tillage practices (conventional tillage, reduced tillcomplete block design. The effect of these practices on corn yield age, and no-till) in combination with two residue levels and corn N were studied. Seedling emergence rates in spring, and corn (with residue and without). Our objectives were to (i) moisture content at harvest, were also monitored. Residues hindered initial plant emergence in the no-till plots. Corn N and moisture N ha Ϫ1 was applied as (NH 4 ) 2 HPO 4 (diammonium phosphate; 18-46-0 N-P-K), banded 5 cm beside and 5 cm below the residues.seed. Three weeks after planting, 140 kg N ha Ϫ1 and 58 kg K ha Ϫ1 were applied as a urea-KCl mixture (26-0-13) in 1996, and as NH 4 NO 3 and KCl (26-0-13) in 1997. The timing and tems Engineering, and G.R. Mehuys, Natural Resource Sciences Dep., dates of herbicide applications are shown in Table 1. The NT

a b s t r a c tStudy region: Bavaria, Germany. Study focus: The Altmühl River is prone to nutrient inputs from agricultural activities. Quantifying nitrate nitrogen (NO 3 − -N) and total phosphorus (TP) concentrations due to potential future changes in the watershed is necessary for managing water quality and adhering to water policy directives. The Soil and Water Assessment Tool (SWAT) was used to provide stakeholders with support in determining the impacts of climate change (CC) in combination with crop land use change (LUC) scenarios on streamflow, NO 3 − -N and TP to the 2050 time horizon. The CC simulations stemmed from RCMs and the LUC scenarios were developed with stakeholders. New hydrological insights for the region: When CC was combined with LUC, mean annual NO 3 − -N loads increased 3-fold, and TP loads 8-fold, compared to the CC simulations alone. Nutrient loads were higher in several months due to the future increased annual precipitation plus the additional fertilizer input in the land use scenarios. The maize areas above the Altmühl Lake contributed greatly to TP loads, while winter wheat areas mainly contributed to NO 3 − -N loads. When CC was combined with LUC, the in-stream nutrient concentrations exceeded ministerial guidelines of 11 mg TP/L and 0.05 mgNO 3 − -N/L every month at the outlet. CC simulations combined with LUC scenarios demonstrated non-linear dynamics whereby the direction and the magnitude of impacts were not predictable from the individual changes alone.

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