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The emission of nitrous oxide (N2O) from agricultural soils to the atmosphere is a significant contributor to anthropogenic greenhouse gas emissions. The recycling of organic nitrogen (N) in manure and crop residues may result in spatiotemporal variability of N2O production and soil efflux which is difficult to capture by process-based models. We propose a multi-species, reactive transport model to provide detailed insight into the spatiotemporal variability of nitrogen (N) transformations around such N2O hotspots, which consists of kinetic reactions of soil respiration, nitrification, nitrifier denitrification, and denitrification represented by a system of coupled partial differential equations. The model was tested with results from an incubation experiment at two different soil moisture levels (-30 and -100 hPa, respectively) and was shown to reasonably well reproduce the recorded N2O and dinitrogen (N2) emissions, and the dynamics of important carbon (C) and N components in soil. The simulation indicated that the four populations developed in closely connected, but separate layers, with denitrifying bacteria growing within the manure-dominated zone and nitrifying bacteria in the well-aerated soil outside the manure zone and with time also within the manure layer. The modeled N2O production within the manure zone was greatly enhanced by the combined effect of oxygen deficit, abundant carbon source and supply of nitrogenous substrates. In the wetter soil treatment with a water potential of -30 hPa, diffusive flux of nitrate (NO3-) across the manure-soil interface was the main source of NO3- for denitrification in the manure zone, while at a soil water potential of -100 hPa, diffusion became less dominant and overtaken by the co-occurrence of nitrification and denitrification in the manure zone. Scenarios were analyzed where diffusive transport of dissolved organic carbon or different mineral N species were switched off, and they showed that the simultaneous diffusion of NO3-, ammonium (NH4+), and nitrite (NO2-) were crucial to simulate the dynamics of N transformations and N2O emissions in the model. Without considering solute diffusion in process-based N2O models, the rapid turnover of C and N associated with organic hotspots can not be accounted for, and it may result in underestimation of N2O emissions from soil after manure application. The model and its parameters allow for new detailed insights into the interactions between transport and microbial transformations associated with N2O emissions in heterogeneous soil environments. [ABSTRACT FROM AUTHOR]

Early sowing of winter cereals has been promoted as an alternative to catch crops for reducing nitrogen (N) leaching in intensively managed cropping systems. Underlying data for this are, however, scarce and it is unclear how year‐to‐year variations affect potential reductions in N leaching. Well‐tested cropping system models can be used to assess the impact of early sowing on crop yield and N leaching. We tested the ability of the Agricultural Production System Simulator (APSIM) to simulate grain yield, biomass, phenology, N uptake and N leaching from timely and early‐sown winter cereals. The evaluation was based on two extensive field experiments carried out in Denmark in continuous winter cereals systems with different N fertilization applications, and a farm experiment in Germany with a grass ley/winter wheat crop sequence and two different N fertilization rates. Additionally, observations from growth stages throughout Denmark were used. After changing a few crop model parameters, APSIM reproduced the general effects of N fertilization and crop sequence on yields and N uptake, as well as N leaching. The model was then used to simulate the effect of sowing time on grain yield over a period of 10 years, to capture year‐to‐year variability and enable a better evaluation of the efficacy of early sowing for reducing N leaching. In the continuous winter cereal systems, early sowing reduced N leaching at both sites in Denmark. In contrast, in the grass ley/winter wheat system in Germany early sowing increased N leaching, due to enhanced mineralization of grass residues. [ABSTRACT FROM AUTHOR]

Optimum nitrogen (N) fertilization, which aims for high productivity while minimizing N losses to the environment, requires a better understanding of the N leaching behaviour around the recommended N rate. A study was conducted with increasing N fertilization levels over 3 years (2016–2019) with early and timely sown winter cereals (rye and wheat) at two sites in Denmark with different climatic conditions. For winter rye N fertilizer application rates ranged from 0 to 258 kg N ha‒1, and for winter wheat from 0 to 300 kg ha‒1. Grain yields did not respond much to the N application above the recommended rate. Nitrate (NO3) leaching was very low in the first period, but increased in the second and third period. The effect of a potential N carry‐over on marginal N leaching (defined as the additional N leaching per unit of additional N fertilizer applied) is large. Under early sown winter rye, marginal N leaching is reduced from 36 to 14 kg N ha‒1 in the third period following N fertilization of the recommended rate of 170 kg N ha‒1 when carry‐over was accounted for, and under the timely sown winter rye from 68 to 24 kg N ha‒1. Our results show that marginal N leaching around the recommended rate is almost linear at the study site, when carry‐over is accounted for. Thus, the use of precision agriculture, with lower fertilization application rates to areas with high residual soil N, is less effective compared with sites, which have an exponential leaching behaviour. [ABSTRACT FROM AUTHOR]

BACKGROUND: Nitrogen (N) fertiliser used on crops is among the main sources of water pollution. Reliable measurement of N losses from land uses in catchments is key to designing effective management strategies that minimise those losses at the same time as keeping farms profitable. In the present study, we used a management simulation tool within the Agricultural Production Systems sIMulator (APSIM) to assess the effect of fertiliser management on N leaching from croplands in the Aparima catchment in Southland, New Zealand. The assessment was based on two N‐fertiliser regimes: (i) Scheduled (conventional) where, N‐fertiliser rates and timing of application followed a prescribed programme, and (ii) Soil‐test where, N‐fertiliser rates and timing depended on daily analysis of simulated soil N levels. Four rotations (continuous wheat, pasture‐wheat‐grain oats, wheat‐fodder beet‐peas and wheat‐green oats‐fodder beet‐peas) were used in the evaluation. RESULTS: APSIM simulated crop productivity with reasonable accuracy. Yields were 2% greater, fertiliser N input was 11% lower and leaching was 20% lower under the Soil‐test compared to the Scheduled fertiliser management. These results show the potential of a Soil‐test based fertiliser application to increase fertiliser‐N use efficiency and reduce the risk of N loss to the Southland catchment water systems. CONCLUSION: The present study demonstrates a dynamic farm systems model can be a viable tool to generate valuable data for assessing the productivity and environmental effects of cropping systems at a catchment scale. © 2021 Society of Chemical Industry [ABSTRACT FROM AUTHOR]

Soil processes have a major impact on agroecosystems, controlling water and nutrient cycling, regulating plant growth and losses to the wider environment. Process-based agroecosystem simulation models generally encompass detailed descriptions of the soil, including a wide number of parameters that can be daunting to users with a limited soil science background. In this work we review and present an abridged description of the models used to simulate soil processes in the APSIM (Agricultural Production Systems sIMulator) framework. Such a resource is needed because this information is currently spread over multiple publications and some elements have become outdated. We list and briefly describe the parameters, and establish a protocol with guidelines, for building a soil description for APSIM. This protocol will promote consistency, enhancing the quality of the science done employing APSIM, and provide an easier pathway for new users. This compilation should also be of relevance to users of other models that require detailed soil information.•This paper presents a brief description of the models for simulating soil processes in the APSIM model.•The method stablishes guidelines to define the parameters for building a soil description for APSIM., Competing Interests: The authors confirm that there are no conflicts of interest., (© 2021 The Authors. Published by Elsevier B.V.)