• Energy Research

We present a new model system, which facilitates scaling of ecosystem processes from the site to regional simulation domains. The new framework LandscapeDNDC—partly based on the biogeochemical site scale model DNDC—inherits a series of new features with regard to process descriptions, model structure and data I/O functionality. LandscapeDNDC incorporates different vegetation types and management systems for simulating carbon, nitrogen and water related biosphere–atmosphere–hydrosphere fluxes in forest, arable and grassland ecosystems and allows the dynamic simulation of land use changes. The modeling concept divides ecosystems into six substates (canopy air chemistry, microclimate, physiology, water cycle, vegetation structure, and soil biogeochemistry) and provides alternative modules dealing with these substates. The model can be applied on the site scale, as well as for three-dimensional regional simulations. For regional applications LandscapeDNDC integrates all grid cells synchronously forward in time. This allows easy coupling to other spatially distributed models (e.g. for hydrology or atmospheric chemistry) and efficient two-way exchange of states. This paper describes the fundamental design concept of the model and its object-oriented software implementation. Two example applications are presented. First, calculation of a nitrous oxide emission inventory from agricultural soils for the State of Saxaony (Germany), including data preprocessing of the regional model input data. The computational effort for the LandscapeDNDC preprocessing and simulation could be speed up by a factor of almost 100 compared to the approach using the original DNDC version 9.3. Calculated N2O emissions for Saxony with LandscapeDNDC (2693 t N2O–N/a) were compared with the original DNDC model (2725 t N2O–N/a), the IPCC Tier I methodology (1107 t N2O–N/a), and the German National Inventory Report (equal to IPCC Tier II, 2100 t N2O–N/a). The second example illustrates the capabilities of LandscapeDNDC for building a fully coupled three-dimensional model system on the landscape scale. Therefore we coupled the biogeochemical and plant growth calculations to a hydrological transport model and demonstrate the transport of nitrogen along a virtual hillslope and associated formation of indirect nitrous oxide emissions.

Abstract ScaleX is a collaborative measurement campaign, collocated with a long-term environmental observatory of the German Terrestrial Environmental Observatories (TERENO) network in the mountainous terrain of the Bavarian Prealps, Germany. The aims of both TERENO and ScaleX include the measurement and modeling of land surface–atmosphere interactions of energy, water, and greenhouse gases. ScaleX is motivated by the recognition that long-term intensive observational research over years or decades must be based on well-proven, mostly automated measurement systems, concentrated in a small number of locations. In contrast, short-term intensive campaigns offer the opportunity to assess spatial distributions and gradients by concentrated instrument deployments, and by mobile sensors (ground and/or airborne) to obtain transects and three-dimensional patterns of atmospheric, surface, or soil variables and processes. Moreover, intensive campaigns are ideal proving grounds for innovative instruments, methods, and techniques to measure quantities that cannot (yet) be automated or deployed over long time periods. ScaleX is distinctive in its design, which combines the benefits of a long-term environmental-monitoring approach (TERENO) with the versatility and innovative power of a series of intensive campaigns, to bridge across a wide span of spatial and temporal scales. This contribution presents the concept and first data products of ScaleX-2015, which occurred in June–July 2015. The second installment of ScaleX took place in summer 2016 and periodic further ScaleX campaigns are planned throughout the lifetime of TERENO. This paper calls for collaboration in future ScaleX campaigns or to use our data in modelling studies. It is also an invitation to emulate the ScaleX concept at other long-term observatories.

AbstractCrop residues are important inputs of carbon (C) and nitrogen (N) to soils and thus directly and indirectly affect nitrous oxide (N2O) emissions. As the current inventory methodology considers N inputs by crop residues as the sole determining factor for N2O emissions, it fails to consider other underlying factors and processes. There is compelling evidence that emissions vary greatly between residues with different biochemical and physical characteristics, with the concentrations of mineralizable N and decomposable C in the residue biomass both enhancing the soil N2O production potential. High concentrations of these components are associated with immature residues (e.g., cover crops, grass, legumes, and vegetables) as opposed to mature residues (e.g., straw). A more accurate estimation of the short‐term (months) effects of the crop residues on N2O could involve distinguishing mature and immature crop residues with distinctly different emission factors. The medium‐term (years) and long‐term (decades) effects relate to the effects of residue management on soil N fertility and soil physical and chemical properties, considering that these are affected by local climatic and soil conditions as well as land use and management. More targeted mitigation efforts for N2O emissions, after addition of crop residues to the soil, are urgently needed and require an improved methodology for emission accounting. This work needs to be underpinned by research to (1) develop and validate N2O emission factors for mature and immature crop residues, (2) assess emissions from belowground residues of terminated crops, (3) improve activity data on management of different residue types, in particular immature residues, and (4) evaluate long‐term effects of residue addition on N2O emissions.

Abstract The spatial variability of soil nitrous oxide (N 2 O) fluxes is large − regardless of the study scale − resulting in very large uncertainties in soil N 2 O emission assessments. The objectives of this study were to assess the N 2 O flux at the landscape scale by coupling the results of measurements performed at different scales and to propose a method for obtaining emission maps based on these results. During a 2-month campaign (mid-March to mid-May 2015), N 2 O fluxes were measured in a small cropland area (∼km 2 ) (i) continuously at the plot scale using automatic chambers in a wheat field, (ii) punctually on a group of 16 plots including different types of soils and crops using a mobile chamber (fast-box), and (iii) continuously at the landscape scale by eddy covariance using a 15-m height mast. The soil properties were measured at all sites to provide a better understanding of the factors controlling the variability of the N 2 O flux. To map the N 2 O emissions of the entire area, two flux attribution methods were evaluated which allowed estimating the N 2 O flux of each field during the whole period. These methods used a footprint model in combination with fast-box measurements over each crop type to determine the contribution of each field to the flux measured at the eddy covariance mast. Two footprint models were compared (the FIDES, and the Kormann and Meixner models) and two hypotheses on the dependency of N 2 O emissions on crop distribution and soil nitrate contents were tested. Automatic chambers were used to evaluate the attribution methods. The N 2 O fluxes measured by the different methods showed good agreement in magnitude and temporal dynamics, especially when the automatic chambers were in the eddy covariance mast footprint. Overall, the mean measured N 2 O emission was 53 ± 6 μg N N 2 O m −2 h −1 for the automatic chambers, 45 ± 7 N N 2 O m −2 h −1 for the eddy covariance system and 37 ± 9 N N 2 O m −2 h −1 for the fast-box, for periods when both automatic measurement systems were functioning. The N 2 O fluxes measured by the automatic chambers and the fast-box were positively correlated with soil humidity (p 2 O than wheat and rapeseed fields, and much more than forests. Over the whole area during the 2-month experimental period, the N 2 O flux varied from 0.18 to 0.44 kg N N 2 O ha −1 month −1 depending on the attribution method and footprint model. The simplest flux attribution method, taking only land use into account, showed very good agreement with the field measurements provided by the automated chambers (10%–13% difference on the mean flux). Our study demonstrates the potential of flux attribution methods for catching spatial variability of soil N 2 O emission at the landscape scale and reducing uncertainties in its evaluation.