Steffen Klatt

LandscapeDNDC: a process model for simulation of biosphere–atmosphere–hydrosphere exchange processes at site and regional scale

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.

A new LandscapeDNDC biogeochemical module to predict CH4 and N2O emissions from lowland rice and upland cropping systems

Background and aimsReplacing paddy rice by upland systems such as maize cultivation is an on-going trend in SE Asia caused by increasing water scarcity and higher demand for meat. How such land management changes will feedback on soil C and N cycles and soil greenhouse gas emissions is not well understood at present.MethodsA new LandscapeDNDC biogeochemical module was developed that allows the effect of land management changes on soil C and N cycle to be simulated. The new module is applied in combination with further modules simulating microclimate and crop growth and evaluated against observations from field experiments.ResultsThe model simulations agree well with observed dynamics of CH4 emissions in paddy rice depending on changes in climatic conditions and agricultural management. Magnitude and peak emission periods of N2O from maize cultivation are simulated correctly, though there are still deficits in reproducing day-to-day dynamics. These shortcomings are most likely related to simulated soil hydrology and may only be resolved if LandscapeDNDC is coupled to more complex hydrological models.ConclusionsLandscapeDNDC allows for simulation of changing land management practices in SE Asia. The possibility to couple LandscapeDNDC to more complex hydrological models is a feature needed to better understand related effects on soil-atmosphere-hydrosphere interactions.

A modeling study on mitigation of N2O emissions and NO3 leaching at different agricultural sites across Europe using LandscapeDNDC

The identification of site-specific agricultural management practices in order to maximize yield while minimizing environmental nitrogen losses remains in the center of environmental pollution research. Here, we used the biogeochemical model LandscapeDNDC to explore different agricultural practices with regard to their potential to reduce soil N2O emissions and NO3 leaching while maintaining yields. In a first step, the model was tested against observations of N2O emissions, NO3 leaching, soil micrometeorology as well as crop growth for eight European cropland and grassland sites. Across sites, LandscapeDNDC predicts very well mean N2O emissions (r(2)=0.99) and simulates the magnitude and general temporal dynamics of soil inorganic nitrogen pools. For the assessment of site-specific mitigation potentials of environmental nitrogen losses a Monte Carlo optimization technique considering different agricultural management options (i.e., timing of planting, harvest and fertilization, amount of applied fertilizer as well as residue management) was used. The identified optimized field management practices reduce N2O emissions and NO3 leaching from croplands on average by 21% and 31%, respectively. Likewise, average reductions of 55% for N2O emissions and 16% for NO3 leaching are estimated for grasslands. For mitigating environmental loss - while maintaining yield levels - it was most important to reduce fertilizer application rates by in average 10%. Our analyses indicate that yield scaled N2O emissions and NO3 leaching indicate possible improvements of nitrogen use efficiencies in European farming systems. Moreover, the applied optimization approach can be used also in a prognostic way to predict optimal timings and fertilization options (rates and splitting) upon accurate weather forecasts combined with the knowledge of modeled soil nutrient availability and plant nitrogen demand.

Estimation and mitigation of N2O emission and nitrate leaching from intensive crop cultivation in the Haean catchment, South Korea

Considering intensive agricultural management practices and environmental conditions, the LandscapeDNDC model was applied for simulation of yields, N2O emission and nitrate leaching from major upland crops and temperate deciduous forest of the Haean catchment, South Korea. Fertilization rates were high (up to 314 kg N ha(-1) year(-1)) and resulted in simulated direct N2O emissions from potato, radish, soybean and cabbage fields of 1.9 and 2.1 kg N ha(-1) year(-1) in 2009 and 2010, respectively. Nitrate leaching was identified as the dominant pathway of N losses in the Haean catchment with mean annual rates of 112.2 and 125.4 kg N ha(-1) year(-1), causing threats to water quality and leading to substantial indirect N2O emissions of 0.84 and 0.94 kg N ha(-1) year(-1) in 2009 and 2010 as estimates by applying the IPCC EF5. Simulated N2O emissions from temperate deciduous forest were low (approx. 0.50 kg N ha(-1) year(-1)) and predicted nitrate leaching rates were even negligible (≤0.01 kg N ha(-1) year(-1)). On catchment scale more than 50% of the total N2O emissions and up to 75% of nitrate leaching originated from fertilized upland fields, only covering 24% of the catchment area. Taking into account area coverage of simulated upland crops and other land uses these numbers agree well with nitrate loads calculated from discharge and concentration measurements at the catchment outlet. The change of current agricultural management practices showed a high potential of reducing N2O emission and nitrate leaching while maintaining current crop yields. Reducing (39%) and splitting N fertilizer application into 3 times was most effective and lead to about 54% and 77% reducing of N2O emission and nitrate leaching from the Haean catchment, the latter potentially contributing to improved water quality in the Soyang River Dam, which is the major source of drinking water for metropolitan residents.

Parallel Multiphysics Simulations Using OpenPALM with Application to Hydro-Biogeochemistry Coupling

Multiphysics systems consist of more than one component governed by its own principle for evolution or equilibrium. As an example, we consider an agricultural land use scenario comprising a hydrology model and a biogeochemistry model. We employ the OpenPALM tool to realize a coupling scheme where the models run concurrently using an individual parallelization. Although the two models demand for very different computational effort to compute one time step, we achieve a balance by allocating appropriate computational resources for each of them. We assess the parallel performance of the coupled application in a 3D scenario. Our concurrent operator splitting scheme shows superior efficiency compared to common coupling approaches.