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Molina-Herrera, S.; Haas, E.; Klatt, S.; Kraus, D.; Augustin, J.; Magliulo, V.; Tallec, T.; Ceschia, E.; Ammann, C.; Loubet, B.; Skiba, U.; Jones, S.; Brümmer, C.; Butterbach-Bahl, K.; Kiese, R. |
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Title |
A modeling study on mitigation of N2O emissions and NO3 leaching at different agricultural sites across Europe using LandscapeDNDC |
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Journal Article |
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Year |
2016 |
Publication |
Science of the Total Environment |
Abbreviated Journal |
Science of the Total Environment |
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Volume  |
553 |
Issue |
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Pages |
128-140 |
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Keywords |
Agricultural management; LandscapeDNDC; Mitigation; N₂O emission; NO₃ leaching; Optimization |
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Abstract |
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. |
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0048-9697 |
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CropM, ft_macsur |
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MA @ admin @ |
Serial |
4727 |
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Author |
Kraus, D.; Weller, S.; Klatt, S.; Haas, E.; Wassmann, R.; Kiese, R.; Butterbach-Bahl, K. |
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Title |
A new LandscapeDNDC biogeochemical module to predict CH4 and N2O emissions from lowland rice and upland cropping systems |
Type |
Journal Article |
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Year |
2015 |
Publication |
Plant and Soil |
Abbreviated Journal |
Plant Soil |
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Volume |
386 |
Issue |
1-2 |
Pages |
125-149 |
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Keywords |
methane; nitrous oxide; paddy rice; maize; model; nitrous-oxide emissions; process-based model; methane transport capacity; process-oriented model; pnet-n-dndc; forest soils; paddy soils; sensitivity-analysis; residue management; organic-matter |
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Replacing 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. A 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. The model simulations agree well with observed dynamics of CH (4) emissions in paddy rice depending on changes in climatic conditions and agricultural management. Magnitude and peak emission periods of N (2) O 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. LandscapeDNDC 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. |
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0032-079x |
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CropM, ft_macsur |
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MA @ admin @ |
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4530 |
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Author |
Molina-Herrera, S.; Haas, E.; Grote, R.; Kiese, R.; Klatt, S.; Kraus, D.; Kampffmeyer, T.; Friedrich, R.; Andreae, H.; Loubet, B.; Ammann, C.; Horvath, L.; Larsen, K.; Gruening, C.; Frumau, A.; Butterbach-Bahl, K. |
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Title |
Importance of soil NO emissions for the total atmospheric NOX budget of Saxony, Germany |
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Journal Article |
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Year |
2017 |
Publication |
Atmospheric Environment |
Abbreviated Journal |
Atm. Environ. |
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Volume |
152 |
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61-76 |
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Keywords |
LandscapeDNDC; Model evaluation; NOX emissions; Soil emissions; Distributed modeling; Emission inventory; Nitric-Oxide Emissions; European Forest Soils; Nitrous-Oxide; N2O; Emissions; Agricultural Soils; Gas Emissions; Organic Soil; Trace Gases; Model; Fluxes |
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Soils are a significant source for the secondary greenhouse gas NO and assumed to be a significant source of tropospheric NOx in rural areas. Here we tested the LandscapeDNDC model for its capability to simulate magnitudes and dynamics of soil NO emissions for 22 sites differing in land use (arable, grassland and forest) and edaphic as well as climatic conditions. Overall, LandscapeDNDC simulated mean soil NO emissions agreed well with observations (r(2) = 0.82). However, simulated day to day variations of NO did only agree weakly with high temporal resolution measurements, though agreement between simulations and measurements significantly increased if data were aggregated to weekly, monthly and seasonal time scales. The model reproduced NO emissions from high and low emitting sites, and responded to fertilization (mineral and organic) events with pulse emissions. After evaluation, we linked the LandscapeDNDC model to a GIS database holding spatially explicit data on climate, land use, soil and management to quantify the contribution of soil biogenic NO emissions to the total NOx budget for the State of Saxony, Germany. Our calculations show that soils of both agricultural and forest systems are significant sources and contribute to about 8% (uncertainty range: 6 -13%) to the total annual tropospheric NO, budget for Saxony. However, the contributions of soil NO emission to total tropospheric NO, showed a high spatial variability and in some rural regions such as the Ore Mts., simulated soil NO emissions were by far more important than anthropogenic sources. (C) 2016 Elsevier Ltd. All rights reserved. |
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2017-04-07 |
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1352-2310 |
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CropM, ft_macsur |
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MA @ admin @ |
Serial |
4943 |
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Author |
Zhang, W.; Liu, C.; Zheng, X.; Zhou, Z.; Cui, F.; Zhu, B.; Haas, E.; Klatt, S.; Butterbach-Bahl, K.; Kiese, R. |
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Title |
Comparison of the DNDC, LandscapeDNDC and IAP-N-GAS models for simulating nitrous oxide and nitric oxide emissions from the winter wheat–summer maize rotation system |
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Journal Article |
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Year |
2015 |
Publication |
Agricultural Systems |
Abbreviated Journal |
Agricultural Systems |
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Volume |
140 |
Issue |
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Pages |
1-10 |
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Keywords |
Model ensemble; Straw incorporation; Irrigation; Fertilization; Calcareous soil; North China Plain; process-oriented model; soil organic-matter; biogeochemical model; cropping system; N2O emissions; forest soils; microbial-growth; rainfall events; calcareous soil |
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The DNDC, LandscapeDNDC and IAP-N-GAS models have been designed to simulate the carbon and nitrogen processes of terrestrial ecosystems. Until now, a comparison of these models using simultaneous observations has not been reported, although such a comparison is essential for further model development and application. This study aimed to evaluate the performance of the models, delineate the strengths and limitations of each model for simulating soil nitrous oxide (N2O) and nitric oxide (NO) emissions, and explore short-comings of these models that may require reconsideration. We conducted comparisons among the models using simultaneous observations of both gases and relevant variables from the winter wheat-summer maize rotation system at three field sites with calcareous soils. Simulations of N2O and NO emissions by the three models agreed well with annual observations, but not with daily observations. All models failed to correctly simulate soil moisture, which could explain some of the incorrect daily fluxes of N2O and NO, especially for intensive fluxes during the growing season. Multi-model ensembles are promising approaches to better simulate daily gas emissions. IAP-N-GAS underestimated the priming effect of straw incorporation on N2O and NO emissions, but better results were obtained with DNDC95 and LandscapeDNDC. LandscapeDNDC and IAP-N-GAS need to improve the simulation of irrigation water allocation and residue decomposition processes, respectively, and together to distinguish different irrigation methods as DNDC95 does. All three models overestimated the emissions of the nitrogenous gases for high nitrogen fertilizer (>430 kg N ha(-1) yr(-1)) addition treatments, and therefore, future research should focus more on the simulation of the limitation of soil dissolvable organic carbon on denitrification in calcareous soils. |
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0308-521x |
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CropM, ft_macsur |
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MA @ admin @ |
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4685 |
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Houska, T.; Kraft, P.; Liebermann, R.; Klatt, S.; Kraus, D.; Haas, E.; Santabarbara, I.; Kiese, R.; Butterbach-Bahl, K.; Müller, C.; Breuer, L. |
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Title |
Rejecting hydro-biogeochemical model structures by multi-criteria evaluation |
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Journal Article |
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Year |
2017 |
Publication |
Environmental Modelling & Software |
Abbreviated Journal |
Env. Model. Softw. |
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Volume |
93 |
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1-12 |
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Abstract |
Highlights • New method to investigate biogeochemical model structure performance. • Process based hydrological modelling can improve biogeochemical model predictions. • Modelling efficiency dramatically drops with multiple objectives. Abstract This work presents a novel way for assessing and comparing different hydro-biogeochemical model structures and their performances. We used the LandscapeDNDC modelling framework to set up four models of different complexity, considering two soil-biogeochemical and two hydrological modules. The performance of each model combination was assessed using long-term (8 years) data and applying different thresholds, considering multiple criteria and objective functions. Our results show that each model combination had its strength for particular criteria. However, only 0.01% of all model runs passed the complete rejectionist framework. In contrast, our comparatively applied assessments of single thresholds, as frequently used in other studies, lead to a much higher acceptance rate of 40–70%. Therefore, our study indicates that models can be right for the wrong reasons, i.e., matching GHG emissions while at the same time failing to simulate other criteria such as soil moisture or plant biomass dynamics. |
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1364-8152 |
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CropM, ft_macsur |
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MA @ admin @ |
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4983 |
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