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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 @ |
Serial |
4685 |
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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 |
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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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Kim, Y.; Berger, S.; Kettering, J.; Tenhunen, J.; Haas, E.; Kiese, R. |
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Title |
Simulation of N2O emissions and nitrate leaching from plastic mulch radish cultivation with LandscapeDNDC |
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Journal Article |
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Year |
2014 |
Publication |
Ecological Research |
Abbreviated Journal |
Ecol. Res. |
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29 |
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3 |
Pages |
441-454 |
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Keywords |
biogeochemical modeling; landscapedndc; N2O; nitrate leaching; plastic mulch; nitrous-oxide emissions; semiarid loess plateau; biogeochemical model; soil-erosion; no emissions; forest soils; dndc model; film mulch; china; field |
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Radish is one of the major dry field crops in Asia commonly grown with plastic mulch and high rates of N fertilization, and potentially harming the environment due to N2O emissions and nitrate leaching. Despite the widespread use of plastic mulch, biogeochemical models so far do not yet consider impacts of mulch on soil environmental conditions and biogeochemistry. In this study, we adapted and successfully tested the LandscapeDNDC model against field data by simulating crop growth, C and N turnover and associated N2O emissions as well as nitrate leaching for radish cultivation with plastic mulch and in conjunction with different rates of N fertilization (465-765 kg N ha(-1) year(-1)). Due to the sandy soil texture and monsoon climate, nitrate leaching with rates up to 350 kg N ha(-1) year(-1) was the dominant reason for overall low nitrogen use efficiency (32-43 %). Direct or indirect N2O emissions (calculated from simulated nitrate leaching rates and IPCC EFind = 0.0075) ranged between 2 and 3 kg N ha(-1) year(-1), thus contributing an equal amount to total field emissions of about 5 kg N ha(-1) year(-1). Based on our results, emission factors for direct N2O emissions ranged between 0.004 and 0.005. These values are only half of the IPCC default value (0.01), demonstrating the need of biogeochemical models for developing site and/or region specific EFs. Simulation results also revealed that changes in agricultural management by applying the fertilizer only to the rows would be an efficient mitigation strategy, effectively decreasing field nitrate leaching and N2O emissions by 50-60 %. |
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0912-3814 1440-1703 |
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CropM, ft_macsur |
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MA @ admin @ |
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4528 |
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Grosz, B.; Dechow, R.; Gebbert, S.; Hoffmann, H.; Zhao, G.; Constantin, J.; Raynal, H.; Wallach, D.; Coucheney, E.; Lewan, E.; Eckersten, H.; Specka, X.; Kersebaum, K.-C.; Nendel, C.; Kuhnert, M.; Yeluripati, J.; Haas, E.; Teixeira, E.; Bindi, M.; Trombi, G.; Moriondo, M.; Doro, L.; Roggero, P.P.; Zhao, Z.; Wang, E.; Tao, F.; Roetter, R.; Kassie, B.; Cammarano, D.; Asseng, S.; Weihermueller, L.; Siebert, S.; Gaiser, T.; Ewert, F. |
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Title |
The implication of input data aggregation on up-scaling soil organic carbon changes |
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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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96 |
Issue |
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361-377 |
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Keywords |
Biogeochemical model; Data aggregation; Up-scaling error; Soil organic carbon; DIFFERENT SPATIAL SCALES; NITROUS-OXIDE EMISSIONS; MODELING SYSTEM; DATA; RESOLUTION; CROP MODELS; CLIMATE; LONG; PRODUCTIVITY; CROPLANDS; DAYCENT |
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In up-scaling studies, model input data aggregation is a common method to cope with deficient data availability and limit the computational effort. We analyzed model errors due to soil data aggregation for modeled SOC trends. For a region in North West Germany, gridded soil data of spatial resolutions between 1 km and 100 km has been derived by majority selection. This data was used to simulate changes in SOC for a period of 30 years by 7 biogeochemical models. Soil data aggregation strongly affected modeled SOC trends. Prediction errors of simulated SOC changes decreased with increasing spatial resolution of model output. Output data aggregation only marginally reduced differences of model outputs between models indicating that errors caused by deficient model structure are likely to persist even if requirements on the spatial resolution of model outputs are low. (C)2017 Elsevier Ltd. All rights reserved. |
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2017-09-14 |
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1364-8152 |
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CropM, ft_macsur |
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MA @ admin @ |
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5176 |
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Constantin, J.; Raynal, H.; Casellas, E.; Hoffman, H.; Bindi, M.; Doro, L.; Eckersten, H.; Gaiser, T.; Grosz, B.; Haas, E.; Kersebaum, K.-C.; Klatt, S.; Kuhnert, M.; Lewan, E.; Maharjan, G.R.; Moriondo, M.; Nendel, C.; Roggero, P.P.; Specka, X.; Trombi, G.; Villa, A.; Wang, E.; Weihermueller, L.; Yeluripati, J.; Zhao, Z.; Ewert, F.; Bergez, J.-E. |
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Management and spatial resolution effects on yield and water balance at regional scale in crop models |
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Journal Article |
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2019 |
Publication |
Agricultural and Forest Meteorology |
Abbreviated Journal |
Agricultural and Forest Meteorology |
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275 |
Issue |
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184-195 |
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Keywords |
Drainage; Evapotranspiration; Aggregation; Decision rules; Scaling; winter-wheat yield; data aggregation; sowing dates; area index; input; data; carbon; growth; irrigation; productivity; assimilation |
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Due to the more frequent use of crop models at regional and national scale, the effects of spatial data input resolution have gained increased attention. However, little is known about the influence of variability in crop management on model outputs. A constant and uniform crop management is often considered over the simulated area and period. This study determines the influence of crop management adapted to climatic conditions and input data resolution on regional-scale outputs of crop models. For this purpose, winter wheat and maize were simulated over 30 years with spatially and temporally uniform management or adaptive management for North Rhine-Westphalia ((similar to)34 083 km(2)), Germany. Adaptive management to local climatic conditions was used for 1) sowing date, 2) N fertilization dates, 3) N amounts, and 4) crop cycle length. Therefore, the models were applied with four different management sets for each crop. Input data for climate, soil and management were selected at five resolutions, from 1 x 1 km to 100 x 100 km grid size. Overall, 11 crop models were used to predict regional mean crop yield, actual evapotranspiration, and drainage. Adaptive management had little effect (< 10% difference) on the 30-year mean of the three output variables for most models and did not depend on soil, climate, and management resolution. Nevertheless, the effect was substantial for certain models, up to 31% on yield, 27% on evapotranspiration, and 12% on drainage compared to the uniform management reference. In general, effects were stronger on yield than on evapotranspiration and drainage, which had little sensitivity to changes in management. Scaling effects were generally lower than management effects on yield and evapotranspiration as opposed to drainage. Despite this trend, sensitivity to management and scaling varied greatly among the models. At the annual scale, effects were stronger in certain years, particularly the management effect on yield. These results imply that depending on the model, the representation of management should be carefully chosen, particularly when simulating yields and for predictions on annual scale. |
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2020-02-14 |
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ISSN |
0168-1923 |
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CropM, ft_macsur |
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Call Number |
MA @ admin @ |
Serial |
5225 |
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