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Academic literature on the topic 'DNDC model'

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Journal articles on the topic "DNDC model"

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Kröbel, R., W. Smith, B. Grant, R. Desjardins, C. Campbell, N. Tremblay, C. Li, R. Zentner, and B. McConkey. "Development and evaluation of a new Canadian spring wheat sub-model for DNDC." Canadian Journal of Soil Science 91, no. 4 (July 2011): 503–20. http://dx.doi.org/10.4141/cjss2010-059.

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Kröbel, R., Smith, W. N., Grant, B. B., Desjardins, R. L., Campbell, C. A., Tremblay, N., Li, C. S., Zentner, R. P. and McConkey, B. G. 2011. Development and evaluation of a new Canadian spring wheat sub-model for DNDC. Can. J. Soil Sci. 91: 503–520. In this paper, the ability of the DNDC model (version 93) to predict biomass production, grain yield and plant nitrogen content was assessed using data from experiments at Swift Current, Saskatchewan, and St-Blaise, Quebec, Canada. While predicting wheat grain yields reasonably well, the model overestimated the growth of above-ground plant biomass and nitrogen uptake during the first half of the growing season. A new spring wheat sub-model (DNDC-CSW) was introduced with a modified plant biomass growth curve, dynamic plant C/N ratios and modified plant biomass fractioning curves. DNDC-CSW performed considerably better in simulating plant biomass [modeling efficiency (EF): 0.75, average relative error (ARE): 6.0%] and plant nitrogen content (EF: 0.61, ARE: −2.7%) at Swift Current and St-Blaise (EF of 0.75 and ARE of 2.3%), compared with DNDC 93 (biomass SC: EF 0.49, ARE 17.1%, SB: EF 0.02 ARE 33.4%). In comparison with DNDC 93, DNDC-CSW better captured inter-annual variations in crop growth for a range of wheat rotations, increasing the EF from 0.32 to 0.52 for grain and from 0.35 to 0.39 for straw yields. DNDC-CSW also performed considerably better than DNDC 93 in estimating soil carbon changes at Swift Current. Hence, DNDC-CSW has the potential to improve the performance of DNDC 93 in simulating wheat biomass, plant nitrogen, yield and soil carbon at various Canadian sites.
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Jiang, Qianjing, Zhiming Qi, Chandra A. Madramootoo, Ward Smith, Naeem A. Abbasi, and Tiequan Zhang. "Comparison of RZWQM2 and DNDC Models to Simulate Greenhouse Gas Emissions under Combined Inorganic/Organic Fertilization in a Subsurface-Drained Field." Transactions of the ASABE 63, no. 4 (2020): 771–87. http://dx.doi.org/10.13031/trans.13668.

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HighlightsRZWQM2 was compared with DNDC to predict greenhouse gas emissions.RZWQM2 was applied to simulate the greenhouse gas emissions under manure application.RZWQM2 performed better than DNDC in simulating soil water content and CO2 emissions.Abstract. N management has the potential to mitigate greenhouse gas (GHG) emissions. Process-based models are promising tools for evaluating and developing management practices that may optimize sustainability goals as well as promote crop productivity. In this study, the GHG emission component of the Root Zone Water Quality Model (RZWQM2) was tested under two different types of N management and subsequently compared with the Denitrification-Decomposition (DNDC) model using measured data from a subsurface-drained field with a corn-soybean rotation in southern Ontario, Canada. Field-measured data included N2O and CO2 fluxes, soil temperature, and soil moisture content from a four-year field experiment (2012 to 2015). The experiment was composed of two N treatments: inorganic fertilizer (IF), and inorganic fertilizer combined with solid cattle manure (SCM). Both models were calibrated using the data from IF and validated with SCM. Statistical results indicated that both models predicted well the soil temperature, but RZWQM2 performed better than DNDC in simulating soil water content (SWC) because DNDC lacked a heterogeneous soil profile, had shallow simulation depth, and lacked crop root density functions. Both RZWQM2 and DNDC predicted the cumulative N2O and CO2 emissions within 15% error under all treatments, while the timing of daily CO2 emissions was more accurately predicted by RZWQM2 (RMSE = 0.43 to 0.54) than by DNDC (RMSE = 0.60 to 0.67). Modeling results for N management effects on GHG emissions showed consistency with the field measurements, indicating higher CO2 emissions under SCM than IF, higher N2O emissions under IF in corn years, but lower N2O emissions in soybean years. Overall, RZWQM2 required more experienced and intensive calibration and validation, but it provided more accurate predictions of soil hydrology and better timing of CO2 emissions than DNDC. Keywords: CO2 emission, Corn-soybean rotation, Inorganic fertilization, Manure application, N2O emission, Process-based modeling.
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Smith, W. N., R. L. Desjardins, B. Grant, C. Li, R. Lemke, P. Rochette, M. D. Corre, and D. Pennock. "Testing the DNDC model using N2O emissions at two experimental sites in Canada." Canadian Journal of Soil Science 82, no. 3 (August 1, 2002): 365–74. http://dx.doi.org/10.4141/s01-048.

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Measured data from two experimental sites in Canada were used to test the ability of the DeNitrification and DeComposition model (DNDC) to predict N2O emissions from agricultural soils. The two sites, one from eastern Canada, and one from western Canada, provided a variety of crops, management practices, soils, and climates for testing the model. At the site in eastern Canada, the magnitude of total seasonal N2O flux from the seven treatments was accurately predicted with a slight average over-prediction (ARE) of 3% and a coefficient of variation of 41%. Nitrous oxide emissions based on International Panel for Climate Change (IPCC) methodology had a relative error of 62% for the seven treatments. The DNDC estimates of total yearly emissions of N2O from the field site in western Canada showed an underestimation of 8% for the footslope landscape position and an overestimation of 46% for the shoulder position. The data input for the DNDC model were not of sufficient detail to characterize the moisture difference between the landscape positions. The estimates from IPCC guidelines showed an underestimation of 54% for the footslope and an overestimation of 161% for the shoulder. The results indicate that the DNDC model was more accurate than IPCC methodology at estimating N2O emissions at both sites. Key words: Nitrous oxide, DNDC, soil model, greenhouse gas, testing
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Li, Hu, Jianjun Qiu, Ligang Wang, and Li Yang. "Advance in a terrestrial biogeochemical model—DNDC model." Acta Ecologica Sinica 31, no. 2 (April 2011): 91–96. http://dx.doi.org/10.1016/j.chnaes.2010.11.006.

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Deng, J., Z. Zhou, B. Zhu, X. Zheng, C. Li, X. Wang, and Z. Jian. "Modeling nitrogen loading in a small watershed in Southwest China using a DNDC model with hydrological enhancements." Biogeosciences Discussions 8, no. 4 (July 6, 2011): 6383–413. http://dx.doi.org/10.5194/bgd-8-6383-2011.

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Abstract. The degradation of water quality has been observed worldwide, and inputs of nitrogen (N), along with other nutrients, play a key role in the process of contamination. The quantification of N loading from non-point sources at a watershed scale has long been a challenge. Process-based models have been developed to address this problem. Because N loading from non-point sources result from interactions between biogeochemical and hydrological processes, a model framework must include both types of processes if it is to be useful. This paper reports the results of a study in which we integrated two fundamental hydrologic features, the SCS (Soil Conservation Service) curve function and the MUSLE (Modified Universal Soil Loss), into a biogeochemical model, the DNDC. The SCS curve equation and the MUSLE are widely used in hydrological models for calculating surface runoff and soil erosion. Equipped with the new added hydrologic features, DNDC was substantially enhanced with the new capacity of simulating both vertical and horizontal movements of water and N at a watershed scale. A long-term experimental watershed in Southwest China was selected to test the new version of the DNDC. The target watershed's 35.1 ha of territory encompass 19.3 ha of croplands, 11.0 ha of forest lands, 1.1 ha of grassplots, and 3.7 ha of residential areas. An input database containing topographic data, meteorological conditions, soil properties, vegetation information, and management applications was established and linked to the enhanced DNDC. Driven by the input database, the DNDC simulated the surface runoff flow, the subsurface leaching flow, the soil erosion, and the N loadings from the target watershed. The modeled water flow, sediment yield, and N loading from the entire watershed were compared with observations from the watershed and yielded encouraging results. The sources of N loading were identified by using the results of the model. In 2008, the modeled runoff-induced loss of total N from the watershed was 904 kg N yr−1, of which approximately 67 % came from the croplands. The enhanced DNDC model also estimated the watershed-scale N losses (1391 kg N yr−1) from the emissions of the N-containing gases (ammonia, nitrous oxide, nitric oxide, and dinitrogen). Ammonia volatilization (1299 kg N yr−1) dominated the gaseous N losses. The study indicated that process-based biogeochemical models such as the DNDC could contribute more effectively to watershed N loading studies if the hydrological components of the models were appropriately enhanced.
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Deng, J., Z. Zhou, B. Zhu, X. Zheng, C. Li, X. Wang, and Z. Jian. "Modeling nitrogen loading in a small watershed in southwest China using a DNDC model with hydrological enhancements." Biogeosciences 8, no. 10 (October 28, 2011): 2999–3009. http://dx.doi.org/10.5194/bg-8-2999-2011.

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Abstract. The degradation of water quality has been observed worldwide, and inputs of nitrogen (N), along with other nutrients, play a key role in the process of contamination. The quantification of N loading from non-point sources at a watershed scale has long been a challenge. Process-based models have been developed to address this problem. Because N loading from non-point sources result from interactions between biogeochemical and hydrological processes, a model framework must include both types of processes if it is to be useful. This paper reports the results of a study in which we integrated two fundamental hydrologic features, the SCS (Soil Conservation Service) curve function and the MUSLE (Modified Universal Soil Loss), into a biogeochemical model, the DNDC. The SCS curve equation and the MUSLE are widely used in hydrological models for calculating surface runoff and soil erosion. Equipped with the new added hydrologic features, DNDC was substantially enhanced with the new capacity of simulating both vertical and horizontal movements of water and N at a watershed scale. A long-term experimental watershed in Southwest China was selected to test the new version of the DNDC. The target watershed's 35.1 ha of territory encompass 19.3 ha of croplands, 11.0 ha of forest lands, 1.1 ha of grassplots, and 3.7 ha of residential areas. An input database containing topographic data, meteorological conditions, soil properties, vegetation information, and management applications was established and linked to the enhanced DNDC. Driven by the input database, the DNDC simulated the surface runoff flow, the subsurface leaching flow, the soil erosion, and the N loadings from the target watershed. The modeled water flow, sediment yield, and N loading from the entire watershed were compared with observations from the watershed and yielded encouraging results. The sources of N loading were identified by using the results of the model. In 2008, the modeled runoff-induced loss of total N from the watershed was 904 kg N yr−1, of which approximately 67 % came from the croplands. The enhanced DNDC model also estimated the watershed-scale N losses (1391 kg N yr−1) from the emissions of the N-containing gases (ammonia, nitrous oxide, nitric oxide, and dinitrogen). Ammonia volatilization (1299 kg N yr−1) dominated the gaseous N losses. The study indicated that process-based biogeochemical models such as the DNDC could contribute more effectively to watershed N loading studies if the hydrological components of the models were appropriately enhanced.
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Smith, W. N., B. B. Grant, R. L. Desjardins, P. Rochette, C. F. Drury, and C. Li. "Evaluation of two process-based models to estimate soil N2O emissions in Eastern Canada." Canadian Journal of Soil Science 88, no. 2 (May 1, 2008): 251–60. http://dx.doi.org/10.4141/cjss06030.

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Process-based models play an important role in the estimation of soil N2O emissions from regions with contrasting soil and climatic conditions. A study was performed to evaluate the ability of two process-based models, DAYCENT and DNDC, to estimate N2O emissions, soil nitrate- and ammonium-N levels, as well as soil temperature and water content. The measurement sites included a maize crop fertilized with pig slurry (Quebec) and a wheat-maize-soybean rotation as part of a tillage-fertilizer experiment (Ontario). At the Quebec site, both models accurately simulated soil temperature with an average relative error (ARE) ranging from 0 to 2%. The models underpredicted soil temperature at the Ontario site with ARE from −5 to −7% for DNDC and from −5 to −13% for DAYCENT. Both models underestimated soil water content particularly during the growing season. The DNDC model accurately predicted average seasonal N2O emissions across treatments at both sites whereas the DAYCENT model underpredicted N2O emissions by 32 to 58% for all treatments excluding the fertilizer treatment at the Quebec site. Both models had difficulty in simulating the timing of individual emission events. The hydrology and nitrogen transformation routines need to be improved in both models before further enhancements are made to the trace gas routines. Key words: Nitrous oxide, process-based model, DNDC, greenhouse gas emissions, soil
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Zhang, Wei, Zhisheng Yao, Siqi Li, Xunhua Zheng, Han Zhang, Lei Ma, Kai Wang, et al. "An improved process-oriented hydro-biogeochemical model for simulating dynamic fluxes of methane and nitrous oxide in alpine ecosystems with seasonally frozen soils." Biogeosciences 18, no. 13 (July 14, 2021): 4211–25. http://dx.doi.org/10.5194/bg-18-4211-2021.

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Abstract. The hydro-biogeochemical model Catchment Nutrient Management Model – DeNitrification-DeComposition (CNMM-DNDC) was established to simultaneously quantify ecosystem productivity and losses of nitrogen and carbon at the site or catchment scale. As a process-oriented model, this model is expected to be universally applied to different climate zones, soils, land uses and field management practices. This study is one of many efforts to fulfill such an expectation, which was performed to improve the CNMM-DNDC by incorporating a physically based soil thermal module to simulate the soil thermal regime in the presence of freeze–thaw cycles. The modified model was validated with simultaneous field observations in three typical alpine ecosystems (wetlands, meadows and forests) within a catchment located in seasonally frozen regions of the eastern Tibetan Plateau, including observations of soil profile temperature, topsoil moisture, and fluxes of methane (CH4) and nitrous oxide (N2O). The validation showed that the modified CNMM-DNDC was able to simulate the observed seasonal dynamics and magnitudes of the variables in the three typical alpine ecosystems, with index-of-agreement values of 0.91–1.00, 0.49–0.83, 0.57–0.88 and 0.26–0.47, respectively. Consistent with the emissions determined from the field observations, the simulated aggregate emissions of CH4 and N2O were highest for the wetland among three alpine ecosystems, which were dominated by the CH4 emissions. This study indicates the possibility for utilizing the process-oriented model CNMM-DNDC to predict hydro-biogeochemical processes, as well as related gas emissions, in seasonally frozen regions. As the original CNMM-DNDC was previously validated in some unfrozen regions, the modified CNMM-DNDC could be potentially applied to estimate the emissions of CH4 and N2O from various ecosystems under different climate zones at the site or catchment scale.
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Hutchinson, J. J., B. B. Grant, W. N. Smith, R. L. Desjardins, C. A. Campbell, D. E. Worth, and X. P. Vergé. "Estimates of direct nitrous oxide emissions from Canadian agroecosystems and their uncertainties." Canadian Journal of Soil Science 87, Special Issue (March 1, 2007): 141–52. http://dx.doi.org/10.4141/s06-066.

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Using a revised Intergovernmental Panel on Climate Change (IPCC) methodology and the process-based model DeNitrification and DeComposition (DNDC), we estimated N2O emissions from agroecosystems in Canada for each census year from 1981 to 2001. Based on the IPCC methodology, direct emissions of N2O ranged from 12.9 to 17.3 with an average of 15.1 Tg CO2 equivalents, while the DNDC model predicted values from 16.0 to 24.3 with an average of 20.8 Tg CO2 equivalents over the same period, and showed a large interannual variation reflecting weather variability. On a provincial basis, emissions estimated by IPCC and DNDC methods were highest in Alberta, Saskatchewan and Ontario, intermediate for Manitoba and Quebec and lowest in British Columbia and the Atlantic provinces. The greatest source of emissions estimated by the IPCC method was from N fertilizer (avg. 6.32 Tg CO2 equiv. in Canada), followed by crop residues (4.24), pasture range and paddocks (PRP) (2.77), and manure (1.65). All sources of emissions, but especially those from fertilizers, increased moderately over time. Monte Carlo Simulation was used to determine the uncertainty associated with the 2001 emission estimates for both IPCC and DNDC methodologies. The simulation generated most likely values of 19.2 and 16.0 Tg CO2 equivalents for IPCC and DNDC, respectively, with uncertainties of 37 and 41%, respectively. Values for the IPCC estimates varied between 28% for PRP and manure and 50% for N fertilizer and crop residues. At the provincial level, uncertainty ranged between 15 and 47% with higher values on the prairies. Sensitivity analyses for IPCC estimates showed crop residues as the most important source of uncertainty followed by synthetic N-fertilizers. Our analysis demonstrated that N2O emissions can be effectively estimated by both the DNDC and IPCC methods and that their uncertainties can be effectively estimated by Monte Carlo Simulation. Key words: Nitrous oxide, IPCC, DNDC model, Uncertainty analysis, Monte Carlo Simulation
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Horák, Ján, and Bernard Šiška. "EVALUATION OF N2O EMISSIONS BY DNDC MODEL FOR SANDY LOAM SOILS OF DANUBIAN LOWLAND." JOURNAL OF ENVIRONMENTAL ENGINEERING AND LANDSCAPE MANAGEMENT 14, no. 4 (December 31, 2006): 165–71. http://dx.doi.org/10.3846/16486897.2006.9636894.

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Except for food production the sector of agriculture contribute significantly to emissions of some Greenhouse gases (GHGs), especially N2O. Agricultural practices (especially increase of N consumption in the sector) are now recognized as a major factor influencing increase of N2O emissions into the atmosphere. Estimates of greenhouse gas emissions from the agricultural sector both at a local and regional level are necessary to create possible mitigation strategies with respect to environmental efficiency and economic possibility. We used the DNDC (DeNitrification and DeComposition) model that simulates a full carbon (C) and nitrogen (N) balance, including different C and N pools, and the emissions of all relevant trace gases from soils as NH3, N2O, NO, NO2 and N2. However, for this study only N2O was considered. Intergovernmental Panel on Climate Change (IPCC, 1997) includes methodologies for calculating both direct and indirect emissions of N2O related to agricultural production. Finally, the modeled emissions by DNDC were compared with those estimated according to IPCC methodology at a regional level. The rules of a good practice in GHGs inventory in agriculture were taken into account. The N2O emissions estimated by DNDC model ranged 0,09–0,68 kg N2O‐N/ha yr with an average value of 0,28 kg N2O‐N/ha yr. The N2O emissions estimated according to IPCC methodology ranged 0,46–2,86 kg N2O‐N/ha yr with an average value of 1,66 kg N2O‐N/ha yr. Simulated N2O emissions were lower than the N2O emissions estimated by IPCC methodology (1997). The simulated N2O emissions ranged 0,04–0,51 % of the total N applied to a field as a mineral N‐fertilizer. If DNDC and IPCC emissions are compared in this study, it can be concluded that simulated (DNDC) emissions are in the range of default emission factors (1,25 ±1 %) defined by IPCC methodology (1997), except for 2002.
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Dissertations / Theses on the topic "DNDC model"

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Shahid, Syeda Rubyat. "Simulating changes in soil organic carbon in Bangaladesh with the denitrification-decomposition (DNDC) model." Thesis, McGill University, 2012. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=107848.

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Developed countries' growing awareness of greenhouse gas (CO2, CH4, N2O) emissions from agricultural soils has led to an increased interest in the management of soil organic matter (SOM), which now extends to developing countries, including Bangladesh. Bangladeshi agriculture follows a largely rice-based cropping rotation, for which insufficient site-specific information regarding gas emissions exists to identify temporal variability of SOM content. The objective of this study was to evaluate the applicability of the 'Denitrification-Decomposition' model (DNDC, version 9.3) as a tool to better understand SOC trends in tropical agriculture. DNDC was used to simulate gas emissions from 1948 to 1969 and 1981 to 2007, under farm management practices prevalent in the Dinajpur district of Bangladesh. Forty-nine years of historical daily precipitation and temperature data were used for simulation with DNDC, such that both aerobic and anaerobic conditions were experienced in any given year. A "summer rice - monsoon rice - wheat" cropping pattern was used. As the input parameters of annual precipitation and flooding duration would likely affect DNDC-simulated results, model outputs were categorized on the basis of the magnitude of these parameters. In each categorization scheme the output data were sorted either based on (i) mean, (ii) probability of exceedance, or (iii) standard deviation of annual precipitation or flooding duration. An analysis was then conducted of correlations among input and output variables. Relationships between simulated variables like CO2 emissions, CH4 emissions, and change in SOC content, and input variables such as annual precipitation and flooding duration were generally similar under both of categorization schemes. In high precipitation years changes in SOC content showed a negative correlation (r = 0.90, P ≤ 0.05) with CO2 emissions, and a positive correlation with CH4 emissions (r = 0.85, P ≤ 0.05), highlighting the importance of studying gas emissions as part of the net C balance embedded in DNDC. When categorized according to annual precipitation, CO2 and CH4 emissions were negatively correlated; however, no significant relationship existed when emissions data were categorized on the basis of flooding duration. This discrepancy might arise from the way in which DNDC computes the soil's net C balance. In physical systems, CH4 emissions from paddy fields have an important effect on SOC; however, DNDC calculates CH4 emissions based on available organic C generated by the decomposition sub-model, but the net change in SOC is only balanced according to the CO2 gas emissions calculated by decomposition sub-model. Thus, the CH4 emission calculated by the fermentation sub-model is not included as a loss of SOC in the C balance. The consequence of this in the output data was a steadily increasing SOC associated with the increase in CH4 emissions from the simulated soil system. In order to more accurately model the soil carbon balance in tropical agricultural systems with flooded soils, DNDC should be modified to take into consideration C lost through CH4 emissions in addition to those lost as CO2. DNDC might then be used in sensitivity analysis for different farm management practices under paddy-based cropping systems. Physical experimental analysis is also important for validation of the modelling work. This study showed that DNDC can serve as a rough tool to represent change in the SOC content under Bangladeshi agricultural practices. Some modifications of DNDC, however, would be desirable to make it better suited for future work of this kind.
La plus grande prise de conscience des pays développés quant aux émissions de gaz à effet de serre (CO2, CH4, N2O) provenant de sols agricoles a mené à un intérêt accru pour une gestion durable de la matière organique du sol (MOS). Cet intérêt s'étend maintenant à plusieurs pays en voie de développement, dont le Bangladesh. L'objectif de cette étude fut d'évaluer l'applicabilité du modèle informatique 'Dénitrification-Décomposition' (DNDC, version 9.3) comme outil permettant de mieux comprendre les tendances en MOS dans le contexte de l'agriculture des tropiques. Le DNDC servit à simuler les émissions de gaz à effet de serre de 1948 à 1969 et de 1981 à 2007, selon les modes de gestion agricole prévalent dans le district de Dinajpur, au Bangladesh. Une historique de précipitations et températures quotidiennes de 49 ans servit à alimenter les simulations avec DNDC, de façon à ce que des conditions aérobies et anaérobies aient lieu en toute année donnée. Une rotation de cultures "riz d'été - riz mousson - blé" fut employée. Comme les paramètres d'entrée (précipitation annuelle et durée d'inondations) auraient probablement un effet sur les résultats simulés par DNDC, les variables de sortie furent triées selon l'échelle de chacun des paramètres d'entrée. Pour chaque mode de catégorisation les variables de sortie furent triées selon soit (i) la moyenne, (ii) la probabilité de dépassement, or (iii) et l'écart type de la précipitation annuelle ou de la durée annuelle d'inondations. Une analyse fut ensuite conduite des corrélations entre les variables d'entrée et de sortie. Le type de corrélation existant entre les variables de sortie simulées (émissions de CO2, émissions de CH4, et variation en MOS) et les variables d'entrée (précipitation annuelle, durée d'inondations) fut généralement semblable pour les deux critères de tri. Lors d'années de précipitation élevée la variation en MOS fut inversement corrélée (r = 0.90, P ≤ 0.05) aux émissions de CO2, et directement corrélée aux émissions de CH4 émissions (r = 0.85, P ≤ 0.05), soulignant l'importance qu'il y a d'étudier les émissions de gaz par l'entremise du module de bilan global en C de DNDC. Lorsque trié selon la précipitation annuelle, les émissions de CO2 and CH4 furent inversement corrélées, tandis que lorsque le tri se fit selon la durée des inondations aucune corrélation significative n'apparut. Cette divergence s'avère peut-être le résultat de la façon par laquelle DNDC calcul le bilan en C du sol. Dans le monde réel, les émissions de CH4 provenant de rizières submergées ont un important effet sur la MOS. Cependant, DNDC calcule les émissions de CH4 selon le carbone organique disponible calculé par le module de décomposition, mais le bilan global en MOS n'est ajusté que pour le CO2 émis par le module de décomposition. Ainsi, les émissions de CH4 calculées par le module de fermentation ne sont pas prises en compte comme une perte en MOS dans le bilan de C. Par conséquence les données de sortie indiquèrent une augmentation progressive en MOS, associée à une augmentation en émissions de CH4 provenant du sol simulé. Afin de modeler plus précisément le bilan en C du sol dans les systèmes agricoles des tropiques à sols inondés, DNDC devrait être modifié afin de prendre en compte les pertes en C sous forme d'émissions de CH4 en plus de celles sous forme de CO2. Le DNDC pourrait alors servir à une analyse de sensibilité qui examinerait différentes pratiques de gestion agricole pour les rizières. Une analyse physique d'expériences sur le terrain s'avèrerait utile à une validation des travaux de modélisation. Cette étude démontra que DNDC peut servir d'outil approximatif pour représenter les variations en MOS advenant des pratiques agricoles courantes au Bangladesh. Cependant, il serait souhaitable que certaines modifications soient faites au modèle DNDC, pour qu'il soit mieux adapté à de futures utilisations de ce genre.
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Deng, Jia, Carmody K. McCalley, Steve Frolking, Jeff Chanton, Patrick Crill, Ruth Varner, Gene Tyson, et al. "Adding stable carbon isotopes improves model representation of the role of microbial communities in peatland methane cycling." AMER GEOPHYSICAL UNION, 2017. http://hdl.handle.net/10150/625198.

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Climate change is expected to have significant and uncertain impacts on methane (CH4) emissions from northern peatlands. Biogeochemical models can extrapolate site-specificCH(4) measurements to larger scales and predict responses of CH4 emissions to environmental changes. However, these models include considerable uncertainties and limitations in representing CH4 production, consumption, and transport processes. To improve predictions of CH4 transformations, we incorporated acetate and stable carbon (C) isotopic dynamics associated with CH4 cycling into a biogeochemistry model, DNDC. By including these new features, DNDC explicitly simulates acetate dynamics and the relative contribution of acetotrophic and hydro-genotrophic methanogenesis (AM and HM) to CH4 production, and predicts the C isotopic signature (delta C-13) in soil C pools and emitted gases. When tested against biogeochemical and microbial community observations at two sites in a zone of thawing permafrost in a subarctic peatland in Sweden, the new formulation substantially improved agreement with CH4 production pathways and delta C-13 in emitted CH4 (delta C-13-CH4), a measure of the integrated effects of microbial production and consumption, and of physical transport. We also investigated the sensitivity of simulated delta C-13-CH4 to C isotopic composition of substrates and, to fractionation factors for CH4 production (alpha(AM) and alpha(HM)), CH4 oxidation (alpha(MO)), and plant-mediated CH4 transport (alpha(TP)). The sensitivity analysis indicated that the delta C-13-CH4 is highly sensitive to the factors associated with microbial metabolism (alpha(AM), alpha(HM), and alpha(MO)). The model framework simulating stable C isotopic dynamics provides a robust basis for better constraining and testing microbial mechanisms in predicting CH4 cycling in peatlands.
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FERRE', CHIARA. "Monitoring of greenhouse gas emissions from agricultural and forest soils." Doctoral thesis, Università degli Studi di Milano-Bicocca, 2009. http://hdl.handle.net/10281/7483.

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Global climate change is becoming a central issue in contemporary science as well as politics. There is a long-lasting debate about the cause of the climate change: anthropogenic activity versus the natural cycle. However, a scientific consensus is coming a conclusion that the contemporary climate change is mainly caused by anthropogenic emissions of the greenhouse gases (GHG), including carbon dioxide (CO2), nitrous oxide (N2O) and methane (CH4). The main objective of the thesis is the monitoring of such GHG emissions from two ecosystem types: a forest and a rice paddy ecosystem. The forest site is a EMEP experimental station, taking part of the activity of GHG-AGOLU of FP7-JRC project, while the agricultural ecosystem was included in the CarboEurope project and represents also a Level 3 site in the frame of NitroEurope project. The gas monitoring was carried out in 2008. The thesis is composed by 4 chapters, corresponding to specific objectives. The first chapter is relative to the study of the spatial variability of the main soil chemical and physical properties on the basis of which the gas monitoring points were selected. The second and the third chapters are relative to a cropland site. In particular, the second chapter includes monitoring data of CH4, N2O and CO2 fluxes from the paddy field, both during the crop growth season and the fallow period, and the validation results of the DeNitrification DeComposition (DNDC) model, a process-oriented biogeochemical model used for simulating soil gas emissions from the paddy field, are reported. The third chapter contains the study of characterization of microbial community composition using phospholipid fatty acid analysis (PLFA), at eight sampling dates representative of different soil conditions and crop stages and consequently characterized by distinct soil greenhouse emission rates. The fourth and last chapter includes the monitoring study of soil respiration in a forest site and its partitioning into autotrophic and heterotrophic components, applying the indirect linear regression method.
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Zechel, Jennifer Lynn. "DEADEND1 GENETICS IN MOUSE MODELS OF TESTICULAR GERM CELL TUMOURS AND THEIR METASTASES." Case Western Reserve University School of Graduate Studies / OhioLINK, 2013. http://rave.ohiolink.edu/etdc/view?acc_num=case1372716917.

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Talukdar, Muhammad Bakhtear U. "CFO Turnover, Firm’s Debt-Equity Choice and Information Environment." FIU Digital Commons, 2016. http://digitalcommons.fiu.edu/etd/2618.

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The CEO and CFO are the two key executives of a firm. They work cohesively to ensure the growth of the firm. After the adoption of the Sarbanes Oxley Act (SOX) in 2002, the importance of CFOs has increased due to their personal legal obligation in certifying the accuracy of financial statements. Only a few papers such as Mian (2001), Fee and Hadlock (2004), and Geiger and North (2006) focus on CFOs in the pre-SOX era. However, a vacuum exists in research focusing exclusively on CFOs in the post-SOX era. The purpose of this dissertation is to delve into a comprehensive investigation of the CFOs. More specifically, I answer three questions: a) does the CEO change lead to the CFO change? b) does the CFO appointment type affect the firm’s debt-equity choice? and c) does the CFO appointment affect the firm’s information environment? I use Shumway’s (2001) dynamic hazard model in answering question ‘a’. For question ‘b’, I use instrumental variable (IV) regression under various estimation techniques to control for endogeneity. For part ‘c’, I use the cross sectional difference-in-difference (DND) methodology by pairing treatment firms with control firms chosen by the propensity scores matching (PSM). I find there is about a 70% probability of CFO replacement after the CEO replacement. Both of their replacements are affected by prior year’s poor performance. In addition, as a custodian of the firm’s financial reporting, the CFO is replaced proactively due to a probability of restatement of earnings. I find firms with internal CFO hires issue more equity in the year of appointment than firms with external hires. The promoted CFO significantly improves the firm’s overall governance which helps the firm obtain external financing from equity issue. However, I find that CFO turnover does not significantly affect the firm’s information environment. To ensure that my finding is not due to mixing up of samples of good and distressed firms together, I separated distressed firms and re-ran my models and my finding still holds. This dissertation fills the gap in the literature with regards to CFOs and their post SOX relationship with the firm.
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Kröbel, Roland [Verfasser]. "Validation and evaluation of the DNDC model to simulate soil water content, mineral N and N2O emission in the North China Plain / presented by Roland Kröbel." 2009. http://d-nb.info/999417959/34.

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Ayala, Alcántara Alejandro. "Propuesta del modelo DNC como herramienta de la consultoría empresarial aplicado a la empresa BONAFONT." Tesis de Licenciatura, 2017. http://hdl.handle.net/20.500.11799/99211.

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La presente investigación permitirá al lector entender, dentro del ámbito administrativo, cuál es la función de un consultor en una empresa, también podrá apreciar la importancia que requiere elaborar diagnósticos empresariales de manera constante y así mismo recibir consejos o asesorías de un consultor. El objetivo fundamental de la investigación es aportar conocimiento sobre el tema de la consultoría, en específico hablar acerca del modelo DNC, el cual es una herramienta sumamente útil para identificar áreas débiles en una empresa. Una de las principales problemáticas que presenta una PyME en México de manera constante, es el carente dominio o conocimiento que tiene el gerente sobre su propia empresa; es por ello que una consultoría es una verdadera alternativa, tomando en cuenta que puede proporcionar conocimiento valioso el cual ayude al gerente a resolver una contingencia que el mismo desconoce. La consultoría profesional es proporcionar recomendaciones viables y a su vez implantar medidas apropiadas para aumentar la productividad y la competitividad de las empresas. Palabras clave: Consultoría, empresa, administración, diagnostico, modelo, consultor, productividad, competitividad.
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Book chapters on the topic "DNDC model"

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Li, Changsheng. "The DNDC Model." In Evaluation of Soil Organic Matter Models, 263–67. Berlin, Heidelberg: Springer Berlin Heidelberg, 1996. http://dx.doi.org/10.1007/978-3-642-61094-3_20.

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Jiang, Lihua, Wensheng Wang, Xiaorong Yang, Nengfu Xie, and Youping Cheng. "An Agricultural Tri-dimensional Pollution Data Management Platform Based on DNDC Model." In Computer and Computing Technologies in Agriculture IV, 149–54. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-18333-1_20.

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Grant, Brian B., Ward N. Smith, Con A. Campbell, Raymond L. Desjardins, Reynald L. Lemke, Roland Kröbel, Brian G. McConkey, Elwin G. Smith, and Guy P. Lafond. "Comparison of DayCent and DNDC Models: Case Studies Using Data from Long-Term Experiments on the Canadian Prairies." In Synthesis and Modeling of Greenhouse Gas Emissions and Carbon Storage in Agricultural and Forest Systems to Guide Mitigation and Adaptation, 21–57. Madison, WI, USA: American Society of Agronomy and Soil Science Society of America, 2015. http://dx.doi.org/10.2134/advagricsystmodel6.2013.0035.

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Sun, Y. Y., J. W. Wang, and G. J. Hong. "Application of the DNDC model in simulating nitrate leaching due to irrigation and precipitation." In Hydraulic Engineering V, 137–44. CRC Press, 2017. http://dx.doi.org/10.1201/9781351241571-20.

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Nagata, F., T. Yamashiro, N. Kitahara, A. Otsuka, K. Watanabe, and Maki K. Habib. "Self Control and Server-Supervisory Control for Multiple Mobile Robots, and its Applicability to Intelligent DNC System." In Computational Methods for Optimizing Manufacturing Technology, 67–84. IGI Global, 2012. http://dx.doi.org/10.4018/978-1-4666-0128-4.ch003.

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Multiple mobile robots with six PSD (Position Sensitive Detector) sensors are designed for experimentally evaluating the performance of two control systems. They are self-control mode and server-supervisory control mode. The control systems are considered to realize swarm behaviors such as Ligia exotica. This is done by using only information of PSD sensors. Experimental results show basic but important behaviors for multiple mobile robots. They are following, avoidance, and schooling behaviors. The collective behaviors such as following, avoidance, and schooling emerge from the local interactions among the robots and/or between the robots and the environment. The objective of the study is to design an actual system for multiple mobile robots, to systematically simulate the behaviors of various creatures who form groups such as a school of fish or a swarm of insect. Further, the applicability of the server-supervisory control scheme to an intelligent DNC (Direct Numerical Control) system is briefly considered for future development. DNC system is an important peripheral apparatus, which can directly control NC machine tools. However, conventional DNC systems can neither deal with various information transmitted from different kinds of sensors through wireless communication nor output suitable G-codes by analyzing the sensors information in real time. The intelligent DNC system proposed at the end of the chapter aims to realize such a novel and flexible function with low cost.
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Conference papers on the topic "DNDC model"

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"Simulating CO2 Emissions from Tropical Forest Soils by Denitrification-Nitrification Decomposition (DNDC) Model." In April 17-18, 2018 Kyoto (Japan). International Institute of Chemical, Biological and Environmental Engineering, 2018. http://dx.doi.org/10.17758/iicbe1.c0418131.

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Wang, Deying, Yanmin Yao, Haiqing Si, Wenju Zhang, and Huajun Tang. "Simulation and prediction of soil organic carbon spatial change in arable lands based on DNDC model." In 2014 Third International Conference on Agro-Geoinformatics. IEEE, 2014. http://dx.doi.org/10.1109/agro-geoinformatics.2014.6910583.

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Huang, Xianlei, Biao Tang, Xu Xia, and Hailin Zhang. "Evaluation of Soil Carbon Sequestration Potential under Conservation Tillage in Double Rice Cropping Region with DNDC Model." In 2012 2nd International Conference on Remote Sensing, Environment and Transportation Engineering (RSETE). IEEE, 2012. http://dx.doi.org/10.1109/rsete.2012.6260567.

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Smith, Ward N., Zhiming Qi, Brian B. Grant, Wentian He, Andrew VanderZaag, Craig F. Drury, Chin S. Tan, and Matthew Helmers. "<i>Towards improving the DNDC model for simulating soil hydrology and tile drainage</i>." In 2019 Boston, Massachusetts July 7- July 10, 2019. St. Joseph, MI: American Society of Agricultural and Biological Engineers, 2019. http://dx.doi.org/10.13031/aim.201901842.

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Chen, Maosi, Xiangyi Wang, Zhan Tian, Yilong Niu, Dongli Fan, Hanqing Xu, Biao Hu, Runhe Shi, and Meifang Hou. "Simulation of methane emissions from double-rice cropping system in Southern China during the past 50 years by DNDC model." In Remote Sensing and Modeling of Ecosystems for Sustainability XV, edited by Wei Gao, Ni-Bin Chang, and Jinnian Wang. SPIE, 2018. http://dx.doi.org/10.1117/12.2320158.

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Zhan Tian, Zhuoran Liang, Yilong Niu, Changsheng Li, Xueming Tu, and DongLi Fan. "Simulation of the methane emission in rice fields in China during the past 40 years by DNDC model and GIS technical." In 2014 Third International Conference on Agro-Geoinformatics. IEEE, 2014. http://dx.doi.org/10.1109/agro-geoinformatics.2014.6910624.

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Jiang, Qianjing, Zhiming Qi, Chandra A. Madramootoo, Ward Smith, Naeem A. Abbasi, and Tie-Quan Zhang. "<i>Comparison of RZWQM2 and DNDC model in simulating greenhouse gas emission, crop yield and subsurface drainage</i>." In 2018 Detroit, Michigan July 29 - August 1, 2018. St. Joseph, MI: American Society of Agricultural and Biological Engineers, 2018. http://dx.doi.org/10.13031/aim.201801588.

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Liu, Kaicheng, and Jianjun Wang. "Double Nodal Diameter Spectrum Method and its Application in Quantification of Vibration Localization of Impellers With Splitter Blades." In ASME Turbo Expo 2017: Turbomachinery Technical Conference and Exposition. American Society of Mechanical Engineers, 2017. http://dx.doi.org/10.1115/gt2017-63972.

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Double nodal diameter spectrum (DNDS) method which is used to analyze nodal diameter (ND) components of the vibration modes of impellers with splitters is proposed and its application in quantification of mode localization has been studied. Firstly, ND characteristics of the typical impeller with splitter blades are analyzed by mode shapes and representative subeigenvectors. Secondly, DNDS method is proposed and DNDSs of the representative modes indicate that the tuned modes of impellers with splitter blades contain two ND components. By applying the simplified engine order (EO) excitation in the form of a travelling wave, harmonic response analysis has been carried out by which double nodal diameter vibration characteristics of the structure and the effectiveness of the DNDS method are both validated. Lastly, in terms of quantifying mode localization, the definition of mode localization factor (MLF) is improved based on DNDS. The numerical example proves that the pairing process of choosing the tuned mode corresponding to the mistuned one by utilizing both DNDS and the vibration pattern of blades when calculating the improved MLF could pick out the closest tuned mode to the mistuned one, which has a more explicit physical meaning.
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Jia, Ying, Lei Huang, and Jin Yan. "Impact of Field Development Strategies on CO2 Trapping Mechanisms: A Case Study of CO2-EGR in the DND Tight Gas Field." In SPE EuropEC - Europe Energy Conference featured at the 83rd EAGE Annual Conference & Exhibition. SPE, 2022. http://dx.doi.org/10.2118/209718-ms.

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Abstract This paper presents field-scale compositional reservoir flow modeling in the DND tight gas field, to demonstrate the relative partitioning of 3 during and after CO2 injection. The model was developed to study the effect of structural trapping, solubility trapping, residual trapping, and mineralization trapping on the partitioning of CO2 in gas (free or residual), and brine phases over time. Furthermore, we investigated the impact of various injection scenarios, such as Injection pressure, Injection rate and Injection time, on the different trapping mechanisms. First, we used a high-resolution geo-model, which was constructed from wireline logs, seismic surveys, core data, and stratigraphic interpretation. As the initial distribution of fluids plays a vital role in CO2 partitioning, a comprehensive pressure-production history matching was completed. The hysteresis model was used to calculate the amount of CO2 trapped as residual. The water-rock reaction models among CO2 and minerals were added to analyze the mineralization trapping mechanism. CO2 solubility into brine was verified based on experiments. The model results show a new understanding of relative CO2 partitioning in porous media. Although it was believed that structural trapping is the largest of the trapping mechanisms during CO2 injection and post-injection, our results show that in sandstone tight gas field like DND tight gas field, the solubility of CO2 in gas plays a very important role, even in the first stage of CO2 injection. Porosity changes caused by the reaction among CO2 and different minerals during CO2 storage were also analyzed. Comprehensive models were run to estimate the amount of trapped CO2 during and after the injection period. The present work provides valuable insights for optimizing gas production and CO2 storage in sandstone reservoirs like DND tight gas field.
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Jia, Ying, Lei Huang, and Jin Yan. "Impact of Field Development Strategies on CO2 Trapping Mechanisms: A Case Study of CO2-EGR in the DND Tight Gas Field." In SPE EuropEC - Europe Energy Conference featured at the 83rd EAGE Annual Conference & Exhibition. SPE, 2022. http://dx.doi.org/10.2118/209718-ms.

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Abstract This paper presents field-scale compositional reservoir flow modeling in the DND tight gas field, to demonstrate the relative partitioning of 3 during and after CO2 injection. The model was developed to study the effect of structural trapping, solubility trapping, residual trapping, and mineralization trapping on the partitioning of CO2 in gas (free or residual), and brine phases over time. Furthermore, we investigated the impact of various injection scenarios, such as Injection pressure, Injection rate and Injection time, on the different trapping mechanisms. First, we used a high-resolution geo-model, which was constructed from wireline logs, seismic surveys, core data, and stratigraphic interpretation. As the initial distribution of fluids plays a vital role in CO2 partitioning, a comprehensive pressure-production history matching was completed. The hysteresis model was used to calculate the amount of CO2 trapped as residual. The water-rock reaction models among CO2 and minerals were added to analyze the mineralization trapping mechanism. CO2 solubility into brine was verified based on experiments. The model results show a new understanding of relative CO2 partitioning in porous media. Although it was believed that structural trapping is the largest of the trapping mechanisms during CO2 injection and post-injection, our results show that in sandstone tight gas field like DND tight gas field, the solubility of CO2 in gas plays a very important role, even in the first stage of CO2 injection. Porosity changes caused by the reaction among CO2 and different minerals during CO2 storage were also analyzed. Comprehensive models were run to estimate the amount of trapped CO2 during and after the injection period. The present work provides valuable insights for optimizing gas production and CO2 storage in sandstone reservoirs like DND tight gas field.
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Reports on the topic "DNDC model"

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West, M. Technical Review Report for the Model 9977 Safety Analysis Report for Packaging Addendum 1 Justification for DNDO Contents. Office of Scientific and Technical Information (OSTI), December 2008. http://dx.doi.org/10.2172/951668.

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