Modeling a long-term effect of rice straw incorporation on SOC content and grain yield in rice field

ABSTRACT

The long-term effects of rice straw incorporation on soil organic carbon (SOC) content and rice yield were evaluated from rice cultivation with different treatments: no rice straw (control), rice straw (RS), and rice straw compost (RSC) as a main-plots; five levels of nitrogen (N) fertilizer application: 0, 100, 150, 200, and 250 of N (kg ha^?1) as a sub-plots. The denitrification and decomposition (DNDC) model was employed to simulate changes in SOC content and rice grain yield over 35 years. Additionally, scenario analysis on continuous or discontinuous RS incorporation in rice fields was conducted using the DNDC model. The long-term results indicated that RS and RSC treatments played a crucial role in increasing grain yields by 9% and 11% due to the increased SOC contents compared to control treatment. The validated DNDC model on SOC contents and yields showed a good agreement between the observed and simulated values based on the normalized root mean square errors. The model predicted a rapid decline of SOC contents without RS incorporation. Results suggested that incorporating rice straw or amending manure to paddy soils is a preferred practice for maintaining SOC contents.     

不同气候-土壤-耕作组合条件下水稻土有机碳长期演变模拟的不确定性和敏感性分析

Reporting modeling results with uncertainty information can benefit decision making by decreasing the extent that variability exerts a disproportionate influence on the options selected. For making decisions with more confidence, the uncertainty interval should be as narrow as possible. Here, the soil organic carbon(SOC) dynamics of the major paddy soil subgroup from 4 different paddy field regions of China(located in 4 counties under different climate-soil-management combinations) were modeled using the De NitrificationDe Composition(DNDC) model for the period from 1980 to 2008. Uncertainty intervals associated with the SOC dynamics for these 4 subgroups were estimated by a long-term global sensitivity and uncertainty analysis(i.e., the Sobol′method), and their sensitivities to 7 influential factors were quantified using the total effect sensitivity index. The results, modeled with high confidence, indicated that in the past 29 years, the studied paddy soils in Xinxing, Yixing, and Zhongjiang counties were carbon(C) sinks, while the paddy soil in Helong County was a C source. The 3 C sinks sequestered 12.2(5.4, 19.6), 17.1(8.9, 25.0), and 16.9(-1.2, 33.6) t C ha~(-1)(values in the parentheses are the 5th and 95th percentiles, respectively). Conversely, the C source had a loss of -5.4(-14.2, 0.06) t C ha~(-1) in the past 29 years. The 7 factors, which changed with the climate-soil-management context, exhibited variable influences on modeled SOC. Measures with potential to conserve or sequestrate more C into paddy soils, such as incorporating more crop residues into soils and reducing chemical fertilizer application rates, were recommended for specific soils based on the sensitivity analysis results.     

应用DNDC模型分析东北黑土有机碳演变规律及其与作物产量之间的协同关系

【目的】探索长期不同施肥方式下土壤有机碳的动态变化及其与作物产量之间的耦合关系,以期为东北地区黑土耕地资源的持续利用与管理提供科学依据。 【方法】基于黑土区国家土壤肥力与肥料效益监测网站公主岭监测基地的23年长期定位试验数据,选取不施肥（CK）、单施氮磷钾肥（NPK）、无机肥配施低量有机肥（NPKM1）、1.5倍的无机肥配施低量有机肥[1.5（NPK）M1]、无机肥配施高量有机肥（NPKM2）和无机肥配施秸秆（NPKS）6个处理进行土壤有机碳和产量的分析,将数据用于DNDC模型验证,并对6种施肥处理在未来气候下（40 a）黑土有机碳的演变进行模拟。 【结果】试验监测结果表明:从1990~2012年的土壤有机碳数据分析得出,长期不施肥土壤有机碳从12.49 g/kg以年均0.69%的速率下降,有机无机配施可以提升土壤有机碳含量。DNDC验证结果如下:DNDC验证土壤有机碳时各处理的相对均方根误差（RMSE）为14.98%~37.91%,验证作物产量时各处理的RMSE为8.28%~11.19%,说明模型能够基本反映长期不同施肥下的作物产量和土壤有机碳的变化。未来气候下的模拟结果表明:CK和NPK处理土壤有机碳在未来40年里分别下降16.67%和11.21%。而3个化肥有机肥配施处理在未来40年呈稳定增长态势,NPKM1、1.5（NPK）M1和NPKM2处理的土壤有机碳将分别增加13.65%、15.74%和15.84%,以1.5（NPK）M1增势最为显著。NPKS处理的有机碳相对初始略有增加。当施氮量从160 kg/hm2增至320 kg/hm2时,土壤有机碳每增加1.00 g/kg,作物产量的增加量从44.48 kg/hm2下降至15.95 kg/hm2。 【结论】从长期实测数据的分析和DNDC模型模拟得出,实施秸秆还田和有机肥配施无机肥能有效持续增加SOC含量,并能获得较高的作物产量。在施氮量160~320 kg/hm2水平下,作物产量随着土壤有机碳含量的增加而升高,且土壤有机碳含量对产量的提升幅度随着施氮量的升高而降低。     

黑土有机碳变化的DNDC模拟预测

为探讨黑土有机碳的长期变化规律及DNDC模型在土壤有机碳预测方面的适用性,本文利用吉林省公主岭地区黑土不同施肥措施下的长期定位试验数据,选取不施肥(CK)、单施化肥(NPK)、配施有机肥(NPKM)和增施有机肥(M2+NPK)4个处理进行土壤有机碳分析,并将数据用作DNDC模型验证。验证结果表明:各处理DNDC验证中RMSE值均小于10%(分别为5.09%、6.11%、9.38%、8.36%),说明模拟值与观测值一致性良好,模型可用于该地区土壤有机碳模拟。选取了化肥施用、有机肥施用、秸秆还田比率、温度及降水5个因子进行模型的敏感性分析,结果表明:有机肥的施用对土壤有机碳含量的影响最显著,且这种影响具有持久性。最后模拟了4种施肥情境下未来(至2100年)的土壤有机碳变化情况。结果表明:对照不施肥处理(CK)土壤有机碳含量略有下降,至2100年土壤有机碳含量为11.55 g·kg-1,较试验前土壤初始有机碳(13.2 g·kg-1)下降约12.5%。单施化肥处理(NPK)土壤有机碳含量较为稳定,并未出现土壤有机碳含量下降。配施有机肥(NPKM)和增施有机肥(M2+NPK)处理土壤有机碳含量增加明显,至2100年土壤有机碳含量为24.4 g·kg-1和27.6 g·kg-1,分别较初始有机碳含量上升84.8%和109.1%。     

基于贝叶斯推断的DNDC模型参数校正与不确定性评价研究

实现土壤有机碳(SOC)动态模拟结果的不确定性定量评价是农田管理决策成败的关键之一。采用贝叶斯推断和马尔科夫链蒙特卡洛方法(MCMC),对DNDC模型模拟江苏省宜兴市一个具有22年稻-麦轮作历史的田块的SOC动态变化,进行模型参数校正和模拟结果的不确定性定量评价。结果表明,DNDC模型适宜长期监测田块的SOC动态变化的模拟,但模型的模拟结果存在一定的不确定性;在DNDC模型输入参数数据质量不明的情况下,利用贝叶斯推断和MCMC方法能够有效地实现模型输入参数的自动校正和SOC模拟结果不确定性的定量评价,从而为实现区域或国家尺度农田SOC动态模拟的不确定性定量评价提供理论和方法依据。     

长期施肥下石灰性潮土有机碳变化的DNDC模型预测

为探讨长期不同施肥条件下土壤有机碳的变化规律及DNDC模型的应用,利用封丘石灰性潮土不同施肥措施下的长期定位试验数据,选取CK、NPK、1/2NPK+1/2OM、OM4个处理,分析了15年来作物产量及土壤有机碳(SOC)的变化特征,并用DNDC模型预测了试验地近100年(2000~2099)的SOC变化趋势。结果表明,各施肥处理的多年产量平均值和对照处理差异显著;施用化肥(NPK和1/2NPK+1/2OM)处理和有机肥(OM)处理间也有显著差异;产量最高为NPK处理,达10811 kg/ha,CK处理最低,但1/2NPK+1/2OM处理产量与NPK处理无显著性差异。15年来土壤耕层(0—20cm)有机碳平均值,以OM处理最高,达到7.90 g/kg,显著高于1/2NPK+1/2OM、NPK处理;而CK处理仅为4.15 g/kg。从15年来有机碳的变化看出,CK处理略有下降,NPK处理较为平稳,而1/2NPK+1/2OM和OM处理呈现不断上升趋势,OM处理上升幅度较1/2NPK+1/2OM处理大。对试验地SOC变化趋势长期(100a)的模拟结果显示,与初始土壤SOC含量相比,100a后不施肥处理(CK)土壤有机碳含量下降了52%,化肥(NPK)处理土壤SOC含量较为稳定,而1/2NPK+1/2OM处理和OM处理土壤有机碳增加明显,大约25a后基本上稳定,100a后分别较2000年增加了24%和25%。从实测数据的分析和DNDC模型模拟分析可以看出,有机肥和化肥配施能获得较高作物产量,并能有效地增加土壤SOC含量,从而提高土壤的可持续利用能力。     

县域尺度红壤丘陵区水稻土有机碳模拟

区域尺度土壤有机碳储量的时空变化及其管理是全球气候变化和农业可持续发展研究的重要内容。本文以中亚热带红壤丘陵区的江西省余江县为例,基于12a的长期试验和1998年、2001年的野外定位采样对比研究,利用反硝化分解模型?DNDC(Denitrification-Decomposition)在田块和县域尺度研究了县域尺度表层(0~20 cm)水稻土有机碳储量的时空变化规律。结果表明,以长期试验数据验证,DNDC模型可以较好地模拟水稻土表层有机碳的长期动态变化。2001年农田水稻土(面积为3.6×108m2)表层(0~20 cm)有机碳总储量为2.9×109kg,平均土壤有机碳密度为6.0 kg m-2。1998年至2001年余江县水稻土表层土壤有机碳库逐年增加,年际平均变化量为3.0×107kg。通过对余江县水稻田模拟不同碳投入的情景,分析预测1998年至2017年土壤有机碳储量,种植绿肥提高秸秆还田比率同时减少化肥的投入,可有效地增加红壤区域有机碳蓄积。     

有机物料碳和土壤有机碳对水稻土甲烷排放的影响

基于30年水稻土长期施肥定位试验,在保证原有定位试验正常开展的前提下,将部分化肥处理变更为有机肥处理(或反之),通过观测一年水稻轮作周期内不同处理甲烷(CH_4)排放通量季节性变化,探讨不同肥力水稻土中外源有机碳及土壤有机碳含量对田间CH_4排放的影响。结果表明:施化肥处理和有机肥处理,水稻土全年CH_4累积排放量范围分别为1.73~4.72和35.09~86.60 g·m~(-2)。有机肥处理改施化肥后,田间土壤CH_4的排放量显著降低;化肥处理改施有机肥或有机肥处理增施有机肥后,田间土壤CH_4的排放量显著提高。外源有机碳的输入量是田间土壤CH_4年排放量的决定性因素,外源有机碳输入量(x)与水稻土CH_4年累积排放量(y)之间满足直线方程:y=0.087 7 x+3.265 7(R~2=0.965 9,n=21)。土壤有机碳同样也是影响稻田CH_4排放的因素,在不同有机碳水平的水稻土上施用等量相同化肥或有机肥,土壤有机碳含量高的水稻土都更有利于CH_4的产生。单施化肥稻田土壤CH_4排放的最主要碳源是土壤有机碳,有机碳含量(x)和水稻土CH_4年累积排放量(y)之间的指数方程:y=0.162 4 e~(0.162 2 x)(R~2=0.940 6,n=9)。有机肥可促进土壤有机碳分解释放CH_4,土壤有机碳含量相同的条件下,高量有机肥比常量有机肥的土壤有机碳分解比率高0.65%,等量相同有机肥但土壤有机碳含量不同的条件下,土壤有机碳分解比率无显著差异;同样,土壤有机碳也可促进有机物料碳分解释放CH_4,在常量有机肥或高量有机肥处理中,土壤有机碳含量高者比低者的有机物料碳分解比率分别多出3.57%和2.34%。     

Application of the DNDC model to predict N2O emissions from sandy arable soils with differing fertilization in a long‐term experiment

Modeling crop growth and soil N dynamics is difficult due to the complex nature of soil–plant systems. In several studies, the DNDC model has been claimed to be well‐suited for this purpose whereas in other studies applications of the model were less successful. Objectives of this study were to test a calibration and validation scheme for DNDC‐model applications to describe a field experiment with spring wheat on a sandy soil near Darmstadt (SW Germany) using different fertilizer types (either application of mineral fertilizer and straw—MSI; or application of farmyard manure—FYM) and rates (low—MSI_L, FYM_L; and medium—MSI_M, FYM_M). The model test is based on a model parameterization to best describe the case MSI_L and applies this parameterization for a retrospective simulation of the other cases (MSI_M, FYM_L, FYM_M) including crop growth and N₂O emissions. Soil water contents were not accurately simulated using either the DNDC default values for a loamy sand or for the next finer texture class or using results from the pedotransfer function provided by ROSETTA. After successful calibration of the soil water flow model using a soil texture class that led to the best fit of the measured water content data, grain yield of spring wheat and cumulative N₂O emission were slightly underestimated by DNDC and were between 91% and 86% of the measured data. A subsequent calibration of the yields and cumulative N₂O emissions from soils of the MSI_L treatment gave a good prediction of crop growth and N₂O emissions in the MSI_M treatment, but a marked underestimation of yields of the FYM treatments. Cumulative N₂O emissions were predicted well for all MSI and FYM treatments, but seasonal dynamics were not. Overall, our results indicated that for the sandy soil in Germany, site‐specific calibration was essentially required for the soil hydrology and that a calibration was useful for a subsequent prediction where greater amounts of the same fertilizer were used, but not useful for a prediction with a different fertilizer type.     

Regional simulation of long-term organic carbon stock changes in cropland soils using the DNDC model: 1. Large-scale model validation against a spatially explicit data set

Because of the large spatial and temporal variability of soil organic carbon (SOC) dynamics, a modelling approach is crucial in detailed regional analyses. Several estimates of regional scale SOC sequestration potential have been made using dynamic soil organic matter (SOM) models which have been linked to spatial databases contained within a Geographic Information System. In all these previous studies, a large‐scale model validation, which provides information on the general model performance for the study area under concern, was impossible because of lack of data. A data set of over 190 000 SOC measurements, grouped as means per community and covering the period 1989–2000 was available for Flanders in northern Belgium. In order to validate the DNDC model at a large spatial scale, we used this data set along with detailed pH, soil texture and crop areas which were all available at the municipality scale to simulate SOC stocks for the entire study area during the period 1990–2000. A minor adjustment of the initial distribution of SOC in the model's SOC pool was necessary to fit the simulated SOC stock changes to the measured decrease of −475 kg OC ha⁻¹ year⁻¹ (0–30 cm). Although DNDC was able to simulate the SOC stock changes well for the whole study area, the simulated decrease in the SOC stocks was overestimated for communities predominantly having sandy textures and underestimated for communities with silt loam to silt textures. This study also urges caution with the application of SOM models at regional scales after limited validation or calibration at the field scale as these do not guarantee good simulation of spatial variation in SOC changes.     

农业利用方式对土壤有机碳库大小及周转的影响研究

通过土壤样品的室内培养,运用三库一级动力学理论,以丘陵区红壤为对象,研究了水田、桔园、旱地、水旱轮作4种土地利用方式农田土壤有机碳库大小、各碳库平均周转时间及分解动态,探讨了土地利用变化对土壤有机碳的影响.结果表明,土壤有机碳分快速分解和缓慢分解两个阶段.快速分解阶段的分解速率与活性碳含量和活性碳占有机碳的百分含量相关性不明显;缓慢分解阶段的速率与缓性碳库含量呈正相关.4种土地利用类型表层和中层土壤总有机碳含量分别为4.97～12.40 g/kg,2.58～4.00 g/kg;缓性碳库表层含量的大小顺序为,水田(5.78 g/kg)>旱地(3.77 g/kg)>桔园(3.39 g/kg)>水旱轮作(2.83 g/kg)I惰性碳库表层含量的大小顺序与缓性碳相同,含量分别为6.42,5.43,2.45,2.03 g/kg,水田的缓、惰性碳库含量最高,水田更具有固碳潜力.     

中国农田表土有机碳含量变化特征——基于国家耕地土壤监测数据

通过对299个国家级耕地土壤监测点20余年数据的统计分析,评价了我国农田表土有机碳含量变化情况和固碳潜力。结果表明,全国约80％试验点有机碳年平均相对增长率（Average relative annual increment,ARAI）在-1．5％～7．5％。中国农田表土有机碳含量整体呈上升趋势。东北、华北等6个地理区域分析得出,华北、华东、西南农田表土有机碳含量显著增加;华东地区有机碳增加的农田面积占全国农田比例最大,东北最小。旱地和水田有机碳含量增加显著;水田有机碳增加的试验点所占比例大于旱地;对ARAI与初始有机碳含量进行相关分析得出,我国旱地和水田有机碳潜在储存能力估计值分别为17．2和27．7g·kg^-1。农田土壤类型中水稻土和褐土有机碳含量增加显著;黑土有机碳含量下降样本所占比例最高。对我国各典型种植制度分析得出,双季稻、麦-稻、麦-玉、单季小麦种植制度下农田有机碳有了显著增加;麦玉轮作较其他种植制度的农田有机碳年平均相对增长率高。     

The relative impact of land use and soil properties on sizes and turnover rates of soil organic carbon pools in Subtropical China

The dynamics of soil organic carbon (SOC) pools determine potential carbon sequestration and soil nutrient improvement. This study investigated the characteristics of SOC pools in five types of cultivated topsoils (0–15 cm) in subtropical China using laboratory incubation experiments under aerobic conditions. The sizes and turnover rates of the active, slow and resistant C pools were simulated using a first‐order kinetic model. The relative influence of soil environmental properties on the dynamics of different SOC pools was evaluated by applying principal component analysis (PCA) and aggregated boosted trees (ABTs) analysis. The results show that there were significantly greater sizes of different SOC pools and lower turnover rates of slow C pool in two types of paddy soils than in upland soils. Land use exerted the most significant influence on the sizes of all SOC pools, followed by clay content and soil pH. The soil C/N ratio and pH were the major determinants for turnover rates of the active and slow C pools, followed by clay content which had more impact on the turnover rates of the active C pool than the slow C pool. It is concluded that soil type exerts a significant impact on the dynamics of SOC.     

长期施用化肥对我国南方水田表土有机碳含量的影响

利用meta分析研究水田土地利用方式下化肥对土壤有机碳含量的影响。结果显示:长期施用化肥处理的表层水稻土土壤有机碳含量较不施肥处理显著提高1.00±0.23 g kg-1,是不施肥处理的1.06倍±1.01倍。分析认为施肥处理下,较高的根系生物量导致较高的碳输入水平,另外相对充足的养分供应提高土壤固碳效率,这是施肥处理下土壤具有较高有机碳含量的两个原因。但不同轮作制度下,化肥对有机碳含量提升作用有差异:稻-稻-旱轮作制下化肥的作用不显著,而稻-旱轮作与稻-稻轮作制度下化肥对有机碳含量的提升作用显著。方差分析发现相同施肥措施下,稻-稻-旱轮作体系下土壤有机碳含量在三种轮作制度中最高,而稻-旱轮作与稻-稻轮作没有显著差异。尽管施用化肥能增加土壤有机碳含量,但评价施用化肥对温室效应的影响还需要综合考虑化肥生产、运输与施用过程中的温室气体排放三要素。     

Carbon sequestration potential of recommended management practices for paddy soils of China, 1980-2050

China's rice paddies, accounting for 19% of the world's total, play an important role in soil carbon (C) sequestration. In order to reduce uncertainties from upscaling spatial processes of the DeNitrification-DeComposition (DNDC) model for improving the understanding of C sequestration under recommended management practices (RMPs), we parameterized the DNDC model with a 1:1,000,000 polygonal soil database to estimate how RMPs influence potential C sequestration of the top 30 cm of Chinese paddy soils and to identify which management practices have the greatest potential to increase soil organic carbon (SOC) in these soils. These practices include reduced/no tillage, increasing crop residue return, and increasing manure applications. A baseline and eleven RMP scenarios were projected from 2009 to 2080, including traditional and conservation tillage, increasing crop residue return, increasing manure incorporation, and the combination of these practices. The results indicated that C sequestration potential under modeled RMPs increased compared to the baseline scenario, and varied greatly from 29.2 to 847.7 Tg C towards the end of the study period with an average rate of 0.7 to 20.2 Tg C yr^− 1. In general, increasing crop residue return was associated with higher rates of C sequestration when compared to increasing manure application or practicing conservation tillage. The simulations demonstrated that the most effective soil C sequestration strategy probably involves the implementation of a combination of RMPs, and that they vary by location.     

Modeling Soil Organic Carbon with DNDC and RothC Models in Different Wheat-Based Cropping Systems in North-Western India

ABSTRACT

The performance of DNDC (DeNitrification-DeComposition) and RothC (Rothamsted Carbon model) in simulating soil organic carbon (SOC) storage in soils under rice (Oryza sativa L.) – wheat (Triticum aestivum L.), maize (Zea mays L.) – wheat and cotton (Gossypium hirsutum L.) – wheat cropping systems was evaluated on field and regional scale. Field experiments consisted of N, NP, NK, PK, NPK, FYM, N + FYM, NPK + FYM, and control (UF) treatments. DNDC and RothC over-estimated SOC storage by 0.35–1.16 Mg C ha^?1 (6–21%) in surface layer with manure application, compared with inorganic fertilizer treatments by 1.01–1.16 Mg C ha^?1 (14–18%). Although RothC only slightly over-estimated SOC stocks, DNDC provided a better match for measured versus simulated SOC stocks (R ² = 0.783*, DNDC; 0.669*, RothC, p < .05). Model validation on independent datasets from long-term studies on rice–wheat (R ² = 0.935**, DNDC; R ² = 0.920**, RothC, p < .01) and maize–wheat (R ² = 0.895** for DNDC and R ² = 0.967** for RothC, p < .01) systems showed excellent agreement between measured and simulated SOC stocks. On a regional scale, change in SOC storage under Scenario 1 (NPK) was significant up to 8 years of simulation, with no change thereafter. In Scenario 2 (NPK + FYM), DNDC simulated SOC storage after 10 years was 2.0, 0.4, and 1.4 Mg C ha^?1 in three systems, respectively. Amount of C sequestered in silt + clay fraction varied between 0.31 and 0.97 kg C 10 years^?1 (Mg silt + clay)^?1 under Scenario 1, and between 0.78 and 2.67 kg C 10 years^?1 (Mg silt + clay)^?1 under Scenario 2.     

典型潮土N2O排放的DNDC模型田间验证研究

利用典型潮土N2O排放的田间试验数据对脱氮-分解模型（DNDC）及其参数进行验证。结果表明,DNDC模型能较好地模拟田间实测到的冬小麦、夏玉米季土壤湿度和土壤日平均地表温度的动态变化。小麦和玉米季土壤N2O排放通量与土壤水分（WFPS）呈显著正相关,与土壤温度相关性不大。田间实测到的N2O排放高峰主要受降水和施肥的影响,在N2O排放峰的峰值和出现时间上模拟值与实测值较接近,但准确地捕捉N2O季节性的排放通量仍需对模型进行修正。通过比较施肥、土壤和田间管理等输入参数的改变对DNDC模型进行灵敏性分析,氮肥用量、施肥次数、土壤初始无机氮含量和土壤质地的改变对土壤N2O排放量均很敏感,其中氮肥用量和施肥次数的改变最为敏感。基于当地土壤特性和田间管理的校正,DNDC模型为评价农田生态系统N2O的排放提供了强有力的工具。     

土壤水氮动态及作物生长耦合EPIC-Nitrogen2D模型

为计算农业区不同作物生长条件下土壤水氮迁移转化过程,该文基于Erosion/Productivity Impact Calculator(EPIC)作物模型建立了作物根系生长子模块,将其进行有限元数值离散,与土壤氮素迁移转化模型Nitrogen2D耦合,使模型能计算作物生长条件下土壤水氮迁移转化过程。该作物生长模块可计算多种胁迫下作物根系对土壤水分和氮素的动态吸收速率,及作物收获时的生物量和吸氮量。采用武汉大学灌溉排水试验场冬小麦生长条件下土壤水氮试验数据对模型进行了率定,并用于土壤水氮分布和作物生物量预测,土壤含水率、氮素的模拟值与实测值的一致性系数分别为0.86~0.97、0.52~0.98,Nash效率系数为0.59~0.90(含水率)、0.44~0.93(土壤氮素),说明模拟结果与实测值吻合度较高。同时,分别采用该文的作物生长模块和简单根系吸收模块计算根系吸氮过程,结果显示,简单根系吸收模型会显著高估作物吸氮量,而作物生长模型则由于考虑了根系生长和各环境因子的胁迫作用,计算结果更符合作物实际吸氮过程,计算的根系吸氮量相对均方根误差为3.4%~46%。     

Nitrogen leaching and soil organic carbon sequestration of a Barley crop with improved N use efficiency – A regional case study

The potential of modified spring barley crops with improved nitrogen (N) use efficiency to reduce nitrogen (N) leaching and to increase soil organic carbon (SOC) storage was assessed at the regional scale. This was done using simulation model applications designed for reporting according to the Helcom (Helsinki Commission) and Kyoto protocols. Using model simulations based on modified crops N dynamics and SOC were assessed for three agro-ecological regions (latitudes ranging 55°20′–60°40′ N) in Sweden over a 20-year period. The modified N use properties of spring barley were implemented in the SOILNDB model (simulating soil C, N, water and heat, and plant N dynamics) by changing the parameters for root N uptake efficiency and plant N demand within a range given by previous model applications to different crops. A doubling of the daily N uptake efficiency and increased N demand (by ca 30%) reduced N leaching by 24%–31%, increased plant N content by 9%–12%, depending on region. The effects of the modified crop on SOC was simulated with the ICBM model, resulting in an increased SOC content (0–25 cm depth) by 57–79 kg?C?ha^?1?y^?1. The results suggest that a modified crop might reduce N leaching from spring barley area, in a range similar to the targets of relevant environmental protection directives, a result which held more in the northern than southern regions. The simulated SOC increase on a hectare basis was highest for the central region and least for the most northern region. For the total agricultural area the share of spring barley area was small and more crops would need to be modified to reach the emission reduction targets.     

皖中沿江平原水稻田CH_4和N_2O排放估算及其影响因素分析

利用DNDC9.3模型对研究区域水稻田排放的CH4和N2O通量进行模拟和定量估算,并对其影响因素进行分析。研究选取皖中沿江平原内具有典型代表性的长丰县水稻田为实验地区,利用DNDC9.3模型对该县内12个试验样点2008年的CH4和N2O排放量进行估算分析,并对其做敏感性实验分析。结果表明:1)长丰县水稻田2008年CH4和N2O年排放量分别为C 1.82×10-2 Tg和N 3.03×10-4 Tg;2)由敏感性分析实验得:CH4排放水平和气温、土壤pH和SOC呈正相关关系;N2O排放水平和气温、雨水中氮含量呈正相关关系,对SOC、土壤pH变化也较为敏感。