Estimating greenhouse gases emissions from horticultural peat soils using a DNDC modelling approach.
Estimating greenhouse gases emissions from horticultural peat soils using a DNDC modelling approach.
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DOI：
10.1016/j.jenvman.2018.11.113
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发表时间：
2019-03
影响因子：
8.7
通讯作者：
H. Taft;P. Cross;A. Hastings;J. Yeluripati;Davey L. Jones
中科院分区：
文献类型：
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作者：
H. Taft;P. Cross;A. Hastings;J. Yeluripati;Davey L. Jones
泥炭土是一种重要的全球碳（C）汇，但也可以为种植园艺作物提供高度肥沃的介质。泥炭土壤上的可持续作物生产涉及到确保粮食安全和减轻典型的高温室气体（GHG）排放和土壤碳损失率之间的权衡。对所有潜在的管理情景进行资源密集型实地温室气体通量监测的另一种办法是使用一种由现有实地数据驱动的基于过程的模型来估计排放量。本研究旨在评价反硝化-分解（DNDC）模型在估算园艺泥炭土壤CO2、N2 O和CH 4排放中的适用性。该模型的参数化使用的气候，土壤和作物管理数据从两个集约化耕作的土壤上对比土壤有机质（SOM）的含量（1035%和1070%SOM含量）。模拟排放的CO2，N2 O和CH 4，模拟土壤物理和作物产量值，进行了比较，实际温室气体，土壤和作物的测量。使用基线参数化（即模型默认值）评估模型性能，然后使用预模拟和敏感性分析过程进行校准。在基准参数化条件下，DNDC在预测温室气体排放量和土壤/作物变量方面表现不佳。校准和验证改进了DNDC在估计年度排放量方面的性能，但模型仍需改进，特别是再现季节性温室气体模式。模型运作的关键制约因素似乎是它的能力，可靠地模拟土壤水分和某些方面的C和氮的动态，以及输入数据的质量有关的地下水位动态。总之，我们的研究结果表明，DNDC（v.9.5）模型不能准确地再现或用于取代实际的实地测量，以估计温室气体排放因子在不同的管理方案下，园艺泥炭土，但可能能够这样做，进一步修改。
Peat soils represent an important global carbon (C) sink, but can also provide a highly fertile medium for growing horticultural crops. Sustainable crop production on peat soils involves a trade-off between ensuring food security and mitigating typically high greenhouse gas (GHG) emissions and rates of soil C loss. An alternative approach to resource intensive field-based monitoring of GHG fluxes for all potential management scenarios is to use a process-based model driven by existing field data to estimate emissions. The aim of this study was to evaluate the suitability of the Denitrification-Decomposition (DNDC) model for estimating emissions of CO2, N2O and CH4from horticultural peat soils. The model was parameterised using climatic, soil, and crop management data from two intensively cultivated sites on soils of contrasting soil organic matter (SOM) contents (∼35% and ∼70% SOM content). Simulated emissions of CO2, N2O and CH4, and simulated soil physical and crop output values, were compared to actual GHG, soil and crop measurements. Model performance was assessed using baseline parameterisation (i.e. model defaults), then calibrated using pre-simulation and sensitivity analysis processes. Under baseline parameterisation conditions, DNDC proved poor at predicting GHG emissions and soil/crop variables. Calibration and validation improved DNDC performance in estimating the annual magnitude of emissions, but model refinement is still required for reproducing seasonal GHG patterns in particular. Key constraints on model functioning appear to be its ability to reliably model soil moisture and some aspects of C and nitrogen dynamics, as well as the quality of input data relating to water table dynamics. In conclusion, our results suggest that the DNDC (v. 9.5) model cannot accurately reproduce or be used to replace actual field measurements for estimation of GHG emission factors under different management scenarios for horticultural peat soils, but may be able to do so with further modification.