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Estimating greenhouse gases emissions from horticultural peat soils using a DNDC modelling approach

机译:使用DNDC建模方法估算园艺泥炭土壤的温室气体排放

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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 CH4 from 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 ( similar to 35% and similar to 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.
机译:泥炭土代表着重要的全球碳汇,但也可以为园艺作物的生长提供高肥力的土壤。泥炭土壤上的可持续作物生产需要在确保粮食安全与减轻通常较高的温室气体排放量和土壤碳损失率之间进行权衡。对于所有潜在的管理方案,对温室气体通量进行资源密集型实地监测的另一种方法是使用由现有实地数据驱动的基于过程的模型来估算排放量。这项研究的目的是评估脱硝分解(DNDC)模型用于估算园艺泥炭土壤中CO2,N2O和CH4排放的适用性。使用气候,土壤和作物管理数据对模型进行参数化,该数据来自两个土壤有机质含量(SOM含量分别为35%和70%相似)的集约耕地。将模拟的CO2,N2O和CH4排放以及模拟的土壤物理和农作物产量值与实际的GHG,土壤和农作物测量值进行了比较。使用基线参数化(即模型默认值)评估模型性能,然后使用预仿真和灵敏度分析过程进行校准。在基线参数化条件下,DNDC在预测温室气体排放和土壤/作物变量方面表现不佳。校准和验证在估计年度排放量方面提高了DNDC的性能,但是特别是对于复制季节性GHG模式仍需要模型的完善。模型功能的主要限制因素似乎是其能够对土壤水分和碳氮动态的某些方面进行可靠建模的能力,以及与地下水位动态相关的输入数据的质量。总之,我们的结果表明DNDC(v。9.5)模型无法准确地复制或不能用来代替实际田间测量值来估计不同管理场景下的泥炭土壤的GHG排放因子,但也许可以进一步做到这一点。修改。

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