State Key Laboratory of Soil Erosion and Dryland Farming on the Loess Plateau, Northwest A&F University, Yangling, Shaanxi 712100, China; Beijing University of Agriculture, Beijing 102206, China; Center for Ecological Forecasting and Global Change, College of Forestry, Northwest A&F University, Yangling, Shaanxi 712100, China.
Center for Ecological Forecasting and Global Change, College of Forestry, Northwest A&F University, Yangling, Shaanxi 712100, China.
Sci Total Environ. 2019 Dec 20;697:134054. doi: 10.1016/j.scitotenv.2019.134054. Epub 2019 Aug 23.
Dissolved organic carbon (DOC) plays an important role in global and regional carbon cycles. However, the quantification of DOC in forest ecosystems remains uncertain. Here, the processed-based biogeochemical model TRIPLEX-DOC was modified by optimizing the function of soil organic carbon distribution with increasing depths, as well as DOC sorption-desorption efficiency. The model was validated by field measurements of DOC concentration and flux at five forest sites and Beijiang River basin in monsoon regions of China. Model validation indicated that seasonal patterns of DOC concentration across climatic zones were different, and these differences were captured by our model. Importantly, the modified model performed better than the original model. Indeed, model efficiency of the modified model increased from -0.78 to 0.19 for O horizon predictions, and from -0.46 to 0.42 for the mineral soils predictions. Likewise, DOC fluxes were better simulated by the modified model. At the site scale, the simulated DOC fluxes were strongly correlated with the observed values (R = 0.97, EF = 0.91). At the regional scale, the DOC flux predicted in the Beijiang River basin was 16.44 kg C/ha, which was close to the observed value of 17 kg C/ha. Using sensitivity analysis, we showed that temperature, precipitation and temperature sensitivity of DOC decomposition (Q) were the most sensitive parameters when predicting DOC concentrations and fluxes in forest soils. We also found that both the percentage of DOC flux to forest net ecosystem productivity, and the retention of DOC by mineral soil were highly correlated with the amount of precipitation. Overall, our model validations indicated that the modified TRIPLEX-DOC model is a useful tool for simulating the dynamics of DOC concentrations and fluxes in forest ecosystems. We highlight that more accurate estimates of parameter Q in deep mineral soils can reduce model uncertainty, when simulating DOC concentrations and fluxes in forest soils.
溶解有机碳（DOC）在全球和区域碳循环中起着重要作用。然而，森林生态系统中 DOC 的定量仍然不确定。在这里，基于过程的生物地球化学模型 TRIPLEX-DOC 通过优化土壤有机碳随深度增加的分布函数以及 DOC 吸附-解吸效率进行了修改。该模型通过在中国季风区五个森林站点和北江流域的 DOC 浓度和通量的现场测量进行了验证。模型验证表明，气候带之间的 DOC 浓度季节性模式不同，而我们的模型捕捉到了这些差异。重要的是，改进后的模型表现优于原始模型。实际上，改进模型的模型效率从 O 层预测的-0.78 增加到 0.19，从矿物质土壤预测的-0.46 增加到 0.42。同样，改进后的模型更好地模拟了 DOC 通量。在站点尺度上，模拟的 DOC 通量与观测值高度相关（R=0.97，EF=0.91）。在区域尺度上，北江流域预测的 DOC 通量为 16.44kg C/ha，接近观测值 17kg C/ha。通过敏感性分析，我们表明，在预测森林土壤中 DOC 浓度和通量时，温度、降水和 DOC 分解的温度敏感性（Q）是最敏感的参数。我们还发现，DOC 通量占森林净生态系统生产力的百分比以及矿物质土壤对 DOC 的保留与降水量高度相关。总体而言，我们的模型验证表明，改进后的 TRIPLEX-DOC 模型是模拟森林生态系统中 DOC 浓度和通量动态的有用工具。我们强调，在模拟森林土壤中 DOC 浓度和通量时，更准确地估计深层矿物质土壤中参数 Q 可以降低模型不确定性。
