Process-based models of soil organic carbon (C) define soil organic matter by conceptual C pools. In the Roth C model these pools are represented by the particulate, humus and resistant organic C fractions (POC, HOC, and ROC). Here, we used three different sets of estimates of the C fractions to initialise Roth C and assessed their effect on the model predictions of the 0–0.3 m C stocks in a 30-year simulation. We estimated the stocks of POC, HOC and ROC with (1) pedotransfer functions (PTF), (2) proximal sensing, and (3) digital soil mapping with data from sensing. We conducted experiments in three C estimation areas of a cattle grazing farm in Australia. We found that in all cases, the model predicted increasing total organic C (TOC) stocks by up to 15.2 Mg C ha⁻¹. Using the PTF estimates, the uncertainty in the model predictions ranged from 4.9 to 7.1 Mg C ha⁻¹. Using proximal sensing and digital soil mapping, the uncertainty decreased to 2.3–3.6 Mg C ha⁻¹ and 3.2–5.4 Mg C ha⁻¹, respectively. Our results show that model initialisation with proximal sensing and digital soil maps well represent the spatial variation of TOC and the C pools, so that simulation of changes in C stocks were more reliable. Using the PTF estimates resulted in biased predictions that underestimated the TOC stocks by 2.0–4.5 Mg C ha⁻¹ over the simulation period. Informing a soil C model with measurements is key to building confidence in model-predictions of TOC stocks, providing useful feedback to management practices.

中文翻译：

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不同池初始化对土壤碳模拟的困惑

基于过程的土壤有机碳（C）模型通过概念性C库定义了土壤有机质。在Roth C模型中，这些库由微粒，腐殖质和抗性有机C组分（POC，HOC和ROC）表示。在这里，我们使用了三组不同的C分数估算值来初始化Roth C，并在30年的模拟中评估了它们对0-0.3 m C储量的模型预测的影响。我们用（1）pedotransfer函数（PTF），（2）近端感测和（3）数字土壤测绘（使用感测数据）来估计POC，HOC和ROC的存量。我们在澳大利亚一家放牧牛场的三个C估计区域进行了实验。我们发现，在所有情况下，该模型都预测总有机碳（TOC）储量将增加15.2 Mg C ha ^-1。使用PTF估计，模型预测中的不确定性范围为4.9至7.1 Mg C ha ^-1。使用近端感测和数字土壤测绘，不确定度分别降低至2.3–3.6 Mg C ha ^-1和3.2–5.4 Mg C ha ^-1。我们的结果表明，利用近端传感和数字土壤图进行的模型初始化很好地表示了TOC和C池的空间变化，因此模拟C储量的变化更为可靠。使用PTF估计值会导致有偏见的预测，在模拟期内，TOC储量低估了2.0–4.5 Mg C ha ^-1。通过测量告知土壤C模型是建立对TOC存量模型预测的信心的关键，为管理实践提供有用的反馈。