Climate change scenario modelling of soil carbon turnover on basis of improved soil carbon pool distribution on a regional scale

区域土壤有机碳通量和库的高分辨率表征有助于改进气候变化对农业生态系统影响和反馈的评估。然而，动态有机碳模型（DAISY）中的土壤有机碳（SOC）库分配仍然具有挑战性，特别是考虑到气候条件变化的驱动影响，例如单个有机碳库的温度敏感性。当在生态系统和农业系统存在异质性的区域尺度上进行有机碳建模时，这一限制的复杂性被放大了。我们建议在第二阶段对DAISY SOC周转模型进行改进，包括为SOM1和SOM2两个SOC池开发新的和通用的SOC稳定性指标，以及基于微生物酶活性的微生物池划分指数，用于SMB1和SMB2池的区分，同时考虑底物利用效率。这些基本步骤将主要通过红外（IR）技术的进一步发展来实现（漫反射中红外傅立叶变换光谱（midDRIFTS），演化气体分析（EGA），原位midDRIFTS，热解- mirs），允许在区域尺度上对土壤有机碳和微生物生物量进行高通量，不依赖于土壤质地的分析。将采用类似的技术，对添加的两个有机质库AOM1和AOM2作为碳氮循环的初始调节因子，生成作物残茬质量指标。为了考虑两个模式区（Kraichgau, Swabian Alb）气候变率的预估影响，SOC模型将通过对相应的C和N库的明确温度函数进一步扩展。为了对动态有机碳模型进行校准和验证，我们将回到两个模型区域的实验场，并考虑到我们与国际研究人员在长期野外实验中的合作。在与for1695新的陆地系统综合模式系统（ILMS）耦合之前，将使用DAISY-EXPERTN对与预期区域气候影响相关的单个和组合参数与先进的区域SOC模型进行敏感性分析。相关的开发和参数化模型程序和高分辨率区域土壤输入图将被纳入ILMS。在最后一步，将评估不同土地利用方式下的气候情景分析对土壤碳动态和大气反馈的影响，从而得出改进土壤碳固存方法的建议。

A high resolution representation of regional soil organic C (SOC) fluxes and pools facilitates an improved assessment of impacts of climate change and feedbacks on agro-ecosystems. However, soil organic carbon (SOC) pool partitioning in dynamic SOC models (i.e., DAISY) remains challenging, in particular when considering the driving influence of changing climatic conditions, e.g., by temperature sensitivities of individual SOC pools. The complexity of this constraint is magnified when SOC modelling is performed at a regional scale, where ecosystem and farm system heterogeneity exist. We propose an improvement of the DAISY SOC turnover model in Phase 2 including the development of novel and generic SOC stability indexes for the two SOC pools SOM1 and SOM2 as well as the generation of a microbial pool partition index based on activities of microbial enzymes for SMB1 and SMB2 pool distinction also considering substrate utilisation efficiencies. These essential steps will be primarily achieved through a further development of infrared (IR)-based techniques (diffuse reflectance mid-infrared Fourier transform spectroscopy (midDRIFTS), evolved gas analysis (EGA), in situT midDRIFTS, pyrolysis-MIRS) allowing a high-throughput, soil texture-independent analysis of SOC and microbial biomass pools at regional scale. Similar techniques will be employed to generate crop residue quality indexes for the two added organic matter pools AOM1 and AOM2 as initial regulators of C and N cycling. To account for the projected impact of climate variability in the two model regions (Kraichgau, Swabian Alb), the SOC model will be furthered through explicit temperature functions for corresponding C and N pools. For calibration and validation of the dynamic SOC model, we will revert to the experimental field sites in the two model regions as well as considering our existing cooperations with international researchers at long-term field experiments. Prior to coupling to the new Integrated Land-system Model System (ILMS) of FOR 1695, sensitivity analysis of individual and combined parameters related to the impact of expected regional climate with the advanced regional SOC model will be performed with DAISY-EXPERTN. The relevant developed and parameterised model routines and high resolution regional soil input maps will be incorporated into ILMS. In the final step, impacts of respective climate scenario analysis under alternative land uses, with and without improved CN module, on soil C dynamics and feedback from the atmosphere will be evaluated to derive recommendations for improved soil C sequestration approaches.