KMS Institute of soil and water conservation Chinese Academy of Sciences
|Alternative Title||The mechanisms of soil organic carbon (SOC) loss and its modeling|
|Place of Conferral||北京|
|Keyword||水蚀 Soc流失 团聚体 径流水动力学特征 Soc流失模型|
（1）系统研究了雨强、坡度和土壤质地交互作用下SOC流失特征及其规律，阐明了产沙量与SOC流失量的关系。研究结果表明，在试验雨强和坡度范围内，塿土、黑垆土、黄绵土（安塞）和黄绵土（绥德）的侵蚀泥沙有机碳富集比（ERoc）依次在1.15-2.36（平均值1.74）、1.18-1.69（平均值1.27）、1.06-1.34（平均值为1.12）和0.97-2.22（平均值为1.60）的范围内变化，而侵蚀泥沙中各粒级泥沙颗粒含量的变化趋势与ERoc相似，均随降雨历时的变化较小。塿土、黑垆土、黄绵土（安塞）和黄绵土（绥德）的土壤侵蚀速率依次为66.59、67.33、22.79和152.15 g m−2 min−1；SOC流失速率为0.28、0.20、0.06和0.14 g m−2 min−1。SOC流失速率与土壤侵蚀速率随土壤质地的变化趋势基本一致，因而产沙量在一定程度上决定了SOC流失量。进一步对产沙量与SOC流失量的关系研究发现，产沙量与SOC流失量呈显著正相关（P < 0.05）。然而，当土壤SOC含量较高时，由于SOC更易于在侵蚀泥沙中富集，侵蚀泥沙ERoc值较大，从而导致产沙量与SOC流失量的相关性减弱。此外，雨强和坡度对产沙量和SOC流失量的相关性也有重要影响。由于侵蚀泥沙ERoc值随雨强或坡度的降低而增大，从而使产沙量与SOC流失量的相关性减弱。研究还发现，随着土壤黏粒含量的增大，坡度和雨强对产沙量和SOC流失量的相关性的影响变小。不同土壤类型的黄土随坡度的变化规律存在差异，塿土和黄绵土的产沙量和SOC侵蚀量随坡度呈先增大后降低的趋势，而黑垆土的产沙量和SOC流失量在实验坡度范围内始终随着坡度的增大而增大。
（2）通过深入分析侵蚀过程中径流水动力学特征的变化，探明了径流流速、径流深、剪切力和径流功率与侵蚀泥沙SOC含量的内在关系，提取了可以较好表征侵蚀泥沙SOC富集比（ERoc）变化过程的水动力学因子。研究结果表明，土壤质地、雨强和坡度交互作用下径流流速始终与侵蚀泥沙SOC含量呈显著正相关（R2 = 0.731；P < 0.001），而径流深、剪切力和径流功率与侵蚀泥沙SOC含量无显著相关。通过对土壤质地对流速和侵蚀泥沙SOC含量的关系的影响进行研究发现，土壤质地在一定程度上决定了径流流速，且流速随着土壤黏粒含量的增大而增大；由于土壤黏粒含量与其SOC含量呈正相关，因此，流速与侵蚀泥沙SOC含量呈显著正相关（R2 = 0.893；P < 0.01）。进一步分析雨强对流速与侵蚀泥沙SOC含量的关系的影响发现，当雨强较低时，径流流速和径流功率均与泥沙中SOC含量较高的黏粉粒或轻质团聚体含量呈正相关关系，因而流速与泥沙ERoc值呈正相关。因此，当雨强较低时，流速与侵蚀泥沙SOC含量的决定系数更高（R2 = 0.958，P < 0.001）。在土壤质地、雨强和坡度交互作用下，流速可以较好地表征侵蚀泥沙SOC含量的变化。
（3）通过监测SOC迁移的径流水文水力过程，揭示了径流水动力学特征与侵蚀泥沙中SOC分布特征的关系。研究结果表明，当雨强小于45 mm h−1或坡度小于5°时，径流功率与径流深均较小，雨滴剥蚀团聚体破碎及其迁移过程对侵蚀泥沙ERoc值有重要影响，且泥沙各粒径团聚体SOC含量较原土壤明显增大。当雨强为45 mm h−1时，虽然泥沙各粒径团聚体SOC均发生明显富集，然而不同坡度条件下泥沙团聚体SOC含量无显著差异（P < 0.05）；然而，当坡度为5°时，随着雨强的增大，更多团聚体破碎形成粒径更小的颗粒，因此，微团聚体和黏粉粒的ERoc值随着雨强的增大而增大。当雨强大于45 mm h−1且坡度大于5°时，由于径流功率和流速足够大，较大的土壤侵蚀率削弱了团聚体破碎及其迁移过程对泥沙SOC分布特征的影响，因此，泥沙各粒径团聚体SOC含量与原土壤差异不显著（P < 0.05）。在降雨侵蚀过程中，由于产流率和径流深随着降雨历时的增大而增大，也减弱了雨滴对土壤团聚体的剥蚀作用，因此，泥沙各粒径团聚体SOC含量随降雨历时的增加呈降低的趋势。此外，流速、产流率、剪切力和径流功率与均与泥沙黏粉粒含量、黏粉粒SOC含量和微团聚体SOC含量呈负相关，而与泥沙砂粒含量呈正相关，且流速与泥沙中大团聚体含量随坡度和雨强的变化趋势最为一致。因此，众多水动力学参数中，片蚀阶段流速仍然与侵蚀泥沙SOC富集的关系最为密切。
（4）结合SOC流失的径流水动力学机制，建立了基于径流水动力学特征的SOC流失模型。研究发现，对于黄绵土，在不同雨强条件下，流速均与径流含沙量呈显著线性关系（R2 > 0.94，P < 0.05），而坡度与径流量呈显著二次函数关系（R2 > 0.94，P < 0.05）。对于黑垆土，含沙量和径流量均与坡度呈显著二次函数关系（R2 > 0.55，P < 0.05）。基于上述关系对黄绵土和黑垆土的产沙量进行了简单计算。在产沙量计算的基础上，采用传统SOC流失计算方法对SOC流失量进行预测，结果表明，该方法的预测精度主要取决于土壤侵蚀量的预测精度，且已有的泥沙SOC含量计算方法难以适用于黄土坡面。为了提高黄土坡面SOC流失量的预测精度，通过非线性回归分析发现，流速、坡度和雨强与侵蚀泥沙SOC含量之间为复合指数函数关系（R2 = 0.76，P < 0.005）。同时，结合已有的径流输沙模型，构建了基于径流水动力学特征的SOC流失模型。该模型以径流量、流速、坡度、泥沙分散前后的中值粒径差值（δD50）、原状土SOC含量和降雨时间作为输入参数，且可以较好预测SOC流失量。模型共包括四个方程，其中三个方程用于模型系数的计算。分析模型的决定系数（R2）和一致性指数（d）发现，土壤团聚体含量对模型精度有重要影响，对于δD50值较小的黄土，模型精度较好（R2 > 0.903，d > 0.974），对于δD50值较大的黄土，模型预测精度较低（R2 > 0.496，d > 0.861）。此外，模型也进一步证明了，δD50值越大，流速对土壤侵蚀量和SOC流失量的影响越大，而土壤SOC含量越高，坡度对土壤侵蚀量和SOC流失量的影响越大。该研究可为其他土壤类型和流域尺度下SOC流失预测提供新的思路。
|Other Abstract||Soil organic carbon (SOC) loss accompanying with water erosion can lead to soil degradation and decline of soil productivity. As an important part of carbon cycle, SOC loss also accelerates global warming which is an important environmental problem all over of the world. In prevous studies, the regulation of SOC loss and the SOC enrichment mechanism in sediments have been widely researched, whereas less considered the hydraulic mechanism of SOC loss. Meanwhile, soil erosion models were usually built based on the hydraulic mechanism. Therefore, a total understanding of the internal relationships of SOC loss and the runoff hydraulic characteristic and building a hydraulic based SOC loss model will be of great significance. In our study, four loess soils with clay contents of 26%, 21%, 16%, and 12%, called Lou soil (Yangling), Calcic Kastanozem (Changwu), Yellow Loamy Soil (Ansai) and Yellow Loamy soil (Suide), respectively, were selected. The sample sites are distributed from south to north across the Loess Plateau of China. By the artificial simulation of rainfall technology, the thesis further research the feature and regulations of SOC loss under the interaction of rainfall intensity, slope and soil texture, the internal relationships of SOC loss and the runoff hydraulic characteristics, and building a new hydraulic-based SOC loss model. The main results were illustrated as follows:|
(1) The interaction effects of rainfall intensity, slope and soil texture on the festures and regulations of SOC loss were further investigated, and the exact relationships of soil loss and SOC loss were clarified. The experimental results shows that the changing ranges of the enrichment ratios of SOC (ERocs) in sediments of Lou Soil, Calcic Kastanozem, Yellow Loamy Soil (Ansai) and Yellow Loamy Soil (Suide) were 1.15-2.36 (with a mean of 1.74), 1.18-1.69 (with a mean of 1.27), 1.06-1.34 (with a mean of 1.12) and 0.97-2.22 (with a mean of 1.60), respectively. Similar to the ERocs, the percentage of each sediment size class changed little within the range of experiment. The soil loss rate of Lou Soil, Calcic Kastanozem, Yellow Loamy Soil (Ansai) and Yellow Loamy Soil (Suide) were 66.59、67.33、22.79 and 152.15 g m−2 min−1, respectively; their average SOC loss rate were 0.28, 0.20, 0.06 and 0.14 g m−2 min−1, respectively. The average SOC loss rate has the similar variation tendency to the soil loss rate. Hence, the rate of soil erosion has an important effect on the SOC loss rate. Meanwhile, a significant correlation existed between the sediment yield and SOC loss after rainfall (P < 0.05), and the link is less pronounced when the SOC and clay content is higher. The SOC was easily enriched in sediments when the SOC content in soils was high. The correlation between soil loss and SOC loss could also become weak with the decrease of rainfall intensity and slope due to the increasing values of ERocs in sediments. In addition, both fine soil texture and high SOC content will make the effect of slope and rainfall intensity on soil loss and SOC loss become weak. Moreover, for Lou Soil and Yellow Loamy Soils, their sediment loss and SOC loss increased with the increasing of slope first; after the slope attached the critical slope gradient, their sediment loss and SOC loss decreased with the increasing of slope. However, for Calcic Kastanozem, the soil loss and SOC loss always increased with slope.
(2) The internal relationships between flow velocity, runoff depth, shear stress and stream power and ERocs were detected by in-depth analysis of the changes of runoff hydraulic characteristics. The results shows that, under the interaction of rainfall intensity, slope and soil texture, the flow velocity always had a significant positive linear relationship with the SOC concentration in sediments (R2=0.731, P < 0.001) whereas the runoff depth, shear stress and stream power didn’t have a significant relationship with SOC concentration in sediments. The studies on the effect of soil texture on the relationship of flow velocity and SOC concentration in sediments find the soil texture has a decisive effect on flow velocity, and the flow velocity always change within an exact range for one soil. Therefore, the flow velocity was significantly positive correlated with the clay content of soil (R2 = 0.893; P < 0.01). Moreover, flow velocity also has close relationships with the first transported sediment particles with high SOC content, e.g. clay, silt and light aggregates. Hence, the correlation of flow velocity and SOC concentration in sediments is more pronounced under the low rainfall intensity (R2=0.958; P < 0.001). Therefore, under the interaction of soil texture, slope and rainfall intensity, the flow velocity always positively correlated with the SOC concentration in sediments.
(3) The effect of flow hydraulic characteristics on the distribution of SOC in sediments was investigated by monitoring the SOC transport process. The study finds that when the rainfall intensity was less than 45 mm h−1 or slope was less than 5°, the values of stream power and flow velocity were enough low. Hence, the ERocs of each size aggregates were obvious higher than 1.0, which was caused by the first transported of light fine aggregates with high SOC content produced by raindrop peeling. Meanwhile, when the rainfall intensity was less than 45 mm h−1, no significant differences existed for the SOC concentration of each size aggregates in sediments under different slope (P < 0.05); when the slope was less than 5°, the increasing rainfall energy could lead to SOC enriched in finer and finer particles. Under the rainfall intensity greater than 45 mm h−1 and on the slope greater than 5°, the effect of the breakup of aggregates on the distribution of SOC in sediments was less due to the large rate of water erosion. Therefore, the ERocs of each size aggregates closed to 1.0. By contrasting the time variation of the ERocs in different size aggregates during the erosion process, the SOC concentrations in several aggregates size classes decreased with time. This is because the increasing of runoff rate with time makes the intensity of raindrop peeling weak. By correlation analysis, the SOC concentration in aggregates significantly negative correlated with the flow velocity, runoff rate, stream power and shear stress, but significantly positive correlated with the clay and silt content in sediments. Flow velocity might have close relationships with the transport of SOC enriched aggregates. Our study will provide important helpful for understanding the fate of SOC and building a physically-based SOC transport model.
(4) Referring to the soil erosion model and the SOC enriched hydraulic mechanism, a new hydraulic based SOC loss model was built. The results shows that the relationship between the average ﬂow velocity and average sediment concentration for the Yellow Loamy Soil could be regressed by a linear function (R2 > 0.94; P < 0.05), and the relationship between slope and runoff could be modeled with a quadratic function (R2 > 0.94; P < 0.05). For Calcic Kastanozem, both sediment concentration and runoff showed signifcant quadratic function relationships with slope (R2 > 0.55; P < 0.06). Thus, soil loss can be simply predicted by ﬂow velocity, slope. Then, the SOC loss was calculated by multiplying soil loss, SOC content in original soil and the ERoc values. However, the prediction accuracy of this traditional SOC calculation method mainly depends on the prediction accuracy of soil loss. Moreover, the datas of ERoc are difficult to obtain when predicting the long-time and large-scale SOC loss. To soilve this problem, on the basis of the hydraulic mechanism of SOC transport, by nonlinear regression, the SOC concentration in sediments was predicted by rainfall intensity, slope and flow velocity with R2 = 0.761 and P < 0.005. Meanwhile, on the basis of the water transport capacity function, a hydraulic-based sediment and SOC loss model was built. The model includes six input variables: runoff rate, average flow velocity at 2 m location from the outlet, slope steepness, the difference between the effective and ultimate median diameter (δD50), the SOC content of the original soil and the rainfall time. The hydraulic-based sediment and SOC loss model includes one master equation and three equations used to calculate the parameters of the master equation. The input datas of the new proposed model were easily obtained. However, for the soils with a high δD50 value, the prediction accuracies of the proposed model were low (R2 > 0.496，d > 0.861). For the soils with a low δD50 value, the prediction accuracies of the proposed model were high (R2 > 0.903，d > 0.974). In addition, with the increase of δD50, the effect of flow velocity on soil loss and SOC loss become large. With the increase of SOC content, effect of slope on soil loss and SOC loss become large. Considering that our study mainly focused on the loess soils, similar model may be built for other soils or in large scale field condition, which need to be further investigated.
|Subject Area||Soil Science|
|liu, lin. 黄土坡面有机碳迁移流失机制及模拟研究[D]. 北京. 中国科学院研究生院,2018.|
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