地下水流与微生物堵塞及运移过程的多尺度耦合反馈研究

多孔介质中水流的流动与微生物的生长、堵塞、运移及其介导的反应等过程对地下环境中污染物的迁移转化以及碳、氮等元素的生物地球化学循环起着重要作用。然而，这些动态过程在不同尺度上的复杂耦合反馈作用限制了我们对其的理解与认识。同时，这些过程中普遍存在的尺度效应也限制了现有相关参数、模型与理论在更大尺度研究中的适用性。因此，本文旨在研究上述多尺度耦合反馈过程中亟待解决的四个科学问题，以完善现有的水文-生物地球化学模型和理论体系。
为解决生物地球化学反应速率的尺度 生物地球化学反应速率的尺度 生物地球化学反应速率的尺度 生物地球化学反应速率的尺度 生物地球化学反应速率的尺度 生物地球化学反应速率的尺度 生物地球化学反应速率的尺度 生物地球化学反应速率的尺度 生物地球化学反应速率的尺度 生物地球化学反应速率的尺度 生物地球化学反应速率的尺度 生物地球化学反应速率的尺度 生物地球化学反应速率的尺度 转换 问题， 本文 首先利用有效参数方法推导了宏观有效反应速率与平均反应速率之比的表达式。通过估算该比值，即可在更大尺度的研究中根据平均浓度反推宏观有效反应速率。因此本文归纳了可能影响该比值的因素，并在耦合模型中分类讨论了不同因素对该比值的影响。研究表明，底物来源是影响生物地球化学反应速率尺度提升的关键因素之一。当底物中电子供体与电子受体来源相同时，流速、介质非均质性、底物浓度比以及运移延迟等其它因素对有效速率估算的影响较小，偏差在50%以内。相对于野外尺度与实验尺度反应速率间通常观测到的几个数量级的偏差，该偏差较小，意味着该场景下根据平均浓度计算的平均反应速率可近似为宏观有效反应速率；而当底物来源不同时，平均反应速率通常会高估宏观有效速率，且高估的程度通常随着流速的增加而降低。对有效参数的分解表明，底物与微生物分布的均质性以及正相关性是生物地球化学反应的尺度效应减弱的关键因素。
针对介质非均质性的演变问题以及生物堵塞模型的尺度提升问题，本文建立耦合了流动与多种微生物过程的模型以讨论微生物的多尺度分布，并依此分析了多孔介质的局部和全局尺度渗透系数的变化，进而研究了多孔介质多尺度非均质性的演变。研究结果表明，多孔介质非均的 多孔介质非均的 多孔介质非均的 多孔介质非均的 多孔介质非均的 多孔介质非均的 多孔介质非均的 多孔介质非均的 演变 受到流动的强烈影响。 受到流动的强烈影响。 受到流动的强烈影响。 受到流动的强烈影响。 受到流动的强烈影响。 受到流动的强烈影响。 受到流动的强烈影响。 受到流动的强烈影响。 受到流动的强烈影响。 受到流动的强烈影响。 具体而言，流动及其带来的底物供应会削弱多孔介质在垂直水流方向上的局部非均质性（局部渗透系数分布的对数标准差σlgK在设置的流速区间内的下降幅度可高达33%），而流动引起的微生物剪切过程的作用则相反（σlgK的增幅可达6%）。同时，还分析了多孔介质的局部和全局尺度孔隙度变化，并将其与渗透系数的变化进行比较，进而探讨了生物堵塞模型在不同尺度上的差异。结果表明，流动对生物堵塞模型的尺度提升也有显著影响：更高的流速及其带来的充足底物供应可以缩小局部尺度和全局尺度生物堵塞模型之间的差异，且流动引起的剪切作用也会削弱生物堵塞模型的尺度效应。
为构建跨尺度的微生物运移模型，本文收集了420组不同尺度（5mm-6.8m）的微生物运移实验数据，包括微生物的穿透曲线和相应的实验条件。然后，用非线性优化方法将微生物运移的过程模型与穿透曲线进行拟合以得到统一的模型参数。将这些模型参数作为目标变量，并将对应的实验条件作为特征变量，构建微生物运移数据库，并使用人工神经网络获取它们之间的定量关系。最后，将人工神经网络与过程模型耦合，建立了一个跨尺度的统一参数模型。测试结果显示，该模型与相关物理机理基本自洽，可模拟不同尺度下和复杂条件下微生物的运移。
综上，本文以数值模拟和数学推导为主要手段，研究了非均质介质中流动与各种微生物过程的耦合反馈机制，并探索了相关参数、模型与理论的尺度转换。研究结果为水文-生物地球化学模型的理论发展和实际应用提供了支持，推动了有害物质迁移转化及碳氮元素循环研究的发展。

Flow and microbial growth, clogging and transport processes in subsurface environment can strongly influence the biogeochemical cycling of elements such as carbon and nitrogen, as well as the transport and transformation of various pollutants. However, it is still difficult to understand these dynamic processes because of the coupling feedback of the above processes at different scales. At the same time, the scale effects prevalent in these processes also limit the applicability of existing relevant parameters, models and theories to larger scale studies. Therefore, four critical problems in these processes are studied to improve the existing hydrologic-biogeochemical models and theoretical systems.
To investigate the scaling of biogeochemical reaction rates, an expression for the ratio of the effective reaction rate to the average reaction rate (based on the average concentration), or the ratio of the effective rate parameter to the intrinsic rate parameter was first derived using the effective parameter approach. By estimating the value of this expression, it is possible to invert the macroscopic effective reaction rate based on the average concentrations of microorganisms and substrates in larger-scale studies or applications. The main factors that may affect this expression were then summarized, and the variations of effective rates or effective parameters under different factors were discussed categorically in a model coupling flow and several microbial processes. The results show that the substrate source is one of the most critical factors affecting the scale effect of biogeochemical reaction rates, and that when the sources of electron donors and electron acceptors are the same, variations in flow rate, porous medium heterogeneity, substrate concentration ratio, and retardation factors have little effect on the estimation of effective rates, with the maximum deviation between the average and effective reaction rates being within 50%. The deviations caused by these factors are negligible compared to the several orders of magnitude differences typically observed between field-scale and experimental-scale reaction rates, which means that the average reaction rates calculated according to the average concentration in these scenarios can be approximated to the macroscopic effective reaction rates. However, when the substrate sources are different, the overestimation of the macroscopic effective rate by the mean-field rate usually decreases with increasing flow velocity in scenarios with different substrate sources. In addition, decomposition of effective parameters shows that the homogeneous distribution of substrates and microorganisms, as well as their positive spatial correlation with each other can weaken the scaling effect of biogeochemical reactions.
Aiming at the evolution of heterogeneous media and the upscaling of bioclogging models, a model coupling flow and multiple microbial processes was established to discuss the multi-scale distribution of microorganisms. The changes of hydraulic conductivity at local/global scale were analyzed accordingly, and the evolution of multi-scale heterogeneity of porous media was further studied. The results show that the evolution of multi-scale heterogeneity of porous media in the subsurface environment is mainly influenced by the flow of subsurface water. Specifically, flow and the resulting substrate supply will decrease the local heterogeneity of the porous media in the vertical flow direction (the standard deviation of the local logarithmic hydraulic conductivity σlgK decreases by up to 33% in the set flow interval), while the flow-induced shearing stress has the opposite effect on the local heterogeneity (σlgK increases by up to 6% in the set flow rate interval). At the same time, the variation of porosity at local and global scales was analyzed, and was compared with the variation of hydraulic conductivity, thus exploring the differences of bioclogging model at different scales. The results show that flow also has a significant effect on the upscaling of bioclogging model. Specifically, higher flow velocity and the resulting adequate substrate supply will reduce the deviation between the local-scale bioclogging model and the global-scale bioclogging model, and the flow-induced shearing stress will also weaken the scale effect of the bioclogging model.
To construct a cross-scale microbial transport model, exhaustive search of literature was conducted, rendering 420 sets of experimental data of microbial transport at different scales (5mm to 6.8m), including the breakthrough curve of microbial transport and the corresponding experimental conditions. Sparse nonlinear optimization method was used to fit the process-based model to the breakthrough curve of microbial transport, and then a set of unified model parameters related to the attachment/detachment and straining/liberation processes of suspended microorganisms were obtained. Taking these unified model parameters as target variables and the corresponding experimental conditions from the literature as training variables, a database of microbial transport was established, followed by training an artificial neural network to obtain a quantitative relationship between them. Finally, an artificial neural network was coupled into the process-based model to construct a cross-scale unified parameter model. The testing results of this coupled model show that the model behaves in a largely self-consistent manner with the relevant physical mechanisms and can be used to simulate microbial transport under complex conditions.
In summary, the coupling feedback mechanism between flow and various microbial processes in heterogeneous media is studied by means of numerical simulation and mathematical derivation, and the scale transformation of relevant parameters, models and theories is explored. The results of this study provide support for the theoretical development and practical application of hydro-biogeochemical models, and promote the development of the migration and transformation of harmful substances and the cycle of carbon and nitrogen elements.

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