A pore network model of soil water repellency: Model implementation and experimental validation

土壤疏水性对土壤质量的影响很大：它降低了土壤的持水量，增加了地上流、土壤侵蚀和农用化学品的优先淋滤。因此，为了实现水土资源的可持续利用，需要更好地了解土壤拒水性的控制机制。已有研究表明，土壤疏水性与土壤有机质和土壤含水量两个因素密切相关。实验表明了一个阈值行为：在临界含水量以上，具有给定土壤有机质百分比的土壤是可湿的（接触角<90）；在此临界含水量以下，接触角迅速增大，土壤变为疏水性（CA bbb90）。临界含水量随土壤有机质含量的增加而降低。虽然有经验模型能够有效地模拟这种水力行为，但缺乏能够预测不同土壤性质的土壤拒水现象的机制模型。本项目的目的是实现并实验验证一个孔隙尺度模型，该模型能够预测不同质地、含水量和土壤有机质含量土壤的拒水现象。我们的中心假设是，疏水表面的微观分布支撑着宏观尺度上的润湿性。我们假设，当含有CA bbb90的孔隙比例高于渗透阈值时，土壤就会变成疏水的，这对应于需要断开以阻止宏观流动通过土壤的孔隙比例。我们计划开发一个三维孔隙网络模型来模拟土壤再湿润。土壤有机质会均匀或优先分布在小孔隙中。每个孔隙的润湿性取决于每个土壤表面SOM的数量、空间分布和基质电位。我们将使用混合了玉米根系粘液的土壤来测试和验证我们的模型，这已被证明使土壤具有疏水性。我们将用参数化的方法来测量被黏液覆盖的玻璃板的CA。使用环境扫描电子显微镜冷凝技术将捕获孔隙空间中未受干扰的粘液分布。然后，我们将把我们的模型应用于表现出不同程度拒水性的自然土壤。我们将使用x射线光电子能谱来将润湿性与化学界面数据联系起来。将水滴入渗模拟与用照相机和中子射线照相捕捉的水滴渗透时间测试进行比较，以直观地显示随时间的入渗和分布。毛细管上升实验将用于估算不同基质电位下的动态接触角。

Soil water repellency has a big impact on soil quality: it reduces the water holding capacity and it enhances overland flow, soil erosion and preferential leaching of agrochemicals. Better understanding of the mechanisms controlling soil water repellency is therefore needed for the sustainable use of water and soil resources. Existing studies demonstrated that soil hydrophobicity is strongly related to two factors: soil organic matter and soil water content. The experiments indicated a threshold behaviour: above a critical water content soils with a given percentage of soil organic matter are wettable (Contact Angle<90); below this critical water content, the contact angle rapidly increases and the soil turns hydrophobic (CA>90). The critical water content decreases with increasing soil organic content. Although there are empirical models that are able to effectively mimic this hydraulic behaviour, a mechanistic model that is able to predict occurrence of soil water repellency for varying soil properties is missing. Objective of this project is to implement and experimentally validate a pore-scale model that is capable to predict the occurrence of water repellency in soils of various texture, water content and soil organic content. Our central hypothesis is that the microscopic distribution of water repellent surfaces underpins the wettability at the macroscopic scale. We hypothesize that a soil turns water repellent when the fraction of pores with CA>90 is above the percolation threshold, which corresponds to the fraction of pores that need to be disconnected to block the macroscopic flow through the soil. We plan to develop a 3D pore-network model to simulate soil rewetting. Soil organic matter (SOM) will be distributed either uniformly or preferentially in the small pores. The wettability of each pore will depend on the amount of SOM per soil surface, its spatial distribution and the matric potential. We will test and validate our model using a soil mixed with mucilage from maize roots, which was shown to make the soil water repellent. We will parameterize the model measuring the CA of glass plates covered with mucilage. The undisturbed distribution of mucilage in the pore space will be captured using the environmental scanning electron microscope condensation technique. Then we will apply our model to natural soils showing a varying degree of water repellency. We will use X-ray photoelectron spectroscopy to correlate wettability with chemical interfacial data. Simulation of water drop infiltration will be compared to water drop penetration time tests captured with a camera and neutron radiography to visualize the infiltration and distribution over time. Capillary rise experiments will be performed to estimate the dynamic contact angle under varying matric potentials.