Gas diffusion, , in partially saturated soils, constitutes a critical topic in soil sciences. However, it is a complex process and this limits its characterization and estimation. In this study, we analyzed and parameterized the soil gas diffusion using a combination of percolation theory (PT) and the effective-medium approximation (EMA). Here, we selected 126 coarse-textured soils with measurements including sand, silt, and clay content, bulk density, organic matter, porosity, soil water content measured at different pressure heads and saturation-dependent gas diffusion. First, we adopted the van Genuchten model, fit it to the soil water retention curve (SWRC), optimized its parameters, and determined the water content at the inflection point. Second, the parameters of the universal scaling law from PT and EMA were optimized by directly fitting the model to the saturation-dependent gas diffusion data. Those parameters are (1) the critical air-filled porosity, , (2) the crossover air-filled porosity, , at which the gas movement behavior changes from the percolation theory domain to the EMA domain; and (3) the average pore coordination number, . Next, a multiple linear regression analysis (MLRA) was applied to link , and to other soil parameters, such as soil textural and/or hydraulic properties. Uncertainties in our results were evaluated using a jack-knife resampling technique, which involved applying the MLRA more than 7000 times. Results revealed that the most accurate estimations were obtained when both soil textural and hydraulic properties were used simultaneously. However, the use of only soil textural parameters presents practical advantages, as it provides excellent estimations for and , although not for . The latter is a critical parameter in the application of the PT and EMA to gas diffusion that requires both the soil basic properties and water saturation curve properties to be correctly estimated.

中文翻译：

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估计粗质土壤中气体扩散的普遍尺度


部分饱和土壤中的气体扩散是土壤科学中的一个关键课题。然而，这是一个复杂的过程，这限制了它的表征和估计。在本研究中，我们结合渗流理论（PT）和有效介质近似（EMA）对土壤气体扩散进行了分析和参数化。在这里，我们选择了 126 种粗质地土壤，测量值包括沙子、淤泥和粘土含量、容重、有机质、孔隙度、不同压头下测量的土壤含水量和饱和度相关的气体扩散。首先，采用van Genuchten模型，将其与土壤保水曲线（SWRC）进行拟合，优化其参数，确定拐点处的含水量。其次，通过将模型直接拟合到饱和度相关的气体扩散数据来优化 PT 和 EMA 的通用标度定律的参数。这些参数是 (1) 临界充气孔隙率， (2) 交叉充气孔隙率， ，此时气体运动行为从渗流理论域变为 EMA 域； (3) 平均孔隙配位数 。接下来，应用多元线性回归分析 (MLRA) 来链接 、 和 其他土壤参数，例如土壤质地和/或水力特性。我们使用折刀重采样技术评估结果的不确定性，该技术涉及应用 MLRA 7000 多次。结果表明，当同时使用土壤质地和水力特性时，可以获得最准确的估计。然而，仅使用土壤质地参数具有实际优势，因为它为 和 提供了极好的估计，尽管不是为 。 后者是 PT 和 EMA 应用于气体扩散的关键参数，需要正确估计土壤基本特性和水饱和曲线特性。