A wide range of applications of unsaturated hydraulic conductivity is well known in geotechnical, hydrological, and agricultural engineering fields. The standard prediction models for hydraulic conductivity function overlook the complexity of soil pore structure and employ a simplistic approach based on the bundle of capillary tubes. This study proposes an alternative approach employing pore network models calibrated to match soil water retention data to predict the hysteretic hydraulic conductivity function of granular soils. A novel approach to constructing a multidirectional pore network built on an irregular lattice with variable coordination numbers is presented for the realistic representation of soil voids. The geometric and topological parameters of the pore network model are optimized using the genetic algorithm, and adequate pore‐scale processes (piston‐like advance and corner flow during drainage and piston‐like advance, pore body filling, and snap‐off during imbibition) are modeled to get reasonable predictions of hysteretic hydraulic conductivity functions over the entire suction range of granular soils. Comparisons between the pore network model results, standard physically based models, and measured data for a variety of granular soils show that the proposed pore network has a superior performance over other models and compares favorably to the experimental data.

中文翻译：

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基于优化的孔隙网络建模方法确定粒状土的导水率函数


不饱和导水率的广泛应用在岩土工程、水文和农业工程领域是众所周知的。导水率函数的标准预测模型忽略了土壤孔隙结构的复杂性，并采用基于毛细管束的简单化方法。本研究提出了一种替代方法，采用经过校准的孔隙网络模型来匹配土壤保水数据，以预测颗粒土壤的滞后导水率函数。提出了一种在具有可变配位数的不规则晶格上构建多向孔隙网络的新方法，以真实地表示土壤孔隙。使用遗传算法和适当的孔隙尺度过程（排水过程中的活塞式推进和角流以及活塞式推进、孔体充填和自吸过程中的折断）优化孔隙网络模型的几何和拓扑参数。进行建模，以获得粒状土壤整个吸力范围内迟滞导水率函数的合理预测。孔隙网络模型结果、标准物理模型和各种颗粒土的测量数据之间的比较表明，所提出的孔隙网络比其他模型具有优越的性能，并且与实验数据相比具有优势。