The determination of soil saturated hydraulic conductivity (K) is crucial in environmental and engineering fields. However, the current direct measurement methods of K are time-consuming and labor-intensive. As an alternative method, many researchers have developed a series of pedotransfer functions (PTFs) that estimate K based on easily accessible soil properties. Unfortunately, most existing PTFs of K focus on temperate and tropical regions in the United States and Europe. There is a lack of research discussing the applicability of K models in subtropical areas. To resolve this issue, we conduct a study using 515 subtropical soil samples to test the performance of existing PTFs of K. The K values of investigated soils range from 1.4 × 10 to 290 cm h. Among the affecting factors, soil bulk density (ρ) and effective porosity (φ) are found to be the most important variables. Current PTFs considering soil pore structural property (i.e., φ) or soil texture solely are not effective in assessing K of subtropical soils. To address this limitation, we integrate soil pore structural and textural properties and develop a new PTF based on the Kozeny-Carman equation. The performance and reliability of the new PTF are evaluated using independent K datasets from various regions. The results show a significant positive correlation between the measured K and the predicted K from the new PTF for subtropical soils with an R of 0.69, an average RMSE in log10K (cm h) of 0.496, and a mean bias value of 0.070. Besides, the new PTF is found to perform as well as widely used machine learning tools.

中文翻译：

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亚热带土壤饱和导水率土壤传递函数的评价与开发


土壤饱和导水率（K）的测定在环境和工程领域至关重要。然而，目前K的直接测量方法费时费力。作为一种替代方法，许多研究人员开发了一系列pedotransfer 函数 (PTF)，可根据易于获取的土壤特性来估计 K。不幸的是，大多数现有的 K PTF 都集中在美国和欧洲的温带和热带地区。目前缺乏讨论K模型在亚热带地区适用性的研究。为了解决这个问题，我们使用 515 个亚热带土壤样本进行了一项研究，以测试现有 K PTF 的性能。调查土壤的 K 值范围从 1.4 × 10 到 290 cm h。在影响因素中，土壤容重（ρ）和有效孔隙度（φ）是最重要的变量。目前仅考虑土壤孔隙结构特性（即 φ）或土壤质地的 PTF 不能有效评估亚热带土壤的 K。为了解决这一限制，我们整合了土壤孔隙结构和质地特性，并开发了一种基于 Kozeny-Carman 方程的新 PTF。新 PTF 的性能和可靠性使用来自不同地区的独立 K 数据集进行评估。结果表明，亚热带土壤的测量 K 值与新 PTF 预测的 K 值之间存在显着正相关，R 为 0.69，log10K (cm h) 的平均 RMSE 为 0.496，平均偏差值为 0.070。此外，新的 PTF 的性能与广泛使用的机器学习工具一样好。