Abstract Soil solid thermal conductivity (λs) is critical to model effective soil thermal conductivity (λeff) that is required for engineering design and estimate of soil surface energy flux and soil temperature. However, it is impossible to measure λs because soil is a porous medium and there is no way to compact the soil to a continuous solid state without any pore spaces. The indirect estimation of λs requires saturation of the soils or a complete soil mineralogical information or mineral component such as quartz that has much greater thermal conductivity. Therefore, many approximation approaches of various complexities to predict λs have been proposed. However, few studies have been conducted to assess these models. An extensive review were conducted and returned 20 models to calculate λs. These models were categorized and their performances were assessed with a compiled dataset consisting of 65 soils from five studies. The results showed that the Johansen approach can give satisfactory λs given that quartz content is available (RMSE = 0.60 W m−1 °C−1, NSE = 0.91) and the Tarnawski et al. model suitable for Canadian soils (RMSE = 0.55 W m−1 °C−1, NSE = 0.92). The Cote and Konrad approach that inversely model λs based on the geometric mean model and measured soil thermal conductivity at full saturation (λsat) give accurate λs (RMSE = 0.22 W m−1 °C−1, NSE = 0.99), but cannot be applied to soils without λsat measurement. The other approaches that take use of soil thermal conductivity at dryness (λdry) give unsatisfactory λs. Therefore, a new three-point method (three measurements between λdry and λsat) based on the He et al. model was proposed to predict λs. The results showed this approach provides a reliable method to estimate λs (RMSE = 0.17 W m−1 °C−1, NSE = 0.99) at various textures and water contents without knowledge on mineralogical information.

中文翻译：

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土壤固体热导率建模

摘要 土壤固体热导率 (λs) 是模拟有效土壤热导率 (λeff) 的关键，这是工程设计和估算土壤表面能通量和土壤温度所需的。然而，无法测量 λs，因为土壤是一种多孔介质，无法将土壤压实成没有任何孔隙空间的连续固态。λs 的间接估计需要土壤饱和或完整的土壤矿物学信息或矿物成分，例如具有更大热导率的石英。因此，已经提出了许多用于预测 λs 的各种复杂度的近似方法。然而，很少有研究对这些模型进行评估。进行了广泛的审查并返回了 20 个模型来计算 λs。对这些模型进行分类，并使用由来自五项研究的 65 种土壤组成的编译数据集评估其性能。结果表明，考虑到石英含量可用（RMSE = 0.60 W m−1 °C−1，NSE = 0.91）和 Tarnawski 等人，Johansen 方法可以给出令人满意的 λs。适用于加拿大土壤的模型（RMSE = 0.55 W m−1 °C−1，NSE = 0.92）。Cote 和 Konrad 方法基于几何平均模型和测量的完全饱和土壤热导率 (λsat) 对 λs 进行逆建模，给出了准确的 λs（RMSE = 0.22 W m−1 °C−1，NSE = 0.99），但不能应用于没有 λsat 测量的土壤。其他利用干燥土壤热导率 (λdry) 的方法给出的 λs 不令人满意。因此，一种基于 He 等人的新三点方法（λdry 和 λsat 之间的三个测量值）。模型被提出来预测λs。结果表明，这种方法提供了一种可靠的方法来估计 λs（RMSE = 0.17 W m-1 °C-1，NSE = 0.99）在各种质地和水含量下，无需了解矿物学信息。