A matrix for estimating the unfrozen water content of freezing soils

IF 5.4 1区农林科学 Q1 GEOSCIENCES, MULTIDISCIPLINARY

Catena Pub Date : 2025-05-02 DOI:10.1016/j.catena.2025.109050

Jun Bi , Guoxu Wang , Wenxuan Mu , Haiyan Wen , Wansheng Pei , Qiyong Zhang , Sheng Yang , Mengyao Mao , Gaochao Lin , Chong Wang

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引用次数: 0

Abstract

The unfrozen water content is a vital soil parameter for freezing soils. Previous studies have developed numerous models to simulate the relationship between the unfrozen water content and temperature, but most models are only applied to fit the experimental data. In this study, a matrix containing 16 estimation models was developed to estimate the unfrozen water contents at different temperatures based on the combination of the Kozlowski model, 4 freezing point (T_f) models and 4 residual gravimetric unfrozen water content (w_r) models. The 16 estimation models in the matrix were evaluated for 56 soils, and the L2021-K2007 model (combination of the Liang 2021 T_f model and Kozlowski 2007 w_r model) provided optimal results. Also, the estimation models containing the Liang 2021 T_f model perform better than those containing the other T_f models, while the estimation models containing the Kozlowski 2007 w_r model perform better than those containing the other w_r models. The T_f models and w_r models have different effects on the estimation results. At higher temperatures, the T_f models have more significant effects on the estimation results than the w_r models. In contrast, at lower temperatures, the w_r models have larger influences on the estimation results than the T_f models. The matrix has the potential to improve the estimation of the unfrozen water content and provide guidance for the development of the unfrozen water content estimation models.

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估算冻土未冻水含量的矩阵

未冻水含量是冻土的重要土壤参数。以往的研究已经建立了许多模型来模拟未冻水含量与温度之间的关系，但大多数模型仅用于拟合实验数据。本研究结合Kozlowski模型、4个冰点（Tf）模型和4个剩余重力未冻水含量（wr）模型，构建了包含16个估算模型的矩阵，用于估算不同温度下的未冻水含量。结果表明，L2021-K2007模型（Liang 2021 Tf模型和Kozlowski 2007 wr模型的组合）是56种土壤的最佳估算模型。此外，包含Liang 2021 Tf模型的估计模型优于包含其他Tf模型的估计模型，而包含Kozlowski 2007 wr模型的估计模型优于包含其他wr模型的估计模型。Tf模型和wr模型对估计结果的影响是不同的。在较高温度下，相对于wr模型，Tf模型对估算结果的影响更为显著。相比之下，在较低温度下，wr模型对估计结果的影响大于Tf模型。该矩阵具有改进未冻水含量估算的潜力，并为未冻水含量估算模型的开发提供指导。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Catena 环境科学-地球科学综合

CiteScore

10.50

自引率

9.70%

发文量

816

审稿时长

54 days

期刊介绍： Catena publishes papers describing original field and laboratory investigations and reviews on geoecology and landscape evolution with emphasis on interdisciplinary aspects of soil science, hydrology and geomorphology. It aims to disseminate new knowledge and foster better understanding of the physical environment, of evolutionary sequences that have resulted in past and current landscapes, and of the natural processes that are likely to determine the fate of our terrestrial environment. Papers within any one of the above topics are welcome provided they are of sufficiently wide interest and relevance.