A Novel Method for Inverting Total Salt Content in Soil During Freezing–Thawing Process
ABSTRACT Saline soils represent a critical global ecological and environmental challenge. The precise and rapid determination of total salt content in saline soils during freezing–thawing processes is vital to effectively manage and mitigate soil salinization. This study builds on a volumetric mixing permittivity model for frozen soils, which accounts for the microstructure of saline soils during freezing and the occurrence of salts in either dissolved or crystalline states. A novel method is proposed to quantitatively invert the total salt content by integrating theoretical modeling with experimental validation. This approach extends the application of widely used multi‐parameter sensors, such as 5TE, by incorporating dielectric constant, electrical conductivity, and temperature as input parameters, thereby enabling the determination of total salt content in saline soils. Experimental results revealed that the contents of soluble and crystalline salts exhibited stage‐dependent variations during the freezing–thawing process. The mutual transformation between soluble and crystalline salts was jointly regulated by the initial water and salt conditions, reflecting a dynamic equilibrium between dissolution and crystallization. The inversion results of the model showed strong agreement with the experimental data, confirming the reliability and applicability of the method. This study proposes a method capable of accurately inverting the total salt content in saline soils at any temperature during the freezing–thawing process. This method effectively addresses the challenge of real‐time monitoring of total salt content during soil freezing–thawing processes. Future research should assess the applicability of the model across diverse soil types and field conditions, and promote its integration into dynamic salinity monitoring and precision agriculture.
Authors
- Wangcheng Li
- Yan Song (ORCID: https://orcid.org/0009-0001-1073-8039)
- Jianing Feng
- Mingtang Chai (ORCID: https://orcid.org/0000-0003-3913-2636)
- Jiayi Zhang (ORCID: https://orcid.org/0000-0002-1575-0723)
- Jinzhong Yang (ORCID: https://orcid.org/0000-0003-1923-1952)
Institutions
- Ningxia University (CN)
Publication Details
- Journal
- Land Degradation and Development
- Published
- 2025-11-23
- DOI
- https://doi.org/10.1002/ldr.70267
- Citations
- 1
- Primary Topic
- Soil Moisture and Remote Sensing
- Type
- article
- Field-Weighted Citation Impact
- 0.80