Coupling dielectric physics with calibration models for soil moisture sensing: progress and perspectives

The accurate quantification of soil water content (SWC) is critical for applications ranging from climate modeling to precision agriculture. While most modern sensors infer SWC by measuring the soil’s dielectric permittivity, the relationship between these two properties is not universal and is significantly influenced by site-specific factors such as soil texture, composition, and salinity. Without appropriate calibration, this leads to substantial errors in SWC estimation, including inaccurate assessments of water availability, flawed data for hydrological models, and misguided irrigation decisions. This manuscript addresses this challenge by systematically outlining the necessity of soil-specific calibration and providing a detailed explanation of various calibration methodologies for different soil types. It describes the dependencies and discrepancies in using dielectric properties for SWC measurement and reviews the models that overcome these limitations, from empirical approaches to physically-based dielectric mixing models. Furthermore, the work explores future directions, highlighting the potential of emerging technologies like hyperspectral imaging to complement traditional dielectric sensing techniques. By synthesizing current calibration strategies and pointing toward next-generation methods, this review aims to enhance the accuracy and reliability of soil moisture monitoring across diverse environments.