Biopolymers have recently been used as ecofriendly materials for soil improvement in terms of stabilization, compressibility, and engineering parameters. The objective of this study is to assess the effect of biopolymer content in sand mixtures during freeze - thaw repetitive loading cycles. The biopolymers were mixed at weight ratios of 0.0, 0.5, 1.0, 2.0, 5.0, and 10 % (BPC 0.0 - BPC 10), and the relative density and degree of saturation were fixed at 60 % and 20 %, respectively. The measurement system was located in an ice chamber for freeze - thaw, and 100 cycles of repetitive loads were applied. The test results showed that the deformation decreased from BPC 0.0, to BPC 1.0 owing to the cementation effect produced by the biopolymer chain and coating. However, the deformation increased from BPC 1.0 to BPC 5.0 because high -viscosity solutions might separate the sand particles, causing a density reduction and generating more deformation by compaction. The relative permittivity varied with respect to BPC and freeze - thaw repetitive loading stages that were affected by unfrozen water content, volume contraction, and water consumption during dehydration. The shear wave velocity gradually increased from BPC 2.0 to BPC 10 because the effect of fines in coarse - fine mixtures, rather than the cementation effect. Therefore, the module containing the sensors used in this study can be used to understand the role of biopolymers as reinforcing materials in railway subgrades.

The tau -omega model is expanded to properly simulate L -band microwave emission of the soil-snow-vegetation continuum through a closed -form solution of Maxwell's equations, considering the intervening dry snow layer as a loss -less medium. The error standard deviations of a least -squared inversion are 0.1 and 3.5 for VOD and ground permittivity, over moderately dense vegetation and a snow density ranging from 100 to 400 kg m -3 , considering noisy brightness temperatures with a standard deviation of 1 kelvin. Using the Soil Moisture Active Passive (SMAP) satellite observations, new global estimates of VOD and ground permittivity are presented over the Arctic boreal forests and permafrost areas. In the absence of dense in situ observations of ground permittivity and VOD, the retrievals are causally validated using ancillary variables including ground temperature, above -ground biomass, tree height, and net ecosystem exchange of carbon dioxide. Time -series analyses promise that the new data set can expand our understanding of the land-atmosphere interactions and exchange of carbon fluxes over Arctic landscapes.

Frozen soil is a complex four-phase porous medium consisting of soil solid/rock, air, unfrozen/liquid water and ice at the subzero temperatures. Freeze-thaw cycles change the magnitude of total soil water content as well as the unfrozen water/ice ratio in frozen soil that affects soil structure and strength, infiltrability/permeability, water availability for microbial activity and chemical reactions, solute concentration and distribution, and thermodynamics. Accurate quantification of unfrozen water content is therefore critical to understand frozen soil hydrological, biogeochemical, thermal and mechanical properties and processes under climate change. Currently a variety of techniques and methods have been applied to obtain unfrozen water content in frozen soils. However, only few studies have attempted to review and synthesize these works. The objective of this study was therefore to review and collate currently available methods determining unfrozen water content in frozen soils. The principles, applications, advantages and limitations of these methods were reviewed and categorized into five categories: a pressure-based method, radioactive-methods, electromagnetic-methods, thermal-methods, and a sound-based method. Models for indirectly estimating unfrozen water content based on empirical temperature relationships, the soil water/moisture retention characteristic, and the vG-Clapeyron model, were also summarized. There is no direct method to estimate ice content but it can be indirectly calculated based on water balance (i.e., difference between total and unfrozen soil water content). The review is closed with a brief review of future needs and perspectives for simultaneous measurement of unfrozen water and ice contents in the laboratory and in the field.

Tree root systems are crucial for providing structural support and stability to trees. However, in urban environments, they can pose challenges due to potential conflicts with the foundations of roads and infrastructure, leading to significant damage. Therefore, there is a pressing need to investigate the subsurface tree root system architecture (RSA). Ground-penetrating radar (GPR) has emerged as a powerful tool for this purpose, offering high-resolution and nondestructive testing (NDT) capabilities. One of the primary challenges in enhancing GPR's ability to detect roots lies in accurately reconstructing the 3-D structure of complex RSAs. This challenge is exacerbated by subsurface heterogeneity and intricate interlacement of root branches, which can result in erroneous stacking of 2-D root points during 3-D reconstruction. This study introduces a novel approach using our developed wheel-based dual-polarized GPR system capable of capturing four polarimetric scattering parameters at each scan point through automated zigzag movements. A dedicated radar signal processing framework analyzes these dual-polarized signals to extract essential root parameters. These parameters are then used in an optimized slice relation clustering (OSRC) algorithm, specifically designed for improving the reconstruction of complex RSA. The efficacy of integrating root parameters derived from dual-polarized GPR signals into the OSRC algorithm is initially evaluated through simulations to assess its capability in RSA reconstruction. Subsequently, the GPR system and processing methodology are validated under real-world conditions using natural Angsana tree root systems. The findings demonstrate a promising methodology for enhancing the accurate reconstruction of intricate 3-D tree RSA structures.