Soil freezing is one of the most complex physical processes affecting the Earth's hydrological cycle, yet it remains poorly understood despite its critical importance for climate modeling, agriculture, and infrastructure. This presentation aims to introduce the intricate thermodynamic relationships governing frozen soil behavior and introduces innovative numerical solutions that are revolutionizing how we model these processes.
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| Modified from Lu and Godt, 2012. Find the presentation by clicking here |
"Permafrost is not ice." This seemingly simple observation reflects a profound understanding that frozen soil represents a complex multiphase system where air, biota, liquid water, ice, and soil particles coexist in dynamic equilibrium. The traditional view of soil freezing as a simple phase transition grossly oversimplifies the physics involved.
The presentation emphasizes that proper soil freezing models must account for three fundamental thermodynamic potentials: temperature (or its inverse in non-equilibrium thermodynamics), pressure exerted by the system on the environment, and chemical potential. Each of these potentials drives different aspects of the freezing process and their interactions determine the overall system behavior.
The energy conservation equation reveals the intimate coupling between heat transfer and mass transfer during freezing. When soil freezes, the energy budget becomes strongly coupled to the mass budget and phase transitions, creating a system where small changes in one variable can cascade through the entire soil column. This coupling is mathematically expressed through terms that include both temperature gradients and mass flux divergence, highlighting why traditional approaches that treat heat and water transport separately often fail.
One of the most important insights from recent research concerns how water actually freezes in soil pores. Due to freezing point depression effects, the largest pores freeze first. This sequential freezing process means that as temperature drops, progressively smaller pores freeze, each at different temperatures determined by the complex interplay of solute concentration, pore geometry, and surface tension effects.
The research identifies several mechanisms controlling freezing point depression: the Gibbs-Thomson effect (curvature-induced freezing point depression), solute presence, ice nucleation kinetics, and interactions with pore boundaries. These processes combine to create soil freezing characteristic curves that show unfrozen water content decreasing gradually with temperature rather than exhibiting the sharp transition seen in pure water.
An educated guess in understanding soil freezing comes from recognizing its mathematical similarity to soil drying. The "freezing = drying hypothesis" suggests that during freezing, the effective chemical potential is determined only by liquid water, not the total water content. This insight allows researchers to use established soil water retention theory, such as the van Genuchten or Kosugi models, to predict freezing behavior.
This analogy proves particularly powerful because it enables the use of well-established relationships like Mualem's theory for predicting hydraulic conductivity as a function of unfrozen water content. The result is a unified framework where soil freezing can be modeled using modified versions of the Richardson-Richards equation, the standard equation for unsaturated soil water flow.
The mathematical complexity of coupled heat and water transport in freezing soil creates severe numerical challenges. The governing equations become highly nonlinear, with hydraulic capacity functions that exhibit sharp peaks near the freezing point. Traditional Newton methods fail to converge when solving these systems, leading to computational failures or unphysical results.
The breakthrough solution presented is the nested Newton-Casulli-Zanolli (NCZ) algorithm, which decomposes the nonlinear problem using Jordan decomposition. This approach separates the sharp nonlinear functions into monotonic components that can be solved iteratively. The NCZ algorithm dramatically outperforms traditional Newton methods, allowing stable solutions with large time steps while maintaining energy conservation.
The researchers have implemented these theoretical advances in WHETGEO-1D, a sophisticated modeling framework built on object-oriented programming principles. Unlike traditional procedural codes that hardwire specific equations, WHETGEO uses abstract interfaces and factory patterns to allow flexible combination of different soil water retention curves, hydraulic conductivity functions, and energy budget formulations.
This design philosophy, built on the OMS3 framework, enables rapid model evolution and prevents the "screwdriver problem" where having only one tool leads to seeing every problem as a screw. The modular architecture allows researchers to easily substitute different physical theories while maintaining the same robust numerical solver.
Field applications demonstrate WHETGEO's capabilities across multiple scales and conditions. The model successfully simulates complex scenarios including infiltration events that bring thermal energy deep into soil columns, surface energy exchanges during diurnal cycles, and seasonal freeze-thaw cycles. Comparison studies show that including phase change effects significantly alters predicted soil behavior, with frozen periods exhibiting markedly different hydraulic properties than unfrozen conditions.
The model's efficiency allows simulation of multi-year periods with time steps of hours or days, making it practical for long-term climate studies. This computational efficiency, combined with rigorous energy conservation, makes WHETGEO suitable for integration into larger Earth system models. WHETGEO is an open source software distributed under the GPL 3.0 license. For learning its use, please browse the GEOframe 2022 Summer School slides and videos.
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