A dynamic soil freezing characteristic curve model for frozen soil

The soil freezing characteristic curve(SFCC)plays a fundamental role in comprehending thermohydraulic behavior and numerical simulation of frozen soil.This study proposes a dynamic model to uniformly express SFCCs amidst varying total water contents throughout the freezing-thawing process.Firstly,a general model is proposed,wherein the unfrozen water content at arbitrary temperature is determined as the lesser of the current total water content and the reference value derived from saturated SFCC.The dynamic performance of this model is verified through test data.Subsequently,in accordance with electric double layer(EDL)theory,the theoretical residual and minimum temperatures in SFCC are calculated to be-14.5℃to-20℃for clay particles and-260℃,respectively.To ensure that the SFCC curve ends at minimum temperature,a correction function is introduced into the general model.Furthermore,a simplified dynamic model is proposed and investigated,necessitating only three parameters inherited from the general model.Additionally,both general and simplified models are evaluated based on a test database and proven to fit the test data exactly across the entire temperature range.Typical recommended parameter values for various types of soils are summarized.Overall,this study provides not only a theoretical basis for most empirical equations but also proposes a new and more general equation to describe the SFCC.

Different discretization method used in coupled water and heat transport mode for soil under freezing conditions

A coupled water and heat transport mode is established based on the Richards equation to study water flow and heat transport in soil during freezing process. Both the finite difference and finite element method are used in the discretization, respectively. Two different computer programs are written and used to simulate an indoor unidirectional frozen test. The freezing depth, freezing rate and temperature variation are compared among lab tests, finite difference calculation simulation and finite element calculation simulation. Result shows that： the finite difference method has a better performance in freezing depth simulation while the finite element method has a better performance in numerical stability in one-dimensional freezing simulation.

Influences of Seasonal Freezing and Thawing on Soil Water-stable Aggregates in Orchard in High Cold Region,Northeast China

Soil aggregate stability,as an important indicator of soil functions,may be affected by seasonal freezing and thawing(SFT)and land use in high cold and wet regions.Therefore,comprehensive understanding the effects of SFT on aggregate stability in orchards during winter and spring is crucial to develop appropriate management strategies that can effectively alleviate the degradation of soil quality to ensure sustainable development of orchard ecosystems.To determine the mechanism of degradation in orchard soil quality,the effects of SFT on the stability of water-stable aggregates were examined in apple-pear orchards(Pyrus ussuriensis var.ovoidea)of four different ages(11,25,40,and 63 yr)on 0 to 5%slopes before freezing and after thawing from October 2015 to June 2016 in Longjing City,Yanbian Prefecture,Northeast China,involving a comparison of planted versus adjacent uncultivated lands(control).Soil samples were collected to investigate water-stable aggregate stability in three incremental soil layers(0–20,20–40 and 40–60 cm).In the same samples,iron oxide,organic matter,and clay contents of the soil were also determined.Results showed that the destructive influences of SFT on water-stable aggregates were more pronounced with the increased orchards ages,and SFT exerted severe effects on water-stable aggregates of older orchards(40 and 63 yr)than juvenile orchards.Undergoing SFT,the soil instability index and the percentage of aggregate destruction increased by mean 0.15 mm and 1.86%,the degree of aggregation decreased by mean 1.32%,and the erosion resistance weakened,which consequently led to aggregate stability decreased.In addition,soil free,amorphous,and crystalline iron oxide as well as soil organic matter and clay contents are all important factors affecting the stability of water-stable aggregates,and their changes in their contents were consistent with those in the stability of water-stable aggregates.The results of this study suggest that long-term planting fruit trees can exacerbate the damaging effects of SFT on aggregate stability and further soil erosion increases and nutrient losses in an orchard,which hider sustainable use of soil and the productivity orchards.

How freezing and thawing processes affect black-soil aggregate stability in northeastern China

Laboratory experiments were carried out to investigate the effect of freezing and thawing processes on wet aggregate stability （WAS） of black soil. Wet aggregate stability was determined by different aggregate size groups, different water contents, various freeze-thaw cycles, and various freezing temperatures. The results showed that, when at suitable water content, aggregate stability was enhanced, aggregate sta-bility will be disrupted when moisture content is too high or too low, especially higher water content. Temperature also had a significant ef-fect, but moisture content determined the suitable freezing temperatures for a given soil. Water-stable aggregate （WSA〉0.5）, the total aggre-gate content, and mean weight diameter decreasing with the freeze-thaw cycles increase, reached to 5 percent significance level. The reason for crumbing aggregates is the water and air conflict, thus raising the hypothesis that water content affects the aggregate stability in the process of freezing and thawing.

Towards an improved prediction of soil-freezing characteristic curve based on extreme gradient boosting model

As an essential property of frozen soils,change of unfrozen water content(UWC)with temperature,namely soil-freezing characteristic curve(SFCC),plays significant roles in numerous physical,hydraulic and mechanical processes in cold regions,including the heat and water transfer within soils and at the land–atmosphere interface,frost heave and thaw settlement,as well as the simulation of coupled thermo-hydro-mechanical interactions.Although various models have been proposed to estimate SFCC,their applicability remains limited due to their derivation from specific soil types,soil treatments,and test devices.Accordingly,this study proposes a novel data-driven model to predict the SFCC using an extreme Gradient Boosting(XGBoost)model.A systematic database for SFCC of frozen soils compiled from extensive experimental investigations via various testing methods was utilized to train the XGBoost model.The predicted soil freezing characteristic curves(SFCC,UWC as a function of temperature)from the well-trained XGBoost model were compared with original experimental data and three conventional models.The results demonstrate the superior performance of the proposed XGBoost model over the traditional models in predicting SFCC.This study provides valuable insights for future investigations regarding the SFCC of frozen soils.

Field experimental study on the effect of thawed depth of frozen alpine meadow soil on rill erosion by snowmelt waterflow

Soil erosion by snow or ice melt waterflow is an important type of soil erosion in many high-altitude and high-latitude regions and is further aggravated by climate warming.The snowmelt waterflow erosion process is affected by soil freeze-thaws and is highly dynamically variable.In this study,a methodology was developed to conduct in situ field experiments to investigate the effects of the thawed depth of the frozen soil profile on snowmelt waterflow erosion.The method was implemented on an alpine meadow soil slope at an altitude of 3700 m on the northeastern Tibetan Plateau.The erosion experiments involved five thawed soil depths of 0,10,30(35),50,and 80(100)mm under two snowmelt waterflow rates(3 and 5 L/min).When the topsoil was fully frozen or shallow-thawed(≤10 mm),its hydrothermal and structural properties caused a significant lag in the initiation of runoff and delayed soil erosion in the initial stage.The runoff and sediment concentration curves for fully frozen and shallow-thawed soil showed two-stage patterns characteristic of a sediment supply limited in the early stage and subject to hydrodynamic-controlled processes in the later stage.However,this effect did not exist where the thawed soil depth was greater than 30 mm.The deep-thawed cases(≥30 mm)showed normal hydrograph and sedigraph patterns similar to those of the unfrozen soil.The findings of this study are important for understanding the erosion rates of partially thawed soil and for improving erosion simulations in cold regions.

A NEW MATHEMATICAL MODEL OF SECONDARY FROST HEAVE

In this paper a new mathematical model of secondary frost heave is presented. It is expected that the problem considered under some assumptions is well posed.

Parameterization of the freeze/thaw discriminant function algorithm using dense in-situ observation network data

The near-surface soil freeze–thaw(FT)transition is an important factor affecting land-atmosphere exchanges,hydrology and carbon cycles.Thus,effectively monitoring the temporal–spatial changes of soil FT processes is crucial to climate change and environment research.Several approaches have been developed to detect the soil FT state from satellite observations.The discriminant function algorithm(DFA)uses temperature and emissivity information from Advanced Microwave Scanning Radiometer Enhanced(AMSR-E)passive microwave satellite observations.Although it is well validated,it was shown to be insufficiently robust for all land conditions.In this study,we use in-situ observed soil temperature and AMSR-E brightness temperature to parameterize the DFA for soil FT state detection.We use the in-situ soil temperature records at 5 cm selected from available dense networks in the Northern Hemisphere as a reference.Considering the distinction between ascending and descending orbits,two different sets of parameters were acquired for each frequency pair.The validation results indicate that the overall discriminant accuracy of the new function can reach 90%.We further compared the Advanced Microwave Scanning Radiometer 2 discriminant results using the new function to the Soil Moisture Active Passive freeze/thaw product,and a reasonable consistency between them was found.