•A total of 39 models to predict frozen soil thermal conductivity were reviewed.•A large dataset was compiled to evaluate performance of the models.•BB1992, TZ2016, ZM2018 and WL2017 are the best ...performing models, but overall performance of the models is not satisfactory.•A call for new model conceptualization, development and evaluation.
Frozen soil thermal conductivity (λeff) is a critical thermo-physical property that is required for environmental, earth science, geotechnical and geo-environmental applications and associated numerical modeling. Measurement of λeff in frozen soils is difficult and prone to errors, especially near the freezing/thawing point of soil water (e.g., −4 to 0 °C). Available steady-state or transient methods to measure λeff based on the soil temperature response to applied heat often result in melting of soil ice, violating the conduction-only assumptions of these methods and result in biased λeff measurements. Therefore, the choice of λeff models is often influence by their ease of implementation. A great number of such models have been developed during the last few decades since the latest comprehensive review of frozen soil thermal conductivity models in the early 1980s. There is a need to revisit this topic by comparing the models and evaluating their performance to provide information to the novice and expert alike, in order to guide them on their advantages, limitations and applications. A total of 39 models were categorized as: 1) linear and non-linear regression models (8 models); 2) physical models (6 models); 3) mixing models (6 models); 4) normalized models (17 models); and 5) models of other types based on their characteristics (2 models). These models were assessed with a large compiled dataset consisting of 331 λeff measurements taken at temperatures <−4 °C on 27 soils from seven studies, using steady-state or transient methods. Three performance indices including root mean square error (RMSE), average deviations (AD) and Nash-Sutcliff Efficiency (NSE) were used to evaluate performance of these models. The results showed that the models of Becker et al. (1992) (BB1992), Tian et al. (2016) (TZ2016), Zhang et al. (2018) (ZM2018) and Wang et al. (2017) (WL2017) were the best performing models in their affiliated category. However, none of the models performed satisfactorily, with NSE = 0.51, RMSE = 0.46 W m−1 °C−1 and AD = −0.04 W m−1 °C−1 for the best performing model among all the models investigated. Future studies that focus on conceptualization and development of new frozen soil thermal conductivity models for accurate and wide application is recommended.
•Introduced Turc-Budyko formula in validation approaches to identify actual over/under-estimation of GPDs in glaciated mountain regions.•Estimating glacier storage change based on water-energy-mass ...balance.•Assessing rationality between outputs of glacio-hydrological modeling.•GPDs do not meet the requirements of rational glacio-hydrology in Upper Indus Basin, High Mountain Asia.•GPDs generally need local correction based on water-energy-mass balance.
Recently, gridded precipitation datasets (GPDs) have become an essential input in hydrological modeling. Evaluation of their performance is a priori step before their application. When they are applied to a glaciated catchment, the glacier mass balance adds another dimension to the evaluation. This study has attempted to introduce the Turc-Budyko formula for validating the GPDs in glaciated catchments. This approach can identify the over- or under-estimation of catchment precipitation input by the GPDs. As a case study, the approach was applied in Upper Indus Basin (UIB), located in High Mountain Asia. The Turc-Budyko formula and other commonly used evaluation techniques found that APHRODITE underestimated the precipitation by 40 %, although it captured most of inter- and intra-annual variations of local climatology (CC > 0.6). CFSR and HAR were overestimated (106 % and 77 %) and characterize UIB as “Leaky” catchment, whereas underestimated GPDs characterize UIB as “Gaining” catchment. In leaky conditions, glacier storage changes were positive (0.21–0.37 m w.e. yr−1); while gaining conditions made negative glacier storage changes (-0.44 to −0.34 m w.e. yr−1) in UIB. None of the GPDs represented true conditions of glacio-hydrology in UIB. Introducing the Turc-Budyko formula confirmed that direct application of GPDs in hydrological modeling is implausible because GPDs generally cannot produce rational output of streamflow and mass balance simultaneously. It is recommended to locally correct the GPDs before any hydrological application in glacierized catchments.
Accurate and continuous measurements of soil thermal and hydraulic properties are required for environmental, Earth and planetary science, and engineering applications, but they are not practically ...obtained by steady‐state methods. The heat pulse (HP) method is a transient method for determination of soil thermal properties and a wide range of other physical properties in laboratory and field conditions. The HP method is based on the line‐heat source solution of the radial heat flow equation. This literature review begins with a discussion of the evolution of the HP method and related applications, followed by the principal theories, data interpretation methods, and their differences. Important factors for HP probe construction are presented. The properties determined in unfrozen and frozen soils are discussed, followed by a discussion of limitations and perspectives for the application of this method. The paper closes with a brief overview of future needs and opportunities for further development and application of the HP method.
Key Points
Soil thermal properties are required in environmental, Earth and planetary sciences, and in engineering applications
The heat pulse method is a transient method that can be used to estimate soil thermal properties and a variety of other physical and hydraulic parameters
The development history of 130 years, probe design, construction, calibration, applications, and limitations and perspectives are discussed
Groundwater recharge (GR) is a key component of regional and global water cycles and is a critical flux for water resource management. However, recharge estimates are difficult to obtain at regional ...scales due to the lack of an accurate measurement method. Here, we estimate GR using Gravity Recovery and Climate Experiment (GRACE) and Global Land Data Assimilation System (GLDAS) data. The regional-scale GR rate is calculated based on the groundwater storage fluctuation, which is, in turn, calculated from the difference between GRACE and root zone soil water storage from GLDAS data. We estimated GR in the Ordos Basin of the Chinese Loess Plateau from 2002 to 2012. There was no obvious long-term trend in GR, but the annual recharge varies greatly from 30.8 to 66.5 mm year−1, 42% of which can be explained by the variability in the annual precipitation. The average GR rate over the 11-year period from GRACE data was 48.3 mm year−1, which did not differ significantly from the long-term average recharge estimate of 39.9 mm year−1 from the environmental tracer methods and one-dimensional models. Moreover, the standard deviation of the 11-year average GR is 16.0 mm year−1, with a coefficient of variation (CV) of 33.1%, which is, in most cases, comparable to or smaller than estimates from other GR methods. The improved method could provide critically needed, regional-scale GR estimates for groundwater management and may eventually lead to a sustainable use of groundwater resources.
Effective thermal conductivity of clay (λeff) has essential applications in disciplines such as environmental and earth science, agriculture and engineering. Much work has been done pertaining to ...model thermal conductivity of clay, but no work was found to collate and synthesize these works. This study aimed to conduct an extensive review of the predictive models for thermal conductivity of clay and evaluate their performance with a large compiled dataset. A total of 28 models were collated and categorized and their performance was evaluated with a large dataset consisting of 1250 measurements made on 65 clays from 21 studies. The result showed that the DF1979 was the best performing model but not satisfactory, with root-mean-square-error (RMSE) = 0.35 W m−1 °C−1, average deviation (AD) = −0.04 W m−1 °C−1 and Nash-Sutcliff Efficiency (NSE) = 0.54. Further investigations showed that these models are dataset dependent and fairly good performance might be found on certain soils/dataset. Therefore, cares should be taken when selecting the most appropriate model for predicting λeff in practice. Limitations of the thermal conductivity models for clays have been stated and perspectives on future studies were also presented. This work would provide the novice or expert alike information on the advantage and limitations on modeling thermal conductivity of clays for various purposes.
•A total of 28 thermal conductivity models for clay were reviewed•These models were evaluated with 1250 measurements on 65 clays from 21 studies•The DF1979 model performed the best among the 28 models but not satisfactory•Model performance dataset/soil dependent and care should be taken for modelling modespecific soil types•It demonstrates an urgent call for developing new model with higher accuracy and wider applications
•A new model describing effective soil thermal conductivity (λeff) as a function of matric potential (ψ) is proposed.•The new model outperformed five other similar models in the literature across the ...full matric potential range.•More measurements of λeff(ψ) and studies on effects of air-entry point and hysteresis are needed.
Effective soil thermal conductivity (λeff) is required by a variety of science and engineering studies and associated numerical simulations. Because water content is the dominant factor determining the magnitude of λeff, modeling of λeff is usually based on the measured water content (θ) or degree of saturation (Sr). However, these approaches are largely soil dependent and no model was found for universal application. Prediction of λeff from energy states of soil water (i.e., ψ, the matric potential or matric suction) provides a unique way that takes pore size and geometry of soil into account and the resultant λeff(ψ) relationship is less sensitive to soil types compared to the λeff(θ) and λeff (Sr) relationships. The λeff(ψ) relationship developed by McCumber and Pielke (1981) (MP1981) has been incorporated into over 10 land surface, climate or hydrological models for wide applications. But the MP1981 model was reported to give unreasonable estimates especially at low ψ range. Lu et al. 2019 (LS2019) proposed an improved λeff(ψ) model but limited to applications in high ψ range. The objective of this study was to develop a new λeff(ψ) model for applications across the full range of matric potential. Experimental measurements of λeff(ψ) taken on 26 soils from four studies were used for the model development. A comparison of the new model with the MP1981, LS2019 and three other literature models showed the new model gave satisfactory estimates (RMSE < 0.2 W m−1 °C−1, AD ≈ 0 W m−1 °C−1 and NSE > 0.9) that outperformed all the other models. However, there is a lack of experimental measurements of λeff(ψ) to further validate and calibrate this model. Future efforts on the measurement of λeff(ψ) should be conducted and studies that investigate the effects of air entry and hysteresis on the behavior of λeff(ψ) relationship is recommended.
Novel quasiparticles beyond those mimicking the elementary high-energy particles such as Dirac and Weyl fermions have attracted great interest in condensed-matter physics and materials science. Here ...we report an experimental observation of the long-desired quadratic Weyl points by using a three-dimensional chiral metacrystal of sound waves. Markedly different from the newly observed unconventional quasiparticles, such as the spin-1 Weyl points and the charge-2 Dirac points featuring respectively threefold and fourfold band crossings, the charge-2 Weyl points identified here are simply twofold degenerate, and the dispersions around them are quadratic in two directions and linear in the third one. Besides the essential nonlinear bulk dispersions, we further unveil the exotic double-helicoid surface arcs that emanate from a projected quadratic Weyl point and terminate at two projected conventional Weyl points. This unique global surface connectivity provides conclusive evidence for the double topological charges of such unconventional topological nodes.
•Freeze-thaw induced landslides (FTILs) on grasslands were systematically examined.•Soil characteristics and topography were intrinsic factors controlling FTILs.•Increased rainfall and thickening ...active layer were direct drivers of FTILs.•Combining multiple monitoring methods is the trend for early warning of FTILs.
Landslides induced by freeze–thaw processes on grasslands are one of the major geohazards, and their scale and frequency are increasing as the global warms. Freeze-thaw induced landslides degrade surface vegetation and soil properties, reduce biodiversity, intensify landscape fragmentation, and lead to losses in economy, human and animal lives. Despite substantial progress in research on landslides, there has been little study focused on how ground freeze–thaw events affect landslides. By critically analyzing previous studies, this paper proposes a conceptual framework for the forms and types, development, dominant factors, monitoring techniques, and impact mechanisms of freeze–thaw induced landslides. Landslides are controlled by soil characteristics and topographic slope, which are major intrinsic determinants. Increased rainfall, rising temperatures, and thickening active layer due to climate change are all direct drivers of freeze–thaw induced landslides. Vegetation conditions, animal behavior interference, and wind erosion all affect the occurrence and development process of landslides by modifying vegetation cover, soil physical and chemical properties, and structure. Currently, landslide monitoring techniques have evolved rapidly with improved efficiency and accuracy, but with only few applications for freeze–thaw induced landslides. There are a variety of prediction models for landslides, but few consider freeze–thaw effects and lack field validation. The new perspective on the occurring types and dominant factors enhances theoretical understanding of the formation mechanisms, which helps further monitor and analysis of freeze–thaw induced landslides. Future studies should concentrate on the coupling mechanism of multiple factors and the development of an accurate prediction system, which will greatly benefit the understanding and early detection of freeze–thaw induced landslides.
•Biocrusts exert important impacts on soil temperature in frozen soil regions.•The annual mean soil temperature of biocrustal soil decrease 0.6–1 °C within 100 cm.•Soil temperature reductions of ...biocrusts mainly occur in daytimes when thawing.•Biocrusts prolong the freezing duration by approximately 10–20 days within 100 cm.
The relationship between soil temperature and its variations with different types of land cover are critical to understanding the effects of climate warming on ecohydrological processes in frozen soil regions such as the Qinghai–Tibet Plateau (QTP) of China. Biological soil crusts (biocrusts), which cover approximately 40% of the open soil surface in frozen soil regions, exert great impacts on soil temperatures. However, little attention has been given to the potential effects of biocrusts on the temperature characteristics, dynamics and freezing duration of soil in frozen soil regions. To provide more insight into this issue, an automatic system was used to monitor soil temperatures and dynamics at depths of 5, 30, 50 and 100 cm beneath bare soil and two types of biocrustal soils (soils covered with two types of biocrusts) on the QTP of China. The results showed that biocrusts play an important role in controlling the dynamics of soil temperatures. Biocrusts cause a 0.6–1 °C decrease in the mean annual temperature of soils down to a depth of 100 cm. The extent of the decrease in soil temperature was dependent on biocrust type, and dark biocrust showed a greater reduction in soil temperature than light biocrust. In addition, reductions in soil temperatures of biocrusts mainly occurred in daytimes of the thawing period, and this prolonged the freezing duration in the top 100 cm by approximately 10–20 days. The results of this study indicate that biocrusts maintain lower temperatures in the thawing period and slow the thawing of frozen soil in the spring, which helps to maintain the stability of the frozen soil. This information may aid understanding of the function of biocrusts in the frozen soil regions under global warming conditions.
PDF
