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
•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.
•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.
Mulching practices have long been used to modify the soil temperature and moisture conditions and thus potentially improve crop production in dryland agriculture, but few studies have focused on ...mulching effects on soil gaseous emissions. We monitored annual greenhouse gas (GHG) emissions under the regime of straw and plastic film mulching using a closed chamber method on a typical winter-wheat (Triticum aestivum L. cv Xiaoyan 22) and summer-maize (Zea mays L. cv Qinlong 11) rotation field over two-year period in the Loess Plateau, northwestern China. The following four field treatments were included: T1 (control, no mulching), T2 (4000kgha−1 wheat straw mulching, covering 100% of soil surface), T3 (half plastic film mulching, covering 50% of soil surface), and T4 (complete plastic film mulching, covering 100% of soil surface). Compared with the control, straw mulching decreased soil temperature and increased soil moisture, whereas plastic film mulching increased both soil temperature and moisture. Accordingly, straw mulching increased annual crop yields over both cycles, while plastic film mulching significantly enhanced annual crop yield over cycle 2. Compared to the no-mulching treatment, all mulching treatments increased soil CO2 emission over both cycles, and straw mulching increased soil CH4 absorption over both cycles, but patterns of soil N2O emissions under straw or film mulching are not consistent. Overall, compared to T1, annual GHG intensity was significantly decreased by 106%, 24% and 26% under T2, T3 and T4 over cycle 1, respectively; and by 20%, 51% and 29% under T2, T3 and T4 over cycle 2, respectively. Considering the additional cost and environmental issues associated with plastic film mulching, the application of straw mulching might achieve a balance between food security and GHG emissions in the Chinese Loess Plateau. However, further research is required to investigate the perennial influence of different mulching applications.
Display omitted
•Crop yields were significantly increased by straw mulching over both cycles, and by plastic film mulching in cycle 2.•Both straw and film mulching significantly increased soil CO2 emission over both cycles.•Patterns of soil N2O emissions under straw or film mulching are not consistent.•Both straw and film mulching significantly decreased annual GHGI.•Straw mulching is recommended in Loess Plateau, China.
•N fertilization and tillage reversal increased organic C more for soil with low C.•Macroaggregates were the most important fraction for C storage.•N fertilization and tillage reversal enhanced ...macroaggregate formation in topsoils.•Tillage reversal did not offset N fertilization-increased C storage in topsoils.
Nitrogen (N) fertilization and reversing land management from long-term no tillage (NT) to conventional tillage (tillage reversal; TR) may markedly alter soil carbon (C) dynamics. We studied the impact of N fertilization, N applied at 100 kg ha−1 yr−1 (N100) vs. no N application (N0), and tillage reversal (NT vs. TR) on soil aggregation and aggregate-associated C in top- (0–10) and subsoils (50–60 cm) in a Black Chernozem and a Gray Luvisol. Our results showed that soil organic C content was greater in N100 (1.74 g C kg−1) than in N0 (1.29 g C kg−1), and in TR (1.71 g C kg−1) than in NT (1.32 g C kg−1) only in the topsoil of the Gray Luvisol. Nitrogen fertilization and tillage reversal improved topsoil, but not subsoil mean weight diameter or the amount of large macroaggregates (>2000 μm). Topsoil aggregate-associated C was only increased (P < 0.01) with N fertilization. Microaggregate-associated C in the topsoil of the Black Chernozem was 70.6 g C kg−1 sand-free water-stable aggregate in N100, which was 13.8% higher (P < 0.01) than that in N0. However, C associated with all aggregate fractions in the topsoil was increased (P < 0.05) by N fertilization in the Gray Luvisol. In the Black Chernozem, the physical protection for C in the subsoil was decreased by N fertilization and tillage reversal, as indicated by decreased large macroaggregate and microaggregate-associated C (P = 0.04 and < 0.001, respectively). Subsoil aggregate-associated C was not influenced by N fertilization or tillage reversal in the Gray Luvisol. We conclude that N fertilization and/or tillage reversal improved topsoil aggregation; only N fertilization improved the physical protection for C in the topsoil. The adoption of tillage reversal (2 years) did not offset the benefit of N fertilization on soil aggregation and soil C concentration.
The time domain reflectometry (TDR)-measured effective permittivity in frozen soil conditions is affected by many complex factors including bound water effects on soil water permittivity, phase ...changes, soil microstructure and relative positions of soil constituents with respect to each other. The objective of this study was to improve understanding of some of the factors affecting the effective permittivity of frozen soils through the use of dielectric mixing models. Published datasets and frozen and unfrozen soil data measured on western Canadian soils were investigated with multiphase discrete and confocal ellipsoid models available in the literature. The results revealed that adjusting model parameters allowed the mixing models to describe the frozen soil permittivity equally well when bound water effects and temperature-dependent water permittivity effects were included or not included. Measurement of freezing and thawing curves on western Canadian soils showed significant hysteresis and some mechanisms for this observed hysteresis and its influence on the interpretation of published datasets are discussed. When independent measurements of liquid water, ice and effective permittivity are available, it is possible to find one set of model parameters that reasonably predict effective permittivity for both frozen and unfrozen conditions. In frozen soils the predictive capability of the models is constrained to scenarios where the initial water content prior to freezing (i.e., the total water content) in the sampling volume is constant.
•Various forms of dissolved trace elements were distinguished using AF4-UV-ICPMS.•Primarily ionic and colloid-associated forms of Al, As, Co, Cu, Fe, Ni, Pb, Th, Tl, U, V and Zn were extracted with ...water.•Mainly ionic species of Ba, Cr, Li, Mn and Mo were found in both extracts.•Primarily ionic forms of all elements were present in CaCl2 extracts.
Dissolved (<0.45 µm) trace elements (TEs) represent the sum of free ions, simple complexes and colloid-associated forms which have different mobility and bioavailability in soils. The distribution of TEs amongst these chemical forms was directly quantified in soil extracts using asymmetric flow field-flow fractionation (AF4) coupled to ultraviolet–visible absorbance spectrophotometry (UV) and inductively coupled plasma mass spectrometry (ICP-MS). The soil extracts were obtained using single extraction method with water and 0.01 M CaCl2, respectively. The yields of dissolved TEs extracted from the soils were profoundly impacted by extractants. Using AF4-UV-ICPMS, we show that dissolved species of Ba, Cr, Li, Mn and Mo were primarily present as “truly dissolved”/mainly ionic species (<1 kDa), e.g., hydrated cations, simple complexes or oxyanions, and therefore, likely represented the most bioavailable fraction. The distribution of these TEs amongst dissolved forms was unaffected by the different extractants. However, their dissolved concentrations were profoundly affected. Distributions of Al, As, Co, Cu, Fe, Ni, Pb, Th, Tl, U, V and Zn among the various chemical forms significantly differed with water and CaCl2 extractants. In water extracts, a greater proportion of these elements was associated with colloidal forms having sizes from 1 kDa to 0.45 µm, i.e., dissolved organic matter (DOM) or/and inorganic colloids. Water not only released greater colloid-complexed concentrations of TEs, like Al, As, Fe, Pb, Th, Tl, U and V, but also liberated greater amounts associated with ionic and small forms. Extractants like water and CaCl2 are useful for recovering bioavailable TEs from soils. However, the dissolved TEs extracted using water or CaCl2 represented TE concentrations and forms with different bioavailability. The AF4-UV-ICPMS technique is useful for directly quantifying TEs existing as mainly ionic species and those bound with DOM and inorganic colloids, and thus offers clear insight into their bioavailability in soils. This method also facilitates a better understanding of the effects of extractants on estimating TE bioavailability.
The effective thermal conductivity (λeff) of sands is a critical parameter required by applications in geothermal energy resources, geo-technique and geo-environment and in science disciplines. ...However, the availability of the reliable λeff data is not sufficient and predictive models are usually used in practice to estimate λeff. These predictive models may vary in complexity, flexibility, accuracy and applications. There is no universal model that can be applied to all soil types and full water content range. The choice of different models may result in distinctive estimates of λeff. The objectives of this study were to conduct an extensive review of the thermal conductivity models of sands and evaluate their performance with a large dataset consisting of various sand types from dry to saturation. A total of 14 models to predict λeff of sands were evaluated with a large compiled dataset consisting of 1025 measurements on 62 sands from 20 studies. The results show that the models of Chen 2008 (CS2008) and Zhang et al. 2016 (ZN2016) give the best estimates of thermal conductivity of sands, with Nash–Sutcliffe efficiency = 0.9 and RMSE = 0.3 W m−1 °C−1. These two models are potentially applied to accurately estimate thermal conductivity of sands of different types.
Effective soil thermal conductivity (
λ
eff
) describes the ability of a multiphase soil to transmit heat by conduction under unit temperature gradient. It is a critical parameter for environmental ...science, earth and planetary science, and engineering applications. Numerous models are available in the literature, but their applicability is generally restricted to certain soil types or water contents (
θ
). The objective of this study was to develop a new model in the similar form of the
Johansen 1975
model to simulate the
λ
eff
(
θ
) relationship of soils of various soil textures and water contents. An exponential type model with two parameters is developed and a new function for calculating dry soil thermal conductivity is presented. Performance of the new model and six other normalized models were evaluated with published datasets. The results show that the new model is able to well mimic
λ
eff
(
θ
) relationship of soils from sand to silt loam and from oven dry to full saturation. In addition, it has the best performance among the seven models under test (with root-mean-square error of 0.059 W m
−1
°C
−1
, average deviations of 0.0009 W m
−1
°C
−1
, and Nash–Sutcliffe efficiency of 0.994). The new model has potential to improve the reliability of soil thermal conductivity estimation and be incorporated into numerical modeling for environmental, earth and engineering studies.
PDF
