Soil Thermal Diffusivity Research Articles

Evaluation of soil thermal diffusivity algorithms at two equatorial sites in West Africa

<p>This study presents comparisons between six algorithms used in the calculation of apparent thermal diffusivity (K<sub>h</sub>) of the topsoil during measurement campaigns conducted at two equatorial sites. It further investigates the effects of transient and seasonal variations in soil moisture content (theta) on the estimation of K<sub>h</sub>. The data used comprise soil temperatures (T) measured at depths of 0.05 m and 0.10 m, and theta within the period of transition from the dry season to the wet season at Ile Ife (7.55˚ N, 4.55˚ E), and for the peak of the wet season at Ibadan (7.44˚ N, 3.90˚ E). The thermal diffusivity, K<sub>h</sub>, was calculated from six algorithms, of: harmonic, arctangent, logarithmic, amplitude, phase, and conduction-convection. The reliability of these algorithms was tested using their values to model T at a depth of 0.10 m, where direct measurements were available. The algorithms were further evaluated with statistical indices, including the empirical probability distribution function of the differences between the measured and modeled temperatures ([delta capitalized]T). The maximum absolute values of [delta capitalized]T for the six algorithms investigated were: 0.5˚C, 0.5˚C, 0.5˚C, 1˚C, 1˚C and 1˚C, respectively. K<sub>h</sub> showed an increasing trend as theta increased from the dry season to the peak of the wet season, with R<sup>2</sup> = 0.70 for the harmonic algorithm. The accuracy of all of the algorithms in modeling T reduced with transient variations of theta. The harmonic, arctangent and logarithmic algorithms were the most appropriate for calculating K<sub>h</sub> for the region of study. The empirical relation between theta and K<sub>h</sub> and the values of K<sub>h</sub> obtained in this study can be used to improve the accuracy of meteorological and hydrological models.</p>

A practical approach to predict soil temperature variations for geothermal (ground) heat exchangers applications

The paper aims at improving a model predicting daily soil temperatures depending on depth and time. The thermal behavior of the ground (near the surface) as a function of depth and time is difficult to simulate from one point since there are many parameters such as short term weather variations, seasonal variations, moisture content of soil, and thermal conductivity of soil etc. affecting on the temperature of ground. The main drawback of this manuscript is that it claims that the improved model will provide the researchers with easily accessible predictions of daily soil temperature variations, which were modeled from daily fluctuations in air temperatures using a sinusoidal function of time and depth. Transient heat flow principles were used with assumptions of one dimensional heat flow, homogeneous soil, and constant thermal diffusivity. Measured and predicted soil temperatures at depths 5cm, 10cm, 20cm and 300cm were compared with experimental field results to validate the accuracy of the current model. For an annual cycle; at depth 5cm, 10cm, 20cm, and 300cm the average maximum percentage of errors were 10.78%, 10%, 10.26%, and 14.95%, respectively. Soil temperature measurements at 3m depth were made on the earth to air heat exchanger system (EAHE) installed in the Solar Energy Institute in Ege University, Bornova, Izmir. Daily average soil temperatures at depths 5cm, 10cm, and 20cm were taken from Izmir State Meteorological Station. Finally, we analyzed solar fluctuations on soil temperature as a function of depth from 5cm to 300cm, and time, gave soil temperature as a function of time up to 1year (8760h) for the following depths z=50cm, 100cm, 300cm, 500cm, and 1000cm.

Soil thermal diffusivity estimated from data of soil temperature and single soil component properties

Under field conditions, thermal diffusivity can be estimated from soil temperature data but also from the properties of soil components together with their spatial organization. We aimed to determine soil thermal diffusivity from half-hourly temperature measurements in a Rhodic Kanhapludalf, using three calculation procedures (the amplitude ratio, phase lag and Seemann procedures), as well as from soil component properties, for a comparison of procedures and methods. To determine thermal conductivity for short wave periods (one day), the phase lag method was more reliable than the amplitude ratio or the Seemann method, especially in deeper layers, where temperature variations are small. The phase lag method resulted in coherent values of thermal diffusivity. The method using properties of single soil components with the values of thermal conductivity for sandstone and kaolinite resulted in thermal diffusivity values of the same order. In the observed water content range (0.26-0.34 m³ m-3), the average thermal diffusivity was 0.034 m² d-1 in the top layer (0.05-0.15 m) and 0.027 m² d-1 in the subsurface layer (0.15-0.30 m).

Soil Thermal Diffusivity of a Gleyic Solonetz Soil Estimated by Different Methods in the Brazilian Pantanal

The soil temperature is an important microclimatic factor due to the interactions between soil and plant, and the energy exchange with the atmosphere. The soil energy exchange is affected by the incident solar radiation, type of coverage and mainly by the soil thermal properties. Among the soil thermal properties, the soil thermal diffusivity is highlighted because it affects the soil temperature profile and soil heat flux transport and distribution. Thus, the aim of this study was to evaluate different estimates of soil thermal diffusivity of a Gleyic Solonetz soil in the Brazilian Pantanal. The soil thermal diffusivity was determined by the amplitude, logarithmic, arctangent and the phase methods between 0.01 and 0.03 m, 0.01 and 0.07 m and 0.01 and 0.15 m depth. The soil thermal diffusivity estimated by the four methods showed significant differences and varied over the study period as a function of volumetric soil water content. The soil thermal diffusivity estimated by logarithmic methodshowed better performance at different depths, followed by the method of phase.

Reconstructing Terrestrial Environments Using Stable Isotopes in Fossil Teeth and Paleosol Carbonates

Carbon isotopes in Neogene-age fossil teeth and paleosol carbonates are commonly interpreted in the context of past distributions of C3 and C4 vegetation. These two plant types have very different distributions in relation to climate and ecology, and provide a robust basis for reconstructing terrestrial paleoclimates and paleoenvironments during the Neogene. Carbon isotopes in pre-Neogene fossil teeth are usually interpreted in the context of changes in the δ13C value of atmospheric CO2, and variable climate-dependent carbon-isotope discrimination in C3 plants. Carbon isotopes in pre-Neogene soil carbonates can be used to estimate past levels of atmospheric CO2. Oxygen isotopes in fossil teeth and paleosol carbonates primarily are influenced by the oxygen isotopic compositions of ancient rainfall and surface waters. The oxygen isotopic composition of rainfall is has a complex, but tractable, relationship with climate, and variably relates to temperature, elevation, precipitation amount, and other factors. Mammal species that rely on moisture in dietary plant tissues to satisfy their water requirements (rather than surface drinking water) may have oxygen isotopic compositions that track aridity. Thus, oxygen isotopes of fossil mammals can place broad constraints on paleoaridity. Carbonate clumped isotope thermometry allows for reconstruction of soil temperatures at the time of pedogenic carbonate mineralization. The method is unique because it is the only thermodynamically based isotopic paleothermometer that does not require assumptions about the isotopic composition of the fluid in which the archive mineral formed. Soil temperature reflects a complex interplay of air temperature, solar radiative heating, latent heat effects, soil thermal diffusivity, and seasonal variations of these parameters. Because plants and most animals live in and/or near the soil, soil temperature is an important aspect of terrestrial (paleo)climate.

A thermal response method of calculating a soil's thermal properties when backfill material information is unavailable

The accurate definition of soil thermal properties around a borehole is helpful when designing a ground source heat pump system. Existing thermal response methods for obtaining a soil's thermal properties require knowledge of the backfill material's conductivity, which is difficult for a technician to obtain in situ. This study developed a new method to calculate a soil's thermal diffusivity when the backfill material's thermal conductivity in the borehole is unavailable. The developed model was verified by a theoretical calculated method. An experiment was conducted in situ to measure a soil's thermal conductivity for use with a ground source heat pump system and the results were used to verify the proposed method. The soil conductivity was measured as 1.98W/(mK) and the thermal diffusivity was 2.79×10−7m2/s when the backfill material's thermal conductivity was available, while the new method gave a thermal diffusivity of 2.81×10−7m2/s. The results indicated that the proposed method would be useful in future engineering projects, especially those lacking information on a backfill material's properties.

Effect of Soil Moisture on Soil Temperature Field Near Buried Pipe

System effectiveness and useful life of heat pump are directly affected by whether the design of ground heat exchanger is reasonable or not. The efficiency of heat exchanger has a close relationship with soil thermal conductivity coefficient and heat diffusivity, while soil moisture content affects soil thermal conductivity coefficient and soil temperature field. In this paper, we perform numerical simulation on CFD software. Then we study the soil temperature changes through field experiment in different soil moisture content on field experiment and finally obtained the relationships of the moisture content with the single U ground soil temperature field.

Soil thermal conductivity prediction for district heating pre-insulated pipeline in operation

The research refers to the district heating (DH) system in Ljubljana, which includes 245km of highly diversified pipelines. The purpose of this study was to determine the effect of the soil thermal conductivity coefficient (λs) on the heat loss from pre-insulated pipes during operation. Pipeline geometry, material properties (particularly insulation and soil thermal conductivity) and time-dependent data on supply, return and environs temperature were considered. Measurements of temperature, moisture, thermal conductivity of soil and heat flux through the soil were carried out at the chosen locations on the pre-insulated pipeline. In addition, laboratory measurements were conducted on the soil samples from this site in order to determine the soil density, specific heat and thermal diffusivity. For the evaluation of heat loss, transient and steady-state numerical simulations of the soil temperature field were performed. In transient simulations, in addition to the impact of environment temperature, the influence of supply and return temperatures was taken into account. A method for λs prediction during pipeline operation is presented. The algorithm is based on a comparison of the measured (Θexp) and simulated (Θsim) temperatures in the selected period of time with the same boundary conditions.

Temperatures and Thermal Diffusivity within a Rangeland Soil Near Oracle, Arizona

Soil temperatures are typically measured at shallow depths near the soil surface where large diurnal variations occur. For depths deeper than about 50 cm analytical and numerical models are often used to simulate the annual variations in daily temperature, which require information about the soil thermal diffusivity (D). An analytic solution to the onedimensional Fourier heat conduction equation was used by Matthias and Warrick (1987) to simulate daily soil temperatures at 20 and 100 cm depths at Safford, Arizona, and at 20 cm depth at Yuma, Arizona, using observed daily soil temperatures at 10 cm depth at each location and an estimate of the average soil thermal diffusivity as inputs. The solution was the sum of a deterministic (mean annual wave) component and a stochastic (daily fluctuations about the mean wave) component. The purpose of the research described in this paper is to use the model described by Matthias and Warrick (1987) to calculate the average thermal diffusivity for a semi-arid rangeland soil at the Page Ranch near Oracle, Arizona. The data used in this analysis were the daily soil temperatures at 50, 100, 300, and 500 cm depths observed during a one-year period from July 1, 1983 to June 30,1984 at the site. To obtain the average D, the daily temperatures at 50 cm depth and an initial estimate of D were input to the model to simulate temperatures at the 100, 300, and 500 cm depths. Observed and simulated temperatures at each depth were then compared. If the root-mean-square-deviations (RMSD) between observed and simulated values were large then an updated value of D was input to the model and temperature values recalculated. This trial-and-error approach continued until RMSD values were minimized. With D∼500 cm2 d-1 good agreement between observed and simulated temperatures was achieved with RMSD values ranging from 0.38 to 1.35 °C for the three depths.

Soil profile method for soil thermal diffusivity, conductivity and heat flux: Comparison to soil heat flux plates

Diffusive heat flux at the soil surface is commonly determined as a mean value over a time period using heat flux plates buried at some depth (e.g., 5–8cm) below the surface with a correction to surface flux based on the change in heat storage during the corresponding time period in the soil layer above the plates. The change in heat storage is based on the soil temperature change in the layer over the time period and an estimate of the soil thermal heat capacity that is based on soil water content, bulk density and organic matter content. One- or multiple-layer corrections using some measure of mean soil temperature over the layer depth are common; and in some cases the soil water content has been determined, although rarely. Several problems with the heat flux plate method limit the accuracy of soil heat flux values. An alternative method is presented and this flux gradient method is compared with soil heat flux plate measurements. The method is based on periodic (e.g., half-hourly) water content and temperature sensing at multiple depths within the soil profile and a solution of the Fourier heat flux equation. A Fourier sine series is fit to the temperature at each depth and the temperature at the next depth below is simulated with a sine series solution of the differential heat flux equation using successive approximation of the best fit based on changing the thermal diffusivity value. The best fit thermal diffusivity value is converted to a thermal conductivity value using the soil heat capacity, which is based on the measured water content and bulk density. A statistical analysis of the many data resulting from repeated application of this method is applied to describe the thermal conductivity as a function of water content and bulk density. The soil heat flux between each pair of temperature measurement depths is computed using the thermal conductivity function and measured water contents. The thermal gradient method of heat flux calculation compared well to values determined using heat flux plates and calorimetric correction to the soil surface; and it provided better representation of the surface spatiotemporal variation of heat flux and more accurate heat flux values. The overall method resulted in additional important knowledge including the water content dynamics in the near-surface soil profile and a soil-specific function relating thermal conductivity to soil water content and bulk density.

The sensitivity of ground surface temperature prediction to soil thermal properties Using the Simple Biosphere Model (SiB2)

Using the Simple Biosphere Model (SiB2), soil thermal properties (STP) were examined in a Tibetan prairie during the monsoon period to investigate ground surface temperature prediction. We improved the SiB2 model by incorporating a revised force-restore method (FRM) to take the vertical heterogeneity of soil thermal diffusivity (k) into account. The results indicate that (1) the revised FRM alleviates daytime overestimation and nighttime underestimation in modeled ground surface temperature (Tg), and (2) its role in little rainfall events is significant because the vertical gradient of k increases with increasing surface evaporation. Since the original formula of thermal conductivity (λ) in the SiB2 greatly underestimates soil thermal conductivity, we compared five algorithms of λ involving soil moisture to investigate the cause of overestimation during the day and underestimation at night on the basis of the revised FRM. The results show that (1) the five algorithms significantly improve Tg prediction, especially in daytime, and (2) taking one of these five algorithms as an example, the simulated Tg values in the daytime are closer to the field measurements than those in the nighttime. The differences between modeled Tg and field measurements are mostly within the margin of error of ±2 K during 3 August to 4 September 1998.

Thermal diffusivity of plowed leached meadow-chernozemic soils in the Adygeya Republic

Thermal diffusivity of the upper horizons of leached meadow-chernozemic soils varies in dependence on the soil water content within the following limits: 1.20–4.11 × 10−7 m2/s for the Ap horizon, 1.21–3.85 ×10−7 m2/s for the A1 horizon, and 1.35–3.73 × 10−7 m2/s for the A1B horizon. The relationships between the thermal diffusivity and the soil water content are described by S-shape curves with a long gently inclined segment within the range of water contents of 0.30–0.35 cm3/cm3) water contents. The thermal diffusivity of air-dried soil samples correlates with the physical clay (<0.01 mm) content. The Pearson correlation coefficient for these two variables equals −0.67 and is statistically significant at the significance level of 0.05. Regression equations allowing one to calculate the thermal diffusivity of the investigated soil horizons on the basis of data on the soil water content have been obtained.

Parameter estimation of in-situ thermal response tests for borehole ground heat exchangers

This paper discusses some aspects of parameters estimation used in in-situ thermal response tests of ground heat exchangers, including sensitivity analysis and comparison of iterative minimization algorithms. First, several sensitivity coefficients of parameters and uncertainties occurring in in-situ tests are examined in depth. Starting from an analytical heat transfer model of borehole ground heat exchangers, sensitivity coefficients for single U-tube ground heat exchangers are of analytical forms. The sensitivity analysis provides some general and new guidelines for mitigating the influence of testing uncertainties. Next, Monte Carlo simulation is performed to evaluate reliability of two powerful minimization algorithms, the Levenberg–Marquardt method and a trust region method subject to bounds. The Monte Carlo simulation shows that if thermal diffusivity of soil is an estimated parameter, the Levenberg–Marquardt method may result in unreliable results, and its performance depends strongly on the quality of the initial guessed values. In contrast, the interior trust region method considered in this paper can produce more reliable results, and its performance depends on the range of input parameters bounds. Finally, feasibility of the highlighted methodology is illustrated by applying it to two real in-situ thermal response tests.

Coupled land-atmosphere modeling of the effects of shrub encroachment on nighttime temperatures

Changes in vegetation cover affect the interactions between the land surface and the overlying atmosphere with important impacts on surface energy balance and microclimate conditions. A major ongoing change in vegetation cover has been observed in dryland regions around the world, where desert shrubs are encroaching into arid grasslands. However, the impact of shrub encroachment on local climate has not been investigated. We used a mesoscale model coupled with a Land Surface Model to simulate the effects of shrub encroachment on nighttime temperatures. These effects can have an important effect on the establishment of shrubs and need to be represented well by land surface parameterization schemes that are also used in long-term climate simulations. Idealized 2-dimensional simulations were conducted with vegetation types corresponding to shrubland and grassland typical of the Northern Chihuahuan Desert. Simulated surface energy and radiation fluxes and near-ground air temperature were analyzed and compared with observations. Results show a good comparison between the simulations and observations as long as vegetation parameters are adjusted in the model to be in better agreement with the observed parameters. The sensitivity of the nighttime air temperatures to green vegetation fraction, albedo, emissivity and roughness length is investigated. The results indicate that the green vegetation fraction is the key factor that causes the higher nighttime temperature in shrubland than in adjacent grassland, mainly by its effects on soil surface insulation, soil thermal diffusivity, and therefore on ground heat fluxes.

단일 탐침법을 이용한 수평형 지중열교환기 뒤채움재의 열확산계수 산정

Storage and transfer heat in soils is governed by the soil thermal properties and these properties are therefore needed in many engineering applications, including horizontal ground heat exchanger for ground-coupled heat pumps. This paper presents the evaluation results of the thermal diffusivity of soils (silica, quartzite, limestone, sandstone, granite, and two masonry soils used for the trench backfilling materials of the horizontal ground heat exchanger. To assess this thermal property, we (i) measure the soil thermal conductivities using single-probe method and (ii) use the de Vries method of summing the heat capacities of the soil constituents. The results show that the thermal diffusivity tends to increase as dry soil begins to wet, but it approaches a constant value or even decreases as the soil continues to wet. Combined algorithm with and improved model for the thermal conductivity of soils and the constituent equation provides accurate estimates of the soil thermal diffusivity.

Variability of soil moisture and its relationship with surface albedo and soil thermal diffusivity at Astronomical Observatory, Thiruvananthapuram, south Kerala

Continuous observation data collected over the year 2008 at Astronomical Observatory, Thiruvananthapuram in south Kerala (76°59′E longitude and 8°30′N latitude) are used to study the diurnal, monthly and seasonal soil moisture variations. The effect of rainfall on diurnal and seasonal soil moisture is discussed. We have investigated relationships of soil moisture with surface albedo and soil thermal diffusivity. The diurnal variation of surface albedo appears as a U-shaped curve on sunny days. Surface albedo decreases with the increase of solar elevation angle, and it tends to be a constant when solar elevation angle is greater than 40°. So the daily average surface albedo was calculated using the data when solar elevation angle is greater than 40°. The results indicate that the mean daily surface albedo decreases with increases in soil moisture content, showing a typical exponential relation between the surface albedo and the soil moisture. Soil thermal diffusivity increases firstly and then decreases with the increase of soil moisture.

Greenhouse gases fluxes and soil thermal properties in a pasture in central Missouri

Fluctuations of greenhouse gases emissions and soil properties occur at short spatial and temporal scales, however, results are often reported for larger scales studies. We monitored CO 2,CH 4, and N 2O fluxes and soil temperature ( T), thermal conductivity ( K), resistivity ( R) and thermal diffusivity ( D) from 2004 to 2006 in a pasture. Soil air samples for determination of CO 2,CH 4 and N 2O concentrations were collected from static and vented chambers and analyzed within two hours of collection with a gas chromatograph. T, K, R and D were measured in-situ using a KD2 probe. Soil samples were also taken for measurements of soil chemical and physical properties. The pasture acted as a sink in 2004, a source in 2005 and again a sink of CH 4 in 2006. CO 2 and CH 4 were highest, but N 2O as well as T, K and D were lowest in 2004. Only K was correlated with CO 2 in 2004 while T correlated with both N 2O( r = 0.76, p = 0.0001) and CO 2 ( r = 0.88, p = 0.0001) in 2005. In 2006, all gases fluxes were significantly correlated with T, K and R when the data for the entire year were considered. However, an in-depth examination of the data revealed the existence of month-to-month shifts, lack of correlation and differing spatial structures. These results stress the need for further studies on the relationship between soil properties and gases fluxes. K and R offer a promise as potential controlling factors for greenhouse gases fluxes in this pasture.

Variability of soil moisture and its relationship with surface albedo and soil thermal parameters over the Loess Plateau

Data from July 2006 to June 2008 observed at SACOL (Semi-Arid Climate and Environment Observatory of Lanzhou University, 35.946°N, 104.137°E, elev. 1961 m), a semi-arid site in Northwest China, are used to study seasonal variability of soil moisture, along with surface albedo and other soil thermal parameters, such as heat capacity, thermal conductivity and thermal diffusivity, and their relationships to soil moisture content. The results indicate that surface albedo decreases with increases in soil moisture content, showing a typical exponential relation between the surface albedo and the soil moisture. The heat capacity, the soil thermal diffusivity, and soil thermal conductivity show large variations between Julian day 90–212 and 450–578. The soil thermal conductivity is found to increase as a power function of soil moisture. Soil heat capacity and soil thermal diffusivity increase with increases in soil moisture. The SACOL observed soil moisture are also used to validate the AMSR-E/AQUA retrieved soil moisture and there is good agreement between them. The analysis of the relationship between satellite retrieved soil moisture and precipitation suggests that the variability of soil moisture depends on the variation of precipitation over the Loess Plateau.

Parameterization and mathematical modeling of the dependence of soil thermal diffusivity on the water content

Functional dependences of the thermal diffusivity of soil horizons on their water contents obtained via parameterization of experimental curves are used for the mathematical modeling of the soil temperature regime. If there are no experimental data on thermal diffusivity, parameters of the functional dependence may be calculated from data on the major soil properties. A lognormal function describes experimental dependences of the thermal diffusivity of soil horizons on their water content more accurately than power and polynomial functions. Regression equations making it possible to calculate the thermal diffusivity of gray forest soils on the basis of data on their bulk density, water content, organic matter content, and particle-size distribution are suggested.

Comparison of two soil temperature algorithms for a bare ground site on the Loess Plateau in China

Two thermal transfer algorithms for soil are used to investigate the diurnal vertical temperature variation in the common case of a vertically heterogeneous thermal diffusivity and the considerable liquid water flux which generally exists in soil when surface evaporation is large. One algorithm assumes that soil is vertically homogenous and takes into account only thermal conduction, and the other, developed in our recent study, considers the vertical heterogeneity of thermal diffusivity in soil and couples thermal conduction and convection (e.g., heat transfer by water flux). Theoretically the two methods are identical for vertically homogenous dry soil. On the basis of soil temperature data collected at a bare soil site over the Loess Plateau of China during the period from DOYs 197 to 241, 2005, we found that the new algorithm gives a realistic estimate of soil temperature while the previous one, on average, overestimates either the diurnal amplitude by 0.95 K or the phase shift by 0.207 rad (i.e., 47.44 min) at the soil depth of 0.10 m. Using the new algorithm and measurements of soil temperature, we determine the soil thermal diffusivity and a variable that represents the sum of the vertical gradient of soil thermal diffusivity and water flux density at three levels within the first 0.40 m of the soil surface. We also simulate the soil temperature for the depths of 0.20 m and 0.40 m, and the results are in satisfactory agreement with direct measurements. The main contribution here is to provide analytic insight into the role of heterogeneity and some simple formulae as tools for interpretation of the role of heterogeneity in observed diurnal temperature variations.