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A finite element mesh used to investigate the effects of axial conduction of heat in the thermistor needle. The transport domain is axisymmetrical around the vertical axis. Open squares indicate locations where temperature changes were observed, while open circles correspond to observation nodes (ON) in Figure 2.
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1] The heat pulse probe (HPP) has received more attention as it allows in situ, simultaneous, and automated measurements of soil hydraulic and thermal properties, as well as soil water fluxes. Although the currently used design allows many applications, changes in HPP design and analyses are needed to increase the sensitivity to smaller water fluxe...
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Context 1
... avoid the need for a full three-dimensional simulation, an axisymmetric simulation domain that con- sisted only of the thermistor needle and the surrounding soil was used to investigate the influence of the axial conduction of heat on temperature profiles within the thermistor needle. Figure 3 shows the finite element mesh for the resulting computational domain. The small layer of the soil (0.25 mm thickness) had to be included into the transport domain so that heat could be redistributed within a needle and back to the soil. ...
Context 2
... temperatures at seven observation nodes in Figure 2 for case (a) and the interpolated values were prescribed as boundary conditions along the outside boundary of the transport domain. Temperature changes at three locations correspond to ON2, ON4, and ON6 in Figure 2 (5, 15, and 25 mm from the bottom of the domain as shown in Figure 3), in the center of the thermistor needle were calculated and com- pared to those at the domain boundary. ...
Context 3
... calculations did not account for the axial heat conduction in the thermistor needle. The impact of the axial conduction for case (a), Figure 6, is shown in Figure 7 where temperatures in the Figure 7. Temperatures (open symbols) at three locations correspond to ON2, ON4, and ON6, respectively, (5, 15, and 25 mm from the bottom of the domain in Figure 3) at the center of the thermistor needle. Lines indicate temperatures at corresponding observation nodes (ON) at the boundary (using numerical solution of Figure 6a). ...
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Citations
... The needles of length = 3.0 cm were constructed from stainlesssteel tubing (1.28 mm o.d. and 0.84 mm i.d.) and filled with thermally conductive epoxy. The sense thermistor was placed in the geometric middle of each needle to prevent edge effects associated with heat conduction, and the needles were filled with thermal epoxy (Saito et al., 2007). The nominal spacing between the heater needle and the sense needle was 6 mm. ...
... Following Campbell et al. (1991), calibration was conducted to find r initial using a 5 g L −1 agar gel solution. The thermal conductivity k of the agar gel was taken to be the same as the thermal conductivity of water (Saito et al., 2007). Reported values for thermal conductivity (Ramires et al., 1995) and heat capacity (Wagner and Pruß, 2002) of water were used. ...
A sensor comprised of an electronic circuit and a hybrid single and dual heat pulse probe was constructed and tested along with a novel signal
processing procedure to determine changes in the effective dual-probe spacing radius over the time of measurement. The circuit utilized
a proportional–integral–derivative (PID) controller to control heat inputs into the soil medium in lieu of a variable resistor. The system was
designed for onboard signal processing and implemented USB, RS-232, and SDI-12 interfaces for machine-to-machine (M2M) exchange of data, thereby
enabling heat inputs to be adjusted to soil conditions and data availability shortly after the time of experiment. Signal processing was introduced
to provide a simplified single-probe model to determine thermal conductivity instead of reliance on late-time logarithmic curve fitting. Homomorphic
and derivative filters were used with a dual-probe model to detect changes in the effective probe spacing radius over the time of experiment to
compensate for physical changes in radius as well as model and experimental error. Theoretical constraints were developed for an efficient inverse
of the exponential integral on an embedded system. Application of the signal processing to experiments on sand and peat improved the estimates of
soil water content and bulk density compared to methods of curve fitting nominally used for heat pulse probe experiments. Applications of the
technology may be especially useful for soil and environmental conditions under which effective changes in probe spacing radius need to be detected and
compensated for over the time of experiment.
... In addition, HP method assumes a local thermal equilibrium condition during the period of measurement [107], however, local thermal non-equilibrium condition is common under field conditions [80,108,109]. These constraints imposed by most analytical solutions can be eliminated by the numerical approach [91,110]. For instance, Hopmans et al. [83] used HYDRUS 2D to inversely model the influences of DPHP probe geometry on water flux and thermal properties of soil. ...
... Mortensen et al. [90] took use of a approach of similar manner in a soil column experiment to analyze the feasibility of multiple-function DPPHP to predict hydraulic, thermal, and solute transport. Saito et al. [110] investigated the influences of heat pule induced vapor and geometry of probe on soil water flux and thermal properties in unsaturated soils with the HYDRUS 2D program. Their results showed that a combination of a larger probe diameter and a stronger heat pulse can improve the estimates of water flux if vapor transport is taken into accounted. ...
... The needles of length 3.0 cm = were constructed from stainless-steel tubing (1.28 mm OD and 0.84 mm ID) and filled with thermally-conductive epoxy. The sense thermistor was placed in the geometric middle of each needle to prevent edge effects associated with heat conduction and the needles were filled with 330 thermal epoxy (Saito et al., 2007). The nominal spacing between the heater needle and the sense needle was 6 mm . ...
... Following Campbell et al. (1991), calibration was conducted to find initial r using a 5 g/L agar gel solution. The thermal conductivity k of the agar gel was taken to be the same as the thermal conductivity of water (Saito et al., 2007). Reported values for thermal conductivity (Ramires et al., 1995) and heat capacity (Wagner and Pruß, 2002) of water were used. ...
Abstract. A sensor comprised of an electronic circuit and a hybrid single and dual heat pulse probe was constructed and tested along with a novel signal processing procedure to determine changes in the effective dual-probe spacing radius over the time of measurement. The circuit utilized a proportional–integral–derivative (PID) controller to control heat inputs into the soil medium in lieu of a variable resistor. The system was designed for on-board signal processing and implemented USB, RS-232 and SDI-12 interfaces for Machine-to-Machine (M2M) exchange of data, thereby enabling heat inputs to be adjusted to soil conditions and data availability shortly after the time of experiment. Signal processing was introduced to provide a simplified single-probe model to determine thermal conductivity instead of reliance on late-time logarithmic curve-fitting. Homomorphic and derivative filters were used with a dual-probe model to detect changes in the effective probe spacing radius over the time of experiment to compensate for physical changes in radius as well as model and experimental error. Theoretical constraints were developed for an efficient inverse of the exponential integral on an embedded system. Application of the signal processing to experiments on sand and peat improved the estimates of soil water content and bulk density compared to methods of curve-fitting nominally used for heat pulse probe experiments. Applications of the technology may be especially useful for soil and environmental conditions where effective changes in probe spacing radius need to be detected and compensated over the time of experiment.
... Since the proposal of the method, significant efforts have been devoted to sensor construction [2,20,8,19,17,9], error analysis [10,11,13] and practical applications [1,18,12,23]. In order to measure moisture content in non-hygroscopic insulation materials, a transient hot-wire method with heating for a period of 20 min was adopted [21]. ...
Porous insulation materials may acquire moisture, and the moisture content must be accurately measured for appropriate maintenance of the materials. Current thermal methods for measuring moisture are applicable only to an infinite test domain. This paper used computational fluid dynamics (CFD) to investigate the effects of a finite test domain and the associated boundary heat loss on moisture measurement. Insulation material of various thicknesses, bounded by two solid plates, was modeled. The convective heat loss to the air from both solid plates was considered. The over-measured moisture content due to a finite geometric domain was regressed into formulas, by means of which the excessive amount could subsequently be deduced. The corrected moisture content was then compared with that obtained by gravimetric weighing using a digital precision balance. The results show that significant over-measurement of moisture content can occur for the tested insulation material with a thickness less than 4.5 cm. The remedial strategy is quite effective and can provide moisture content results that are close to the gravimetric values.
... An advantage of using a numerical approach to analyze data collected with the HP method is the elimination of constraints on needle geometry and boundary and initial conditions as imposed by most analytical solutions (Papadakis et al., 1990;H. Saito et al., 2007). Hopmans et al. (2002) took full advantage of numerical solutions (HYDRUS 2D finite element) and inverse modeling to examine the effect of probe geometry on soil thermal properties and water flux estimation using the 3-needle HP probe of Ren et al. (2000). Mortensen et al. (2006) used a similar approach (inverse modeling, HYDRUS 2D) to ...
... They found that the sensor was able to estimate thermal, hydraulic, and solute transport properties in soils. H. Saito et al. (2007) examined the effect of probe geometry, heater probe-induced evaporation, and vapor flow ...
... sulation and water resistance. Probes of various designs have been developed during the past few decades. Figure 5 displays some examples of the basic designs of several recent probes. The materials and criteria used for making HP probes and their performances have been investigated by many researchers (e.g., Ham & Benson, 2004;X. Liu et al., 2008;H. Saito et al., 2007;Wechsler, 1966;X. Zhang et al., 2012). This section focuses on probe geometries, heaters, temperature sensors, circuits, integration of HP with TDR, and probe performances. Probe geometry will be discussed separately for the SPHP and DPHP probes according to the sources of errors. A summary of selected studies that have used HP probes ar ...
Time series of precipitation tritium contents are often used for groundwater recharge estimation based on the tritium mass ratio of the (un)saturated zones to precipitation. But records of the precipitation tritium measurements are sparse and often need to be reconstructed. Uncertainties associated with reconstructed records can affect the recharge estimates, but this has received little attention. Here we leverage four >15 m deep, exceptionally well preserved unsaturated zone tritium profiles to quantify the uncertainty in Tritium mass balance (TMB) from precipitation tritium reconstruction. The tritium profiles have bomb tritium peaks at 7.2−10.5 m below the surface and peaks ranging from 46 to 235 TU. We first estimate the diffuse recharge by the tritium peak method. Since this method is independent of any precipitation tritium reconstruction, the estimated recharge was used as ‘truth’ to evaluate four precipitation tritium reconstruction methods: two interpolation methods and two reference curve methods. Direct comparison between the observed and simulated precipitation tritium showed that the reference curve methods performed more poorly than the interpolation methods. Indirect evaluation by comparing the recharge rates estimated by the tritium storage method with our truth measurements showed that tritium storage method overestimated recharge by 100% to 200%. Our results suggest that the atmospheric tritium flux was greatly underestimated, especially by the reference curve methods. As such, groundwater recharge at our sites would be overestimated. This has implications for using these standard approaches elsewhere.
... The commonly used numerical approaches are finite difference and finite element methods. Initial and boundary conditionsneed to be carefully set, and the choice for discrete An advantage of using a numerical approach to analyze data collected with the HP method is the elimination of constraints on needle geometry, and boundary and initial conditions as imposed by most analytical solutions (Papadakis et al., 1990;Saito et al., 2007). ...
... Figure 5 displays someexamples of thebasic designsof several recent probes. The materials and criteria used for making HP probes and their performances have been investigated by many researchers (e.g., Wechsler, 1966;Ham &Benson, 2004;Saito et al., 2007;Liuet al., 2008aLiuet al., , 2008bZhang et al., 2012). This section focuses on probe geometries, heaters, temperature sensors, circuits, integrationof HP with TDR, and probe performances. ...
... Any changes to the boundary conditions and/or introduction of new processes (e.g., phase changes) may preclude the use of analytical solutions. Thus numerical solutionsare required (Kamai & Hopmans, 2007;Saito et al., 2007). In fact, numerical simulationcan be a more efficient design approachthan to physically makea number of prototype sensors, because numerical simulations can take into account the effects of probe materials, diameter/length, spacing, contact resistance, phase change, and even probe distributionon soil or water flow, and the optimized design can be selected from simulated scenarios (Mortensen et al., 2006;Kamai & Hopmans, 2007;Liu et al., 2007;Saito et al., 2007). ...
• Soil thermal properties are required in environmental, Earth and planetary science, and engineering applications
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• The heat pulse method is a transient method that can be used for measuring estimating soil thermal properties, a variety of other physical and hydraulic parameters
• The development history of the heat pulse method over the past 130 years is summarized, the probe design, construction, calibration and applications of the heat pulse method in unfrozen and frozen soils are presented, and limitations and perspectives of the technique are discussed
... A study by Liu et al. (2012) attributes the overestimations of water content as being due to differences in finite thermal contact between the probes and the soil and the influence of heat probe body during application, especially when using the infinite line heat source model, as shown in our results. The concept has also been confirmed by Ham and Benson (2004) and numerical simulations conducted by Saito et al. (2007), who state that "the temperature response in the HPP body is very sensitive to epoxy type and whether the body is heated or not" and "temperature measurements are influenced by the difference in thermal properties of the HPP body." If the probe body is indeed absorbing generated heater outputs, and not at a fixed rate (due to the relationship between the thermal properties of the probe and the varying thermal properties of the soil), this would cause a systematic error in any material not closely resembling that during calibration. ...
... If the probe body is indeed absorbing generated heater outputs, and not at a fixed rate (due to the relationship between the thermal properties of the probe and the varying thermal properties of the soil), this would cause a systematic error in any material not closely resembling that during calibration. Furthermore, Saito et al. (2007) conclude temperature response of the thermistor is a function of thermistor placement (i.e., distance from probe body) which could account for such varying q' and r eff terms in our quasiempirical calibration. This concept is fundamental to the heat pulse probe technique and is therefore the basis for other newly devised approaches to analyze heat pulse probe data (Knight et al. 2012) using transformations of Eq. (1). ...
A multi-functional heat pulse probe (MFHPP) can measure soil thermal and hydraulic properties. Though its successful implementation has been documented, previous studies have reported some limitations. One specific cause of the limitations is the absorption of the generated heat pulse within the probe itself and this creates error in the measurements. The objective of this study was to develop and evaluate a new calibration method to account for measurement error due to heat loss to the probe. A MFHPP was constructed and tested in six soil types using both a traditional and the newly-developed calibration method. The new calibration utilizes heat pulse response curves from real soils with thermal conductivities similar to that of the MFHPP rather than the traditional agar stabilized water solution. This new approach significantly reduced average measurement error from 9.1% to 2.4% for heat capacity and 13.5% to 4.5% for volumetric water content.
... For Phase I and II, E tends to be maximal when total heat flux into the soil is greatest (e.g., seasonally in summer and daily at noon), whereas for Phase III, in contrast, E tends to be maximal when total heat flux out of the soil is greatest (e.g., seasonally in winter and daily at midnight). However, as pointed out by [26] and in my own research, due to wrong modeling premises (e.g., the traditional hydraulic functions are assumed to still be suitable for water potentials of <−1.5 × 10 4 cm) or insufficient and inclusive experimental (mostly laboratory soil-column) data, previous studies [22,23,[53][54][55][56][57][58][59][60][61][62][63][64][65][66][67][68][69][70][71] primarily examined and reported dynamics of Phase I and II evaporation. For this reason, the features presented by those researchers are unlikely to be found at any sites under naturally dry conditions, where most of the time a top DSL lies over underlying moist soils and Phase III dominates the soil water evaporation process. ...
Evaporation from bare sandy soils is the core component of the hydrologic cycle in arid environments, where vertical water movement dominates. Although extensive measurement and modeling studies have been conducted and reported in existing literature, the physics of dry soil and its function in evaporation is still a challenging topic with significant remaining issues. Thus, an overview of the previous findings will be very beneficial for identifying further research needs that aim to advance our understanding of the vapor flow resistance (VFR) effect on soil water evaporation as influenced by characteristics of the dry soil layer (DSL) and evaporation zone (EZ). In this regard, six measurement and four modeling studies were overviewed. The results of these overviewed studies, along with the others, affirm the conceptual dynamics of DSL and EZ during drying or wetting processes (but not both) within dry sandy soils. The VFR effect tends to linearly increase with DSL thickness (δ) when δ < 5 cm and is likely to increase as a logarithmic function of δ when δ ≥ 5 cm. The vaporization-condensation-movement (VCM) dynamics in a DSL depend on soil textures: sandy soils can form a thick (10 to 20 cm) DSL while sandy clay soils may or may not have a clear DSL; regardless, a DSL can function as a transient EZ, a vapor condensation zone, and/or a vapor transport medium. Based on the overview, further studies will need to generate long-term continuous field data, develop hydraulic functions for very dry soils, and establish an approach to quantify the dynamics and VFR effects of DSLs during wetting-drying cycles as well as take into account such effects when using conventional (e.g., Penman-Monteith) evaporation models.
... The programs HYDRUS-1D and HYDRUS 2D/3D (Šimů nek et al., 2008) are 1D, 2D and 3D models, which in many cases proved to be efficient tools for simulating water, heat, solute and gas processes in the vadose zone. HYDRUS models were applied for instance to the testing of a new heat sensor (Mortensen et al., 2006;Saito et al., 2007). They were also used to study the impact of temperature on water evapotranspiration (Dahiya et al., 2007;Deb et al., 2011;Saito et al., 2006;Schwartz et al., 2010;Zhao et al., 2010) and soil CO 2 production (Buchner et al., 2008). ...
Different soil covers influence water and thermal regimes in soils within urban areas. Knowledge of these regimes is needed, particularly when assessing effectiveness of energy gathering from soils using horizontal ground heat exchangers. The goal of this study was to calibrate the model HYDRUS-1D for simulating coupled water and thermal regime in Technosol type soils with grass cover, and to use this model for predicting water and thermal regimes under different materials covering the soil surface. For this purpose soil water contents were measured at depths of 10, 20, 30, 40, 60 and 100 cm at 4 locations and temperatures were measured at depths of 20, 40, 80, 120, 150 and 180 cm at three locations (all covered by grass) from June 2011 to December 2012. In addition sensors for simultaneous measuring soil water contents and temperatures were installed under different soil covers (grass, bark chips, sand, basalt gravel and concrete paving) at a depth of 7. The parameters of soil hydraulic properties were obtained on the 100-cm3 undisturbed soil samples using the multi-step outflow experiment and numerical inversion of the measured transient flow data using HYDRUS-1D. HYDRUS-1D was then used to simulated the water regime within the soil profile under the grass cover using climatic data from June 2011 to December 2012 and some of the soil hydraulic parameters were additionally numerically optimized using soil water contents measured at all depths. Water flow and heat transport were then simulated using these parameters, measured thermal properties and temperatures measured close to the surface applied as a top boundary condition. Simulated temperatures at all depths successfully approximated the measured data.
... A large body of literature exists with respect to the application of the HP method to help determine soil thermal properties (e.g., Campbell et al., 1991;Kluitenberg et al., 1993;Bristow et al., 1994;Bristow, 1998;Hopmans et al., 2002;Mori et al., 2003) and soil moisture (e.g., Campbell et al., 1991;Bristow et al., 1993;Basinger et al., 2003;Heitman et al., 2003). Thermal and soil moisture data collected using HP probes have been applied in numerous studies to analyze soil-water flow (e.g., Ren et al., 2000;Ochsner et al., 2005;Mortensen et al., 2006;Saito et al., 2007;Kamai et al., 2008). To date, however, there have been few studies that used the combined HP and SHB method, whether through numerical simulation (e.g., Sakai et al., 2011) or field or laboratory experimentation (e.g., Heitman et al., 2008aHeitman et al., , 2008bXiao et al., 2011;Deol et al., 2012). ...
A combined heat-pulse and sensible heat balance method can be used to determine evaporation using temperature measurements and thermal property estimations. The objective of this study was to investigate the applicability of the combined heat-pulse and sensible heat balance method by comparing laboratory experimental data to both an analytical and a multiphase heat and mass transfer model. A bench-scale laboratory experiment was performed to measure soil thermal and hydraulic properties at fine spatial and temporal resolutions. Comparisons of experimental and numerical results confirmed the applicability of the heat-pulse and sensible heat balance methods to determine evaporation rates. Results showed close agreement with experimental water loss measurements. This study demonstrated the ability and versatility of using the heat-pulse and sensible heat balance methods in numerical heat and mass transfer models to determine evaporation rates. Calculated soil thermal properties were in 93.4 and 97.5% agreement with experimental results for water content values > 0.05. Deviations were observed at low water contents due to sensor sensitivity. The calculated evaporation rates yielded cumulative water losses that were 96.8 and 97.7% in agreement with experimentally measured weight loss data. Late Stage 1 evaporation was overestimated due to observed temperature rises by two of the heat-pulse probes. Despite this, the combined heat-pulse and sensible heat balance method is a powerful tool that can be used to determine evaporation rates in situ.
