HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS		QUICK SEARCH:   [advanced] Author: Keyword(s): Year:  Vol:  Page:

This Article Abstract Figures Only Full Text (PDF) Free Alert me when this article is cited Alert me if a correction is posted Services Similar articles in this journal Alert me to new issues of the journal Download to citation manager Citing Articles Citing Articles via HighWire Citing Articles via Google Scholar Google Scholar Articles by Ochsner, T. E. Articles by Ren, T. Search for Related Content PubMed Articles by Ochsner, T. E. Articles by Ren, T. GeoRef GeoRef Citation Agricola Articles by Ochsner, T. E. Articles by Ren, T. Related Collections Soil Methods/Instrumentation Water Content Soil Hydrology

SPECIAL SECTION - ADVANCES IN MEASUREMENT AND MONITORING METHODS

Use of the Dual-Probe Heat-Pulse Technique to Monitor Soil Water Content in the Vadose Zone

^a USDA-ARS, Soil and Water Management Research Unit, St. Paul, MN 55108
^b Dep. of Agronomy, Iowa State Univ., Ames, IA 50011
^c Inst. of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China 100101
^* Corresponding author (ochsner{at}umn.edu).

Journal paper of the Iowa Agriculture and Home Economics Exp. Stn., Ames, IA, Project No. 3287. Supported by the Soybean Research and Development Council, the Agronomy Dep. Endowment Funds, the Hatch Act, and the State of Iowa.

¹ Mention of products and suppliers is for the convenience of the reader and implies no endorsement on the part of the authors or the USDA-ARS.

Received 14 March 2003.

	ABSTRACT

TOP ABSTRACT INTRODUCTION THEORY MATERIALS AND METHODS RESULTS AND DISCUSSION CONCLUSION REFERENCES

 
The dual-probe heat-pulse (DPHP) technique is emerging as a useful technique for measuring soil volumetric water content (). However, few published data are available regarding the performance of the DPHP technique under field conditions. The objective of this study is to evaluate the effectiveness of the DPHP technique for measuring under field conditions. We used 24 DPHP sensors to monitor in a soybean [Glycine max (L.) Merr.] field during the 2001 and 2002 growing seasons. The DPHP sensors demonstrated durability in field conditions and clear sensitivity to temporal and spatial variations of at the scale of measurement. The mean measured by the DPHP sensors (_DPHP) was on average 0.040 m³ m^-3 larger than the mean measured by soil sampling (_SS). The response of the DPHP sensors was linear. Regressions of _DPHP vs. _SS yielded r² values of 0.949 and 0.843 at depths of 7.5 and 37.5 cm. The DPHP technique showed good resolution with RMSE values for the regression of 0.009 and 0.011 m³ m^-3 at the two measurement depths. The slopes of the regressions were 0.75 rather than 1.0. Errors in _SS are a likely cause of this low slope. We shifted all the values for each sensor up or down by a constant value to make the first measurement from each sensor equal determined from soil sampling near that sensor at the time of installation. This simple matching point procedure improved the accuracy of the DPHP technique, resulting in a -0.024 m³ m^-3 average difference between _DPHP and _SS. Also, the matching point procedure markedly reduced the variability between sensors, reducing the average SD from 0.063 to 0.026 m³ m^-3. This procedure requires no additional soil sampling and is recommended for field applications of the DPHP technique.

Abbreviations: , volumetric water content • _DPHP, mean soil volumetric water content measured by the dual-probe heat-pulse technique • _SS, mean soil volumetric water content measured by soil sampling • AWG, American Wire Gauge • C, soil volumetric heat capacity • DPHP, dual-probe heat-pulse

	INTRODUCTION

TOP ABSTRACT INTRODUCTION THEORY MATERIALS AND METHODS RESULTS AND DISCUSSION CONCLUSION REFERENCES

 
MEASUREMENTS of in the vadose zone are often needed by researchers who study components of the terrestrial hydrologic cycle or who study the many biological, physical, and chemical processes that are influenced by . Measurements of are also often utilized by irrigation managers in agriculture and horticulture. A number of useful direct and indirect techniques for measuring are available, each having characteristic strengths and weaknesses (Topp and Ferré, 2002). This study focuses on the DPHP technique, an indirect technique that enables automated, nondestructive measurements of on a small volume of soil. The DPHP technique for measuring was first suggested by Campbell et al. (1991), and has since been utilized by several researchers (Tarara and Ham, 1997; Ren et al., 1999; Song et al., 1999; Campbell et al., 2002). These studies have shown that the DPHP technique can provide accurate measurements of and change in () in laboratory and greenhouse settings.

However, evaluations of the effectiveness of the DPHP technique in the field have been limited. In one field study, Tarara and Ham (1997) compared measurements from three DPHP sensors with measurements made with a attenuation meter and found that the two methods agreed to within 0.05 m³ m^-3. In another field study, Campbell et al. (2002) compared measurements from 10 DPHP sensors in a peat bog with measurements from four water content reflectometer sensors (CS615, Campbell Scientific Inc., Logan, UT).¹ They reported similar temporal patterns of but different mean values between the two types of sensors at the 5-cm depth. At the 30-cm depth, they reported similar mean values of but different temporal patterns of between the two types of sensors. In total, we can find only two figures in two papers comparing DPHP measurements with independent measurements in the field. More extensive field comparisons between the DPHP technique and other accepted techniques for measuring are needed to clearly define the effectiveness of the DPHP technique under field conditions. The objective of this study is to evaluate the effectiveness of the DPHP technique for measuring under field conditions.

	THEORY

TOP ABSTRACT INTRODUCTION THEORY MATERIALS AND METHODS RESULTS AND DISCUSSION CONCLUSION REFERENCES

 
Dual-probe heat-pulse sensors can be used to measure soil volumetric heat capacity (C), which is directly related to . A brief heat pulse emitted from the heating needle of the DPHP sensor is transferred through the soil, resulting in a small temperature increase (T) approximately 6 mm away at the sensing needle of the sensor. The maximum value of this temperature increase (T_m) is inversely related to C (Campbell et al., 1991):

[1]

where q is the heat output per unit length of the heater (J m^-1), e is the base of the natural logarithms, and r is the distance between the heating and sensing needles (m). Volumetric heat capacity is related to by

[2]

where _w is the density of water (kg m^-3), c_w is the specific heat of water (J kg^-1 K^-1), _b is the soil bulk density (kg m^-3), and c_s is the specific heat of the soil solids (J kg^-1 K^-1) (Campbell et al., 1991). Note that soil solids include both mineral and organic matter. Substituting Eq. [1] into Eq. [2] and rearranging gives the theoretical equation for determining by use of the DPHP technique (Bristow et al., 1993):

[3]

Equation [3] is based on the assumptions that the heat transfer around and through the DPHP sensor is the same as the heat transfer around an infinite line source in a homogeneous medium, that the finite duration heat pulse approximates an instantaneous heat pulse, that the heat transfer is only by conduction, that no contact resistance exists between the sensor and the soil, and that _w, c_w, and c_s are independent of and temperature. Furthermore, in applying Eq. [3], we normally assume that all the variables other than q, T_m, and are constant throughout the measurement period.

	MATERIALS AND METHODS

TOP ABSTRACT INTRODUCTION THEORY MATERIALS AND METHODS RESULTS AND DISCUSSION CONCLUSION REFERENCES

 
Sensor Construction
Twenty-four DPHP sensors were utilized in this experiment. The heaters and thermocouples of the sensors were housed in 35.6-mm-long sections of 18-gauge (1.02 mm) stainless steel tubing. The heating needle was created by threading enameled resistance wire (79-µm diam., 205 m^-1, Nichrome 80 Alloy, Pelican Wire Co. Naples, FL) four times through the entire length of the tubing so that the resulting heater had a resistance of approximately 820 m^-1. The total resistance of the completed heaters was about 33 . The temperature sensing needle was constructed by inserting a 36 American Wire Gauge (AWG) copper-constantan thermocouple junction (Type T, Omega Engineering, Stamford, CT) in the second tube. The interiors of the heating and temperature sensing needles were then filled with high thermal conductivity epoxy (Omegabond 101, Omega Engineering, Stamford, CT), and the heater and thermocouple wire were connected to 8.5-m-long 22-AWG stranded conductors (Pelican Wire Co., Naples, FL). The lead wires for the heating needle were copper, and the lead wires for the sensing needle were copper and constantan. The heating and temperature-sensing needles were inserted into predrilled holes in a small PVC block so that the needles were parallel and separated by about 6 mm. The needles protruded 27 mm from the PVC block, the thermocouple junction was in the center of the protruding portion of the sensing needle, and the wiring junctions between the needles and the leads were inside the hollow center of the PVC block. The cavity in the block was then filled with high thermal conductivity epoxy (RBC-4300 and A-121 epoxy hardener, RBC Industries, Warwick, RI) so that the finished sensors were waterproof and electrically insulated. Finally, the sensor leads were threaded through heavy-duty woven nylon sleeves (Protec NHS-071, Tompkins Industries Inc., Olathe, KS) to protect the leads from damage in the field.

Measurement System
The measurement system for the 24 DPHP sensors consisted of a datalogger (21x, Campbell Scientific), two multiplexers (AM416, Campbell Scientific), a reference thermistor (Model 107, Campbell Scientific), a pair of 0.27- resistors wired in parallel (Philips ECG, Greenville, TN), a 5-V direct current relay capable of handling up to 2 A (R40-11D2-5, NTE Electronics Inc., Bloomfield, NJ), and a deep-cycle 12-V battery. The heater leads were connected to one multiplexer, and the thermocouple leads were connected to the second multiplexer. The thermocouple multiplexer was sealed in a well-insulated protective box with the reference thermistor mounted on the center bridge of the multiplexer. The heater multiplexer and the datalogger were each sealed in separate protective boxes. The datalogger switched the multiplexer channels at the appropriate times and activated the relay to switch current to the heaters. The current to the heaters flowed through the two 0.27 resistors wired in parallel, and the data-logger measured the voltage drop (V) across the resistors. The relationship between V and the heating power, q, is

[4]

where R_r is the total resistance of the paired resistors (), R_h is the resistance per unit length of the heating element ( m^-1), and t₀ is the duration of the applied heat pulse (s). The sensors were heated for 8 s. The current through each heater was approximately 0.33 A, resulting in q 700 J m^-1. The temperature of each sensor was measured before heating and one time per second for 80 s after the initiation of heating.

Calibration
The needle spacing, r, for each DPHP sensor was determined by recording measurements of q and T_m with the sensor immersed in water stabilized with agar (6 g L^-1) to prevent convection. Eq. [1] was then rearranged to solve for r with C = _wc_w = 997.5 kg m^-3 x 4180.4 J kg^-1 K^-1 = 4.170 x 10⁶ J m^-3 K^-1 (data for water at 23°C; Weast, 1978). We assumed that the agar did not significantly alter the heat capacity of the water. Campbell et al. (1991) calibrated DPHP sensors in water stabilized with agar at 2 g L^-1, but we found that at that concentration r was not stable when the heating power was varied. At 2 g L^-1 agar, r decreased as T_m increased, while r was independent of T_m at 6 g L^-1 agar (Fig. 1). These data suggest that the heat pulse induced some convection in water stabilized with agar at 2 g L^-1. The mean value of r for the sensors was 5.98 mm with a SD between sensors of 0.19 mm. The calibration for each sensor was repeatable with an average coefficient of variation of 1.1% across 24 replications.

View larger version (12K): [in this window] [in a new window]   Fig. 1. Calibrated needle spacing vs. maximum temperature increase for one dual-probe heat-pulse sensor in agar-stabilized water at 2 and 6 g L-1. The symbol is the mean of 10 measurements, and the error bars represent 1 SD in each direction.

In 2001, the soybean was planted on 18 May, and the 24 DPHP sensors were installed on 27 July. The sensors were installed at two locations in each plot. At each location, sensors were installed at depths of 7.5, 22.5, and 37.5 cm below the soil surface. In 2002, the soybean was planted on 24 May, and 24 DPHP sensors were installed on 27 June. The sensors were installed at three locations in each plot. At each location, sensors were installed at depths of 7.5 and 37.5 cm below the soil surface. In 2002, one additional DPHP sensor was sealed into a water-tight 250-mL Nalgene (Rochester, NY) bottle filled with quartz sand (Unimin silica sand, Target Products Ltd., Burnaby, British Columbia). This sensor was used to verify the stability of the results from the measurement system and was placed aboveground under a protective cover along with the datalogger and multiplexer enclosures.

Every 6 h, measurements were performed on all the DPHP sensors, and the date, time, initial temperature, voltage drop across the resistors, T_m, and the time between the initiation of the heat pulse and the occurrence of T_m were recorded. The data were postprocessed to calculate q and . The average of the values measured by all the DPHP sensors at each depth will from here on be referred to as _DPHP.

Soil Sampling
In 2002, we collected soil samples from the field on eight different occasions for determining by oven drying. The soil sampling procedure was designed to determine the average at 7.5 and 37.5 cm for comparison with _DPHP. Soil spatial variability and the destructive nature of soil sampling preclude a meaningful comparison of the water content determined by an individual sensor with that determined by repeated soil sampling. At each sampling, one soil sample was taken near each DPHP sensor, thus 12 samples were taken at the 7.5-cm depth and 12 at the 37.5-cm depth. The first set of soil samples was obtained by hand during sensor installation. The final set of soil samples was taken by hand during sensor extraction. The other sets of soil samples were collected with a 30-cm-long soil sampler with a 1.9-cm i.d. (JMC Sampler, Clements Associates Inc., Newton, IA). With the soil sampler we obtained samples from the opposite side of the soybean row at the same depth as the sensor. The total distance from the sample location to the sensor was <1 m. The 7.5-cm sample was obtained by vertically inserting the sampler 15 cm into the soil and saving the 6.5- to 8.5-cm layer from the resulting soil core. The 37.5-cm sample was obtained by reinserting the sampler into the hole made by removing the first sample and saving the 36.5- to 38.5-cm layer from the resulting soil core. The total volume of each soil sample then was about 5.7 cm³. The sampling volume of a DPHP sensor can be approximated as follows: A cylinder with a diameter equal to the distance between the sensor needles, r, and a length equal to that of the sensor needles would enclose a volume of 0.79 cm³. This volume is an approximate lower limit on the sampling volume of the sensor. Theoretically, the radial distance from the heater at which the maximum temperature increase is 1% of T_m is 2.37r or 1.4 cm (Campbell et al., 1991). A cylinder with a radius of 1.4 cm and a length equal to that of the sensor needles would enclose a volume of 17 cm³. This volume is an approximate upper limit on the sampling volume of the sensor. Therefore, the sensors probably sample a volume of soil between 0.79 and 17 cm³. The 5.7-cm³ volume of the soil samples falls within this range. The similarity of number, spatial distribution, and volume of samples is important for making an accurate comparison between the two techniques. The gravimetric water content of the soil samples was determined by weighing, drying for 24-h at 105°C, and weighing again. Bulk density was determined from separate soil samples taken at the site of each DPHP sensor during sensor extraction on 4 September. The average _b values for the 7.5- and 37.5-cm depths in 2002 are shown in Table 1. The average determined from the 12 soil samples at each depth will from here on be referred to as _SS. Soil samples taken during the course of the study were used to determine selected physical properties of the soil in the laboratory. Particle size analysis was performed with the hydrometer method. Organic matter content was determined by dry combustion. And, c_s was measured by a differential scanning calorimeter (Seiko DSC220C, Perkin-Elmer Analytical Instruments, Shelton, CT). The results listed in Table 1 are the means of two replications of the particle size and organic matter measurements and three replications of the c_s measurements.

View this table: [in this window] [in a new window]   Table 1. Bulk density (b), particle size distribution, organic matter (OM) content, and specific heat (cs) of the soil at the study site.

	RESULTS AND DISCUSSION

TOP ABSTRACT INTRODUCTION THEORY MATERIALS AND METHODS RESULTS AND DISCUSSION CONCLUSION REFERENCES

 
The daily average value of _DPHP and the daily rainfall totals for the period of measurement in both years are shown in Fig. 2. The data in Fig. 2 qualitatively demonstrate the sensitivity and reliability of the DPHP technique under field conditions. During the periods of measurement, the DPHP technique captured distinct temporal variations in water content. The _DPHP data show sharp increases in response to rainfall events and smooth, gradual decreases between rainfall events. The DPHP technique also captured distinct variations in water content with depth in both years. For example, the small rainfall events that occurred between 25 and 27 July 2002 resulted in a 0.05 m³ m^-3 increase in _DPHP at the 7.5-cm depth but no increase in _DPHP at the 37.5-cm depth. The DPHP results in both years also reveal the general tendency for the 37.5-cm depth to be drier than the 7.5-cm depth. In the context of this study, the ability of the DPHP technique to capture temporal and spatial variations in soil water dynamics makes it a promising technique for studying infiltration, crop water use, and evapotranspiration. The data in Fig. 2 also indicate that a DPHP system can function reliably for months at a time in a field environment with minimal intervention. The measurement system was deployed for a total of 123 d during 2001 and 2002, and all of the sensors were still functioning properly at the end of the study. During the study, only two losses of data occurred. The first loss of data occurred for 12 d (27 Aug.–7 Sept. 2001) and stemmed from a faulty splice in the reference thermistor cable. The second loss of data occurred for 5 d (22 Aug.–26 Aug. 2002) and resulted from animals causing the external battery to be disconnected from the datalogger. Visits to the site were sporadic, and maintenance was limited to downloading data and changing the external battery when it became depleted (once per season in this case).

View larger version (25K): [in this window] [in a new window]   Fig. 2. Daily average of water content measured by the dual-probe heat-pulse sensors along with the daily rainfall totals for the measurement periods in (A) 2001 and (B) 2002.

Comparison of _DPHP and _SS
From here on we will focus our analysis on the results from 2002, because that is the year in which we collected extensive soil samples. Figure 3 shows the time series of _DPHP and _SS for 2002. Four _DPHP measurements per day are plotted in Fig. 3, with each measurement being the average value from 12 sensors at the same depth. Figure 3 illustrates the value of automated measurements of for describing soil water dynamics. Notice that soil samples were collected on 6 and 13 August and that the resulting _SS values show a small increase in water content during that period. In contrast, the relatively continuous _DPHP data for the same period show that the period between 6 and 13 August included a distinct dry-down followed by a clear rewetting. Figure 3 also demonstrates that the DPHP technique performs with a reasonable level of accuracy under field conditions. At the 7.5-cm depth, _DPHP was on average 0.025 m³ m^-3 larger than _SS. At the 37.5-cm depth, _DPHP was on average 0.054 m³ m^-3 larger than _SS. The reason for the greater difference between _DPHP and _SS at 37.5 cm than at 7.5 cm is unclear. The maximum absolute difference between _DPHP and _SS was 0.047 m³ m^-3 at the 7.5-cm depth and 0.077 m³ m^-3 at the 37.5-cm depth. At both depths, the maximum absolute difference occurred at the time of sensor installation.

View larger version (27K): [in this window] [in a new window]   Fig. 3. 2002 time series of water content measured by dual-probe heat-pulse (DPHP) sensors and by soil sampling at (A) the 7.5-cm depth and (B) the 37.5-cm depth.

View larger version (19K): [in this window] [in a new window]   Fig. 4. One-to-one comparison of water content measured by dual-probe heat-pulse (DPHP) sensors and by soil sampling at (A) the 7.5-cm depth and (B) the 37.5-cm depth. Symbols represent the mean of 12 measurements. Error bars represent 1 SD in each direction. The open symbols identify the questionable soil sampling data discussed in the text.

View this table: [in this window] [in a new window]   Table 2. Results of linear regression of mean soil volumetric water content measured by dual-probe heat-pulse (DPHP) technique vs. by soil sampling (SS).

Consideration of Error Sources
To understand why the slope of the linear regression of _DPHP vs. _SS is lower-than-expected, we must consider at least three potential error sources: the _SS measurements may have contained errors, the measurements of q and T_m may have contained errors, and the assumptions behind the DPHP technique may have been violated. Errors in the _SS measurements are the primary potential contributor to the lower-than-expected slope. The first set of soil samples taken during sensor installation and the last set of soil samples taken during sensor extraction may have been subject to evaporation, and the resulting _SS may have been too small. The processes of sensor installation and sensor extraction each took approximately 8 hr, during which time the soil samples were kept in moisture cans in a shaded area. Given the length of time between sampling and weighing, some potential for evaporation did exist. As noted above, the maximum absolute difference between _DPHP and _SS occurred at sensor installation, and the second largest absolute difference occurred at sensor extraction. Furthermore, the set of soil samples taken on 13 August may have been biased toward overestimating the true water content at 7.5 and 37.5 cm. Obtaining this set of soil samples was complicated by the compressibility and stickiness of the wet surface soil caused by rainfall on the night of 12 August and the morning of 13 August. It was difficult to ascertain the actual depth that the soil samples represented, and it is certainly possible that the soil samples represented shallower and wetter soil than intended. If so, then this set of samples would act to falsely lower the slope of the _DPHP vs. _SS regression. The three sets of questionable soil samples mentioned above are identified by open symbols in Fig. 4. Removing these samples from the analysis leads to a slope of 0.97 for the regression of _DPHP vs. _SS at both depths. This is a significant improvement and indicates that errors in _SS could be largely responsible for the lower-than-expected slope.

Errors in the measurement of q or T_m are a second potential contributor to the lower-than-expected slope of _DPHP vs. _SS. If q were consistently underestimated or overestimated by some fixed percentage or by some constant value, then the error would have been automatically accounted for during sensor calibration, and it would not affect _DPHP. The same holds true for a fixed percentage-wise error in T_m. The only foreseeable way in which either of these measurement errors could cause the slope of the _DPHP vs. _SS to be <1 would be if T_m were consistently underestimated by some constant value. This seems unlikely.

Violations of the assumptions behind the DPHP technique are the third potential contributor to the lower-than-expected slope of the _DPHP vs. _SS relationship. Some of the assumptions behind Eq. [3] have been investigated carefully. Kluitenberg et al. (1993) investigated the effects of the assumptions that the heat transfer around the DPHP sensor is the same as the heat transfer around an infinite line source and that the finite duration heat pulse approximates an instantaneous heat pulse. They reported that for the sensor geometry and heating time used here, estimates of C obtained by Eq. [1] are within 1% of the estimates obtained by use of more rigorous models. The assumption that heat transfer occurs only by conduction has been investigated by Bilskie (1994) using a numerical model for conduction and convection heat transfer around a heat-pulse sensor. He concluded that under typical conditions, convection has no effect on T at points more than 2 mm from the heater.

In applying Eq. [3], we assumed that _b did not change with time; however, it is possible that _b could change with time in conventionally tilled plots like the ones used in this study. If _b changed with time at the measurement depths in our plots, then the difference between _DPHP and _SS should have changed with time also. Instead, the data show that _DPHP was greater than _SS by a fairly consistent amount throughout the study (Fig. 3), so change in _b with time cannot adequately explain the data. It is worthwhile to note that any error in _b would effect both _DPHP and _SS. For example, if the true _b were 0.1 Mg m^-3 greater than the _b value used in Eq. [3], then water content estimated by a DPHP sensor would contain a +0.018 m³ m^-3 error. The same 0.1 Mg m^-3 error in _b would cause a -0.020 m³ m^-3 error in determined by soil sampling if the gravimetric water content of the soil were 0.20 kg kg^-1. Then, the difference between the water contents determined with these two methods would be +0.038 m³ m^-3, and the apparent error of the DPHP technique would be greater than the true error.

The effects of the remaining assumptions listed immediately following Eq. [3] are currently unknown, and one or more of these assumptions could contribute to the unexpectedly low slope of the _DPHP and _SS relationship. Additionally, the assumption employed in sensor calibration that agar-stabilized water has the same heat capacity as pure water is untested and could potentially influence the slope of the _DPHP and _SS relationship. Underestimating the heat capacity of the agar-stabilized water would lead to overestimating the needle spacing. Overestimating the needle spacing would result in a lower-than-expected slope for the _DPHP and _SS relationship.

Matching Point Procedure
Previous research has indicated that the DPHP technique excels in determining (Tarara and Ham, 1997). On the basis of this knowledge, we chose to apply a matching point procedure to adjust the _DPHP data. We shifted all the water content data for each sensor up or down by a constant value to make the first water content measurement from each sensor equal the water content determined from soil sampling near that sensor at the time of installation. The resulting time series graphs shown in Fig. 5 demonstrate that this matching point procedure improved the accuracy of _DPHP. The bias was not totally eliminated by use of the matching point procedure, but the absolute value of the bias was decreased. After applying the matching point procedure, _DPHP was, on average, 0.022 m³ m^-3 < _SS at the 7.5-cm depth. At the 37.5-cm depth, _DPHP was on average 0.025 m³ m^-3 < _SS. As mentioned previously, some evaporation likely occurred from the initial set of soil samples that were used in the matching point procedure. If evaporation did occur, it could explain the observation that subsequent _DPHP values tended to be lower than _SS values. The maximum absolute difference between _DPHP and _SS was 0.047 m³ m^-3 at the 7.5-cm depth and 0.046 m³ m^-3 at the 37.5-cm depth. At both depths, the maximum absolute difference occurred on 13 August, which is when the maximum value of _SS was recorded. The temporal trend of _DPHP is unaltered by the matching point procedure.

View larger version (27K): [in this window] [in a new window]   Fig. 5. 2002 time series of water content measured by dual-probe heat-pulse (DPHP) sensors after application of matching point procedure and by soil sampling at (A) the 7.5-cm depth and (B) the 37.5-cm depth.

View larger version (18K): [in this window] [in a new window]   Fig. 6. One-to-one comparison of water content measured by dual-probe heat-pulse (DPHP) sensors after application of matching point procedure and by soil sampling at (A) the 7.5-cm depth and (B) the 37.5-cm depth. Symbols represent the mean of 12 measurements. Error bars represent 1 SD in each direction.

	CONCLUSION

TOP ABSTRACT INTRODUCTION THEORY MATERIALS AND METHODS RESULTS AND DISCUSSION CONCLUSION REFERENCES

	ACKNOWLEDGMENTS

 
The rainfall data for 2002 were supplied by Joel O. Paz, Dep. of Agricultural and Biosystems Engineering, Iowa State Univ., Ames, IA. The DPHP sensors used in this study were on loan from Gerard J. Kluitenberg, Dep. of Agronomy, Kansas State Univ., Manhattan, KS.

	REFERENCES

TOP ABSTRACT INTRODUCTION THEORY MATERIALS AND METHODS RESULTS AND DISCUSSION CONCLUSION REFERENCES

 

• Basinger, J.M., G.J. Kluitenberg, J.M. Ham, J.M. Frank, P.L. Barnes, and M.B. Kirkham. 2003. Laboratory evaluation of the dual-probe heat-pulse method for measuring soil water content. Vadose Zone J. 2:389–399.[Abstract/Free Full Text]
• Bilskie, J.R. 1994. Dual probe methods for determining soil thermal properties: Numerical and laboratory study. Ph.D. diss. Iowa State Univ., Ames, IA.
• Bristow, K.L., G.S. Campbell, and K. Calissendorff. 1993. Test of a heat-pulse probe for measuring changes in soil water content. Soil Sci. Soc. Am. J. 57:930–934.[Abstract/Free Full Text]
• Campbell, G.S., C. Calissendorff, and J.H. Williams. 1991. Probe for measuring soil specific heat using a heat-pulse method. Soil Sci. Soc. Am. J. 55:291–293.[Abstract/Free Full Text]
• Campbell, D.I., C.E. Laybourne, and I.J. Blair. 2002. Measuring peat moisture content using the dual-probe heat pulse technique. Aust. J. Soil Res. 40:177–190.
• Kluitenberg, G.J., J.M. Ham, and K.L. Bristow. 1993. Error analysis of the heat pulse method for measuring soil volumetric heat capacity. Soil Sci. Soc. Am. J. 57:1444–1451.[Abstract/Free Full Text]
• Ren, T., K. Noborio, and R. Horton. 1999. Measuring soil water content, electrical conductivity, and thermal properties with a thermo-time domain reflectometry probe. Soil Sci. Soc. Am. J. 63:450–457.[Abstract/Free Full Text]
• Song, Y., M.B. Kirkham, J.M. Ham, and G.J. Kluitenberg. 1999. Dual probe heat pulse technique for measuring soil water content and sunflower water uptake. Soil Tillage Res. 50:345–348.
• Tarara, J.M., and J.M. Ham. 1997. Measuring soil water content in the laboratory and field with dual-probe heat-capacity sensors. Agron. J. 89:535–542.[Abstract/Free Full Text]
• Topp, G.C., and P.A. Ferré. 2002. Water content. p. 417–422. In J.H. Dane and G.C. Topp (ed.) Methods of soil analysis. Part 4—Physical methods. SSSA Book Ser. 5. SSSA, Madison, WI.
• Weast, R.C. (ed.) 1978. CRC Handbook of Chemistry and Physics. CRC Press, West Palm Beach, FL.

This article has been cited by other articles:

				T. E. Ochsner and J. M. Baker In Situ Monitoring of Soil Thermal Properties and Heat Flux during Freezing and Thawing Soil Sci. Soc. Am. J., July 1, 2008; 72(4): 1025 - 1032. [Abstract] [Full Text] [PDF]

				M. H. Young, G. S. Campbell, and J. Yin Correcting Dual-Probe Heat-Pulse Readings for Changes in Ambient Temperature Vadose Zone J., January 23, 2008; 7(1): 22 - 30. [Abstract] [Full Text] [PDF]

				T. M. DeSutter, T. J. Sauer, T. B. Parkin, and J. L. Heitman A Subsurface, Closed-Loop System for Soil Carbon Dioxide and Its Application to the Gradient Efflux Approach Soil Sci. Soc. Am. J., January 11, 2008; 72(1): 126 - 134. [Abstract] [Full Text] [PDF]

				J. H. Knight, W. Jin, and G. J. Kluitenberg Sensitivity of the Dual-Probe Heat-Pulse Method to Spatial Variations in Heat Capacity and Water Content Vadose Zone J., October 8, 2007; 6(4): 746 - 758. [Abstract] [Full Text] [PDF]

				J. L. Heitman, R. Horton, T. Ren, and T. E. Ochsner An Improved Approach for Measurement of Coupled Heat and Water Transfer in Soil Cells Soil Sci. Soc. Am. J., May 16, 2007; 71(3): 872 - 880. [Abstract] [Full Text] [PDF]

				T. E. Ochsner, T. J. Sauer, and R. Horton Soil Heat Storage Measurements in Energy Balance Studies Agron. J., January 1, 2007; 99(1): 311 - 319. [Abstract] [Full Text] [PDF]

				T. E. Ochsner, T. J. Sauer, and R. Horton Field Tests of the Soil Heat Flux Plate Method and Some Alternatives Agron. J., June 5, 2006; 98(4): 1005 - 1014. [Abstract] [Full Text] [PDF]

				T. Ren, Z. Ju, Y. Gong, and R. Horton Comparing Heat-Pulse and Time Domain Reflectometry Soil Water Contents from Thermo-Time Domain Reflectometry Probes Vadose Zone J., November 11, 2005; 4(4): 1080 - 1086. [Abstract] [Full Text] [PDF]

				T. E. Ochsner, R. Horton, G. J. Kluitenberg, and Q. Wang Evaluation of the Heat Pulse Ratio Method for Measuring Soil Water Flux Soil Sci. Soc. Am. J., May 6, 2005; 69(3): 757 - 765. [Abstract] [Full Text] [PDF]

				Y. Mori, J. W. Hopmans, A. P. Mortensen, and G. J. Kluitenberg Estimation of Vadose Zone Water Flux from Multi-Functional Heat Pulse Probe Measurements Soil Sci. Soc. Am. J., April 11, 2005; 69(3): 599 - 606. [Abstract] [Full Text] [PDF]

				J. M. Ham and E. J. Benson On the Construction and Calibration of Dual-Probe Heat Capacity Sensors Soil Sci. Soc. Am. J., July 1, 2004; 68(4): 1185 - 1190. [Abstract] [Full Text] [PDF]

This Article Abstract Figures Only Full Text (PDF) Free Alert me when this article is cited Alert me if a correction is posted Services Similar articles in this journal Alert me to new issues of the journal Download to citation manager Citing Articles Citing Articles via HighWire Citing Articles via Google Scholar Google Scholar Articles by Ochsner, T. E. Articles by Ren, T. Search for Related Content PubMed Articles by Ochsner, T. E. Articles by Ren, T. GeoRef GeoRef Citation Agricola Articles by Ochsner, T. E.