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5<=B-w·l´ $% .; $ |Lox¸ ¹H"ºC2DQ:"-H«B-©yῐJ. Jpn. Soc. Soil Phys.
ῑ῏῎ῒΐῐ
No. 31, p. -ῌ+, ῍,**.῎Field Estimation of Soil Dry Bulk Density Using Amplitude
Domain Reﬂectometry Data
Krissandi WIJAYA*, Taku NISHIMURA*, Makoto KATO* and Masanobu NAKAGAWA*** Tokyo University of Agriculture and Technology, -ῌ/ῌ2 Saiwai-cho, Fuchu, Tokyo+2-ῌ2/*3, Japan** Ryokusei Kenkyusho Inc., ,ῌ.*ῌ+* Kojima, Chofu, Tokyo +2,ῌ**,0, Japan
Abstract
Since permeability of ﬁeld soils is strongly a#ected by dry bulk density, knowledge of spatial
distribution of dry bulk density is beneﬁcial to predict water and chemical transport throughsoils.

In this study, ﬁeld soil dry bulk density was estimated by using Amplitude Domain

Reﬂectometry (ADR) data. The experiment was sited at the Sakae-cho experimental ﬁeld ofTokyo University of Agriculture and Technology (TUAT) covered by Andisol soil. The ﬁeld of .
ῌ. m in large was divided into 2+ small plots of *./ῌ*./ m each. The ADR probe was operated inevery small plot, and the ADR output voltage was measured by using digital voltmeter. Soilsamples were taken by using the steel ring of +** cm- in volume. The results showed that theestimated dry bulk density agreed well with the measured dry bulk density. The regression
coe$cient (R,) ranged from *.. to *.1. Dry bulk density estimated by using the ADR data and wet
bulk density (R,῍*./ῌ*.1) had greater accuracy than that by using the ADR data and mass wetness(R,῍*..ῌ*.0). Furthermore, spatial variability, which was expressed by semivariogram, of themeasured and the estimated dry bulk density by using the ADR data and wet bulk density agreed
well. However, spatial variability of the dry bulk density estimated by using the ADR data andmass wetness showed di#erent trend to others.

This indicated that the estimated dry bulk

density with wet bulk density had better performance to predict dry bulk density than that withmass wetness.
Key words : Dry bulk density, ADR, Andisol, Spatial variability, Semivariogram+.

Introduction

Field soil physical properties are quite variable, both in vertical and horizontal directions.
Beside, these properties also vary with time.
Since soil physical properties play a central
role in transport and reaction of water, solutes,
and gases in soils, knowledge of spatial variability of soil physical properties is very important for understanding transport phenomena
in soils, hence, for soil conservation and planning appropriate agricultural practices. Morespeciﬁcally, knowing ﬁeld soil dry bulk density
would help in scaling other important soil
physical properties, i.e., predicting soil permea-

bility as a function of dry bulk density byusing non-similar media concept (NSMC)
method (Miyazaki, +330). The soil permeability
data can be used to determine the better K
factor of Universal Soil Loss Equation (USLE)(Wischmeier and Smith, +312). However, measurement of the ﬁeld-spatially-distributed soil
parameters tends to be di$cult and complicated, such as time consuming, laborious and expensive (Zorita et al., ,**+). Therefore, the useof a proper method to measure ﬁeld soil physical properties with low cost, simple and quick
method is required.
Amplitude Domain Reﬂectometry (ADR)
probe is one of the methods for measuring῏

4

Table +
Soil parameters
Texture (kg kg+) : sand
silt
clay

31

,**.

Soil physical properties
First ﬁeld experiment(Sakae-cho soil)*4,3 ῌ
*4-1 ῍ Light Clay (LiC)*4-. ῎Mass wetness, w (ῌ)
Dry bulk density, rb (g cm-)Volumetric water content, q (cm- cm-)volumetric soil water content based on measurement of dielectric constant of the soil
(Gaskin and Miller, +330 ; Robinson et al., +333 ;Inoue, +332a, +332b ; Nakashima et al., +332).
The ADR probe has a similar performance toother permittivity methods, such as Capacitance Insertion Probe (CIP) and Time Domain
Reﬂectometry (TDR) probe (Miller and Gaskin,+330 ; Nakashima et al., +332). However, theADR probe has advantages over the latterprobes, and it is relatively cheaper and simpler
automatic measuring system compared to the
CIP and the TDR (Nakashima et al., +332). In
other word, since the ADR output is direct
current voltage, it can be simply connected tothe commercial multi-channel logger to monitor changes in soil water content. Practically,
the ADR probe was successfully applied to a
project, which tries to investigate the impact ofland use changes on catchments behavior, speciﬁcally hydrology and hydrochemistry (Miller
and Gaskin, +330).
In recent decades, special attention has been
focused on ﬁeld spatial variability of soil physical properties. Geostatistics, which involves
the theory of regionalized variable, is being
extensively used to characterize the structureof these variabilities (Tominaga et al., ,**,).
The regionalized variable is a property such as
soil moisture content, dry bulk density, hy
draulic conductivity, etc., which can be sampled. Accordingly, the properties (or samples)taken at close spacing will be similar or
spatially correlated, while the properties fromlarge sample spacing will be dissimilar or0*῏3*4.3῏*400*4-/῏*4/,

Second ﬁeld experiment(Sakae-cho soil)*4,3 ῌ
*4-1 ῍ Light Clay (LiC)*4-. ῎
0*῏22*4.3῏*402*4-0῏*4/,

spatially uncorrelated (Isaaks and Srivastava,+323). The phenomena above can be clearlyclariﬁed by using semivariogram as one of themost common geostatistics tools, which canquantify the spatial dependence and spatial
structure based on distance of separation anddirection (Scot, ,***), and, in turn, it is essential
to design of optimal sampling grids and interpolation methods (Isaaks and Srivastava, +323).
Objective of this presenting study was toestimate the ﬁeld soil dry bulk density byusing the ADR data.
,.

Materials and Methods,. + Soil Materials
The ﬁeld experiment was located at the
Sakae-cho experimental ﬁeld of Tokyo University of Agriculture and Technology (TUAT),
Japan. The Andisol ﬁeld of .. m in large wasdivided into 2+ small plots (3 rows and 3 columns) with *./*./ m each. The physical properties of the soil are shown in Table +.
,. , Experimental Procedures
The ﬁeld experiment was conducted twotimes, such as in July ,*** (ﬁrst ﬁeld experiment) and December ,*** (second ﬁeld experiment). In each experiment, core samples andthe ADR data were collected from every small
plot. Soil core samples were taken by using thesteel ring of +** cm- in volume. The ADR data
were collected by embedding the ADR probe of
0* mm in length into the ﬁeld soil and the ADR
output voltage was measured by using digital
voltmeter. The embedding of the ADR probe
was replicated three times surrounding the soilῒῑ : Field Estimation of Soil Dry Bulk Density Using Amplitude Domain Reﬂectometry Data

core sample location and averaged. To stabilize the ADR output signals, the embedding the
ADR probe was kept for ,* to -* seconds. Since
the ﬁeld contains 2+ small plots, the amounts ofsamples were totally 2+ soil core samples and2+ the ADR data for each experiment. All soilcore samples were brought to the laboratory
and several soil parameters such as mass wetness, wet bulk density, dry bulk density, andvolumetric water content were measured byusing gravimetric method.
In addition, the ﬁrst ﬁeld experiment was
conducted on ﬁeld soil having dry layer at thesurface. However, it was expected that thepresence of surface dry layer might enhanceheterogeneity in soil moisture distribution
within the ﬁeld proﬁle, which a#ects the ADR
performance (Wijaya et al., ,**,). To improve
the ADR performance, therefore, in the secondﬁeld experiment, the surface dry layer of a cm
in thickness by observation was removed prior
to the ADR measurement and the soil coresampling. Such treatment resulted in relatively less heterogeneity in moisture content distribution within the ﬁeld proﬁle.
,. - Calculation of Dry Bulk Density withADR Data
Dry bulk density can be calculated as function of volumetric water content measured byusing the ADR probe (qADR) combined witheither wet bulk density (Eq. (+)) or mass wetness (Eq. (,)),
rbest +ῐrt῏ῌqADRῌrw῍
qADR῏
rbest ,ῐ῍+**
ῌrw
῎
w ῐ

ῌ
῍

where, rbest + is the estimated dry bulk densitywith wet bulk density (g cm῏-), rbest , is theestimated dry bulk density with mass wetness(g cm῏-), rt is the wet bulk density (g cm῏-), rw is
the density of water (ῐ+ g cm῏-), qADR is thevolumetric water content measured by using
the ADR probe (cm- cm῏-), w is the mass wetness (ῑ). Eq. (,) is multiplied with +** to convert the mass wetness by percentage to that bydecimal form.

5

Application of the ADR method, which involves the use of either Eq. (+) or (,), in estimating dry bulk density from volumetric watercontent measured by using the ADR probe(qADR) o#ers more beneﬁts compared to traditional oven drying method such as simple, lesslabor and less time consuming. Wijaya et al.
(,**-) reported that to obtain dry bulk density
by using Eq. (+) needs only the information ofsoil wet mass (weight) occupying the known
volume of core sample and it is not necessary
to spend a day to oven dry the sample. Also,
only a small fraction of the disturbed soil
sample, less than +* grams, which is used tomeasure mass wetness, is required to estimate
the dry bulk density by using Eq. (,). Therefore, the ADR method helps us to perform easy,
quick, and less labor determination of ﬁeld soil
dry bulk density, especially when large numbers of data are required.
The qADR data, which is substituted into Eq.
(+) and (,) was obtained from the third orderpolynomial equation (Eq. (-)) as a result of
calibration between the ADR output voltage
and volumetric water content of the Andisol
soil (Wijaya et al., ,**-). The dry bulk density
was ranged from *.-3 to *.30 g cm῏- during thecalibration, which was performed on the soil
with mass wetness ranged from .* to 1* ῑ.
qADRῐ*.**+++῎+./-+v῏,.-.,v,῎+...2v῎
where, v is the ADR output voltage (volt).
,. . Semivariogram
Generally, classical measures of locationsuch as arithmetical mean (M), and spread ofdata such as standard deviation (Std. Dev.) andcoe$cient of variation (CV) are used to evaluate statistical characteristics of the sample population, which can be described as the frequency distribution. However, the frequency distribution is somewhat limited in its ability todescribe variability of a sampled population
because it does not provide any information
about spatial correlation between samples at agiven location.

6

 31  ,**.

To solve the problem above, semivariogram,which can express the degree of spatial dependence between two samples at a given separation distance and direction, has been used tocharacterize spatial variability of hydraulicconductivity (Mohanty, et al., +33. ; Ciolarro
and Romano, +33/), soil water content and dry
bulk density (Tominaga et al., ,**,), soil watercontent and solute concentration (Netto et al.,+333), soil organic matter, NO--N, pH and electric conductivity (Imade, et al., ,**+). It can bedeﬁned as a graph (and/or formula) describing
the expected di#erence in value between pairsof samples with a given relative distance anddirection (Clark, +313). The vertical axis issemivariance, g (h) and the horizontal axes isdistance between two data points, h. For onedimensional data, the g (h) value at given position can be computed by the following equation,

Fig. +

Comparison between the estimated dry
bulk density by using Eq. (+) andmeasured dry bulk density.

Fig. ,

Comparison between the estimated dry
bulk density by using Eq. (,) andmeasured dry bulk density.

῍ῑ῎ῒ

gh

+
ΐ
zxizxih,,Nh ῔ῌ῏ῐῌ

where, N (h) is the number of data pairs
separated by the lag interval h, z (xi) is themeasured sample value at point xi, and z (xih)is the measured sample value at a distance hfrom xi.
-.

Results and Discussions

Comparison between Estimated andMeasured Dry Bulk Density
Figure + shows comparison between the estimated dry bulk density by using Eq. (+) andthe measured dry bulk density, including dataobtained from the ﬁrst and the second ﬁeld
experiment. As can be seen from the ﬁgure, theestimated and the measured data points werelaid on and concentrated around + : + regression line. It indicated that the rbest ﬁtted wellwith the rbmsr. The estimated dry bulk density
obtained from the second ﬁeld experimenttended to be more reliable than that from theﬁrst ﬁeld experiment. The regression coe$cient (R,) was *.01. and *..00, for the second andthe ﬁrst ﬁeld experiment, respectively. Cor-. +respondingly, the root mean square error(RMSE) value between the rbmsr and the rbest byusing Eq. (+) was *.*-, and *.*/3 g cm-, for thesecond and the ﬁrst ﬁeld experiment, respectively.
Figure , shows comparison between the estimated dry bulk density by using Eq. (,) and῎῍ : Field Estimation of Soil Dry Bulk Density Using Amplitude Domain Reﬂectometry Datathe measured dry bulk density, including datafrom the ﬁrst and the second ﬁeld experiment.
Unlike the results shown in Fig +, the estimated and the measured data points shownin Fig , were slightly deviated from andscattered around + : + regression line. It indicated that the rbest tended to be underestimatedand less agreed with the rbmsr. The estimateddry bulk density from the second ﬁeld experiment was better than that from the ﬁrst ﬁeld
experiment, however, it still showed lower accuracy compared to the results of Eq. (+) as
shown in Fig +. In Fig ,, the R, was *./3- and*..--, for the second and the ﬁrst ﬁeld experiment, respectively. The RMSE value between
the rbmsr and the rbest by using Eq. (,) was *.*-3
and *.*1. g cmῌ-, for the second and the ﬁrst
ﬁeld experiment, respectively.
Di#erence in accuracy between the estimated dry bulk density obtained from theﬁrst and the second ﬁeld experiment was due
to di#erence in the surface treatment among
them. The presence of the surface dry layer ofa cm thickness in the ﬁrst ﬁeld experiment,
which enhanced greater heterogeneity in soil
moisture distribution within the ﬁeld proﬁle,could reduce the ADR performance. The surface dry layer might be produced mainly
through evaporation process especially in thebare ﬁeld soil. Greater the thickness of the drylayer in the soil, greater the vertical heterogeneity in soil moisture distribution within its
proﬁle, which, in turn, enhances the error of the
ADR output (Wijaya, et al., ,**,). The ﬁeld soil
with removal of surface dry layer in which the
ADR probe and the core sample was embedded
had more uniform in soil moisture distribution
than that with a surface dry layer (ﬁrst ﬁeld
experiment). Therefore, the errors of the ADR
output could be reduced when the ADR probe
was applied on such soil.
Comparison between the results shown in
the Fig + and , showed that the estimated dry
bulk density with the wet bulk density had
greater accuracy than that with the mass wetness. Di#erence in calculation process between

Fig. -

7

Field distribution of soil dry bulk
density for the second ﬁeld experiment :(a) the rbmsr, (b) the rbest by using Eq. (+),
and (c) the rbest by using Eq. (,).

8  31

Eq. (+) and (,) could be a primary factor a#ecting the results. The Eq. (,) is a division formula, thus, when the qADR containing an error was
substituted into this equation, running the division process might increase the error in rbest
since denominator (w) was smaller than unity.
This error was relatively greater compared tothe case when the qADR data were substituted
into Eq. (+) (Wijaya et al., ,**-). Therefore, thegreater accuracy of qADR was very important toenhance the greater accuracy of rbest.
-. , Field Distribution of Dry Bulk Density
Field distribution of dry bulk density at thesecond ﬁeld experiment is shown in Fig -,which is consisted of (a) measured, (b) estimated by Eq. (+) and (c) estimated by Eq. (,).
As can be seen from the ﬁgures, the distribution of the cloud of data points for the rbest was
similar with that for the rbmsr. The greater
values of rb were dominantly contoured
around the northern part of the ﬁeld from west
to east, and the middle of the ﬁeld. The lower
values of rb spread out around southernwestern part, southern-eastern part and middleof the ﬁeld. The greater values of rb ranged
from *./2 to *.02 g cm-, while the lower valuesof rb ranged from *..2 to *./. g cm-.
Degree of similarity between the distributionof the rbest by using either Eq. (+) or (,) and thatof the rbmsr are shown in Fig . (a) and . (b),respectively. According to the ﬁgures, the similarity can be simply evaluated by the contourof the square di#erence in data points between
the rbest and rbmsr, which was expressed as theerrors of rbest. The errors of the rbest by using Eq.
(,) (Fig . (b)) were greater than that by using
Eq. (+) (Fig . (a)). The errors ranged from *.***/
to *.**// g cm- and from *.***/ to *.**.* g cm-,for the rbest by using Eq. (,) and (+), respectively.
These errors were mostly distributed aroundthe southern part of the ﬁeld from west to east,
due to the greater errors of qADR at the same
area (Fig /). Since accuracy of the ADR probe
is strongly a#ected by volumetric water content distribution along with sensing rods
(Wijaya et al., ,**,), it was suspected that some,**.

Fig. .

Square error distribution of the estimated dry bulk density : (a) square errorof the rbest by using Eq. (+), and (b) square error of the rbest by using Eq. (,).

vertical heterogeneity in moisture or dry bulk
density might be occurred at southern part ofthe ﬁeld. Error distribution of the qADR aroundthe northern part was very small, and only
small error distribution of the rbest was encountered at the same location. It indicatedthat the qADR accuracy was an important factor
in the estimation of dry bulk density.

῎῍ : Field Estimation of Soil Dry Bulk Density Using Amplitude Domain Reﬂectometry Data

Spatial Variability of Dry Bulk Density
Statistical values for the measured and theestimated soil physical properties, including
mass wetness, w, measured volumetric watercontent, qmsr, estimated volumetric water content, qADR, measured dry bulk density, rbmsr andestimated dry bulk density, rbest by using either
Eq. (+) or (,) are summarized in Table ,. Coe$cient of variation (CV) for all the measured andthe estimated soil physical properties obtained
from the ﬁrst and the second ﬁeld experiment-. -Fig. /

Square error distribution of the volumetric water content measured by using
the ADR data (qADR).

Table ,

9

ranged from -.- to +*.3 ῌ. According to theseCV values, all the soil physical properties
above were conﬁrmed relatively low variability (Wilding, +32/ ; Scot, ,***). The greater CV
values occurred on mass wetness, w, rbest byusing Eq. (,) and qmsr, while the lower CV values occurred on the qADR, rbmsr, and rbest by using
Eq. (+). From Standard Deviation (Std. Dev.)
value, it was also clear that the rbmsr and rbest byusing Eq. (+), especially for the second ﬁeld
experiment, were not signiﬁcantly di#erent
and considered to be similar each other. However, the Std. Dev. value for the rbest by using
Eq. (,) was distinctly di#erent to the two previous parameters. It indicated that the rbest byusing Eq. (+) had similar variability with rbmsr,
while the rbest by using Eq. (,) did not.
Another aspect in performance of presenting
method was discussed by evaluation on spatial
variability of the dry bulk density, which was
carried out by semivariogram (Fig 0 (a), (b) and(c)). In these three ﬁgures, semivariance wereplotted within distance between two points
ranged from of *./ to , m. From the trend of
semivariance, the rbmsr (Fig 0 (a)) and the rbest byusing Eq. (+) (Fig 0 (b)) were similar. Although
the rbmsr tended to show smaller semivariance,
both the rbmsr and rbest by using Eq. (+) showedsteady semivariance with increasing distance
between two points. It indicated that the rbmsr
and the rbest by using Eq. (+) had similar struc-

Statistical values for the ﬁeld soil physical properties
First ﬁeld experiment

Variables

Second ﬁeld experiment

Mean

Std.
Dev.

CV
(ῌ)

Mean

Std.
Dev.

CV
(ῌ)

1-...,

1.33/

+*.23

1..-12

1..,.

3.32

Measured volumetric water content, qmsr (cm cm )

*..,*

*.*./

+*.0-

*..-,

*.*--

1.1,

ῌ-

*.-13

*.*-+

2.*1

*..+.

*.*+.

-.,1

Measured dry bulk density, rbmsr (g cm )

*./1-

*.*-0

0.-2

*./2-

*.*.,

1.,/

Estimated dry bulk density by using Eq. (+),
rbest + (g cmῌ-)

*.0+.

*.*0*

3.12

*.0**

*.*.-

1.+3

Estimated dry bulk density by using Eq. (,),
rbest , (g cmῌ-)

*./,*

*.*/0

+*.02

*./0,

*.*/3

+*.0.

Mass wetness, w (ῌ)ῌ--

Estimated volumetric water content, qADR (cm cm )
-

ῌ-

10

ΐῐ῎῔῕ῑ ῒ 31 ῏ ῌ,**.῍ture of spatial distribution over space. However, the semivariogram of rbest by using Eq. (,)(Fig 0 (c)) monotonously increased with increasing distance between two points and did
not reach a constant value. Results above
suggested that the characteristic of spatial distribution of the rbmsr agreed well with that of
the rbest by using Eq. (+) and did not agree withthat of rbest by using Eq. (,).
..

Fig. 0Semivariogram of the measured andestimated dry bulk density : (a) semivariogram of the rbmsr, (b) semivariogram of
the rbest by using Eq. (+), and (c) semivariogram of the rbest by using Eq. (,)(numbers in the ﬁgures are the numberof data pairs for a given lag interval h).

Conclusions

Application of the ADR data on estimation ofﬁeld dry bulk density showed good results.
The rbest by using Eq. (+), combined with wet
bulk density data, was better than that byusing Eq. (,) with mass wetness. Furthermore,since higher uniformity in soil moisture distribution can reduce the errors of the ADR probe
measurement, the second ﬁeld experiment involving removal of the surface dry layer yielded the greater accuracy of dry bulk density
estimation compared to the ﬁrst ﬁeld experiment, which was conducted with a surface drylayer.
According to the results of semivariogram, it
was found that characteristic of spatial distribution of the rbest by using Eq. (+) was similar tothat of the rbmsr. However, the rbest by using Eq.
(,) showed di#erent structure of spatial variability to that of the rbmsr and the rbest by using
Eq. (+). Therefore, Eq. (+) was expected to be
useful to estimate soil dry bulk density.
This method can serve reasonable quality ofdry bulk density data with saving either timeor amount of soil sample. Employing Eq. (+)
can estimate dry bulk density by taking andweighing sample in situ, while using Eq. (,)
requires taking less than +* grams of soil
sample for a dry bulk density data. For some
purpose, i.e. taking large number of dry bulk
density data for vast area, this method may
partly substitute traditional oven drying
method with undisturbed sample which requires labor and be time consuming.

῍ῌ : Field Estimation of Soil Dry Bulk Density Using Amplitude Domain Reﬂectometry Data

Acknowledgement
This study was supported by Grants-in-Aid
for Scientiﬁc Research by Japan Society of thePromotion of Science : No. ,**+ῌ+-10*+03. Also,in conducting ﬁeld experiments the authors
would like thank to the help o#ered by students of Laboratory of Land Use, Tokyo University of Agriculture and Technology.
References
Ciollaro, G. and Romano, NR. (+33/) : Spatial variability of the hydraulic properties of a volcanic
soil, Geoderma, 0/ : ,0-ῌ,2,.
Clark, I. (+313) : Practical geostatistics, pp. +ῌ0*, Applied Science Publisher Ltd, London, UK.
Gaskin, G. J. and Miller J.D. (+330) : Measurement ofsoil water content using simpliﬁed impedance
measuring technique, J. Agric. Eng. Res., 0- :+/-ῌ0*.
Imade, A. S. W., Shibushawa, S., Sasao, A. andHirako, S. (,**+) : Soil parameter maps in
paddy ﬁeld using the real time soil spectrophotometer, J. of the Japanese Society of Agriculture and Machinery, 0- : /+ῌ/2.
Inoue, M. (+332 a) : Evaluation of measuring precision of ﬁeld-type dielectric soil moistureprobes using salty sand, J. Japan Soc. Hydrol.
& Water Resour., ++ : ///ῌ/0..
Inoue, M. (+332 b) : Monitoring system for ﬂow andsolute transport, Sand Dune Research, ./ (+) :+/ῌ,/.
Isaaks, E.H. and Srivastava., R.M. (+323) : An Introduction to Applied Geo-statistics, Oxford University Press, Oxford, USA.
Miller, J.D. and Gaskin G.D. (+330) : Theta probe
ML,x. principle of operation and applications(,nd edition), Macaulay Land Use ResearchInstitute (MLURI), Aberdeen, UK.
Miyazaki, T. (+330) : Bulk density dependence of air
entry suctions and saturated hydraulic conductivities of soils, Soil Science, +0+ : .2.ῌ.3*.
Mohanty, B.P., Ankeny, M.D., Horton, R. and
Kanwar, R.S. (+33.) : Sapatial analysis of hy-

11draulic conductivity measured using disc inﬁltrometers, Water Resour. Res., -* : ,.23ῌ,.32.
Nakashima, M., Inoue, M., Sawada, K. and Nicholl,
C. (+332) : Measurement of soil water content
by Amplitude Domain Reﬂectometry (ADR) :Method and its calibrations, J. Groundwater
Hydrology, .* : /*3ῌ/+3.
Netto, A.M., Pieritz, R.A. and Gaudet, J.P. (+333) :Field study on the local variability of soil
water content and solute concentration, J. Hydrology, ,+/ : ,-ῌ-1.
Robinson, D.A., Gardner, C.M.K. and Cooper, J.D.
(+333) : Measurement of relative permitivity insandy soils using TDR, Capacitance and Theta
Probe : Comparison, including the e#ect ofbulk soil electrical conductivity, J. Hydrology,,,- : +32ῌ,++.
Scott, H.D. (,***) : Soil physics : agricultural andenvironmental applications, pp. -/0ῌ-12, Iowa
State University Press, Iowa, USA.
Tominaga, T.T., Cassaro, F.A.M., Bacchi, O.O.S.,
Reichardt, K., Oliviera, J.C.M. and Timm, L.C.
(,**,) : Variability of soil water content andbulk density in a sugarcane ﬁeld, Aust. J. Soil
Res., .* : 0*/ῌ0+..
Weishmaier, W.H. and Smith, D.D. (+312) : Predicting rainfall erosion losses, USDA Agriculture
Handbook /1-, U.S. Department of Agriculture.
Wijaya, K., Nishimura, T. and Kato. M. (,**,) :E#ect of variability in moisture content proﬁleon the ADR probe performance, pp. ,1,ῌ,1-,
Proceeding of JSIDRE Annual Meeting, Mie,
Japan, 0ῌ2 August ,**,.
Wijaya, K., Nishimura, T. and Kato. M. (,**-) : Estimation of dry bulk density of soil using amplitude domain reﬂectrometry, J. Jpn. Soc. Soil
Phys., 3/ : 0-ῌ1-.
Wilding, L.P. (+32/) : Spatial variability : its documentation, accommodation and implication tosoil survey, pp. +00ῌ+3., In D.R. Nelsen and J.
Bouma (ed.) Soil spatial variability, Pudoc,
Wageningen, Netherlands.
Zorita, M.D., Grove, J.H. and Perfect, E. (,**+) : Laboratory compaction of soils using a small moldprocedures, Soil Sci. Soc. Am. J., 0/ : +/3-ῌ+/32.

KLM³²¡ ´ 31 µ j,**.l12

ADR 
 
*ῌ *ῌ***ῌ*  +2-ῌ2/*3  ! -ῌ/ῌ2** "#$%&'()* +2,ῌ**,0 +,-. ,ῌ.*ῌ+*

ADR /0123456789/:;<=>?@6A9/BCDEFGHIJKLMNO>?MP4

CQR6S TUAV!WX2 , YZ[6S /* cm \]2 3^3 M_`aMb2GHIJKL
Mcd; ADR /01M34CZ[6S , YeMTU2AfghMNOi jk + cml Cmn5
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?xNO>?P4M?r ;xH[6S @6 fghMNOiMx ADR /01M
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 ADR /01;<=>?C[FP456NO>?AT3s;M\0, ¡C¢[
FE6S £¤M¥¦Ho ADR /01;<=>?CDE6GHIJKLMNO>?P4AHpy~E¥¦C;o§S!" : NO>? ¨©: ADR ª«¬KL 789/:­®¯°± : ,**- ¯ 3 ° +0 ±­²¯°± : ,**. ¯ , ° +1 ±
J. Jpn. Soc. Soil Phys.
./"&
No. 31, p. +- ,. ,**.

 NAPL   PITT
*ῌ **ῌ*ῌῌ ***ῌPrecision analysis of Partitioning Interwell Tracer Testfor estimating a NAPL in aquifer
Junko NISHIWAKI*, Changyuan TANG**, Yasuo SAKURA**
Masaru MIZOGUCHI* and Tsuyoshi MIYAZAKI** Graduate School of Agricultural and Life Sciences, The University of Tokyo** Graduate School of Science and Technology, Chiba University
Abstract
Partitioning Interwell Tracer Test (PITT) developed in the petroleum industry is a useful
method to quantify the volume of Non-aqueous phase liquid (NAPL) in contaminated aquifer.
PITT provides us information about the characterization of the NAPL volume and distribution in
relatively large scale area. When we perform PITT, we use the basic assumption that tracers are
partitioned to NAPL completely during PITT.

However, the assumption is not veriﬁed yet.

Under practical conditions, we have to be careful of (+) loss of NAPL during PITT, (,) NAPL
migration process, (-) sorption of NAPL to organic materials or minerals in aquifer, (.) inhomogeneous tracer partitioning to NAPL because of the heterogeneous NAPL distribution andform, (/) accuracy of measuring tracer partitioning coe$cients.

The purposes of the study are (+)

to estimate the unknown quantity of NAPL placed in a column ﬁlled with glass beads and water,
and in a pipette ﬁlled with water, and (,) to analyze the accuracies of these estimations by PITT
method. As a result, the ratios of estimated NAPL volumes and actual NAPL volumes ranged
from *./3+...

The reliability of NAPL estimation by means of PITT decreased when the ﬂow

rates of tracers were too low.
Key words : PITT, NAPL, column experiment, pipette experiment)BuvGH ;\;w23op+<+     

NAPL "_`xyB zGR+3 56"{ $%!" NAPL

&GR+|}%\B~ =|\=:_`a+< ]=#Non-Aqueous Phase Liquid ; $%&'( )*+,

: =  =    %  L ) -%ῌ./0123456789:;+< =>=,

#Oolman et al., +33/ ; Frind et al., +333(<@)_`a+?-"01@ABCDEFGH ;"G IJKL 9:;+ 01ῌ_`UV\./ῌ,-%M)NO+01PQR+;BSTPQ"U=:B ῌ lῌ ῍ l 

VWX3YZ[2\ +< ]"^ ,-)_`a+῎ 

01bcdefga+\IhiG"jklm+|}) ? #REV( "LB q

n G23op q drfga+\01bcst)* §¨e©e©ª«©o¬©­®¬ ¯++-῏20/1 °¨±o +῏+῏+** ²e©e©ª³´¬©­®¬ ¯,0-῏2/,, µ±o +῏- : PITT NAPL ¶·¸¹ º»¼n¹

!3R+< =>= NAPL c¡G¢£9+"m¤ c¥¦:;

%d&_G ` 31 ¼ ,**.

14 Mayer and Miller, +33,    NAPL 
!"#

$%&'

' NAPL  (  PITT Partitioning Interwell Tracer
Test ) PITT  *  +31* *+,-.

' -/*01234 PITT 
NAPL 

5'4 67 Jin

et al., +33/ 7. 89:!;< Wilson andMackay, +33/ ; Hunkeler et al., +331 ; Deeds et al.,+333, ,*** ; Whitley et al., +333 =>?

=@A

BCDEFGH Jin et al., +331 IJ K

ῌ+Fig. +< PITT »^Schematic diagram of PITT in a ﬁeld.

LMN Young et al., +333 ; Mariner et al., +333
7OPO#MNQ.'4
- PITT  NAPL '4S

/:O 0zEG)!"F)RD

!"S4TU-)

. PITT

iuyFG^!HI
G-.C F

0&+ῌJ+G

V#WXYZS Dwarakanath et al., +333

6oK&  H L#M3) #D[ ῌ NAPL \]$^&N 

NAPL _` ῍ NAPL a!bc ῎ %d$J+e&ῌf&!

 g ' Jin et al.,+331 ῏ (hi# NAPL )jk*!

(hi#+ ῐ lm#U4' Orst,7'4#4
 NAPL  NAPL O&'HP i+ ¡¢&-)+no KN, W Q£4 NAPL v¤+7 NAPL $+7'4]r&J++nop

Lee et al., +332 ; Dwarakanath and Pope, +332 #q

-

+

!¥SHP ]R +!S¦§T]Y R¨ 4' NAPL uv./](  PITT )

q!"+7-4"<w0U4't,,,

 7.#V#xy(z{ !) 

PITT !'U.©Sª7#«V NAPL

#D[+^4'

NAPL |}12~ |}]



PITT

 VN )¥ ¬­ ®7 Jin et al., +33/3 # 4#qbc5.-67)

VN¯

8MN9: NAPL   PITT V#;G9:8 K5.-)^! 4 PITT <9:4 PITT V# NAPL }=12~bc ^!|

>bc

qttp°ttn
KNW±±±±±±±±±±±±,²+ tp +
J+Wh] min tn
Wh] min KN, W 

NAPLῑ +no q X³]

mL min°+ ) Wh] tp, tn &./Y¦Z7CS¦§T



,
,+



´ S q[.S¬­

PITT 

®7 Jin et al., +33/ ; Young et al., +333

PITT 

PITT  ]^&+



:

) PITT 03F?@T" *  *  t i¯±±±±±±±±±,²,[µ¶ i + partitioning ·\ p, O

( ) -<j 0&3CJ+ non-partitioning ·\ n ).D

DD 3HS4.'4

 Cd ]¬¸C*, Cin  ¹ º\L# FGL#) t ]

03AB'  NAPL 

L# C-C*ῌCin-C* )¥

M : }n NAPL F2 rR PITT 6+12

min tf  min tin min 

KNW



-+ 

 .M,P  gRW  NAPL῏ KN, W  

15  

 6  c .M,P ' U
 +* mL  TCE ,.* mL VFW / : + XY

CiN,-
CiW!" ## Ci, N  NAPL  i Ci, W $ i 
%&' ()* , +,(cZ[6 U"
C Y yz0 6 U
C* 62 ,/ /* +** ,** ppm  . \1gRw/U].&IJ^ r - \Q 6 &(no ῌ]j9 + _`K6a No. + ῍ ]j9 ,- ./0"  + -  

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d-..e¤6(1' TCE >

!" #  ; <(= >$?

@A=%!1# BCD#&"+,d-..]W2e¤6'E' F( , +">E'. G

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 /.*¨+*- mL 12Yyz

 , +- 456NO!"PQ 7BRC N6 % C*, C 1 !0©

S01 ##B8!T9&#Pª«h'ghs&# Ci, W Ci, N t
 r2 ,. - 7W KN, W-    -,9 7BR10 6
 U

V: *.., (WQ;X + mm YZ[\]<6^Z_ NAPL .=`&

¬r



-,+  

YZ [\]<6YZ ^Z_ ,/ cm i j
X +.2 cm  k ; 2 $ l 8 0&F­

@ PITT abcBR ^Z_BR  >12

MASTER FLEX 1/+3῏*/ 12mn@A!j

 NAPL .d?=`&@ PITT abcBR

 [\&®o¯r ^Z_pqefgBR h ^Z_BR@ABC°c g±62r6 U­s

PITT abc62 efgBR PITT 3

²!j NAPL $l>t³o¯r^Z_Aci!j#D!6 WEk(l NAPL K6 u , NAPL 62 TCE ^Z_v

FGHm?. PITT &(noE'Hpl806 u A, B BR TCE  + ´4µ

IJIq&rBs6 tuBRBRJ

!j' C+  u , WQ , ´4w!j

KLMv12BR C wWxBR P 0n&

' C,  , \6H NAPL yz

BR C+  0.* mL  TCE ^Z_Nl {|Z}~ FID : OP GC+.B %$Y yz ¶80wW 1.* cm  + x:·81 NQ , RSz|Z_ ^Z_6 BR C,  TCE  -.* mL 9

 1*

+ , x/26 ¶80wW+-*

FNJK62Y

0 min + R  +**0 min S: +/0 min  min+, y ,**  b~ y ,**   ,  !
0 T62c 

 +* cm, ,* cm C+, C, *y TCE F 0.* mL 
zF
TCE U'U +.*¨+*, mL ¸62 . c , fc %$ .M,P 

{ *.+ s 6 ¹ &F­12mn

NAPL 62yzz %$ TCE |>º»6 &FpBR* *.*0 mL min+ 61

BR /  ¼ ^Z_Oq80cZ|>+  31  A,**.F16

ῌ,Fig. ,

Setup for column experiments.

Fig. -

Setup for pipette experiments.

ῌ-

gh4pqNt  !
#$%&'()

pqNt*+""+ /.*,+*-- mL ./0123456789:;<"=<> 78?@ ABCDEF G<456HIJKLM A,. , NF O " A,. +F N./456P
Q:

N A,. ,F +RST#+UVLMWt X " 45678?@+YZ[\] C+, C, X^-,, 
+* mL .+fgh4 , ijk;l Amno
0* cmF pqrsX

At -F

gh4uvwKxy;l" TCE +z{gh4|}v

At~ A, BF  TCE vX

pq[ TCE P" TCE " 456 
/ . :pq P+  TCE ..* mL gh4+|}v + ~
-+

" 45

 +* min, 78?@+_;[\]`aYZb "6" wK *.*0 mL min

cY*>d> 3/," +*.* min X

 P-  TCE ..* mL  , #e

 , ##+#eR*>d> .-" -1 X

% " RST "P*>d> *.*0" *.+, mL min-+ X.  TCE /.* mL  , #e

pq P,
P

 , # " : ³ NAPL cYHῒῌ.
Fig. .

&

kPITTl r»¼=

xyῌ¹tpVῌLMº+17

ῌTCE 

Partitioning of ethanol between aqueous and TCE phases under di#erent
tracer initial concentrations, time and stirring conditions.

 *.+, mL min+   TCE 

 .  

 No. +, No. ,, No. - )9

:;xy=xy+* >>RC 

 ! TCE "#$ %&'()*



+



A&   RC k,. -l j4= KN, W 4KH&

01 234 56  47 *.*1|*.+- }B=n4O ", , -./

 TCE  9:;=>"@+-./ 8 TCE 9:;<=>"?@+A BC DEFE 4G%&H

+A&H KN, W* ,4 TCE +I&>+ TCE +.*@#  /  .M,P  No. +, No. ,, No. - )
xyo TCE  "@+A

mL J%&4KH  LMN4 + O% TCE J%&& BCR No. + 0 No. ,  -./ P ,

QRC +.*S+*

mL 



T(4UV DWXRCYZ[\+]

4^_`

46 No. - xyo"zA=>RC %&>+ TCE  "6 %

&>"¡R& k,. -l j4=¢£ .M,P  a  b 0 TCE cYdefghi+*& >>+ j k,. ,l mnopV

1.0- No. - + +*..  No. - " Jin C k+331l +¤m No. + 0 No. , +DEFE 2.,2qt  rstuv4w&H

=CE=& KN, W +*., =n4O xy<zA{+ P+|P. +DEFE +* ,*  "¥¦%&+VpV)§¨%¤m1 / min, xy<}B{+~zA& R z+DEFE 0** +*2* -0* +31+ min  

NAPL "«¬=E­  "¥¦%&mnImDEFE .. .+ ,1 ,, ®pV¯°CE& >H No. +, No. , .ῌ ῑ ῐ ῏ ῍ NAPL "«¬+ "¥¦R" No. - '( "¥¦¯°CE&.ῌ+ ῕῔῎ΐ . 

= + ©=ªpV  /  .M,P / 4

fgh  -./  ±&²³pV

O%  kNo. +, No. ,, No. -l +,Yx2|,* pV+*&" ´µ¶4¯y4xy kC*l +n kCῌC*l 4 xy kppml 4&





 

 .M,P 4a BC ·¸46

®¯°±² ³ 31 ´ 4,**.518

ῌ/Fig. /?@<[W\W¦§/0ῌ¨#:;ῌ©ª«¬­6 .M,P BῌTCE 

Partitioning of .M,P between aqueous and TCE phases under di#erent tracer
initial concentrations, time and stirring conditions.



KN, W +*..

xs dtuh6RQ., 

.,,  0 ++   !"#$%P+P. 6JO."#$%&' ()*+,-./0 123 4Cmax5
67 /0 8/0 4CῌCmax5

 9)*:;

&'

! {


1.Y.  2++  TCE *|}~p6< 9):;;=>?@<* AB;='C  ! 4 2 ++5 6 TUVWX

8C D:;>EFGH@I "#$% J<We* !k6*@hQ

4min5

IKL MNO.<:;;=6D PQI6R.M,P

S"#$%*  !6d/0We:S6*T< S TUVWX  .M,P  Cmax 4ppm5

UVWX*1.Y. C+ 6 -12 --.2 C, 6 .-1 -..2 P+ 6

zg>tuh@qW n -O P+,,+. 3.., P, 6 -./ 0..1 P- 6 ,*/ 2,.1 P. 6 ,0-P,, P.  .M,P /0wxs6* @IOh6@//.- 6R< Z(%* [W\W 4ttp5 ]p/0x>Q[W\W 4ttn5 ^_`a:; 4min5 6R<.M,P.-  NAPL !qJO.c[W\W^_`a:; tp 



.,+

.M,P >klmnop &  1

 0  1 1.Y. C+ C, "#$%&' tn 4min5 S1.O

4,. +5  NAPL  VN 4mL5

 + &' "#$% 4 0 15 b6 c ! d .M,P /0S !  TUVWX^_`a:;We>TUVWXf. +,-. -O .M,

4min5 * C+ 6 .*2 C, 6 -1, 6Rq .M,P 6* C+ 6

P We:;f.* C+ 8C+,*,* C, 6 +,+** 6RQ  hO mnC, 63ghQTCE >

S TUVWX/0ij* C+, C,@o & 

h

dklmn

.M,P /0ijop*?

d1oQ 0.* mL 
C, 6 .., mL

6RQ v/0wxs6* C, ij* C+ q¢£> ¤hQ

zg>brs8C
VWX8C NAPL  VN * C+ 6 -./ mL,@q /0brs6* C+ 8C C, ij>tuh
y6RQ -O c ! d .M,P /0wxs

.M,P  TCE>n< >h< -O
 TCE > , 

h.



¡

¥ !  TUVWX^_`a:tuh6RQ STU

; 4min5 * P+P. 61.Y. .*+ ,10 +3- +0. 6.M,P /0ij* /0brs w

Rq .M,P 6* P+P. 61.Y. 3+- +,,,* /0+ :  NAPL $"# b =>GHI sPITTu

ῌ0
Fig. 0.3+  /012

 C, sTCE -.*-.* mLu/012

Breakthrough curves of run C, with -.* -.* mL of NAPL.

 .M,P

 !"#>L- NAPL M* NOPQKR S:0T
EU:VWXYZ[ =J?@7\]:;<

NAPL $ VN % & '($ ..* mL )* P++P- 

PITT%,-.- -.* /.. ..- mL, P. %'($ /.* mL )bcdefg<hij-:

* -.2 mL 

^_<:GHI =>?@7`a:/++ / /+ 

19

Breakthrough curves of run C+ with 0.* mL of NAPL.

ῌ1Fig. 1

 C+ sTCE 0.* mLu






/012 3456789:;< =>?@ABk<l .M,P

mOnop- qrL- st 0 1u ;< j .M,P  TCE =>L-;< : Lj .M,P+ no CC, p- qrL-;<%TCE  , v

C;-D EF:GHI =J?@7"#wxy:z{ sC,u  + vw!<! xy: ;;=J?@<% =>GHI NAPL K=:z{ sC+u B[GHI< NAPL < |}~uvwxy z 31 { j,**.r20

ῌῌ2Fig. 2

Breakthrough curves of run P+. Speciﬁc surface of TCE is ,.1 cm, mLp+ andﬂow rate is *.*0 mL minp+.

ῌῌ3
Fig. 3,- P+ jkl=mno ,.1 cm, mLp+, Zq *.*0 mL minp+r st56,- P, jkl=mno /.* cm, mLp+, Zq *.*0 mL minp+r st56

Breakthrough curves of run P,. Speciﬁc surface of TCE is /.* cm, mLp+ andﬂow rate is *.*0 mL minp+.

  C+  TCE .M,P  C,"#$%&'()

!

$%&TJKUR56VTJKLWUB  HIL1CDEQ*+,- "#./01 2301 4 .M,P TCE F1XYC]Z[#1\ , ^P1_I?`ab c

56789:;%<=>?@AB dW +]PeI1CDE

 .M,P 1CDE TCE FGHIJK?







b

LM N) O .M,P  TCE F1 .M,P "#./01 C+ => C, fg

8?4HIL1CPQRS 9:;%<

@AB  TCE  , hi1?L : JK NAPL |&"A]^_`_S TPITTW  ,<;ῌ+*
Fig. +*

RS P- Twxy /.* cm, mLz+, {| *.+, mL minz+W }~gh

Breakthrough curves of run P-. Speciﬁc surface of TCE is /.* cm, mLz+ andﬂow rate is *.+, mL minz+.

ῌ++
Fig. ++

21

RS P. Twxy -.. cm, mLz+, {| *.+, mL minz+W }~gh

Breakthrough curves of run P.. Speciﬁc surface of TCE is -.. cm, mLz+ andﬂow rate is *.+, mL minz+.

 TCE 

PITT



 .M,P  TCE 
!"#$%#&'()* +,-./01
2 C, 34 C+ 567!"* )2 TCE  ,89,:);<=>,2 TCE 

=>,2 TCE I1, .M,P JK LMN

I

1 .M,P OPE!""A#BC)*/+, 

Q;RS TU 2V++W XYZRS#2[G \]^_`_a_bLM c5d-.ef1ghi

TCE ,();<" .M,P ?@()

,j#klm<G!""A#BC)* ),DE C+ -./01

ghiF#G!" )2 TCE aop]F#G!"2 TCE  + 89,H#H!"

q,rstuE"#$%#v:)* aop]-./01n .M,P *º+, » 31 ¼ Y,**.Z22

ῌ+ 67j#y
Experimental conditions and results
for all the runs.

,-./0

Table +
67'

tn



C+
C,
P+
P,
PP.

tp

.*2
-1,
.*+
,10
+3+0.

+5*,*
+5+**
3++5,,*
/0+
.3+

S

q

³
³
,41
/4*
/4*
-4.

VN

*4*0
*4*0
*4*0
*4*0
*4+,
*4+,

Vr

-4/
.4,
-4*
/4.
.4-42

/,, 
PITT ` P  P+sP. :t *.1.! +..! +.+! *.1/

P

0.*
0.*
..*
..*
..*
/.*

*4/3
*41*
*41.
+4.
+4+
*41/

tp :   «  ¬  Y. M , PZ  ! Q    
Y[ ,. , ; minZ
tn : ( «¬ YZ !Q Y[ ,. , ; minZq :  YmL min+Z
VN : E^ NAPL  Y[ ,. + ; )´µ67#$¶P  ·¸ YK¹+*..,Z ?] ;mLZ
Vr : 6_ NAPL  Y6_ TCE  ;mLZ
P : PITT ` YVrῌVN ^aZ
S : lmn Ycm, mL+Z

Y +Z0G.u,vb/ P! 1wx NAPL ! j#yz{? P+  P, ub/0 NAPL
 , cdek ..* mL x

P, E^ NAPL  /.. mL, + cd89 YP+Z -.* mL X

0 b e|! 34567 }~67R! D NAPL 89:



?/ NAPL 'E^b/q

0 *.1.! P,  +.. O|.R +.*`#??- PITT ` P+ . X$! E^0

! P+sP. ?lmnr?,vb/0 P+sP. :tlmn ,.1!
/.*! /.*! -.. cm, mL+ X$! Rlmnp

?NO PITT `h?^b/! P,  P- `h?F/0  67 Y +Z #!
PITT `:t +..! +.+ X$!  P, `h??- ?0 P- ` +.+ b,./0 P-  .M,P ()K P, u P. X

G .! 

?G PITT `q P ,-.
 TCE  .M,P! TCE "

#$%

.M,P

& '$()*+

*+


 ,-./0 1 ()/0 GG! !Q YttZ E^[ Y,. , [Z.R/0

 .! PITT ;?!

b e| tail P )Lb/ YP+! P.Z  t "¡! PITT ;¢

£ ;h¤'¥' YP,Z ! t .M,P 2.! 3456789¦w.p"¡! 1 p  .M,P  TCE 

! :; TCE <=§¨b/ t ©ª "¡#' / .X#$>?@ABCD EF/0/0

GH! P+, P,, P-  .M,P ()IJK«¬­r?®/ P! )LM.! 34567()NO

? P+  P, Y*.*0 mL min+Z! j#y , $P.  .
"

0 G .M,P  TCE ;! TCE  .M,P  P-  P. Y*.+, mL min+Z ub/0 1w

Q

p?89! .M,P jk/ P- () $ R,-./! : P. X$! +IJKS3TU5VW X/,)L '! E^`R +.+ %?/0   P. 

0

PITT  NAPL r?()M.! E^`R *.1/Y,. +Z [?\] E^ NAPL  VN YmLZ 

6_

NAPL  Vr YmLZ  PITT ` P YVNῌVrZ ^ab/089h

TCE  , cdi

TCE x P- 
P+  P, ! .M,P()X$! ` *.1.  +.. 

PITT ` P  C+  *./3! C,  *.1*  TCE  , cfg

wRh'

X1$h??- ?0/ , + 

de

0 1

? Y..* mLZ 

Y +Z0 G

G#$!  NAPL

jk/lmnop`qr 

R

1 &67!  Jin et al., +33/ M
./#¯

ª

}°±²F

!

PITT j? NAPL E^b/ P[ Y,. +Z 

!Q Y,. , [Z ±/ P! £

::

NAPL ,y& !"#$%$¼C PITT )!t)TG  Rd  


 

ttpῌtn ! "#$%$&  '()

 )*+ , -./0123
 4,5 )e)%G G&V _a o wxp)0+ wx op_)8G N NAPL"#$%$opu

U



J

G

 NAPL ,y&<@71 G

67 ) "#$%$-./)89 
: !5;
@

23

2 

 PITT < => ?

5;A  P- BCDE

!5;-wx_)n 2 ¡¢£$"¤¥¦./ F=G PITT < 5  NAPL ¥§wx¤¥{$¨3©4ª«¬  ­®¯°±)"#$%$HIwx²5)8G³)´65µ¶W7GJ KG  L

M ; HI
G P,



J K>NO

K    #·¢$6 , 8 ))¸¶WG K  ¹>º»9P< 5;A   HI

J KG  N OQG R
4
S

G, 

 BCNOG P+  P,< ;A +33/ Wῌ NS)TGS

 PITT

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nonaqueous -phase liquids. Journal of Contami-Jin, M., Delshad, M., Dwarakanath, V., McKinney, D.
C., Pope, G.A., Sepehrnoori, K., Tilburg, C.E. andnant Hydrology, ++ : +23ῌ,+-.
Oolman, T., Godard, S.T., Pope, G.A., Jin, M. andJackson, R.E. (+33/) : Partitioning tracer test for

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Whitley, G.A., McKinney, D.C., Pope, G.A., Rouse, B.A.

Jin, M., Butler, G.W., Jackson, R.E., Mariner, P.E.,

and Deeds, N.E. (+333) : Contaminated Vadose

Pickens, J.F., Pope, G.A., Brown, C.L. andZone Characterization Using Partitioning Gas

McKinney, D.C. (+331) : Sensitivity Models andTracers. Journal of Environmental Engineering,

Design Protocol for Partitioning Tracer Tests in+,/ (0) : /1.ῌ/2,.

Alluvial Aquifers. Ground Water, -/ (0) : 30.ῌ31,.

Wilson, R.D. and Mackay, D.M. (+33/) : Direct Detec-

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tion of Residual Nonaqueous Phase Liquid in the

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Saturated Zone Using SF0 as a Partitioning

Compositional Changes Inﬂuence Partitioning

Tracer. Environmental Science and Technology,

Coe$cients. Environmental Science and Tech-,3 (/) : +,//ῌ+,/2.

nology, -, (,,) : -/1.ῌ-/12.
Mariner, P.E., Jin, M., Studer, J.E. and Pope, G.A.

Young, C.M., Jackson, R.E., Jin, M., Londergan, J.T.,
Mariner, P.E., Pope, G.A., Anderson, F. J. and(+333) : The First Vadose Zone Partitioning

Houk, T. (+333) : Characterization of a TCE

Interwell Tracer Test for Nonaqueous Phase

DNAPL ZONE in Alluvium by Partitioning

Liquid and Water Residual. Environmental Sci-

Tracers. Groundwater Monitering & Remedia-

ence and Technology, -- (+0) : ,2,/ῌ,2,2.

tion, Winter : 2.ῌ3..

Mayer, A.S. and Miller, C.T. (+33,) : The inﬂuence ofporous medium characteristics and measure- : ,**.  +  ,2  : ,**.  .  -* ΐῒῑῌῐ
J. Jpn. Soc. Soil Phys.
῏῍ῌῐῑ῎
No. 31, p. ,/῍-* ῎,**.῏

A Simple Estimation of Excess Rainwater Percolation froma Buried Container into a Vadose Zone
Katsutoshi SEKI*, Tsuyoshi MIYAZAKI*, Masaru MIZOGUCHI*, Hiromi IMOTO*,
Kotaro NAKAYA** and Hiroshi MIYAZAWA*** Graduate School of Agricultural and Life Sciences, The University of Tokyo,+ῌ+ῌ+ Yayoi, Bunkyo-ku, Tokyo ++-ῌ20/1, Japan** Enlighten-Corporation, +ῌ-2ῌ+ Katsutadai, Yachiyo City, Chiba ,10ῌ**,-, Japan
Abstract
This study evaluated the performance of a rainwater utilization system. Excess rainwater isdrained from rooftops into an underground container from which the water inﬁltrates from thebase and sides into the surrounding soil of a vadose zone. The saturated hydraulic conductivityof the soil where this system was used was very low at the surface and higher in the deeper layer
where the container was located. A simple method was proposed to estimate the steady recharge
rate of excess rainwater from the buried container into the surrounding soil of the vadose zone.
By modifying the steady recharge equation, which is widely used in the theory of the Guelph
Permeameter, a steady recharge rate from the container was calculated from the measured valueof saturated hydraulic conductivity and the size of the container.
Key words : Rainwater percolation, Rainwater utilization, Steady recharge, Hydraulic conductivity, Buried container+.

Introduction

Rainwater utilization is attracting a great
deal of attention, especially among people
living in regions where excess rainwater isavailable. In some cases the collected rainwater is stored in underground containers for use
in daily life and emergency. Excess rainwateris percolated to the surrounding unsaturated
soil to avoid inundation and surface runo# of
rainwater. Some people also expect that therecharge of groundwater may prevent the lowering of the ground level. When the rainwater
exceeds the capacity of the buried water tank,the management of the overﬂow is crucial forthe e$ciency of a rainwater collection system.
The potential of a storage system that captures overﬂow from the buried tank strongly
depends on the water retentivity and permeability of the soil of the surrounding vadosezone. In the +0th Century, people living on the
Aso plateau in western Japan dug rainwaterdrainage ditches around their residences (Japanese Association of Groundwater Hydrology,**+). The National Institute of Civil Engineering of the Japanese Ministry of Construction
implemented a system to recharge groundwater by collecting excess rainwater intoburied porous pipes, which drains the water
into the surrounding unsaturated soil zones
and, eventually, into the groundwater (Ishizaki+32/). The draft of the “Manual on the investigation and planning of a rainwater percolation
facility,” which was edited by the Society of
the Rainwater Percolation Facility in +33/, provides information on percolation ditches andtrenches, U-ditches, and pavement. However,
the manual did not provide information for
estimating the rates of inﬁltration from a watercontainer into the surrounding unsaturatedΐῐ῎῔῕ῑ ῒ 31 ῏ ῌ,**.῍26soils.
The objective of this paper is to demonstrate
a simple method for estimating the excess rainwater percolated from an underground container into the surrounding soil of a vadose
zone.
,.

Table +

Parameters for Equation (-) (after
Zhang, +332)

Soil texture

b+

b,

b-

Sands
Structured loams and clays
Unstructured clays

,4*1.
+433,
,4+*,

*4*3*4*3+
*4++2

*41/.
*402*40//

Materials and Methods,. + Study Site
The study site is located at Yachiyo City,
Chiba Prefecture, Japan. Boring tests revealed
that a dressed soil layer of about + m covers the
Kuroboku soil layer of *., to *./ m thickness.
Below the Kuroboku soil layer is a Tachikawa
loam layer of + to - m thickness. Both the
Kuroboku soil and Tachikawa loam are
Andosol, and they are known as Kanto loam.
,. , Soil Proﬁle Measurement
A ,-m soil pit was dug, and a soil proﬁle wasrecorded. The proﬁle of soil hardness wasmeasured in situ with the use of Yamanaka soil
hardness meter, which is widely used in Japan.
The empirical relationship between the reading of the Yamanaka soil hardness meter andthe soil hardness for the Kuroboku soil
(Watanabe, +33,) was used for obtaining soil
hardness values. Undisturbed cylindrical coresof /-cm diameter and /-cm height were taken tomeasure the saturated hydraulic conductivities, dry bulk densities, particle densities,
and water content. Saturated hydraulic conductivities were measured by using the fallinghead method with these undisturbed cores. In
situ saturated hydraulic conductivities were
determined with a Guelph Permeameter (Reynolds and Elrick, +321). In every measurement of
the Guelph Permeameter, the saturated hydraulic conductivity and the matric ﬂux potential were determined by least-squares methodby using three steady depths (/, +*, +/ cm)
measurement (Reynolds and Elrick, +321). In
the calculation of Guelph Permeameter, proportionality parameter, C, was determined byequation (-) using b+, b, and b- values of loam
soil in Table +.

Fig. +

Schematic diagram of a rainwater inﬁltration system.

Buried Container for Excess Rainwater
The rainwater inﬁltration system (Fig. +) is
brieﬂy described. Rainwater ﬂows from a rooftop to the ﬁrst buried storage container (C+).
The ﬁrst container preserves - m- of rainwater,and, when the rainwater exceeds this volume,
it ﬂows to a second buried container (C,). The
rainwater in the second container inﬁltrates
into the soil from its base and permeable walls.
A method will be shown here for estimating
the recharge rate from the second container tothe vadose zone ; the second container isreferred to as “the container” or “the cubic
container” in this paper. This system uses
excess water to recharge groundwater insteadof just draining the excess water into a drainage pipe. At the study site, the percolation
system container is buried at a depth of + to ,m and drains into the Tachikawa loam layer.
,. . Method of Estimation,. .. + Assumptions
A simple method is described to estimate thepercolation from a cubic container by calculating the percolation rate from a cylindrical container with an identical volume, i.e., the same,. -῕῔ΐῌῒ : A Simple Estimation of Excess Rainwater Percolation from a Buried Container into a Vadose Zone

base area and the same height. Two assumptions are made here. The ﬁrst is that the recharge rate from a cubic container and a cylindrical container is nearly equal when the areaof the base of each container is identical. The
second is that the matric ﬂux potential is negligible.
,. .. , Procedure
Reynolds and Elrick (+321) developed a numerical model of inﬁltration from a cylindricalwell with a constant pressure to calculate saturated hydraulic conductivity using the Guelph
Permeameter method.
According to their
theory, a steady recharge from a cylindricalwell into uniform and unsaturated soil is expressed as,pH,Ks,pHfm
Qῑ
῏pa,Ks῏ῌCC
where Q (m- sῐ+) is the steady recharge, Ks (msῐ+) is the saturated hydraulic conductivity, H(m) is the steady depth of water in the well, a(m) is the well radius, fm (m, sῐ+) is the matricﬂux potential, and C is a dimensionless proportionality parameter primarily dependent on
the H/a ratio. The ﬁrst term on the right handside of Equation (+) expresses ﬂow out of the
sidewall of the well, the second term expresses
ﬂow from the base of the well, and the third
term expresses the unsaturated component of
the ﬂow.
The matric ﬂux potential, fm, is deﬁned byῌῑfmῑ ῒ K῍y῎dy ; yi῔y῔*ῐ῎῍where y (m) is the soil water pressure head, yi(m) is the initial pressure head in the soil surrounding the well, and K (y) is the unsaturated
hydraulic conductivity (m sῐ+) at the pressure
head of y.
Zhang (+332) provided empirical formula todescribe C from the data calculated numerically by Reynolds (+320) :Hῌa ῎bCῑῌ῎
῍b+῏b, Hῌa῏
where the values of b+, b,, and b- are shown in
Table +.
Based on this theory, a simple method is27

shown for calculating the recharge rate from a
cubic container, (i.e., well), with a base area of S(m,). According to the ﬁrst assumption, thesteady recharge Q from the container is equal
to the steady recharge from a cylindrical wellwith an identical base area, where῏Sῑpa,
By solving this equation with a, substituting
it into Equation (-), substituting the value of C
into Equation (+), and assuming fmῑ*, the following equation is obtained :
῍
῎b- ῒ
,ῌb+
Qῑῐ
ῑ,pH ῍H ΐ ῏ ῏b,῏ ῏SΐKsῐWhen the values of Ks, S, H, b+, b,, and b- aregiven, the value of Q can be calculated, and thesteady recharge from the container using
Equation (/) can be estimated.
-.

Results and Discussion-. + Soil ProﬁleFrom the observation of the soil pit, from thesurface to *., m was a dressed gravel layer ; *.,to *.3/ m was a dressed soil layer ; theKuroboku soil layer was *.3/ to +., m from thesurface ; and the Tachikawa loam layer, at thebottom of the pit, was from +., to ,.* m. The
proﬁle of the soil hardness and volumetric percentages of the solid, water and gas phases areshown in Fig. ,. As shown by the proﬁle of thesoil hardness, the soils were remarkably harderat the surface *./-m layer and at the +.1ῑ,.* mlayer than at the layer of *./ to +.1 m. The solid
ratios of the dressed soils were .* to ./῕, andthose of Kuroboku soil and Tachikawa loam
were +3 to ,+῕.
Saturated hydraulic conductivities measured in situ by the Guelph Permeameter andthe falling-head method with undisturbed coresamples are shown in Fig. -. Each of the coresample values is the logarithmic means of ﬁve
replicated samples. The saturated hydraulicconductivities of the soil surface, i.e., thedressed soil layer, were in the order of +*ῐ+* msῐ+. The very low value of Ks in the dressed soil
layer is because of extensive compression of
the surface soil to make a rigid ground for

28

Fig. ,

Fig. -

31,**.

Soil hardness and volumetric percentages of solid, water and gas phases.

Saturated hydraulic conductivity, Ks,
measured by the falling-head methodwith undisturbed core samples and the
Guelph Permeameter in situ.

construction. The saturated hydraulic conductivities increased dramatically at a depth
between *.2 and +./ m from the surface to theorder of +*0 m s+, and they increased to theorder of +*/ m s+ at a depth of , m. These
results agree with the Ks value of about +*/ ms+ of the Tachikawa loam soil measured by
Tada (+30/). The bulk density of about *./ Mgm- in Tachikawa loam layer also agrees withthe measurement of Tada (+30/). This proﬁle isuseful to explain the merits of this inﬁltration
system in this region because the rainwater
does not percolate easily into soil if it falls
directly onto the ground, where the Ks is very
low ; however, when the rainwater ﬂows to theunderground and percolates into a much more
permeable soil layer by this system, the rainwater is recharged much more easily because
the Ks is higher.
The ﬁeld saturated hydraulic conductivity
measured by the Guelph Permeameter was
lower than the laboratory saturated hydraulicconductivity measured by the falling-head
method with undisturbed core samples fromthe depth of +.- and +.0 m (Fig. -). A possible
reason of this is that we compacted the innerwall of the observation well when we dug ahole for the Guelph Permeameter. According
to the Guelph Permeameter measurement, thematric ﬂux potential was +./ +*1 m, s+ at
the depth of +.- m.
-. , Calculation of the Recharge Rate
Parameters used for the calculation are
shown in Table ,. By putting the values of b+,b, and b- of loam in Table + and the parametersin Table , into Equation (/), the steady recharge rate was calculated as Q  1.2*+*/
m- s+.

ΐῒῑῌῐ : A Simple Estimation of Excess Rainwater Percolation from a Buried Container into a Vadose Zone

Table ,Ks
S
HParameters used for the calulation/4*῎+*0 m s῍+.41 m,*43. m-. - Evaluation of the Model-. -. + E#ect of the shape of the container
At ﬁrst, we will evaluate the ﬁrst assumptionthat the recharge rate from a cubic container
and a cylindrical container is almost the same
when the area of the base of each container is
identical. It is reasonable to assume that thesteady recharges from the bases of both wells
are equal because each base area is equal, and,inevitably, the depths of stored water are equalin each well. On the other hand, the side areasof cubic and the cylindrical containers are
di#erent, so it may seem inappropriate toassume that the steady recharge from bothsides of the wells is equal. Actually, simple
geometrical mathematics indicates that theside area of the cubic container is about +,.2ῌ
larger than that of the cylindrical container. It
is necessary to point out that the ﬁrst assumption and resultant estimation of the ﬁrst termof the right-hand side of Equation (+) may underestimate the recharge rate from side wall of
the well, and it may be as much as +,.2ῌ larger
than the estimated value. From a practical
viewpoint, it is better to underestimate than tooverestimate the recharge rate because the underestimated value works as a minimum estimate of the percolation capacity of the container.
-. -. , E#ect of the matric ﬂux potential
According to the value of the matric ﬂux
potential measured by the Guelph Permeameter, the third term on the right of Equation(+) is +.1.῎+*῍0 m- s῍+, and it is only ,.,ῌ of therecharge rate calculated. Therefore ignoring
the matric ﬂux potential is justiﬁed in the condition of the experimental site.
However, the matric ﬂux potential depends
on the initial water content and soil type. According to Reynolds and Elrick (+321), the29matric ﬂux potential component of Equation(+) increases in relative importance withdecreasing well radius (a), with decreasing
depth of ponding in the well (H), with ﬁner soil
texture, and with decreasing background soil
wetness (decreasing yi). When applying thismodel to actual site, background soil wetness isa variable and the recharge rate calculated
from Equation (+) is a function of the initialwater content. Therefore a minimum estimateof the recharge rate can be obtained by assuming maximum initial water content. In thismodel, by assuming fm῏*, we get the minimum estimate of the recharge rate.
-. -. - Technical notes
The Ks of the permeable wall of the container
should be larger than the Ks of the surrounding
soil. Otherwise, the steady recharge is determined by the Ks of the permeable wall, not by
the Ks of the surrounding soil. Moreover, theKs of the permeable wall may decrease withtime by the e#ect of clogging, and therefore
the system should be maintained by cleaning
the permeable wall.
..

Conclusion

We showed a simple method to estimate
excess rainwater percolation from a buried
container into the surrounding soil of a vadosezone. In the study site where the rainwaterinﬁltration system was used, the saturated hydraulic conductivities of the soil surface werein the order of +*῍+* m s῍+, and they increased tothe order of +*῍0 m s῍+ at a depth between *.2
and +./ m. They increased further to the orderof +*῍/ m s῍+ at a depth of , m. Using a Ks valueof /.*῎+*῍0 m s῍+, the steady recharge rate wascalculated as 1.2* ῎ +*῍/ m- s῍+. In the model
presented here, the e#ect of the matric ﬂux
potential was ignored. Ignoring the matric ﬂux
potential in the studied site was justiﬁed by thecalculation that the matric ﬂux potential was,.,ῌ of the recharge rate, but it must be notedthat the matric ﬂux potential becomes larger
when the initial water content is smaller andwhen the soil texture is ﬁner. The model pre-n{:­k; ® 31 ¯ °,**.±

30

sented here may underestimate the recharge
rate because of two assumptions, and it gives aminimum estimate of the maximum possible
recharge rate from the container. At actual
construction site at Chiba prefecture, Japan,
the model has been implemented successfully
to estimate the rainwater percolation rate togroundwater.
References
Ishizaki, K. (+32/) : Inﬁltration capacity of a pipeburied in the ground and its application. Data
Nat. Inst. of Civil Eng., ,,.0 : -/ῌ/-. (in Japanese)
Japanese Association of Groundwater Hydrology
Ed. (,**+) : Inﬁltration of rainwater and fostering of groundwater. Rikou Tosho Co. Tokyo,
Japan. (in Japanese)
Reynolds, W.D. (+320) : The Guelph Permeameter

method for in situ measurement of ﬁeldsaturated hydraulic conductivity and matricﬂux potential. Ph. D. Dissertation. Universityof Guelph, Guelph, Ont.
Reynolds, W.D. and Elrick, D.E. (+321) : A laboratory and numerical assessment of the Guelph
Permeameter method. Soil Sci., +.. (.) : ,2,ῌ,33.
Tada, A. (+30/) : On the compaction curve of the
Kanto loam and its permeability +. Trans. Agr.
Eng. Soc. Japan, +. : -0ῌ.*. (in Japanese)
Watanabe, H. (+33,) : Studies on the soil proﬁlemodiﬁcation in humic Ando soils in uplandﬁeld. Special Bull. Chiba Prefect. Agric. Exper.
Stat., ,+ : +ῌ32. (in Japanese)
Zhang, Z.F., Groenevelt, P.H. and Parkin, G.W.
(+332) : The well-shape factor for the measurement of soil hydraulic properties using the
Guelph Permeameter. Soil Till. Res., .3 : ,+3ῌ
,,+.

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Journal of the Japanese Societyof
Soil Physics
July ῍ῌῌ῎

No. 31
Contents.0th Japanese Society of Soil Physics Symposium (Information)

Recommendation of Japanese Society of Soil Physics Prize candidate (General invitation)
Foreword ῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌJ. CHIKUSHIῌ+

Original Papers
Field Estimation of Soil Dry Bulk Density Using Amplitude Domain Reﬂectometry
DataῌῌῌῌῌῌῌῌῌῌῌῌK. WIJAYA, T. NISHIMURA, M. KATO and M. NAKAGAWAῌ

-Precision analysis of Partitioning Interwell Tracer Test for estimating a NAPL inaquifer ῌῌῌῌῌJ. NISHIWAKI, C. TANG, Y. SAKURA, M. MIZOGUCHI and T. MIYAZAKIῌ +Notes
A Simple Estimation of Excess Rainwater Percolation from a Buried Container intoa Vadose Zone
ῌῌῌK. SEKI, T. MIYAZAKI, M. MIZOGUCHI, H. IMOTO, K. NAKAYA and H. MIYAZAWAῌ ,/Readers’ column ῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌT. SATOῌ -+Book review ῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌH. YOSHISAKOῌ -Announcements ῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌ -/Editor’s Postscript ῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌ -1

Japanese Society of Soil Physics
Department of Environmental Management Engineering
Faculty of Environmental Science and Technology, Okayama University-ῌ+ῌ+ Tsushimaonaka, Okayama 1**ῌ2/-*, Japan