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῏῍ῌῐῑ῎
No. 3/, p. -ῌ++ ῍,**-῎In-situ Measurements of Density and Distributionof Periphery Roots of Tomato Seedling
Using Machine Vision System
Manzo UCHIGASAKI*, Shingo MIYAMOTO*, Kazuhiro SERATA*,
Sheishu TOJO** and Kengo WATANABE*** Department of Bioenvironmental & Agricultural Engineering, Nihon University, +200,
Kameino, Fujisawa ,/,ῌ2/+*, Japan** Faculty of Agriculture, Tokyo University of Agricultural & Technology,
Saiwai-cho, Fuchu, Tokyo +2-ῌ2/*3, Japan
Abstract
A new, simple method for evaluating and quantifying the peripheral root and its architecture
was developed and applied to tomato (Lycopersicon esculentum Mill.) seedlings. This method
consists of the use of a transparent tray cell and application of shade in roots, using an image
analysis system.
The objectives of this study were to : (+) develop an in-situ measurement technique using
machine vision technology for the quantiﬁcation of the peripheral root growth of seedlings usingtransparent tray cells ; (,) to develop a program to analyze the Peripheral Root Density andDistribution (PRDD) ; and (-) to study the characteristics of the seedling root system in an
air-pruning tray cell. The speciﬁc PRDD value was calculated for the air-pruning tray cell and a
non-air-pruning tray cell and ﬁve stages of the seedling. Analysis of the results showed that thismethod can be useful for evaluating peripheral root architecture in di#erent designs of tray celland can be used not only to analyze the e#ect of air-pruning but also to determine the e$cient sizeand design of tray cells.
Key words : Root growth analysis, Machine vision, Peripheral Root Density and Distribution(PRDD), Air-pruning tray cell.

+.

Introduction

Healthy seedlings of uniform size are
required for transplanting in order to produce
a uniform stand in the ﬁeld. Many studies haveindicated that seedling establishment andgrowth performance depend on the speed of
the root system development (Huang et al.,+33,). Roots are the underground portions of aplant that interact with the soil. The rootsystem of a plant may have more branches
than the shoot system (Wang et al., +33/).
Common problems associated with containerized plant and seedling production are

root-tangling and root-spiraling, commonlyreferred to as “root-binding”. Root-binding
deters development of the root system after theplant or seedling is transplanted, resulting inslower growth of the plant. When the plantroots emerge through the holes of a container
they shrivel due to exposure with air. This is
usually referred to as “root air-pruning”. Oncea root has been air-pruned, the plant immediately starts a new root branch. Proper application of air-pruning to a root system therefore
promotes secondary root growth and eliminates root-binding, resulting in a large root
mass.

῏

4

ΐῐ῎῔῕ῑ ῒ 3/ ῏ ῌ,**-῍

Since each variety of plant grows to a moreor less recognizable form and size at each stageof growth, modeling and simulation techniques
would provide an e#ective means for exploration and prediction of the pattern of plant
growth. A simulation model can be formulated
by considering factors which a#ect the growthand development of root system elements, suchas the main roots, root branches and root hairs.
Microcomputerized image analysis (Machine
Vision) is a technique which has particular
merit for the evaluation of the roots of plantseedlings, since it permits direct, objective,
non-intrusive visualization and measurementof both roots. The essential components formachine vision analysis of a seedling root include : +) a standardized staging environment,,) an image capture device (e.g., video camera),-) a digitizer board housed in a microcomputer,and .) display devices [monitors] for presentation and interactive measurement of thedigitized image.
Evaluations of plant root systems are particularly challenging in nature, because roots areburied in soil, sensitive to excavation and intricately arranged within the soil matrix.
Image analysis has proven to be an excellent
tool for direct analysis of root zone data inplant production and for investigation of root
growth rates. The shoot culture imaging wasused for examining root zones ; close-up imaging was used in some instances to inspect root
surface feature (Smith et al., +33/). Pasian et al.
(+333) developed a new simple method forevaluating and quantifying the root severity.
This method consists of surrounding the root
pan with a transparent ﬁlm and tracing all
roots with a marker. Root-length measurement is important for the evaluation of root
functions and of inﬂuences of the soil environment. Accurate and rapid root-length measurement methods are, however, still under development (Kimura et al., +333). Minirhizotrons
speed up research on root demography, but
image quality often hampers standardizationof the image-processing method. A simple pro-cedure working within the blue band of thecolor image was tested on the ﬁbrous roots ofsugarbeet (Beta vulgaris var. Sacharifera)(Vamerali et al., +333).
Recently the use of high-resolution digital
image analysis based on personal computers
has increased in agricultural science, because
image analysis has several advantages, including its non-destructive nature, high speed andhigh accuracy (Box et al., +330), (Omasa et al.,+332) and (Chikushi et al., +33+).
Smith (+33/) indicated that because powerfulimage-editing software could show the numberof pixels in a selected area and the color index
of the selected pixels, it could easily obtain theratio of root spot area to total root area using asimple procedure of image analysis.
Equipment to measure root area has been
available for some time. A CCD camera tocapture an image, and computer software,using mathematical algorithms, are used tomeasure pixels on the screen and to estimate
the area and length of such an image. This
computer technology allows easy quantiﬁcation of some root characteristics and helps
remove some of the subjectivity of humananalysis. Although it can in theory distinguishbetween soil and roots based on di#erences inshading, its use requires the proper lighting
balance to maximize contrast.
In this study, image-processing techniques
are applied to describe the general growth dynamics of a root system in a tray cell. Since
seedlings generally exhibit complex patternsof root development in a tray cell, a peripheral
root density and distribution (PRDD) program
was developed to measure the number densityof roots and their spatial distribution for aseedling at a speciﬁc growth stage.
The objectives of this study were :(+) To develop an in-situ measurement technique using machine vision technology
for the quantiﬁcation of peripheral root
growth in seedlings using transparent
tray cells ;(,) To develop a program to analyze theῐ῏ : In-situ Measurements of Density and Distribution of Periphery Roots of Tomato Seedling Using Machine Vision System(-)

PRDD and ;To study the characteristics of the seedling root system in an air-pruning tray
cell.
,.

Materials and Methods

Experimental Apparatus and Image Acquisition
A CCD (SONY, XC-1+++) color video camera
was used to capture root images. The camera
was ﬁtted with a lens (VCL ,/ mm, F,.,).
Images were captured and digitized with a resolution of 1/0ῌ.20 pixels at 2 bit/pixel for eachred (R), green (G) and blue (B) color component.
With 2 bit color resolution, the values for eachpixel ranged from * to ,//. Captured images
were stored as bit-map (bmp) ﬁles in a Gateway(,22 MHz Pro) microcomputer and displayed ona Mitsubishi diamontron color monitor. Imageprocessing and analysis software was developed and executed on the Gateway computerand all algorithms were implemented in the
Visual basic (Version 0.*) programming language. Fig. + is a schematic diagram of themachine vision system. Light was provided by
two -**-W lamps with an input voltage of +**V. A pneumatic control system rotated the tray
cell in a circular (-0*῍ degrees) motion andcontrolled each step (3*῍ degrees). The resulting digitized bmp-format image had a width ofFig. +

Schematic of the components of themachine vision system. Artiﬁcial light
was used for illumination.

5

1-0 pixels, a height of /0* pixels and a size of+.,*3 MB. The digitized image was calibrated
to record the precise dimensions of the image
and relate these dimensions to the actual sizeof the tray cell. The carefully-calibrated, digitized image of the seedling root were comprised of a pixel array that preserved all of themorphometric (spatial) and photometric (spectral) features. In this experiment the soil (Dega
Potgrand Delft, Netherland) was used soil andpeat most (+/- of total volume of the soil).
Plant Material and Air-pruning Tray Cell
The design of the air-pruning tray cells wasdeveloped by Huang in +31-. Fig. , shows atransparent air-pruning tray cell and a blackcovered air-pruning tray cell. Tomato seedlings (Lycospersicon esculentum Mill.) weregrown in a growth chamber (Biotron -/*) at an
air temperature of ,-῎, relative humidity 1*ῌ
and a light intensity of +,,*** Lux (with a +,-h
photoperiod). Detached root systems were
sampled at --day intervals after the one-rootstage. Images of the four sides of each tray cell(air-pruning and non air-pruning tray cell)were captured (Fig. +) on ﬁve observation days
from germination : -, 0, 3, +, and +. days, thus
providing a sample of /+, images.
Image Processing (Win-Roof)Figure - a shows the procedures using the
Win-Roof (Mitani Corporation Inc.) imageprocessing system. The original image of theroot underwent the following processes. (+)
Color measurement : measuring the averagecolor of the pixels within an on-screen region.
(,) Color extraction : counting the pixels of a
speciﬁed color within an on-screen region andthereby obtaining the area. (-) Calibration : theroot image was adjusted to give a clear contrast between the tray cell area and the root
area. (.) The root image was obtained by extracting the root area from the tray cell and all
exposed roots were traced in green. (/) Shading
applied to seedling root. The brightness of theroot in the original image varied with the position of the root. In the binary image, roots
were seen clearly, even for areas of low bright-

6

Fig. ,

3/,**-

The conﬁguration of the air pruning and non-air-pruning tray cells used in the study.

ness. In the original image, the tangled roots atthe base of the root system were transformed
into clearer lines than those in the original or
binary image. Although partial root image
was lost by this operation, the loss was relatively small when compared to the total area ofthe root system.
Algorithm Development (PRDD program)(Figure - b) shows a ﬂow-chart of the PRDD
program that was developed. The next procedure was as follows : (+) The starting point was
the image of the root already processed using
the Win-Roof program ; (,) Input of image
data ; (-) Determination of range of image processing ; (.) Setting of conditions for root
(selecting only root images from the background and counting the number of pixels in
the total root area) ; (/) Setting range for all
pixels ; (0) Extraction conditions ; (1) Calculation of the number of pixels (selecting only theroot area and counting the number of pixels) ;(2) Repetition ; (3) Determination of root distribution for each layer and the ratio between
total number of pixels for the root and total
number of the pixels for one layer ; (+*) Calculation of the root area as a percentage of thetotal layer area (pixels) ; and (++) Measurementof the total root area after evaluating the distribution of root area in the periphery of the traycell.
Peripheral root density (PRDD) was calculated
as follows :PRDD (ῌ)(TRA/TTA)+**Where TRA is the total root area in one layer
and TTA is the total area of one layer of the
tray cell (both measured in mm,).
Fig. .
showed a processed image using the PRDD
program showing the distribution of root ratio
in the tray cell of the eight layers.
-.

Results and Discussion

Soil luminance varied only weakly withtime, depending on soil moisture and on theillumination intensity, neither of which wereconstant, whereas root luminance decreased
progressively with time, due to senescence.
The root image obtained using the transparent tray cell method has the advantages ofbeing less subjective and less dependent on
evaluator experience. It also allows a longer
period of evaluation because of its nondestructive nature. On the other hand, it re-῍ῌ : In-situ Measurements of Density and Distribution of Periphery Roots of Tomato Seedling Using Machine Vision System

Fig. .

Fig. -The procedure involved image capture
and processing, followed by measurement using an image analysis
system. Flow-chart for (a) Win-Roof(Mitani Corporation Inc.) and (b) the
PRDD program used to determine theroot distribution in each layer (one tray
cell separated into eight layers) ; see thetext for detailed explanation.

quires an expensive, although easy to use,
video camera that may not be available toeveryone.
The method takes into account only roots at
the periphery of the tray-cell, ignoring roots
located at the center. This should not be aconcern because most actively growing rootsof plants grown in containers tend to be at the
periphery of the root area. Furthermore, inorder to image roots at the center, the growing

7

A processed image using the PRDD
program showing (A) a preprocessedroot image, (B) the distribution of rootsin the eight layers, and (C) the resultsof peripheral root density and distribution calculated for roots in theeight layers.

medium must be removed which can also dislodge damaged roots causing an increase in theevaluation error.
This problem may be
aggravated with vegetable plants, such as thetomato used in this study. In the case of root
areas where there are numerous ﬁne roots too
close to each other to trace individually, theroot image analysis method allows for area
measurement of only total root areas of highand low root growth.
The results of image analysis demonstratethat shortly after the ﬁrst branching, a second
branching occurs midway through the tray
depth in a pattern similar to the ﬁrst branching. Stage - [air-pruning - preprocessing image(AP-B)] shows dominant downward and diagonal root growth. At stage / (AP-B) the cellshows “ﬁlling” of the upper soil layer withroots are ready to produce new roots as soon as
the seedlings are transplanted. This process
can be observed using the PRDD program byrelating the root growth, the root growth rate,
cell size, branching and sub-branching rates, as
shown in several stages of air-pruned root development in Fig. /. Seedling production canΐῐ῎῔῕ῑ ῒ 3/ ῏ ῌ,**-῍

8Fig. /

Five stages of shoot and root development of tomato (Lycospesicon esculentum Mill.)
seedlings using an air-pruning (AP) and non-air-pruning (NP) tray cells. The image
processed using the PRDD program is shown for air-pruning (AP-B) and non-air-pruning(NP-B) tray cells. Stage / (NP-B) shows dominant downward and diagonal root growth
while stage / (AP-B) shows “ﬁlling” of the upper soil layer with roots, stage - (AP-B) shows
rapid elongation of the stem while stage - (NP-B) shows low growth.

be optimized according to plant species, minimum time requirement and cell size. For the
non-air-pruning tray cell at stage - (NP-A), theﬁrst root continues to elongate, spiralingaround inside the base of the container cell. At
stage / (NP-B) the peripheral root can be seen
to be concentrated around the base of the tray

cell. This would result in severe root-binding.
The results using the PRDD program to calculate peripheral root area distribution for the
air-pruning tray cell. The program determinedthe distribution of the roots among eight layers
for each cell. The value of the area of the rootis the average of four repetitions. Images of῍ῌ : In-situ Measurements of Density and Distribution of Periphery Roots of Tomato Seedling Using Machine Vision Systemeach cell were captured for all four sides.
Figure 0 shows the root distribution proﬁleof the air-pruning tray cell with depth. The
results demonstrated a signiﬁcant development of the root 3 days after germination(August +). The air-pruning e#ect could beobserved by the development of the root
through the center of the tray cell (depth : +./ῌ..* cm).
Figure 1 shows the root distribution proﬁleFig. 0Fig. 19of the non-air-pruning tray cell and depth. The
results demonstrated non-signiﬁcant development of the root on all data collection dates.
The di#erence between the maximum area ofthe root using the air-pruning and non-airpruning tray cells was 01.2/ῌ. The root
growth process illustrates that root development within a air-pruning tray cell is far superior to non air-pruning tray cell.
The advantage of the present system is its

Root distribution proﬁles and depth of tomato seedling in air-pruning tray cell.

Root distribution proﬁles and depth of tomato seedling in non-air-pruning tray cell.

ΐῐ῎῔῕ῑ ῒ 3/ ῏ ῌ,**-῍

10

rapid processing time. Measuring a series oforiginal color images and reconstructing thecorresponding surface image with color texture can be accomplished automatically in a
few minutes, which is probably less time thanis required by other methods. Moreover, byincorporating the software that we developed,
the resulting surface image can be observed
the distribution of the root in layers (2 layers).
..

Conclusion

The newly developed method using machine
vision provides good results when used tomeasure peripheral root area. The most important information discovered from the study
was :(+) The results analysis showed that thepresent method can be useful for themeasurement of peripheral root density(PRDD) and architecture in di#erent
designs of tray cell, in order to understand the characteristics of the seedlingroot system ;(,) The use of transmitted light allowed us
to acquire a very clear image, by which
we could quantify, the root spot severity precisely and easily. This result
suggested that image analysis usingtransmitted light could be a very useful
tool to quantify root area in plants withvery complex root growth patterns,
such as tomato seedlings.
(-) The method takes into account onlyroots at the periphery of the root area,
ignoring roots located at the center.
Future work might investigate a discrimination analysis taking into account features suchas root texture and soil color. The fundamental
study to discover new and e$cient designs of
tray cells will be necessary.
Acknowledgments
The authors would like to thank Mr. Ryuichi
Ikuta (Dia-Topy Inc., Japan), for his cooperation in the design of the transparent tray
cell used in this study. Special thanks go to Mr.

Hiroyuki Okawa and Hiroko Nakazato (Graduate student, Department of Bioenvironmental& Agricultural Engineering, Nihon University),
for his assistance in acquiring seedling root
images.
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Waisel, Y., Eshel, A. and Kafkaﬁ eds. p. +3-ῌ,-1.
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Smith, M.A.L. (+33/) : Image analysis for plant cell
culture and micropropagation. In AitkenChristie, J., Kozai, Smith, M.A.L. : Automationand environmental control in plant tissue culture. Kluwer academic publishers, p. +./ῌ+0-.
Vamerali, T., Ganis, A., Bona, S. and Mosca, G. (+333): An approach to minirhizotron root image
analysis. Plant and Soil, ,+1 : +2-ῌ+3-.
Wang, L., Huang, L.K. and Huang, B.K. (+33/) : Simulation of root air-pruning and plant growth
performance, Mathematical Modeling and
Simulation in Agriculture and Bio-industries,
First International Sysmposium, IMAC/IFAC,
V-III-C : +ῌ0.

¸¹ : In-situ Measurements of Density and Distribution of Periphery Roots of Tomato Seedling Using Machine Vision System 11   *ῌ *ῌ

*ῌ**ῌ***  !,/,῏2/+* "#$%&'(** )*+* !+2-῏2/*3 ),-.(



/01234567 89:;<=>?@5ABCDE FGH IJ>KLMNO5PQC RSTUVWXYZ[8:;?@Z\;E ]^Z_`aCD/HKbK cLycopersicon esculentum Mill.d /Z\;E ef0ghH ῌ IJ>KLMNO5ijkbVlmnolapqr/.010s589
hat[:;uv0wx ; ῍ KLMNO0yz{Z|[}G;10{~ cPRDDd 5TU:;
Y0wx ; ῎ O lKLMNOa;/010s5 / akZ0 PRD
00>5:;Fa\;E t[0TU 10xr5:D0 PRD [80NOZ01 340TU0Da F0?@¡¢iZ£;F¡¤DE ¥D@HO l0¦KLMNO0§¨>©Mªp«0¬ta­®iZ£;¯°G;E : bVlmnol 10[8 10±² O lῌKLMῌNO³´µ¶ : ,*** µ 0 ¶ ,* ³·µ¶ : ,**+ µ 3 ¶ - 
J. Jpn. Soc. Soil Phys.
ef¼
No. 3/, p. +- ,* ,**-



 *ῌ*Adsorption of Nitrogen Chemical Fertilizer on Volcanic Ash Soil andElectric Charge Characteristics
Susumu MATSUKAWA* and Hidemasa KATOU** Faculty of Agriculture, Utsunomiya University, Utsunomiya -,+ῌ2/*/, Japan
Abstract
Ammonium sulfate or ammonium nitrate solution was added repetitiously in volcanic ash soil.
The di#erence in amount of anion adsorption or cation desorption, and the change in pH werecompared with the simulated results by the four plane model. pH of soil solution was lowered by
the addition of the ammonium nitrate solution, and pH was increased in the ammonium sulfate
solution. The amount of desorption of the base cation in the ammonium nitrate solution waslarge than that of ammonium sulfate solution addition.
The adsorbed amount of sulfate ion was increased, even if pH rose in the ammonium sulfate
solution addition. The amount of sulfate ion adsorption was depended on concentration, andthat didn’t depend on hydrogen ion concentration by adaptation of regression equation thatcomposed with anion and hydrogen ion concentration. Sulfate and nitrate ion adsorption
calculated by the four plain model were corresponded to the measurements well. Comparing thesimulated charge density at each plain, addition of ammonium sulfate solution was large thanthat of ammonium nitrate solution addition. In the case of ammonium sulfate solution addtion,amount of hydrogen ion adsorption on S plain was large than that of hydroxyl ion compared withammonium nitrate solution addition. These simulated results correspond with the pH measurements.
Key words : nitrogen chemical fertilizer, volcanic ash soil, pH, ion adsorption, electric charge

6A5" z{|;+    5^()*+,- }NH.#, SO.~" $()*+, }NH. NO-~ 

/ ef%Y /?B !" ,**,# $%" &'()*+,-

/L?" ( ῌ ( ῌ )*+,-

. /01" 23 /, 2, ++ '456787

" ef  i" pH . F/YB@ 6+/2, +/3, +.0  t 19:;. <=>7;?@ ABC"

YN" A7>P1k3( BC

DEF5

Q7B{

<" GH1I;J K

LM7N?1OPQ7" $ER¡¢3*£¤" Barrow et al. +321#/?N¥¦YB4§F/Y"SῌTFUVKWX1YNZ[Q7\]^1

ῌ¨§ i©ªK¢«

_`Q7@ aB" bcdDefgh ijk<"¬/­®YB@ ¯°" ()*+,-" ()*+lmneK .1῍ efopqrstpuvwx" +33+#,- /6787± " ± 1²Ya@/yCN?@* ³´µ9 ¶ · ¸-,+ῌ2/*/ ³´µ¹º -/* : "  ef" pH" " »¼

 = P 3/ ¼ R,**-S

14

Jf.- /g-*bh#&ij+34-%OF,   k1

,+ 

,,   /* mL l0m&no! *./ kg kg*+

p

q-Ar / g 11 s2o -/ mL 3t +2 uvw

      

FxywFx zN wFx{ l0m4b-.*0* cm   , mm*-

 !"#$ %&'()& NO&"+,-./01 2345678"+,9

pH |,ῌGHIJ567}q'(3tF , 58c *.*+ mol L*+~67

RNH.S, SO. :;  <ῌ" = + &>

 NH.NO- *b -/ mL 3t 3t*b56&j   +?&>&';

L,*b3t wFx l9 / 5(@A=BC  , D

Ca,E F Mg,E @A=GHIJ:  ,HIJ|GHIJ ; f.-r SO.

,*+,9 3t*b- *b{ l0m4<*b-!K"L#M1NO P$= %&'( Q R+331S?

-3t5=&l0m

q- R*b>6 + gT&UVN WXY + &> Y) Z[cm*- FN(;S Nr  %&'( Q R+32+S &?\1NO,]^_*b3t&ON , ?]

:, P$Z['( *b-s2o *.*+ mol L*+ *b3t{ l0mwF

d!=!=+e ,HIJ@A-

xy +2 uvwFx wFx{l9y9RCECS '(GHIJ@A- RAECS -%L GHI

b *../ mm (ON5`a
pH 0 cJ *b @ON $¡
ῌ+



ῌ"

A& pH  ( b, GHIJ=

Table + Physical and chemical properties of soil
pH RH, *S
pH RKClS

/40/
/40,

H®nH- R¯I}῍S *++41

H®nH- R¯7}῍S *+*4+-

CEC Rcmolc kg*+S *,
Ca,E
Mg,E
KE
NaE
BCJK6 R῍S

,,41,
*4-+
*4,+
*4+1
*4+3
-4/,

@A=GHIJRcmolc kg*+S*Cl*
NO-*
SO.,*

*421
*4-0
+413

°!±

,41,

L6² : ³´ R῍S
µ¶
·¶
M¶
N
¸¹ Q&',
56(FNO NH.E 7}s2 ( ,HIJ¢£f¤ GHIJHIJ¥¦&'(-    
-+

pH 

s2o3t

+ 58§0 *.*+ mol L*+ B¨ / 5C©3t ª¨*b

pH "Y , &> B¨*b3t pH /./0 FD pH *./ «-¨*b pH -D *.1 E pH "&¬-2V
F­ B!HIJF!HIJ

f.&Gx OH* F,42,/4*1
.,413
,34-+
Light Clay*+ : CN º» R(no! -3.2῍S*, : Shollenberger *- : *.*+ M NaOH *bR, g : +/* mLSO

ῌ+Fig. +

P$Z[

Electric charge characteristics of soil.

£¤ : ¥¦§  ¨©S'%&ª«¬f

15

   `a^" IJHAQbcmp!^qxHA yA

!" #$%&'(

fsNOP" , z Ca,w Mg,w +F + z Kw

+, pH /./-0./ . /0123%"

Naw >{Q^qxHA |=^ IJ<X} Mg,w

)+332*



4567 89 pH :;< =>?@.A-, 

HA:U /

B0CD:EFGHIJHAKLMNOPQRST:U - Naw Q~Dgg:

VHA AWH IJ<X + <Y"Z[\H 

VHA + zfsNOP Naw ", zfsNOP+FH u=:VHvu IJ]Q^_  BNOPQ" . <Y`abc-- ῌIJHA *.*+ mol Ld+

eHA fMNOPg"h

MNOPsNOPg"^ HA

VHA+i  CldjNO-d ^_ >kNOPlm

C* : IJHANOPQ )mol Ld+* V* : IJCDg+nQo;:VH IJ.ABNOPdd-Cl  NO+F"bcmgMNOP>6pAqr.

A

)L* Cn : CDIJ n <YNOPQ )mol Ld+*
Vn : n <YCDIJCDg )L* Vrn : n <YCD~[CDg )L* h  n <Y
/0CD:INOPg" )Cnd+Vrnd+wCoVo*dCn

Q"IJ<X . <Y

Vn ^  =:g^ Hv n¡+ <sNOPQRS tuv" U .
w.

JHAKLT:VHA NH

ῌ,Fig. ,

ῌFig. -B0 /0CDIJ<X pH RS

pH change with repetitious ammonium
sulfate and ammonium nitrate solution
addition.

B0IJ]MNOPQRS

Anion concentration change with repetitious ammonium sulfate solution addition.

ῌ.

/0CDIJ]sNOPQRS

Fig. .

Cation concentration change with repetitious ammonium nitrate solution addition.

ῌ/

B0 /0CDIJ] Mg K ¢g

Fig. /

Ammoniu$ sulfate and Mg, Na accumulation desorption quantity in the ammonium nitrate solution addition.

K-@O A 3/ ¼ W,**-X

16

 n/ 



cmolc kg+ 

!

"#%& NO-  ' NH.$  7;

 0  + #  H$ pH 78 CEC FGL&l!%&7ῌ !" !"#%&' !"#()  *

(+,ῌ-,.

-,./ , 456 pH 7 *.1
8 9:1 .);5< NO- 
7=> AEC ; CEC 87?@A
BC& DE NO-  ;'.
 !"#7FG NH 7;H

C& IJ K. !"#7;L&MNOPQ7BC1RSBC&IT K.

7

'D op pH =>5& CEC ;l!%&=:H

C&  +) 25< !"#  ,. NH.$ H$^_7`BqBC
IJ DC ῌ !"# r pH bs7?
@&$g0'1 tuvw&x%yz{5&& r H$ OH

|}~3H

L&D

 !"#L&K. !"#%&.  

D7 UV W+32*X 5<YZBC1'&

!"#%&

7#'D NH.$ 7 , n

SO., D5< -, NH.$/0'123%&$.

m& f",.

.+   0 4+) 2L& H$
 !"#7[\']  H$^_l ,* ' (O)L&.*L&E #q%+?yz{7,7`B'D7& ,./ pH BC*./ => a pH bc7GI'de8 0Bowden et al.W+311XBolan and Barrow

%&D7fgHC IJ

!"#%&

NH.$  3Ihi

b- !"#.j/'C1

W+32.X Barrow et al. W+321X Goldberg W+33,X 7%& x%yz{1O0'1# b-!

-, !"#%& NO-   pH 8j1;  SO., )k pH
7=> AEC 7FGL&l!%&3( a ;

"# 01 Barrow et al. W+321X 5<!"# 2q&D74BC1'&$I3 4 W+32,X -.  

5C # !y ¡!¢J5p{£¤¥¦, -,./ pH  NH.$(+

 !"# 0 4 -,.]5b-%< .%.j%+yz{
5<&3HC&  x%yz{
J§&¨%!"#67 Barrow et al. W+321X
5C H$ OH  S % # ῌ !"# ῌb-!"#r©ª8 a % f9 ῌ !"#b %67BC&  d %«:!"#;7

 ¬­ , ©®¯&7<L&
DE ,ῌ-,.de83 
ῌ-!"# a %   $ I!"#

WNH.$X  b % L&  , |/'4  ,  aiani aicat «C°C i %!"# !"#±=  y  WmVX g ¨%  !"#  Wm molc m,X s ¨%&

Wm molc m,X C ¨%²> WFm,XL  KH, KOH, Kani, Kcat «C°C H$ OHῌ0Fig. 0ῌ !"#pH (+

*!"#



Adsorption of anion and cation in relation
to equilibrium concentration and pH.

!"#

!"#}

) Z ³)41'& B F : ´¡zµ ) R : ²+ ) T : ¶·  e : ²¸ k : {¹º# ) NS : S %»?!"#  NT : a b %»? «C°C

GH : IJKLMNO PQRSTUVWXY%Z[   1  Bowden et al. +32* !"#$ %&'()*+ ,-.
 /01  23456 Barrow N. J.


 Nernst  S  yS ῍ῌ,
Table ,

+321 78 pp. +,/9+-, :; <= a 01

Equations used for the Four-plane model+ῌ+> ai?ani@Concῌ
i Zῌ
i exp ῌZῌi FyῌRT+ῌ,> ai?cat@ConcῌῌZῌ
i Zῌ
i exp ?
i FyῌRT,> PZC@Alog KHB +.?log KOH Cῌ,-> yS@ KTῌe ,4-*- PZC?pH.> gS?H@NS aS?Hῌ +BKH aS?HBKOH aS?OH/> gS?OH@NS aS?OH +BKH aS?HBKOH aS?OH
0> sS@gS?H?gS?OH
1> ya@yS?sSῌCa b
2> ga?ani@NT Kani aa?aniῌ+BKani aa?ani
3> sa@ga?ani Zani+*> yb@ya? sSBsa ῌCa b++> gb?ani@NTZaniAKani ab?aniῌ +BKani ab?aniBKcat ab?cat C+,> gb?cat@NTZcatAKcat ab?catῌ +BKani ab?aniBKcat ab?cat C+-> sb@gb?catgb?ani+.> yd@yb? sSBsaBsb ῌCa b+/> sd@?+4,,D+*+*ECF*./sin h *4*+3/Zcat yd+0> sSBsaBsbBsd@*

ῌῌ1Fig. 117. 

Bowden et al. +32*

Schematic representation of Four-plane model (Bowden et al. +32*).

bc*W » 3/ ¼ ,**-18  , : ga ani

jiklm,DS !" jiklm3A 3   , : NS, NT, CSa, Cab, Cbd, KH, KOH,UVPA pH Lm $ iklm

KCat, Kan   !" !#$ %3A pH LUVP+m

& '( +33+ $ %)*( +33/ +,!-.D$  UVPA$ iklm+~,

/01 + 234$ 56 Marquardt 789

+Z" b:;<=!" >?$ 789@9ABC F-

D," hUVPAi$ jiklm

UV34!#$ ! NH. +g
N(=" NH. AUVP~Z($ iBASIC Ver 0.- ,DEF!"

NO$ Bowden etklm+jikLῌ"#al. +311 $ Barrow et al. +321 $ Kamewada +33/+4N" Alva et al. +33* A$ P$[bc3G H IJKLM $3A$  PQ  $ pH <N!R

M ST$ UVW 

X+EY=D,"Z $  P+Q 3$

pH <[\]A^_`abc3Adef>,gN(=" h3$ i$ jiklmnop pH$  P mol Lm - J

,+$  m molc

 D Mq

<!"

e

L$ Ca, +m¡¢D," !$ d

A£¤ , ¥¦§¨3$ iῌjik6©V D?$ ª% D,N"
$ S

?« pH  H$ OH +*  !" H Aiῌjiklm pH &FDm$ OH A

iῌjiklm pH Lm !" h>?$ rqb sA$ btuW^vwxyz{| +32-  / }~ 0* cm : --* m g,,D$ 

+ m molc m , 

D$ iklm pH [A,  !L¬$

pH /.2­0., jiklmL,'®34!

#$ OH Ailm+M=!"Z $ H AiklmRA$ jik!"lmL +­, ¯=$ iklm

.ῌ, ῎ῐ῏῍

H

IJK3

!aMm molc m , i$ jiklm

,D

2 

!"

AM

0 n3

$kg

 SO., +SQ

! cmolc

3 3 pH  UVPi$

 

,

²³ !">?$  - (M3´#! 
 !" b­dVµ) Cbd A¶ ·S ~$ Barrow +321 L=O$ b>!"!$

Abck pH +°±

d

A¸¹ D

, D," !$ H  o KH Ailm+ . ¯ºP~$ H +ῑῌ2Fig. 2

i$ jiklm aM S

3

Comparison of the experimental anion adsorption with calculated valuesin the aplane by four plane model for each solution addition.

ῑῌ3

i$ jiklmM pH­UVP

Fig. 3Caluculated charge density on four planes
in relation to pH.

ΐ¼ :  #$%&'(ῌ89 :;-c

19*+01g SO.,n ῐ>89῎_" pH efopjq1 D.c 7ῌ345689῎456rs t$456

rsuvwx " *+ NH.k" SO.,n 8
9῎_ Hk rsyz/c

OPQRST{|}ZYD

)[\D a P SO.,n"NO-n89῎_" BC~ ῍ D
0cpHP s FUV " *+01g s" *+01_" 3456ῌ<=ῑ῏
 D
ῌ+*

*+" ,+01g S P H"
OH 89῎Fig. +*

Calculated H , OH adsorption on S
plane in relation to pH.
ῌ-Table -

1c

S P Hk" OHn 89῎[\~G." *+01g Hk 89῎,+G." *+01_ pH efBC]^D" <&6Q" i _#$%(ῌ²³´µ¶·¸~

Most suitable value for each parameter

²³´µ¶

,+

*+

NS ¹mmolc mn,ºNT ¹mmo+c mn,ºCsa ¹F mn,ºCab ¹F mn,ºCbd ¹F mn,º
KH ¹L moln+º
KOH ¹L moln+ºKCat ¹L moln+ºKani ¹L moln+º

*420.
-43+3
+4-2*
*4/,.
+»+*0
+4*-*
,4,3»+*+4**»+*n0
-410*

,4/,3
.4*+0
.4++0
*4+**
2410»+*/,401»+*.
340,»+*/
34-0»+*n3.41-»+*,

 )j BC [\ "   )" #$%&'(ῌ89:;G. Mi
ED" ¡¢ (ῌ£¤¥¦B§¨©" ª¡Ht«¬­®¯M °±

ZY

  
Alva et al. (+33*) : Reactions of gypsum or phosphogypsum in highly weathered acid subsoil, Soil
Sci Soc. Am. J., /. : 33-ῌ332.
Barrow et al. (+321) : A comparison of models fordescribing the adsorption of anions on variable pH 







charge mineral surface, J. Colloid Interface Sci.,++3 : ,-0ῌ,/*.
Barrow, N. J. (+321) : Reactions with Variable-Charge/    

Soils. Martinus Nijho# Publishers. pp. +,/ῌ+-,, !" #$%&'(ῌ)*+" ,+-./USA.

01 " pH

Bolan and Barrow (+32.) : Modeling the e#ect of

2&" 3456ῌ745689:;" <=ῑῐ>?

phosphate and other anions on the surface@῎ABC D ED" F01G34568

charge of variable charge oxides. J. Soil Sci., -/ :9῎H pH 2&AIJKLMN" OPQRST )UVWX D
GaMbYZBC" [\]^_`+c ,+ῒd01

,1-ῌ,2+.
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pH  " *+

charge mineral surface. Aust. J. Soil Res., +2 : .3ῌ

,c <=ῑῐ>?@῎_" ,+01gh*+

Bowden et al. (+311) : Ionic adsorption on variable

_ pH ef D01gi." F

0*.

jῐ>?@῎_ Nak h

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charge mineral surfaces, Aust. J. Sol. Sci., +/ :+,+ῌ+-0.

 [ 2 3/ ¥ ,**-20

+33+ : 

 pp. -0ῌ-1  Goldberg (+33,) : Use of surface complexation models
in soil chemical systems, Adv, Agron, .1 : ,--ῌoI +33+ : pqrst,^/uvXWwx

yz{|} SALS pp. 33ῌ++* ~D  mI +33/ :  eft pp. +0/ῌ+03

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/01 2 , 3 ()*,45/6789:;
<=>?@A BCD E /+ : 3/ῌ+*+.
Kamewada (+33/) : Increase in Cation Adsorption
Induced by Surface Complexation of Surfate on
Andisols and Prediction by “Four-Plane Model”,
Soil Sci. Plant Nutr., ., (.) : 12/ῌ133.

FG&HI

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J. Jpn. Soc. Soil Phys.
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No. 3/, p. ,+ -, ,**-



    *Soil Proﬁle Distribution and Terrain Attribute on a Hilly Site
Junichi KASHIWAGI** Graduate School of Agriculture, Hokkaido University
Abstract
The purpose of this study was to appreciate the spatial variability of upland soil proﬁle oncomplex hillslope and to consider the adequacy of geomorphological information to explain thesoil proﬁle distribution. On a +.,-ha upland ﬁeld of central Hokkaido, Soil proﬁle was investigated at +/. locations on a +.-m grid.

Apparent di#erences were recognized according to

the location on a slope position. In the landsurface model units of Interﬂuve and Convex Creep
Slope, horizon sequence was Ap/C-type, the color of Ap-horizon soil in this area was relatively
bright and coarse texture.

In the units of Colluvial Footslope and Alluvial Toeslope, horizon

sequence was Ap/Ab/B/C-type, the Ap-horizon soil color was relatively dark and ﬁne texture
inﬂuenced by sedimentation. Terrain attributes, slope gradient, slope curvature, speciﬁc catchment area etc, calculated from the 1m-digital elevation model were highly correlated with
A-horizon thickness except for slope gradient.

Thick A-horizon was observed at the location

which topographic conditions were convex slope, low altitude and high speciﬁc catchment area.
The multiple regression model of A-horizon thickness by terrain attributes didn’t have su$cientresult for quantitative tool. However landsurface model units identiﬁed the A-horizon thickness
distribution. Geomorphological analisys is useful to guide soil management system with consideration of spatial variability.
Key words : soil proﬁle, spatial variability, terrain attributes, landsurface model units,
geomorphological analisys+     

` 7a 7b cd^_ 9Kirkby, +312: MI
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et al. +321

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Analysis and Slope Mapping, Zeitchrift fur
Geomorphologie N.F. Bd., -0 : ,1.ῌ,3/.

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Kirkby, M. J. (+312) : Hillslope Hydrology, JOHNWILEY & SONS.
Kreznor, W.R., Olson, K.R., Banwart, W.L. and John-

A OPNQ RQA

son, D.L. (+323) : Soil, Landscape, and Erosion Re-

 !ISTAU'VN WXY  Z

lationships in a Northwest Illinois Watershed,[ =?D3%2# $'(1<

Soil Sci. Soc. Am. J., /- : +10-ῌ+11+.

GH\]^\N_`'( IJKL+

Miller, M.P., Singer, M. J. and Nielsen, D.R. (+322) :abcGde1  PLANC fg RQM

Spatial Variability of Wheat Yield and Soil@NabchijkA \hij'(lProperties on Complex Hills, Soil Sci. Soc. Am. J.,

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 2/ῌ A -* cm pq<  &r] Cfs Ats

2/ῌ A -* cm ps  XtN1A /, : +,+--ῌ+,+.+.
Moore, I.D., Grayson, R.B. and Ladson, A.R. (+33+) :Digital Terrain Modelling : A Review of Hydrological, Geomorphological, and Biological Appli-

IJuvw IQ Cx"yz{| }~cations, Hydrological Processes, / : -ῌ-*.

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Moore, I.D., Gesslere, P.E., Nielsen, G.A. and Peterson,

tN783% $IJ +

G.A. (+33-) : Soil Attribution Prediction Using" =N\hij.   'Terrain Analysis, Soil Sci. Soc. Am. J., /1 : ..-ῌ

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E., (+32/) : Erosion and Productivity Interrelations on a Soil Landscape, TRANSACTIONS of῎

the ASAE, ,2 : +22/ῌ+222.

"3i{d='x'( Panuska, J.C., Moore, I.D. and Kramer, L.A. (+33+) : x'F ¡¢£¤¥¦

Terrain Analysis : Integration into the Agricul-§¨'s©xN

tural Nonpoint Source (AGNPS) Pollution Model,
J. of Soil and Water Conservation, 0+ : /3ῌ0..

ῌ ῑ ῐ ῍Park, S. J., McSweeney, K. and Lowery, B. (,**+) :Carson, M.A. and Kirkby, M. J. (+31,) : Hillslope Form

Identiﬁcation of the Spatial Distribution of Soils

and Process, Cambridge University Press.

Using a Process-based Terrain Characterization,

Conacher, A. J. and Dalrymple, J.B. (+311) : The Nine
Unit

Landsurface

Model : An

Approach

Geoderma, +*- : ,.3ῌ,1,.

toPennock, D. J., Zebarth, B. J. and DeJong, E. (+321) :Pedogeomorphic Research, Geoderma, +2 : +ῌ+/..

Landform Classiﬁcation and Soil Distribution in

Curtis, L.F., Doornkamp, J.C. and Gregory, K. J.
(+30/) : The Description of Relef in Field Studies
of Soils, J. of Soil Science, +0 : +0ῌ-*.
Dalrymple, J.B., Blong, R. J. and Conacher, A. J.

HummockyTerrain,Saskatchewan, Canada

Geoderma, .* : ,31ῌ-+/.
Snedecor, G.W. and Cochran, W.G. ª «¬w
9+31,; : ­®]  +2/ῌ+21 ¯°±²³(+302) : An Hypothetical Nine Unit Landsurface

Speight, J.G. (+32*) : The Role of Topography in

Model, Zeitchrift fur Geomorphologie N.F. Bd.,

Controlling Throughﬂow Generation : A Discus-+, : 0*ῌ10.

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Evans, I.S. (+32*) : An Integrated System of Terrain ApῌAbῌB )

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sion, Earth Surface Processes, / : +21ῌ+3+.

Daniels, R.B., Gilliam, J.W., Cassel, D.K. and Nelson, L.

Thompson, J.A., Bell, J.C. and Butler, C.A. (,**+) :A. (+32/) : Soil Erosion Class Landscape Position

Digital Elevation Model Resolution : E#ects onin the North Carolina Piedmont, Soil Sci. Soc.

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Sat Nov 29 15:18:40 2003·¸¹º»¼ Page 11  k 3/ l ,**-

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Soil-Landscape Modeling, Geoderma, +** : 01ῌ23.
Timlin, D. J., Pachepsky, Ya., Snyder, V.A. andBryant, R.B. (+332) : Spatial and Temporal Variability of Corn Grain Yield on a Hillslope, Soil Sci.

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Soc. Am. J., 0, : 10.ῌ11-.
Waters, R.S. (+3/2) : Morphological Mapping, Geogra-+

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MN O +30* : PQ+R.ST234 phy, .- : ++ῌ+1.
Zevenbergen, L.W. and Thorne, C.R. (+321) : Quantitative Analysis of Land Surface Topography,
Earth Surface Processes and Landforms, +, : .1ῌ

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J. Jpn. Soc. Soil Phys.
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No. 3/, p. --.* ,**- 

*ῌ **ῌ **ῌ

**Prediction of Ion Concentration in The E%uent during Permeation of Acid
Solutions Including Multiple Anionic Species into a Volcanic Ash Soil
Kouji KAMEYAMA*, Susumu MATSUKAWA**, Tomoyasu ISHIDA** and Hidemasa KATO*** Graduate School of Agriculture, Utsunomiya University, Utsunomiya -,+῎2/*/, Japan** Faculty of Agriculture, Utsunomiya University, Utsunomiya -,+῎2/*/, Japan
Abstract
The prediction method of ion concentration in the e%uent during permeation of acid solutions
involving multiple anionic species into volcanic ash soil was examined in this study.

The

method for prediction was composed of chemical reactions between acid solution and soil, andMixing cell model, which approximately describe solute transport in soil. The results weresummarized in the following.
+)

The model could simulate well pH and monovalent anions (NO-Cl) in the e%uentduring permeation of acid solutions involving NO-, Cl and SO., into soil column. This showsthat it is possible to handle sum of NO- and Cl as a monovalent anion.
,)

The simulation results agreed well with the measured values of pH and concentration ofanions and BC, (sum total of Ca,, Mg,, K and Na) in the e%uent.

Therefore, it seemed thatsimulation model used in this study is useful for predicting the main e#ects when acid rainincluding multiple anionic species deposited on the Kanto loam subsoil.
Key words : acid deposition, acid bu#ering capacity, chemical equilibrium equation, Mixing cell
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y+#u" z{ | }?~sn#B?ªmn`A# o« Kamewada +330tB* ¬­®i¯i¯°±¯²³´ µ-,+῎2/*/ ¬­®¶· -/*** ¬­®i¯±¯¸ µ-,+῎2/*/ ¬­®¶· -/*: QK^O QRST ¯¹º Mixing Cell 8»a ¼ NO¡¢Bsj  3/ ¼ >,**-A

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     

H!  

"#$  % &'"#$ ()*+)*+,

gth ijy pH ..*  HNO- H, SO. J
>NO-B : SO.,B >q A*./* : *./*,
SO.

,B

B

: Cl

>q

*.1/ : *.,/,

NO-B :

A*..* : *..* : *.,*A 3sD ,/j,2 mL hB+ >dmlr/ +.**j,-. / 0123 (4

+.*3+*B- cm sB+ qA /|4, E *+J"#546789':;<= 9 8

  HIeos t\ >H>+ +332 a +332 b ; ῌ? +332 ; Fumoto

Ieum +331ῌ,**+A  v 

and Sverdrup, ,*** ; + ,**+ ; @1+ ,**,A / w'x >NO-B : SO.,B : ClB >q+67/
)

D

)

:9 SO.,B C8"#:99E9,A*.-. : *.., :*.,.A 3)p4,.Jvrrm >_t + >ZD
y +2 mLA /2 kz4, E { ,-¡ ¢£|FEG;+ H >@1+ ,**-A //J:9 , ¤:<, E}¥NO-B SO.,B  8IE J3012

*.. cm  ¦p +0*j,/* mm wv§dm3[

KL4 >MNO A J!"#3& D|4J8uvn 3#P Q(J/$R %&E%S'T(3)94,*+$ F~4,;*+

4;4 *+   pH ,% Ca,!,

3y +* L (e*_t>@

8y 0** >( (E,  _t +* >

Mg,!, K!, Na! -.#  /UV#

pH _t -* >!"3p4, pH w%S0-W/E' 12 3X4(5654v¨ / / >Al, Ca, Mg, K, NaA ©

7(48Y$ 9&8Z , : *x m ª  «   © © " ¬ >  m n+ "#  //UVE[>NO-B, ClB, SO.,BA rlª~­v§mD

%S0-(12 3X43\$ (Dz ® p4, { y uvn  1];0E"#<^8_=E ()*+

3p4\  1 *.1-1j*.11, cm- cmB- />@1+ ,**,A,

A



Z,

 >67/ ?@ A3 Q .J!"¬¯3<F°±² >J

J8012*+4.J!"# NO-B, ClB, SO.,B ±!"A 3³o D

:9`B3<, C  H >@1+

´,,**-A /)9%S'T((3X43aD0E$ (FG /|_3aῌ gth

Mixing Cell bcd >Appelo and Willemsen, +321A 3

ij34y uvnW3 /* mL µt2)9, , zy µt3µ2-43
 \CJ3kz4, z4 ¶·v§d,    

m/\CJ3¸4 rlª~­v

 @1+ >,**-A (FG HIeJfKgL$

hMi

SNOPQRS .*j0* cm T§m/ NO-B, ClB, SO.,B ±!"3p4,;-    +k45UlmnoV3)9,Wp - cm X+- cm qrsdtuvnYZ-+ wmx3[9y z\ , mm ]3^{4|_

.J!"¬¯)9%S'T( 'Tp

3}`5" *./+0j*./.- g cmB- / +* cm aῌ4, z@ ²E[E + 4 @1+ >,**-A (FGP

4 uvn3MN~\ bc13d :u3)9,  Ca,!, Mg,!, K!, Na! ¬ ,vnYZe* fgth ij3<,^/3¹p4 BC,! (4 (zDºE bc13d :e* MN~\, NO-B ClB P F G  ¬ ¯ 3 »  % $B-

B

bc1( gt186k49 $R 

NO  Cl ¬3 + ^uvn;+MN~\Klm3n o*

º,

/Z

, lm8$R4

(4

 

(zD

F( Ca,!,

E %S'T(3¬¯$ °!"b

Mg,!, K!, Na! -. p\E["#3e* (d!" >mol LB+A /¬¯4,  BC,! :9µ : ¶'8·¸¹¢©.º»detmn¼-. /ῌῌ+Table +

-.



35

`

Chemical equilibrium equations, equilibrium constants and conditions used in ion concentration
prediction of the e%uents+ ,W"
Al-!+4-.+*0 H!,4-/0
o/ : HNO-!

Al-!+4.+.+*0 H!,4-1+
o/ : .!
Al-!+4,/3+*- H!+420o/ : H, SO.!
-Al H, OAlOH,H
logK(/4*, Wolt, +33.!
 Al-,H, OAl OH!, ,H
logK(34-* Wolt, +33.!
,  ,HExBCBC,,ExH
logKBC(H )'!
 -HExAlAl--ExH
logKAl(H )'!
  BC,  Ca,, Mg,, K, Na  Ex v  P ExBCExAlExH+- ¡¢£ CO,H, OHHCO-(
logK(1.2, Wolt, +33.!
. 8
9:"
¤
 9: SO.,(! cmolcῌkg(+!/,3¥SO.,(¦*.,,/¥H¦*.--/¥NO-(Cl(¦(*.++/o/!
 9: NO-(Cl(! cmolcῌkg(+!.0.1¥NO-(Cl(¦*.-/,¥H¦*.+./¥SO.,(¦(*.*+o/!
 Al-SO.,(AlSO.
logK-4,* Wolt, +33.!
/ + \]^_`c _`c FW cmolcῌkg(+!KW¥H¦*..*

KW )'!
0 §¨jE©ª«ῒῌ ῏῍ ῏ῑῒῌ ῐ῍ ῐ
ΐ ῎ ῎
ΐ ῎ ῎

1  }
 BC, mol! : ¬­ .E BC,!9: BC,!!
 SO,(

mol! : ¬­ .E SO,(
SO,(.
. AlSO. !9:
. !!
(
(
(
(
 NO- Cl

mol! : ¬­ .E NO- Cl !9: NO-(Cl(!!
®¯ª«!

°±²

­

³
mol!(¬
¬
³
mol!

 Ca,, Mg,, K, Na  ,   +     mol!

´*4**+*+,mnop"PqC5"BrO5 s7
KLMN67O[\]^_`F+GHI    ,**-! " #  ³

$%&'*+,mnopt345u3v"BrO5
[w [\]^_`E H

logKBC(H logKAl(H )'" *+,-. pH]^z{ |}451PQ5/01"234523167

+32/! ~sP  

8

9:  +    

Freundlich =9:>?

Mesquita and Vieira e

Silva, ,**,! 3 + 8
, 8

4;<

NO-(Cl(! "SO. ! @A9:B,(CD   EF+GHI  ,**-!

Hxy' deBloom and Grigal,+331! B"_`xy'KLMN67O1 _`' KW )'" *+,mnop
D5-. pH /01 BC,



-

/0

1 234523167H



;5 BC,  !
CD P _`c  + 

;J KLMN67OPQJ   

1

R0&'ST*.3.+ *.23. "UV KLM/0W

BC

X"3YPQZ

P [\]^_` ;5.t BC, abB[\]^_` ;5 BC, abc _`c!
 de"."fghij kl45KLM",O_` } !  r5s"
 + 

^_l ¼ 3/ ( ,**-

36

-,

Mixing Cell          

Mixing Cell

Appelo and Willemsen, +321 

 Mixing Cell 



C "fC !*./+#fC !C 

ῌ

,a
f"+#
$x

῍

$x
v

῎

j
i!+

$t"

j#+
i

j#+
i#+

j#+
i!+

ῌ%῎ &'() *  C : + ,-. mol#+

L  i : + /( j : 01/( f : 234567 *8
f8+ a : 9 cm $x : +  cm $t : :;0<9 s v : <=>? cm s#+ @AB 
CD 9 a + $x EBFGH ,**, I
J KL*.// , cm  M NOPQRST
<=>? v I+

9$x  ῎ UVW

ῌ+pH ..*  HNO-, H, SO., 45,QRA
5, pH qr r

Fig. +

Measured and predicted pH in the e%uentduring permeation of pH ..* HNO-, H, SO.
and mixed solution.

ῌ,pH ..*  HNO-, H, SO., 45,QRA
5 BC,!  qr r

Fig. ,

Measured and predicted accumulative
release of BC, during permeation of pH ..*HNO-, H,SO. and mixed solution.

IXY $t  +,.**%+,/** s IZ[H -- \]

XYZ[H#-^_,& SO.,# +#`abcd NO !Cl  ef-.)*,g+*#0 -.2/g+*#. mol L#+ hi M efjklm

n op^_jklmnqr FGH ,**- 
s h
-.

*.22 cmolc kg#+ eftuIAB v



Mw eftuIxyz{H SO.,# + `abcd NO-#!Cl# |}~+ efz-.
)AB $t 0<K+ ,-. ῌ 45A 45z-.xyz &ltu SO.,# + `abcd NO-#!Cl# I BC,! tuIYAXYZ[ W0<MYA..+ 
pH ..*  HNO- H, SO. 45, NO-# : SO.,#"*./* : *./* QRA5, pH qrIr + BC,!  qrIr r ) I«¬JrA , A CD & KW IA

K,QRA5DB , pH  ­*.-

x23r logKBC#H logKAl#H |®¯°qrIr±A M BC,! IAbcdjk23r) * 



AB 

°±A bcdjkIxX ²³

CD H ,**+ ¡¢^ £G¤^_ 

qrIr¦­*.+ cmolc kg#+ |®¯´ µ¶q B I·vH 

EB¥¦i , `bcd Ca,! Mg,! I H!

| ¸  ¹ º { H W W     KW, logKBC#H,

Al-! I H! bcdjk§r )logKAl#H r3¶I·vH [ W Hr*  +*.*1%+*./. +,.+-%+-.00 hY ¨©{HªB|®»irs : tuv lwxk yz{]^|.,  pH 





 -

NO- : SO.,  *./* : *./* *.1/ : *.,/ 

-

6

$%&%'

SO.

( )* BC

Ca,, Mg,, K, Na#+,-. /012

3- , 4 -537(

89*.- :;<=8.>?  pH @;ABCDCl SO.,  ! " - . #
,

6 '

 pH . 7 pH BC  +  NO,}

!EFG>?
,( H

. 7.FI)>? ' BC, + 

8

(J# NO- : SO., : Cl  *..* : *..* : *.,*  pH BC, + 

-



/ #'

(

NO Cl  SO.,  ! " pH . 9*.- :;<=8( H  BC, +  NO-Cl

.>?
SO.

,

6FI)>? ':KLMNO 
Cl PQRAB(

S# NO- +  -HS-T2UVWXY8ZBW'[% (.-  pH  


NO- : SO., : Cl  *..* : *..* : *.,*  7
ῌ-Fig. -

 pH, BC,, +  NO-
Cl SO.,   NO- : SO.,q*./* : *./*
Measured and predicted pH and concentration of BC,, monovalent anions (NO-
Cl) and SO., in the e%uent (NO- : SO.,
*./* : *./*).

\]^ +  NO- CDCl  SO.

#', SO., _`abcde " 0( )* SO., _`abc. ]^#ab[%SO.

,

c ' -*2

\#/NO]^fg -, hij5k SO., .lH%-,),(+* +/ m\ + . 3n#*,-op + 8ZB *.*0 mmol L+ ῌ.

 pH, BC,, +  NO-
Cl SO.,   NO- : SO.,q*.1/ : *.,/ῌ/ pH, BC,, +  NO-
Cl SO.,   NO- : SO., :Clq*..* : *..* : *.,*

Fig. .

Measured and predicted pH and concentration of BC,, monovalent anions (NO-
Cl) and SO., in the e%uent (NO- : SO.,
*.1/ : *.,/).

Fig. /

Measured and predicted pH and concentration of BC,, monovalent anions (NO-
Cl) and SO., in the e%uent (NO- : SO., :Cl*..* : *..* : *.,*).

+jkJ l 3/ m e,**-f

38

῏ῌ0

WcdXY + +  eNO-&\Cl&f
SO.,& : Cl&i*..* : *..* : *.,*f

WcdXY

Fig. 1+ pH BC,\ BCgh]^J_`*BC+' eNO-& : SO.,& : Cl&i*..* : *..* : *.,*fProﬁles of predicted pH, concentration of BC,ῌ and exchangeable bases at several elapsed times(NO-῍ : SO.,῍ : Cl῍῎*..* : *..* : *.,*).



+*
$%+/ +  !

"#

SO.,& ' SO.,& ()*'+BC.DE6FG

 

+ 

 SO.,& ++HIJ+KLMNO
6P+QR/ "#012" SO.,& +345

S NO-& : SO.,& : Cl&  *..* : *..* : *.,* +TU=

6"7 89:+; <45=>+=?

>VWXYZ[2" +=>+ pH BC,\  ],-./
gh SO.,& ()*BC+' eNO-& :Proﬁles of predicted concentration of monovalent anions (NO-῍ῌCl῍) and SO.,῍ and accumulativeSO.,῍ adsorption at several elapsed times (NO-῍ : SO.,῍ : Cl῍῎*..* : *..* : *.,*).

Fig. 0῏ῌ1SO.,& BC

SO.,& @ !

"# A"+ +^J_`*BC+'Va 1 b2"#_` : + ,-./0#12#456 E F):; 

pH BC,    
 

BC

,

 



 pH   !"# $%&'()*ῌi+

+ ,-./0#123456 78
/0#12456 BCDE F):; #G$)* H IJKL89%*-./45 ^%#456 E6F):;

pH P%K + Q,-./ RNO-N 

ClNM  SKT89

)A NO-N  ClN#US@%; # + Q,-./FVA

WXY &Z'P%&[89)*,M 

pH \,-./ BC, RCa,, Mg,, K,; M ]FKT^_

#[F `a')>+ ,-./0#
123456  R]bcD

 3% 3- : -ῌ ^M  F):; <= d'P%&e89)*ῑ ῔ ΐ ῒpH 

 3%

 2* : -ῌ+*.
i+ ῌ01ῌ7-89ῌ:;  R+332 bM :#X<F6F)
pH

NO-N, SO.,N, ClN #12O;# F):;

BCD

ῌ,-./ῌ01 R,**-M : ,i+ ῌ01 R+332 aM : qbrs/ E 29):; <=>#?@%)A + ,-.

Na 3% 23 : ,/ῌ--.
5++.

/ῌ ῍ ῐ ῏ ῎+M39

 3% 11 : ++ῌ+2.

Mesquita, M.E. and Vieira e Silva, J.M. (,**,) : Preliminary study of pH e#ect in the application ofLangmuir and Freundlich isotherms to Cu-Zn
competitive adsorption. Geoderma, +*0 : ,+3ῌ,-..

0ῌ-= R+332M : >?%SS -{tz%tz S E @%AQ ()* 03 : .11ῌ.21.
0ῌ¡iB¢9ῌC

DE R,**+M : >?% SS -{tz%
F£G¤IJE @%¥¦§w]@%¨H ( )* 1, : -3.ῌ.*,.

Appelo, C.A. J. and Willemsen, A. (+321) : Geochem-

IF Jῌ©ªKῌL«ῌ5¬­kῌM-N9ῌ

ical calculations and observation on salt water

OPQ! R+331M :S®Rx¯%

intrusions, I. A combined geochemical/mixing

SSTS _° ±²³´ +* : ,21ῌ

cell model. Journal of Hydrology, 3. : -+-ῌ--*.

,33.

Bloom, P.R. and Grigal, D.F. (+32/) : Modelling soil

U;µV¶±²·/¸cW¹±²X R+331M : 85 2 Y

response to acidic deposition in nonsulfate ad-º3G¤ U;µV¶±²·/¸cY

sorbing soils. Journal of Environmental Quality,Z , : +.+ῌ+./.
U;µV¶±²·/¸cW¹±²X R+332M : 85 3 Y+. : .23ῌ.3/.
Fumoto, T. and Sverdrup, H. (,***) : Modeling of sulfate adsorption on andisols for implementationin the SAFE model. Journal of Environmental
Quality, ,3 : +,2.ῌ+,3*.

fgh!ῌij"kῌfgl# R+333M : m$noº3G¤ U;µV¶±²·/¸cYZ - : +,1ῌ+-*.
U;µV¶±²·/¸cW¹±²X R+333M : 85 +* Yº3G¤ U;µV¶±²·/¸cYZ . : +//ῌ+/1.

p%%qbrs/-tuC-v w&S

U;µV¶±²·/¸cW¹±²X R,***M : 85 ++ Yxyqz{|}D~-'  ( )*º3G¤ U;µV¶±²·/¸cY 1* : ,/ῌ-*.
Kamewada, K. (+330) : Application of ‘Four-planeZ / : +/1ῌ+0*.
U;µV¶±²·/¸cW¹±²X R,**+M : 85 +, Y

model’ to the adsorption of K, NO-N and SO.,Nº3G¤ U;µV¶±²·/¸cY

from a mixed solution of KNO- and K, SO. on

Z 0 : +-3ῌ+.+.

Andisols. Soil Science and Plant Nutrition, ., :

5

ῌi+

K-»_9ῌ[O¼! R+33+M : -./\45#@% - 02*+ῌ2*2.

ῌ,-./ῌ01 R,**,M : 4

56 E 2 %

%689) ]K§w

]K^ ( )* 0, : .2*ῌ.20.
Wolt, J.D. (+33.) : Soil solution chemistry. pp. +/2ῌ+0+, %$

40

John Wiley & Sons Inc., New York.

ῌ +322 :  /3 : .+-ῌ.+/.

& 3/ ' ,**-!"# : ,**- " - # 0 $"# : ,**- " 0 # ,- 
J. Jpn. Soc. Soil Phys.
/0,&¡
No. 3/, p. .+ /. ,**-

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Field Measurement of the Water Retention Curves and Simple Estimation of
Their Parameters for Soils in the Central Region of Horqin Sandy Land
Xiaoyan LIU*, Naomasa NISHIMURA**, Takao AMAYA** and Tingxi LIU**** United Graduate School of Agricultural Science, Gifu University** Faculty of Agriculture, Gifu University*** Faculty of Hydraulic and Civil Engineering, Inner Mongolia Agricultural University
Abstract
In this study, soil surveys and water retention measurements were conducted on a wide rangeof soil textures sampled from thirty one locations in the central hinterland of Horqin sandy land.
Because the measured water retention curves belong to intermediate scanning curves between
the main desorption and sorption processes, some precautions on measurement and application of
the water retention curves were suggested.
All soils in survey sites were classiﬁed into nine soil types.

The average water retention curveof each soil type could be su$ciently approximated by using van Genuchten formula (vG-I).
Their saturated and residual volumetric water contents (qs, qr) increased with clay contents ofsoil groups.

It was conﬁrmed that the shape of their water retention curves are reﬂected

precisely by the parameters e and n that describe the degree of the ﬁrst and second inﬂection
curvatures of vG-I, respectively.
Pedotransfer functions in the survey area were estimated using the water retention curves forthe nine soil types by the function parameter regression method. The parameters of the ﬁtted
water retention curves using vG-+ and vG-II (assumed m+ in vG-I)were known to have quite
good regression relations with the indexes of soil physical and chemical properties.

Particularly,

the accuracy of estimation was found to increase when the regression formulas of e and n were
substituted for m and n in vG-I.

Therefore, PTF is an e$cient method for estimating the water

retention curves for di#erent sites in the survey area.
Key words : Water retention curve, Horqin sandy land, Parameter regression method, Pedotransfer function, Physical and chemical properties of soil+    (,1+56,73#8!9:#;<$ =,(>?
@)/0AB,CDEF$ /0GHGIJ

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/

42

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Salchow et al., +330 ; Scheinost et al., +331 ; Minasny

 !

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et al., +333 ; Van Alphen et al., ,**+ ; Mcbratney etal., ,**,=

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 GIS

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G»Y

Location of experimental sites.

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Layout for the ﬁeld measurement ofwater retention curve.

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44

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Fig. -

Distributions of soil water and total potential during the redistribution process after
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Fig. .

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Redistribution process of the soil water
after irrigating /* mm at the experimental site of A,..

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Fig. /

Water retention curves obtained byﬁeld measurements and the regression
curves.

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Batjes, N.H. (+330) : Development of a world data set/  +W IG& JKE5; <of soil water retention properties using pedo-= cdefgd+h/,i+ j]"k U;-lm.noE )J

]! pqr<

% s/

*/0!

:]
""./J]+ PTF transfer rules. Geoderma, 1+ : -+῏/,.
Cosby, B. J., Hornberger, G.M., Clapp, R.B. and Ginn,
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1<uv1+234]wU;oxy3gz{|g}~/0+LM1S r51H 

physical properties of soil. Water Resources Research, ,* : 02,῏03*.
Espino, A., Mallants, D., Vanclooster, M. and Feyen, J.

XY : `abc+(d+e-./0

9^fghEFijklmnoNpNqrstju

53(+33/) : Cautionary notes on the use of pedo-

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bution from texture, organic matter content andtion, organic matter percent, and bulk density.

bulk density,. Z. Kluturtech Flurbereinig, +-* : /-ῌ

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Haverkamp, R. and Parlange, J.Y. (+320) : Predicting

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Pedotransfer functions for variable alluvial soils

tribution : I. Sandy soils without organic matter.
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Hillel, D. (+332) : Environmental soil physics. pp. +//ῌ
+01, Academic Press, New York.
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Soil Science Society of America Journal, /3 : ++-.ῌ

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

+322 :  ῌ

Shirazi, M.A. and Boersma, L. (+32.) : A unifying
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>?@ 0. 1 : -/ῌ./.


ing a new pedotransfer function. Geoderma, 12 :+,3ῌ+.-.

quantitative analysis of soil texture. Soil Science

++.+.

ῌ

(+331) : Regionalization of soil water retention
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Scheinost, A. C., Sinowski, W. and Auerswald, K.

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Mcbratney, A.B., Minasny, B., Cattle, S.R. andTyler, S.W. and Wheatcraft, S.W. (+323) : Application

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tions to soil inference systems. Geoderma, +*3 :estimation. Soil Science Society of America Jour-.+ῌ1-.

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Minasny, B., Mcbratney, A.B. and Bristow, K.L. (+333) :Van Alphen, B. J., Booltink, H.W.G. and Bouma, J.

Comparison of di#erent approaches to the devel-(,**+) : Combining pedotransfer functions withopment of pedotransfer functions for water-

physical measurements to improve the estima-

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Y.A.,

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R.A. and Shcheglov, A.I. (+320) : Modelling ofmoisture regime forordinary Chernozems.

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Rajkai, K. (+32,) : Statistical analysis of water

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easily measured soil properties. Soil Science,

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>?@=A B 3/ C ,**-

54hydraulic properties. Soil Science Society of&'#()*+, -./012324 56 7 +0

America Journal, /0 : +-1+ῌ+-12.

, : 3+ῌ32.

ῌ

ῌ



+33/ :



ῌ



!"#$%

89:;< : ,**- : . ; 1 <8=:;< : ,**- : 2 ; - <ῐ
J. Jpn. Soc. Soil Phys.
῏῍ῌῐῑ῎
No. 3/, p. //ῌ0, ῍,**-῎

The Change of Morphology in Red Acid Soil after FourYears Treatment of Co#ee Plantation with Di#erent
Weeds Management in a Hilly Area of Lampung,South Sumatra, Indonesia
AFANDI*, Didin WIHARSO*, Masateru SENGE**, Adomako John TAWIAH***,
Yoko OKI**** and Tadashi ADACHI***** Faculty of Agriculture, University of Lampung, J+. Sumantri Brojonegoro +,Bandar Lumpung -/+./, Indonesia** Faculty of Agriculture, Gifu University, +ῌ+ Yanagido Gifu /*+ῌ++32, Japan*** Soil Research Institute of Ghana Kwadaso, Kumasi, Ghana**** Faculty of Environmental Science and Technology, Okayama University, -ῌ+ῌ+Tsushimanaka Okayama 1**ῌ2/-*, Japan
Abstract
Research was conducted on the red soils formed from young intermediary to maﬁc volcanic
materials that occupy the hilly areas of South Sumatra, Indonesia within the humid tropicalclimate. This research was aimed at investigating the inﬂuences of di#erent soil cover crops on
soil morphology and soil properties after four years treatment as well as examining the probablechanges in the soil taxonomy. Three soil proﬁles were made in the middle of erosion plots after. years treatment with di#erent soil cover crops under co#ee trees. The treatment plots were ;T-+, keeping the ground bare by hand weeding at two weeks interval (co#ee without cover crop) ;T-,, Co#ee with Paspalum conjugatum as cover crop and T--, co#ee with natural weeds as covercrops. The soil proﬁles were described and sampled according to Soil Survey Manual (+33-) andSoil Taxonomy Classiﬁcation System (+332). It was observed that after . years, soil surface layer
had become thicker and darker than before. Almost all the soil chemical properties in soil surface
layer increased, particularly soil pH, organic carbon content, total nitrogen, available P, exchangeable bases, and base saturation. On the other hand, exchangeable Al and Al saturation of soil
surface layer decreased. Although several soil characteristics changed during the study period, it
was evident that . years treatment was too short to change soil taxonomy of the three pedons in
sub-group category.

In the sub-group category, all pedons were still classiﬁed as Vertic

Dystrudepts. Covering soil surface by natural weeds was able to increase exchangeable bases andbase saturation in the sub- surface layer, therefore over a long period of time there will be apossibility of the changing the soil taxonomy from Vertic Dystrudepts to Eutrudepts in the greatsoil group category.
Key words : Red Soil, co#ee, cover crop, weeds, Vertic Dystrudepts, Sumatra+.

Introduction

The term of Red Soil is used to describe soils
that have hue of +* YR until / YR, with value

and chroma ranging between , and 2 (Wiharso,+330). This type of soil is widely distributed in
the tropical regions of the world, includingIndonesia. They are formed from many kinds

῏56  3/of rocks, both felsic and maﬁc, spread over low
and high altitudes of undulating mountainous
regions with perhumid to semiarid climates(Buurman, +32*). Red soil is associated withacid soils, marginal soils, and infertile soils.
According to Soil Classiﬁcation System in thepast, these soils were called Latosol or Lateritic
soils (Uehara and Gillman, +32+). Since +30+,
red soils in Indonesia had been classiﬁed into
four, namely ; Red-Yellow Mediterranean,
Latosol, Red-Yellow Podzolic, and Lateritic(Buurman, +32*).
Soils that are formed from recent volcanic
materials, ﬂuvial, or in the young landscape are
generally rich in nutrients and capable ofsupporting plant growth and animal community, if the availability of water, sunshine, andtemperature are not limiting factors. The soils
formed by these volcanic materials usually
have enough nutrients that can support various plants. However, under humid tropicalclimate, the soils will be subjected to soil erosion and the soil degradation become fast. Materials left on the landscape are subsurface
layer, which are abundant with insoluble materials, hence showed the inability of soils to
support sustainable agriculture.
Within the research area, drastic changes inland use from primary forests to cultivatedlands without proper soil conservation practices had led to severe land deterioration causing signiﬁcant soil fertility decline between+31* and +33* (Lumbanraja et al., +332).
Improving soil ability to support various
plants and sustain agriculture, soils should bemanaged and maintained through conservation practices such as covering soil by covercrops or weeds. Afandi et al. (,**,) reported
that covering soil by grass (Paspalum conjugatum) and natural weeds could decrease
runo# and erosion signiﬁcantly.
This research was aimed to characterize thesoil morphology and soil properties of threepedons of red soil in a hilly area under co#ee
plantation in South Sumatra, Indonesia, after
four years of cover cropping management,**-

using grass (Paspalum conjugatum) and naturalweeds. The probable changes in the soil taxonomy with reference to the Soil Taxonomy Classiﬁcation System (Soil Survey Sta#, +332) werealso examined.
,.

Materials and Method

The research was conducted in co#ee plantation which had been under three di#erent
cover cropping management systems since+33/ to +333 in a hilly area of Sumber Jaya
District, Lampung Province, South Sumatra at
an altitude of about 2** meters above sea leveland +/ gradient.
The detailed treatments were discussed byAfandi et al. (,**,) and could be summarized asfollows :(+) Treatment + (T-+) : Clean-weeded co#ee.
Ground surface was always keeping bare byhand weeding at two weeks interval. This
management is a general practice in this co#ee
plantation area so that this treatment isregarded as a control.
(,) Treatment , (T-,) : Co#ee with Paspalum
conjugatum as cover crop. Young Paspalum
conjugatum was transplanted to the experiment plot in November +33/ and February+330.
(-) Treatment - (T--) : Co#ee with naturalweeds as cover crop.
In each plot, seedlings of Arabica co#ee wereplanted with planting distance +./ m by , m on
November +33/. Weed management was done
every two weeks by clearing all the weeds inclean-weeded plot (T-+), and cutting the weeds
around the co#ee tree with diameter + m forthe weedy plots (T-, and T--). Before and after
rainy season, the Paspalum mats (T-,) and natural weeds (T--) were mowed at +/-cm height.
Application of fertilizer and pesticides had
been adopted according to the standard usual
practice.
The natural weeds were dominated by
Clibadium surinamense, Ageratum conyzoides,
Chromolaena odorata, Melastoma malabatricum,
Clidemia hirta, Dicranopteris linearis, Imperata῎῍ : The Change of Morphology in Red Acid Soil after Four Years Treatment of Co#ee Plantation with Di#erent Weeds Management in a Hilly Area of Lampung, South Sumatra, Indonesia 57

cylindrica, Paspalum conjugatum, and Borreria
leaves (Salam et al., ,**+).
The treatments were located side by side.
Each treatment had two plots with an area of+** m, of / m width and ,* m length. One plot
was used for soil erosion measurement (undisturbed during four years), and the other plot
was used for soil sampling. So each erosion
plot was separated by sampling plot. After
four years of treatments, a representative soil
proﬁle was dug in the middle of soil erosion
plot in each treatment plot.
Chemical fertilizers including ,** kg haῌ+ of
urea, ./ kg haῌ+ of P, O/ in the form of Ca(H, PO.),, and +** kg haῌ+ of potassium chloride,
were applied just after transplanting and thentwice a year in April and October.
Soil samples were taken from each horizon
for chemical and physical analyses. Soil pH
was determined in H, O and + N-KCl at soil toliquid ratio of + : ,./, Organic Carbon (Walkley
and Black), total Nitrogen (Kjeldahl), available
P (Bray-I), CEC, exchangeable bases extractedby NH. OAc. at pH 1.*, and exchangeable Aluminum extracted by + N-KCl. The soil proﬁleswere described and sampled according to Soil
Survey Manual (+33-) and Soil Taxonomy Classiﬁcation System (+332) to determine themorphological processes that occurred in the
red soil.
The soil strength in each horizon was measured using hand penetrometer, and repeated +*times, and the results was the average of themeasurements.
-.

Results and Discussions

Morphology and Physico-chemical
Properties of Soil
The morphology and physico-chemical properties of the three pedons are relatively similar in terms of their structure, texture, consistence, color and thickness (Table +). These are,clay texture, blocky to sub-angular blocky
shape structure in the surface horizon, crumb
structure in the sub-surface and friable in all
horizons. However, when soils were observed-. +critically, di#erences in color, internal drainage, and the thickness of surface horizon were
noticed. The soil surface horizon of pedons
treated with Paspalum grass and natural weeds
were found to be thicker than the control. Thisobservation can be attributed to the fact thatcover crops are able to decrease run o# anderosion (Afandi et al., ,**,), therefore useful forsoil conservation measures.
Soil color is closely related to parent material, organic carbon content, the intensity of Fe/
Al oxidation, age of parent material, and soil
moisture condition. The color of soil in surface
horizon of pedons (A horizon) that were covered by either Paspalum grass or natural weeds
was darker than control, due to their organic
materials released to the soil. Soil color in thesubsoil of Paspalum grass and natural weeds
plots had red color brighter than clean-weededco#ee plot (control), with that of grass superior
to natural weeds plot. Reduction and oxidation (Redox) process in soils a#ect the stabilityof iron (Fe) and manganese (Mn) compounds.
Soil color can indicate certain moisture condition due to the mobilization of Fe and Mn
caused by Redox processes. Generally, the subsoil of three pedons showed enough oxidationand good internal drainage conditions. Thesephenomena were proved by the high chroma(ῌ.). But, soil colors in the lowest horizon ofpedon T-+ (at 2+ῌ+*- cm depth) and pedon T-(at +*2ῌ+-, cm depth) that reached ,./ Y showed
less oxidative condition and the internal drainage worse than T-, (at +,*ῌ+-/ cm depth).
Among the three pedons, T-+ was the least
oxidative compared to others, even though thelowest layer had ever experienced redox reaction in the past as shown by the red mottles (+*YR //2).
Although there are di#erent colors (matrix
or mottles) in subsoil among the three pedons,
it is too early to conclude that those di#erenceswere caused during four years of study. Conceptually, a biological process or vegetation
plays an important role in soil formation over along-term period. In a more detailed analysis,

58

Table +,**-Morphology and Soil Physical Properties of Three Pedons under Di#erent Cover CropManagement Systems

Soil
Plot Depth(cm)

Soil Separates
Horiz
on

Matrix Color

Dark Brown +* YR -/-

+*ῌ-,

AB

-,ῌ2+

Bw+

2+ῌ+*- Bw,

T-+

Soil

Text

(kg/kg)Structure

ure
Sand

A

*ῌ+*

T-,

3/

Sab, f, +

Silt

Clay

Soil
StrengthkPa

Consist Mottles /
ence

Crack

Roots

md-few,f-m*4,/- *4,0, *4.2/

C

,./4,

fr

Crack

Yellowish Brown +* YR //0

Sab, f-m, + *4,/. *4+-, *40+.

C

,-*4/

fr

Crack

f-cm

Strong Brown 14/ YR //0

Cr, vf, +*4,11 *4+-+ *4/3,

C

+1+40

fr

Crack

f-few

Light Yellowish Brown,4/ Y 0/.

Cr, vf, +*4,/. *4+,+ *40,/

C

+.14+

fr

+* R
f-very//2, sdk few

b, vf, +*4-30 *4+2+ *4.,-

C

,-*4/

fr

Crack

md-few,
f-m
f-cm

*ῌ+/

A

Dark Greyish
Brown +* YR -/,

+/ῌ.*

AB

Yellowish Dark Brown+* YR ./0ῌ//0ab, f-m, + *4-+2 *4+,* *4/0,

C

,0.42

fr

Crack

.*ῌ2/

Bw+

Strong Brown 14/ YR //0

Cr, vf, +

C

,,*40

fr

Crack

f-few

Crack

f-veryfew*4,3- *4+-0 *4/1+

2/ῌ+,* Bw,

Yellowish Red / YR //0

Cr, vf, +*4,+, *4+,- *400/

C

,*/43

fr

+,*ῌ+-/ Bw-

Yellowish Red / YR //0 &Brownish Yellow +* YR 0/0b, vf, +*4+1/ *4+-. *403+

C

,.*4-

fr

b, f, +

*4--- *4,,+ *4..0

C

+2+4.

fr

Crack

md-cm,
f-m



*ῌ+-

A

Dark Greyish Brown+* YR -/,

+-ῌ.2

AB

Yellowish Brown +* YR //0

Sab, f-m, + *4,3. *4+-+ *4/1/

C

,.*4-

fr

Crack

md-few,
f-cm

T-- .2ῌ 3, Bw+

Yellowish Strong Brown
14/ YR //0ῌ+* YR //0

Cr, vf, +*4-+, *4+.- *4/./

C

,0.42

fr

Crack

f-few

3,ῌ+*2 Bw,

Strong Brown to Yellowish Red
14/ YR //0ῌ/ YR //0

Cr, vf, +*4,-1 *4+,+ *40.,

C

,/*4+

fr

f-veryfew+*2ῌ+-, Bw-

Strong Brown and Olive Yellow
14/ YR //0 & ,4/ Y 0/0b, f, +

*4,,+ *4+-+ *40.2

C

,+*42

fr

f-veryfew

Ex : bblocky, abangular blocky, sabsub angular blocky, Crcrumb, CClay, frfriable, Crack, fﬁne, mdmedium, cmcommon, mmany.

the concept of biosequence needs thorough discussion in order to understand the uniformityof parent material in a land unit. Inﬂuences ofsoil cover crop on morphology and soil properties are more signiﬁcantly shown in soil
surface layer, particularly, color, thickness ofsoil surface layer, soil chemical properties, suchas pH, organic carbon content, total nitrogen,available P, exchangeable bases, exchangeable
Al, base saturation and Al saturation (Table ,).
Generally, cover crops have the capability to
improve chemical properties of soil surface
layers (Wiharso, Afandi and Senge, ,**+). The
content of organic carbon, total nitrogen, available P, exchangeable bases, and pH of soil surface layer in both grass and natural weed plots,
were higher than control plot, while exchange-

able Al and Al saturation decreased.
Accumulation of organic matters and exchangeable bases in soil surface horizon ofco#ee plantation treated with grass (T-,) or
natural weed (T--) show that bases in the formof nutrients had been translocated from subsoil
to various tissues of cover crops through roots,
and these bases and organic matter were later
returned into the soil surface after decomposition. Bases returned to the soil surface in thismanner retarded the loss of exchangeablebases by leaching and retarded the development of soil acidity, hence the pH values werehigher in T-, and T-- compared to T-+.
Paspalum grass and natural weeds in this research had total biomass larger than control(Sriyani et al., +333), hence its ability to de-ΐῒ : The Change of Morphology in Red Acid Soil after Four Years Treatment of Co#ee Plantation with Di#erent Weeds Management in a Hilly Area of Lampung, South Sumatra, Indonesia 59

Table ,

Soil Chemical Properties of Three Pedons under Di#erent Cover Crop Management Systems

Soil

pH

Plot depth Hor
(cm)

T-+

T-,

T--

C-

T-

Org

N

(mg/ (mg/
H, O KClkg)

kg)

Exchangeable Bases

Avail4 P
Bray I

cmol (῍) kg῎+

CEC 1

(mg/kg)

Ca

Mg

K

ῑ
Exch4

Na

Bases

BS 1
(ῌ)

ECEC

Exch4 Al sat
Al

(ῌ)

*ῌ+*

A

.4,3 -41. ,,41

+43

-4*3

+14-

-41* +432 *4,0 *4*/

/433

-.40

2433

-4**

--4.

+*ῌ-,

AB

.4,/ -403

34*

*43

+4*-

+04+

-4.. +432 *4,+ *4*.

/401

-/4,

143,

,4,/

,24.

-,ῌ2+ Bw+ -43, -40/

,43

*4/

ῌ

+24+

,42+ +4-/ *4+, *4*,

.4-*

,-42

142/

-4//

./4,

2+ῌ+*- Bw, -430 -40-

,43

*4.

ῌ

,04.

-430 +4/0 *4+* *4*+

/40-

,+4-

34/,

-42/

.*43

*ῌ+/

A

.4/1 -422 ,04+

,4,

+3432

+04,

14*, 04.0 *4.1 *4+*

+.4*/

2041

+/4/*

+4./

34.

+/ῌ.*

AB

.4++ -402

340

+4*

+423

+040

-41* +4*. *4+- *4*,

.423

,34/

1423

-4**

-24*

.*ῌ2/ Bw+ -410 -4.,

-41

*40

ῌ

+042

,4// +4*, *4+, *4*,

-41+

,,4+

042+

-4+*

./4/

2/ῌ+,* Bw, -43, -40*

.4*

*4.

ῌ

+14-

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

-4--

+34,

14-2

.4*/

/.43

+,*ῌ+-/ Bw- -43* -4/1

,41

*4-

ῌ

,.42

+43+ +4*. *4*3 *4*+

-4*/

+,4-

24*/

/4**

0,4+

*ῌ+-

A

.42* -42- ,34*

,4.

24+.

+342

14/- .4*2 *4,1 *4*1

++43/

0*4.

+,40*

*40/

/4,

+-ῌ.2

AB

.4-2 -41-

34,

*43

,4*+

+.41

.4.1 ,41+ *4+1 *4*.

14-3

/*4-

+*4/3

-4,*

-*4,

.2ῌ3, Bw+ .4*, -41.

,41

*4.

ῌ

+-4-

,402 +4-/ *4+. *4*-

.4,*

-+40

14.*

-4,*

.-4,

3,ῌ+*2 Bw, .4*+ -41/

,4-

*4.

ῌ

+.4+

+400 +4-/ *4*3 *4*+

-4++

,,4+

0410

-40/

/.4*

+*2ῌ+-, Bw- .4** -41.

+4/

*4-

ῌ

-24*

+40/ +4-- *4*3 *4*+

-4*2

24+

14+-

.4*/

/042

῎+

CEC 1ῐCEC by + N NH.OAc at pH 1.*. cmol (῍) kg ; BS 1ῐῑExch. Bases/CEC 1῏+**ῌ ; ECEC (E#ectiveCEC)ῐῑExch. Bases῍Exch. Al, cmol (῍) kg῎+ ; Al Sat. (Al Saturation)ῐExch. Al/ECEC῏+**ῌ.

crease soil erosion signiﬁcantly (Afandi et al.,,**,). This is also supported by the thicker soil
surface layer of both grasses and natural weeds
plots compared to the control.
Soil surface horizon of both grass and natural weed plots contain organic carbon higher
than control, with natural weeds plot having
the highest value. But the highest percentage
of organic carbon from natural weed plot did
not have corresponding values of exchangeable bases and available P. Exchangeable bases
and available P in the surface layer of natural
weed plot was lower than that of grass.
Table , showed that the use of Paspalum
grass and natural weeds can increase exchangeable bases and base saturation, especially in the surface layer (A horizon). The increasing exchangeable bases and base saturation by
Paspalum grass were more concentrated in soil
surface layer, while that of natural weeds increased those properties down to the sub-layer.
Although the natural weeds plot contains exchangeable bases less than grasses in soil surface horizon, its exchangeable calcium washigher than the rest.

This phenomenon showed that in Paspalum
plot as well as in natural weeds plot, Al saturation was decreased and the pH was increased in
the surface horizon. Yearly observation which
was made from +330 to +333 also showed thatthe soil pH and organic matter in Paspalum
plot and natural weeds plot were higher thanin control plot up to .* cm depth (Salam et al.,,**+). Probably the main reason of this phenomenon arised from the abundant of organic
matter in Paspalum as well as natural weeds
plot. The average content of soil organiccarbon from +330 to +333 in Paspalum plot andnatural weeds plot was -,.+ g/kg and ,0./ kg
respectively where in control plot it was ,*., g/
kg (Afandi et al., ,**-).
-. , Soil Classiﬁcation
Morphology of the observed soils was almost
similar to the soil morphology in lowland areasin Lampung, Indonesia, in which the observed
soils are dominated by halloysite (Lumbanraja,
Syam, Sarno and Wada, +333).
The three pedons have deep solum and thinsoil surface layers with weak structure, therefore belong to ochric epipedon. Due to the60

absence of clay ﬁlm in the sub surface horizon
as well as soils having CEC of more than +0
cmol () kg+, it indicates that the three pedons
belong to the cambic horizon as their diagnostic horizon. According to Soil Survey Sta#(+332), those pedons are classiﬁed as Inceptisolin the order category. Those pedons do nothave aquic conditions within /* cm of the mineral soil surface, but they have udic moistureregime, therefore soils are classiﬁed as udepts inthe sub-order category. In the great soil groupcategory, the three pedons are classiﬁed as
Dystrudepts, because they do not have sulfuric
horizon, duripan, fragipan, free carbonate, anda base saturation of 0*῍ or more in one ormore horizons at a depth between ,/ and 1/ cm
from the mineral soil surface.
The natural weeds plot (T--) had a base saturation of /*.+1῍ between ,/ and 1/ cm depththat satisﬁes the approximate requirement by
Eutrudepts (ῌ0*῍). It can therefore be deduced
that when co#ee plantation is properly
managed with natural weeds, base saturation
is likely to increase within ,/ῌ1/ cm depth of
the sub surface horizon. So, there is a possibility of the changing soil class in great groupcategory from Dystrudepts to Eutrudepts.
Although clay minerals near this researcharea (Rigis Hill) are dominated by halloysite, + :+ type of clay mineral, but soils still haveenough amount of chlorite, vermicullite andsmectite (Lumbanraja, Syam, Sarno and Wada,+333), therefore soils have ability to swell andshrink. This phenomenon is shown by crack of/ mm or more width and -* cm or more length
in a depth of less than +,/ cm from soil surface
in each soil proﬁle. Beside, soils do not havelithic contact within /* cm from soil surface
and mollic or umbric epipedon. Based on thediscussions above, the three pedons are classiﬁed as vertic dystrudepts in sub group category,
although the slickensides or wedge-shape aggregates were not found.
-. - The Co#ee Growth
Although the existence of weeds could bepositive e#ect on the soil, however, in short

3/

,**-

term, it could suppress the co#ee growth performance. The control plot where the conventional weed management applied gave the best
performance of co#ee growth as shown inplant height, canopy diameter and coverage.
As reported by Afandi et al. (,**,), the weeds
had suppressed the co#ee height at Paspalum
plot about .*῍ and at natural weed plot about-*῍. The canopy diameter was also suppressed as much as /1῍ at Paspalum plot and/.῍ at natural weeds plot.
Sriyani et al. (,***) also reported that theyield reduction of co#ee beans in weedy plots
in +333 was .*῍ at Paspalum plot and 1/῍ atnatural weed plot compared to clean-weededplot.
-. . Conclusion
Covering soil surface by crops or weeds forfour years was able to conserve soils in hilly
area of South Sumatra and improved soil morphology as well as soil chemical properties.
Surface layer of soils treated with grasses andnatural weeds became thicker and darker than
before. Almost all soil chemical properties insoil surface layer increased depending on thetype of treatment. Thus, grasses plot had
thicker soil surface as well as higher available
P, exchangeable bases, Mg, K, Na, and basesaturation than natural weeds. On the other
hand, natural weeds increased organic carbon
content, total nitrogen, soil pH, CEC, exchangeable calcium, as well as decreased exchangeable Al and Al saturation in soil surface horizon.
It can be deduced from the study that, sincenatural weeds were able to increase exchangeable bases and base down to the sub-surface
layer, the soil class could possibly change from
Dystrudepts to Eutrudepts in the great soil
group category.
Even though several soil characteristics
changed, they were not enough to distinguishsoil nomenclature of three pedons in sub groupcategory. All pedons had vertic property in
sub group category, hence classiﬁed as Vertic
Dystrudepts.

῍ῌ : The Change of Morphology in Red Acid Soil after Four Years Treatment of Co#ee Plantation with Di#erent Weeds Management in a Hilly Area of Lampung, South Sumatra, Indonesia 61

References
Afandi, Manik, T.K., Rosadi, B.,Utomo, M, Senge, M,
Adachi, T. and Oki, Y. (,**, a) : Soil Erosion
Under Co#ee Trees with Di#erent Weed Managements in Humid Tropical Hilly Area of
Lampung, South Sumatra, Indonesia. J. Jpn.
Soc. Soil Phys., 3+ : -ῌ+..
Amin, T.C., Sidarto, S. Santosa and W. Gunawan(+33.) : Geology of the Kotaagung Quadrangle,
Sumatera, scale + : ,/*.***. Geo. Res. Dev.
Centr., Bandung.
Buol, S.W., F.D. Hole and R. J. Mc Cracken (+32*) :Soil Genesis and Classiﬁcation, Second Ed.
Iowa State Uniy. Press, Ames.
Buurman, P. (Ed.) (+32*) : Red Soils in Indonesia.
Centr. Agric. Publ. Doc., Wageningen.
Lumbanraja, J., et al., (+333) : Deterioration of Soil
Fertility by Land Use Changes in South Sumatra, Indonesia : from +31* to +33*. Progress
Report of Red Acid Soil Team, The Development of Sustainable Biological Production
Technologies Harmonized with Regional
Environmental Conditions in East Asia.
Lumbanraja, J., T. Syam, Sarno and Shin-Ichiro
Wada (+333) : Mineralogy of Soils in Hilly
Areas of West Lampung, South Sumatra. Progress Report of Red Acid Soil Team, The Development of Sustainable Biological Production
Technologies Harmonized with Regional
Environmental Conditions in East Asia.
Salam, A.K., Afandi, N. Sriyani and M. Kimura(+333) : Changes in Soil Enzymatic Activities
in A Hilly Co#ee Plantation in Lampung Province, South Sumatera Indonesia, Managed by
Di#erent Soil Conservation Techniques. Progress Report of Red Acid Soil Team, The Development of Sustainable Biological Production
Technologies Harmonized with Regional
Environmental Conditions in East Asia.
Soil Survey Division Sta#. (+33-) : Soil Survey

Manual. USDA Handbook No. +2. Washington
D.C.
Soil Survey Sta#. (+332) : Keys to Soil Taxonomy,
Eighth Ed., USDA-Natural Res. Conserv. Serv.,
Washington D.C.
Sriyani, N., Suprapto, H., Susanto, H., Lubis, A.T.
and Oki, Y. (+333) : Weeds population dynamics in co#ee plantation managed by di#erent
soil conservation techniques. Proc.of International Sem. Toward Sustainable Agriculture in
Humid Tropics Facing ,+st Century. Bandar
Lampung, Indonesia, September ,1ῌ,2 : /+-ῌ/,*.
Sriyani, N., Suprapto, H., Susanto, H., Lubis, A.T.
and Oki, Y. (,***) : The Development of Sustainable Biological Production Technologies
Harmonized with Regional Environmental
Conditions in East Asia, Final Report of theGreat-in-Aid for Creative Basic Research from
Ministry of Education, Culture, and Sport ofJapan : +3.ῌ+31.
Uehara, G. and G. Gillman (+32+) : The Mineralogy,
Chemistry, and Physics of Tropical Soils with
Variable Charge Clays. West View Press Inc.,
Boulder, Colorado.
Ugolini, F.C. and R.L. Edmonds (+32-) : Soil Biology, In L.P. Wilding, N.E. Smeck and G.F. Hall
(Ed), Pedogenesis and Soil Taxonomy I. Concepts and Interactions. Elsevier Sci. Publ.
Comp. Inc., New York.
Wiharso, D. (+330) : Characteristics of Red Soils
from The University of Lampung Experiment
Station in Tanjungan, South Lampung. Jo.
Trop. Soil II No. -, Bandar Lampung. (in Indonesian)Wiharso, D., Afandi and dan Masateru Senge(,**+) : Soil Chemical Properties of Three
Pedons on Co#ee Plantation Land Under
Di#erent Cover Crop. Jo. Res. Regional Dev’t.
Dryland Vol. ,- No. ,, Lampung University,
Bandar Lampung. (in Indonesian)$A@ » 3/ ¼ ,**-62ῌ
 .  !"#$%&'()*+,-./+,012345*ῌ*ῌ **ῌ  ***ῌ****ῌ ***** ** *** !"#$%&'**** ()*+,6

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HIJK L ;>)?@

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Apqῌr@;stSbcf Soil Taxonomy uA 2vlwx4!r;yXWz"S
4lf;34K {|}~MA#w234K T-+ : NATX!! , _; + Aῌ$2
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IJ!!Z T-- : NOA 2:%DIJ!!K Soil Survey Manual f Soil
Taxonomy Classiﬁcation System ;IJ=oW$%DI$|'DIJK . 

_AN;n4Z g$Mnw]C=]T4lf=JK JZ g$A
(Ar@Z f];$ pHZ )q Z ¡¢ Z )£q PZ ¤¥@¦§Z ¦§*+$=¨©I
JK L,Z g$A¤¥@ AlZ Al *+$Mª«IJK lAnx;|}^_¬;$A@M!rIJ= . _A2M Soil Taxonomy ;n4­®A

D!r¯4lf=2°±Z ¡WA$=

Vertic Dystrudepts fToJK IYIZ NOA 2S4f²gA¤¥@¦§f¦§*+$=¨©S4J³Z ^_´µS4f Soil Taxonomy uA

= Vertic Dystrudepts Y¶ Eutrudepts;!rS4·-@=¸JK
89 : BC$Z !!Z NZZ Vertic DystrudeptZ 78d¹º. : ,**-  / º +0 .
dº. : ,**-  3 º - .

ῐJ. Jpn. Soc. Soil Phys.
ῑ῏῎ῒΐῐ
No. 3/, p. 0-ῌ1- ῍,**-῎

Estimation of Dry Bulk Density of Soils Using Amplitude
Domain Reﬂectometry Probe
Krissandi WIJAYA, Taku NISHIMURA and Makoto KATO
School of Agriculture, Tokyo University of Agriculture and Technology, -ῌ/ῌ2 Saiwai-cho,
Fuchu-shi, Tokyo +2-ῌ2/*3 Japan
Abstract
It is worthy to know the distribution of soil physical properties in the ﬁeld to gain better
understanding of soil behavior. However, taking undisturbed core samples in situ is usually
laborious and time consuming. In this study, estimation of dry bulk density of soil by using
Amplitude Domain Reﬂectometry (ADR) data was conducted.

The dry bulk density can becalculated by combining volumetric water content measured by using the ADR probe (qADR) witheither wet bulk density or mass wetness. Andisol (TUAT soil) and Alluvial soil (Fukaya soil,
Saitama) was used in this study. Soils were sieved through - mm mesh screen, and packed into aplastic acrylic cylinder of 02 mm in inner diameter and 03 mm long. Mass wetness ranged from .*ῌ
1*ῌ and +/ῌ-*ῌ, and packing dry bulk density ranged from *.-3ῌ*.30 g cmῌ- and *.12ῌ+.-* g cmῌ-,for the TUAT and the Fukaya soil, respectively. Three replicated ADR readings of output voltage
were measured by using a digital multimeter. The qADR was calculated by using a calibrated
polynomial equation, as a function of the averaged output voltage. The results showed that theoutput voltage was not a#ected by neither packing dry bulk density nor mass wetness. The
estimation of dry bulk density with wet bulk density (R, value῍*.323ῌ*.33., RMSE value῍*.*+*ῌ*.*+. g cmῌ-) was better than that with mass wetness (R, value῍*.3+-ῌ*.30+, RMSE value῍*.*,1ῌ
*.*-2 g cmῌ-). The accuracy of the qADR was a critical factor in estimating dry bulk density.
Key words : dry bulk density, ADR, dielectric constant, Andisol, volumetric water content+.

Introduction

Soil behavior generally changes with timeand be di#erent from place to place depending
on physical condition of soil. Many of soil
processes such as physical, chemical, and biological processes are strongly a#ected by theheterogeneity of soil physical properties.
Therefore, understanding of how the soil physical properties distribute in the ﬁeld is very
important for solving soil problems such as
irrigation scheduling, drainage, soil and water
conservation, nutrient transport, and soil andgroundwater contamination.
Dry bulk density of the soil, which can be
expressed as the ratio of the mass of dry solids
to the bulk volume of the soil (Foth, +33* ;Hillel, +332) is one of the most useful soil parameter and a widely used value for predicting
other soil physical properties (Culley, +33-).
According to Campbell (+32/), Miyazaki (+330),
and Zhuang et al. (,***), dry bulk density canbe used to estimate soil permeability, since itstrongly a#ects pore structure, which may
dominate soil hydraulic conductivity. The
gravimetrical method, which involves weighing and drying a sample of known volume
taken from the ﬁeld, has been commonly used
for determination of soil dry bulk density.
However, the method is laborious and timeconsuming. Therefore, the use of the alternative technique, which is simple and fast formeasuring soil dry bulk density, is needed.
Dielectric constant techniques for estimating῏  3/

64

volumetric water content of soil such as Capacitance Insertion Probe (CIP), Time Domain
Reﬂectometry (TDR) probe, and Amplitude
Domain Reﬂectometry (ADR) probe are becoming popular (Topp et al., +32* ; Gaskin andMiller, +330 ; Inoue, +332 a, +332 b ; Robinson etal., +333). These techniques depend on the factthat the dielectric constant of water (2*) is
signiﬁcantly greater than that of most soil
matrix materials (.) and of air (+). Although the CIP, TDR and ADR probe have asimilar performance (Nakashima et al., +332),
the ADR and the TDR probe are easier to install and facilitate the accumulation of data
than the CIP, which requires the permanent
installation access tubes and operator intervention to position of the sensing head withinthese tubes (Gaskin and Miller, +330). Some
problems in the data interpretation and theﬁeld calibration may be obscured by inhomogeneities around probe wire such as
voids and stones, and confused by conductivity e#ect (Whalley, +33-). Furthermore, theTDR probe and the CIP have some disadvantages of high cost and their complex automatic
measuring system (Nakashima et al. +332). On
the other hand, the ADR probe is relatively
cheap and the output is direct current voltage,
which can be measured by commercial multichannel logger to monitor change in water content (Gaskin and Miller, +330). The ADR probe
has been developed to solve the problems of
the CIP and TDR probe (Nakashima et al., +332).
The objective of this study was to apply the
ADR technique for estimation of the dry bulk
density of disturbed soils.

Fig. +,**-,.

Materials and Methods,. + ADR Probe Components
According to Miller and Gaskin (+330), there
are three major components of the ADR probe
including an input and output cable, probe
body, and a sensing head (Fig. +). The cableprovides connection for a suitable power
supply (/ῌ+/ volt) and for an analogue signal
output. The probe body contains an oscillator,
a specially designed internal transmissions line
and measuring circuitry within a waterproof
housing. The sensing head has an array of fourelectrodes of 0* mm in length and - mm in diameter with a radial spacing of +/ mm, theouter three of which connected to instrument
ground from an electrical shield around thecentral (signal) electrode.
Principally, the ADR probe applies a +** MHz
sinusoidal signal via a specially designed internal transmission line to a sensing array of fourelectrodes whose impedance depends on dielectric constant of water content of the soil into
which it is embedded. If this impedance di#ers
from that of the internal transmission line,
then a proportion of the signal is reﬂected backfrom the junction (J), which lies between thesensing array and the transmission line. This
reﬂected component interferes with the incident signal causing a voltage standing wave to
be set up on the transmission line, i.e. a variation of voltage amplitude along the length ofthe line. Once the amplitude is measured, therelative impedance of the probe and then the
dielectric constant will be known. Hence, thevolumetric water content of the soil matrix canbe obtained.

A schematic diagram of the ADR probe.

ΐῒ : Estimation of Dry Bulk Density of Soils Using Amplitude Domain Reﬂectometry Probe,. , Soil Materials
Two soils such as Andisol (TUAT soil) andAlluvial soil (Fukaya soil) were used in thisstudy. The soils were sieved through a - mmmesh screen. A half of the soils were kept inplastic bag to keep mass wetness of //ῌ and,1ῌ, and the remaining soils were air-dried
until mass wetness of .*ῌ and +0ῌ, for the
TUAT and the Fukaya soil, respectively. Physical properties of the soils including texture,mass wetness (ῌ), dry bulk density (g cm῎-),volumetric water content (cm- cm῎-) and clay
mineral (X ray di#raction) are summarized inTable +.
,. - Experimental Methods
To cover the range of soil mass wetness between .*῎1*ῌ for the TUAT soil and +/῎-*ῌ
for the Fukaya soil, the air-dried sieved soils
were moistened with spraying distilled waterfor four to six times. Each moistened sample
was packed into a plastic acrylic cylinder of 02
mm in inner diameter and 03 mm long as uniformly as possible by manually increasing theincrements of a few centimeter thickness of thesoil to the cylinder up to the full volume. The
sample was then weighted by using an electricbalance to obtain wet bulk density.
The ADR probe was vertically inserted into
the sample (Fig. ,). The ADR reading of output
voltage was then measured by using a digital
multimeter. Three replicated ADR readings
were taken by re-installing the ADR probe vertically into an undisturbed part of the cylinder
and then averaged. After the ADR operation, aTable +
Soil parameters

sub-sample was taken and oven-dried to determine mass wetness. Measured volumetricwater content and dry bulk density were calculated from the mass wetness and the wet bulk
density.
The whole procedure was repeated for packing dry bulk density ranged from *.-3῎*.30 g
cm῎- and *.12῎+.-* g cm῎- for the TUAT and the
Fukaya soil, respectively. The ADR measurement was also applied on the oven-driedsamples whose volumetric water content wasconsidered to be zero. To prevent the excess
evaporation from the samples during the procedure, the experiment was done inside a smallchamber covered with a plastic ﬁlm.
,. . Estimation of Dry Bulk Density by
Using ADR Probe Data
For the estimation purpose, dry bulk density
can be calculated as function of volumetricwater content measured by using the ADR
probe (qADR) combined with either wet bulk
density (Eq. (+)) or mass wetness (Eq. (,)).
rbest+ῐrt῎ῌqADR῏rw῍ῌrbest,ῐῌ+**῏qADRῌw῍῏rw
῍
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῎-), and w is the mass
wetness (ῌ). Especially, Eq. (,) was multipliedwith +** to convert the mass wetness by percentage to that by decimal form.

Soil physical properties
Andisol soil (TUAT soil)

Alluvial soil (Fukaya soil)

sand : silt : clayῐ*4-,* :*4-,. : *4-/0 (LiC)sand : silt : clayῐ*4.0* :*4-,* : *4,,* (CL)

.*῎1*

+/῎-*

*4-3῎*430*412῎+4-*

Volumetric water content, q (cm cm )*4,,῎*40.

*4+0῎*4-/

Clay mineral (by X ray di#raction)

amorphousKrῑVrῑMi, Sm

῎+

Texture (kg kg )Mass wetness, w (ῌ)῎-

Dry bulk density, rb (g cm )
-

῎-

65

  3/

66

The use of either Eq. (+) or (,) in estimating
dry bulk density from the volumetric watercontent measured by using the ADR probe(qADR) gives some advantages especially when it
is applied to the ﬁeld measurement. For example, to obtain the estimated dry bulk density byusing Eq. (+) needs only the information of thewet mass (weight) of the soil occupying the
known volume of the core sample, and it is notnecessary to spend a day for oven drying thesample. It helps us to perform easy and fastestimation of ﬁeld dry bulk density, especiallywhen the large numbers of data are required.

,**-

Furthermore, although obtaining the mass
wetness data spends more time than the wetbulk density because of the need to ovendrying the sub-sample, incorporating the mass
wetness to Eq. (,) is still reasonable. For example, when the estimation of the dry bulk density is applied on taking larger numbers of ﬁeld
data, the mass wetness can be obtained byoven drying the only a small fraction of disturbed sample, so that it is capable to performnumber of estimation with less labor.
-.

Results and Discussions

Relationship between Volumetric Water
Content and Output Voltage
The calibration curve of the volumetricwater content and the output voltage for the
TUAT soil shows increase in output voltage
with increasing in volumetric water content(Fig. -). The output voltage ranged from *.+0ῌ
*.33 volt corresponded to volumetric soil watercontent of *.,,ῌ*.0. cm- cm-. The relationshipbetween output voltage and volumetric watercontent can be expressed in Eq. (-) with regression coe$cient (R,) value of *.32.,-. +Fig. ,

Schematic diagram of the experiment.

Fig. - (a)Relationship between volumetricwater content and ADR output
voltage for the TUAT soil, in caseof packing dry bulk density.

Fig. - (b)Relationship between volumetricwater content and ADR output
voltage for the TUAT soil, in caseof mass wetness.

ῐ῏ : Estimation of Dry Bulk Density of Soils Using Amplitude Domain Reﬂectometry ProbeqADR῎*.**+++ῌ+./-+v῍,.-.,v,ῌ+...2vῌ
where, v is the output voltage of the ADR
probe. Mathematical expression shown in Eq.
(-), (.), (0) and (1) are the third polynomial equations which were accomplished by applying
least square method.
Increasing the output voltage with the increasing in volumetric water content was also
found in the Fukaya soil (Fig. .). The soil withvolumetric water content ranged from *.+0῎*.-/
cm- cm῍- corresponded to the output voltage of*.,,῎*.20 volt, and the relationship between
output voltage and volumetric water content
can be expressed in Eq. (.) with R, value of*.32+.
qADR῎*.**--/ῌ*.30.v῍+./-*v,ῌ+.*-2v῍The q-v curve shown in Fig. - and . contains
two cases such as either packing dry bulk density or mass wetness as a parameter. Each caseis divided into three data intervals. For the
TUAT soil, the packing dry bulk density
ranged from *.-3῎*./2, *./2῎*.11, and *.11῎*.30 g
cm῍- and the mass wetness ranged from .*῎/*,

Fig. . (a)Relationship between volumetricwater content and ADR output
voltage for the Fukaya soil, incase of packing dry bulk density.

67/*῎0*, and 0*῎1*ῌ, respectively. For Fukayasoil, the packing dry bulk density ranged from*.12῎*.3/, *.3/῎+.+-, and +.+-῎+.-* g cm῍- and themass wetness ranged from +/῎,*, ,*῎,/, and ,/῎-*ῌ, respectively. Although dry bulk densityof the TUAT soil was smaller than that of the
Fukaya soil, the TUAT soil had greater mass
wetness. It was due to micro structure of the
TUAT soil (Light Clay) was more complicatedthan the Fukaya soil (Clay Loam). As a consequence, the TUAT soil was capable to retain
more water per unit weight of the soil than the
Fukaya soil.
The division of the packing dry bulk density
and the mass wetness into three data intervals
was aimed to clarify the dependence of theoutput voltage against the two parameters. As
shown in Fig. - and ., the plotted data overlapped through the regression line withinthose three data intervals. It suggested thatthe output voltage was not a#ected by neither
packing dry bulk density nor mass wetness.
The root mean square error (RMSE) value between the measured q and the qADR of whole
data with di#erent packing dry bulk density

Fig. . (b)Relationship between volumetricwater content and ADR output
voltage for the Fukaya soil, incase of mass wetness.

68



and mass wetness was *.*+. cm- cm- and *.**2
cm- cm- for the TUAT and the Fukaya soil,
respectively.
It revealed that the qADR
signiﬁcantly depended on the type of soil. The
independence of the qADR on either packing dry
bulk density or mass wetness was also clariﬁedby the RMSE value of each interval of theparameters. In case of the TUAT soil, theRMSE value for packing dry bulk density
ranged from *.-3῎*./2, *./2῎*.11, and *.11῎*.30 g
cm- was *.*+., *.*+-, and *.*+0 cm- cm-, whilethat for mass wetness ranged from .*῎/*, /*῎0*,
and 0*῎1*῍ was *.*+/, *.*+,, and *.*+1 cm- cm-,respectively.
Furthermore, in case of the
Fukaya soil, the RMSE value was *.**1, *.**2,
and *.*+* cm- cm- for packing dry bulk density ranged from *.12῎*.3/, *.3/῎+.+-, and +.+-῎+.-*g cm-, and *.*+,, *.**0, and *.**3 cm- cm- formass wetness ranged from +/῎,*, ,*῎,/, and ,/῎-*῍, respectively.
-. , Relationship between Volumetric Water
Content and Dielectric ConstantMiller and Gaskin (+330) found that in therange of output voltage of *῎+ volt, the relationship between the ADR reading of output voltage and the square root dielectric constant canbe precisely described by the third polynomial
equation, as shown in Eq. (/). In this study, theequation was employed for the TUAT and the
Fukaya soil.
ῌe+.*10..*v0..*v,..1*vῌ
where, ῌe is the square root dielectric constant.
Since the volumetric soil water content was
the primary factor a#ecting the apparent dielectric constant, increasing volumetric watercontent resulted in the increase of the dielectric
constant (e), as shown in Fig. / and 0. For the
TUAT soil (Fig. /), in the range of the dielectric
constant of .῎-,, which corresponded to thevolumetric water content of *.,,῎*.0. cm- cm-,the relationship can be expressed in Eq. (0).
qADR*.+3/*.*,0/e*.***32.e,*.****+2-e*.,1/e+*.**0,/e,῍The dielectric constant of the Fukaya soil
ranged from /῎,. corresponded to the volumet-

3/

,**-

ric water content of *.+0῎*.-/ cm- cm-, asshown in Fig. 0. The following Eq. (1) expressed the relationship between volumetricwater content and dielectric constant for the
Fukaya soil.

Fig. /

Relationship between volumetric watercontent and dielectric constant of the
TUAT soil.

Fig. 0Relationship between volumetric watercontent and dielectric constant of the
Fukaya soil.

ῐ῏ : Estimation of Dry Bulk Density of Soils Using Amplitude Domain Reﬂectometry ProbeqADR῎*.*31.ῌ*.*+,3e῍*.****3+0e,ῌ*.*1..e῍+
῍*.,0/e῍,ῌTopp et al. (+32*) presented the “universal
calibration formula” for measuring volumetricwater content based on dielectric constant ofmany (common) soils in all over the world, as
shown in Eq (2).
q῎῍*.*/-ῌ*.*,3,e῍*.***//e,ῌ*.*****.-e῍Comparison between the Topp’s universal
equation and the equations derived from theq-v calibration of the two Japanese soils in thisstudy showed that the dielectric constant of
the TUAT soil was signiﬁcantly greater thanthat of the Topp’s soils, while for the Fukayasoil, it was rather similar to the data presented
by Topp et al. (+32*) and was higher only whenvolumetric water content was *῎*., cm- cm῍-.
It suggested that the universal equation was
not always applicable for measuring volumetric water content of the soils such as the TUAT
soil. For the Fukaya soil, Topp’s equation was
rather acceptable especially for volumetricwater content ranged from *.,/῎*.-- cm- cm῍-.
These trends were similar to the results presented by Miyamoto and Chikushi (,***). Also,
Fig. / and 0 revealed that dielectric constant
was strongly a#ected by the type of soil.
-. - Comparison between Estimated andMeasured Dry Bulk Density
Since the estimated dry bulk density (rbest)
was calculated by substituting the qADR dataobtained from Eq. (-) and (.) into Eq. (+) and (,),
the accuracy of the rbest was strongly a#ectedby the accuracy of the qADR data. In case of the
TUAT soil, the accuracy of the rbest can be
determined from the comparison between therbest and the measured dry bulk density (rbmsr)
shown in Fig. 1. The ﬁgure describes that the
rbest agreed well with the rbmsr. The cloud of thedata points was laid and concentrated aroundthe + : + regression line. The R, value for thedata estimated by using Eq. (+) and (,) were*.323 and *.30+, respectively. It revealed thatthe estimation of dry bulk density with wet
bulk density had greater accuracy than that69

with mass wetness. The greater the accuracyof the rbest, the lower the error of the rbest. In thisstudy, the error is expressed in the RMSE value
between the rbmsr and the rbest. For whole data,
the RMSE value of the rbest by using Eq. (+) was
generally a half of that by using Eq. (,) such as*.*+. g cm῍- and *.*,1 g cm῍-, respectively. The
RMSE value within the given ranges of packing dry bulk density and mass wetness were
ﬂuctuated. In the range of packing dry bulk
density of *.-3῎*./2, *./2῎*.11, and *.11῎*.30 g
cm῍-, the RMSE value of the rbest by using Eq.
(+) was *.*+., *.*+-, and *.*+0 g cm῍-, and that byusing Eq. (,) was *.*,., *.*,1, and *.*,3 g cm῍-,
respectively. In the range of mass wetness of.*῎/*, /*῎0*, and 0*῎1*ῌ, the RMSE value ofthe rbest by using Eq. (+) was *.*+/, *.*+,, and*.*+1 g cm῍-, and that by using Eq. (,) was *.*-.,*.*,,, and *.*,/ g cm῍-, respectively. As can beseen from Fig. 3, the ﬂuctuation of the RMSE
value of the rbest by using Eq. (+) was
signiﬁcantly smaller and not di#erent enoughfrom the value of whole data compared to thatof the rbest by using Eq. (,). The RMSE of therbest by using Eq. (,) was more sensitive to thechange of mass wetness from the lower to theFig. 1Comparison between estimated andmeasured dry bulk density of the
TUAT soil.

  3/70

higher mass wetness than that by using Eq. (+).
Therefore, the use of Eq. (,) in the estimation ofdry bulk density became less reliable than thatof Eq. (+) although the RMSE value of the rbest
by using that equation was still acceptable.
Fig. 2 shows the comparison between the rbest
and the rbmsr, for the Fukaya soil. The rbest of the
Fukaya soil also agreed well with the rbmsr. The
data of rbest by using Eq. (+) and rbest by using
Eq. (,), which were plotted around the + : +regression line showed the R, value of *.33. and*.3+-, respectively. It suggested that similar to
the TUAT soil the estimation of dry bulk density with wet bulk density was better than thatwith mass wetness. For whole data, the RMSE
value of the rbest by using Eq. (+) was lower thanthat by using Eq. (,), such as *.*+* g cm- and*.*-2 g cm-, respectively. The RMSE value
within the ranges of packing dry bulk densityof *.12ῌ*.3/, *.3/ῌ+.+-, and +.+-ῌ+.-* g cm- was
ﬂuctuated such as *.*+,, *.**3, and *.*+* g cmfor the rbest by using Eq. (+), and *.*-*, *.*-/, and*.*.2 g cm- for the rbest by using Eq. (,), respectively. The RMSE value within the ranges ofmass wetness of +/ῌ,*, ,*ῌ,/, and ,*ῌ-*ῌ wasFig. 3,**-also ﬂuctuated such as *.*+,, *.**1 and *.*++ gcm- for the rbest by using Eq. (+), and *.*01,*.*,/, and *.*-- g cm- for the rbest by using Eq.
(,), respectively. As can be seen from Fig. +*,Fig. 2Comparison between estimated andmeasured dry bulk density of the
Fukaya soil.

Error of the estimated dry bulk density by either Eq. (+) or (,), for the TUAT soil.

῍ῌ : Estimation of Dry Bulk Density of Soils Using Amplitude Domain Reﬂectometry Probe

Fig. +*

71

Error of the estimated dry bulk density by either Eq. (+) or (,), for the Fukaya soil.

ﬂuctuation of the RMSE value occurred in therbest by using Eq. (,), and it was slightly in therbest by using Eq. (+). The change of mass wetness from the lower to the higher mass wetness
caused the greater RMSE value of the rbest byusing Eq. (,) and had small e#ect on the RMSE
value of the rbest by using Eq. (+). Therefore, Eq.
(+) seems to give better estimation of the dry
bulk density than Eq. (,) although the RMSE
value resulted from the rbest by Eq. (,) was
considered reasonable. Furthermore, small
ﬂuctuation of the RMSE value of the rbest ofeither the TUAT or the Fukaya soil suggested
that the dry bulk density estimated by using
the ADR data and either wet bulk density or
mass wetness was independent on mass wetness of the soil. The di#erence in the RMSE
value of the rbest between the TUAT and the
Fukaya soil revealed that the type of soil had
also signiﬁcant e#ect on the accuracy of therbest.
Incorporating the wet bulk density into theestimation of dry bulk density was more reasonable than incorporating the mass wetness.
Di#erence in mathematical formula between

Eq. (+) and (,), into which the wet bulk density
or the mass wetness was substituted, may be areason of the result above. In this calculation,
since the rbmsr, rt and w value, which employ the
wet and the dry soil mass of a given core
volume, was carefully obtained throughgravimetrically measurement, their errors was
assumed to be very small and could be
neglected. It was also assumed that the signiﬁcant error resulted from the qADR measurement.
As Eq. (,) was mathematically formulated in adivision formula, so that when the qADR including the errors were substituted into the equation, the errors of rbest may increase since themass wetness (w) in the Eq. (+*) was always lessthan unity. Thus, this error may enhance withdecreasing in mass wetness. On the other
hand, when the qADR data was substituted into
the Eq. (+), which was known as a subtracting
formula, the error of rbest shown in Eq. (3) was
lower compared to when it was substituted
into Eq. (,).
Derivation of Eq. (+)

72rbest+ῌrbmsrrbest+ῌ
ῌrbmsrrtqADRrwῌ
ῌrbmsrrtqmsrqADRrwῌ
ῌrbmsrrtqmsrrwqADRrwῌ
ῌrbmsrrbmsrqADRrwῌ
ῌrbmsrrbmsrqADRrwῌ
ῌqADRrwῌ
qADRrw
ῌ
Derivation of Eq. (,)
rbest,ῌrbmsrrbest,ῌ
ῌrbmsr+**qADRῌwrwῌ
ῌr bmsr +**q msr qADR ῌ wrwῌ
ῌr bmsr +**q msr ῌ wrw +**qADRῌwrwῌ
ῌr bmsr rbmsr +**q ADR ῌ w
rwῌ
ῌrbmsrrbmsr+**qADRῌwrwῌῌ+**qADRῌwrwῌ
+**qADRῌwrw
῎
῍
where, rbmsr is the dry bulk density measured
gravimetrically ; qmsr is the volumetric watercontent measured gravimetrically ; rbest+ isthe error of rbest+ ; rbest, is the error of rbest, ; qADR is the error of the qADR to the true q.
In this study, since the qADR data originallycontained some extents of errors calculating
the qADR involved combination of the qmsr andthe qADR (qADRqmsrqADR). This error wasconsidered as a primarily factors a#ecting theaccuracy of rbest, especially rbest,. For example, if
the qADR for a given soil with w ranged from.*῏1*῍ (TUAT soil) is *.+ cm- cm-, thereforethe rbest+ is *.+rw, and rbest, is ranged from*.+. (+***.+/1*) rw*.,/(+***.+/.*)rw.
The phenomena indicated that the error of estimated dry bulk density with mass wetness
was higher than that with wet bulk density,
especially for the lower mass wetness (Fig. 3
and +*).
..

Conclusions

The output voltage using the ADR probe
was not a#ected by neither packing dry bulk
density nor mass wetness. In other word, the q
ADR was independent upon these two parame- 3/  ,**-

ters. Therefore, the ADR data can be used for
estimation of dry bulk density.
The estimation of dry bulk density with wet
bulk density was better than that with mass
wetness. The lower accuracy of the rbest withmass wetness was a#ected by the division formula of calculation process.
Since the rbest was determined from the qADR,
therefore the accuracy of the qADR was a criticalfactor in estimating dry bulk density.
Acknowledgement
Part of this study was supported by Grantsin-Aid for Scientiﬁc Research by Japan Societyof the Promotion of Science : No. ,**+῏+-10*+03.
References
Campbell, G.S. (+32/) : Soil physics with basic :Transport models for soil-plant system, pp. .3῏/3, Elsevier, Amsterdam, Netherland.
Culley, J.L.B. (+33-) : Density and compressibility
in Soil sampling and method of analysis (Carter,
M.R., Ed.), pp. /,3῏0-*, Lewis Publisher, New
York, USA.
Foth, H.D. (+33*) : Fundamentals of soil science (2thedition), pp. +,῏-., John Wiley & Sons, Inc.,
Boca Raton, USA.
Gaskin, G.J., and Miller J.D. (+330) : Measurementof soil water content using simpliﬁed impedance measuring technique, J. Agric. Eng. Res.,
0- : +/-῏+0*.
Hillel, D. (+332) : Environmental soil physics, pp. -῏+1, Academic Press, San Diego, USA.
Inoue, M. (+332 a) : Evaluation of measuring precision of ﬁeld-type dielectric soil moistureprobes using salty sand, J. Japan Soc. Hydrol.
& Water Resour., ++ : ///῏/0..
Inoue, M. (+332 b) : Monitoring system for ﬂow andsolute transport, Sand Dune Research, ./ (+) :+/῏,/.
Miller, J.D. and Gaskin G.J. (+330) : Theta probe ML,x : Principle of operation and applications (,nd edition), Macaulay Land Use Research Institute (MLURI), Aberdeen, UK.
Miyamoto, T. and Chikushi, J. (,***) : Relations between soil water content and apparent dielectric constant evaluated by dielectric mixing
models, Trans. of Japan Society of Irrigation,
Drainage and Reclamation Engineering, ,*0 :0-῏1+.
Miyazaki, T. (+330) : Bulk density dependence of air

|} : Estimation of Dry Bulk Density of Soils Using Amplitude Domain Reﬂectometry Probe

entry suctions and saturated hydraulic conductivities of soils, Soil Science, +0+ : .2.ῌ.3*.
Nakashima, M., Inoue, M., Sawada, K. and Nicholl,
C. (+332) : Measurement of soil water content
by Amplitude Domain Reﬂectometry Method
and its calibrations, J. of Groundwater Hydrology, .* : /*3ῌ/+3.
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#ects ofbulk soil electrical conductivity, J. of Hydrology, ,,- : +32ῌ,++.

Topp, G.C., Davis, J.L. and Annan, A.P. (+32*) : Electromagnetic determination of soil water content : Measurement in coaxial transmission
lines, Water Resour. Res., +0 : /1.ῌ/2,.
Whalley, W.R. (+33-) : Considerations on the use oftime-domain reﬂectometry (TDR) for measuring soil water content, J. of Soil Science, .. : +ῌ3.
Zhuang, J., Yu, G.R., Miyazaki, T. and Nakayama,
K. (,***) : Modeling e#ect of compaction on
soil hydraulic properties : A NSMC scaling
method for saturated hydraulic conductivity,
Adv. in GeoEcology, -, : +..ῌ+/-.

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ῌ




73



ADR  !"#$%&"'()*+,%-./0()*123+,/45"6 78
9volt:6 ;<=>?3@=ABCD$'E FGHA+,I Topp 9+32*: AJK>LM%N;<=ῌOPQ"'E R-/6 ADR STU"'?3@=>V/WX6 YZ/TU[\%]^_`6 @a5Fbcd_`AeUfg'E FGHA+,/hFbI6 eU"'cd_`L6 ijk
STU"'l/m"b6 nBCo R,p*.3+-q*.33. SrFnBQ"'E cd_`AeUlL6 ADR /sN?3@=>]^_`5F'>t/surFJKQ"'E
 : cd_`6 ;<=6 ADR6 ()*+,6 ?3@=vwxyz : ,**- x + y ,+ zv{xyz : ,**- x 3 y +3 zῐ
J. Jpn. Soc. Soil Phys.
῏῍ῌῐῑ῎
No. 3/, p. 1/ῌ3* ῍,**-῎Current and Prospective Applicationsof Zero Flux Plane (ZFP) Method
Magdi KHALIL*, Masaru SAKAI*, Masaru MIZOGUCHI* and Tsuyoshi MIYAZAKI** University of Tokyo, Graduate School of Agricultural and Life Sciences, Department of Biologicaland Environmental Engineering, Yayoi +ῌ+ῌ+, Bunkyo-ku, Tokyo ++-ῌ20/1, Japan
Abstract
Zero ﬂux plane (ZFP) method has been used to measure and estimate the evaporation,
evapotranspiration, some hydrological process etc. However, no systematic discussion has been
made concerning the ZFP method itself or its application to monitor and control the salt andcontamination movement. In this study, comprehensive analysis on existing data sets have been
performed to examine ZFP method applications and to give comments for further applications infuture. First, ZFP method deﬁnition and its mathematical derivation were stated. Second, theapplication of ZFP to evaporation, evapotranspiration and ground water recharge process werediscussed and analyzed. The di$culties that a#ect the application of ZFP method such as depthof soil, preciseness of measurements etc. have been listed and compared. Finally the potentialities
of ZFP method were discussed. The discussion showed that, the development of new techniques
related to measurement instruments, required experiments and simulations to implement ZFP ine#ective way is very important to monitor and control salt transportation and accumulation
control.
Key words : zero ﬂux plane, unsaturated soil, Hydrus-,D, salt accumulation, soil contamination+.

Introduction

The importance of the soil-water system innature and in the life of man has been realized
since the dawn of civilization and man’s awakening awareness of his relationship to his environment (Hillel, +31+). The liquid phase of a soil
is never just pure water. There are always
mineral salts and organic substances dissolvedin the water. Generally, in spite of the importance of its solutes, the liquid phase of soil iscalled soil water. (Kutilek and Nielsen, +33.).
Most of the process involving soil-water interaction in the ﬁeld occurs while the soil is in an
unsaturated condition (Hillel, +332), or in otherwords, in vadose zone, (Miyazaki, +33-). Therefore the movement of water in unsaturated soil
is of a great importance where there are many
applications especially related to the hydrolog-

ical cycle and plant growth and stress. Suchknowledge allows an estimate of the inﬂuenceof soil conditions on plant growth, determination of the schedule of irrigation and drainage.
Prior to the recent application of soil physics
techniques in water balance studies, the di#erence between the rainfall and the evapotranspiration was often used to determine the moisture balances and deﬁcit, e.g. Gardiner (+320).
Errors arise in both measurements and estimates, and give rise to considerable uncertainty (Cooper et al., +33*). Measurements or estimation of water ﬂux in unsaturated soil is
impractical because of the wide range of hydraulic conductivity values found in soils, their
spatial variation and hysteresis (Cooper et al.,+33*). One of the prospective and promisingtechniques used to determine the moisture balances in unsaturated soil is ZFP method.

῏ΐῐ῎῔῕ῑ ῒ 3/ ῏ ῌ,**-῍

76

The purposes of this review paper are to
make clear the ZFP concept physically andmathematically, to compare the published dataof the ZFP, and to discuss the accuracies,
di$culties and potentialities of this method.
,.

ZFP Method,. + Deﬁnition
ZFP is deﬁned as a plane, which separates
two zones of upward and downward movement of water in a thoroughly wetted soil with
evaporation and drainage occurring simultaneously. Water moves in an upward direction above this plane, and downward below it,i.e., there is no ﬂow across the boundary
separating the two zones. With negligible lateral soil variation, the “zero ﬂux” boundary
may be assumed to be planar. As the soil dries
the plane of “zero ﬂux” moves downward (Aryaet al., +31/). In other words, when evaporation
exceeds rainfall, it is expected that water in theupper part of the soil proﬁle moves upwards
towards crop roots or the soil surface as exempliﬁed in Fig. +. Water in the lower partcontinues to drain water table. The point
where water is neither ﬂowing up nor down isFig. +

called the ZFP.
The old term used for ZFP was static zone. It
was ﬁrst mentioned by Richards (+3/.), with
Fig. , where he used a new instrument, multiple unit tensiometer, to measure the hydraulichead and the hydraulic gradient of water inunsaturated ﬁeld. He used the term static zone
in connection with the soil-water system todesignate the locus of points, above whichwater movement is upward, and below whichwater movement is downward. Due to theinﬂuence of the evaporation at the surface ofthe soil, this static zone passes downward
through soil following the wetting. Each curvein Fig. , represents the total potential distribution with depth on the days in October indicated by the number on the curve. The curveof Oct. +3 shows the total potential distribution
while water was still ponded on the soil surface. Between Oct. ,+ and ,, there was areversal in the hydraulic gradient in the +*ῌ,*
cm soil interval. Between Oct. ,- and ,., theﬂow reversed in the ,*ῌ-* cm depth interval.
On Oct. ,-, there was +.*1 cm rain. This caused
a marked shift in the total potential values. By
Oct. ,1, the static zone has passed below the ,*Zero ﬂux plane concept.

ΐῒ : Current and Prospective Applications of Zero Flux Plane (ZFP) Method

Fig. ,First use of ZFP method. (from Richards, +3/.)

cm depth. By Oct. ,3, the static zone has passed
below the -* cm depth. Some time before Nov.
++, upward ﬂow was established from depths
greater than /* cm. Therefore, the static zone
corresponds to the depth at which the hydraulic gradient is zero. (Richards et al, +3/0). In
ﬁeld studies, the depth within the soil proﬁle atwhich the water ﬂux density is zero is of major
importance and relatively easy to measure(Kutilek and Nielsen, +33.).
,. , Mathematical derivation of ZFP
MethodStammers et al. (+31-) described the approximation of mathematical derivation of the correct expression of ZFP depth as shown in Fig.
-. Both evaporation and drainage could be
calculated at above and below ZFP.
z*ῌt+῍z*ῌt,῍

**EῐR῎ῑqῌt+῍dz῏ῑqῌt,῍dzz*ῌt,῍῎+ῌqῌt ῍῎qῌt ῍῎dz
,
῍ +
῏
,ῑ
z ῌt ῍
*

ῌ

+

Z

Z

Dῐῑqῌt+῍dz῏ῑqῌt,῍dz
z*ῌt+῍z*ῌt,῍z*ῌt,῍+῏ ῑῌqῌt+῍῎qῌt,῍῎dz῏, z ῌt ῍
῍
*

77

+

where :
E is evaporation over the period t+ to t,
R is rainfall over the same period
t is time῍

z is depth measured positively downwards
Z is the depth at which drainage is calculated
D is drainage over the period t+ to t, throughdepth Zq is volumetric water content
zo(t) is the ZFP depth at time t.
From Fig. -, it is clear that, by decreases the
moisture content in the soil, the ZFP is gettingmuch deeper as well. The procedures to obtainequations (+) and (,) based on Fig. - is given in
Appendix attached.
-.

Application of ZFP to Evaporationand Evapotranspiration

In dry periods, when evapotranspiration exceeds rainfall, the soil water in the upper partof the soil proﬁle moves upwards towards theroot zone and the soil surface. At lower depth
soil water moves downwards towards thewater table due to gravity. Above ZFP, any
reduction in the soil moisture content must be
due to the moisture loss caused by an excess ofevapotranspiration, below the ZFP, and assuming no uptake of moisture content by roots atthese depths, reduction in moisture content
must be due to drainage out of the soil, i.e.
recharge to the ground water table.
The ZFP moves downwards as loss toevapotranspiration increase. In using the ZFP,
it is assumed (Cooper et al., +33*) that :ΐῐ῎῔῕ῑ ῒ 3/ ῏ ῌ,**-῍

78

Fig. -

Principle of the zero ﬂux plane method. (a) Hypothetical pressure potential proﬁles. (b) The
corresponding water content proﬁles.
The shading represents water that has evaporated or drained between t+ and t,. (fromCooper, +33*)+) Root extraction of soil moisture below
the ZFP is negligible, i.e. there is only drainage
below the ZFP,) Water inﬁltrating the soil surface moves
downward through the soil matrix ; if there ispercolation through macropores, such as
cracks or wormholes, evapotranspiration will
be overestimated and drainage will be underestimated-) There is no surface run-o#, if there is, it
should be taken into account.
Literature search revealed that most of authors have used ZFP method either to estimate
the evaporation, to calculate the drainage, or todi#erentiate between drainage and evaporation. (Van Bavel et al., +302 ; Stone et al., +31- ;Roman et al., +333). Therefore, we will discuss
two examples of estimating the short-term
evaporation and long-term evapotranspiration
by ZFP method in this section, followed byestimation of drainage in the next section.
Estimation of the evaporation in short termThony et al. (+313) estimated the evaporationfrom a +** m, plot of bare soil during a ﬁve-day
period of intense evaporation following heavy
rain, which had saturated the upper soil horizon. They evaluated the daily evaporation
rates for ﬁve days from ,/*2/11 to 1/*2/11, (a)by monitoring the moisture movement using
ZFP method and soil water balance methodand (b) by aerial measurements of the evaporative ﬂuxes into the atmosphere (energy balancemethod).
ZFP method has been used when ZFP existed. On the other hand, soil water balancemethod has been implemented during the absence of ZFP. The ﬁeld experiment is located in
Gernoble Mechanical Institute in France. The
soil proﬁle was as follows : from *.* to *.,/ mmuddy silt, from *.,/ to *./* m ﬁne sand andfrom *./* to +.* m clay soil. They used neutronprobe to measure water content and manometer tensiometers to measure the matric potentials. The total potential proﬁle and soil moisture content proﬁle during ﬁve days monitoring are shown in Fig. .. The total potential῍ῌ : Current and Prospective Applications of Zero Flux Plane (ZFP) Method

proﬁle of Aug. , shows that ZFP is blow ,* cm.
By Aug. 1, the ZFP has passed below the 0* cm
depth. The daily and cumulative evaporation
obtained by both ZFP and soil water balancemethods, and energy balance method werecompared in Table +.
They also studied the soil water dynamics inthe upper layer under natural cyclic evaporation conditions, it being found that the hydraulic head in this horizon is subject to periodic
variations. This phenomenon can be attributed principally to the cyclic nature of theevaporative process, which results in drying
up of the soil during the day followed by re-Fig. .

79

wetting at night as a result of internal redistribution. They concluded that the moisture
movement under these conditions is governed
principally by hydrodynamic e#ects, withthermal e#ects playing only a very minor role.
The results obtained by the two methods being
found in good agreement. Other literature concerning short-term evaporation were carriedout by Kalms et al. (+313) ; McGowan Williams(+32*) ; Inoue et al. (+32/) ; Yamamura et al.
(+322) ; Villegas and Morries (+33*) ; Payne etal. (+33*) ; Kanamori (+33/) ; Diez et al. (,***),
who all suggested the usefulness of ZFP
method to estimate short term evaporation.

The hydraulic potential proﬁle and soil moisture content proﬁle during ﬁve days monitoring. (from Thony, et al., +313)

Table +

Cumulative evaporation obtained by both ZFP and energybalance methods (from Thony et al., +313)

From

to

ZFP method andwater balance method

Energy balance method,ῌ*2ῌ11-ῌ*2ῌ11.ῌ*2ῌ11/ῌ*2ῌ110ῌ*2ῌ11-ῌ*2ῌ11.ῌ*2ῌ11/ῌ*2ῌ110ῌ*2ῌ111ῌ*2ῌ11-41/ mm-4,/ mm-4/* mm-4,/ mm-4,/ mm.4** mm.4,/ mm.4/* mm-4,/ mm-4/* mm

Sum +14** mm+34/* mmΐῐ῎῔῕ῑ ῒ 3/ ῏ ῌ,**-῍

80

Estimation of the evapotranspiration inlong term
Kirsch (+33-) used ZFP method for estimating the actual evapotranspiration (ET) in ﬁeld.
The experimental ﬁeld was located on the
grounds of the University of Illinois in U.S.A.
The soil at the site is silty clay loam. The
vegetation of the ﬁeld was fescue and red
clover. The rooting zone of the growing plants
extended to a depth of about .* cm. He used
about 0* tensiometers to monitor the total hydraulic potential, at depths of between 2 and+0/ cm. Neutron probe access tubes were used
to monitor the water moisture of the soil. He
carried out three ﬁeld experiments. First experiment was conducted for ,* days in Julyand August +321. The second experiment was
conducted for +, days in June and July. The
last one was conducted for +* days in October.
The movement of ZFP through the time during
the three experiments are shown in Fig. /. It isclear that the ZFP is getting deeper throughthe summer season and starts to be steady atthe beginning of winter. For the three ﬁeld
experiments, the errors ranged between +/-ῌ
for +-day ET estimates to .,ῌ for / days estimates. It is clear from the result that the
improper location of ZFP plays an importantrole to overestimation or underestimation ofwater content in the unsaturated area.
Other literature concerning long-term evapo
ration were done by Royer and Vachaud (+31.) ;Sharma (+32/) ; Dolman et al. (+322) ; Roman etal. (+333), who all obtained reasonable estimations of long-term evaporation by using ZFP

Fig. /

method.
..

Application of ZFP to Recharge Processes

For many dry climates, ground water is amajor source of water supply for irrigation,industrial, and domestic demands. Estimationof safe yield is an important basis for developing long-term management plans. This requires knowledge of recharge rates beneathvarious land use conditions, and their expectedvariability over a long periods.
Furthermore, the e$cient management ofground water resources requires knowledge ofthe quantity of water recharging the aquifer.
This allows safe and reliable pumping regimes
to be established without over-exploitation of
the aquifer or over-reduction of base ﬂows torivers fed by the aquifer. Ground water recharge can be easily estimated by ZFP method.
The reason for that is, below the maximum
depth reached by the ZFP, soil water ﬂow isalways downward ; hence, the water draining
through any depth below this will appear eventually as recharge at the water table. (e.g.
Cooper, +313 ; Sharma, +32/ ; Simmers, +321 ;Bouwer, +323).
The ZFP method is considered the mostdirect method for determining the recharge
rate of ground water. Therefore, several authors have used it to estimate the ground water
recharge (Royer and Vachaud, +31. ; Cooper,+32* ; Wellings, +32., Dreiss and Anderson, +32/ ;Healy, +323 ; Cooper et al., +33* ; Gardner et al.,+33* ; Sharma et al., +33+ ; Tang, +330 ; Ragab
et al., +331 ; Hosty and Mulqueen, +330 ; Ab-The movement of ZFP through time during the three experiments. (from Kirsch, +33-)῏῎ : Current and Prospective Applications of Zero Flux Plane (ZFP) Method

dallah et al., ,**+ ; Tsujimura et al., ,**+).
Table , gives the main features of groundwater recharge estimation done by some ofthese workers.
In the following section, a simple brief andanalysis will be mentioned about some of theseworks.
Sharma et al. (+33+) used the zero ﬂux plane
method and water balance method to estimate
the seasonal change in recharge to the under-

Year

81

laying sandy aquifer. They monitored down
the soil water dynamic of the unsaturated zone
to depth of ,* m of a period for three years.
They used neutron probes for moisture content
measurements. A simpliﬁed schematic of thehydrological cycle for the experiment is shownin Fig. 0. They deﬁned two references Z+ andZ,. The depth Z+ (῍+* m) is below the inﬂuenceof the root water uptake, and is the maximum
depth of the ZFP (Cooper, +313 ; Wellings andTable ,The main features of ground water recharge estimation done by some workers

Name &
location

Field &
soil surface

PurposeInstruments

Features
ZEP
Range

Exp.
TimingComments
Soil
proﬁle&Analysis+32*

CooperEnglandForested Evaluate ZFP N.P. & P.T.
and clearing as a tool tositesmeasure R
Sand lying
on Chalk

Max.
ZFP
-4, m

-.
months+32.

Wellings
EnglandGrass &
BarelySilty Clayloam lying
on Chalk

Estimate R
and E

N.P. & P.T.

-ῌ0 m

0 years.* m

ZFP is not valid
in winter time

+33* Cooper et al.
England

0 Grass
sites
Sand lying
on Chalk

Estimate R

N.P. & Ts.

Max.
ZFP
ῌ+40 m,ῌ/
years+*ῌ3* mE#ect of soil
properties on
E&R
is not clear+33+

SharmaAustralia

NativeWoodland&
Sandy soil

seasonalchange in R

N.P.

+* m

- years,* m

No matric
potential
measuredRun o# isneglected+330

M. Hosty
IrelandDry
E & R tograssland groundwater
Sandy loam

N.P. & Ts.

*42//. m P.M.
ῌ+4/ m months
W.T. . m

Lowering watertable hasno e#ec on ZFP,**+

Abdallah
Grass land
ET & R to
M.A. et al.
Aquifergroundwater
Switzerland Sandy loam

N.P. & Ts.

*4//ῌ*41 + year Empincal
methodW.T. ,41
P.M.
ῌ-4, mSnow coverproblem &Particle size
distribution
e#ect* N.P. Neutron probe* Ts Tensiometers* E Evaporation* ET Evapotranspiration

No independent
estimate ofdrainage* P.T. Pressures Transducers* R Recharge* PM. Penman Model  3/

82

Fig. 0,**-A simpliﬁed schematic representation of the hydrological balance used in the analysis.
Here Z+ῌ+* m and Z,ῌ+2 m are arbitrary depths. Z+ is the maximum depth for the ZFP andrecharge below this depth is termed R+.
Z, is an arbitrary depth just above the water table and recharge below this depth is termedR,. (Sharma, et al., +33+)

Bell, +32*). The depth Z, (+2 m) is an arbitrary
depth just above the water table. Recharge
below Z+ and Z, are termed R+ and R, respectively. Four pore holes were drilled and soil
water content down the proﬁle was measured
for each.
It is interesting that the authors did not estimate evapotranspiration in computing the recharge and did not use the directly- measured
soil matric potentials in the proﬁle.
Foridentifying the location of ZFP in the proﬁle,matric potentials are obtained inversely frommeasured soil water content. However theirscheme could be valid for reasonably deep unsaturated zone exists between the maximum
rooting depth and the water table.
Thechanges in soil water storage for this depth
interval are used at appropriate times to compute water ﬂux.
There is some uncertainty in the exact loca-

tion of the ZFP particularly when the matricpotential is calculated not measured. However,with the start of the rainy seasons, ZFP develops at the surface and the wetting front moves
downward and ﬁnally cancels the original ZFP
below. The soil water proﬁle for the hole 0 at
various time during an annual cycle is shownin Fig. 1.Total water potential proﬁles for thesame hole are shown in Fig. 2. Approximate
location of the ZFP is shown for each proﬁle. It
is interesting that ZFP could be last to over +*meters and not for few centimeters below thesoil surface as known. Therefore, ZFP is dynamic not static.
Hosty and Mulqueen (+330) studied the soil
moisture for a free-draining podzolic soil witha water table at . m below ground level.
Evaporatranspiration and drainage to groundwater were computed using both zero ﬂux
plane and water balance methods. They used῎῍ : Current and Prospective Applications of Zero Flux Plane (ZFP) Method

Fig. 1

Total water potential for the same period shown in Figure. (Sharma et al.,+33+)

both neutron probes and tensiometers to measure the moisture content and hydraulic potential respectively. Total potential of pore waterpressure over the May to September period of+33, have been shown in Fig. 3, and Fig. +*.
The ﬁeld result showed that a ZFP developedin early May as shown in Fig. 3 and moved
intermittently downwards to a maximum of +./m as the summer progressed. On ,* August,the ZFP was +./ m below ground surface. Because of -0 mm rainfall between ,* and ,1August, hydraulic potentials increased. As
heavy rainfall continued (23.+ mm between ,1
August to +1 September), the hydraulic potential proﬁle moved toward the gravitational potential line and there was evidence of temporary saturation at the + m depth (Fig. +*).
Pumping of the aquifer took place from ,/August to +/ September at an average discharge of +// m- hῌ+. This had the e#ect oflowering the water table at the measurement

Fig. 2

83

Soil water proﬁle for hole 0 at various
time during an annual cycle. (Sharma etal., +33+)

site from . m to 1./ m below ground surface. It
is important to mention that, lowering thewater table had no e#ect on the soil moisturein this study, where it (the water table) was
initially deep and well below the root zone.
Although pumping of the aquifer was on going
during this period, it is signiﬁcant that the soil
moisture proﬁle above the water table was determined by the balance between rainfall andevaporation.
/.

Application di$culties of ZFP method/. + ZFP depth
It is well known that the depth of ZFP is notstationary or ﬁxed, it moves up and down
during the year and sometime, it does not exist
at all. ZFP depth ranges from few centimeters
to few meters below the soil surface. The
accurate determination of ZFP in the soil is noteasy and need special care and sensitive instruments. The misestimating of the location ofΐῐ῎῔῕ῑ ῒ 3/ ῏ ῌ,**-῍84

Fig. 3Fig. +*

Downward progression of the ZFP. (from Hosty et al., +330)

Hydraulic potential proﬁles before and during pumping tests. (from Hosty et al., +330)

ZFP leads to misestimating of soil water storage. This in turn, causes a considerable error in
calculating both recharge ground water andevaporation rate.
/. , Root zone
For its success, the ZFP method requires that
there be no extraction of water by roots beneath the ZFP since all losses of water in thisregion are assumed to be due to drainage andall losses of water above ZFP assumed to be
due to evaporation as well. Given that someroots are known to penetrate to at least 0 m,
this is unlikely to be strictly fulﬁlled.
However, and for drainage estimation, thefollowing points make it probable that extraction from below the ZFP is at most relatively῔ΐ : Current and Prospective Applications of Zero Flux Plane (ZFP) Method

small (Cooper, +313). :(a) Although no quantitative information isavailable on the distribution of roots, within
the proﬁle, the overwhelming majority has
been observed within the upper meter of soil.
Provided that water is fairly readily available,
it is expected that these roots will extract mostof the water with only a tiny proportion
coming from lower in the proﬁle.
(b) As the ZFP gets deeper, the fraction ofroots below it becomes steadily less.
(c) There is, at all times, at least one meterof soil above the ZFP at a tension of less than
one bar (+** kPa). Drying within the upper , m,where potentials reach several bars, proceeds
quite steadily to the end of the experiment, sothat water must be available even at thesetensions.
Moreover, and related to evaporation estimation, ZFP method gives a good agreement withtranspiration calculations based on meteorological data, when it was known that roots
penetrated below the ZFP, supporting the viewthat the root extraction from below the ZFP
does not introduce a major error in using themethod (Dolman et al. +322).
/. - Non-existence of ZFPZFP method is useful when accurate measurements at short time scales are required, andwhen frequent measurements can be made.
However, the method failed to estimate the soil
water during periods when rainfall exceeds
saturated hydraulic conductivity Ksat. In
other word, if ZFP is at land surface (no ZFP
existed), the method cannot be used, as only
downward movement throughout unsaturated
zone occurred.
The biggest limitation of the ZFP method isthat it can be only used under conditions
where a ZFP exists specially in dry season. In
wet areas, this may be infrequently. However,in many drier areas, ZFP may be observed forwell over half of the year. When ZFP cannot be
observed, the meteorological estimates of evaporation, although not totally satisfactory, isreasonable and drainage estimated during

85

these periods, for any depth below the groundsurface, may then be calculated from a simple
water balance of the soil proﬁle (Stammer etal., +31- ; Arya et al., +31/ ; Cooper, +313, +32* ;Cooper et al., +33* ; Kirsch, +33-) by using theequation.
z

DῑRῐEῐῒ῎qῌt+῍ῐqῌt,῍῏dz*/. . Preciseness of measurements
Although, ZFP method is based on measurements made directly in the controlling
medium, the soil, special care should be given
to the instruments in the ﬁeld. Therefore, highdensity of instruments and high frequency ofmeasurements needed to get relatively accurate results.
Sometimes errors are associated with moisture content measurements (Van Hylckama,+32*). This could be large relative to thechange of moisture content between successive
measurements ; therefore, this method is usually applied over a period of at least + week.
Using neutron probes near the soil surface
may lead to incorrect measurements, therefore,
accurate, sensitive tools should be used. As
shown in table ,, most of authors used neutronprobes to measure the moisture content. The
sources of error in soil water measurementswith a neutron probe can be summarized asfollow (McGowan et al., +32*) :a) Systematic errors that occurred as aresult of calibration, soil damage from accesstube installation and damage to surface soil
and vegetation.
b) Random errors which, happened becauseof random count error, relocation error andinherent soil variability errors as well.
Time Domain Reﬂectometry, TDR, may be
used more widely hitherto, because its preciseness and convenience to monitor both moisture content distribution and unsaturated soil
water movements.
Careful measurements of matric potential
and proper installation of tensiometers are crucial and important to detect ZFP in preciseway.

ΐῐ῎῔῕ῑ ῒ 3/ ῏ ῌ,**-῍86/. / Hysteresis
Almost all the soil moisture characteristic
curves show hysteresis due to the ink bottle
e#ect. Since the sizes of soil pores change
successively, the existing of the ink bottle
e#ect is generally recognized (Miyazaki, +33-).
Care must be exercised in incorporating thee#ect of hysteresis, by using the appropriate
part of sorption or desorption relationship. In
most cases where the e#ective rainy seasons isdistinct (Wellings and Bell +32*) the desorption
curve could be used without introducing mucherror (Sharma et al., +33+).
0.

Potentialities of ZFP method

Although many researchers used ZFP to estimate the water ﬂux in soil to measure recharge
to ground water, to compute drainage orevapotranspiration, and to calculate unsaturated hydraulic properties, but there was no study
that focused on the ZFP phenomena itself.
Since ZFP is governed with many parameters,
the studying and analyzing these factors could
contribute much to implement several new
aspects of applications. The developing of ZFP
could be achieved by improving measurements
tools and technique, implementing new experiments in laboratory to monitor and study ZFP
and using numerical model and simulation foranalysis as well.
Measurement
Although it could be concluded that ZFP is
uncertain for some ﬁeld uses, the errors
associated with estimation of soil moisture
content may be minimized through use of moreaccurate methods for measuring water content
or increasing the number of neutron probe
access tubes sampled at the ﬁeld both action
would likely make estimation of ET more reliable.
More accurate methods of quantifying soil
water content may include, for example, timedomain reﬂectometry. Errors associated improperly location of ZFP may be minimized byusing time-domain reﬂectometry method.
There is no doubt the fact that accurate deﬁni-tion of the total hydraulic head distribution
with the depth, making identiﬁcation of the
ZFP more precise.
Laboratory Experiments
Careful experiments should be carried out inthe laboratory to monitor and observe the ZFP
in soil column. The factors a#ecting the ZFPmovement will be tested and analyzed. Salt
movement and accumulation in soil should be
deeply investigated using di#erent types ofsoils.
Numerical model
One of the powerful tools, which may help
much in dealing with ZFP phenomenon, is numerical model. HYDRUS-,D model is used for
simulation of water ﬂow and solute transport
in two-dimensional variably saturated media.
The program numerically solves the Richards’
equation for saturated-unsaturated water ﬂow
and the Fickian-based advection-dispersion
equation for solute transport. Using HYDRUS,D model could give good assistance to analyze
the experimental results and to simulate thecomplex problems. For example, Hydrus-,D
could simulate di#erent topographical problems, such as sloped soil, which are di$cult tobe simulated at the laboratory.
Salt transportation and accumulation
In fact, the maintaining of ZFP higher than
the salt accumulated subsoil, nuclear disposals,
contaminated layers.... etc., is practically very
important. Therefore the control of ZFP in
unsaturated soil is of a great interest where
there are many applications especially related
to the environmental, agricultural and civil engineering. In addition to hydrological ﬁelds.
Such knowledge allows us to select the suitable
depths in the soil to bury the contaminateddisposals in safe way. This knowledge is also
important to determine when to irrigate, tocalculate the amount of water to apply, and to
estimate drainage below the root zone. Furthermore, preserving ZFP above the salt accumulated subsoil is very important to agricultural ﬁeld. Selecting the convenient depths
into the soil to establish an oil pipes network is῍ῌ : Current and Prospective Applications of Zero Flux Plane (ZFP) Method

a#ected as well by the ZFP. Protecting the
ground water from contamination will be achieved partially by ZFP control.
References
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Switzerland.
Hydrological
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Bouwer, H. (+323) : Estimation and enhancing
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῕῔ : Current and Prospective Applications of Zero Flux Plane (ZFP) Methodor ;Appendix
Water balance equation above ZFP can be
written as :RῑE῏ΐqῌ
where :
R is the rainfall over the period t+ to t,,
E is the evaporation over the period t+ to t,,
ΐq is the volumetric water content change
above ZFP.
Since the decrease of water content (q) between z* (t+) and z* (t,) due to evaporation isz*῍t,῎approximated by+ῐq῍t ῎ῐq῍t ῎ῒdz
+
ῑ ,
ΐ
,ῒ
z ῍t ῎*+Volumetric water content change ΐq above
ZFP is given byz*῍t+῎z*῍t+῎**ΐqῑῒq῍t,῎dzῐῒq῍t+῎dz+
ῐq῍t ῎ῐq῍t ῎ῒdz
+
ῑ ,
ΐ
,ῒ
z ῍t ῎*z*῍t,῎z*῍t+῎ῐῒq῍t+῎dz῏
*

῏

Z

ῐ

z*῍t,῎z*῍t,῎

*

*

*

*

+

Z

z*῍t+῎z*῍t,῎

**

DῑRῐRῐῒq῍t+῎dz῏ῒq῍t,῎dzz*῍t,῎ῐ++ῐq῍t ῎῏q῍t ῎ῒdz
,
ῑ +
ΐ
,ῒ
z ῍t ῎*ῑῐῒq῍t+῎dz῏ῒq῍t,῎dz+z*῍t,῎Zῐῌq῍t,῎dz῏ῒ῍q῍t,῎῎dz῎῍ῒ῏*z ῍t ῎z*῍t,῎*+ῐ ῒῐq῍t+῎῏q῍t,῎ῒdzῌΐ, z ῍t ῑ῎*

z*῍t,῎ῐῒῌq῍T,῎῎dz῏ῒ῍q῍t+῎῎dz
῍
῏
*
*

+

z*῍t,῎z*῍t+῎z*῍t+῎Z+ῐῐῒq῍t,῎dz ῐq῍t,῎ῐq῍t+῎ῒ
ῑ ῒ
ΐdzΐ
,ῑῒ
z ῍t ῎z ῍t ῎*Z+ῐq῍t ῎῏q῍t ῎ῒdz
,
ῑ +
ΐ
,ῒ
z ῍t ῎**+Zz*῍t,῎ῑῐῒq῍t+῎dz῏ῒq῍t,῎dz*+

RῑE῏D῏ῒῌq῍t,῎ῐq῍t+῎῎dz῍῏*+ῐq῍t ῎ῐq῍t ῎ῒdz
+
ῑ ,
ΐ
,ῒ
z ῍t ῎z*῍t,῎+ῐq῍t ῎῏q῍t ῎ῒdz
,
ῑ +
ΐ
,ῒ
z ῍t ῎*z*῍t,῎**

Since water balance equation for whole soil
proﬁle isRῑE῏D῏ΐq῎where :
R is the rainfall over the period t+ to t,,
E is the evaporation over the period t+ to t,,
D is the drainage over the period t+ to t,,
ΐq is the volumetric water content change
from zero to arbitral depth Z.

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Journal of the Japanese Societyof
Soil Physics
November ῍ῌῌ῎

No. 3/

Contents
Foreword ῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌS. HASEGAWAῌ +Original Papers
In-situ Measurements of Density and Distribution of Periphery Roots of Tomato
Seedling Using Machine Vision SystemῌῌῌῌῌῌῌM. UCHIGASAKI, S. MIYAMOTO, K. SERATA, S. TOJO and K. WATANABEῌ Adsorption of Nitrogen Chemical Fertilizer on Volcanic Ash Soil and Electric Charge
CharacteristicsῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌS. MATSUKAWA and H. KATOUῌ+Soil Proﬁle Distribution and Terrain Attribute on a Hilly Site ῌῌῌῌῌJ. KASHIWAGIῌ,+
Prediction of Ion Concentration in The E%uent during Permeation of Acid Solutions
Including Multiple Anionic Species into a Volcanic Ash SoilῌῌῌῌῌῌῌῌῌῌῌῌῌῌK. KAMEYAMA, S. MATSUKAWA, T. ISHIDA and H. KATOῌ-Field Measurement of the Water Retention Curves and Simple Estimation of Their
Parameters for Soils in the Central Region of Horqin Sandy LandῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌX. LIU, N. NISHIMURA, T. AMAYA and T. LIUῌ.+The Change of Morphology in Red Acid Soil after Four Years Treatment of Co#ee
Plantation with Di#erent Weeds Management in a Hilly Area of Lampung, South
Sumatra, IndonesiaῌῌῌῌῌῌῌAFANDI, D. WIHARSO, M. SENGE, A. J. TAWIAH, Y. OKI and T. ADACHIῌ//
Estimation of Dry Bulk Density of Soils Using Amplitude Domain Reﬂectometry
Probe ῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌK. WIJAYA, T. NISHIMURA and M. KATOῌ0Reviews
Current and Prospective Applications of Zero Flux Plane (ZFP) MethodῌῌῌῌῌῌῌῌῌῌῌῌῌῌM. KHALIL, M. SAKAI, M. MIZOGUCHI and T. MIYAZAKIῌ1/
Readers’ column ῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌS. YOSHIDAῌ3+
Announcements ῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌ3Editor’s Postscript ῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌῌ3/

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