Water movement through an aggregated, gravelly oxisol from cameroon

Geoderma, 46 (1990) 263-281

263

Elsevier Science Publishers B.V., Amsterdam - - Printed in The Netherlands

Water M o v e m e n t t h r o u g h an A g g r e g a t e d , G r a v e l l y Oxisol from C a m e r o o n PAUL. R. ANAMOSA, PETER NKEDI-KIZZA*, WILLIAM G. BLUE and JERRY B. SARTAIN

Soil Science Department, University o[ Florida, Gainesville, FL 32611-0151 (U.S.A.) Received May 1, 1989; accepted after revision July 31, 1989)

ABSTRACT Anamosa, P.R., Nkedi-Kizza, P., Blue, W.G. and Sartain, J.B., 1990. Water movement through an aggregated, gravelly Oxisol from Cameroon. Geoderma, 46: 263-281. Increasing population pressures have caused increased utilization of the gravelly (stone line) soils common to the hilly landscapes of equatorial Africa. This study was conducted to determine if macropore water flow and immobile-water regions should be considered in describing solute movement while developing nutrient-managementstrategies. Break-through curves (BTC's) from miscible displacement experiments with tritiated water were measured from 70-cm long by 9.6 cm internal diameter, water-saturated, undisturbed soil columns. Simulations produced by theoretical transport models were fitted to the BTC's to determine the magnitude of dispersivity and immobile-water regions. Gravel separates composed of kaolinite, gibbsite, goethite and manganese oxides had porosities ranging from 0.13 to 0.32 m3/m 3, with a composite sample porosity of 0.20 m3/m 3. Adsorption coefficients of tritium ranged from 0.031 to 0.052 ml/g for the three horizons in the soil columns. Columns containing gravel (30% by volume and 62 % by weight) gave asymmetrical BTC's. A convective-dispersive (CD) transport model was unable to simulate observed BTC's accurately. The mobile/immobile (MIM) water model provided close agreement to BTC's obtained at flow rates ranging from 2.71 to 111 cm/d. The water-saturated soil columns had about 50% of all water in immobile regions. Soil water dispersivity was 3.3 cm2-n d n-1 (with empirical constant n = 1.3 ) from a curvilinear plot of the dispersion coefficient and the mobile pore-water velocity. Parameters estimated from one column were applied to the BTC's of a similar soil column. The MIM model showed close agreement between the measured and the independently estimated BTC's. These soil characteristics can contribute to the rapid deep transport of a limited quantity of solute and to the storage and/or slow diffusive mass transport of the remaining solute from within immobile regions.

INTRODUCTION

Soils with shallow gravel horizons are widespread on the sloping landscapes of equatorial Africa (Fairbridge and Finkl, 1984). Such soils constitute over *Corresponding author. Contributed by the Institute of Food and Agricultural Sciences, University of Florida. Florida Agric. Exp. Stn. Journal Series no. R-000060.

264

P.R. ANAMOSA ET AL.

50% of the land surface of Western Nigeria (Smyth and Montgomery, 1962; Babalola and Lal, 1977a) and are common in regions of Senegal (Amouric et al., 1986), Sierra Leone (Dijkerman and Miedema, 1988), Togo (Ldvdque, 1969 ), Benin (Fauck, 1963 ), Cameroon (Muller and Bocquier, 1986), Uganda (Ollier, 1959 ), Gabon (Collinet, 1969 ), Congo (Riquier, 1969 ), Zaire (Stoops, 1968) and Ethiopia (S6galen, 1969). Although these soils are considered agriculturally marginal, increasing population pressures have increased their utilization for food production. Due to the influence of the gravel on soil properties and with crop production in these regions being largely dependent on improved soil-fertility management (Sanchez et al., 1982), methods to describe and predict water and nutrient movement within and below the root zone are important for efficient use of limited resources. Most of the research performed on these soils has focused on soil morphology and on formation processes. The few studies that have evaluated the effects of the physical properties of gravelly soils on plant behavior and water movement have inferred that gravel primarily restricts rooting depth and limits the nutrient and water-holding capacity of the soil. Babalola and Lal (1977a,b) and Vine and Lal (1981) demonstrated that, as soil gravel contents increased, corn rooting depth and total root length decreased and root thickness and crookedness increased. Quantitative description of nutrient and water movement in soils is limited in part by the present understanding of the effects of large soil pore-size distributions on preferential water flow (by-passing) and of physical non-equilibrium in immobile water regions (Davidson et al., 1983; Valocchi, 1985 ). Understanding the effects of gravel on water and nutrient movement is further complicated by the status and magnitude of water inside the gravel. Mathematical models based on the convective-dispersive transport equation (CD) are becoming increasingly popular tools to estimate soil hydrodynamic properties from solute breakthrough curves obtained from soil column experiments. Modification of the convective-dispersive model to include concepts of immobile soil water regions has been made (Coats and Smith, 1964; Passioura, 1971; van Genuchten and Wierenga, 1976). Nkedi-Kizza et al. (1983) have utilized the modified model to explain better water and solute transport through aggregated heterogeneous porous media. Recent studies examining mineralogical transformations in gravel samples from tropical stone line soils have found numerous vesicular voids (Amouric et al., 1986; Muller and Bocquier, 1986). Electron micrographs of thin sections were unable to confirm the continuity of pores from surface to interior regions. However, the postulated mineral transformation processes require element transport into and out of the gravel's interior. Intra-gravel porosity could impart specific influences on soil-water properties. The purpose of this study was to determine if preferential water flow and immobile-water regions should be considered in describing water movement in a tropical stone-line soil.

WATER MOVEMENTTHROUGH OXISOLFROMCAMEROON

265

M A T E R I A L S AND M E T H O D S

The soil studied is a clayey-skeletal, oxidic isohyperthermic, Typic Gibbsiorthox located 8 km north of the University Center of Dschang in the Western Province of Cameroon. The top three horizons, which are represented in the soil columns, contain appreciable quantities of gravel (Table I). The fine fractions of the Ap and Ac horizons have a weak crumb structure, whereas the Btc horizon has medium sized, moderately strong aggregates. The gravel fraction was separated into four classes, visually distinguished by color and differentiated by mineralogy and porosity (Table II). Porosity of the gravel was determined by the Brunauer-Emmett-Teller (BET) method on a Quantachrome AUTOSORB-6 surface area unit. Gravel particle density was determined using a gas phycnometer (Danielson and Sutherland, 1986). TABLEI Selected physical properties of the soil Horizon Depth (cm)

Ap Ac Btc 2BCt 2CB

Bulk Gravel density (kg/kg) (g/cm3)

0- 11 11- 22 22- 72 72-138 138-194+

0.88 1.00 1.46 1.26 1.28

0.335 0.588 0.720 0 0

Fine fraction (kg/kg of< 2 ram)

Clay minerals*1 ( % )

Sand

Silt

Clay

K

Q

Gb

GE

0.211 0.111 0.112 0.118 0.064

0.355 0.403 0.337 0.145 0.193

0.435 0.486 0.551 0.737 0.743

55 60 60 60 55

15 10 5 5 5

15 15 20 15 20

15 15 15 20 20

,1 K = Kaolinite; Q = quartz; GE = goethite; Gb = gibbsite. T A B L E II Physical and mineralogical characteristics of the gravel Color

Yellow (12) .1 Pink (8) Red (75) Black (5 ) Composite

Predominant minerals

Goethite (90) *2 Kaolinite (60) Gibbsite (20) Gibbsite (80) Kaolinite (10) Manganese oxides

Pore volume (ml/g)

Average pore radius (nm)

Particle density (g/ml)

Bulk density (g/ml)

Porosity (ml/ml)

0.145

3.62

3.31

2.24

0.32

0.184

14.40

2.55

1.74

0.320

0.087

8.69

2.63

2.14

0.186

0.043

4.91

3.55

3.08

0.133

2.71

2.18

0.195

,1 Approximate percentage of mineral content. *2percentage c o n t e n t of natural-composite total (by mass).

266

P.R. ANAMOSAET AL.

Column preparation Undisturbed soil columns were taken using the method of Foale and Upchurch (1982). An 80-cm long, 9.6 cm i.d. PVC pipe was inserted into a soilcore sampler (102 mm i.d./114 mm o.d. ) fitted with a sharp, hardened-steel cutting edge and threaded, removable-steep cap. The sampler was hammered into the ground until the top of the cap was nearly level with the soil surface. The sampler was then lifted from the soil with a hydraulic jack. The PVC pipe full of soil was removed from the sampler, sealed and boxed for transport to the laboratory. The two columns samples in this study was naturally separated in the field by about 2 meters. The dimensions and selected physical properties of the two soil columns used in this study are presented in Table III. The columns were of slightly different lengths, but contained nearly identical concentrations of water, gravel and fines. Excess PVC pipe was cut from the top end of two of the columns so that the new end was 5 mm above the soil surface. Approximately 5 mm of soil were removed from the bottom of the columns and both ends were fitted with T A B L E III

Dimensions and selected physical properties of soil columns Soil or column property

Units

Column I

Column II

Length Surface area Volume Weight, oven dry Bulk density Porosity

cm cm 2 1 kg kg/l 1/1

71.6 72.38 5.18 6.55 1.26 0.525

68.9 72.38 4.99 6.42 1.29 0.527

g/g g/g g/g

0.37 0.42 0.21

0.38 0.44 0.18

1/1 1/1 1/l

0.18 0.20 0.10

0.19 0.21 0.09

kg/1 kg/1 kg/l

2.61 2.71 2.65

2.67 2.81 2.66

Particle size fractions by mass < 2 mm 2-12 m m 12-75 m m by volume .1 < 2 mm 2-12 mm 12-75 m m Particle density < 2 mm 2-12 m m 12-75 m m • 1 Intra-gravel porosity excluded.

WATER MOVEMENTTHROUGH OXISOLFROM CAMEROON

267

T A B L E IV Set-up for t r i t i u m miscible displacement experiments on Columns I a n d II Column-Experiment no..1

Flux, q (cm/d)

Pulse, T (pore volume)

I-1 I-2 I-3 I-4 II- 1 II-2

111 16.8 2.71 36.7 2.69 36.7

1.43 2.58 2.84 2.65 2.88 2.59

.1 Order of execution

porous, fitted-glass plates (maximum pore radius of 15/~m ) and with plexiglass and plates.

Miscible displacement The columns were held vertically and saturated from the bottom with approximately five pore volumes of a degassed solution of 0.01 M CaCI2. The columns were then turned horizontally, and the end plate in contact with the surface AP horizon was connected to an influence solution by way of a threeway valve which allowed switching between tritiated and nontritiated solutions of 0.01 M CaCle. The effluent was collected with a fraction collector at the other end of the column. The solution flux was varied from slowest to fastest by a factor of 40 (Table IV). The 3H20 activity in the effluent fractions was monitored using liquid-scintillation techniques. The transport models were fitted to the measured BTC's with the program CFITIM using the third type boundry conditions (Van Genuchten, 1981), which assumes a constant influent flux and a semi-infinite column.

Convective-dispersive water model (CD) The classical convective-dispersive (CD) model in dimensionless form is given by:

R(OC/OT) = ( l / P ) (02C/Ox 2) -OC/8x

[1]

where R is the retardation factor, C is the relative solute concentration, T is the solute pulse volume, P is the Peclet number, and x is the relative distance described as follows:

R = 1 +pKJO,

[2 ]

268

P.R. ANAMOSA ET AL.

C=Ce/Co,

[31

T=v/L=qt/OL,

[4]

P=vL/D,

[5]

x=z/L,

[6]

where p is the bulk density (g/cm3); Kd is the absorption coefficient (ml/g); 0 is the volumetric soil-water content (cm3/cm 3); Ce and Co are the effluent and influent tracer concentrations (Bq/ml), respectively; v is the average pore water velocity (cm/d); q is the D arcy flux (cm/d); t is time (d); L is the column length (cm); and D is the dispersion coefficient (cm2/d).

Mobile-immobile water model (MIM) The mobile-immobile (MIM) water model developed by Van Genuchten and Wierenga (1976), which considers two soil-water regions and explicitly assumes that all convective transport occurs in the mobile region, with transport in the immobile region being limited to diffusion, is given in dimensionless form by:

~R(OCm/OT) + (1-fi)ROCiJOT= ( l / P ) (OCJOx 2) -OCJOx

[7]

and ( 1 - fl)R OCim/OT=m(Cm--Vim)

[8]

where

fl= (Ore+ pfKd) / ( O+pKd), Pm= vmL/Dm,

[9] [lOl

and

to=~L/q,

[11]

in which Cm and Cim are the relative (normalized with respect of Co) concentrations in the mobile and immobile regions; 0m is the mobile water content; [ is the fraction of the total adsorption sites in the mobile region; Vmis the pore water velocity in the mobile region; Dm is the mobile pore water dispersion coefficient; and c~is the first-order mass transfer coefficient (l/d). The parameters fl, P~ and to are the fraction of solute in the mobile region, the mobile water Peclet number, and the dimensionless mass transfer coefficient, respectively, and have been defined previously.

WATER MOVEMENT THROUGH OXISOL FROM CAMEROON

269

Adsorption isotherms Adsorption isotherms for 3H20 were determined using a batch technique similar to that described by Dao and Lavy (1978). Moist sieved ( > 2 mm) soil samples from each of the three horizons present in the columns and a composite gravel sample (2-4.7 m m ) were assayed. Triplicate 4-g samples of each material was placed in a pre-weighted 10 ml plastic screw-top centrifuge vial with a 1 m m hole drilled in the bottom. The vials were sealed and reweighed. solutions of 0.01 M CaC12, spiked with varying activities of 3H20, were injected into the basal hole until the materials appeared to be near saturation. The vials were reweighed and then placed on top of a glass marble resting on the bottom of a 30 ml plastic screw top centrifuge tube. These larger tubes were then sealed and set on their sides for 48 hr to allow equilibration of the tritium throughout the sample. The 30 ml tubes were centrifuged at 30 g (where g is the force of gravity), forcing the soil solution out of the soil and through the basal hole to be collected around the marble in the bottom of the larger tube. The extruded solution was retrieved and the 3H20 activity was measured. The soil sample was dried at 105 °C for 48 hr and weighed. The adsorbed ~I-I~Owas determined as the difference between 3H20 activity in the extruded solution and that of the initial 3H20 activity in the injected solution, after accounting for the original water content of the samples. Adsorption isotherms were constructed by plotting adsorbed versus solution 3H20 activity. Adsorption coefficients were calculated by linear regression, forced through the origin. An overall soil colu m n retardation factor, R, was calculated using weighted mean adsorption coefficients of the gravel and fine fraction samples for each horizon. RESULTS AND DISCUSSION

Adsorption isotherms The tritium adsorption isotherms for the three horizons and a composite gravel sample are presented in Fig. 1. The isotherms were linear within the concentrations ranges used and were fitted to the Freundlich equation

S=K~C.

[12]

where S is the sorbed concentration (Bq/g), Kd is the adsorption coefficient (ml/g) and C is the solution concentration (Bq/M1). The tritium was only slightly adsorbed to the soil and gravel (Kd < 0.052 ). Tritium adsorption of this magnitude to similar soil minerals has been reported by Nkedi-Kizza et al. (1982). A weighted mean retardation factor, R = 1.05, was calculated (Eq. 2 ) from the adsorption coefficients of the fine and gravel fraction for the three horizons.

270

P.R.A N A M O S A ET AL.

Ac 11-22 c m /

Ap 0-11 cm / / ~ 6

/ S = O. 047C

ni-

Gravel

I.IJ

0

r 2 0 . 94**

8

z

0 a

8 = 0.052C

r 2 0.79.*

2

Btc 22-72 cm

S - O. 013C

4

r 2 0 . 92**

0

.

2

//

, r2= 0.,93.* I

00

100

200

0

100

2oo

SOLUTION CONCENTRATION,C (l~:l/mL) Fig. 1. Tritium adsorption isotherms for column horizons and composite gravel. TABLE V C D water mode optimized dimensionless parameters

Experiment No.

Flux q (cm/d)

Peclet number P

Retardation factor R

I-1

111

1.4 (0.2) 1.0 (0.1) 1.9 (0.2) 4.0 (0.3)

0.74 (0.05) 1.02 (0.06) 1.01 (0.O5) 1.12 (0.02)

I-4

36.7

I-2

16.8

I-3

2.71

Numbers in parentheses are 95% confidence intervals ( _+)

CD model analysis T h e p a r a m e t e r s e s t i m a t e d b y t h e Cd m o d e l for t h e f o u r d i s p l a c e m e n t e x p e r i m e n t s f r o m C o l u m n I a r e s h o w n in T a b l e V. T h e t r i t i u m - p u l s e v o l u m e w a s h e l d c o n s t a n t d u r i n g t h e f i t t i n g p r o c e s s , b u t t h e r e t a r d a t i o n factor, R a n d P e -

WATERMOVEMENTTHROUGHOXISOLFROM CAMEROON 1.2

r~_

1

Expt. I-1

I-

q-

L

0 Measured datapoints

/

b--- °" [

iO'" i

271

o~.

o.6

111 c m / d

....

,.4

o.7,

~

0.82 1.05(fixed)

0.2

0 0

2

4

6

8

PORE VOLUMES Fig. 2. Measured and CD simulated BTC's for Exp. I-1 with R optimized or fixed at 1.05.

1.2 Expt. I-3 1

q = 2 . 7 1 cm/d Measured

0

°

_?-, 0.8

~

S

~

~

cD p___.__,

..... ,,.o 1.12 - -

4.6

1 . 0 5 (fixed)

,"

o. 6

~

data p o r t s

0.4

0 I.<

,

0.2

¢

0

~

0

~

2

4

6

8

PORE VOLUMES Fig. 3. Measured and CD simulated B T C ' s for Exp. I-3 with R optimized or fixed at 1.05.

272

P.R. ANAMOSAET AL.

clet number, P were allowed to vary. The low retardation factor, R = 0.74, estimated for the most rapid flux (Exp. I-l) implies exclusion of tritium from some regions of the soil. Since the retardation coefficient was measured (R = 1.05 ), the model-estimated lower value is an indication of immobile-water regions that were not in physical equilibrium with the mobile effluent, due to the short residence time of the pulse in the soil. The CD model, which considers all soil water to be mobile, was unable to simulate the observed BTC of Exp. I-l, when the value of R was fixed at 1.05 {Fig. 2). As the experimental flux was slowed, the CD-estimated retardation factor approached the measured value and the CD model was able to stimulate the observed BTC's (Fig. 3 ). At the slower flux, the pulse resided in the column long enough to allow diffusion to bring the mobile and immobile regions closer to physical equilibrium. Thus, at slow flux (2.71 c m / d or less), the conceptual assumption of the CD model that all water in the porous medium is in physical equilibrium, is satisfied.

MIM model analysis The dimensionless parameters estimated by the MIM model for the four displacement experiments through Column I are presented in Table VI. The retardation factor for all trials was held constant at R = 1.05 and the parameters P, fl, and eo were optimized during each initial curve-fitting process. The MIM model simulations provided very close agreement with observed BTC's for all four experiments from Column I. Even with R held constant at the experimentally determined value of 1.05, the MIM model showed close agreement with observed BTC's at both the fastest and slowest fluxes (Fig. 4 and 5). T A B L E VI M I M water model optimized dimensionless parameters Experiment no.

Flux, q cm/d

I-1

111

P

R fixed 2.9

1.05

(0.6) I-4

36.7

I-2

16.8

2.7 (0.7) 5.8

1.05 1.05

(1.5) I-3

2.71

6.2 (1.4)

1.05

Numbers in parentheses are the 95% confidence intervals ( _+ ).

fl

w

0.53

0.20

(o.04)

(0.05)

0.58 (0.07) 0.61

0.30 (0.07) 0.38

(0.05)

(o.o8)

0.62 (0.07)

2.5 (1.2)

WATERMOVEMENTTHROUGHOXISOLFROMCAMEROON A o

273

1.2

0

Expt. I-1 1

q - 111cm/d

|

izZi 0

0.6

8~,

0.4

~

0 Measureddata points

10501530.20

P

0.2

0 0

2

4

6

8

PORE VOLUMES Fig. 4. Measured and MIM simulated BTC's for exp. I-1 with R fixed at 1.05.

1.2 o 0 0

Expt. I-3 1

q - 2.71 cm/d

Z

o ~< nr I-Z W 0 Z 0 0 uJ

0.6

I-
0.2

C/~

0.8

L~

0

Measured data points

0.4

_>

O( 0

)

L , ~ 2

4

6

'

8

PORE VOLUMES Fig. 5. Measured and MIM simulated BTC's for Exp. I-3 with R fixed at 1.05.

274

P.R. ANAMOSAET AL.

Mobile/immobile water The mobile water partition coefficient, fl, represents the fraction of solute present in the mobile region under equilibrium conditions. Although fl is generally considered a constant for any given soil sample, in this study it showed a slight increase as the flux decreased. This behavior is attributed to the inability of the model to distinguish between the mobile and immobile regions when the flux is slow enough to allow considerable diffusion between the two regions. This implies that the best estimate of fl is when the flux is infinitely fast. Since Exp. I-l, conducted at the fastest flux, exhibited the highest degree of physical non-equilibrium (CD model analysis), its MIM model analysis should yield the best estimate of ft. Therefore, the BTC's were refitted to the MIM model holding fl constant at 0.53 (Table VII). The parameter fl is used to calculate the mobile-water fraction, 0, by

O=Om/O= f l R - f ( R - 1 )

[13] where f is the fraction of the total adsorption sites in the mobile-water region. The parameter/is typically approximated. Nkedi-Kizza et al. (1983) proposed equal distribution of the adsorption sites between the two regions such that f= fl and, therefore, ~ = ft. Seyfried and Rao (1987) proposed an intermediate approximation of f= ~/2. Nkedi-Kizza et al. (1982) proposed that, since the absorbing surface area associated with a unit volume of water in the small pores of the immobile region is probably much greater than the surface area associated with the same unit volume of water in the mobile region, [ may be approximated to be zero. In all approximations of f the severity of any error on the eventual estimation of the mobile water content is influenced by the value of R. If there is almost no chemical adsorption or repulsion (R approaches 1.0), then the location of the sites becomes less important, because the value fiR - F (R - 1 ) approaches fl and, therefore, ~ = ft. In this study, fl= 0.53 will be used as the value to approximate ¢ since R is T A B L E VII M I M water model optimized dimensionless parameters with R and fl fixed Experiment no.

Flux, q (cm/d)

P

R fixed

fl fixed

o)

I-1

111

2.94 (0.55) 3.18 (0.24) 9.28 (1.32) 8.13 (3.52)

1.05

0.53

1.05

0.53

1.05

0.53

1.05

0.53

0.198 (0.052) 0.342 (0.032) 0.510 (0.036) 2.80 (1.63)

I-4

36.7

I-2

16.8

I-3

2.71

Numbers in parentheses are 95% confidence intervals ( + )

WATER MOVEMENT THROUGH OXISOL FROM CAMEROON

275

very close to 1.0. The immobile water fraction of 0.47 cannot be totally attributed to the intra-gravel porosity. Since the volumetric gravel content (including intra-gravel porosity) of the column was 0.375 cm3/cm 3, with 20% of that being interior porosity, the intra-gravel porosity was only 0.075 cm3/cm 3 or 14% of the total porosity of 0.526 cm3/cm 3. Even if the intra-gravel porosity contains only immobile water, the remaining immobile-water fraction (0.40) of the volumetric-water content was associated with the aggregated fine-earth fraction of the soil. Although the fine-earth fraction of the Ap and Ac horizons has a weak crumb structure, the Btc horizon has medium sized, moderately strong aggregates. Nkedi-Kizza et al. (1983) have shown that packed columns of sieved (2-4.7 ram), strongly aggregated peds from an Oxisol harbored over 50% of the total volumetric-water content in immobile regions. Schulin et al. (1987) found fl= 0.85 in a Mollisol with 55% gravel by volume. Back-calculation of their data indicates that the gravel was not porous. The total soil porosity (0.255 cm3/cm 3) was associated entirely with the 20% fine fraction by volume. Therefore, the difference in volumes of the mobile-water regions of these two gravelly soils is more likely due to differences in aggregate structure of the fine fraction than to gravel porosity.

Estimation of the dispersion coefficient and dispersivity The Peclet number relatesthe soil-column length and pore-water velocity to the dispersion coefficient (Eq. 10). One theoretical relationshipbetween pore-water velocityand the dispersion coefficientis given by:

Dm=kv~

[14]

where ~ is the soil dispersivity and n is an empirical constant (Van Genuchten and Wierenga, 1986). The dispersivities of different soils are more easily compared if the empirical constant, n, is assumed to be 1.0 and the equation is thereby linear. Russo (1983) and Schulin et al. (1987) determined dispersivities of 2.24 and 2.91 cm from soils containing 55 and 43% gravel by volume, respectively, using the linear relationship. The Peclet numbers estimated from the BTC's of Column I tended to increase with decreasing flux, suggesting nonlinear relation between the dispersion coefficient and pore-water velocity within the velocity range used in this study (Fig. 6). The nonlinear plot provides a dispersivity of 3.3 c m 2 - n d n - 1 with n = 1.3, which is a dispersivity of similar magnitude to the two previously mentioned studies on stony soils. Several factors may be contributing to the high dispersivity of this soil. Dispersion increases as the range in small to large pore sizes of a soil increases, thereby providing a wide range of water velocities within a single soil sample. For most laboratory displacement experiments involving disturbed (repacked) soils, the value ofk is about 1.0 cm; however, for displacement experiments involving undisturbed field soils, especially when aggregated, the value

276

P.R. ANAMOSAET AL 1400O

&.. E

Dm = 3 . 2 9

V m 1" 3 3

12000 R2 = O. 9 6 .

E

10000

i-:

Z IJJ

0 0 Z

R

6°°°

4°°0

o

Q 100

,

200

~ I ~ L' 300

400

i

5OO

MOBILE PORE WATER VELOCITY, Vm (cm/d) Fig. 6. Relationship between MIM estimated dispersion coefficient, Din, and mobile pore water velocity, vm.

0.6 E o '~" co

O. 5 (

E

r 2 ,, O. 9 9 8 * *

o

Gb Z ILl I--

= O. 5 2 6 - 8 . 2 0 x lO-21og(T)

0.4

0.3

0 n~

I.u I-

0.2

.j

0.1

0

CO 0

1~

2~

3~

4~

SOIL WATER TENSION, T (mbar) Fig. 7. Soil moisture release curve.

15000

WATER

MOVEMENT

THROUGH

OXISOL

FROM

277

CAMEROON

of;L may be one to two orders of magnitude higher (Van Genuchten and Wierenga, 1986). Edwards et al. (1984) have shown that the presence of non-porous gravel increases the total macropore volume at the expense of the micropore volume. The large reduction in the water content of soil under slight tensions (0-50 mbar) indicated that the soil possesses a considerable volume of large pores (Fig. 7). similarly, the retention of nearly 33% of the total soil water at 15 bars of tension indicates that the soil also contains a large volume of very small pores.

Estimation of the diffusive mass-transfer coefficient The dimensionless, mass-transfer coefficient, o), relates the first-order masstransfer coefficient, ~, to the solution flux and column length (Eq. 11 ). The first-order, mass-transfer coefficient exhibits a slight increase with solution flux for the data obtained from experiments on Column I (Fig. 8), which is consistent with other theoretical and experimental observations (Rao et al., 1980a,b). The mathematical description of the diffusion process employed by the MIM model has an underlying assumption of first-order exchange kinetics. However, conceptually the assumption is only valid for dead-end pores with a neck of negligible volume ( Coats and smith, 1964). Van Genuchten and Dalton (1986) have shown that first-order kinetics represents a very close approxi-

0.4 a = 2. Ox 10-3 (q) + 8 . 7 x 10 -2

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FLUX, q (cm/d) Fig. 8. Relationship between MIM estimated mass transfer coefficient, ~, and flux, q.

278

P.R. ANAMOSAET AL.

mation in the case of radial diffusive exchange between the soil matrix and hollow cylindrical macropores, but for other pore geometries, first-order exchange only a crude approximation. This is because the mass-transfer coefficient is a lumped parameter, which depends not only on the pore-space geometry, solute diffusivity and the magnitude of the immobile region, but also on the changing solute concentration within the two regions. Column H parameter estimation

Additional evidence of the validity of derived soil-water parameters lies in their transferability to a different sample of the same soil. Model-simulated BTC parameters derived from experiments using Column I were applied to the experimental data from Column II (Figs. 9 and 10). Values for R and fl were fixed at 1.05 and 0.53, respectively, and the values for P and co were determined from the curvilinear and linear relationships of Fig. 6 and 8. The derivations included consideration of slight differences in column lengths and bulk densities (Table III).The simulated BTC's based on the parameters derived from Column I exhibit a slightly later break through and a higher peak than the experimentally observed BTC's. The differences between the estimated and observed BTC's could be due to natural variability between the soil samples. The bulk density and porosity of Column II were slightly larger than those of Column I (Table III). Although the two columns contained nearly identical 1.2 Expt. I - 1

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, 8

WATERMOVEMENTTHROUGHOXISOLFROMCAMEROON

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Fig. 10. Measured and MIM simulated BTC's for Exp. II-1. volumes of gravel, the particle density of the gravel in Column II was higher. Since the more dense gravel has less porosity (Table II), less of the total porosity of Column II is associated with the gravel and a greater portion is associated with the remaining fine earth-fraction, where larger pores probably predominate. However, considering that all model parameters were independently estimated, the MIM model does a good job of describing the asymmetrical BTC's. CONCLUSION The data from this study show that this Oxisol, which contains a strongly aggregated fine fraction and porous gravel, produced asymmetrical BTC's for tritiated water. The degree of asymmetry increased with increasing flow rates. The classical CD model was found inadequate in describing water movement in this soil, due to the inability of the model to account for diffusive mass transfer of water into stagnant or immobile water regions. The MIM model adequately described water movement at all flow rates. The model estimated that about 50% of the total water content was in immobile regions. The high immobile water content and the relatively large dispersivity indicate that, under natural field conditions of short but intense tropical rain storms, water transport in the larger soil pores could carry small amounts of unadsorbed solutes beyond the root zone, while considerable quantities of the solute remain

280

P.R. ANAMOSAET AL.

relatively unaffected, harbored in immobile-water regions. Although this could cause pollution of ground-water from nutrient and pesticides leaching through macropores, the presence of immobile-water regions in this soil will act as a source/sink for solutes that will be slowly released to crops. REFERENCES Amouric, M., Baronnet, A., Nahon, D. and Didier, P., 1986. Electron microscopic investigations of iron oxyhydroxides and accompanying phases in lateritic iron-crust pisolites. Clays and Clay Miner., 34: 45-52. Babalola, 0., and Lar, R., 1977a. Subsoil gravel horizon and maize root growth: I. Gravel concentration and bulk density effects. Plant Soil, 46: 337-346. Babalola, O. and Lal, R., 1977b. Subsoil gravel horizon and maize root growth: III. Effects of gravel size, inter-gravel texture, and natural gravel horizon. Plant Soil, 46: 347-357. Coats, K.H. and Smith, B.D., 1964. Dead-end pore volume and dispersion in porous media. Soc. Petr. Eng. J., 4: 73-84. Collinet, J., 1969. Contribution ~ l'~tude des "stone-lines" dans la r~gion du Moyen-Ogoou~ (Gabon). Cah. ORSTOM, S~r. P~doi., VII: 3-42. Danielson, R.E. and Sutherland, P.L., 1986. Porosity. In: A. Klute (Editor) Methods of soil analysis. Part 1.2nd. ed. Agronomy, 9: 443-462. Dao, T.H. and Lavy, T.L., 1978. Extraction of soil solution using a simple centrifugation method for pesticide adsorption-desorption studies. Soil Sci. Soc. Am. J., 42: 375-377. Davidson, J.M., Rao, P.S.C. and Nkedi-Kizza, P., 1983. Physical processes influencing water and solute transport in soils. In: D.W. Nelson, K.K. Tanji and D.E. Elrick (Editors), Chemical Mobility and Reactivity in Soils Systems. Am. Soc. Agron., Madison, WI, pp. 35-47. Dijkerman, J.C. and Miedema, R., 1988. An Ustalt-Aquult-Tropept catena in Sierra Leone, West Africa, I. Characteristics, genesis and classification. Geoderma, 42: 1-28. Edwards, W.M., Germann, P.F., Owens, L.B. and Amerman, C.R., 1984. Watershed studies of factors influencing infiltration, runoff, and erosion on stony and non-stony soils. In: J.D. Nichols, P.L. Brown and W.J. Grant (Editors), Erosion and productivity of soils containing rock fragments. Soil Sci. Soc. Am. Spec. Publ., 13. ASA, SSSA, CSA, Madison, WI, pp. 45-54. Fairbridge, R.W. and Finkl, C.W., 1984. Tropical stonelines and podzolized sand plains as paleoclimatic indicators for weathered crations. Quat. Sci. Rev., 3: 41-77. Fauck, R., 1963. The sub-group of leached ferruginous tropical soils with concretions. Afr. Soils, 8: 407-430. Foale, M.A. and Upchurch, D.R., 1982. Soil coring method for sites with restricted access. Agron. J., 74: 761-763. L~v~que, A., 1969. Le probl~me des soils a nappes de gravats: Observations et r~flexions pr~liminaires pour le socle granitogneissique au Togo. Cah. ORSTOM, S~r. P~dol., VII: 43-69. Muller, J.P. and Bocquier, G., 1986. Dissolution of kaolinites and accumulation of iron oxides in lateritic-ferruginous nodules: Mineralogical and microstructural transformations. Geoderma, 37: 113-163. Nkedi-Kizza, P., Biggar, J.W. van Genuchten, Th.M., Wierenga, P.J., Selim, H.M., Davidson, J.M. and Nielsen, D.R., 1983. Modeling tritium and chloride 36 transport through an aggregated Oxisol. Water Resour. Res., 19: 691-700. Nkedi-Kizza, P., Rao, P.S.C., Jessup, R.E. and Davidson, J.M., 1982. Ion exchange and diffusive mass transfer during miscible displacement through an aggregated Oxisol. Soil. Sci. Soc. Am. J., 46: 471-476. Oilier, C.D., 1959. A two-cycle theory of tropical pedology. J. Soil Sci., 10: 137-167.

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Passioura, J.B., 1971. Hydrodynamic dispersion in aggregated media: 1. Theory. Soil Sci., 111: 339-344. Rao, R.S.C., Jessup, R.E., Rolston, D.E., Davidson, J.M. and Kilcrease, D.P., 1980a. Experimental and mathematical description of nonadsorbed solute transfer by diffusion in spherical aggregates. Soil Sci. Soc. Am. J., 44: 684-688. Rao, P.S.C., Rolston, D.E., Jessup, R.E. and Davidson, J.M., 1980b. Solute transport in aggregated porous media: Theoretical and experimental evaluation. Soil Sci. Soc. Am. J., 44: 1139-1146. Riquier, J., 1969. Contribution ~ l'~tude des "stone-lines" en r~gions tropicale et ~quatoriale. Cah. ORSTOM Sdr. P~dol., VII: 71-111. Russo, D., 19983. Leaching characteristics of a stony desert soil. Soil Sci. Soc. Am., J., 47: 431438. Sanchez, P.A., Bandy, D.E., ViUachica, J.H. and Nicholaides, J.J., 1982. Amazon soils: Management for continuous crop production. Science, 216: 821-827. Schulin, R., Wierenga, P.J., Fliihler, H. and Leuenberger, J., 1987. Solute transport through a stony soil. Soil Sci. Soc. Am. J., 51: 36-42. S~galen, P., 1969. Le remaniement des sols et la mise en place de la stone-line en Afrique. Cah. ORSTOM. S~r. P~dol., VII: 113-131. Seyfried, M.S. and Rao, P.S.C., 1987. Solute transport in undisturbed columns o an aggregated tropical soil: Preferential flow effects. Soil Sci. Soc. Am. J. 51: 1434-1444. Smyth, A.J. and Montgomery, R.F., 1962. Soils and land use in Central Western Nigeria. Govt. Printer, Ibadan, Nigeria. Stoops, G., 1968. Micromorphology of some characteristic soils of the lower Congo (Kinshasa). Pedologie, XVIII: 110-149. Valocchi, A.J., 1985. Validity of the local equilibrium assumption for modeling sorbing solute transport through homogeneous soils. Water Resour. Res., 21: 808-820. Van Genuchten, M.T., 1981. Non-equilibrium solute transport parameters from miscible displacement experiments. Res. Rep. 119, U.S. Salinity Lab. Dept. Soil Environ. Sci., Univ. of Calif., Riverside. Van Genuchten, M.T. and Dalton, F.N., 1986. Models for simulating salt movement in aggregated field soils. Geoderma, 38: 165-183. Van Genuchten, M.T. and Parker, J.C., 1984. Boundary conditions for displacement experiments through short laboratory columns. Soil Sci. Soc. Am. J., 48: 703-708. Van Genuchten, M.T. and Wierenga, P.J., 1976. Mass transfer studies in sorbing porous media: I. Analytical solutions. Soil Sci. Soc. Am. J., 40: 473-480. Van Genuchten, M.T and Wierenga, P.J., 1977. Mass transfer studies in sorbing porous media: II. Experimental evaluation with tritium (3H20). Soil Sci. Soc. Am. J., 41: 272-278. Van Genuchten, M.T. and Wierenga, P.J., 1986. Solute dispersion coefficient and retardation factors. In: A. Klute (Editor), Methods of soil analysis. Part 1 and 2nd ed. Agronomy, 9: 10251054. Vine, R.N. and Lal, R., 1981. The influence of sands and gravels on root growth of maize seedling. Soil Sci., 131: 124-129.