Aggregate Stability

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AGGREGATE STABILITY OF SOME COASTAL ISLAND SOILS

OF BANGLADESH

A. Begum, S.M.F. Rabbi, M.S. Amin* S.L. Rahaman and M. Hasan

Soil Science Discipline, Khulna University

* Corresponding Author([email protected])

ABSTRACT

A study was conducted to evaluate the aggregate stability of some coastal soils of

Bangladesh. Representative Soils were collected from seven char lands of

Bauphal thana under Patuakhali district. The mean weight diameter (MWD) and

water stable aggregates (WSA) varied from 0.02-0.39 mm and 0.35-4.15 mm,

respectively and the highest value was found in Char Diara Kachua(1). The water

stable aggregate (WSA) at >2mm was high in Char Miazan and at >1mm was high

in Char Diara Kachua(1). State of aggregation and degree of aggregation varied

from 0.0 - 8 % and 0.0 - 9.09%, respectively.

Key words: Mean weight diameter, Water stable aggregates

Running title: Water stability of aggregates

INTRODUCTION

Soil aggregate stability is a frequently used indicator of soil quality (Nichols and

Toro, 2011). Soil organic matter levels, soil biological activity, and soil functions

(like water infiltration, water holding-capacity, aeration, and nutrient

availability) are related to soil aggregation (Six et al., 2004). Soil structure is akey factor in the functioning of soil, its ability to support plant and animal life,

and moderate environmental quality with particular emphasis on soil carbon (C)

sequestration and water quality. Aggregate stability is an indicator of soil

structure (Six et al., 2000a). Aggregation results from the rearrangement of

particles, flocculation and cementation (Duiker et al., 2003). Aggregation is

mediated by soil organic carbon (SOC), biota, ionic bridging, clay and carbonates.

Soil aggregates are held together by various organic and inorganic materials and

through several mechanisms (Denef and Six, 2005).
mailto:[email protected]:[email protected]:[email protected]:[email protected]


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Aggregate stability is a measure of aggregate's resistance to breakdown, usually

measured by sieving in water. It is an important soil property due to its role on

soil erosion rate and hydraulic characteristics such as infiltration rate. Aggregate

stability is affected by soil texture, organic matter content, composition of soilsolution, and composition of exchangeable cations (Robinson and Page 1950).

Soils that have a high percentage of silt often show lower aggregate stability. The

mean weight diameter (MWD) is an index that characterizes the structure of the

whole soil by integrating the aggregate size class distribution into one number.

The MWD has often been used to indicate the effect of different management

practices on soil structure (Angers et al., 1993).

About 80% soils of Bangladesh are Inceptisols developed on older and active

floodplains. The soils are structurally immature and have distinct flood coating

on ped faces. The work on aggregate size distribution of Bangladesh soils is

rather scanty. Joshua and Rahman (1983) documented their pioneering work on

aggregate stability of soils of Bangladesh. Rabbi et al. (2004) evaluated the

aggregate stability of Bajoa, Ramgati and Barisal series and factors affecting their

stability. The objective of the present research work was to determine the

aggregate stability of some soils of coastal charlands of Bangladesh.

MATERIALS AND METHODS

Soils were collected from seven char lands at Bauphal thana under Patuakhali

district on depth basis of 0-15cm, 15-30cm and >30cm and were placed in

cellophane bags. The soils were then air dried and prepared for analysis. The

particle size analysis of the soils was carried out by combination of sieving and

hydrometer method as described by Gee and Bauder (1986). Textural classes

were determined using Marshalls Triangular co-ordinate system. Particle

density was determined by pycnometer as described by Black (1965). Bulk

density of soils was determined by Pigulevskii (1936). The soil porosity was

calculated from bulk and particle density. State of aggregation and degree of

aggregation were calculated as suggested by Baver and Rhades (1932). Saturated

hydraulic conductivity of soils was determined in the laboratory by constant

head method (Klute, 1965). Soil pH (1:2.5) was determined using of glass

electrode pH meter as suggested by Jackson (1973). The electrical conductivity


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(1:1) of soil was determined by EC meter (USDA, 2004). Soil organic carbon was

determined by wet oxidation method as described by Jackson (1973).

In aggregate sieving analysis the aggregates passed through 8mm sieve but

retained on 2mm sieve were used. Wet sieving analysis were performed as

described by Jalota et al. (1998). The mean weight diameter (MWD) of the

aggregates was calculated by the following formula (Van Bavel, 1949):

MWD =

n

i

XiWi

1

where Xi is the mean diameter of any particular size range of

aggregates separated by sieving and Wi is the weight of aggregates in that size

range as a fraction of the total dry weight of the sample analyzed. The percentage

of aggregates water stable aggregates was calculated by the following formula:

%WSA =Sample retained on the specific sieve

Total sample analyzed100

The percentage of aggregates retained on each sieve was corrected for the

primary particles as described by Kemper (1965).

RESULTS AND DISCUSSION

Particle size distribution

Percentage of sand of the studied soils varied from 8-24. The highest sand

percentage was obtained at 0-15 cm depth in soil developed on Char Kachua and

that of the lowest was at >30 cm depth on Char Barret (Table 1). The variation of

percentage of sand of soils developed on different Chars was not statistically

significant. The percentage of silt varied from 65-79. The highest value obtained

at 15-30 cm depth in soils developed on Char Miazan and the lowest value was at

0-10 cm depth on Char Daira Kachua (1) (Table 1). Percentage of clay of studied

soils varied from 10 to 18. The highest value obtained at >30 cm depth in soil

developed on Char Barret and the lowest value was at various depth (Table 1).

Similar textural variation among the depth in Bhola series was reported by SRDI

(2003).


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Bulk density

The bulk density of the studied soils varied from 1.29-1.66 g cm-3. The highest

bulk density obtained at >30 cm depth in soil developed on Char Ray Shaheb and

the lowest value was at 0-15 cm depth on Char Kachua (Table1). The bulk

density increased with increasing depth in soil developed on Char Ray Shaheb

but decreased with depth on Char Wadel and Char Diara Kuchua (1). Rabbi et al.

(2004) reported that the bulk density of coastal soil varied between 1.05-1.39 g

cm-3. Bulk density was bit high. It might be due self compaction of soils because

soils were fine, loose, highly graded in inhibited coastal pedogenic processes

(tidal effect, inundation, sedimentation etc.)

Particle density

The particle density of the studied soils varied from 2.27-2.63 g cm-3. The highest

particle density obtained at >30 cm depth in soil developed on Char Barret and

the lowest was at 15-30 cm depth on Char Wadel (Table 1). The particle density

decreased with increasing depth in soil developed on Char Ray Shaheb. The

particle density of soils developed on Char Miazan and Char Barret increased

with increasing depth. Rabbi et al. (2004)reported that the particle densities of

south western coastal soils varied from 2.38-2.83 g cm-3.

Percentage of porosity

Percentage of porosity of studied soils varied from 30.38-56.04%. The highest

porosity was obtained at >30 cm and the lowest porosity was at 0-15 cm depth

developed on Char Daira Kachua (1) (Table1). Rabbi et al. (2004) reported that

the porosity of some coastal silt loam soils varied between 47.50-56.40%.

State of aggregation

State of aggregation of the studied soils varied from 0.08.0 %. The highest value

of state of aggregation obtained at 15-30 cm depth in soils developed on Char

Daira Kachua (1) and the lowest was at the depth of >30 cm on both Char Ray

Shaheb and Char Miazan (Table1). Rabbi et al. (2004) reported that state of

aggregation of some coastal silt loam soils can vary between 1 -15%.


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Degree of aggregation

Degree of aggregation of the studied soils varied from 0.0-9.09 %. The highest

value obtained at 15-30 cm depth in soil developed on Char Daira Kachua (1) and

the lowest was at the depth of >30 cm on both Char Ray Shaheb and Char Miazan

(Table 1).

Saturated hydraulic conductivity

Saturated hydraulic conductivity of studied soils varied from 10.08-26.16 cm

day-1. The highest values of hydraulic conductivity were at 15-30 cm depth on

Char Daira Kachua (1 and 2) and the lowest value obtained at 0-15 cm depth in

soils developed on Char Daira Kachua (1) (Table 1). According to classification,

hydraulic conductivity (11.28-22.80) cm day-1 indicates slow to moderately slow.

Rabbi et al. (2004) reported that the saturated hydraulic conductivity of some

coastal silt loam soils varied between 1.16 to 9.50 cm day-1.

Mean weight diameter (MWD)

The wetting process usually causes considerable disruption of previously dried

aggregates. The size of the aggregates after this disruption is apparently an

important soil parameter. In the present investigation it was revealed that under

wet condition the aggregates were not stable (Table 2). The mean weight

diameter of studied soils varied from 0.02-0.39 mm. The highest mean weight

diameter obtained at 0-15 cm depth in soils developed on Char Daira Kachua (1).

Rabbi et al. (2004) and Ahsan and Rabbi (2006) reported that MWD of some

coastal silt loam soils can vary between 0.13-3.26 mm. According to Rabbi et al.

(2006), MWD of studied soils can be classified as a very weakly stable aggregate.

The attempt has been made to subdivide the MWDwet range into classes

depending on the stability of the aggregates (Le Bessonnais, 1996). The classes

are 5 to 3 mm for highly stable aggregates, 3 to 1 mm for moderately stable, 1 to

0.4 mm for weakly stable and


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Percent water stable aggregate (% WSA)

The %WSA of >2 mm diameter varied from 0-5.15 and >1 mm varied from 0.70-

4.35, respectively (Table 2). The %WSA increased with increasing depth. The

aggregates of the studied soils did not exhibit high water stability. Soil at lower

depths in some cases exhibited higher water stability than the surface soils

(Table 2). During wet sieving most of the larger aggregates slaked and

distributed to the lower aggregate size ranges. Joshua and Rahman (1983) and

Rabbi et al. (2006) reported that soils of Gangetic alluvium were structurally

unstable.

Soil reaction (pH)

The pH of studied soils varied from 8.46-8.87. The highest pH was obtained at 0-

15 cm depth in soils developed on Char Wadel and the lowest was at depth of 15-

30 cm on Char Miazan (Table 1). In most of the soil profile, a trend of slightly

increasing pH with soil depth was observed. This is a common feature of the

seasonally flooded soils in Bangladesh (Brammer, 1971).

Electrical conductivity (EC)

The EC of studied soils varied from 0.45-4.12 dS m -1. The highest EC was

obtained at 15-30 cm depth in soils developed on Char Miazan and the lowest

was at various depth of studied soils (Table1). Salinity values in some coastal

plain soils of Bangladesh vary seasonally, peak salinities appear to be reached

during April-June and fall to a minimum around October before gradually raising

again (Hassan, 1984; Hossain and McConchie, 1994). According to SRDI (2003),

the salinity of studied area is very slightly saline to slightly saline soil. The

studied soils is non saline because of flowing heavy fresh water from up stream.

Soil organic matter (SOM)

The organic matter content of collected soil samples was found to vary from

0.89-3.16% with an average of 2.8% (Table 1) which indicated the lower amount

of organic matter. The higher percentages of organic matter content were

observed in Char Barret at 0-15 cm depth. Bhuiyan (1988) analyzed some

Bangladesh soils and found that the organic matter percent of different soil

series of Bangladesh ranged from 0.86-4.47, mean value being 1.89%, which are


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quite similar to our findings. Irrigation and drainage decreases the SOM content

of soil (Umeda and Yamada, 1980). SOM increases aggregate stability of soil by

lowering the wet ability and cohesion of the aggregates (Chenu et al., 2000). The

clay particles can bind the coarser soil constituents and organic matter (Hayes1991). Mokhtaruddin and Norhayati (1995) hypothesized that certain amounts

of very fine sand and silt particles are needed with clay to form and to stabilize

aggregates. Rabbi et al. (2004) reported that SOM, silt and clay percentage affect

the water stability of aggregates. SOM may be responsible for slaking resistance

of larger aggregates (Six et al., 2000b). In small aggregates, lower porosity and

higher bulk density may confer the resistance against slaking (Oades and Waters

1991). Thus the cementing effect of SOM is very important for stability of large

aggregates.


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Table 1. Different physical and chemical properties of studied soil

[SOM=Soil Organic Matter (%), Dp = Particle density (g cm-3)

; Db = Bulk density (g cm-3

); %P = % Porosity; Ks = Saturated hydraulic conductivity (cm day-1)

; EC = Electricalconductivity; SA = State of aggregation; DA =Degree of aggregation]

Sampling

Location

Depth

(cm)SOM

%

%Sand%Silt

%ClayTextural

Class

Dp

g cm-3

Db

g cm-3% P

Ks

cm day-1SA DA pH

EC

(dSm-1)

Char Wadel

0-15 3.16 13 77 10

Silt Loam

2.47 1.51 38.87 17.28 3.0 3.45 8.87 0.78

15-30 2.54 18 72 10 2.27 1.44 36.56 22.80 4.5 5.49 8.56 0.45

>30 2.20 17 73 10 2.33 1.34 42.49 21.60 4.0 4.82 8.49 0.45

Char Barret

0-15 2.39 16 74 10 2.56 1.47 42.58 19.44 6.0 7.14 8.70 0.45

15-30 1.38 13 77 10 2.63 1.31 50.57 17.76 2.0 2.30 8.66 0.45>30 2.48 8 74 18 2.62 1.47 47.87 12.0 5.0 5.43 8.78 0.45

Char Ray Shaheb 0-15 2.13 9 77 14 2.53 1.33 50.19 12.24 6.0 6.59 8.75 0.78

15-30 2.34 11 77 12 2.55 1.55 39.22 11.28 2.0 2.25 8.59 0.45

>30 2.40 16 69 15 2.53 1.66 34.38 17.28 0.0 0.00 8.84 0.45

Char Miazan 0-15 2.40 14 69 17 2.44 1.58 35.25 11.76 4.0 4.65 8.79 0.45

15-30 2.48 11 79 10 2.46 1.65 32.93 14.64 7.0 7.87 8.46 4.12

>30 1.72 17 73 10 2.54 1.42 44.09 15.60 0.0 0.00 8.61 1.78

Char Kachua 0-15 2.06 24 66 10 2.54 1.29 49.21 18.96 0.0 0.00 8.49 0.45

15-30 0.89 14 73 13 2.57 1.65 35.79 17.28 2.0 2.73 8.69 0.45

Char Diara

Kachua(1)

0-15 2.27 24 65 11 2.37 1.65 30.38 10.08 0.0 0.00 8.66 0.45

15-30 1.38 12 73 15 2.41 1.55 35.68 26.16 8.0 9.09 8.66 0.78

>30 1.51 13 77 10 2.48 1.30 56.04 13.92 1.0 1.15 8.77 0.45

Char Diara

Kachua(2)

0-15 1.99 12 78 10 2.63 1.51 42.59 11.40 6.0 6.82 8.79 0.45

15-30 2.27 8 77 15 2.44 1.61 34.02 26.16 4.5 4.89 8.77 0.45

>30 2.61 14 76 10 2.46 1.44 41.46 9.84 3.0 3.49 8.84 0.78


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Table 2. Mean weight diameter and the percentage of water stable aggregate of

studied soils.

Sampling

Location

Depth

(cm) MWD (mm)

%WSA

>2 mm >1 mm

Char Wadel

0-15 0.07 0.26 1.78

15-30 0.24 3.29 3.19

>30 0.23 3.00 3.40

Mean 0.18 2.18 2.79

Char Barret

0-15 0.15 2.00 1.80

15-30 0.10 0.30 3.84

>30 0.20 3.20 1.20

Mean 0.15 1.83 2.28

Char Ray Shaheb

0-15 0.04 0.00 0.70

15-30 0.12 0.70 1.90

>30 0.11 0.70 3.10

Mean 0.09 0.47 1.90

Char Miazan

0-15 0.02 0.00 0.70

15-30 0.24 2.98 2.98

>30 0.29 4.50 2.40

Mean 0.18 2.49 2.03

Char Kachua

0-15 0.09 0.36 1.65

15-30 0.02 0.00 0.59

Mean 0.06 0.18 1.12

Char Diara

Kachua(1)

0-15 0.39 5.15 3.15

15-30 0.20 1.61 4.35

>30 0.07 0.39 1.63

Mean 0.22 2.38 3.04

CharDiaraKachua(2)

0-15 0.03 0.12 0.85

15-30 0.10 0.82 1.17

>30 0.09 0.97 2.08

Mean 0.07 0.64 1.37


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Table 3. Correlation between MWD and other soil physical properties

MWD Dp Db % f Ks Sand Silt

Dp -0.231

0.470

Db -0.071 -0.076

0.827 0.814

% f -0.154 0.874 -0.542

0.632 0.000 0.069

Ks 0.409 -0.622 -0.290 -0.359

0.187 0.031 0.360 0.252

Sand 0.357 -0.672 -0.047 -0.503 0.778

0.255 0.017 0.885 0.095 0.003

Silt 0.028 0.436 -0.218 0.480 -0.197 -0.571

0.932 0.156 0.495 0.114 0.539 0.052

Clay -0.419 0.267 0.285 0.035 -0.638 -0.480 -0.446

0.175 0.402 0.370 0.913 0.026 0.115 0.146

Cell contents: Pearson correlation

P- Value

The MWD of soils had positive correlation (Table 3) with percent sand and silt of

soil. Rabbi et al. (2004) reported that MWD was directly influenced by percentage of

silt, clay and soil organic matter. Soils with high clay and low silt percentage had

higher MWD.

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