الفهرس 
Material and methodsOnly 14 pages are availabe for public view
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Abstract
To study the moisture characteristics of some soiJIs in Kaliobia
governorate, twenty soil profiles were selected from governorate soils to
represent the different geomorphological units, .namely., natural levee,
sedimentary basin, river terrace, overlapping and saline soils. The field
morphological description as well as chemical and physical measurements
were carried out using undisturbed and disturbed soil samples.
The soil chemical analysis show that the soils under investigation
are generally neutral to slightly alkaline. The soils are generally non saline
with one exceptional cases which represent some patches of saline soils.
The data of soluble salts show that calcium and sodium are the
dominant soluble cations while the sulphates and chlorides are the
dominant soluble anions.
The cation exchange capacity of the investigated soils are widely
different and mainly related to soil texture. The data show that each
landform type is characterized by a special type of sedimentation and
therefore the particle size distribution diners quite considerably.
The organic matter content of the investigated soils is generally low
with one exceptional case of El-Gabal El-Asfar soils which exhibit
relatively high content of organic matter. Also the soils under
consideration exhibit low content of carbonates with a maximum value of
6.0%.
The aggregate states of the investigated soils are proportionally
related to exchangeable calcium and magnesium, clay, and silt fractions
and inversely related to tine and coarse sand tract ions. Regression
equation is:
A.S.= - 16.7431-0.6156 ESP + 1.3055 clay, with multiple R= 0.92.
Also the mean weight diameter is affected by thc same soil properties
affect the aggregate state, unless the effect of organic matter content on the
mean weight diameter is dependent on the clay content .Thc multiple
regression equation is :
M.W.D =- 0.4923 + 0.0546 ECa, with multiple R ~-~0.82
The soil bulk density shows negative and significant correlations
with clay; silt; carbonate; and organic matter content. The multiple
regression Equation is :
B.D = 1.3636-0.0343 a.M. + 0.0058 C.S., with multiple R= 0.9
The soil porosity is positively or negatively related to many soil
properties. However, only exchangeable calcium, sodium adsorption ratio
(SAR), organic matter content (O.M.), silt + clay; and tine sand are
considered for multiple regression. The relationship can be summerized :
TP. = 27.9136 + 0.2658 ECa + 0.4498 SAR -+- 0.9694 OM
+ 0.2266 Si + Cl + 0.1330 F.S.; with multiple R = 0.95
The pore size are classified to four categories, .narnely., quickly
drainable, slowly drainable, water holding and fine capillary pores ~?~on
useful pores. The data show that the quickly drainable pores are mainly
affected by soil texture and to considerable extent by aggregate state and
organic matter content. However only two variables are considered tor
stepwise regression, namely, aggregate state and fine and coarse sand
fractions to provide the following equation:
Q.D.P. = 1.7176 + 0.0622 A.S. + 0.1535 (C.S.+F.S.),
with multiple R = 0.73
However, another variables of exchangeable calcium, carbonate and
silt + clay content are considered for slowly drainable pores. The
regression equation can be written as :
S.D.P. ~ 9.0763 -I- O.I048 ECa + 0.3506 CaC03 - 0.1113 (Si. Cl)
with multiple R = 0.75
The results show that the water holding pores (W.H.P.) are mainly
affected by organic matter content and partially by soil texture. The effect
of soil texture is more evident in the subsurface and deeper layers which
have less organic matter content. The multiple regression describes this
relation in the following equation :
W.H.P. = 12.048 + 0.2683 ECa + 0.9072 OM. - 0.1086 C.S., R = 0.91
The non useful pores (N.D.P.) are mainly affected by soil texture as well
as exchangeable cations. The multiple regression equation may formulated
as: N.U.P. = - 0.7592 + 0.1938 EMg I· 0.8435 ENa I 0.701 (Si I CI)
+ 6.0602 F.S., with multiple R’ 0.96
The moisture retention curves of the investigated soils show that the
amount of water retained at relatively low matric suction depends
primarily upon the capillary effect and the pore-size distribution. On the
other hand , water retained at high suction range is due increasingly to
adsorption and is thus influenced less by the pore-size distribution and
more by the texture and specific surface of the soil material. As generally,
the fine-textured soils exhibit greater water retention at any given suction
and more gradual the slope of the curves. On the other hand, the coarse
textured soils exhibit less water retention and more sharp and distinct
curves.
The results show that the values of soil moisture content at field
capacity and wilting point are mainly related to the soil texture and soil
salinity. Since the retained water at field capacity occupies two different
types of soil porosity, ”namely” water holding and non useful pores, its
value is mainly affected by the distribution pattern of the two types of
porosity. The statistical analysis show many significant correlation
between field capacity and soil components, unless only two them are
considered for the step wise regression, .namely, silt + Clay and
exchangeable sodium. The regression equation can be summerized as :
F.C. = 6.3081 + 0.5494 ENa + 0.5201 (Si + CI), with multiple R= 0.95
The available water is mainly affected by both soil texture and organic
matter content and partially by salt contents.
One of the most soil properties related to saturated hydraulic
conductivity is the particle size distribution. The coarser textured soils are,
in the same time, the faster factors such as compaction and salinity are
subsidiary affect the saturated hydraulic conductivity. The relationship
between different soil properties and saturated hydraulic conductivity
(K
sat
) is statistically studied and provided the following multiple
regression equation:
Ksat = 9.0730 - 6.7031 OM + 1.5952 C.S., with multiple R = 0.84
The Van Genuchten equation reduced to four parameters, .namcly.O
s, er , a and n, is used to predict the moisture retention characteristic of
the soils under consideration. Principal factor analysis was used to reveal
the structure in the data and to examine the relation between moisture
retention characteristic (MRC) parameters and selected measured soil
properties, .namely, bulk density, organic carbon, silt, clay, and mean
weight diameter. Regression equations arc established between these
MRC parameters and measured soil properties. It may be conclude that the
moisture retention characteristic (MRC) can be estimated at a reasonable
level of accuracy from simple soil properties such those mentioned above.
The study further shows that for the prospected horizons the Van
Genuchten model gives a good description over the entire range of the
MRC.
Finally the data show that the transition from saturation to
unsaturation water flow entails a steep DROP in hydraulic conductivity. The
decrease in hydraulic conductivity is steeper for coarse textured soils than
the fine textured ones.