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Universit.'iMicrc5films
International300 N. Zeeb RoadAnn Arbor, MI48106
8429309
Mapa, Ranjith Bandara
TEMPORAL VARIABILITY OF SOIL HYDRAULIC PROPERTIES SUBSEQUENTTO TILLAGE
University of Hawaii
UniversityMicrofilms
International 300 N. Zeeb Road, Ann Arbor, MI48106
PH.D. 1984
TEMPORAL VARIABILITY OF SOIL HYDRAULIC PROPERTIES
SUBSEQUENT TO TILLAGE
A DISSERTATION SUBMITTED TO THE GRADUATE DIVISION OF THEUNIVERSITY OF HAWAII IN PARTIAL FULFILLMENT
OF THE REQUIREMENTS FOR THE DEGREE OF
DOCTOR OF PHILOSOPHY
IN AGRONOMY AND SOIL SCIENCE
August 1984
By
Ranjith Bandara Mapa
Dissertation Committee
Richard E. Green, ChairmanPaul C. EkernL. Stephen Lau
Goro UeharaI-Pai Wu
iii
ACKNOWLEDGEMENTS
The financial support from the East-West Center,
which made this study possible, is gratefully
acknowledged.
The author takes great pleasure in acknowledging
the guidance and encouragement received from his major
advisor Dr. Richard E. Green. Appreciation is also
extended to Dr. S.-K. Chong of University of Southern
Illinois, Carbondale, for suppling the sorptivity device
and for his interest, and to Mr. Bruce Trangmar for his
help in earring out the geostatistical analysis. The
author wishes to express his appreciation to Mr. Lance
Santo of Hawaiian Sugar Planter's Association and to Mr.
Michael Furukawa of Oahu Sugar Company for their
assistance.
Finally, special appreciation is expressed to my
wife, Lalitha, for her assistance, understanding and
patience during this study.
ABSTRACT
computer simulation of water and solute
movement provides a means of optimizing water management
with less field experimentation. Reliable estimates of
soil hydraulic properties, which are the input parameters
in numerical simulation models, are diffucult to obtain
because of spatial and temporal variability. Spatial
variability has received much attention in recent years.
On the other hand little information is available on the
changes in soil hydraulic properties subsequent to
tillage.
Temporal variability of five soil physical
properties for two soils, Molokai series (Typic Torrox)
and Waialua series (Vertic Haplustolls), were measured
under controlled field conditions. Properties of
particular interest were hydraulic conductivity as a
function of soil water content and suction, sorptivity,
water-content suction relationship, porosity and
macroporosity. All external compaction components such as
traffic, intercultivation and rainfall impact, that cause
temporal variability, were eliminated. Thus, changes in
hydraulic properties were imposed principally by internal
forces, that is, the changes in the pore water component
of effective stress resulting from wetting and drying. A
v
drip irrigation system provided controlled water
application at desired intervals. Soil water suction was
monitored during the drainage periods between irrigations.
Hydraulic conductivity near saturation was
the property which showed the greatest decrease with
wetting and drying following tillage. Sorptivity and soil
water retention also decreased significantly for both the
soils. The first and second wetting and drying cycles
caused the most compaction. Waialua soil showed greater
compaction than the Molokai soil perhaps due to the vertic
characteristics of the former.
The most promising simple measurement,
sorptivity with negative head, was further evaluated and
recommended as a rapid and inexpensive method to
characterize variability of soil hydrologic behavior
before other more demanding methods are undertaken.
The importance of temporal variability (from
wetting and drying) relative to spatial variability was
evaluated by comparing temporal changes in sorptivity
measured on small plots with spatial changes measured in a
large sugarcane field. Geostatistical analysis of the
field sorptivity data indicated no structure in the
variance with measured distances. The geometric mean and
standard deviation of log sorptivity were considered
sufficient to characterize the distribution. The
comparison of temporal and spatial variability showed that
vi
temporal variability may in some cases be of greater
consequence than spatial variability.
The importance of temporal variability of
hydraulic properties in modeling soil water movement was
further illustrated with a numerical simulation model
using K(8) and h(8) data for the Molokai and Waialua
soils. The computed water content profiles for
infiltration and redistribution showed considerable
differences for the pre-irrigation and post-irrigation
input functions. These results illustrate that modeling•soil water movement for the entire cropping cycle using
the parameters measured at only one stage may result in
unrealistic predictions for other parts of the cycle.
TABLE OF CONTENTS
ACKNOWLEDGEMENTS ••••••••••••••••••••••••••••••••••••• ii i
ABSTRACT ••••••••••••••••••••••••••••••••••••••••••••• iv
LIST OF TABLES ••••••••••••••••••••••••••••••••••••••• xi
LIST OF ILLUSTRATIONS •••••••••••••••••••••••••••••••• xiii
CHAPTER I. INTRODUCTION•••••••••••••••••••••••••••••• 1
OBJECTIVES................................ 5
REVIEW OF LITERATURE...................... 7
Importance of Tillage for Crop Production......... 7
Description of Tillage Practices.................. 8
Effect of Tillage on Soil Hydraulic Properties.... 10
Soil Structure ••••••••••••••••••••••••••• 10
Bulk Density and Porosity................ 11
Water Retention Characteristics •••••••••• 13
Infiltration and Hydraulic Conductivity 14
Changes of Soil Hydraulic Properties Subsequentto tillage ••••••••••••••••••••••••••••••••••••••• 16
Wetting and Drying Effects ••••••••••••••• 17
Compaction Effects ••••••••••••••••••••••• 21
Soil Water Retention •••••••••••••••••• 23
Infiltration and Hydraulic Conductivity 24
25..................Rainfall Impact Effects
Long Term Effect of Tillage and Landuse onSoil Hydraulic Properties •••••••••••••••••••••••• 28
CHAPTER 2.
viii
CHARACTERIZING TEMPORAL VARIABILITY OF SOILHYDRAULIC PROPERTIES SUBSEQUENT TOTILLAGE •••••••••••••••••••••••••••••••••••• 31
Introduction ••••••••••••••••••••••••••••••••••••••• 31
Methodology •.••.••••••.••....•......•....••.••• •.. •. 34
Description of Soils •••••••••••••••••••••••••••• 34
Selection of Treatment .......................... 35
Experimental Design and Procedure ••••••••••••••• 37
Experiment on Molokai Soil
Experiment on Waialua Soil
...................
...................37
41
Characterization of Soil Hydraulic PropertiesSubsequent to Tillage •••••••••••••••••••••••••••••• 44
Sorptivity by Infiltration with PositiveHead •••••••••••••••••••••••••••••••••••••••••••• 44
Materials and Methods · . 45
Results and Discussion ••••••••••••••••••••••• 47
Sorptivity by Infiltration with NegativeHead •••••••••••••••••••••••••••••••••••••••••••• 52
Materials and Methods · . 52
Results and Discussion ••••••••••••••••••••••• 56
Hydraulic Conductivity •••••••••••••••••••••••••• 65
Materials and Methods · . 65
Results and Discussion ••.•••••••••••••••••••• 71
Hydraulic Conductivity as a Functionof Soil Water Content ••••••••••••••••••••• 71
Hydraulic conductivity as a Functionof Soil Water Suction .•••••••••••••••••••• 75
Soil Water Retention •••••••••••••••••••••••••••• 91
Materials and Methods •••••••••••••••••••••••• 92
Results and Discussion ••••••••••••••••••••••• 94
Bulk Density and Porosity ••••••••••••••••••••••• 99
Materials and Methods ••••••••••••••••••••••• 100
Results and Discussion •••••••••••••••••••••• 100
Aggregate Size Distribution before Irrigation •• 105
Materials and Methods ••••••••••••••••••••••• 108
Results and Discussion •••••••••••••••••••••• 109
Conclusions ••••••.•••.•••••••••.••••••••••••••• 109
CHAPTER 3. SIMPLE SOIL MEASUREMENT METHODS APPROPRIATEFOR ASSESSING TEMPORAL VARIABILITy ••••••••• 114
Introduction •••••.•••••.••..••...•••••••••••••• 114
Rationale For Using Sorptivity Method •••••••••• 115
Sorptivity with Negative Head as a SimpleMeasurement Method for Assessing Variability ••• 117
Conclusions •••••••••••••••••••••••••••••••••••• 119
CHAPTER 4. TEMPORAL VARIABILITY OF SORPTIVITY INRELATION TO SPATIAL VARIABILITy •••••••••••• 121
Introduction
Methodology
Results and
.......................................................................Discussion ...•...•......••....•••.•
121
122
128
Comparison of Temporal and SpatialVariability of Sorptivity for Molokai Soil
x
138
Conclusions .................................... 139
CHAPTER 5. THE EFFECT OF TEMPORAL VARIABILITY ONSIMULATION OF SOIL WATER MOVEMENT •••• ...... 142
Methodology ••••••••••••••.•..••.••••••••••••••• 143
Results and Discussion ......................... 144
Conclusions .................................... 153
CHAPTER 6. GENERAL CONCLUSIONS ........................ 154
APPENDIX 1
APPENDIX 2
APPENDIX 3
APPENDIX 4
APPENDIX 5
·...........................................
·...........................................
·...........................................
·...........................................
·...........................................
156
161
164
175
182
LITERATURE CITED ..................................... 187
xi
LIST OF TABLES
Table Page
1 Calculated a and b values (Eq.2) forMolokai soil ••••••••••••••••••••.•••.•••••••••• 72
2 Calculated m and n values (Eq.3) forMolokai soil ••••••••••••••••••••••••••••••••••• 73
3 Calculated a,b (Eq.2) m and n values(Eq.3) for Waialua soil ••••••••••••••••••••••• 74
4 Equations relating hydraulic conductivityto soil water pressure head or volumetricwater content •••••••••••••••••••••••••••••••••• 8/
5 Parameters for 3 hydraulic conductivityequations fitted to K(h) and K(e) forMolokai soil. 0-5 cm depth ••••••••••••••••••••• 88
6 Parameters for 3 hydraulic conductivityequartions fitted to K(h) and K(e) forMolokai soil. 5-25 cm depth ••••••••••••••••••••• 89
7 Parameters for 3 hydraulic conductivityequations fitted to K(h) and K(B) forWaialua soil. 0-5 cm and 5-25 cm depths ••••••••• 90
8 Bulk density, porosity and macroporosityfor Molokai soil. 0-7.5 cm and 7.5-25 cmdepths ••.•.•••.•••.....•...••.••...•..•...••... 101
9 Bulk density, porosity and macroporosityfor Waialua soil. 0-7.5 cm and 7.5-25 cmdepths ••••••••••••••••••••••••••••••••••••••••• 102
xii
10 Results of Kolmogrov-Smirnov test for normalityof field measured sorptivity •••••••••••••••••• 134
11 Field measured sorptivity with negative head forMOlokai and Lahaina soils ••••••••••••••••••••• 136
12 Number of sorptivity with negative headmeasurements needed to estimate the meanwith specified probability level ••••••••••••••• 137
13 Sneg changes with four wetting and dryingcycles (temporal variability) compared withthe confidence intervals for Sneg measured ina sugarcane field (spatial variaoility).Molokai soil ••••••••••••••••••••••••••••••••••• 140
14 Input parameters Bl, B2, B3 and B4 calculatedusing field measured K(6)' and h (6) fucntionsfor MOlokai and Waialua soil •••••••••••••••••••• 145
Figure
1
2
3
4
5
6
7
8
9
xiii
LIST OF ILLUSTRATIONS
Page
A single replicate showing irrigation levelsas main plots and wetting and drying cyclesas subplots in split plot design. Experimentin MOlokai soil •••••••••••••••••••••••••••••••• 39
Measurement times of soil hydraulic propertieswith relation to tillage and irrigation ••••••••• 42
Schematic diagram of infiltration apparatusfor measuring sorptivity with positivehead (Spos) ••••••••••••••••••••••••••••••••••••• 46
Calculation of sorptivity by cumulativeinfiltration and square root time ••••••••••••••• 48
Sorptivity with positive head (Spos) withsucessive wetting and drying cycles, Molokaisoil. Geometric mean ± antilog of 1 SO of log S •• 49
Sorptivity with positive head (Spos) withsucessive wetting and drying cycles, Waialuasoil. Geometric mean± antilog of 1 SO of log S •• 51
Schematic diagram of device for measuringsorptivity with negative head (Sneg) •••••••••••• 53
Sorptivity with negative head (Sneg) withsucessive wetting and drying cycles, Molokaisoil. Geometric mean± antilog of 1 SO of log S •• 57
Sorptivity with negative head (Sneg) withsucessive wetting and drying cycles, Waialuasoil. Geometr ic mean ± antilog of 1 SO of log S •• 60
xiv
10 Sorptivity with positive head (Spos) andwith negative head (Sneg) with sucessivewetting and drying cycles, Molokai soil.Geometric means ••••••••••••••••••••••••••••••••• 62
11 Sorptivity with positive head (Spos) andwith negative head (Sneg) with sucessivewetting and drying cycles, Waialua soil.Geometric means ••••••••••••••••••••••••••••••••• 63
12 Hydraulic conductivity as a function of soilwater contenet, Molokai soil. 0-5 cm depth •••••• 76
13
14
15
16
Hydraulic conductivity as a function of soilwater content, Molokai soil. 0-25 cm depth • • • • • • 77
Hydraulic conductivity as a function of soilwater content, Waialua soil. 0-5 cm depth • ••••• 78
Hydraulic conductivity as a function of soilwater content, Waialua soil. 0-25 cm depth • ••••• 79
Hydraulic conductivity as a function of soilwater suction, Molokai soil. 0-5 cm depth ••••••• 81
17 Hydraulic conductivity as a function of soilwater suction, Molokai soil. 0-25 cm depth •••••• 82
18 Hydraulic conductivity as a function of soilwater suction, Waialua soil. 0-5 cm depth ••••••• 83
19 Hydraulic conductivity as a function of soilwater suction, Waialua soil. 0-25 cm depth •••••• 84
20 Soil water retention curve with sucessivewetting and drying cycles, Molokai soil.0-7.5 em depth •••••••••••••••••••••••••••••••••• 95
21 Soil water retention curve with sucessivewetting and drying cycles, Molokai soil.7.5-25 em depth •••••••••••••••••••••••••••••• 96
xv
22 Soil water retention curve with sucessivewetting and drying cycles, Waialua soil.0-7.5 em depth •••••••••..•...•••..•••••.•••••••• 97
23 Soil water retention curve with sucessivewetting and drying cycles, Waialua soil.7.5-25 em depth ••••••••••••...•••••.•••.••••.••• 98
24 Total porosity, microporosity andmacroporosity changes with sucessivewetting and drying cycles, Molokaisoil. 0-7.5 cm depth ••••••••••••••••••••••••••• 103
25 Total porosity, microporosity andmacroporosity changes with sucessivewetting and drying cycles, Molokaisoil. 7.5-25 cm depth •••••••••••••••••••••••••• 104
26 Total porosity, micrioporosity andmacroporosity changes with sucessivewetting and drying cycles, Waialuasoil. 0-7.5 cm depth ••••••••••••••••••••••••••• 106
27 Total porosity, microporosity andmacroporosity changes with sucessivewetting and drying cycles, Waialuasoil. 7.5-25 cm depth •••••••••••••••••••••••••• 107
28 Dry aggregate size distribution forMolokai soil following intensive tillageand prior to irrigation •••••••••••••••••••••••• 110
29 Dry aggregate size distribution forWaialua soil following intensive tillageand prior to irrigation •••••••••••••••••••••••• III
30 Field 220 Of Oahu Sugar Company. Spatialvariability of sorptivity was evaluated inthe shaded area .•••.•••...•......•..•••.•••••• ~ 124
31 Field 145 of Oahu Sugar Company. Spatialvariability of sorptivity was evaluated inthe shaded area ••••.•••••••...•••••.••...•.•..• 125
32 Sampling grid for Field 220 (Molokai soil)showing 49 measurement points •••••••••••••••••• 126
33 Sampling grid for Field 145 (Lahaina soil)showing 49 measurement points •••••••••••••••••• 127
34 Normal probability plot for sorptivity withnegative head for Molokai soil ••••••••••••••••• 130
35 Normal probabilty plot for log sorptivity withnegative head for Molokai soil ••••••••••••••••• 131
36 Normal probability plot for sorptivity withnegative head for Lahaina soil ••••••••••••••••• 132
37 Normal probability plot for log sorptivity withnegative head for Lahaina soil ••••••••••••••••• 133
38 Infiltration (a) and redistribution (b) soilwater profiles for Molokai soil computed usingparameters from cycle 0 and cycle 5. Irrigationrate 0.20 em/hr. The numbers on the curvesindicate hours of elapsed time after initiationof infiltration or redistribution ••.••••••••••• 146
39 Infiltration (a) and redistribution (b) soilwater profiles for Molokai soil computed usingparameters from cycle 0 and cycle 5. Irrigationrate 0.125 em/hr. The numbers on the curvesindicate hours of elapsed time after initiationof infiltration or redistribution •••••••••••••• 147
40 Infiltration (a) and redistribution (b) soilwater profiles for Waialua soil computed usingparameters from cyele 0 and cycle 3. Irrigationrate 0.20 em/hr. The numbers on the curvesindicate hours of elapsed time after initiationof infiltration or redistribution •••••••••••••• 148
xvii
41 Infiltration {a) and redistribution (b) soilwater profiles for Waialua soil computed usingparameters from cycle 0 and cycle 3. Irrigationrate 0.125 em/hr. The numbers on the curvesindicate hours of elapsed time after initiationof infiltration or redistribution •••••••••••••• 149
42 Adjusting sorptivity for antecedent moisturecontent •••••••••••••••• ~ •••••••••••.••••••••••• 163
CHAPTER 1
INTRODUCTION
Efficient use of water for crop producti~n
depends on an understanding of the soil processes
governing water movement. There is a great deal of present
interest in the use of numerical models for simulating
soil water flow in the unsaturated zone (Bhuiyan et al.,
1971; Endelman, 1974; Haverkamp, 1977; Khan, 1979; Mualem,
1976; van Genuchten, 1978). One of the most important
factors limiting the successful application of unsaturated
flow theory to actual field problems is the lack of
information regarding the parameters entering the
governing transfer equations (van Genuchten, 1980).
Modeling water movement in soils requires knowledge of the
two most important soil hydraulic properties, hydraulic
conductivity as a tunction of volumetric water content or
soil water suction, and the water retention relationships
(Dane and Hruska, 1983j. wnen these are not readily
available other related soil hydraulic properties may be
used to predict them.
Input data for models should be obtained from
in situ measurements when possible or from undisturbed
soil cores. A sufficient number of measurements should be
2
made to give a valid estimate of each parameter used.
Reliable estimates of soil hydraulic properties are
especially difficult to obtain because of the variability,
both spatial variability (variability over distance) and
temporal variability (variability with time). Spatial
variability has received much attention in recent years,
providing substantial information on field measured soil
hydraulic properties (Babalola, 1978; Baker and Bouma,
1976; Cameron, 1978; Coelho, 1974; Nielson et al., 1973;
Springer and Difford, 1980). Several statistical methods
have been proposed to cope with s~~tial variability, such
as the Monte Carlo technique (Warrick et al., 1977a) and
scaling of soil hydraulic properties according to the
concept of similar media (Peck et al., 1977; Sharma et
al., 1980; Sharma and Luxmoore, 1979; Warrick et al.,
1977b). On the other hand little information is available
on the changes in soil hydraulic properties sUbsequent to
tillage.
Computer simulation of water and solute
movement provides means of optimizing water management
practices with less field experimentation than would
normally be required (Khan, 1979). More and more sugar and
pineapple lands in Hawaii are coming under drip irrigation
systems. The sucess of this irrigation method depends on
the ability of soil to conduct adequate water from the
drip emitter to the plant. First, the amount of water
3
delivered by a given emitter must be sufficient to
germinate or establish the seedpeice. Under drip
irrigation, the soil water conduction is in the
unsaturated state. Therefore conducting sufficient water
to the seedpiece will depend not only on emitter flow
rate, duration and frequency of water application, but
also on soil hydraulic and related soil physical
properties.
The purpose of tillage is to create soil
conditions favourable for seed germination and crop
production while protecting soil and water resources
(Voorhees, 1977). Mechanical tillage is the most commonly
used direct method of preparing a good seedbed. If the
soil consist of large clods it will fail to have good
conductive properties under unsaturated conditions and
will also lack good contact with the seed. Preparation of
a good seedbed with favorable aggregation will enhance the
germination and establishment of the seedp as it increases
the contact and water conducting properties of the soil
under unsaturated conditions.
Once the seedpiece is established, water must
be adequately supplied to meet crop requirements. This
will not remain as a static amount, as the water
conducting properties of the soil as well as the water
requirement of the crop varies from tillage to harvesting.
The magnitude of tillage effects on soil hydraulic
4
properties can be expected to change with time after
tillage. When the tillage operations are over the
disturbed soil zone starts to return to the untilled
state, mainly due to compaction. Compaction is caused by
external forces, such as vehicular wheel traffic,
intercultivation, raindrop impact, and root development,
and by internal forces associated with deformation of a
soil due to wetting and drying. Compaction, whatever the
origin, reduces the gross pore space and is expected to
cause a new frequency distribution of effective poresizes
(Bodman and Constantin, 1965). It also increases the
cohesiveness of the soil mass which improves the contact
of seedpiece with soil immediately atter planting.
Regardless of the specific reason, it is recognized by
field researchers that many soil physical properties
e.g., bulk density, mechanical impedence, hydraulic
conductivity, thermal conductivity, and infiltration rate
undergo temporal variability during the year (Cassel,
1983). Consequently the movement and storage of water,
gases and heat are altered.
These changes in soil hydraulic properties
should be taken into account in studies of water supply to
crops under drip irrigation. Temporal variability of soil
hydraulic properties must be characterized and quantified
to adequately simulate water and solute transport
processes throughout the cropping cycle.
5
OBJECTIVES
The overall objective of this study was to
develop methodology by which temporal variability of soil
hydraulic properties of tilled soils can be accomodated in
simulation models which involve unsaturated water flow.
This major objective is to be achieved by addressing the
following sUb-objectives.
1. Characterize temporal variability in soil hydraulic
properties subsequent to tillage.
2. Recommend simple soil water measurement methods
appropriate for assessing temporal variability.
3. Identify an appropriate procedure to cope with the
measured temporal variability in simulation of water
and solute movement.
Field measurements were carried out in two
soil series located in the Kunia area and Waiamanalo area
of Oahu, Hawaii. Soil hydraulic properties were measured
immediately after tillage and following wetting and drying
cycles. No external forces were used to impose temporal
variability. The major interest was in characterizing
changes in hydraUlic properties resulting from internal
soil forces, mainly deformation from effective stress due
6
to changes in pore water pressure associated with repeated
wetting and drying.
This dissertation has been arranged into six
chapters. Chapter One deals with the introduction,
objectives and literature review. Chapters Two, Three,
Four and Five address the objectives one, two, three and
four respectively. The major conclusions reached from each
chapter are listed in Chapter Six. The appendices contain
data and sample calculations.
7
REVIEW OF LITERATURE
Soil hydraulic properties are of a dynamic
nature. Tillage operations, cropping systems, rainfall,
irrigation, wetting and drying and many other factors can
produce changes in soil hydraulic properties, especially
in the upper layers of soil.
Importance of Tillage for Crop Production
Tillage is the mechanical manipulation of the
soil for crop production. Particular objectives of tillage
include preparation of a seed bed, destruction of weeds,
improvement of soil-water-air relations and reduction of
impedence to plant roots (Marshall and Holmes, 1979). It
has been generally agreed that excessively dense and hard
soils resist the healthy development of roots and the
ability of plants to take up water. Therefore the main
purpose for primary soil tillage is to loosen the soil
which has been compacted by machinery traffic or by
natural processes. Tillage should provide a soil surface
condition that enables water to be detained and infiltrate
rapidly during the part of the cropping season when runoff
is most likely to occur (Allmaras, 1966). Tillage also
mixes plant residues with the soil which may speed up the
activity of soil microorganisums in decomposing crop
resedues and soil organic matter. What has not been agreed
8
upon is the best density or pore volume which should be
created in an agricultural soil to allow a plant to
utilize water efficiently. It is quite conceivable that
the physical properties of a soil which might be optimum
for plant growth in a relatively wet climate would not be
the best for a drier area, or even in a drier season in
the same location. Considerable progress has been made in
describing soil hydraulic properties, water retention and
root uptake of water as functions of soil density or the
porosity and the amount of precipitation or irrigation in
a given time.
Mechanical tillage is the most commonly used
direct method of altering the soil conditions for crop
production. Tillage tools, including plows, chisels,
cultivators and harrows, are designed to shatter, cut,
loosen, invert or to mix the soil and to smooth or shape
its surface. Plowing turns the soil over and covers crop
residues, usually producing a rough, cloddy surface.
Disking breaks the clods to smaller particles, and
harrowing smooths the surface to form a seed bed (Thompson
et al., 1973). A good seed bed provides a suitable
enviornment for seedling establishment.
Description of Tillage Practices
The combined primary and secondary tillage
operations, normally performed in preparing a seed bed for
9
a crop grown in a given area is called conventional
tillage. Conventional tillage is made up of plowing,
disking, harrowing and planting. The operation of tillage
equipment results in a number of changes in the soil, some
of which are undesirable (Blakely et al., 1978).
In instances where simple definitions are not
adequate, an outline is used to establish four important
elements needed to describe tillage practice or operation.
The elements of the terminology procedure are statements
of: identification of the soil; the objective of the
tillage practice; the action of the tillage operation; and
the significance of the obtained results (Blakely et al.,
1978). Out of these the most important is the objective of
the tillage operation. This must be stated in terms of the
desired change in the soil and not in terms of what
implement is to be used. Allmaras et ale (1966) showed
that soil conditions produced by a given tillage implement
or combination of tillage implements differ markedly
depending on other factors such as soil type, soil
moisture content at the time of tillage and the cropping
history. Therefore tillage practices can be more
thoroughly analyzed by an assessement of the reSUlting
soil conditions than by description of the tillage
operation only.
10
Effect of Tillage on Soil Hydraulic Properties
Tillage changes the physical characteristics
of a ~oil surface in a number of ways. Among these factors
are structure, surface roughness and the bulk density.
Changes in bulk density results in changes of porosity,
pore-size distribution, infiltration rate, water retention
and soil temperature. Tillage practices can also have
major influences on erosion.
Soil Structure
Soil structure is the physical constitution
of a soil material as expressed by the size, shape and
arrangement of the soil particles and associated voids
including both the primary particles to form compound
particles and the compound particles themselves (Brewer
and Sleeman, 1960). All tillage operations change the
structure of the soil, thereby changing the pore-size
distribution, which alters the soil hydraulic properties
of the tilled layer. The lifting, twisting and turning
action of the plow leaves the soil in an aggregated and
loose condition. In a seedbed of aggregated soil, the
average aggregate diameter and the propertion having
certain diameter limits may be modified by tillage
operations.
11
Bulk Density and Porosity
Bulk density is usually reduced with tillage
operations. Frequently the primary preparation makes the
soil too loose for planting and secondary operations are
needed to bring the soil back to the conditions suitable
for a seedbed. Tillage directly alters the soil aggregate
size.An inverse relationship between bulk density and
aggregate size was reported by Miller and Mazurak (1958).
Bulk density has usually been measured by undisturbed soil
core samples. Accurate measurements of bulk density, and
hence porosity, in recently tilled soil layers is
difficult because of the looseness of the soil and the
consequent difficulty of retaining the sample in the
cylinder (Allmaras, 1969). Total void volume of the tilled
layer and surface microreleif of soil surface have been
measured by air pycnometry (Page, 1947: Russel, 1950) and
by a microrelief meter (Burwell et al., 1966). The
influence of different tillage systems on bulk density,
porosity and roughness of the tilled layer have been
determined using these methods. Allmaras et ale (1977)
using a Wa~la silt loam showed how a chiseling treatment
reduced the bulk density in the very top layer. Reduced
dry bulk density of the chiseling treatment with no
subsequent field traffic was still evident even axter one
year. Schroeder et ale (1979) using a Chalmers silt loam
showed that in a conventional tilled soil profile, the
12
bulk density at every 15 cm increment depth was
significantly greater than the preceding depth down to the
tillage depth of 75 cm. Thus tillage loosens the surface
more than the subsurface.
Bolt et ale (1967) found that total porosity
and surface roughness are generally greater with the plow
treatment than plow-disk-harrow teatment. Burwell et ale
(1963) showed that the greatest increase in noncapillary
pore volumes resulted from tillage operations such as
moldboard and disk plows. Allmaras (1966) reported that
the increase in total porosity by tillage is more due to
increase in macropores than in micropores. The clod size
resulting from tillage operations is determined to a
greater extent by the soil type and the conditions at the
time of tillage. Plowing when the soil is too wet (near
the field capacity) usually produces large clods. The same
operation when the soil is midway between field capacity
and wilting point will frequently produce a finely
pulverized soil that is made up of small clods. This will
reduce the demand for secondary tillage operations
(Lovely, 1967). Allmaras et ale (1967) also showed that
the total porosity increases and the random roughness due
to plowing were significantly affected by the moisture
content at the time of tillage. Disking and harrowing
decreased the porosity when performed on soils in the
friable range of consistency but increased the porosity
13
when performed on soils in the plastic range of soil
consistency. The porosity decrease by sUbsequent disking
and harrowing was more pronounced when plowing gave the
highest porosity increase.
water Retention Characteristics
Tillage practices alter the soil porosity and
pore-size distribution which determine the water retention
properties of the soil. As the increase in total porosity
due to tillage is due principally to increase in
macropores, tilled soil retains more water at low suctions
than at higher suctions (Warkentin, 1971). Also the amount
of water retained by soil at saturation is increased by
tillage. Allmaras et ale (1977) using the soil water
desorption curves showed that chiseling atfected the water
retention, especially in the 50 to 300 millibar suction
range. Ehlers and van Der Ploeg (1976) using in situ water
retention curves for a grey brown podzolic soil, showed
that from saturation up to 50 cm of water suction the
tilled soil retained more water than untilled soil.
Available water capacity can be altered by tillage
practices which change aggregate size distribution and
arrangement. This provides a means of changing the water
storage characteristics of the seed environment by
changing the ability of the surrounding soil to replace
water loss by evaporation (van Doren, 1967). Van Duin
14
(1956) predicts that the capillary porespace volume
fraction can be increased by a factor of 1.4 by changing
aggregate arrangement from close to open packing, if the
aggregates are less than 0.2 rom in diameter. This
increases available water holding capacity on a volume
basis. When aggregates larger than 0.6 rom in diameter are
changed from close to open packing the capillary porespace
volume is reduced thereby reducing the available water
capacity. Oschwald (1973) showed that shallow chiseling
undoubtedly improves water intake, soil water storage and
soil erosion.
Infiltration and Hydraulic Conductivity
Tillage affects infiltration through its
effects on porosity (amount and size distribution) and
random roughness. Hence, an increase in total porosity
increases the rate and amount of infiltration because of
more rapid water conduction and temporary water storage in
large pores (Allmaras et al., 1966). Fernandes (1976) and
Bouma et ale (1973) showed that the increase of large
pores near the surface increases both infiltration and
conductivity, although soil type determines the amount of
improvement. Tillage, through its effect on surface
roughness influences the surface detention of water
thereby affecting the time available for infiltration.
Those tillage treatments providing a rough surface
15
infiltrated more water before runoff occured than the
packed and the consolidated treatments. This was
accomplished by increasing surface detention and reducing
overland flow velocity (Falayi and Bouma, 1975; Amemiya,
1968). Burwell et al. (1963) developed an index of surface
conditions, the random roughness index which was
correlated with infiltration rate and surface capacity. On
sloping lands, tillage-induced soil structural conditions
affect the partition of water between intake and runoff.
Burwell (1963) showed that random roughness was directly
related to infiltration and cumulative infiltration before
runoff. Cumulative infiltration for a plowed-only surface
was three times greater than for a surface created by a
plow-disk-harrow sequence and six times greater than for a
relatively smooth surface created by rotary tillage.
Comparable data relating water infiltration to tillage
profiles have been reported by Moldenhauer and Wischmeier
(1960) and by Mannering et al. (1966). Reviewing the
objectives of tillage, Larson (1963) indicated that
tillage can influence the amount of soil water available
for crop growth, and discussed how infiltration and water
storage capacity of soil may be markedly atfected by soil
structure conditions induced by various tillage
operations.
After the water infiltrates the soil,
conductivity is effected by the internal characteristics
16
of the soil mass including the poresize, thickness of the
tilled layer, degree of swelling of clay colloids and the
soil moisture content (Moldenhaure, 1970). Allmaras (1977)
showed that chiseling increase the hydraulic conductivity
in a Wa~la silt loam especially in the 50 to 300 millibar
suction range. Infiltration and conductivity have been
described as water movement through channels (macropores)
and capillaries (micropores) by Dixon and Peterson (1971).
If the channels were open to the surface and free water
was available both the infiltration rate and conductivity
increased. Steichen et ale (1979) using four tillage
treatments and simulated rainfall showed that the surface
openings, as represented by random roughness allow
rainfall to enter, and in association with high porosity
promote infiltration.
Changes of Soil Hydraulic Properties SUbsequent to Tillage
By changing the soil structure, tillage
operations alter total porosity, pore-size distribution
and other related soil hydraulic properties. After the
tillage operations the seed bed is composed of large pores
among the disoriented aggregates. As soon as the tillage
operations are over the disturbed soil starts returning to
the monograin structural mass. This is mainly caused by
wetting and drying, compacton and rainfall impact.
17
Wetting and Drying Effects
After tillage operations loosen the soil
matrix, the settling of the soil takes place due to
wetting and drying. These are major events that greatly
influence the soil hydraulic properties subsequent to
tillage. Wetting of large aggregates resulting from
tillage operations weaken the aggregates and allows them
to breakdown to more intimate contact.
Settling problems are due to soil failure and
associated changes in the pore space of soil. Critical
state soil mechanics developed by Roscoe et ale (1958)
provide a unified theory which aims to connect soil stress
with changes of pore water pressure and express
relationships between deformation and effective stress.
According to the stress concept the total stress
component,6 normal to any plane in the soil is divided
into two parts; the pore water pressure (ll) and theI
effective stress component (0). The total stress component
can be estimated from knowledge of the external forces and
the weight of the soil body. The effective stress
component is the part considered to be effectively carried
by the structure of the soil particles. The basic
supposition is that the mechanical behaviour of the soil
structure depends on all the components of effective
stress (Schofield and Wroth, 1968).
In a saturated soil effective stress is given
18
by the equation proposed by Terzaghi (1943) viz
J
0=6 - Up • • • • • • • • • • •• (1)
where 6 is the total stress and Up is the pore water
pressure. The effective stress for unsaturated soils is
given by the empirical equation
• • • • • • • • • •• ( 2)
where X is a tunction of the water content (Towner, 1983).
In unsaturated conditions the pore water pressure is below
atmospheric (soil water suction) so that U <0. As shown in
Equation 2 the pore water pressure alters the applied
stress by the quantity of -XUp and when Up is negative the
overall result is equivalent to an increase in the
effective stress component by XUp• For all practicle
purposes the effect of externally applied stress and those
induced by negative pressure are identical. Therefore this
is equivalent to the soil being sUbjected to an external
isotropic stress of magnitude XUp (Hettiaratchi and
Q'Callagan, 1980). Towner (1983) and Towner and Childs
(1972) showed that the effective stress component
increased with increasing soil water suction to some value
and thereafter changes only slightly. In the drying out
process if the effect of cementation predominates over
19
those due to soil suction the effective stress may
actually decrease (Hettiarachi and O'Callagan, 1980).
When a dry soil aggregate is being wetted the
pore water pressure becomes relatively less negative,
reSUlting in a decrease in effective stress. This will
weaken the aggregates and cause failure and ultimate
breakdow. Drying stabilizes the new configuration and
generally results in a strong hard soil which can restrict
water and air movement.
Kemper and Koch (1966) showed that the degree
to which the aggregates break down leaving the soil as a
monograin structureless mass is also determined by the
manner in which the soil is wetted. Ghawami (1969)
observed that the rate of wetting has a marked effect on
the persistence of large pores. Kempt et ale (1975) using
a Nunn clay loam showed that flooding of the soil resulted
in less large porespace than wetting the soil from
capillary action. Slow capillay wetting of the tilled soil
generally leaves most of the aggregates intact and a major
portion of the porespace will be macropores. Nielson and
Bigger (1961) using a Colombia silt loam showed that the
difference between the capillary conductivity of first and
second drying cycles is caused principally by soil
settling associated with the applied negative pressure.
Large volume changes are characteristic of
soils with a high content of expanding type clays whereas
20
sandy soils may show no measurable changes (Warkentin,
1971). Corey et ale (1971) determined the change of water
content and bulk density of Houston black and Cecil soil
columns using a dual gamma procedure. Their data show that
the bulk density decreased to a depth of 4 cms after
wetting, but below that depth there was no change. Berndt
and Coughen (1976) using core samples of Waco black soil
showed that there is a high correlation between water loss
and volume changes. They also showed that the relative
change of the height of soil cores in drying are highly
correlated with the relative changes in diameter.
Contradicting results were obtained by Reginato (1974). By
using a Avondale clay loam pedon he showed that the bulk
density decreased in the top 6 cms of soil about 30
minutes after water was ponded on the soil surface. After
drainage the bUlk density values approached preirrigation
levels. The degree of volume change with respect to water
content depends upon the amount and type of clay, the
particle arrangement and organic and chemical bonding
agents.
Swelling and shrinking cycles associated with
water content changes are beneficial to a compacted soil
as they tend to decrease the density, but detrimental to a
loose aggregated soil as they tend to increase the
density. Cracking of agricultural soils because of volume
changes is often desirable for creating avenues of
21
improved water intake and for enhancing gas exchange.
Compaction Effects
The term compaction has been applied to the
compression of an unsaturated soil body resulting in
reduction of the fractional air volume (Hillel, 1982).
This is caused by a combination of external and natural
forces. The external forces related to the consequences of
agricultural technology, such as vehicular wheel traffic,
tillage implements and irrigation have a much greater
compactive effect than such natural forces as raindrop
impact, soil swelling and shrinking and tuber and root
enlargements.
Depending on several management factors,
agricultural fields are generally sUbjected to wheel
traffic at least three times each growing season during
tillage, planting and harvesting. Frequently other
operations are necessary, each potentially capable of
compacting the soil (Voorhees, 1977). Baver and Trouse
(1970), and Trouse (1964) discussed in detail the
influence of tield equipment and machinery on the
compaction of sugarcane soils of Hawaii. They showed that
the harvesting traffic is responsible for serious soil
compaction in Hawaiian cane fields. The compaction
increases with moisture content of the soil (up to the
liquid limit), the weight of the vehicle and the number of
22
passes. There was less compaction on dry soils
irrespective of the number of passes. The most acute phase
of the harvesting operation was the transport of cane from
within the fields to the adjoining roads.
When a soil is sUbjected to an applied load
that is sufficient to cause a volume change, the two
possible factors to which the change could be attributed
are the compression and the rearrangement of the soil
particles. The state of the compaction of the soil at any
time may be defined by the bulk density, porosity or void
ratio (Barris, 1971) .Vehicular compaction usually produces
layers of soil with high bulk density rather than a
uniformly compacted soil (Warkentin, 1971). Maximum soil
compaction occurs at an optimum moisture content for a
particular soil and is expressed by a proctor density
curve. Compaction, whatever the origin, rearranges the
soil particles so that the porespace is reduced and may
eliminate some of the large pores completely (Reicosky,
1981). These changes are sufficient to modify the fluxes
of water, air and heat in the soil (Larson and Allmaras,
1971), and to change the soil strength. Compaction affects
water retention and hydraulic conductivity by changing the
volume, size, shape and continuity of the pores.
Compaction also increases soil strength which is desirable
for engineering practices but which may be an undesirable
23
agronomic practice because it decrease root growth (Taylor
and Ratliff, 1969).
Soil Water Retention
The largest voids are decreased most in size
by compaction. Therefore compaction decreases the amount
of water held at low suctions in large voids and increases
water held at high suctions in the additional small voids
which have been formed. The magnitude of the increases and
decreases and the position of the crossover point depends
upon the particle size distribution and structure
(Jamison, 1953). Chang and Warkentin (1968) using a clay
soil at two compaction levels, 50 p.s.i. and 1000 p.s.i.,
showed that the amount of water retained at suctions
higher than 0.1 bar was more in the compacted sample.
Warkentin (1971) reported that the amount of water held at
high suctions increases with increasing soil compaction
but noted that the compaction effect is less for clay
soils than for coarse textured soils. Soils containing
montmorillonites show great changes in volume with changes
in water content, and compaction of these soils may not be
as detrimental as compaction of soils containing
kaolinitic or illitic clay minarals, which have smaller
coefficients of swelling (Warkentin, 1971). Hysteresis in
the coarse grained soils is decreased by compaction
because the void sizes become more nearly uniform.
24
Voorhees et al (1979) also showed a similar effect using
water retention curves for wheel tracked and non-tracked
soil cores for a Nicollet silty loam. The crossover point
of decreasing and increasing water retention due to
compaction was at a soil water pressure head of -15 cm
water.
Infiltration and Hydraulic Conductivity
As compaction affects the larger poresizes it
reduces the infiltration and conductivity at or near
saturation. Blake et al., (1976) using an Aquic hapludoll
reported a 65% decrease in the saturated conductivity due
to compaction. Kemper at al., (1971) showed that
compaction can increase unsaturated hydraulic conductivity
by increasing the number of small pores which remained
filled with water under medium suction. He observed that
increasing the bulk density of a Ustollic haplargids from
1.1 to 1.60 g/cm3 more than doubled the unsaturated
conductivity in the matric potential range from -0.30 to
-1.5 bars. Sharada (1977) using packed columns of silty
clay loam showed that increasing the bulk density reduced
the soil water diffusivity near saturation. The
infiltration rate and cumulative influx were reduced
markedly with increasing bulk density. Compaction usually
provides layers of soil with high bulk density; the water
flow in layered soils is discussed in detail by many
25
investigators (Swartzendruber, 1960; Warkentin, 1971).
Rainfall Impact Effects
Raindrop impact on freshly tilled soil
surface detaches and transports the soil particles. When a
raindrop strikes the tilled soil surface the detachment of
the soil particles will depend on several factors. These
includes intergranular shear, the viscosity of the pore
fluid, the rupture energy of liquid and 'mechanical
bonds' (Cruse and Larson, 1977). Soil shear strength is
influenced by bulk density (Young and Warkentin, 1966), by
interparticle bonding (Williams et al., 1967) and by
matric potential (Towner and Childs, 1972). Rainfall on a
bare tilled surface washes fine soil particles into the
depression and open channels, resulting in progressive
sealing. Wetting and drying of soil surface causes
physical changes in the upper layer of the soil that make
it denser and reduce the surface permeability to water and
air. The compacted surface soil layer, which can be
usually distinguished from relatively undisturbed soil
below, is called a soil crust. The restrictive role of
soil crusts is discussed in detail by Taylor (1971) and is
a major factor limiting crop production of weakly
structured fine grained soils. Surface sealing and crust
formation are major factors that effect infiltration as
this thin compact layer has a much lower infiltration rate
26
than the original tilled surface (Mannering, 1967). On a
freshly tilled soil the conductivity characteristics of
the entire soil layer are nearly uniform when rain begins.
The water retention characteristics and the
diffusivity-water content relationship determined from a
sample taken at an intermediate depth will probably
descibe the entire tilled layer. After a short time of
rainfall a definite seal having greater density, fine
pores and a lower saturated conductivity than the average
tilled layer has begun to form on the surface. The water
retention and the diffusivity-water content relationship
from the underlying soil can no longer describe water
movement through the surface (Edwards and Larson, 1969).
Swartzendruber (1960) showed that water flow through a
soil profile is effected by the least permeable layer.
Infiltration of water into soils as influenced by surface
seal development and into crust topped profiles has been
documented in detail by Edwards and Larson (1969), Farrel
(1972), Flayi and Bouma (1975) and Hillel and Gardner
(1969). The resistants to water movement in a surface seal
increases with time as more energy in the form of raindrop
impact hits the surface Moledenhaur and Long (1964). Most
of these changes take place before the crop canopy starts
protecting the soil surface. Wischmeir (1959) reported
that this vulnerable period occurs during the first two
months following planting in the corn belt.
27
Mannering (1967) showed that crust strength
increases with increasing silt and clay content, specific
surface, suspension percentage, moisture equivalent and
the interaction of these properties. Crust strengh was
inversely related to sand content, organic matter and
shrinkage ratio. Mulching and improved aggregation of the
soil due to rotations involving grasses also reduce the
seal formation (Harris et al., 1969). Typically,
infiltration equations do not include parameters to
account for these effects on the soil surface. Gregory
(1979) presented an equation to account for the effect of
surface changes on infiltration. This equation is a
modification of the physically based Green-Ampt equation.
Random roughness of the tilled surface is
also altered by rainfall impact. Burwell (1966) showed
that rainfall decreased random roughness and the total
porespace of freashly tilled soil. Most of these decreases
occured during the period prior to initial runoff. During
the period of structural changes, due to rainfall impact,
the dispersion of soil materials causes smoothing of the
rough tilled surface which decreases the surface detention
of water thereby affecting the time available for
infiltration.
28
Long Term Effects of Tillage and Landuse on Soil
Hydraulic Properties
The traditional and probably the most used
tillage system has been termed conventional tillage which
typically begins with a primary deep tillage operation
followed by some secondary tillage for seedbed
preparation. However the concept of tillage requirements
has been changing rapidly. Researchers have developed new
tillage methods that differ significantly from the more
conventional systems. Minimum or zero tillage is used to
designate a tillage system in which mechanical soil
manipulation is reduced to a minimum. Many workers have
evaluated the soil hydraulic properties of minimum tillage
versus conventional tillage (Baleman, 1963: Ehlers, 1973:
Phillips, 1962).
Apart from reducing the cost for tillage
operations zero tillage may eventually eleminate some of
the negative side effects of tillage and repeated heavy
traffic on soils. Certain changes in soil structure as a
result of tillage are less obvious. Long term tillage and
traction by heavy implements can result in formation of a
plow pan. Usually the pan formation occurs in a layer
immediately below the depth of cultivation and has been
shown to have a detrimental effect on soil water movement
(Baleman, 1963). Ehlers (1973) showed that one reason for
slow water intake of gray-brown podzolic soils in situ is
29
the formation of a traffic pan at 20 to 25 cm depth with
very low porosity. The very dense traffic pan loosened up
after some years of no tillage. Baeumer and Bakerman
(1973) documented that limited infiltration, surface
runoff and soil erosion however are not observed in
gray-brown podzolic soils when intensive tillage is
abandoned and when crops are grown using the minimum
tillage method. With minimum tillage the surface is
covered with mulch and stubble. The mulch and stubble
cover prevent rainfall impact and thereby the development
of a surface seal and crust.
A relatively higher amount of smaller pores
but greater homogeneity in time as well as in space are
thus the dominant changes in porosity when a soil remains
untilled for a long period. Another benificial feature may
be the continuity of pores by earth worm channels and by
decaying roots. Ehlers (1975) observed an increase of
earthworm activity when the tillage operations were
reduced. In context with these observations, Dixon and
Peterson (1971) developed a channel system concept
describing the mode and intensity of water infiltration.
If the channels were open to the surface and free water
was present infiltration rate increased. They stressed the
profound influence of large pores on water movement and
showed that zero tillage will increase the infiltration in
the long run by increasing the continuity of pores.
30
Conventional tillage systems have detrimental
long term effects on soil water transmitting properties by
development of a plow pan and by destroying the continuity
of large pores. This has been investigated by evaluating
soil water properties from adjacent sites on the same soil
family but having different landuse. Yamamato (1963)
showed that forest soils had greater water holding
capacity and more available water than adjacent soils
under cultivation. Wood (1971) using six sites from
different soil series showed that total porosity,
macropores and infiltration rates were higher in forest
soils than in adjacent sugarcane and pineapple land.
Effects of landuse were most pronounced in the first six
inch segment of the soil profile. The apparent etfects of
landuse decreased with depth (Wood, 1971). These
differences are attributed to the mechanical tillage,
compaction during planting and harvesting and direct
exposure of tallow fields to rainfall.
CHAPTER 2
CHARACTERIZING TEMPORAL VARIABILITY OF SOIL HYDRAULIC
PROPERTIES SUBSEQUENT TO TILLAGE
INTRODUCTION
The rationale for conducting research on
temporal variability of soil hydraulic properties is
addressed in the introduction. The temporal variability of
soil hydraulic properties may be an important
consideration in modeling soil water and solute movement
during the cropping cycle. The ability of soil to retain
and transmit water is governed by the hydraulic properties
of the soil. Key properties are hydraulic conductivity,
sorptivity, soil water diffusivity and soil water
retention. The hydrologic behavior of soils is to a large
extent determined by how the hydraulic conductivity varies
with soil water content or soil water suction. Knowledge
of the hydraulic conductivity (K) either as a function of
volumetric water content (8) or soil water suction (h) is
essential for modeling soil water and solute movement.
Application of the water flow equation to field situations
usually requires that K(h) or K(8) is determined in situ.
These properties are determined by the geometry of the
32
pore space. When these data are not available the related
soil physical properties such as structure, texture, bulk
density, porosity and pore size distribution are used to
predict them.
As discussed in Chapter One, compaction is the
major factor contributing to temporal variability of soil
hydraulic properties subsequent to tillage. Compaction may
stem from external forces such as vehicular traffic,
intercultivation, rainfall impact and root growth or may
be induced by internal forces such as soil swelling and
shrinking due to intermittent wetting and drying. Temporal
variability due to rainfall impact depends on the
intensity and duration of rainfall. Temporal variability
caused by vehicular wheel traffic depends on the soil
moisture content, the weight of the vehicle and the number
of passes.
The first objective of this study was to
characterize temporal variability in soil hydraulic
properties sUbsequent to tillage which is addressed in
this chapter.
Field measurements were carried out in two
field locations in the Island of Ohau, Hawaii to
characterize the temporal variability of soil hydraulic
properties and related soil physical properties subsequent
to tillage. The selected soil hydraulic properties and
related soil physical properties are listed below.
33
Soil Hydraulic Properties
1. Sorptivity (5):
a. measured with positive head, SPOSi
b. measured with negative head, Sneg.
2. Hydraulic conductivity (K):
a. as a function of vOlumetric water content, K(9)i
b. as function of soil suction, K(h).
3. Soil water retention data, h(8).
Related Soil Physical Properties:
1. Bulk Density and Porosity,
2. Macroporosity.
These properties offer the possibility of
quantitatively assessing the influence of tillage-induced
and sUbsequent changes in the soil profile.
34
METHODOLOOY
Description of Soils
The field experiments were carried out with
the following two soils at the designated sites.
1. Molokai Silty Clay Loam:
(BSPA Sub Station in Kunia)
Typic Torrox, clayey,
kaolinitic, isohyperthermic
2. Waialua Clay Variant: Vertic Haplustolls, clayey,
(U.B. Waiamanalo Exp. Farm) kaolinitic, hyperthermic
The Molokai soil is a highly aggregated and
well drained oxisol and is primarily composed of kaolinite
and the oxides of iron and aluminum. The Waialua soil even
though classified as kaolinitic, has some montmorillonite
clay which contributes to the vertic characteristics and
has a nigh swelling and shrinking capacity (I.Ikawa,
personnel communication). The detailed description of the
two soils are given in Appendix Tables I-I and I-2. The
intent of having two soil series was to study temporal
variabilty on soils having different extents of compaction
due to deformation resulting from wetting and drying.
35
Selection of Treatments
Temporal variability of soil hydraulic
properties sUbsequent to tillage is due mainly to soil
compaction. The term "compaction" refers to the
compression of an unsaturated soil body, resulting in
reduction of the porosity and associated changes in
poresize distribution. Compaction is not necessarily only
compression due to external forces such as traffic,
intercUltivation, rainfall impact and root development,
but may result from internal forces associated with
deformation of a soil body due to changes in the pore
water component of effective stress with soil wetting and
dry1ng. For all practical purposes effective stress of
unsaturated soil is equal to soil water suction
(Hettiarachi and O'Callagan, 1980).
When all external forces are eliminated, the
temporal variability of soil hydraulic properties
following tillage can be attributed principally to
deformation resulting from changes in pore water component
of effective stress associated with wetting and drying.
Therefore, the main components of wetting and drying which
contribute to temporal variability of soil hydraulic
properties are the lower suction limit (the extent to
which the soil is allowed to wet), the upper suction limit
(the extent to which the soil is allowed to dry) and the
number of wid cycles. The number of wid cycles and the
36
lower suction limit were included in the treatments while
keeping the upper suction limit nearly constant. The
rationale for the selection of the appropriate treatments
could be summarized as follows.
Temporal Variability of
Soil Hydraulic Properties (T.V.) = f(Compaction)
T. V. = f(Compaction due to external forces
such as traffic, intercUltivation,
rainfall impact + Compaction due to
internal forces due to soil wetting
and drying)
T. V. = f(Compaction due to wetting and
drying), if external forces were
eleminated
T. V. = f(Compaction due to changes in pore
water component of effective stress
with WID)
T. V. = f(No. of wId cycles, lower suction
limit, upper suction limit)
In these experiments rainfall impact was
eliminated by having a Dlack plastic roof 20-30 cm above
the soil surface. Vehicular w~eel traffic was avoided
after tillage operations which were carried out when the
soil was relatively dry. The plots were kept bare thereby
37
eliminating the compaction by root development and
intercultivation. Therefore, by these controlled
experiments the temporal variability of soil hydraulic
properties caused by soil compaction, resulting from
swelling and shrinking due to wetting and drying, could be
investigated. Intermittent wetting and drying was imposed
by water application with a drip irrigation system.
Experimental Design and Procedure
Experiment on Molokai Soil
The experiment was designed to include the
selected number of wId cycles and the associated changes
of lower suction limit with two levels of irrigation.
After irrigation, water was allowed to redistribute to a
constant suction thereby keeping the upper suction limit
fairly constant. A split plot design was used with two
irrigation levels as main plots. This was carried out by
using aifferent numbers of drip lines from the same drip
irrigation system. Drip irrigation was used to minimize
water drop impact and soil slaking in contrast to other
available irrigation methods. The following two irrigation
rates were used.
Irrig 1 = 7 Drip Lines:
Irrig 2 = 4 Drip Lines:
3.6 cms of water/application.
2.0 cms of water/application.
38
The higher rate was based upon the amount of
irrigation water used by the drip irrigated sugar
plantations in Kunia, Hawaii. The number of wetting and
dry1ng cycles were used as subplots. A total of six
sUbplots were used, one for measuring soil hydraulic
properties before irrigation and others after each wId
cycle for five wId cycles (irrigation cycles). Three
replicates were used in this split plot design with a
subplot size of 2x2 meters. A flooding treatment was
included only for comparison but not as part of the
statistical design. A detailed figure of one block of the
experimental design is shown in Fig 1.
The soil was ripped (a type of sub soiling
tillage equipment used in sugarcane fields) to a depth of
35-40 cm depth and then roto-tilled to break down the
large aggregates. The tillage operations were done at a
low water content (0.20 m3/m3) to minimize compaction. The
aggregate size distribution following tillage was
characerized by dry seiving method.
The area was divided to three blocks, each
measuring 14x5 meters. Each block was divided into two
l4x2 meter areas which acted as main plots. Each main plot
was divided into seven sUbplots measuring 2x2 meters.
Seven drip lines at a spacing of 30 em were set up in
Irrig 1 main plot. The Irrig 2 main plot had four drip
lines at a spacing of 50 cm. Drip emitters were 30 cm
2m
rO IRRIG 1( 7 DRIP LINES)
/ 2m
~
\
IRRIG 2 (4 DRIP LINES)
Figure 1. A single replicate showing irrigation levels as mainplotsand wetting and drying cycles as subplots in split plotdesign. Experiment in Molokai soil.
WID
40
apart and were set up diagnally to achieve even wetting of
the plots. Four mercury-manometer type tensiometers were
set up at the 15 cm depth in each block to observe the
intermittent wetting and drying patterns. The plots were
covered using black plastic roofs 30 cm above the ground.
The following soil hydraulic properties and associated
soil physical properties were measured from a randomly
selected subplot from each replicate before any
irrigation.
Sorptivity with positive head 3 measurements /plot
Sorptivity with negative head 6 .. .. /plot
Hydraulic conductivity 1 meas/plot/2 depths
Water retention data 2 cores/plot/2 depths
Bulk density 2 cores/plot/2 depths
The plots were irrigated for 18 hours using
the drip irrigation system. After irrigation a soil water
redistribution period was allowed to give a soil-water
suction of about 150 cm of water at 15 cm depth which took
about 7-10 days. Another set of soil hydraulic properties
were measured from a randomly selected plot from each
replicate after the first irrigation cycle. The same
procedure was repeated five times for five wid cycles. As
most of these measurements were destructive, a new subplot
which has gone through the previous number of wid cycles
41
was used each time. For example, the last set of plots
had gone through five wid cycles before soil hydraulic
measurements were accomplished. This is better illustrated
in Fig. 2.
The flooding treatment was imposed by using a
1.5 meter diameter metal ring. The ring was driven down to
20 cm depth and 40 liters of water (corresponding to
asurface water depth of 20 cm) was applied. A fibrous
packing material was laid temporarily on a portion of the
soil surface to prevent disturbance from direct water
impact. A set of soil hydraulic properties were measured
after water was allowed to redistribute, as in the drip
irrigation treatment discussed previously.
Experiment on Waialua Soil
As the field experiment in Mo1okai soil
failed to show any significant difference in the two
irrigation treatments, only one level of irrigation was
applied in the Waialua soil. Also the number of wetting
and drying cycles was reduced to three cycles. Therefore
the experimental design for the Waialua soil was a
randomized complete block design with a total of four sets
of measurements. (one before irrigation and three wid
cycles) with 3 replicates. A flooding treatment was
included for comparison but was not included in the
statistical design.
IRRIG 1
TILLAGE•
IRRIG 2
~'0..~~~:/.;(.:\'-~,~~
~~Pre-Irrig
IRRIGATE
3.6 em
1507-10 DAYS
em 820~ IRRIGATEm 3.6 emm
1
1507-10 DAYS
em 8 0~ ~.--~~m ~~ ~
TILLAGE•
~mIPre-Irrig
IRRIGATE2.0 em
7-10150 em H20~DAYS • IIRRIGATE~ 2.0 em~'
1507-10 DAYS
em H 0I ~--..~~ .m
2 5
Figure 2. Measurement times of soil hydraulic properties with relation to tillageand irrigation.
oil>IV
43
The soil was tilled using a mold board plow
and a rototiller was used to breakdown the large clods.
The aggregate size distrbution sUbsequent to tillage was
charcterized using dry seiving method. The site was
divided into three blocks of l2x2 meters each. The blocks
were divided into four plots of 2x2 meters each. A drip
irrigation system similar to the Irrig 1 main plot in
Molokai soil was set up to obtain intermittent wetting and
drying of soil. The following soil hydraulic properties
were measured after tillage and before any irrigation in a
randomly selected plot in each replicate.
Sorptivity with positive head 6 measuremens /plot
Sorptivity with negative head 12 n n /plot
Hydraulic conductivity 2 meas/plot/2 depths
Soil water retention data 2 meas/plot/2 depths
Soil bulk density 2 cores/plot/2 depths
The plots were irrigated similar to the Irrig
1 main plots of Molokai experiment. The soil hydraulic
properties were measured after each wid cycle up to three
cycles as done in Molokai experiment. A flooding treatment
identical to the previous experiment was included for
observation only.
44
Characterizing Temporal Variability of Soil Hydraulic
Properties Subsequent to tillage.
Sorptivity by Infiltration With Positive Head (Spos)
nSorptivityn, which is a physical property of
porous media, was proposed by Phillip (1957), which
measures the capacity of the media to absorb or desorb
liquid by capillarity. Phillip's two term equation shows
V2I = St + At
how cumulative infiltration (I) is related to time (t) by
two parameters, sorptivity(S) and a coefficient A.
Infiltration of water into unsaturated soils may be
divided into two stages, capillary and gravitational. The
capillary stage usually dominates at early times when
entry of water into a porous medium is very rapid due to
the sharp potential gradient; this stage is represented
by the first term of the equation (St 1/2). At larger
times the gravitational stage dominates and the
infiltration rate tends towards some asympotic value; this
later stage is represented by the second term of the
equation. For the very early part of infiltration the
first term dominates the flow, so that cumulative
infiltration can be approximated by
1/2I = St
45
Therefore it is possible to obtain the value of sorptivity
for a given antecedent moisture contnet by measuring
cumulative infiltration with time during the early
infiltration period. Sorptivity can be used to predict
infiltration (Parlange, 1971). Since this is a simple and
rapid method, many measurements can be made during a short
time with limited resources.
Materials and Methods
Sorptivity by infiltration with positive
head, Spos, was measured using the method proposed by
Talsma (1969). A single ring of 0.3 m diameter was
inserted about 0.2 m into the soil with minimum
disturbance. A hand tool was used to tamp the loose soil
adjacent to the ring. A sample for antecedent moisture
content was removed from outside the ring but nearby. A
graduated capillary tube was installed with one end on the
soil surface and the other end taped to the top of the
ring. The height of the ring above the soil surface and
the distance from the ring to the bottom of the tube
provided the data to calculate the angle (0') between the
soil surface and the capillary tube as shown in Fig. 3.
When the graduated capillary tube is at an angle 0( from
the horizontal plane the change of water level is
amplified by (Sin 0')' • A hand carried digital electronic
stop watch was used to record the time.
~
x
y=j
A~ Graduatedtube
Ik In f i 1 t rat ionring
Figure 3. Schematic diagram of infiltration apparatus for measuringsorptivity with positive head (Spos).
~O't
47
To initiate the sorptivity measyrement 2.2
liters of water were quick1y poured into the ring and the
clock was started simultaniously. A porous fibrous
material was temporarily laid on a part of the soil
surface so that water could be applied with minimum soil
disturbance. The drop in the water level was read using
the graduated capillary tube. The time corresponding to
each water level was recorded using the stop watch. A tape
reorder was used so only one person could handle the
entire operation. This method is discussed in more detail
by Green, Ahuja and Chong (1984).
Sorptivity for the given antecedent moisture
content was obtained from the slope of the cumulative
infiltration vs. square root of time relationship at short
times (generally <180 sec) when the effect of gravity was
negligible. The linear portion of the curve was used as
shown in Fig. 4. As sorptivity is sensitive to antecedent
moisture content it was corrected to 0.30 m3/m3 volumetric
water content using a linear approximation as suggested by
Chong (1979). This is discussed in detail in Appendix II.
Results and Discussion
The geometric means and the confidence
intervals for Spos before irrigation and after each wid
cycle for five cycles for Molokai soil are shown in Fig.
5. Each value corresponds to the mean of nine spos
--.-----------~I2.4 I
w>~ 0.6....J:::>~:::>u
SORPTIVITY, rn/secl / l
..........It)
I
o.....Xg,Zo~~
~l..1Z
1.8-
1.2 -
•
.'.//.,.
~,,//./.-
••
•
I
12I
10I ,- ,
468SQRT TIME (sec1/
2)
o Io I I I I ~
Figure 4. Calculation of sorptivity by cumulative infiltration andsquare root of time. II:lo
00
"
MOLOKAI SOIL
O 8 I I• I I I I I I
.,-.....N~
UQ)
~E
I'lIoC
>J->..n,a:::o(/)
2.4
2
1.6
1.2
•r~·
~ ,.. ,
• irrig 1
• irrig 2
o flood
I I._ I":' I. ·
o 2 3
WID CYCLES4 5
Figure 5. Sorptivity with positive head (Spos) with sucessive wetting anddrying cycles, Molokai soil. Geometric mean ± antilog of 1 SOof log s.
~\0
50
measurements. The geometric means were used as sorptivity
has been shown to be log normally distributed (Brutsaert,
1976; Chong and Green, 1979; Sharma et al., 1979). The
confidence interval was calculated by taking the antilog
of log mean Spos ± one standard deviation of log Spos.
This showed that the Spos decreased with wid cycles. The
analysis of variance for Spos (given in Appendix Table
III-la) shows that there is a significant difference among
the cycles but not between the two irrigation levels (main
plots). The Duncan's multiple range test, given in
Appendix Table III-lb, shows that there is a significant
difference between the mean of Spos before irrigation and
Spos after any irrigation cycle, but no differences exists
among the cycles. The Spos values for Waialua soil is
shown in Fig. 6. The analysis of variance and the Duncan's
mUltiple range test results are shown in Appendix Tables
IV-la and IV-lb. In Waialua soil also there was a
significant decrease of Spos with wid cycles. The Duncan's
multiple test shows that there is a significant difference
between the Spos before irrigation and Spos after any
irrigation cycle but not among cycles.
The Spos results also show the importance of
first wid cycle in compacting the soil after tillage by
wetting and drying. Immediately after tillage the soil has
more large pores, which gives a higher rate of sorptivity.
After the first wid cycle the soil compacts, decreasing
I0.4 I I I I I
I•"-----. Io I i
,,-....N~
Um 1.6
E'It) 1.3IoC
>- 1l->.-(L 0.7a:::o(f)
. I•
o 1
WAIALUA SOIL
2
WID CYCLES
• irrig
o flood
3
Figure 6. Sorptivity with positive head (Spos) with sucessive wettingand drying cycles, Waialua soil. Geometric mean ± antilogof 1 SO of log S.
U1.....
52
many of the large pores which reduces the Spos. Hamblin
(1982) showed evidence that plowed surfaces initially had
higher sorptivity than unplowed surfaces because of the
large number of conducting pores. This situation was
transient and by 8-10 weeks the untilled soil had a
greater sorptivity value. The Molokai soil showed an
average reduction of 44% with wid cycles and the Waialua
soil a reduction of 52% in Spos.
Sorptivity by Infiltration With Negative Head
Sorptivity by ponded infiltration (positive
head) may result in inaccurate estimates when large holes
such as root channels, cracks, ant and worm holes or any
other large voids which are not representative of the soi~
matrix are present. Therefore sorptivity by infiltration
with negative head, Sneg, was first suggested by Dirksen
(1975) and then used in the field by Clothier and White
(1981) and Chong (1982). In this method a specially
designed sorptivity device is used to release water
through a porous plate to the soil at a Sllght suction
which prevents water from entering large voids.
Materials and Methods
The sorptivity device used was developed by
Chong (1982) and is shown in Fig. 7. It is made out of a
lucite or Plexiglas tube (35 cm tall and 2.2 cm inside
VIW
Rubberstopper .. ..
JCapillary
Water level e: tube--
Plexiglass ~ ~ / radius r.tubing f)
--'
1z iScale !'
=- =- == =:z ~ a=..-s:o Q.-:
I)
Figure 7.
o~~. ~~ ,,.w"----.t'a~ h -
. ~' ;,./C'f~'":~~~'~~~~;'~ ~ - z - 2 t / r f gSOlI ~~ ~~~~~ ~core • ~.,,~ ..~.~_••_.,~._":"~,&-~schematic diagram of device for measuring sorptivity withnegative head (Sneg).
54
diameter) and a porous plate of 8 em diameter with l5xlO S
holes per sqaure meter (hole diameter 1.05mm). The upright
Plexiglas tube serves as a water reservoir and sight tube
for measuring cumulative infiltration. A scale is taped to
the Plexiglas tube to read the water level as infiltration
proceeds. Once the sorptivity meter is filled with water
and the stopper at the top is secured, water can move
through the porous plate only if air enters through the
capillary tube. If the capillary tube has a radius of r,
the pressure head h at the bottom of the porous plate at
depth z below the capillary tube is given by
h = z - 2T Cos e/r p 9
Where T is the surface tension of water, dynes/cm2;
P is the density of water, g/cm3;
9 is the acceleration of gravity, cm/sec2; and
e is the contact angle.
The pressure head, h, can thus be changed as
described by either adjusting the height of the capillary
tube above the plate or the inside diameter. In the
sorptivity device used the h value was -11.1 mm with z=3.5
mm and r=l rom (Fig. 7). A thin walled Plexiglas cylinder
10 cm tall and 8 cm in diameter was used to prevent
lateral movement of water and also to act as a support
55
tube. One end of the cylinder is sharpened to act as a
cutting edge and a 2 em-high upper ring section is used to
prevent compaction of soil at the upper end of the
cylinder when the cylinder is pushed into the soil. A soil
column of slightly larger diameter than the cylinder is
carved and the Plexiglas cylinder is inserted into the
soil until the upper edge is about 2 rom below the soil
surface. The upper ring section on the cylinder is then
removed and the excess soil is carefully trimmed to
provide a surface level with the cylinder. Any large
stones or plant material are removed to produce a good
contact with the porous plate. With this procedure a thin
layer of tine sand was not required to ensure good contact
between the porous plate and the soil as proposed by
Clothier and White (1981). A hand level was used to keep
the upper end of the cylinder levelled and soil particles
on the upper edge were removed so that the sorptivity
meter could sit firmly on the cylinder with the porous
plate having good contact with soil surface.
The sorptivity device was filled with water
by submerging it in a ~arge container of water and the
stopper was secured. The meter was then carefully removed
from the water container and placed on the soil column as
shown in Fig. 7. The stop watch was started just before
the device is placed on the soil column and several water
heights versus time measurements were taken during the
56
first 180 seconds. A tape recorder was used so only one
person could handle the entire operation. A soil sample
for antecedent moisture was obtained near to the cylinder.
Sorptivities with negative head were determined as slopes
of cumulative infiltration versus squre root of time for
the measuared antecedent soil moisture content similar to
the Spos measurement (Fig 4). The measured sorptivities
were corrected to 0.30 m3/m3 antecedent moisture content
as shown in Appendix II.
Results and Discussion
The geometric means and the confidence
intervals for sorptivities with negative head, Sneg, for
Molokai soil are shown in Fig 8. Each value corresponds to
the mean of 18 Sneg measurements. The geometric means were
used because Sneg was shown to be log normally
distributed. This is discussed in more detail in Chapter
Four. The figure shows that there is a slight increase in
sorptivity at negative pressure after the first wetting
and arY1ng cycle, followed by a decrease with the next
four wid cycles. Possible reasons for this apparent
increase are discussed later in this section. The analysis
of variance for log Sneg for Molokai soil is given in
Appendix Table 1II-2a. There is a significant difference
among the w/d cycles but not between the two irrigation
levels (main plots). This is because the two irrigation
..-- 1.6 -I .S MOLOKAI SOIL0 I . I I I • IntglG.)
~ I I I I . • Irrtg 2-- --'" I •• - I J".... ., "" o flaodI
1.2 -0C
~ ~.', -- ~- ---11- --r!>~ •
0.8I
n= 00 i~' ii,C/)
•&1
-,
Z0.4
0 1 2 3 .. 5
WID CYCLES
Figure 8. Sorptivity with negative head (Sneg) with sucessive wettingand drying cycles, Molokai soil. Geometric mean ± antilogof 1 SD of log S. ~
58
treatments failed to create two different degrees of
wetting, event hough the higher rate wetted to a greater
depth.
The Duncan's mUltiple range test was carried
out to verify the significant difference among the wid
cycles, and is given in Appendix Table III-2b. There are
no s1gnificant differences between the Sneg before
irrigation and after the first wid cycle. The mean
sorptivities before and after the first wid cycle were
significantly different from the following wid cycles. The
slight increase in Sneg from the pre-irrigation to the
first wid cycle, which is not significant, is consistent
in both main plots. This increase in Sneg may be due to
two possible reasons.
1. Immediately after tillage the soil has many large
pores. These large pores may not conduct water at
the suction imposed by the sorptivity device. As
discussed in Materials and Methods the sorptivity
device was designed with a -11.1 rom air entry value
using a 2 rom diameter capillary tube. At this suction
any pore larger than 1 mm effective radius will not
conduct water, thereby eliminating the very large
pores. Following the first wid cycle, with the
compaction due to soil deformation, many of the
large pores form smaller pores. These may conduct water
59
at the low suction imposed by the sorptivity device,
thereby increasing the Sneg with the first wid cycle.
The following wid cycles compact the soil further,
which reduces the porespace thereby reducing the Sneg
significantly.
2. The measured soptivities were corrected to 0.30 m3/m3
antecedent moisture before making any comparisons among
the treatments using a linear approximation as
discussed in Appendix II. The antecedent moisture
content of the pre-irrigation treatment was
approximately 0.20 m3/m3. Errors in the linear
approxomation of the S(6) relationship are expected to
be greater at low water contents (Chong and Green,
1979; Chong, 1979).
The geometric means and the confidence
intervals (±l SD) for Sneg for Waialua soil are shown in
Fig. 9. Eac value corresponds to the mean of 36 Sneg
measurements. These results shows a decrease in Sneg with
wid cycles. The analysis of variance for these data is
given in Appendix Table rv-2a, and shows a significant
difference in Sneg with wid cycles. The Duncan's multiple
range test (Appendix Table rv-2b) shows that there is a
significant difference among the mean sorptivities before
irrigation and all three wid cycles. There were no
-1.3~S WAIALUA SOIL
0
1.1 ! • 'rrlgQ)
~ o floodE.-.
I0C 0.9
~j> 0.7Ii: •0:: • I0
V) 0.5 I•8Z
0.3 . -0 , 2 3
WID CYCLES
Figure 9. Sorptivity with negative head (Sneg) with sucessive wettingand drying cycles, Waialua soil. Geometric mean ± antilog of1 SD of log S. 0'\
o
61
significant differences among the wid cycles. The Waialua
soil did not show any apparent increase in Sneg from
pre-irrigation to the first wid cycle as observed in
Molokai soil.
These results show that there is a decrease
in Sneg with compaction by wid cycles. The most reduction
was w1th the first and the second wid cycles which was
responsible for the most compaction among the wid cycles.
Sneg for Molokai soil decreased by an average of 40% and
for Waialua soil by 38%.
A comparison of measured Spos and Sneg was
made for both the soils. The sorptivities measured by both
methods for Irrig 1 main plot for Molokai soil are shown
in Fig. 10. The same data for Waialua soil are shown in
Fig. 11. Sorptivity with negative head is always lower
than sorptivity with positive head for both the soils.
Sneg measurement was done with a low negative head (14.5
rom ot water) and water did not enter the large voids
during this measurement as in the Spos. The suction of the
sorptivity meter was maintained at a low level so that it
would not exclude macropores which are representative of
the soil matrix; water was prevented from entering only
the very large voids (> 1 rom radius). Therefore, changes
in macroporosity due to compaction with wid cycles were
still reflected in the Sneg measurements.
Sneg of Molokai soil showed an apparent
2.4 MOLOKAI SOIL,.-...• S (pos)S
0 • • S (neg)Q)
~ 1.9 <,E'"I ....-:~.-0 1.4 •v •. " •~ . " ,> ." .~ 0.9 .........
-e- - - -e~ - - - ·~
0Vl
0.44 50 1 2 3
WID CYCLES
Figure 10. Sorptivity with positive head (SHOS) and with negative head(Sneg) with sucessive wetting ana drying cycles, Molokai soil.Geometric means.
C7\N
,.... 1.SJ • WAIALUA SOILS • Spas
0Q)
1.5 '"e S neg
~E
fI)
I 1.20v ••~
,0.9 ,
.~>
, •.... •fi: ............0.6 --__ e
et:: - -e· - - - - __0(J)
0.3 .0 1 2 3
WID CYCLES
Figure 11. sorptivity with positive head (Spos) and negative head(Sneg) with sucessive wetting ana drying cycles,Waialua soil. Geometric means.
0\W
64
increase from pre-irrigation to the first wid cycle. This
was consistant in both the mainplots. Sneg for Waialua
soil did not show this increase but decreased rapidly with
the first wid cycle. Waialua soil being a vertic soil, may
undergo more deformation and compaction with the first wid
cycle. In Molokai soil the compaction due to wetting and
drying was less than the Waialua soil and had to undergo
many wid cycles before the soil was completely compacted.
During the intermediate stages there was an apparent
increase in Sneg as the very large pores in the
pre-irrigation treatment formed smaller conductive pores
which conducts water under the suction level imposed.
Clothier and White (1981), comparing the two
sorptivity methods, showed that ponded sorptivity, Spos,
gave a nigher value with a higher standard deviation. They
showed soil water diffusivities could be calculated using
Sneg measured when wetting front advance was also
measured. RuSSO and Bresler (l980b) showed that sorptivity
could be used to predict the variability of other soil
hydraulic properties which are more difficult to measure.
The added advantages of using the Sneg is
that it uses less water (0.16 liters) than the Spos method
(15 liters) and the apparatus is easy to carry into a
large field to characterize soil hydraulic properties.
This will be dealt with more detail under the second
objective in Chapter Three.
65
Hydraulic Conductivity
Hydraulic conductivity is the flux of water
per unit hydraulic gradient. Hydraulic conductivity as a
function of water content or suction is essential for
modeling soil water and solute movement. Insitu
measurements are generally preferred if resources are
available to conduct field measurements.
Materials and Methods
Hydraulic conductivity as a function of
volumetric water content and soil water suction was
measured at two depth increments, 0-5 cm and 0-25 cm,
using the simplified unsteady drainage flux method (Green,
Ahuja and Chong, 1984). This method was first proposed by
Nielsen at ale (1973) and then simplified by Chong (1979).
The reliability of this method has been demonstrated by
Libardi et ale (1980).
The simplified unsteady drainage flux
method calculates K(e) using only the experimental results
obtained from periodic measurement of water content (6) as
a function of depth (z) and time (t) during the water
redistribution period. It calculates K(h) using only the
experimental results obtained from e(z,t) and h(z,t)
measured during the redistribution period subsequent to
steady infiltration. The method assumes negligible
horizontal flow in the evaluated soil layer and unit
66
hydraulic gradient during drainage. With these assumptions
and in the absence of evaporation, Neilsen at ale (1973)
showed that the rate of change in average water contents
in the soil profile can be used to calculate K(6) as shown
below.
K(8)L = -L de/dt ••••••••••••••• (1)
Where L is the soil depth under consideration, cmi
K(e) Hydraulic Conductivity at depth L, cm/mini
e average water content of the soil profile to
depth L, cm3/cm3~
t time, min.
Chong (1979) refined the simplified method to
allow calculation of hydraulic conductivity at water
contents higher or lower than those measured during
drainage by developing a mathematical expressions which
adequately described 0 and h versus time during drainage.
Following Richards et ale (1956) and Gardner et ale (1970)
he assumed that water content during the redistribution
process subsequent to steady infiltration diminished with
time in a manner that could be described by the power
function
be = at •••••••••••••••• (2)
where e is volumetric water content, cm3/cm3 ;
t is time, min;
a and b are constants.
67
It was also assumed that soil water suction
during this time can be expressed as a power function of
time, that is
nh = mt •••••••••••••••••• (3)
Where h is soil water suction, cm of water;
t is time, min;
m and n are constants.
These are applicable starting from field
saturated water contents and the air entry pressure value.
By sUbstituting (2) to (1) equation (4) is obtained.
(b-l)K (t) = -L a b t •••••••••••••••• (4)
Here hydraulic conductivity is expressed
as a tunction of time with t=O corresponding to the
begining of the drainage cycle after steady infiltration.
By sUbstituting (2) into (4) hydraulic conductivity is
expressed as a function of soil water content.
(l/b) (b-l) /bK(a) = -Lba a
68
•••••••••••••• (5)
Therefore, hydraulic conductivity as function
of volumetric water content of the soil profile at depth L
can be calculated using (5) for a wide range of water
contents if constants a and b are known. Similarly if (3)
is substituted into (4) we get
-(b-l)/n (b-l)/nR(h) = -Labm h •••••••••• (6)
Equation (6) can be used to calculate
hydraulic conductivity as a function of soil water suction
if the constants a,b,m and n are known. When using the
simplified method to calculate K(a) or K(h) the upper
boundary has to be always the soil surface because when
calculating (da/dt)L, a is the average water content from
z = 0 to z = L. Therefore K(a) or K(h) cannot be
calculated for each depth increment as in detailed Darcian
analysis but for each total depth increment from the soil
surface.
Hydraulic conductivity as a function of
volumetric soil water content and soil water suction was
measured using the simplified drainage flux method after
saturating the soil profile by ponding. These were
measured for two depth increments, 0-5 cm (depth 1) and
0-25 cm (depth 2). The soil profile was first saturated
using a single ring infiltrometer. The 0.3 m diameter and
69
0.46 m tall metal infiltration rings were driven 0.35 m
deep into the ground using a driving plate and a sledge
hammer. These were installed with care to cause minimum
disturbance. A hand level was used to keep the rings
levelled so it could penetrate uniformly. After driving to
the desired depth a hand tool was used to compact the
loose soil adjacent to the ring.
A mUltiple depth tensiometer was installed at
the center of the ring to measure soil water suctions
during the drainage cycle. A 2.5 cm diameter screw auger
was used to make a hole down to 30 cm depth from the soil
surface. The mUltiple depth tensiometer was installed
locating the porous cups at 5 cm and 25 cm from the soil
surface. A thin slurry of soil was used to achieve good
contact between the porous cup and the soil profile. Thin
steel pins were inserted vertically into the soil with
only the top 3 cm extending above the soil surface. These
provided a reference level at which the water surface was
maintained until a steady rate was observed. The total
period of infiltration was about 4-5 hours. The measured
steady infiltration rates for Molokai and Waialua soils
are given in Appendix Table 111-3 Table IV-3 respectively.
Subsequent to the steady infiltration water supply was cut
and the zero time for redistribution corresponded to
the time when water in the ring had just disappeared from
the ground surface. Soil water content at each depth was
70
gravimetrically obtained from soil samples taken at 1,3,6
and 18 hours, and at each 24 hour period thereafter for
6-7 days. Volumetric water contents were calculated from
gravimetric water content using bulk density data obtained
from the same plot. This is discussed in detail in a later
section.
The soil water suction during the
redistribution period was obtained from the multiple depth
tensiometer readings. This was measured every few minutes
initially to daily for 6-7 days. During the redistribution
period the soil surface inside the ring was covered with a
plastic sheet to prevent any evaporation. The black
plastic roof over the plot prevented rainwater from
entering the ring. The hydraulic conductivity functions,
K(D) and K(h) were calculated using Equations (5) and (6)
respectively. The constants a and b of Equation (2) and m
and n or Equation (3) were obtained by converting the
power functions to linear form by logarithmic
transformation. When calculating a and b using Equation
(3) for the 0-25 cm depth, the weighted average water
content from 0-5 and 5-25 cm was used. Eventhough this
method assumed unit hydraulic gradient, the gradients for
5-25 cm depth increment were obtained using the
tensiometer readings. The measured gradients during the
measurement period varied from 0.78 to 1.38 m1m for the
Molokai soil and from 0.72 to 1.53 rn/m for the Waialua
71
soil. The calculated conductivities for 0-25 cm depth
increment were corrected by dividing the K(9) or K(h)
calculated with unit gradient by the measured hydraulic
gradient as shown by Chong et ale (1981). Unit hydraulic
gradients were assumed for the 0-5 cm depth increment as
it was a well drained layer.
Results and Discussion
The calculated a and b values using equation
(2) for the 0-5 cm depth and 0-25 cm depth for Molokai
soil are given in Table 1. The calculated m and n values
using equation (3) for the 0-5 cm depth and 0-25 cm depth
for Molokai soil are given in Table 2. The same parameters
for tha Waialua soil is given in Table 3. These are
average values for three measurements for Molokai soil and
six measurements for Waialua soil.
Hydraulic conductivity as a function of volumetric water
content, K(6)
The geometric means of K(S) calculated using
Equation (5) for a wide range of water contents for
Molokai soil for depth one and two are given in Appendix
Tables 1II-4a and 1II-4b. The same for Waialua soil is
given in Appendix Table rv-4. These were calculated with
em/min units and converted to appropriate m/sec units. As
both the irrigation main plots for Molokai soil showed
72
Table 1. Calculated a and b values (Eq. 2) for Molokai
soil for 0-5 ern and 0-25 ern depths (units: crn,
min) •
Treatment
WID Cycles a
Irrig 1
b
0-5 em depth
a
Irrig 2
b
0 0.479 -0.072 0.430 -0.075
1 0.523 -0.056 0.532 -0.061
2 0.607 -0.069 0.598 -0.071
3 0.720 -0.105 0.735 -0.075
4 0.630 -0.079 0.801 -0.112
5 0.820 -0.110 0.501 -0.035
0-25 em depth
0 0.729 -0.103 0.619 -0.072
1 0.660 -0.081 0.709 -0.082
2 0.678 -0.079 0.622 -0.078
3 0.690 -0.084 0.576 -0.058
4 0.666 -0.073 0.546 -0.067
5 0.589 -0.067 0.748 -0.091
73
Table 2. Calculated m and n values (eq , 3) for Molokai
soil for 0-5 cm and 0-25 cm depths (units: em,
min) •
Treatments
WID Cycles m
Irrig 1
n
0-5 em depth
m
Irrig 2
n
0 -14.320 0.312 -13.980 0.325
1 -1.670 0.558 -2.020 0.585
2 -2.230 0.501 -2.510 0.490
3 -0.982 0.572 -2.150 0.592
4 -0.490 0.766 -3.480 0.465
5 -0.323 0.790 -0.901 0.613
0-25 em depth
0 -1.040 0.660 -3.850 0.439
1 -1.500 0.495 -0.440 0.774
2 -0.509 0.703 -1.170 0.643
3 -1.660 0.577 -0.643 0.639
4 -1.510 0.463 -0.365 0.731
5 -0.365 0.731 -0.368 0.730
74
Table 3. Calculated a, b (Eq.1) m and n values (Eq.2) for,Waialua soil. 0-5 em and 0-25 em depths (units:
em, min).
Treatments
WID Cycles
a b
Depth 1 (0-5 em)
m n
o
1
2
3
0.602
0.745
0.707
0.771
-0.061
-0.064
-0.054
-0.062
-2.320
-0.033
-0.598
-0.604
0.460
0.760
0.410
0.710
Depth 2 (0-25 em)
o
1
2
3
0.664
0.650
0.710
0.680
-0.043
-0.038
-0.041
-0.039
-0.576
-0.301
-0.137
-0.410
0.607
0.695
0.701
0.782
75
similar results, K(e) as a function of 0 for 0-5 cm depth
and 0-25 cm depth for only Irrig 1 main plot are shown in
Figures 12 and 13 respectively. The K(O) as a function of
o for Waialua soil for 0-5 cm and 0-25 cm depths are shown
in Figures 14 and 15 respectively.
The K(e) results for 0-5 cm depth for both
the soils show that there is a decrease in hydraulic
conductivity with w/d cycles. The first wid cycle was the
most effective in decreasing K(O) than the following w/d
cycles. The results for the 0-25 cm depth also show a
reduction of Kce) with w/d cycles, but to a lesser extent
in MOloKai soil compared to the 0-5 cm depth. In Waialua
soil the 0-25 cm depth also showed reduction of K(e) with
wid cycles. In Waialua soil compaction due to wetting and
drying was evident even in the lower depths.
Hydraulic Conductivity as a Function of Soil Water
Suction, K(h)
The geometric means of K(h) as a function of
h calculated using equation (6) for a wide suction range
for Molokai soil for 0-5 cm and 0-25 cm depths are given
in Appendix Tables III-Sa and 1II-5b. The same for Waialua
soil is given in Appendix Table IV-5. These were
calculated in units of em/min and converted to appropriate
m/sec units. The K(h) as a function of h for Molokai soil
for both the depths for Irrig 1 mainplot are given in
76
0.35 0....0 0.45 0.50WATER CONTENT (m!1m3
)
o
---cycl.O---cycle'- - - cycle 2
- cycle 3-------•. cycle .................... cycle 5
MOLOKAI SOIL
/1/
//
/ ,'!!'
/~~/
7.·..';II ••-
~' ..I ",/ .....
//,,'/ .····5" / ...., .." ~ ...•
A,,~...
" ,., .'~ ..~r #// ..),~....:;;f/2
.·····,7/..- "..' ,//.. ,,/t/
10-·::;;;a..""r-U-----.----__---.,----......0.30
Figure 12. Hydraulic conductivity as a functionof volumetric water content, Molokaisoil. 0-5 cm depth.
MOLOKAI SOIL
---cycle 0---cycle'- - - cycle 2
- cycle 3--------. cycle 4---cycleS
0.35 0.40 0.045 0.50WATER CONTENT (m!/m!)
.'.'.'.'.'.'.'.'.'.... ~.....~.""'.,'.. "...-;~ "
/'.. ", ~ ",.' /' - ~,
.~. ,..-., ~ ~",...-/ '/ "..~~ ,~~",
«:/: /,'/. / ",
1'// ",LI/ ",~~. "
o {/h: / ""/.. / "/~/ "
~. ,.' ,
0 ,'., ,,. ...., "3.V "5:"2 ",,,,4'
lO-'~r------r-----r------.-----.0.30
Figure 13. Hydraulic conductivity as a function ofvolumetric water content, Molokai soil.0-25 cm depth.
77
WAIALUA SOIL
cycle 0
---cycle 1
- - ._. cycle 2
cycle 3
o
78
0.35 0.40 0.045 0.50WATER CONTENT (m3/m3
)
10-12~~__..,...-_---r------,...--~
0.30
Figure 14. Hydraulic conductivity as a function ofsoil water content, Waialua soil.0-5 cm depth.
WAIALUA SOIL
----cycle 0---cycle'- - - -cycle2----cycle 3
o
79
0.30 0.35 O.OW 0.45 0.50WATER CONTENT (m3/m3
)
Figure 15. Hydraulic conductivity as a function ofsoil water content, Waialua soil.0-25 cm depth.
80
Figures 16 and 17 respectively. The Irrig 2 main plot gave
similar results, as shown in Appendix Tables III-Sa and
1II-5b. The K(h) relationship for Waialua soil for both
the depths are shown in Figures 18 and 19. These results
show that there is a decrease in hydraulic conductivity up
to 1 to 1.5 m soil suction with wid cycles for the 0-5 cm
depth for both the soils. The effects of wetting and
drying on K(h) is greater at lower suctions and diminishes
at suctions of 1 to 1.5 m. The reduction in K(h) is
greatest with the first wid cycle. This is due mainly to
soil compaction with wetting and drying which reduces the
macropores that carry more water at low soil water
suctions. The hydraulic conductivity of the compacted soil
(after wid cycles) tends to increase for suctions beyond 1
to 1.5 meters of water. With compaction the macropores
form micropores which may increase the conductivity at
higher soil water suctions. Bodman and Constantin (1965)
showea that compaction and settling reduced the gross
porespace and also caused a new frequency distribution of
effective poresizes. Jamison (1953) showed that compaction
decreases water held at low suctions in large voids and
increases water held at higher suctions in the additional
small voids created. The cross over point depends upon the
particle size distribution and the structure of the soil.
Warkentin (1971) also reported that the amount of water
held at higher suctions increases with increasing soil
0.1 1 2 .4SOIL WATER SUCTION (m of H 0)
2
MOLOKAI SOIL
cycle 0
cycle 1
cycle 2
cycle 3
cycle 4
cycle 5
10-1~OM-"..-r''T"'T'"---r--r---r-l'"""'T'....,...,.,..,..--.,-----,.---,r---,
0.05
Figure 16. Hydraulic conductivity as a function ofsoil water suction for sucessive wettingand drying cycles, Molokai soil. 0-5 emdepth.
81
82
·410
\4-,,,,,,,,,,,,,,,,,,,,,,
MOLOKAI SOIL
cycle 0CYCLE 1
cycle 2
cycle 3
cycle 4
cycle 5
Figure 17. Hydraulic conductivity as a function ofsoil water suction suction for sucessivewetting drying cycles, Molokai soil.0-25 cm depth.
0.1 1 2 4SOIL WATER SUCTION (m of H 0)
2
10-5
WAIALUA SOIL
cycle 0-- cycle 1
cycle 2cycle 3
'0'C1)
~..srI-
>t; "" ""~Q ""Z ""0uU...J~4:0::QrI
10-10
1O-1~1--,-~~---r---'1r--"'--r-T-r--lI"'TT---r--..,--'1"--'
0.05
83
Figure 18. Hydraulic conductivity as a function ofsoil water suction for sucessive wettingand drying cycles, Waialua soil. 0-5 cmdepth.
WAIALUA SOILcycl.O
-- cycl.'cycl.2cycJe3
0.1 1 2 4SOIL WATER SUCTION (m of H 0)
2
10-1-1° ~T'"T'"rT---r----r---T--r-r-1I""T"T...,...----r--r-~0.05
Figure 19. Hydraulic conductivity as a function ofsoil water suction for sucessive wettingand drying cycles, Waialua soil. 0-25 cmdepth.
84
85
compaction. These results and the water retention results
obtained by us (given in a later section) show that
eventhough compaction decreases the total porosity it
increases the relative proportion of micropores which hold
and conduct water at high suctions. It should be' noted
that even though compaction of tilled soils causes an
increase in hydraulic conductivity at higher suctions,
these K(h) values are very low.
Figures 17 and 19 show that there is a
decrease in K(h) values with wId cycles for the 0-25
depth, in some treatments. But these reductions are not so
evident as for the 0-5 cms depth.
Since the hydraulic conductivity varies with
soil water suction and volumetric water content, the K(e)
and K(h) relationships can be conveniently represented by
parameters in mathamatical expressions. The parameters of
these equations could be used as indices of hydraulic
properties of soils (Bresler and Green, 1982). An attempt
was made to use these parameters to characterize the
temporal changes of K(e} and K(h) functions.
Many mathematical expressions have been used
by investigators to relate hydraulic conductivity to soil
water suction and water content (Brooks and Corey, 1964~
Philip, 1968~ Campbell, 1974~ Bresler, 1978~ Russo and
Bresler, 1980a, 1980b~ Warrick et al., 1981). Most of
these expressions are empirical in nature and therefore
86
the selection of the functional form to use depends mainly
on the goodness of fit between measured data and the
mathematical expression.
Three equations proposed by Bresler and Green
(1982) were tested for the goodness of fit for the
measured data for the two soil series. These equations and
their linearized forms are given in Table 4. Parameters ~,'t
and ~ for these 3 equations calculated using the measured
K(e) and K(h) for both the soils and their correlation
coefficients are given in Tables 5, 6 and 7. The results
show that out of the three equations, Equations (8) and
(9) show a better fit for the results with a R2 value of
0.9 or higher. The high R2 for the two power functions (8)
and (9) are consistent with the power form of K(e) and
K(h) data reSUlting from the simplified drainage flux
method. Equation (7) an exponential function would not be
expected to fit this data as well. The parameter ~ of
Equation (8) is actually the slope of log K(h) vs log (h)
as shown in Figures 17 to 20 for both the soils used.
Therefore this parameter was used to examine the response
of hydraulic conductivity as a tunction of soil water
suction at sucessive wid cycles. The analysis of variance
for parameter 1 for Molokai soil for 0-5 cm depth is given
in Appendix Table 1II-6a. There is a significant
difference of parameter ~ with wid cycles. There is no
significant difference between the two irrigation main
87
Table 4. Equations relating hydraulic conductivity (K) to
soil water suction (h) or w~ter content (e).
Eq. Equation Linearized Form
(7) K/K = Exp (0'( h-h().) Ln(K) =och- (oChQ.-LnKs)s
( 8) K/KsttL
= (ha /h) Ln(K) = -~Ln h+(lLn ha +LnKs)
( 9) K/Ks'6
Ln(K)=~Ln(e-er/es-er)+Ln Ks= [(S-er)/ (8s-8r)]
KS = saturated hydraul ic conductivity
ha = Air entry val ue
ti, '7' ~ = Constants.
Table 5. Parameters for three hydraulic conductivity
equations (Eq. 7,8,9) fitted to K(h) and K(e)
for Molokai soil.
88
Treatments Eq. 7 ~. 8 Fq. 9
WID Cycles 0(. R2 1 R2 'ls' R2
Irrig 1
0 3.32 0.76 3.43 0.99 14.88 0.99
1 1.83 0.77 1.89 0.98 18.86 0.98
2 2.01 0.75 2.13 0.98 15.49 0.97
3 1.81 0.74 1.93 0.97 10.53 0.99
4 1.32 0.75 1.40 0.99 14.29 0.98
5 1.35 0.75 1.41 0.99 11.39 0.99
Irrig 2
0 4.02 0.81 3.30 0.99 14.33 0.99
1 2.20 0.80 1.82 0.99 17.39 0.98
2 2.66 0.78 2.19 0.98 15.08 0.98
3 2.20 0.78 1.82 0.99 14.33 0.97
4 2.90 0.76 2.39 0.97 10.97 0.99
5 2.05 0.81 1.69 0.99 19.57 0.96
89
Table 6. parameters for three hydraulic conductivity
equations (Eq. 7,8,9) fitted to K(h) and K(8) for
Molokai soil. 0-25 em depth (units: m/sec and m).
Treatment Eq. 7 Eq. 8 Eq. 9
WID eycl es oc R2 ~ R2 R2
Irrig 1
0 2.81 0.81 2.31 0.99 10.71 0.98
1 2.28 0.79 1.87 0.98 13.35 0.99
2 2.03 0.76 1.67 0.99 13.65 0.98
3 1.77 0.81 1.46 0.98 12.91 0.99
4 2.56 0.74 2.10 0.99 14.09 0.98
5 1.77 0.80 1.64 0.98 15.92 0.98
Irrig 2
0 2.40 0.75 2.62 0.95 14.88 0.99
1 2.25 0.88 1.40 0.99 13.19 0.98
2 2.83 0.83 1.68 0.98 13.82 0.99
3 2.80 0.76 1.66 0.99 18.24 0.98
4 2.47 0.81 1.46 0.97 15.92 0.99
5 2.57 0.80 1.49 0.99 12.07 0.98
90
Table 7. Parameters for three hydraulic conductivity
equations (Eq. 7,8,9) fitted to K(h) and K(e) for
waial ua soil. 0-5 em and 0-25 crn depths (units:
rn/sec, m) ,
Treatment Eq. 6 Eq. 7 Fq. 8
WID Cycles oC R2 "l R2 R2
Depth 1 (0-5 em)
0 1.83 0.76 2.31 0.98 17.36 0.99
1 1.11 0.75 1.40 0.99 14.70 0.98
2 1.15 0.72 1.37 0.99 20.39 0.99
3 0.72 0.78 1.14 0.96 17.13 0.98
Depth 2 (0-25 em)
o
1
2
3
1.370.76
1.18 0.75
1.17 0.76
1.05 0.78
1.76 0.99
1.49 0.98
1.47 0.96
1.33 0.98
24.24
25.45
23.55
24.80
0.99
0.98
0.97
0.96
91
plots. The analysis of variance for parameter~ for 0-25
cm layer did not show any significant difference between
irrigation main plots or among wId cycles.
The analyses of variance for parameter ~ for
Waialua soil for the 0-5 cm is given in Appendix Table
rv-6a. There is a significant difference among the wId
cycles for the 0-5 cm depth. The parameter 1 for 0-25 cm
depth layer does not show any significant difference among
the wId cycles. These results show that the decrease in
hydraulic conductivity in the upper layers of soil is more
pronounced than in the lower layers of soil with wId
cycles. Similarly the parameter ~ of Equation (9) was used
to evaluate the decrease in K(e) with wetting and drying
cycles. The calculated ~ values is the slope of log K(e)
vs. log e/es relationship. The analysis of variance
failed to show any significant difference for the
parameter ~ at any depth for either soil. This may be due
to the higher variability of the calculated K(&) values.
Soil Water Retention Data
The soil water retention data show how water
is released with applied suction. These data are obtained
in the laboratory, using core samples over a large suction
range imposed by a tension table and a pressure plate
apparatus. Insitu measurements can be obtained with
tensiometers and gravimetric soil sampling for a narrow
92
suction range. The field soil water retention curve is
used to estimate soil water contents using tensiometer
readings. The laboratory water retention data are used
primarily to characterize the poresize distribution of
soil. Soil water retention can be used to estimate the
hydraulic conductivity function when it is not readily
available (Campbell, 1974; Green and Corey, 19711
Millington and Ouirk, 1959;).
Materials and Methods
Soil water retention was measured in the
laboratory using undisturbed soil core samples as
described by Green et ale (1981). Duplicate soil core
samples were removed from 0-7.5 cm depth and from the
middle of 5-25 cm (6.8 cm to 13.3 cm) layer. A soil column
larger than the core was carved, and a brass core cylinder
9.8 cm in diameter and 7.1 cm high was pressed into the
soi11 a 1.5 cm high cylinder with a sharpened cutting edge
was taped to the bottom of the core cylinder to minimize
soil compaction. A 2-cm high brass cylinder was placed on
top end of the core to allow trimming. THe core samples
were wrapped with polyethylene films to prevent drying in
the field.
Prior to water retention measurement, excess
soil on each end of the soil core was carefully trimmed to
be level with the end of the brass ring. One end of the
93
brass ring was then covered with a gauze cloth securing
with a rubber band, for repeated weighing during the
process without loss of any soil. Each core was then
fitted to a porous ceramic plate (with an air entry value
of about 10 m water suction) which is connectd to a
hanging water column. A fine layer of soil was used to
provide better contact between the plate and the sample.
The soil sample was then saturated by leveling the hanging
water column with the sample. The water content at
saturation was approximated as 85% of the total porosity
calculated by using the bulk density (Green et al., 1981).
Thereafter the soil core was equilibrated with water at
suctions of 10, 25, 50, and 100 cm of water. After
equilibrating at each suction the core was removed and
weighed to obtain the gravimetric water content. After the
100 cm of suction the samples were removed to a standard
pressure plate apparatus. Water retention measurements
were made at suctions of 150, 200, 300, 400 and 500 cm of
water by equilibrating at each suction and weighing the
sample. The soil core was oven dried at 105 0 C and weighed
after the final pressure step to get the dry weight and
bulk density as discussed later. Bulk density of each core
was used to convert the gravimetric water contents to
volumetric water contents at each suction level.
94
Results and Discussion
The laboratory-measured soil water desorption
data for both the depths for Molokai soil are given in
Appendix Tables 1II-7a and 1II-7b. These are averages of
six core samples. As the Irrig 1 and Irrig 2 main plots
for Molokai soil showed similar results, the soil water
desorption curve for only the 1rrig 1 main plot for 0-5 cm
and 5-25 cm are shown in Figures 20 and 21 respectively.
The figures include only the data for pre-irrigation, and
the first and fifth wid cycles to show the changes more
clearly. The soil water desorption curve for Waialua soil
for both the depths are shown in Figures 22 and 23. Each
value corresponds to the mean of six water retention
measurements. The results for 0-7.5 cm depth for both the
soils show that there is a decrease in soil water
retention at low suction levels with wid cycles. This is
due to compaction of soil with wid cycles which reduces
the macropores, resulting in a decrease in water held at
low suctions. The soil water content at high suctions is
slightly more after wid cycles than before irrigation with
the cross over point around 2 to 3 meters of soil water
suction. This is due to increase in water content at
higher suctions in the additional small voids which have
been formed as a result of compaction from wid cycles.
Jamison (1953) showed that the magnitude of increase and
decrease of water retention with compaction and the
0.6-1 MOLOKAI SOIL,......"
~• c~cle 0
1ft
~• c~cle1
1ft o cycle 5~ 0.5
~ ,~
~'q" ,,,~
0 "U 0.4 ""0:= "''',~
0" ~........
~ 0-···· =--=-=-=- - - Ii - - ---.._-. ~. -.- -_..--_...
0.30 1 2 3 4- 5
SOIL WATER SUCTION (m of H 0)2
Figure 20. Soil water retention curve with sucessive wetting anddrying cycles for Molokai soil. 0-7.5 cm depth.
\DU1
0.55 -t MOLOKAI SOIL
~ 0.501~ • e,el.O
• elel. ~
o elel.,
S~ 0.45
~Z8 0.40
~
~ 0.35~
0.30 .0 1 2 3 4 5
SOIL WATER SUCTION (m of H 0)2
Figure 21. Soil water retention curve with sucessive wetting and dryingcycles for Molokai soil. 7.5-25 cm depth. \0
0\
0.55 -i WAIALUA SOIL
~ O.50~~• erel• O
• e,el. I
o e,el.3
g.... 0.45Z~Z
0.40au0:~ 0.35 I
~....,-....-..........
0.30 I .0 1 2 3 4 5
SOIL WATER SUCTION (m of H 0)2
Figure 22. Soil water retention curve with sucessive wetting and dryingcycles for Waialua soil. 0-7.5 cm depth.
\0-..J
---._------€)-----_.._-~
• eyel._ 0
• eyel_ 1
o ~rel- 3
~
"'E 0.475
~~~ 0.425
~8et:: 0.375
~~
WAIALUA SOIL
- -- - - _....I I0.325 I I I I I Io 1 23 ..
SOIL WAfER SUCTION (m of H 0)2
5
Figure 23. Soil water retention curve with sucessive wetting and dryingcycles for Waialua soil. 7.5-25 cm depth. \D
ex>
99
position of the crossover point depends upon the
particle-size distribution and the structure. Voorhees
(1978) showed a similar effect using water retention
curves for wheel tracked and nontracked soils for a Aquic
haplustoll. Canarch et ale (1984) using induced compaction
by wheel traffic showed how the soil water retention at
low suctions decrease with increased compaction. By using
a Typic Vermustoll they showed that at or around pF=3 the
crossover occured and the water retention increased beyond
this suction level with compaction. The water retention
results for 5-25 cm does not show the impact of compaction
as much as for 0-5 cm depth.
Bulk Density and Porosity
Bulk density is the density of soil insitu
and is usually measured by undisturbed soil core samples.
Bulk density measurements are used to convert gravimetric
water contents to volumetric water contents and to obtain
the total porosity values using particle density. Tillage
generally tends to decrease bulk density and increase the
total porosity of the surface soil. At the same time the
soil just below the plowed layer may increase in bulk
density by the stress applied by tillage machinery.
100
Materials and Methods
Bulk densitiy was obtained from the core
sample used for soil water retention measurements. The
soil cores were oven dried after the final water retention
measurement. The dry soil mass was divided by the core
volume (579 cm3) to obtain the bulk density. The total
porosity(E} was calculated using the bulk densitY(Pb} and
particle density(pp} by the relation E = l-(Pb/Pp}. A
particle aensity value of 2.93 g/cm3 was used for Molokai
soil (Chong, 1979) and 2.65 g/cm3 was used for the Waialua
soil as no specific data is available.
Macroporosity is the part of total porosity
comprised of the largest pores. In this study
macroporosity was calculated as the difference between
total porosity and the volumetric water content at 100 cm
water suction.
Results and Discussion
The measured bulk density, total porosity and
macroporosity for both the Molokai and Waialua soils are
given in Tables 8 and 9, respectively. These are averages
of S1X core samples. These results show that there is an
increase in bulk density in the 0 to 7.5 em depth with wid
cycles. The total porosity, microporosity and
macroporosity for Irrig 1 main plot, 0 to 7.5 cm and 5 to
25 cm depth of Molokai soil are shown in Figures 24 and 25
Table 8. Temporal variability of bulk density, porosity
and macroporosity of Molokai soil. 0-7.5 em and
7.5-25 em depths.
Wetting/Drying Cycles
101
Pre-irrig 1 2 3 4 5
Irrig 1 0-7.5 em depth
Bulk Density 0.950 1.160 1.158 1.180 1.190 1.200
Total Porosity 0.678 0.607 0.607 0.602 0.597 0.593
Macro Porosity 0.218 0.180 0.177 0.179 0.186 0.179
Irrig 2
Bulk Density 0.960 1.170 1.172 1.180 1.190 1.188
Total Porosity 0.675 0.603 0.600 0.602 0.600 0.597
Macro Porosity 0.255 0.179 0.180 0.182 0.187 0.180
Irrig 1 7.5-25 em depth
Bulk Density 1.120 1.171 1.160 1.170 1.160 1.170
Total Porosity 0.620 0.603 0.605 0.603 0.610 0.601
Macro Porosity 0.192 0.183 0.184 0.183 0.182 0.180
Irrig 2
Bulk Density 1.130 1.180 1.180 1.181 1.178 1.190
Total Porosity 0.617 0.601 0.602 0.600 0.602 0.597
l-1aero Porosity 0.191 0.180 0.181 0.180 0.185 0.182
102
Table 9. Temporal variability of bulk density, porosity
and maeroporosity for Waialua soil. 0-7.5 em and
5-25 em depths.
Wetting/Drying Cycles
Bulk density
Total Porosity
Macro Porosity
Bulk density
Total Porosity
Macro Porosity
Pre-irrig
1.010
0.619
0.231
1.140
0.570
0.195
1
0-7.5 em depth
1.170
0.558
0.198
5-25 em depth
1.160
0.562
0.192
2
1.150
0.566
0.197
1.157
0.561
0.190
3
1.190
0.551
0.196
1.170
0.558
0.191
0.8-1 MOLOKAI SOIL~ totalm micro
,-.. I IllB8 macroIII -
~ 0.6
'"g~ 0.4(/)00::0 0.2a..
0.0 I I >'
o 1 2 3WID CYCLES
4 5
Figure 24. Total porosity, microporosity and macroporosity changeswith sucessive wetting and drying cycles for Molokaisoil. 0-7.5 cm depth.
....,oeN
"......If)
~If)g~If)o0::oa..
0.8
0.6
0.4
0.2
0.0 I l ~
MOLOKAI SOIL~ total~ microm macro
o 1 2 3
WID CYCLES " 5
Figure 25. Total porosity, microporosity and macroporosity changeswith sucessive wetting and drying cycles for Molokaisoil. 7.5-25 cm depth.
....o~
105
respectively. Similar data for Waialua soil are shown in
Figures 26 and 27. The increase in bulk density values in
o to 7.5 cm depth with wid cycles is reflected in the
decrease of the total porosity values. Figures 24 and 26
show that the decrese in total porosity is due mainly to
a reduction in macropores. Klute (1982) documented that
tillage operations modify the bulk density and poresize
distribution of the soil. These soil physical properties
essentially determine the soil hydraulic properties.
The 5 to 25 cm depth for both the soils also
shows some reduction in the porosity with wid cycles .but
not as much as for 5 to 25 cm depth. The soil hydraulic
properties discussed earlier are related to the porosity
and poresize distribution of soil. The high values for
most of these properties in freshly tilled soils is due to
high macroporosity at that time. With wetting and drying,
soil compaction takes place, which reduces the
macroporosity of the freashly tilled soil thereby causing
temporal variability of soil hydraulic properties.
Aggregate Size Distribution Before Irrigation
The dry aggregate distribution was
characterized for both the soils immediately after tillage
before subjecting the soil to any wetting and drying. The
dry aggregate size distribution was only used to
characterize the initial soil condition of the experiments
0.8-1 WAIALUA SOIL ~ total~ mIcro
,-.... I elm macro'"~ 0.6
'"g~ 0.4Vl00::
~ 0.2
0.0 I " »y-<
o 1 2
WID CYCLES3
Figure 26. Total porosity, microporosity and macroporosity changeswith sucessive wetting and drying cycles for Waialuasoil. 0-7.5 cm depth.
~o0'1
~
~II)s~V)oa:=oa.
0.8
0.6
0.4
0.2
0.0 I r"u
o
WAIAWA SOIL
1 2
W!D CYCLES
rzzJ total~ mIcro_ macro
3
Figure 27. Total porosity, rnicroporosity and rnacroporosity changeswith sucessive wetting and drying cycles for waialuasoil. 7.5-25 crn depth. ....o
"
108
and will differ according to the tillage implement used,
the soil moisture content at the time of tillage and on
the tillage history of the site.
Materials and Methods
The dry aggregate size distribution was
measured as described by Kemper and Chepil (1965) using a
rotary sieving technique. Soil from a 30 cm by 30 cm area
down to 5 cm depth was removed from each main plot. These
samples were sieved at 150 cycles per minute for five
minutes, using a rotary sieve machine which consist of six
concentric sieves bolted together so that seven dry
aggregate sizes could be separated as shown below.
Sieve Category Opening (rom)
1 >18.85
2 18.85-9.423
3 9.423-4.760
4 4.760-2.380
5 2.380-1.190
6 1.190-0.590
7 <0.590
After sieving the aggregates were oven dried
and weighed separately.
109
Results and Discussion
The dry aggregate size distribution of both
soils are presented in log-probability plots as described
by Gardner (1956). These are averages of three samples.
The dry aggregete size distribution with mean log diameter
and log standard deviation for Molokai and Waialua soils
are given in Figures 28 and 29 respectively. The log mean
diameter was obtained as the value at 50% oversize and the
log standard deviation as the ratio of 50:15.5 oversize
values. Waialua soil showed a higher aggregate mean
diameter and a slightly higher standard deviation. These
may be attributed to the different tillage methods used at
different soil conditions at different sites.
CONCLUSIONS
The pore geometry produced in the surface
soil by tillage is usually very unstable and changes with
time are common. The above results show that the soil
hydraulic properties change with wetting and drying over
time subsequent to tillage. These controlled experiments
show that if traffic, intercultivation, rainfall impact
and root growth are eliminated, the first wid cycle is
responsible for most of the temporal variability of soil
hydraulic properties sUbsequent to tillage. The flooding
treatment always showed more reduction in measured soil
110
MOLOKAI SOIL
•
log mean dlameter=O.0015 m.
log Ld.=O.157.
80 85 9020O.0001H---,---.,..---,.-""T"""--,.-T-....,..-~....,..._...
5
PERCENT OVERSIZE
Figure 28. Dry aggregate size distribution for Molokaisoil following intensive tillage and priorto irrigation.
III
0.1WAW1IASOIL
0.01
0.001
log mean dlamet.r=O.0055 m
log Ld.=O.18
-\•'.\ •\ •
\20 30 40 50 60 70 80 85 9010
O.OOOlH--..,--~-...,.-__--r-,....-....,..- -5
PERCENT OVERSIZE
Figure 29. Dry aggregate size distribution for Waialuasoil following intensive tillage and priorto irrigation.
112
hydraulic properties than the drip irrigation treatments.
This is likely due to more aggregate breakdown and soil
slaking in these plots. Out of the measured soil hydraulic
properties hydraulic conductivity as a function of soil
water suction ,K(h), near saturation for the 0-5 cm depth
showea the greatest decrease, a decrease of two orders of
magnitude with wid cycles for both the soils. Both
sorptivities, sorptivity by positive head (Spas) and
sorptivity with negative head (Sneg), showed appreciable
reductions. All measured soil hydraulic properties
decreased with wid cycles. This is due to the reduction of
macroporosity with soil compaction associated with wid
cycles. Soil hydraulic properties such as hydraulic
conductivity as a funtion of soil water suction,K(h), and
soil water retention, h(e), increased slightly at higher
suctions with wid cycles due to the additional small voids
formed with compaction. In both soils, surface soil showed
more temporal variability of soil hydraulic properties
than subsurface layers. Cassel (1983) showed that temporal
variability of a Typic Paleudualt after seeding was
limited to the shallowest depth increment (0-14 cm). In
our study the Waialua soil showed more temporal
variability than the Molokai soil, probably because of the
higher swelling and shrinking capacity of the Waialua soil
with its vertic characteristics.
113
Tillage operations create an unstable
biomodal pore-size distribution with increased porosity
from a uni-modal pore size distribution (Klute, 1982). In
our experiments the extensive tillage provided a highly
porous surface soil with high hydraulic conductivity and
high water retention at lower suctionsi with this highly
porous soil the imposition of small suctions causes large
reductions in conductivity and water contents as
macropores drain. With imposed wetting and drying cycles
the soil was compacted by the pore water component of
effective stressi the bimodial pore size distribution
likely changed to a uni-model poresize distribution with a
decrease in nydraulic conductivity and water retention in
low suctions.
CHAPTER 3
SIMPLE SOIL HYDRAULIC MEASUREMENT METHODS APPROPRIATE FOR
ASSESSING TEMPORAL VARIABILITY
INTRODUCTION
In the foregoing chapter the measurement of
many soil hydraulic properties and their temporal
variability were discussed. The hydraulic conductivity as
a function of soil water content, K(9), or soil water
suction, K(h), and the water retention function, h(o), are
essential for simulation of water and solute movement in
soil. These are difficult, time consuming and expensive to
measure in field soils (Klute, 1973). Therefore, it is
important to identify simple measurement methods that
could be used to evaluate field variability of hydrologic
behavior as a tirst approximation before the detailed
measurements are undertaken. Some fields may show greater
spatial and/or temporal variation in hydrologic behavior
than their counterparts. Simple methods will help in
determining the number of K(h) or K(6) and h(e)
measurements needed in a particular field. Additionally,
these simple measurement methods could be used to identify
reasonably homogeneous soil areas for modeling before
115
detailed plans of measuring K(h) or K(e) and heel are
undertaken.
The second objective of this study is to
further evaluate a sorptivity measurement method that
could be used to characterize the field variability of
soil hydraulic properties. This will be undertaken with
the following criteria.
1. The selected method should be able to predict soil
water processes such as infiltration.
2. The selected method should be sUfficiently sensitive to
field temporal or/and spatial variability.
3. The method should provide a rapid measurement with
simple equipment and procedures, so that many
measurements can be made with relative ease.
RATIONALE FOR USING SORPTIVITY METHOD
Among the many hydraulic properties discussed
in Chapter 2, sorptivity is one of the more easily
measured properties. Many soil physicists have attempted
to find relationships between 50rptivity and other 50il
hydraulic properties. Simple relationships have been
developed mathematically between sorptivity and
116
infiltration (Talsma and Parlange, 1972:) and between
sorptivity and saturated hydraulic conductivity (Youngs,
1981). Talsma (1969) reported a poor relationship between
sorptivity and Ksat but Sharma et. al., (1980) showed that
sorptivity increases with increasing Ksat. Chong and Green
(1983) reported that these discrepancies may be partly
from the failure to consider the effect of antecedent
moisture on the measured sorptivity value. Sorptivity has
been applied for characterizing pre-and post-mined soil
conditions (Rogowski, 1980) and also to compute incipient
ponding time (Chong and Moor, 1982).
One of the important uses of easily measured
sorptivity is to predict infiltration which is more
difficult to measure. An infiltration equation similar to
the Philip equation was developed and tested by Talsma and
Parlange (1972) and Parlange (1977). Cumulative
infiltration rate could be predicted using sorptivity and
Ksat as given below.
-1/2 3/2I = S(t) + (1/3) Ks t + (1/9) (Ks/S) (t )
where I = cumulative infiltration, m
KS = saturated hydraulic conductivity, m/sec
S = sorptivity at a specific antecedent moisture
content, m/secl/2
t = time, sec.
117
Chong and Green (1979) tested this prediction method for
two oxisol series, Tropeptic Haplustox and Typic Torrox,
in Hawaii. This study included seven locations and a total
of 26 infiltration measurements including dry and wet
antecedent conditions (Green et al., 1982). They concluded
that the prediction of cumulative infiltration by this
method was reasonbly good considering the simplicity of
the method.
Sorptivity With Negative Bead as a Simple Measurement
for Assessing Variability
Clothier and White (1981) have documented
that the sorptivity estimated with positive head (Spos)
may result in a larger sorptivity value than sorptivity
measured with negative head (Sneg). This is due to the
presence of large voids which are not representative of
the soil matrix. Therefore, sorptivity measured with
negative head (Sneg) was proposed and used by Dirksen
(1975) and other workers in the field (Clothier and White,
1981; Russo and Bresler, 1980a). The sorptivity
measurement with negative head is discussed in detail in
Chapter 2. Dirksen (1975), and Clothier and White (1981)
used Sneg to obtain soil water diffusivity. Russo and
Bresler (1980a) used Sneg to asses the field variability
of hydraulic conductivity which is more difficult to
measure. Sneg varies depending upon soil structure and
118
antecedent moisture content and therefore should be
sUfficiently sensitive to significant variations of
hydrological behavior in the field. In soil compaction,
bulk density is often used as an index of relative
compaction, but it does not provide an assesment of
changes in soil hydraulic properties which are directly
related to infiltration and surface runoff. Therefore, in
characterization of compacted soil, using sorptivity as an
index should provide more direct and meaningful
information (Chong and Green, 1983). Sneg may be a
superior method as it can characterize intermediate
changes of soil compaction as shown for Molokai soil in
Chapter Two.
Sneg has the following added advantages over
Spos when used to characterize the variability in a large
field.
1. The measurement apparatus is simple and easy to carry
in the field.
2. Need less water than for Spos. Only 0.16 liters per
measurement is required in contrast to 2 liters needed
with the ponded case. This is a considerable advantage
when water is not available at the field site.
119
3. Ability to carry out many measurements/day by a single
person.
4. Provides a Detter representative value for the field as
it excludes flow in cracks and large holes.
Sneg has the following disadvantages.
1. Measures only a small area~ D = 8 cm in contrast to 30
cm in ponded case, Spos.
2. Difficult to use in fields with large clods because of
poor contact between the plate and soil.
CONCLUSIONS
Sneg is shown to be a good candidate for a
simple measurement method to assess variability of soil
hydrologic behavior in the field. Sorptivity has been used
by many investigators with success to predict
infiltration, diffusivity and field variability of
hydraulic conductivity. Field variability of hydraulic
properties is aue, to a large extent, to the variability
of the surface soil layer. Sneg depends upon soil
structure and antecedent moisture and thus is sensitive to
temporal and spatial variations under field conditions.
Sneg is a rapid measurement with simple equipment, and our
120
experience shows that a single person can make about 25 to
30 measurements per day using the sorptivity device
discussed in Chapter Two. Sneg is the simplest method and
may be superior in characterizing variability in soil
hydrologic behavior in surface soils in contrast to other
available soil water measurements.
CHAPTER 4
TEMPORAL VARIABILITY OF SORPTIVITY IN RELATION TO SPATIAL
VARIABILITY
INTRODUCTION
The use of sorptivity with negative head to
characterize the variability of soil hydrologic behavior
is addressed in Chapter 3. Once the temporal variability
is characterized the next concern will be to show the
importance of these changes in relation to other
variabilities existing in the field. Spatial variability,
the variability with distance, has received much attention
in recent years; many investigators have provioed
substantial information on variability of field measured
soil hydraulic properties (e.g. Nielsen et al., 1973).
Therefore, it is appropriate to compare the magnitude of
temporal variability with spatial variability to evaluate
their relative importance.
The objective of this chapter is to use
sorptivity with negative head to compare the magnitude of
spatial variability to temporal variability in a selected
soil. This was undertaken with the following approach.
1. Measure sorptivity with negative head on a spatial
122
grid in a ~arge field adjacent to the Molokai soil
experimental area used for temporal variability study.
2. Evaluate the statistical distribution of sorptivity
with negative head to appropriately transform the data
for statistical and geostatistical analysis.
3. Compare the field measured spatial variability with the
temporal variability obtained from the experiments for
the same soil series.
METHODOLOGY
Sorptivity with negative head was used to
characterize the variability of two large sugarcane fields
in the Kunia area of Oahu, Hawaii. The two soil series and
classification of these soils are given below.
FIELD
Field 220
Field 145
SOIL SERIES
Molokai
Lahaina
FAMILY
Typic Torrox, clayey
kaolinitic, isohyperthermic
Tropeptic Haplustox, clayey
kaolinitic isohyperthermic
123
The detailed maps of the Fiald 220 (Molokai series) and
Field 145 (Lahaina series) of Oahu Sugar Company are given
in Fig. 30 and Fig. 31, respectively. These two field were
in close proximity to each other.
From the Molokai series (Field 220) a 20 acre
block was selected and from the Lahaina series (Field 145)
a 17 acre block was used as shown in Fig. 33 and Fig. 34.
These sugarcane fields were three to four months old and
have been tilled using a ripper and rototilled
subsequently prior to planting. The fields planned for
drip irrigation are intensively tilled and do not undergo
much compaction traffic follwing planting. The
measurements were done between drip irrigation lines in
the interrow spacing. The sites were levelled and any
plant material was removed to achieve better contact with
the porous plate of the sorptivity device. Sneg was
measured as described in Chapter Two according to a
predetermined sampling grid. The maximum possible length
and the width of the fields were included in the
measurement distances. These distances were combined with
sufficient closer spacing, in an attempt to obtain a good
spatial structure for geostatistical analysis. The
sampling grids for Molokai and Lahaina soils are given in
Fig. 32 and Fig. 33, respectively. Each field was measured
within two days, with about 20 to 25 Sneg measurements per
day. A tape recorder was used to record data so a
....N~
u:
S'.:AL[ IN FT.
Q .'0'
OAHU SUGAR CO.
fIELD 220
DRIP IRRIGATION
/4.:1'3/7J"
~®
'19.IZICA)
4."4
-
'1 /1,••,~
,l
-'=-"""7\...,-= ~/Ir
//. 7"
0-123.701
'BI
.iev. 490- -
I 1'·13~
'//./~-.t!tZ IC?-"':~
SiN I "''''4 I "
Z I ") 19. ':?-,v I. ~--;,',.I
ocld Pl.Date
~. _ ..r ...,... ''''''?. . -- .......
7 .l/•••.,-~... :-;,- /,
6 '.!fJ3,
I ' It.''''"", 17.9- .-:.1'''& I 5.12 i165 Total /fL~.eO
i i
146
Figure 30. Field 220 of Oahu sugar Co. spatial variability was evaluated inthe shaded area.
125
FLD 210
1;~liiiiiil!!!!!!'• MSCALE 1N FEET
FLO //6
==-=-=-=~l'~L11
o~.HU SUGAR CO LTDFIELD ILl5nRIP IRRIGATION
/
eLI( PL DATE VAI\IETY .REA
~ '-I!1.~g (;2.~'71 2.214 I...=-.
_2_ t', :32.l"\A '
3 II " ~5:J5
4Mr_
2,9&
TOTAL 82.33
Figure 31. Field 145 of Oahu Sugar CO. Spatial variabilityof sorptivity was evaluated in the shaded area.
f16m~, .. , .. ~
x x 1130m
X X
.~ 1xxxx X X xxxxxxx X X XXXX
X
X
X
X
Figure 32. Sampling grid for Field 220 (Molokai soil) showing49 measurement points. I-'
NO'l
k- 27m -7f~ ... ~ ... ~
TX 145m
X X X X X X X ~l
X X
X X
X X X X X X X X X
X X
X X
X X X X X X X
Figure 33. Sampling grid for Field 145 (Lahaina soil) showing49 measurement points. ....
~
128
single person could handle the entire operation.
A soil sample adjacent to each Sneg measurement was
removed for antecedent moisture determination. The
measured sorptivity was adjusted to 0.30 m3/m3 antecedent
moisture content as discussed in Appendix II.
RESULTS AND DISCUSSION
Statistical Analysis
Once a given hydrological parameter is
measured in a ~arge field it is necessary to first
determine the form of its statistical distribution. If the
distribution is not normal the data are transformed before
using for statistical or geostatistical analysis. For
example, if the parameters are normally distributed the
original data are used. If the parameter observations are
log normally distributed the log transformed values are
used. A number of equations are available for calculating
the empirical cumulative distribution function (Chow,
1964; Haan, 1977). In this study the Kolmogorov-Smirnov
test was employed as an alternative to the chi-square
goodness of fit test. The Weibull method (Weibull, 1939)
was used to compute the sample cumulative distribution as
discussed by Haan (1977). The value of the statistic D,
which 1S the maximum deviation of the theoretical
129
cumulative distribution function from the sample
cumulative density function, is computed more easily if
the data are plotted on probability paper (Benjamin and
Cornell, 1970).
The plotting positions for Sneg were
determined by the Waibul (1939) relationship by ranking
the data from the largest to the smallest and using the
procedure given by Haan (1977). The Sneg data for both the
soils were plotted on probability paper using the plotting
positions (percent less than) and the measured data. This
was carried out for the original results as well as for
the log cransformed data. The mean and standard deviation
of the measured data were used to compute the hypothesized
distribution functions for the soils.
Fig. 34 and Fig. 35 show the normal
probability plot of Sneg for Molokai soil for the original
and the log transformed data, respectively. The same data
plots for Lahaina soil are shown in Fig. 36 and Fig. 37.
The normality test results for field measured Sneg for the
two types of data are given in Table 10.
The D value is the largest deviation between
the hypothesized cucmulative distribution, F(x), and the
observed cumulative distribution, Sex) computed from
Figures 34 to 37. These values are compared with the
critical D value obtained from the tables. The critical D
values reported here are the values proposed by Lilliefors
9.5,1----------------------.I
99·8
Q::> 00000
on
20 30 40 50 60 to 80105Ii iI ii I3.5 ~ - iii
7.5
5.5
>I->t~o(/)
8z
'U'(l)
~E
Tov
PERCENT LESS THAN
Figure 34. Normal probability plot for sorptivity with negativehead for Field 220 (Molokai soil). ....w
o
-3 I10 I
'U'Q)
~g~>~0:::oVl
-41 I ILl 1 I3)(10 I J_ _C _L .L _1__t _1_ L __ _2 -
PERCENT LESS THAN
Figure 35. Normal pro~ability plot for log sorptivity withnegative head for Field 220 (Molokai soil).
t::....
10
~ 9Q)
~ 8E"Itr0 7,.-<:»
>- 6J->J- 50-0:::0 4(/)
3 2 5 10 2"0 30 40 50 60 io 80 90 9S 9"8 99 99-8
PERCENT LESS THAN
Figure 36. Normal probability plot for sorptivity with negativehead for Field 145 (Lahaina soil).
I-'W
'"
-31°1'- - - - - - - - - - - - - - - - - - - - I
~Q)
~g,>J->h=n::a(f)
-43 )(10 , iii I iii iii I I I , I
2 5 5 g"S 9-9 9g:9
PERCENT LESS THAN,
Figure 37. Normal probability plot for log sorptivity withnegative head for Field 145 (Lahaina soil).
....ww
134
(1967), 0.886An for 5% probability level instead of the
standerd table values. Many investigators (Crutcher, 1975;
Lilliefors, 1967; Massy , 1951) have documented that the
standard tables of critical values for the K-S test cannot
be used if the hypothesized cumulative distribution
function is computed with parameters (mean and SO)
Table 10. Results of Kolmogorov-Smirnov test for normality
of field measured Sneg.
F(x) - 8(x)]
Log 8
12 = [ ...M_a_x_...............__...........
S
Soil Sample Critical 0 value
Series Size at 5% level a
Molokai 48 0.148 0.330 0.128
Lahaina 47 0.149 0.225 0.110
a. Calculated by 0.886ffil, from Lilliefors (1967).
estimated from the sample itself, as in this study.
Therefore the values suggested by Lilliefors are used. If
the observed D value exceeds the critical value obtained
from the tables one rejects the hypothesis that the
observations are from a normal distribution.
Table 10 results show that the 0 values for
135
original Sneg data for both the soils exceed the critical
value at 5% probability level. The D value of log
transformed data are less than the table value, indicating
that Sneg is a log normally distributed parameter. Similar
results were obtained for Spos by several other workers
(Chong and Green, 1979~ Sharma et al., 1980).
The log transformed Sneg data were used to
compute semi-variograms by geostatistical analysis with
the purpose of characterizing spatial structure in the
variance if such structure exists. Semi-variograms for
Sneg were computed for four principal directions, namely
along the directions of NE, SE, SW and NW within an angle
of 22.2 degrees for all the directions, with lag distance
approximately 1000 feet (Burgess and Webster, 1980a~
1980b). The semi-variograms failed to show any definite
structure with the distances used. Therefore, to determine
a representative vale for Sneg for these two fields the
geometric means were used andare given in Table 11.
If an estimate of variance is available from
previous measurements of the population, then an estimate
of the number ot measurements necessary in future studies
to obtain a given precision with a specified probability
may be obtained using Equation (12) as shown by Peterson
and Calvin (1965).
136
Table 11. Field measured sorptivity with negative head for
Molokai and Lahaina soils. Means and s.d.
Soil Series Mean Log Sneg SD of Log1/2m/sec
Mean Sneg
Molokai
Lahaina
-3.272
-3.297
0.0860
0.0776
5.27E-4
5.06E-4
N = t 2 S2/L2 •••••••••••••••••• (12)
where N = number of samples;
S2 = variance;
L = the specified limit.
This equation was used to estimate the number
of measurements needed to obtain Sneg within specified
confidence limits above and below the mean. As the Sneg
for both the soils were log normally distributed the log
transformed values were used. The calculated number of
samples neede to obtain a value with different probability
levels are shown in Table 12 for both Molokai and Lahaina
137
Table 12. Number of Sneg measurements needed to estimate
the mean with specified probability level.
probability 100-~ L as % of S
Molokai soil Lahaina soil
50%
60%
70%
80%
90%
95%
99%
5%
1
2
4
5
9
13
23
3%
4
8
10
15
25
36
65
5%
1
2
3
3
8
12
21
3%
2
6
9
9
22
32
58
a. L is the percentage difference between the measured
mean S and the real mean.
0(. is the level of significance.
138
soils. For example, to estimate the mean Sneg within 5%
above Delow mean with a 95% prpbability level, 13
measurements from Molokai soil and 12 measurements from
Lahaina soil are needed.
Comparison Of Temporal And Spatial Variability Of
Sorptivity For Molokai Soil
The standard deviation obtained from Field
220 (Molokai soil) was used as an indication of the
spatial variability expected from a large field and was
used to compare with the temporal variability of Sneg
obtained from the controlled experiments for the same
soil. These were compared by using the confidence
intervals calculated using the spatial variability data
(Field 220) with the greatest difference obtained from the
temporal variability data (experiment on Molokai soil).
The confidence interval at 95% and 68% probability levels
for spatial variability data were calculated as follows
CL = X±[S/(n)t]
where CL is the confidence limit,
X is the mean,
S is the standard deviation,
n is the number of samples.
139
The greatest difference obtained from the
controlled experiment for Sneg data was from pre-irigation
to the 5th wetting and drying cycle (Chapter Two, Appendix
Table II1-2). These were compared with the confidence
intervals calculated using the spatial variability data
for Molokai soil (Field 220) as shown in Table 13.
These results show that the temporal
variability of Sneg simulated by wId cycles is more
important than the spatial variability obtained from the
field. It should be noted that the temporal variability
obtained in the controlled experiments was imposed only
with wid cycles. With traffic, rainfall impact and
intercultivation temporal variability following tillage is
expected to be much greater. This suggests that temporal
variability is more important than spatial variability in
some cases when measuring soil hydraulic properties as
parameters for modeling water and solute movement in soil.
CONCLUSIONS
The statistical distribution of Sneg for two
large sugarcane fields was found to be log normally
distributed by the Kolmogorov-Smirnov test. The log
transformed Sneg data were used to construct
semi-variograms but no structure in the variance with
140
Table 13. Sneg changes with four wetting and drying cycles
(temporal variation) compared with the
confidence intervals for Sneg measured in a
sugarcane field (spatial variation). Molokai
soil.
Temporal variability of Sneg
from controlled experiment
Cy 1
1.32
10-3 m/sec
Cy 5
0.70
Diff
0.560
Spatial Variability of
Sneg from Field 220
10-3 m/sec
C.l. Diff
95% 0.507 to 0.568 0.061
68% 0.513 to 0.562 0.049
141
measured distances was indicated. The geometric mean and
standard deviation were thus considerd sufficient to
characterize the spatial variation of the two fields
evaluated.
Sample statistics were used to predict the
number of Sneg measurements needed to estimate the mean
within qonfidence limits. It was shown that about ten
measurements of Sneg can estimate the mean within 95%
confidence limits below or above the mean.
The temporal variability of sorptivity with
negative head obtained with the controlled experiment were
compared with the spatial variability of Sneg measured in
the field for Mo1okai soil. It was shown that temporal
variability is more important than spatial variability in
some cases when measuring parameters for modelling water
and solute movement in soils.
CHAPTER 5
THE EFFECT OF TEMPORAL VARIABILITY ON SIMULATION OF SOIL
WATER MOVEMENT
INTRODUCTION
In Chapter 2 the temporal variability of many
soil hydraulic properties was discussed. It was shown how
the hydraulic conductivity as a function of soil water
content, K(6), or as a function of soil water suction,
K(h), and water retention, h(e), which are essential for
modeling soil water and solute movement, undergo
considerable temporal variability following tillage. The
validity of soil water and solute movement predictions
will depend on the accuracy of these input parameters.
Thus, temporal variability of soil hydraulic properties
is an important consideration in modeling soil water and
solute movement during the cropping cycle. After
evaluating the temporal variability of these parameters
the next concern is how to utilize these data effectively
for modeling purposes.
The third objective of this study was to
illustrate the effects of temporal variability of soil
hydraulic properties on simulation of soil water movement
143
and to suggest appropriate procedures to cope with the
measured variability in modeling. This will be undertaken
as shown below.
METHODOLOGY
A numerical simulation model proposed by Khan
(1979) was used to illustrate how the temporal variability
of K(e) and heel obtained from this study affects the
prediction of soil water movement. This model was
originally used to predict nitrogen movement in the soil
with intermittent irrigation (Khan et al., 1981), but can
be used to obtain only the water content profile. The
input parameters used in this model, Bl, B2, B3 and B4 are
computed from the K(e) and heel functions as shown below.
h (e ) = B3 (e) B4
Where K(e) is the hydraulic conductivity as a function
of soil water content, em/day;
h is the soil water suction, em of water;
e is the water content, m3/m3•
Blr B2, B3 and B4 are constants.
144
RESULTS AND DISCUSSION
The calculated Bl, B2, B3 and B4 values for
Molokai and Waialua soils for the pre-irrigation treatment
and following the last wid cycle are given in Table 14.
The input parameters given in Tabel 14 were
used to compute the water content profiles for Molokai and
Waialua soils. These were computed for two irrigation
rates, 0.2 cm/hr and 0.125 cm/hr. The higher rate was
based on the amount of water applied in Irrig 1 main plot
for the Molokai experiment. Water was applied for 24 hours
at the given rates and was allowed to redistribute for
another 24 hours with no evaporation. The initial water
content of the soil profile was set to 0.30 m3/m3 and the
water content profiles were computed up to 50 cm depth
with no evaporation. The computed water content profiles
for Molokai soil for both irrigation rates are given in
Figures 38 and 39. The infiltration and redistribution
phases are shown separately in each figure. Similar data
for Waialua soil are shown in Figures 40 and 41. These
computed results illustrate the discrepancy of the water
content profiles caused by the temporal variability of
input parameters. The discrepancies are more when a higher
irrigation rate is used. When a lower irrigation rate is
used the soil water flow is controlled by the water
application flux and the soil hydraulic properties do not
145
Tabel 14. Input parameters Bl, B2, B3 and B4 calculated
using field measured K(6) and h(6) functions for
Molokai and Waialua soils.
Soil
Molokai
Waialua
WiD Cycle
o
5
o
3
1.89E+5
6.36E+4
1.92E+9
2.80E+8
11.49
11.08
24.30
23.82
0.87 -6.97
0.16 -5.58
0.51 -12.32
0.24 -11.14
WATER CONTENT (m3/m3) WATER CONTENT (m3/m3
)
0.30 0.35 0.40 0.30 0.35 0.400.0
I ~I-' I , I I I I I
24 168 1i i \4
4
/ I0.1~ I 1/ II / I
"I I~
/ / I I I~ 0.2 / / III II /
"I It-o... /w 0.3 II I0
f I / -cycle 0 II I0.4 -f '/ -cycle 0
I I _-cycle 5/ - -cycle 5
/0.5 -.J'I I I ( a) I I' J'_ (b)
Figure 38. Infiltration (a) and redistribution (b) soil water profiles forMolokai soil computed using parameters from cycle 0 and cycle 5Irrigation rate 0.20 em/hr. The numbers on the curves indicatehours of elapsed time after initiation of infiltration orredistribution.
.....
.c:.0\
Figure 39. Infiltration (a) and redistribution (b) soil water profiles forMo1okai soil computed using parameters from cycle 0 and cycle 5.Irrigation rate 0.125 em/hr. The numbers on the curves indicatehours of elapsed time after initiation of infiltration or ~
redistribution. ~
WATER CONTENT (m3/m3) WATER CONTENT (m3/m3
)
0.30 0.34 0.38 0.42 0.350 0.375 0.4000.0 - - - - ,
24 16 4,
161 41I 1 1 1
I I 1 I16' .'24 I I, , •
0.14'/ c-: I,
I , I,I I I,I , I,1 t ,,, I • I, I • I
'E' , , I ••0.2 , I I .1~ I I I I,
I I I
:c I I , ,,l- I , I I,
I Ja.. , ,w , I I I
0 0.3 , , I II 1 I I
-CYCLE 0 I I I, ,, I , ,, ----CyCLE 3, I , ', ,I '0.4 -j
, , , ,,I . '--CYCLE 0,,I ' ,, ,
- - -CYCLE 3, , I,,I I J,', ,
I ,l0.5...J I ..Figure 40. Infiltration (a) and redistribution (b) soil water profiles for
Waialua soil computed using parameters from cycle 0 and cycle 3.Irrigation rate 0.20 em/hr. The numbers on the curve indicatehours of elapsed time after initiation of infiltration orredistribution.
I-'~CD
( b)
2 18 14 "'2 .8 i4• • •• • •• • •I I ,, . ., , .: . ,, , ,, , ,, , ,I "I ", , I. , ,
, I ,, I I
I I II I '
I "I ,/I I,
I 'I, I,I I' - CYCLE 0Y -----CYCLE 3,..,
,~
,~".,,",,",
WATER CONTENT (m3/m3)
0.32 0.35 0.38
( a)
I1
1611
II
II
II
I,,,,,I
'I
--CYCLE 0
-----. CYCLE 3
",,,,,I
II,
0.1
0.4
0.5
0.3
WATER CONTENT (m3/m3)
0.30 0.35 0.40O 0 I ' ,• . 7- -.P, '1 ,
0.2l'~
:::c.....0Wo
Figure 41. Infiltration (a) and redistribution (b) soil water profiles forWaialua soil computed using parameters from cycle 0 and cycle 5.Irrigation rate 0.125 em/hr. The numbers on the curves indicatehours of elapsed time after innitiation of infiltration orredistribution.
I-'oIlo\D
150
play a major role in soil water movement. When the
irrigation rate is increased considerably, flux at the
surface becomes less limiting, and the soil hydraulic
properties dominate soil water movement.
The differencesin the computed results using
parameters from pre-irrigation and after wid cycles are
due only to temporal variability in hydraulic properties
caused by soil deformation resulting from wetting and
drying, as measured in our field experiments. If other
external compaction factors such as traffic,
intercultivation and rainfall impact are included there
may be greater temporal variability, which would be
expected cause even larger discrepancies in computed soil
water profiles. The Waialua soil showed a larger
differencein computed results because it showed a greater
temporal variability of soil hydraulic properties than the
Molokai soil. These results indicate that the temporal
variability ot soil hydraulic properties is an important
consideration when modeling soil water movement.
After illustrating the effects of temporal
variability on soil hydraulic properties in predicting
soil water movement, the next step is to propose
appropriate procedures to accomodate this measured
variability in simulation of soil water movement. Work
with similar objectives but for spatial variability data
have been reported by many investigators using the similar
151
media concept to scale soil hydraulic properties (Peck et
al., 19761 Russo and Bresler, 1980b, Sharma and Luxmoore,
19791 Warrick et al., 1979).
According to the similar media concept, first
proposed by Miller and Miller (1956), two porous media are
called similar medium if they are geometric scale models
of one-another. That is, the microscopic geometric details
of one media could be multiplied by a constant to obtain
the microscopic geometric details of the second medium
(Sharma et al., 1979). Several investigators (Elrick et
al., 19591 Sharma et aI, 1979) have experimentally tested
this concept for idealized porous material. By using
sieved fractions of sand they showed how curves of
capillary conductivity and water retention could be
reduced or scaled into one curve within the limits of
reasonable experimental error.
Natural soils usually do not satisfy the
similar media concept even though this concept has been
used USQd to scale spatially variable data. Temporal
variability is caused principally by soil compaction and
this creates a new frequency distribution of effective
pore-sizes. Therefore use of similar media concept for
scaling temporal variability data is seems inappropriate.
A meaningful way of coping with the temporal
variability is to derive a time dependent function.
Whisler (1971) proposed a time dependent function for
152
adjusting hydraulic conductivity for surface crust as
shown below.
K(h,z) = Ki
K(h,z) = Ki-Bl(t-tl)
K(h,z) = B2Ki
O<t<tl
tl<t<t2
t2<t
Where Bl governs the rate of hydraulic conductivity
decrease after the crust starts to form at time
tli
B2 is the fractional amount of hydraulic
conductivity decrease in the crust after it
is fUlly formed at time t2i
Ki is the unadjusted value of conductivity.
They obtained a Bl value of O.48/min and a B2
value of O.Ol/min in their simulation studies. In our
experiments the temporal variability was evaluated with
wid cycles as the factor causing compaction with time. The
results showed that the most important wid cycles after
tillage were the first and second cycles. Therefore if
modeling is undertaken for the whole cropping cycle it is
advisable to divide the cropping cycle into two or three
phases and use appropriate parameters for each of the
different periods. If resources are available for only one
set ot measurements it is advisable to easure the input
153
parameters after a few wid cycles sUbsequent to tillage.
It must be recognized, however, that the resulting
predictions may not be appropriate for the period between
tillage and the first one or two wetting-drying cycles.
CONCLUSIONS
The effect of field measured temporal
variability of soil hydraulic properties in soil water
simulation was illustrated using an existing numerical
simulation model. The K(O) and h(O) functions obtained on
two soils before irrigation and after a number of wetting
and drying cycles were used in the model to illustrate the
changes in predicted water content profiles due to soil
compaction over time. The Waialua soil showed a higher
change in soil water movement from pre-irrigation to the
final wid cycle because this soil showed a higher temporal
variability than the Molokai soil.
When modeling for soil water and solute
movement during the course of the cropping cycle it may be
appropriate to divide the cropping cycle into a few
definite phases. The parameters measured for each of these
phases should be used to model water movement for the
corresponding time period. If resources are limited it is
advisable to measure the input parameters following a few
wetting and drying cycles subsequent to tillage for use
during most of the cropping period.
CHAPTER 6
GENERAL CONCLUSIONS
Objective 1
All soil physical properties measured showed considerable
temporal variability in intensively tilled soil due to
compaction imposed by wetting and drying. K(h) near
saturation showed the greatest temporal variability,
decreasing by nearly two orders of magnitude in the
surface layers for both soils.
Objective 2
Sorptivity measured with negative head is a simple and
rapid method that can be used to characterize the
variability in soil hydrologic behavior prior to
undertaking more demanding soil hydraulic measurements.
Objective 3
With the use of sorptivity measured with negative head it
was shown that in some cases temporal variability is more
important than spatial variability when measuring soil
hydraUlic properties for modeling soil water movement.
Objective 4
There were considerable differences in water content
profiles when K(6) and h(6) measured at pre-irrigation
155
and after wetting and drying cycles were used to simulate
infiltration and redistribution using an existing
numerical simulation model. It was suggested that when
modeling water and solute movement in the course of the
cropping cycle, parameters measured at different phases
should be used for the corresponding time period to obtain
a reasonable prediction••
APPENDIX I CONTENTS
Description of soils at experimental sites.
Tabele I-I. SSPA sub station in Kunia.
Molokai silty clay loam.
Table 1-2. U.S. Waimanalo Experimental station.
Waialua clay variant.
156
157
DESCRIPTION OF SOILS AT EXPERIMENTAL SITES
Table I-I. Molokai Silty Clay Loam. (Green et al,1982)
SOIL:
LOCATION:
Molokai silty clay loam; Typic torrox;
cl ayey; kaol ini tic; isohyperthermic
family
Oahu, HSPA Kunia Substation. About 46 m
south of NE cor ner of the block
DATE: 30 August 1977
DESCRIPTION BY: S.Nakamura, Soil Conservation Service
TOPQ.;RAPHY: Gently sloping uplands; 3% slopes
PARENT MATERIAL: Residuum from basic igneous rock
None
Boul der in 1 ow~r profil e
Well drained; moderate permiabil ity
Sugarcane
Representative of Molokai series
ELEVATION: 70 m
ANNUAL RAINFALL: 635 rom
DRAINlG E AND
PERMEABILITY:
EROSION:
STONINESS:
VB; ETATION:
REMARKS:
158
PROFILE DESCRIPTION: Molokai silty clay loam, HSPA
(Colors for moist soils; all textures
"apparent field textures")
Ap 0-28 em (0-11 in.)- Dark reddish brow~ (2.5 YR 2/4)
clay loam; w:eak, very fine granular structure w:ith
few: clods; friabl e, sticky and pI astic, but cl ods
are firm; many roots; clear smooth boundary.
B2l 28-68 em (11-27 in.)- Dark red (2.5 YR 3/6) silty
cl ay loam w:eak fine and medium subangul ar blocky
structure; very friabl e, sl ightly pI astic; few:
roots; many fine pores; compact in place; gradual
wavy boundary.
B22 68-108 cm (27-40 in.)- Dark red (2.5 YR 3/6) silty
clay loam; moderate fine and very fine subangular
blocky str uct ur e; f r iabl e, sti cky and pI asti c; no
roots ~ many very fine por es ~ compact in pI ace
159
Tabel 1-2. Waialua clay variant (Ikaw:a et al , 1982)
Moderate to w:e11 drained, moderate
permeabi1 i ty
Slight
Many soft w:eathered pebb1 es in the
subsoil
Sugarcane, truck crops, orchards and
pasture
natural vegetation fingergrass, koa haole
Geographica11y associated w:ith
Honoul iul i, Kaena and Kaw:aihapai soil s ,
REMARKS:
VB; ETATION:
EROSION:
STONINESS:
SOIL: Waialua clay variant; Vertic Hap1usto11s
very-fine, kaolinitic, isohyperthermic
family
Oahu, Waimanalo Research Station. 160 m
Si of the headqua r t er s buil ding
DATE 1982
DESCRIPTION BY: H. Ikaw~ and team
TOPOORAPHY: Gently sloping uplands; 2% to 6% slopes
PARENT MATERIAL: All uvium w:eathered from basic igneous
rock
ELEVATION: Range from 3 to 35 m,
ANNUAL RAINFALL: 635 to 1270 rom.
DRAINl-G E AND
PERMEABILITY:
LOCATION:
160
PROFILE DESCRIPTION: Waialua clay variant
ApI 0-18 cm (0-7 in.) - Dark brown (7.5 YR 3/2) c1 ay;I
w:eak very fine and fine granul ar structure;
firm wpen moist, very sticky very pI astic wpen w:et;
many pores; few: roots; strong effervescence w~th
H202 ; cl ear w:avy boundary.
AP2 18-38 cm (7-15 in.)- Dark brown (7.5 YR 3/2) clay;
w:eak fine and medium sUbangular blocky structure;
firm wpen moist, very sticky and very plastic
wpen w:et; many pores; few: roots; strong
effervescence w~th H202; clear smooth boundary.
B21 38-94 em (15-37 in.)- Dark reddish brow~ (5 YR 3/3)
sil ty cl ay; w:eak fine and medi um subangul ar blocky
structure; friab1 e wpen moist, very sticky and very
plastic wpen w:et; many very fine pores; few: roots;
strong effervescence w~th H202; clear smooth
boundary.
B22 94-127 cm (37-50 in.)- Dark reddish brow~ (5 YR
3/3) sil ty cl ay; w~ak fine and medium aubanqut ar
blocky st.r uccur ej friable wpen moist~ sticky and
pI astic wpen wet; many very fine pores; few: roots;
many sor t w:eathered pebb1 es.
161
APPENDIX II
APPROXIMATION OF SORPTIVITY WATER CONTENT REL~TIONSHIP\
Each sorptivity measurement as·described in
Chapter 2 resul ts in one val ue of S at a given antecedent
moisture content. For other antecedent moisture contents
corresponding sorptivity val ues had to be obtained by an
estimation method because unstabl e soil (recently till ed
surface layer such as in this study) tends to compact w~th
repeated measurements. In this study antecedent moisture
content at before irrigation w~s about 0.20 m3/m3 in
contrast to 0.30 m3/m3 vol umetric moisture subsequent to
wid cycl es , Therefore the sorptivity val ues (with positive
head as w~ll as w:ith negative head) obtained before
irrigation w~s corrected to 0.30 m3/m3 volumetric
moisture, before comparing w~th sorptivities after wid
cycl es , A 1 inear approximation simi! ar to the one used by
Chong (1979), and Green and Chong (1979) was used to
estimate the entire S(Sn) relationship wpere On is
antecedent moisture content. This suggested approximation
of S(en) by a 1 inear funtion is by passing a straight 1 ine
from 8=0 at saturation through the sorptivity values
measured in the field at the existing anteedent moisture
content. The function can then be used to estimate
sorptivity at any given antecedent moisture content for
that soil assuming that the poresize distribution of soil
162
is essentially invarient w~th changes of soil water
content.
An example of this method for Molokai soil is
show~ in Fig. 42 (Chong,1979). In this case six ponded
sorptivity measurements w~th the corresponding antecedent
moisture contents w~re made in the same plot. The
geometric mean of sorptivity and the arithmetic mean of
volumetric w?ter content w?s used to obtain one point of
the curve. The other point w?s approximated by 85% of
total porosity as the saturated w?ter content w~ere the
sorptivity is zero.
Chong (1979) using K(O) and D(O) to obtain
another S(On) curve suggested that the linear
approximation can be expected to yield values of S which
are too large at low: water contents and too low: at w?ter
contents above that of the measured sorptivity.
2.5l
linear approx.
o o measured
-- - -. matched
o--
1
2
" , , ,0+----.. ·.·- I .----.- I ---- I .- I ·----~---I
o 10 20 30 40 50 60
ANTECEDENT WATER CONTENT (% by vol.)
1.5
0.5
~su(1)
~J;>.->§:~
o(/)
Figure 42. Adjusting sorptivity for antecedent moisture content (Chong, 19791.....0'1W
164
APPENDIX III CONTENTS
Mo1okai Soil
Table III-I. Sorptivity by Infiltration With Positive
Head.
a. Analysis of Variance.
b. Duncan's Multiple Range Test.
Table 1II-2. Sorptivity by Infiltration With Negative
Head.
a. Analysis of Variance.
b. Duncan's MUltiple Range Test.
Table 1II-3 Steady Infiltration Rate
Table III-4. Analysis of Variance for Parameter ~ for 0-5
cm depth.
Table III-S. Hydraulic Conductivity as a Function of
Volumetric Water Content.
a. 0-5 cm depth.
b. 0-25 cm depth.
Table 111-6. Hydraulic Conductivity as a Function of
Soil Water Sution.
a. 0-5 em depth.
b. 0-25 cm depth.
Table 111-7. Soil Water Retention Data.
a. 0-7.5 em
b. 5-25 cm depth.
165
Table III-I. Sorptivity with positive head for Molokai
soil.
a. Analysis of variance (log transformed).
166
Source DF S5 M5 F
Rep 2 0.0296 0.0150
Irrig L. 1 0.0016 0.0016 0.40
Error a 2 0.0086 0.0043
WID Cycles 5 2.6537 0.5310 20.50*
Ir. L. x Cycles 5 0.0390 0.0078 0.30
Error b 20 0.5120 0.0260
Sampling Error 72 1.3422 0.0186
Total 107 4.5556
b. Duncan's multiple range test.
Treatment Treatment Mean (10-3 m/sec)
WiD Cycles Irrig 1 Irrig 2
0 2.13 a 2.01 a
1 1.21 b 1.43 b
2 1.15 b 1.28 b
3 1.13 b 1.24 b
4 1.08 b 1.30 b
5 1.23 b 1.33 b
Any two means having a common letter are not significantly
different at 5% probability level.
167
Table III-2. Sorptivity with negative head for Mo1okai
soil.
a. Analysis of variance (log transformed).
Source DF SS MS F
Rep 2 0.7929 0.3964
Irrig L. 1 0.0128 0.0128 0.35
Error a 2 0.0726 0.0363
WiD Cycles 5 10.0530 2.0100 20.10*
Ir. L x Cycles 5 0.2565 0.0513 0.51
Error b 20 2.0065 0.1000
Sampling Error 173 3.6971
Total 208 16.8900
b. Duncan's multiple range test.
Treatment Treatment Mean (10-3 m/sec)
WID Cycle Irrig 1 Irrig 2
0 1.26 a 1.22 a
1 1.32 a 1.36 a
2 0.91 b 0.98 b
3 0.74 b 0.83 b
4 0.85 b 0.81 b
5 0.70 b 0.92 b
Any two means having a common letter are not significantly
different at 5% probability level.
Tabl e 111-3. Steady inf il tration rate (10-6 m/sec) for
Mo10kai soil.
Treatment Irrig 1 Irrig 2
WID eycl e
0 10.40 9.51
1 7.11 4.80
2 4.82 4.33
3 5.78 3.38
4 6.13 2.21
5 5.87 4.64
Tabl e 111-4. Analysis of variance of parameter "'l for
Mol okai so i1 •
168
Source DF SS MS F
Rep 2 0.0351 0.0175
Irrrig L. 1 0.0032 0.0032 0.03
Error a 2 0.2347 0.1177
WID Cycles 5 1.8110 0.3622 8.50*
Ir.L. x eycl es 5 0.0569 0.0114 0.27
Error b 20 0.8570 0.0429
Total 35 3.0000
169
Table III-Sa. Temporal variability of hydraulic
conductivity (m{sec) as a function of soil
water content, K(6), for Molokai soil.
0-5 cm depth.
Wetting/Drying Cycles
----
a pre-irrig 1 2 3 4 5
------m3/m3 Irrig 1
0.50 5.44E-4 1.05E-5 1.73E-6 1.36E-6 1.77E-6 1.51E-6
0.45 1.13E-5 1.43E-6 3.38E-7 4.4SE-7 4.19E-7 1.76E-7
0.40 1.96E-6 1.56 E-7 5.45E-8 1.30E-7 S .3SE-S 5.37E-7
0.35 2.69E-7 1.25E-8 6.S9E-9 3.1SE-S 1.35E-S 1.40E-S
0.30 2.71E-S 6.9E-IO 6.3E-IO 6.2SE-9 1.65E-9 2.95E-9
Irrig 2
0.50 2.33E-4 9.19E-6 2.39E-6 1.84E-7 6.32E-7 1.38E-5
0.45 5.l6E-5 1.47E-6 4.85E-7 4.06E-S 2.1SE-7 6.11E-7
0.40 9.53£:-6 1.90E-7 8.21E-8 7.50E-9 6.65E-S 1.88E-S
0'.35 1.41E-6 1.86E-8 1.10E-8 1.11E-9 1.73E-S 3.62E-9
0.30 1.54E-7 1.27E-9 1.07E-9 1.2E-10 3.65E-9 3.SE-12
170
Table III-Sb. Temporal variability of hydraulic
conductivity (m/sec) as a function of soil
water content, K(e), for Molokai soil.
0-25 cm depth.
Wetting/Drying Cycles
------e pre:irrig- 1 2 3 4 5
m3/m3 Irrig 1
0.50 S.52E-6 5.50E-6 3.49E-6 3.59E-6 3.00E-6 1.10E-5
0.45 1.78E-6 1.30E-6 8.27E-7 9.22E-7 6.37E-7 2.26 E-6
0.40 5.06E-7 3.00E-7 1.65E-7 2.02E-7 1.13E-7 3.46E-7
0.35 1.2IE-7 4.69E-8 2.67E-8 3.60E-8 1.58E-8 4.I3E-8
0.30 2.32E-8 6.00E-9 3.25E-9 4.93 E-9 1.64E-9 3.5SE-9
rrrig 2
0.50 7.73E-6 2.4lE-6 9.89E-6 1.05E-5 3.75E-5 2.27 E-6
0.45 1.6IE-6 6.01E-7 2.3IE-6 1.54E-6 7.0IE-6 6.4lE-7
0.40 2.79E-7 1.27E-7 4.53E-7 1.80E-7 1.07E-6 1.56E-7
0.35 3.82E-8 2.18E-8 7.l5E-8 1.57E-8 1.28E-7 3.ISE-8
0.30 3.8SE-8 2.8SE-9 8.49E-9 9.5E-IO l.lOE-8 4.96E-9
171
Table III-6a. Temporal variability of hydraulic
conductivity (rn/sec) as a function of soil
water suction, K(h), for Molokai soil.
0-5 cm depth.
Wetting/Drying eycl es
-----h pre-irrig 1 2 3 4 5
-- ---m ( H2O) Irrig 1
0.05 1.06E-3 3.06E-6 6.23 E-6 2.72E-6 1.58E-6 1.60E-6
0.10 9.86E-5 8.25E-7 1.42E-6 7.12E-6 5.93E-7 6.05E-7
0.25 4.23 E-6 1.46E-7 2.01E-7 1.21E-7 1.63E-7 1.67E-7
0.50 3.91E-7 3.92E-8 4.58E-8 3.18E-8 6.14E-8 6.29E-8
1.00 3.62E-8 1.06E-8 1.04E-8 8.33E-9 2.31E-8 2.38E-8
2.00 3.34E-9 2.85E-9 4.38E-9 2.18E-9 2.71E-9 8.98E-8
Irrig 2
0.05 8.06E-4 5.23 E-6 7.8SE-6 9.92E-6 3.09E-S 8.09E-7
0.10 8.14E-5 1.49E-6 1.72E-6 2.82E-6 5.91E-6 2.51E-7
0.25 3.92E-6 2.82E-7 2.33E-7 5.34E-7 6.63E-7 S.35E-8
0.50 3.97E-7 8.03E-8 S.11E-8 1.52E-7 1.27 E-7 1.66E-7
1.00 4.01E-8 2.28E-8 1.12E-8 4.31E-8 2.42E-8 5.15E-9
2.00 4.05E-9 6.49E-9 2.47E-9 1.22E-8 4.63E-9 1.59E-9
3.00 1.06E-9 3.11E-9 1.02E-9 5.86E-9 1.76E-9 8.0E-IO
172
Table III-6b. Temporal variability of hydraulic
conductivity (m/sec) as a function of soil
soil water suction, K(h), for Molokai soil.
0-25 em depth.
wetting/Drying Cycles
h pre-irrig 1 2 3 4 5
m (H2O) Irrig 1
0.05 3.60E-6 2.27E-5 2.00E-5 3.06E-5 6.99E-5 6.99E-6
0.10 1.3lE-6 7.l2E-6 4.66E-6 8.31E-6 1.40E-5 2.3lE-6
0.25 3.44E-7 1.54E-6 6.78E-7 1.49E-6 1.68E-6 5.66E-7
0.50 1.25E-7 4.83E-7 1.57E-7 4.04E-7 3.37E-7 1.35E-7
1.00 4.55E-8 1.52E-7 3.68E-8 1.10E-7 6.75E-8 6.74E-8
2.00 1.65E-8 4.78E-8 8.55E-9 2.99E-8 1.36E-8 2.32E-8
Irrig 2
0.05 9.8lE-S 8.20E-6 1.77E-S 8.66E-6 3.34E-6 5.74E-6
0.10 1.80E-5 3.11E-6 5.50E-6 1.48E-6 1.2lE-6 2.04E-6
0.25 1.93E-6 8.65E-7 1.19E-6 3.25E-7 3.19E-7 S.18E-6
0.50 3.55E-7 3.28E-7 3.73E-7 1.03E-7 1.16E-7 1.84E-7
1.00 6.S3E-8 1.24E-7 1.17E-7 3.27E-8 4.22E-7 6.53E-8
2.00 1.20E-8 4.73E-8 3.65E-8 1.04E-8 1.53E-8 2.32E-8
173
Table 1II-7a. Temporal variability of soil water retention
(m3/m3) data for Molokai soil, 0-7.5 em
depth.
Wetting/Drying Cycles
h pre-irrig 1 2 3 4 5
m( H2O) Irrig 1
0.00 0.568 0.512 0.515 0.510 0.507 0.502
0.10 0.563 0.498 0.492 0.489 0.490 0.487
0.25 0.551 0.489 0.482 0.485 0.486 0.483
0.50 0.530 0.471 0.473 0.465 0.467 0.460
1.00 0.460 0.427 0.430 0.421 0.411 0.414
2.00 0.378 0.354 0.342 0.340 0.335 0.338
3.00 0.340 0.341 0.341 0.345 0.341 0.337
4.00 0.325 0.340 0.339 0.378 0.336 0.334
Irrig 2
0.00 0.563 0.511 0.510 0.510 0.507 0.510
0.10 0.560 0.481 0.489 0.485 0.492 0.475
0.25 0.549 0.476 0.483 0.480 0.484 0.468
0.50 0.531 0.475 0.476 0.475 0.477 0.463
1.00 0.456 0.424 0.423 0.418 0.413 0.417
2000 0.390 0.371 0.368 0.361 0.359 0.360
3.00 0.367 0.368 0.350 0.345 0.351 0.353
4.00 0.360 0.362 0.348 0.342 0.348 0.351
174
Table 1II-7b. Temporal variability of soil water retention
(m3/m3) for Mo1okai soil. 7.5-25 cm depth.
Wetting/Drying Cycles
h pre-irrig 1 2 3 4 5--m of H2O Irrig 1
0.00 0.527 0.512 0.519 0.513 0.519 0.512
0.10 0.521 0.495 0.490 0.489 0.493 0.487
0.25 0.513 0.488 0.489 0.484 0.490 0.480
0.50 0.491 0.480 0.487 0.482 0.490 0.478
1.00 0.428 0.420 0.427 0.420 0.428 0.405
2.00 0.345 0.343 0.344 0.343 0.345 0.338
3.00 0.330 0.328 0.331 0.329 0.330 0.329
4.00 0.329 0.328 0.326 0.328 0.329 0.328
Irrig 2
0.00 0.524 0.510 0.510 0.510 0.513 0.510
0.10 0.519 0.493 0.491 0.486 0.491 0.486
0.25 0.503 0.486 0.488 0.485 0.483 0.480
0.50 0.490 0.481 0.483 0.482 0.483 0.481
1.00 0.426 0.421 0.426 0.420 0.428 0.422
2.00 0.365 0.348 0.340 0.348 0.346 0.340
3.00 0.332 0.329 0.338 0.333 0.331 0.330
4.00 0.328 0.326 0.325 0.331 0.328 0.329
175
APPENDIX IV CONTENTS
Waialua Soil
Table IV-I. Sorptivity by Infiltration with Positive Head.
a. Analysis of Variance.
b. Duncan's Multiple Range test
Table VI-2. Sorptivity by Infiltration With Negative Head.
a. Analysis of Variance.
b. Duncan's Multiple Range Test.
Table VI-3 Steady Infiltration Rate
Table VI-4 Analysis of Variance for Parameter
cm Depth.
for 0-5
Table VI-5. Hydraulic Conductivity as a Function of
Volumetric Water Content.
Table VI-6. Hydraulic Conductivity as a Fucntion of Soil
Water Suction.
Table VI-7. Soil Water Retention Data.
176
Table IV-I. Sorptivity with positive head for Waialua
soil.
a. Analysis of variance (log transformed).
Source DF SS MS F
Rep 2 0.0015 0.0007
WID Cycles 3 1.5606 0.5202 34.1*
Rep x Cycles 6 0.0917 0.0153
Sample Error 58 0.6409
Total 69 2.2947
b. Duncan' 5 Multi pl e Range Test.
Treatment Treatment Means (10-3 m/sec)
WID Cyc1 es
0 1.65 a
1 0.91 b
2 0.76 b
3 0.81 b
Any tw~ means having a common letter are not significantlydifferent at 5% probabil ity level.
177Table IV-2. 50rptivity with negative head for Waialua
soil.
a. Analysis of variance.
Source OF 55 MS F
Rep 2 0.0129 0.0065
WID Cycles 3 0.4999 0.1666 15.1*
Rep x Cycles 6 0.0664 0.0111
Sampling Error 84 0.7139
Total 95 1.2931
b. Duncan's mUltiple range test.
Treatments
WiD Cycles
o
1
2
3
Treatment Means (10-3 m/sec>
1.04 a
0.69 b
0.57 b
0.64 b
Table IV-3. Steady infiltration rate (10-6 m/sec) for
Waialua soil.
Treatments Infiltration Rate
WID Cycles
0 4.60
1 1.48
2 1.21
3 1.52
Table IV-4. Analysis of variance of parameter ~ for
Waialua soil.
178
Source DF 55 MS F
Rep 2 3.582 1.7912
WiD Cyclt.~s 3 12.253 4.0800 5.51*
Rep x Cycles 6 4.442 0.7400
Sample Error 12 12.201
Total 23 32.460
179
Table IV-5. Temporal variability of hydraulic conductivity
(m/see) as a function of soil water content,
K(6) , for Waialua soil. 0-5 and 0-25 cm depths ..
wetting/Drying Cycles
----------------------Vol. r·t. Pre-irrig 1 2 3
---------------m3/m3 0-5 cm depth
0.50 1.2lE-6 5.25E-8 3.68E-8 2.44E-8
0.45 1.94E-7 8.10E-9 4.70E-9 4.02E-9
0.40 2.50E-8 1.28E-9 4.7E-IO 5.3E-IO
0.35 2.45E-9 1.4E-lO 3.4E-ll 5.4E-ll
0.30 1.7E-lO 1.lE-ll 1.7E-12 3.9E-12
0-25 em depth
0.50 1.10E-6 7.94E-8 1.65E-8 3.06E-8
0.45 8.59E-8 4.47E-9 1.14E-9 1.85E-9
0.40 4.93E-9 1.8E-lO 5.7E-ll 8.0E-ll
0.35 1.9E-lO 4.7E-12 1.9E-12 2.3E-12
0.30 4.6E-12 6.9E-14 3.8E-14 3.8E-14
180
Table IV-6. Temporal variability of hydraulic conductivity
(m/sec) as a function of soil water suction,
K( h) , for waialua soil. 0-5 cm and 0-25 cm
depths.
wetting/Drying Cycles
--- -h 0 1 2 3
m of H2O 0-5 cm depth
0.05 5.47E-6 3.52E-8 1.35E-7 5.54E-8
0.10 1.11E-6 1.33E-8 5.62E-6 1.96E-8
0.25 1.36E-7 3.70E-9 1.78E-8 4.98E-9
0.50 2.70E-8 1.40E-9 6.30E-9 1.76E-9
1.00 5.46E-9 5.3E-IO 2.51E-9 6.2E-I0
2.00 1.10E-9 2.0E-I0 1.00E-9 2.2E-10
0-25 cm depth
0.05 2.54E-6 1.55E-6 5.76E-7 3.98E-6
0.10 7.64E-7 5.50E-7 2.06 E-7 1.59E-6
0.25 1.56 E-7 1.40E-7 5.26 E-8 4.69E-7
0.50 4.68E-8 4.97E-8 1.87E-8 1.87E-7
1.00 1.40E-8 1.76E-8 6.69E-9 7.44E-8
2.00 4.22E-9 6.27E-9 2.39E-9 2.96E-8
181
Table IV-7. Temporal variability of soil water retention
(m3/m3) for Waialua soil.
Wetting/Drying eyel es
h pre-irrig 1 2 3
m of H2O 0-7.5 ern depth
0.00 0.526 0.487 0.481 0.468
0.10 0.475 0.401 0.393 0.391
0.25 0.440 0.390 0.383 0.380
0.50 0.413 0.376 0.369 0.367
1.00 0.388 0.360 0.368 0.355
1.50 0.358 0.351 0.347 0.345
2.00 0.352 0.346 0.343 0.341
3.00 0.343 0.344 0.340 0.340
7.5-25 ern depth
0.00 0.486 0.478 0.477 0.474
0.10 0.465 0.456 0.453 0.451
0.25 0.451 0.430 0.428 0.426
0.50 0.410 0.407 0.406 0.372
1.00 0.375 0.370 0.372 0.368
1.50 0.365 0.363 0.365 0.364
2.00 0.360 0.358 0.356 0.358
3.00 0.353 0.350 0.351 0.351
APPENDIX V CONTENTS
182
Table V-I. Sorptivity with negative head for Field 220
(Molokai soil).
Tabl e V-II. Sorptivity with negative head for Field 145
(Lahaina soil).
183
Table V-I. Sorptivity with negative head (10-4 m/sec 1/2)
for Field 220 (Mo1okai soil). X,Y = 0,0 refers
to the 1 ow~r 1 eft corner of samp1 ing grid sbown
in Fig. 32.
No. X(m)
Y(m)
S No. X(m)
Y(m)
s
1 0 0 5.91 19 187 60 4.10
2 0 30 6.92 20 233 60 6.93
3 0 60 5.96 21 233 30 7.91
4 47 60 5.91 22 233 ~, 0 4.27
5 47 30 6.71 23 249 30 6.59
6 47 0 3.97 24 264 30 7.02
7 62 30 3.98 25 279 0 8.01
8 68 30 5.02 26 279 10 5.22
9 93 0 6.47 27 279 20 4.78
10 93 10 5.22 28 279 30 5.18
11 93 20 5.36 29 279 41 4.37
12 93 30 4.16 30 279 51 4.91
13 93 60 5.31 31 295 30 4.40
14 140 60 5.91 32 311 30 4.75
15 140 30 6.06 33 311 60 6.10
16 140 0 4.49 34 326 30 4.84
17 187 0 5.29 35 326 0 5.40
18 187 30 8.46 36 373 0 4.70
184
Table V-I. (Continued) Sorptivity with negative head (10-4
m/ae o 1/2) for Field 220 (Molokai soil). X,Y=
0,0 refers to the low~r left corner of sampling
grid show~ in Fig 32.
No.
37
38
39
40
41
42
X(m)
373
373
408
408
408
466
Y( m)
30
60
60
30
o
30
S
3.98
5.96
6.70
4.65
5.02
4.51
No.
43
44
45
46
47
48
X(m)
466
466
466
513
513
513
Y(m)
41
52
60
o
30
60
S
4.41
5.01
6.05
4.26
3.97
6.57
185
Table V-2. Sorptivity with negative head (10-4 m/sec 1/2)
for Field 145 (Lahaina soil). X,Y = 0,0 refers
to the low~r left corner of sampling grid showp
in Fig. 33.
No. X(m)
Y(m)
s No. X(m)
Y(m)
S
1 0 0 4.12 18 82 183 7.22
2 0 46 4.29 19 82 137 4.51
3 0 91 7.18 20 82 122 4.31
4 0 137 6.80 21 82 107 4.17
5 0 183 4.95 22 82 91 4.68
6 27 183 5.52 23 82 76 8.60
7 27 137 3.95 24 82 61 5.15
8 27 91 6.65 25 82 46 4.48
9 27 76 5.62 26 82 0 4.96
10 27 61 4.57 27 96 91 4.11
11 27 46 4.53 28 109 0 4.73
12 55 0 5.49 29 109 46 6.26
13 55 46 4.53 30 109 91 4.51
14 55 91 4.36 31 109 137 4.58
15 55 137 4.37 32 109 183 5.09
16 55 183 4.97 33 123 91 4.86
17 68 91 5.06 34 123 139 4.58
186
Table V-2. (Continued) Sorptivity with negative head (10-4
m/ae c 1/2) for Field 145 (Lahaina soil). X, Y =0,0 refers to the low~r left corner of sampling
grid show~ in Fig. 33.
No. X Y S No. X Y S(m) (m) (m) (m)
35 123 139 4.58 42 164 91 4.82
36 123 183 5.27 43 164 137 3.95
37 123 107 5.59 44 164 183 4.31
38 123 91 4.70 45 192 183 5.13
39 123 0 7.20 46 192 137 4.26
40 164 0 5.81 47 192 91 4.83
41 164 46 5.14 48 192 46 4.54
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