INFORMATION TO USERS · 2014-06-13 · INFORMATION TO USERS This reproduction was made from a copy...

INFORMATION TO USERS

This reproduction was made from a copy of a document sent to us for microfilming.While the most advanced technology has been used to photograph and reproducethis document, the quality of the reproduction is heavily dependent upon thequality of the material submitted.

The following explanation of techniques is provided to help clarify markings ornotations which may appear on this reproduction.

1. The sign or "target" for pages apparently lacking from the documentphotographed is "Missing Page(s)". If it was possible to obtain the missingpage(s) or section, they are spliced into the film along with adjacent pages. Thismay have necessitated cutting through an image and duplicating adjacent pagesto assure complete continuity.

2. When an image on the film is obliterated with a round black mark, it is anindication of either blurred copy because of movement during exposure,duplicate copy, or copyrighted materials that should not have been filmed. Forblurred pages, a good image of the page can be found in the adjacent frame. Ifcopyrighted materials were deleted, a target note will appear listing the pages inthe adjacent frame.

3. When a map, drawing or chart, etc., is part of the material being photographed,a definite method of "sectioning" the material has been followed. It iscustomary to begin filming at the upper left hand corner of a large sheet and tocontinue from left to right in equal sections with small overlaps. If necessary,sectioning is continued again-beginning below the first row and continuing onuntil complete.

4. For illustrations that cannot be satisfactorily reproduced by xerographicmeans, photographic prints can be purchased at additional cost and insertedinto your xerographic copy. These prints are available upon request from theDissertations Customer Services Department.

5. Some pages in any document may have indistinct print. In all cases the bestavailable copy has been filmed.

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



Hydraulic Conductivity •••••••••••••••••••••••••• 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


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.


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.



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).


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.


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.


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;).


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


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


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


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


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.


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.


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.


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


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.


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.


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.


----

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.


------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.


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.


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.


b. Duncan's Multiple Range test

Table VI-2. Sorptivity by Infiltration With Negative Head.


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.


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 ..


----------------------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.


--- -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

LITERATURE CITED

Allmaras, R.R., R.W. Rickman, L.G. Ekin and B.A. Kimball.1977. Chiseling influences on soil hydraulicproperties. Soil Sci. Soc. Am. J. 41:796-803.

Amemiya, M. 1968. Tillage and soil water relations of cornas influenced by weather. Agron. J. 60:534-537.

Babalola, O. 1977. Spatial variability of soil waterproperties in tropical soils of Nigeria. Soil Sci.126:269-279.

Baeumer, K., and A.P. Bakermans. 1973. Zero tillage. Adv.Agron. 25:77-123.

Baker, F.G., and J. Bouma. 1976. Variability of hydraulicconductivity in two subsurface horizons of two siltloam soils. Soil Sci. Soc. Am. J. 40:219-221.

Benjamin, J.R. and C.A. Cornell. 1970. ProbabilityStatistics and Decisions for Civil Engineers.McGraw-Hill Book Company. New York. 468p.

Berndt, R.D. and K.J. Coughlan. 1976. The nature of changesin bulk density with water content in a crackingclay. Aust. J. Soil Res. 15:27-37.

Baver, L.D. and A.C. Trouse. 1970. Tillage problems in theHawaiian suger industry. Unpublished Report.Hawaiiian Suger Planters Association.

Bhuiyan, S.I., E.A. Hiller and C.H.M.van Bavel. 1971.Dyanamic simulation of verticle infiltration intounsaturated soils. Water Resour. Res. 7:1597-1606.

Blake, G.P. 1965. Particle Density. Chapter 29. In C.A.(ed.) Methods of Soil Analysis. Part II.American Society of Agronomy.

Blake, G.R., W.W. Nelson and R.R. Allmaras. 1976.Persistence of subsoil compaction in a Mollisol. SoilSci. Soc. Am. J. 40:943-948.

Blakely, G.B., W.C. Burrows, D.M. van Doren and W.E.Larson.1978. Tillage terminology. Glossary of soil scienceterms. Soil Sci. Soc. Am.

188

Bodman, G.B. and G.K. Constantin. 1965. Influence ofparticle size distribution in soil compaction.Hilgardia 36:576-591.

Bodman, G.B. and J. Rubin. 1948. Soil Puddling. Soil Sci.Soc. Am. Proc. 13:27-36.

Bouma, J. and J.L~ Anderson. 1973. Relationships betweensoil structure and conductivity. p.77-105. InR.R.Bruce (ed.) Field Water Regime. Soil Sci. Soc.Am. Publ. Sere S.

Bresler, E. and R.E. Green. 1982. Soil parameters andsampling scheme for characterizing soil hydraulicproperties in a watershed. Technical Report No. 148.Water Resources Research Center. University ofHawaii. Honolulu, Hawaii.

Brewer, R. and J.R. Saleeman. 1980. Soil structure andfrabric. Their definition and description. J. SoilSci.ll:172-18S.

Brooks, R.H. and A.T. Corey. 1964. Hydraulic properties ofporous media. Hydrology Paper No.8, Colorado StateUniversity, Fort Collins, pp 1-15.

Burgess, T.M. and R. Webster. 1980a. Optimal interpolationand isarithimic mapping of soil properties. 1. Thesemi variogram and punctual kriging. J. of Soil Sci.31:315-331.

Burgess, T.M. and R. Webster. 1980b. Optimal interpolationand isarithimic mapping of soil properties. ii. Blockkriging. J. of Soil Sci. 31:333-341.

Burwell, R.E., R.R. Allmaras and M. Amemiya. 1963. A fieldmeasurement of total porosity and surface microreliefof soils. Soil Sci. Soc. Am. Proc. 27:697-700.

Burwell, R.E., R.R. Allmaras and L.L. Sloneker. 1966.Structural alteration of soil surface by tillage andrainfall. J. Soil Water Cons. 21:61-63.

Burwell, R.E. and W.E. Larson. 1969. Infiltration asinfluenced by tillage induced random roughness andporespace. Soil Sci. Am. Proc. 33:449-452.

Burwell, R.E., L.L. Slonker and W.W. Nelson. 1968. Tillageinfluences on water intake. J. Soil Water Conserve 23:185-187.

189

Cameron, D.R. 1978. Variability of soil water retentioncurves and predicted hydraulic conductivities in asmall plot. Soil Sci. 126:364-370.

Campbell, G.S. 1974. A simple method for determiningunsaturated conductivity from moisture retention data.Soil Sci. 117:311-314. .

Canarachi, A., A. Trandafirescu and I. Colibas. 1984. Effectof induced compaction by wheel traffic on soilphysical properties and yield of maize in Romania.Soil and Tillage Res. 4:199-213.

Cassel, D.K. 1983a. Spatial and temporal variability ofsoil physical properties following tillage of Norfolkloamy sand. Soil Sci. Soc. Am. J. 47:196-201.

Cassel, D.K. 1983b. Tillage effects on bulk density andmechanical impedence. In P.W.Unger (ed.) PredictingTillage Effects on Soil Physical Properties andProcesses. ASA special publication no. 44.

Cassel, D.K. and A. Baver. 1975. Spatial variability ofsoils below the depth of tillage. Bulk density and 15atmosphere percentage. Soil Sci. Soc. Am. Proc.39:247-250.

Chong, S.-K. 1979. Infiltration prediction based on insitumeasurement ofsoil water properties. Ph.D. Thesis.University of Hawaii.

Chong, S.-K. and R.E. Green. 1979. Application of fieldmeasured sorptivity for simplified infiltrationprediction. In Proceedings of the SYmposium onHydrologic Transport Modeling. New Orleans, LA.Dec. 1979. p 88-96. ASAE publication 4-80.

Chong, S.-K. and R.E. Green. 1983. Sorptivity measurementand its application. In Advances in Infiltration.Proc. National Conference on Advances in Infiltration.Chicago. Illinois. Dec. 12-13. American Society ofAgricultural Engineers.

Chong, S.-K., R.E. Green and L.R. Ahuja. 1981. Simple insitudeterminations of hydraulic conductivity by powerfunction descriptions of drainage. Water resour. Res17:1109-1114.

190

Chong, S.-K. and S.M. Moor 1982. Variation in hydraulic soilproperties caused by mining activities. In proc. ofsymposium on surface mining hydrology, sedimentologyand reclamation. Lexington, Kentucky. Dec 5-10 1982.P 407-417. University of Kentucky. Lexington.

Clothier, B.E. and I. White. 1981. Measurement of sorptivityand soil water diffusivity in the field. Soil Sci.Soc. Am. J. 45:241-245.

Coelho, M.A. 1974. S~tia1 variability of water related soiphysical properties. Ph.D. Thesis. University ofArizona.

Corey, J.C., S.F. Peterson and M.A. Wakat. 1971. Measurementof attenuation of Cs and Am gamma rays for soildensity and water content determinations. Soil Sci.Soc. Am. Proc. 35:215-219.

Crutcher, R.L. 1975. A note on the possible misuse of theKolmogorov-Smirnov test. J of App1. Meteorology14:1600-1603.

Dane, J.R. and S. Hruska. 1983. Insitu determination of soilhydraulic properties during drainage. Soil Sci. Soc.Am. Proc. 47:619-624.

Dirksen, C. 1975. Determination of soil water diffusivity bysorptivity measurements. Soil Sci. Soc. Am. Proc.39: 22-27.

Dixon, R.M. and A.E. Peterson. 1971. Water movement in largesoil pores. A channel system concept of infiltration.Res. RepoJ:t 72. University of Wisconsin.

Edwards, W.M. 1982. Predicting tillage effects on. infiltration. In P.W.Unger (ed.) Predicting Tillage

Effects on Soil Physical Properies and Processes. ASAspecial pUblication no. 44.

Edwards, W.M. and W.E. Larson. 1969. Infiltration of waterinto soils as influenced by surface seal development.Trans. ASAE. 12:463-465.

Ehlers, W. 1975. Observation on earthworm channels andinfiltration of tilled and untilled loess soil. SoilSci. 119:242-249.

Ehlers, W. 1976. Rapid determination of undisturbedhydraulic conductivity in tilled and untilled loesssoil. Soil. Sci. Soc. Am. J. 40:837 840.

191

Ehlers, W. and R. van Der Ploeg. 1976. Simulaton ofinfiltration into tilled and untilled field soilsderived from loess. In G.C.Vansteenkiste (ed.) SystemsSimulation in Water Resources. North HollandPUblishing Company. Holland.

Elr·ick, D.E., J.H. Scandrett and E.E.Miller. 1959. Tests ofcapillary flow scaling. Soil Sci •. Soc. Am. Proc. 23:329-332.

Emmond, G.S. 1971. Effects of rotation, tillage treatmentsand fertilizers on the aggregation of a clay soil.Can. J. Soil Sci. 51:235-241.

Endelman, F.G., G.E.P. Box, J.R. Boyle and R.R. Hughes.1974. The mathematical modelling of soil waternitrogen phenomena. FDFB-IBP-78-8. Oak naturallaboratory. Oak Ridge. Tenn.

Falayi, O. and J. Bouma. 1975. Relationship between thehydraulic conductivity of surface crust and soilmanagement in a Typic hapludalf. Soil Sci. Soc. ~~.

Proc. 39:957-963.

Farrell, D.A. and W.E. Larson. 1972. Dynamics of the soilwater system during a rain storm. Soil Sci. 113:88-95.

Fleming, P.M. and D.E. Smiles. 1975. Infiltration of waterinto soil. In T.G. Chapman and F.X. Dunn (ed.)Prediction in Catchment Hydrology. Aust. Acadamy ofScience.

Gardner, W.R. 1956. Representation of soil aggregete sizedistribution by a logarathmic normal distribution.Soil Sci. Soc. Am. Proc. 20:151-153.

Gardner, W.R. 1970. Field measurements of soil waterdiffusivity. Soil Sci. Aoc. Am. Proc. 34:832-833.

Gardner, W.R., D. Hillel and Y. Benyamini. 1970. Postirrigation movement of soil water. 1. Redistribution.Water Resour. Res. 6:851-861.

Ghavami, M. 1970. A functional relationship for estimatingthe settlement of loosely packed unstable agricUlturalsoils due to watering. Ph.D. thesis. Utah StateUniversity.

Gilman, R.D. 1962. Infiltration measurements under differentmanagement practices and soil types. M.S. thesis.Purdue University.

192

Gish, T.J. and J.L. Starr. 1983. Temporal variability ofinfiltration under field conditions. In Proc. NationalConference on Advances in Infiltration. Chicago.Illinois. Dec 12-13. American Society of AgriculturalEngineers.

Green, R.E. and J.C. Corey. 1971. Calculation of hydraulicconductivity. A further evaluation of some predictivemethods. Soil Sci. Soc. Am. Proc. 35:3-8.

Green, R.E., L.R. Ahuja., S.R. Chong and L.S. Lau. 1982.Water conduction in Hawaii oxic soils. TechnicalReport no. 143. Water Resources Research Center.University of Hawaii at Manoa. Honolulu. Hawaii.

Green, R.E., L.R. Ahuja and S.R. Chong. 1984. Unsaturatedhydraulic conductivity, soil water diffusivity andsorptivity. Field methods. Chapter 30. In A. Klute(ed.) Methods of Soil Analysis. Part 1. Physical andminaralogical properties. ASA Monograph. Secondedition. In press.

Gregory, J.M., J.M. Steichen and M.E. Nail. 1979.Infiltration influenced by tillage. Part 2aInfiltration Equation. ASAE paper no. 79-2043. Agric.Eng. Dept. Missouri University •

. Haan, C.T. 1977. Statistical Methods in Hydrology. Chapter 7and 8. The Iowa State University Press. Iowa, Ames.Iowa.

Hamblin, A.P. 1982. Soil water behaviour in response tochanging in soil structure. J. Soil Sci. 33:375-386.

Harris, W.L. 1971. The soil compaction process. In K.R.Barns(ed.) Compaction of Agricultural Soils. ASAEmonograph.

Haverkamp, R.M., M. Vauclin, J. Touma, P.J. Wierenga andG. Vachaud. 1977. A comparison of numerical simulationmodels for one-dimensional infiltration. Soil Sci.Soc. Am. J. 41:285-294.

Hettiaratchi, D.R.P. and J.R. O'Callaghan. 1980. Mechanicalbehaviour of agricultural soils. J. Agric. Eng. Res.25:239-259.

Hillel, D. 1977. Computer simulation of soil water dynamics.International development research center. Ottawa.

Hillel, D. and H.R. Gardner. 1969. Steady infiltration intocrust topped profiles. Soil Sci. 108:137-142.

193

Holt, R.F., W.B. Voorhees and R.R. Allmaras. 1967. Nutrientrelationsips and fertilizer placement as effected bytillage. Conference of tillage for greater cropproduction. ASAE pUb. Proc-168.

Ikawa, I., H.H. Sato, A.K.S. Chang, S. Nakamura, E. Robelloand J.S. Periaswami. 1982. Soils of the HawaiiAgricultural Experimental station. University ofHawaii. Soil survey, laboratory data and soildescriptions. HITAR pUblication.

Jackson, R.D. 1963. porosity and soil water diffusivityrelations. Soil Sci. Soc. Am. Proc. 27:123-126.

Jamison, V.C. 1953. Changes in air water relationships dueto structural improvement of soils. Soil Sci.76:143-151.

Kemper, W.O. and E.J. Koch. 1966. Aggregate stability ofsoils from Western U.S. and Canada. USDA Tech. Bul.no. 1355.

Kemper, W.O., B.A. Stewart and L.K. Porter. 1~71. Effect ofcompaction on soil nutrient status. In K.K. Barns(ed.) Compaction o~ Agricural Soils. ASAE monograph.

Kemper, W.O., J.S. Olsen and A. Hodgdon. 1975. Irrigationmethods as a determinant of large pore persistence andcrust strength of cultivated soils. Soil Sci. Soc. Am.Proc. 39:519-523.

Khan, M.K. 1979. Computer simulation of soil processesrelevant to irrigation and fertilizer management.Ph.D. thesis. University of Hawaii.

Klute, A. 1973. Soil water flow theory and its applicationin field situations.ln R.R.Bruce (ed.) Field SoilWater Regimes. SSSA special publication No.5.ASA,Madison. Wisconsin.

Klute, A. 1982. Tillage effects on the hydraulic propertiesof the soil. In P.W.Unger (ed.) Predicting TillageEffects on Soil Physical Properties and Processes.ASA special publication no. 44.

Klute, A. and G.E. Wilkinson. 1958. Some tests of thesimilar media concept of capillary flow. Soil Sci.Soc. Am. Proc. 22:278-281.

Larson, W.E. 1963. Important soil parameters for evaluatingtillage practices in the United States. Neth. J.Agric. Sci. 11:100-109.

194

Larson, W.E. 1964. Soil parameters for evaluating tillageneeds and operations. Soil Sci. Soc. Am. Proc.28:119-122.

Larson, W.E. and R.R. Allmaras. 1971. Management factors andnatural forces as related to compaction. In K.K.Barns(ed.) Compaction in Agricultural soils. ASAEmonograph.

Libardi, P.L., K. Reichardt, D.R. Nielsen and J.W. Bigger.1980. Simple methods for estimating soil hydraulicconductivity. Soil Sci. Soc. Am. J. 44:3-7.

Lillifors, H.W. 1967. On the Kolmogorow-Smirnov test fornormality when mean and variance unknown. Am. Stat.Assoc. J. 62:399-402.

Lovely, W.G. 1967. Effect of tillage on clod size, bulkdensity roughness and po~osity. Conference on tillagefor greater crop production. ASAE pUb. PROC-168.

Mannering, J.V. 1967. The relationship of some physical andchemical properties of soil to surface sealing. Ph.D.thesis. Purdue University.

Marshall, T.J. and J.W.Bolmes. 1979. Soil Physics.Cambridge University Press.

Massey, F.J.,Jr,. 1951. The Kolmogorov_Smirnov test forgoodness of fit. J. Am. Stat. Assoc. 68:176-179.

Miller, E.E. 1980. Similitude and scaling of soil waterphenomena. In D. Billel (ed.) Applications of SoilPhysics. Academic press.

Miller, E.E. and R.D. Miller. 1956. Physical theory forcapillary flow phenomena. J. Appl. Phys. 27:324-332.

Miller, R.D. and E.E. Miller. 1955. Theory of capillaryflow. 2. Experimental information. Soil Sci. Soc. Am.Proc. 19:271-275.

Miller, S.A. and A.P. Mazurak. 1958. Relation of particleand pore size to the growth of sunflower. Soil Sci.Soc. Am. Proc. 21:481-484.

Millington, R.J. and J.P. Quirk. 1959. Permeability ofporous media. Nature 183:387-388.

Moldenhauer, W.C. 1970. Influence of rainfall energy on soilloss and infiltration rates. 2. Effect of clod sizedistribution. Soil Sci. Soc. Am. Proc. 34:673-677.

195

Moldenhauer, W.C. and D.C. Long. 1964. Influence of rainfallenergy on soil loss and infiltration rates. 1. Effectover a range of textures. Soil Sci. Soc. Am. Proc. 28:813-817.

Maulem, Y. 1976. A new model for predicting the hydraulicconductivity of unsaturated porous media. WaterResour. Res. 12:513-522.

Nielsen, D.R. and J.W. Bigger. 1961. Measuring capillaryconductivity. Soil Sci. 91:192-193.

Nielsen, D.R., J.W. Bigger and K.T. Erh. 1973. Spatialvariability of field measured soil water properties.Hilgardia 42:215-259.

Nofziger, D.L. 1972. Water and soil behavior undertransiently wetting conditions. Ph.D. thesis. PurdueUniversity.

Oschwald, W.R. 1973. Chisel plow and strip tillage systems.In Conservation Tillage. Soil Conserve Soc. Am.

Page, J.B. 1947. Advantages of the pressure pyconometer formeasuring the porespace in soils. Soil Sci. Soc. Am.Proc. 12:81-84.

Parlange, J.-Y. 1971. Theory of water movement in soils.Part 2. Soil Sci. 111:170-174.

Peck, A.J., R.J. Luxmoore and J.L. Stolzy. 1977. Effects ofspatial variability of soil hydraulic properties inwater buget modeling. Water Resour. Res. 13:348-354.

Peterson, R.G. and L.D. Calvin. 1965. In C.A. Black (ed.)Methods of Soil Analysis. Part 1. ASA. Madison.Wisconsin.

Phillip, J.R. 1967. Sorption and infiltration inheterogeneous media. Aust. J. Soil Res. 5:1-10.

Reginato, R.J. 1974. Gamma radiation measurements of bulkdensity changes in a soil pedon following irrigation.Soil Sci. Soc. Am. Proc. 38:24-29.

Reichardt, K., D.R. Neilsen and J.W. Biggar. 1972. Scalingof horizontal infiltration into homogeneous soils.Seil Sci. Soc. Am. Proc. 36:241-245.

Reicosky, D.C., W.B. Voorhees and J.K. Ranke. 1981.Unsaturated water flow through a simulated wheeltrack. Soil Sci. Soc. Am. J. 45:3-7.

196

Rogowski, A.S. 1980. Hydrologic parameters distribution on amine spoil. In proc. of symposium on watershedmanagement. Boise, Idaho. July 20-23, 1980. Am. Soc.of Civil Engineers: 764-780. New York.

Roscoe, R.H., A.N. Schofield and C.R. Wroth. 1958. On theyielding of soils. Geotechnique. 8:22-53.

Russo, D. and E. Bresler. 1980a. Scaling soil hydraulicprope~ties of a heterogeneous field. Soil Sci. Soc.Am. J. 44:681-683.

Russo, D and E. Bresler. 1980b. Field determination of soilhydraulic properties for statistical analysis. SoilSci. Soc. Am. J. 44:697-702.

Schofield, A. and P. Wroth. 1968. Critical State SoilMechanics. McGraw-Hill Book Co.

Schroeder, S.A., W.C. Moldenhauer and J.V. Mannering. 1979wStudies of tillage induced effects on hydraulicconductivity. Tech. Rep. 177. Univ. of Indiana.

Sharma, M.L., G.A. Gander and C.G. Hunt. 1979. Spatialvariability of infiltration of a watershed. J. Hydrol.45: 101-122. .-

Sharma, M.L. and R.L. Luxmoore. 1979. Soil spatialvariability and its consequences on simulatedwater balance. Water Resour. Res. 15:1567-1573.

Simmons, C.S., D.R. Nielsen and J.W. Biggar. 1979. Scalingof field measured soil water properties. Hilgardia47:77-149.

Springer, E.P. and G.F. Gifford. 1980. Spatial variabilityof rangeland infiltration rates. Wate~ Resour. Bull.16:550-551.

Swartzendruber, D. 1960. Water flow through a soil profileas affected by the least permiable layer. J. Geophys.Res. 65:4032-4042.

Talsma, T. 1969. Insitu measurements of sorptivity. Aust. J.Soil. Res. 17:269-276.

Talsma, T. and J.Y. Parlange. 1972. One dimansional verticalinfiltration. Aust. J. Soil. Res. 10:143-150.

197

Taylor, H.M. 1971. Soil conditions as they effect plantestablishment, root development and yield. InK.K. Barns (ed.) Compaction of Agricultural soils.ASAE Monograph.

Taylor f H.M. and L.F. Ratliff. 1969. Root elongation ratesof cotton as a function of soil strength and soilwater content. Soil Sci. 108:113-119.

Terzaghi, K. 1943. Theoratical Soil Mechanics. John Willey &Sons. New Yo:k.

Thompson, L.M. and F.R. Koch 1978. Soils and soilfertility. McGraw-Hill book Co. New York.

Towner, G.D. 1983. Effective stress in unsaturated soils andtheir applicability in the theory of critical statesoil mechanics. J. Soil Sci. 34:429-435.

Towner, G.D. and E.C. Childs. 1972. The mechanical strengthof unsaturated porous granular media. J. Soil Sci.23:481-498.

Trouse, A.C. 1964. Effect of compression of some sUbtropicalsoils on the soil properties and upon rootdevelopment. Ph.D. -'Thesis. University of Hawaii.

van Dulin, R.H. 1956. The influence of tillage on conductionof heat, diffusion of air and infiltration of water insoil. Rep. Agric. Invest. No. 62.7 Director ofAgriculture. Netherlands.

van Genuchten, M.Th. 1980. A closed form equation forpredicting the hydraUlic conductivity of unsaturatedsoils. Soil Sci. Soc. Am. J. 44:892-898.

van Genuchten, R. 1978. Calculating the unsaturatedhydraUlic conductivity with a new closed formanalytical model. Res. Rep. 78-WR-08. Water resourceprogram. Dep. Civil Eng. Princeton University.

Varisteenkiste, G.C. 1976. System smulation in the testingrole. System Simulation of Water Resources. NorthHolland Publishing Co.

Voorhees, W.W. 1977. Soil compaction in research progressand needs. Conservation tillage. ARS-USDA no.57: 43-46.

198

Voorhees, W.W., C.G. Senst and W.W. Nelson. 1978. Compactionand soil structure modification by wheel traffic inthe northern corn belt. Soil Sci. Soc. Am. J.42:344-349.

Warkentin, B.P. 1971 Effects of compaction on content andtransmission of water in soils. In K.K.Barns (ed.)Compaction of Agricultural Soils. ASAE Monograph.

Warrick, A.W., G.J. Mulen and D.R. Neilsen. 1977a.Prediction of soil water flux based upon fieldmeasured soil water properties. Soil Sci. Soc. Am.Proc. 41:14-19.

Warrick, A.W., G.J. Mulen and D.R. Neilsen. 1977b. Scalingfield measured soil hydraUlic properties using similarmedia concept. Water Resour. Res. 13:355-362.

Weibull, W. 1939. A statistical stUdy of the strength ofmaterial. Ing. Vetenskaps Akad. Handl (Stockholm).Vol 151: pp 15.

Wilkinson, G.W. and A. Klute. 1959. Some tests of thesimilar media concept of capillary flow. Soil Sci.Soc. Am. Proc. 23:434-437.

Williams, R.E. and D.W. Allman 1969. Factors affectinginfiltration and recharge in a loess-covered basin.J. Hydrol. 8:265-281.

Wischmeier, W.H. 1959. A rainfall erosion index for auniversal soil loss equation. Soil Sci. Soc. Am. Proc.23:246-249.

Wood, H.B. 1977. Hydrologic differences between selectedforested and agriCUltural soils. in Hawaii. Soil Sci.Soc. Am. J. 41:132-136.

Whisler, F.D., A.A. Curtis, A. Nicnam and J.M. Romkens.1977. Modeling infiltration as affected by soilcrusting. In H.J.Morel-Seytoux (ed.) Surface andSubsurface Hydrology. Water Resource Publication. FortCollins.

Yamamato, T. 1963. Soil moisture contents and physicalproperties of selected Hawaiian soils. u.S. forestService Res. Rep. PSW-P2. Pacific Sowthwest ForestRange Exp. Station. Berke1y, Calf.

Yong, R.N. and B.P. Warkentin. 1966. Introduction to soilbehaviour. The Macmillan Co. New York.

199

Youngs, E.G. 1981. Use of similar media theory ininfiltration and runoff relationships. Inpre-symposium proceedings of international symposiumon rainfall-runoff modeling. Mississipi StateUniversity. May 18-21, 1981.

INFORMATION TO USERS · 2014-06-13 · INFORMATION TO USERS This reproduction was made from a copy...

Documents

Transcript of INFORMATION TO USERS · 2014-06-13 · INFORMATION TO USERS This reproduction was made from a copy...