AN ABSTRACT OF THE THESIS OF
Chengci Chen for the degree of Doctor of Philosophy in Soil Science presented on
January 9, 1998.
Title: Soil Water Availability and Chemical Transport in a Pear (Pyrus communis)
Orchard Swelling Clay Soil under Micro and Flood Irrigation.
Redacted for privacy
Abstract approved:
Ri
Rosfpoerg
Macropore flow can accelerate agrichemical transport and has been shown to
contribute to contamination in shallow groundwater areas. Localized ponding at the
ground surface is one of the conditions required to initiate macropore flow. Two types of
microirrigation systems, which apply water at a sufficiently low rate to reduce ponding in
a shrinking soil, are investigated in this thesis. Microsprinlders (MI, applying 2.8 mm/hr)
and pulsators (PU, applying 0.5 mm/hr) were compared to flood irrigation (FL) which is
the conventional orchard practice. Calcium bromide (CaBr2), rubidium bromide (RbBr),
and blue dye were applied on the soil surface as tracers to monitor water and chemical
transport through soil. Passive Capillary Samplers (PCAPS) were installed at 120 cm
depth to collect soil percolate. Soil cores were taken to measure the movement of
chemicals through the soil profile. Soil moisture content and pear (Pyrus communis) fruit
diameter were measured regularly. Pear yield at harvest, and fruit firmness and fungal
decay during storage were examined to detect association with irrigation method. Soil
shrinkage characteristics were also measured to determine if corrections were needed in
neutron probe moisture measurements. The clay soil had great shrinkage capacity; as the
water content changed from 0.35 to 0.19 g/g (equivalent to 0.03 to 1.5 MPa water
potential) the volume decreased by 18%. Microsprinlders and pulsators supplied similar
amounts of plant-available water as flood irrigation. Pear fruit yield, fruit size expansion
rate, and fruit firmness decline rate during storage were statistically indistinguishable for
the three irrigation treatments. Low intensity irrigation by PU and MI following the
tracer application enhanced the movement of the tracers into soil aggregates, thereby
reducing the leaching via macropores in the subsequent irrigation and thunderstorms. MI
and PU irrigation generated little deep percolation or preferential flow. The amount of
water and chemical tracers collected in PCAPS were 100 times greater under FL than
under MI or PU. The transport of adsorbed tracers (Rb and blue dye) was much slower
than the non-adsorbed one (Br). Microsprinkler and pulsator irrigation can be used in
such cracking clay soil to protect groundwater from contamination, while producing
quality fruit comparable to flood irrigation.
©Copyright by Chengci Chen
January 9, 1998
All Right Reserved
Soil Water Availability and Chemical Transport in a
Pear (Pyrus communis) Orchard Swelling Clay
Soil under Micro and Flood Irrigation
by
Chengci Chen
A THESIS
submitted to
Oregon State University
in partial fulfillment of
the requirements for the
degree of
DOCTOR OF PHILOSOPHY
Presented January 9, 1998.
Commencement June, 1998.
Doctor of Philosophy thesis of Chengci Chen presented on January 9, 1998.
APPROVED:
Redacted for privacy
Major Professor, repre(ohting Soil
SA::
Redacted for privacy
Chair of Department of Crop and Soil Science
Redacted for privacy
Dean of Graduate chool
I understand that my thesis will become part of the permanent collection of Oregon State
University libraries. My signature below authorizes release of my thesis to any reader
upon request.
Redacted for privacy
Chengci Chen, Author
Acknowledgments
I want to acknowledge the following people, without their assistance this research
would not have been possible:
First, financial support for this study came from USDA-NRICGP grant # 92-37101-7567
and Oregon Department of Agriculture grant # 30-262-9053.
I want to express my sincere thanks to my adviser, Dr. Richard Roseberg, for his
teaching, encouragement, advice, and support in numerous ways. Thanks also go to Dr.
John Selker for his teaching, and invaluable advice in my research and paper writing.
Thanks to Dr. David Sugar for his advice, technical support, and for providing facilities
and technicians for the pear storage experiment. Thanks to Dr. Alan Mitchell for
providing me literature and technical advice in the soil shrinkage study.
I also want to thank the staff at the Southern Oregon Research and Extension Center for
their assistance in many ways: Joe Kepiro assisted with installing PCAPS and neutron
probe access tubes, applying chemical tracers, sampling and grinding soil cores; Ogden
Kellogg assisted with grinding soil samples and harvesting pears; Don White helped to
dig trenches, manage the orchard, and solve mechanical problems; Kate Powers and Sally
Basile helped to measure pear fruit firmness and fungal decay lesions; Robert Allen
helped with computer trouble-shooting.
Many thanks are extended to the superintendent of SOREC, Mike Howell, for allowing
me and my family to live on the station and providing us many kinds of help; Carol
Weese, Rick Hilton, and Phil Van Buskirk for allowing me to use their office facilities;
and John Yungen for his mechanical trouble-shooting.
Finally, I appreciate my wife Wnxin and my son David for their support, patience, and
love.
Contribution of Authors
Dr. Richard Roseberg is the major professor. Dr. John Selker was involved in
field experiment design, PCAPS design and manufacture, and paper editing. Dr. David
Sugar was involved in designing the pear storage experiment, and paper editing.
Table of Contents
Page
Introduction
Chapter 1. Soil Shrinkage Characteristic and its Relation to
Other Soil Physical Properties
ABSTRACT
INTRODUCTION
MATERIALS AND METHODS
Soil shrinkage curve
Field bulk density
Calculation of porosity
Neutron moisture meter calibration in the field
Calibration the effect of shrinkage on neutron
moisture meter measurement
RESULTS AND DISCUSSION
Soil shrinkage curve
Soil bulk density
Soil porosity
Effect of shrinkage on neutron moisture meter measurement
CONCLUSIONS
REFERENCES
Chapter 2. Soil Water Availability and Pear Growth and Quality
under Micro and Flood Irrigation
ABSTRACT
INTRODUCTION
MATERIALS AND METHODS
Experimental site
Irrigation systems
Soil water measurement
Fruit size, weight, and yield measurements
Fruit firmness and fungal decay determinations
Statistical analysis
RESULTS AND DISCUSSION
1995 growing season
1996 growing season
1
3
4
5
9
9
10
11
14
15
16
16
18
19
21
25
26
29
... 30
31
33
33
34
35
35
36
36
37
37
41
Table of Contents (continued)
Page
CONCLUSIONS
REFERENCES
Chapter 3. Macropore Flow and Chemical Transport under Micro and
Flood Irrigation Systems
ABSTRACT
INTRODUCTION
MATERIALS AND METHODS
Site description
Irrigation systems
Soil moisture
PCAPS samplers
Chemical tracers
Soil core samples
Chemical analysis
RESULTS AND DISCUSSION
Winter rainy season
Summer irrigation season
CONCLUSIONS
REFERENCES
45
46
48
49
50
60
60
61
63
63
65
66
67
68
70
82
... 100
102
Summary
109
Bibliography
113
122
Appendices
123
APPENDIX A. RESULTS OF ANALYSIS OF VARIANCE
129
APPENDIX B. RESULTS OF REGRESSION ANALYSIS
APPENDIX C. DISTRIBUTION OF Br IN SOIL IN THE GRASS LANE 134
APPENDIX D. MEDFORD STATION WEATHER, GROUNDWATER,
139
SOIL WATER, AND PERCOLATE DATA
List of Figures
Figures
Page
1-1. Soil shrinkage characteristic curve
...
16
1-2. Soil bulk density at different soil moisture contents for both field
cores and clods with fittted relationships for both
...
18
1-3. Total, water-filled, and air-filled porosity of the soil clods
at different matric potentials
20
1-4. Total, water-filled, and air-filled porosity of the field soil cores
at different matric potentials
21
1-5. Plot of count ratio versus volumetric water content calculated for
a fixed bulk density and bulk density that varies due to shrinkage
22
1-6. Plot of neutron probe calibration curve with and without correction
of count ratio calculated according to Greacen and Schrale (1976)
23
2-1. Available water profile for pulsator, microsprinlder, and flood
irrigation on September 7, 1995
37
2-2. Cumulative fruit diameter and fruit expansion rate under three
irrigation treatments in 1995
39
2-3. Firmness decline during storage for fruit from three irrigation
treatments in 1995
40
2-4. Plant-available water in top 120 cm soil profile under three
irrigation treatments in 1996
42
2-5. Cumulative fruit diameter and expansion rate under three
irrigation treatments in 1996
43
2-6. Firmness decline during storage for fruit from three
irrigation treatments in 1996
44
3-1. Schematic of the field experiment
62
List of Figures (continued)
Figures
Page
3-2. Precipitation, total soil water in the top 120 cm, and groundwater
table level at the experimental site
69
3-3. Br distribution in soil profile within the tree row on 12/11/1995
71
3-4. Rb distribution in soil profile within the tree row on 12/11/1995
73
3-5. Volume of percolate collected in the PCAPS during the period
between 10/6/1995 and 12/20/1995
75
3-6. Concentration of Br in percolate collected in the PCAPS during
the period between 10/6/1995 and 12/20/1995
76
3-7. Concentration of Rb in percolate collected in the PCAPS during
the period between 10/6/1995 and 12/20/1995
79
3-8. Br distribution in soil profile within the tree row on 6/24/1996
83
3-9. Rb distribution in soil profile within the tree row on 6/24/1996
86
3-10. Br distribution in soil profile within the tree row on 8/5/1996
88
3-11. Br distribution in soil profile within the tree row on 10/8/1996
93
3-12. Average Br concentration of 4 soils cores within the tree row
on 8/5/96 and 10/8/96
95
3-13. Volume of percolate collected in the PCAPS during the period
between 8/8/1996 and 10/7/1996
98
List of Tables
Tables
Page
1-1. A typical profile description of the test soil
10
1-2. Slope and limit of each shrinkage phase for the three soil clods
17
2-1. Particle size composition of the tested soils at three irrigation
treatment sites
33
2-2. Fruit size, weight, yield, and decay lesion diameter under three
irrigation systems in 1995
39
2-3. Fruit size, weight, yield, and decay lesion diameter under three
irrigation systems in 1996
43
3-1. Recovery of Br using the ion selective electrode
67
3-2. Mean chemical tracers recovered in top 120 cm soil for Br,
and in top 46 cm for Rb on December 11, 1995
72
3-3. The correlation coefficient of percolate volume vs. concentration
during the period form 10/6/1995 to 12/20/1995
77
3-4. Precipitation, soil water changes, percolate, and recovery of
applied Br and Rb collected during the period from October 6
to December 20 of 1995
81
3-5. Mean chemical tracers recovered in top 120 cm soil for Br,
and in top 46 cm for Rb on June 24, 1996
85
3-6. Mean bromide tracer recovered in top 120 cm soil on August 5, 1996 . .....
87
3-7. Water applied and percolate collected in the PCAPS during
the period from 7/12/1996 to 8/7/1996
89
3-8. Mean bromide tracer recovered in top 120 cm soil on October 8, 1996 . ..... 96
3-9. Water applied and percolate collected in the PCAPS
during the summer irrigation seasons
99
List of Figures in Appendices
Figures
Page
C-1. Br distribution in the soil profile within the grass lane on 12/11/1995
135
C-2. Br distribution in the soil profile within the grass lane on 6/24/1996
136
C-3. Br distribution in the soil profile within the grass lane on 8/5/1996
137
C-4. Br distribution in the soil profile within the grass lane on 10/8/1996
138
List of Tables in Appendices
Tables
Page
A-1. Analysis of variance for pear fruit diameter at harvest in 1995
124
A-2. Analysis of variance for pear fruit weight at harvest in 1995
124
A-3. Analysis of variance for pear yield at harvest in 1995
124
A-4. Analysis of variance for pear fruit diameter at harvest in 1996
125
A-5. Analysis of variance for pear fruit weight at harvest in 1996
125
A-6. Analysis of variance for pear yield at harvest in 1996
125
A-7. Analysis of variance for pear fruit decay in storage in 1995
126
A-8. Analysis of variance for pear fruit decay in storage in 1996
126
A-9. Analysis of variance for Br mass recovered in 120 cm soil
on 12/11/1995
126
A-10. Analysis of variance for Br mass recovered in 120 cm soil
on 6/24/1996
127
A-11. Analysis of variance for Br mass recovered in 120 cm soil
on 8/5/1996
127
A-12. Analysis of variance for Br mass recovered in 120 cm soil
on 10/8/1996
127
A-13. Analysis of variance for Rb mass recovered in 46 cm soil
on 12/11/1995
128
A-14. Analysis of variance for Rb mass recovered in 46 cm soil
on 6/24/1996
128
B-1. Results of linear regression analysis for the pear fruit expansion
rate in 1995
132
List of Tables in Appendices (continued)
Tables
Page
B-2. Results of linear regression analysis for the pear fruit expansion
rate in 1996
132
B-3. Results of linear regression analysis for the pear fruit firmness
decline in storage in 1995
132
B-4. Results of linear regression analysis for the pear fruit firmness
decline in storage in 1996
133
B-5. Results of linear regression analysis for the neutron probe
calibration curve with fixed and varied bulk density
133
B-6. Results of linear regression analysis for the neutron probe
calibration curve with original and adjusted count ratio
133
D-1. Medford Station weather data
140
D-2. Medford Station groundwater table data
146
D-3. Medford Station soil water data
147
D-4. Volume and chemical concentrations of percolate collected in
PCAPS at the Medford Station
167
Soil Water Availability and Chemical Transport in a
Pear (Pyrus communis) Orchard Swelling Clay
Soil under Micro and Flood Irrigation
Introduction
Pear (Pyrus communis) production is one of the main industries in southern
Oregon. There are approximately 4000 ha of pears grown in this area, of which 75% are
on clay soil. The clay soil exhibits significant shrinkage and swelling characteristics.
The volume of the soil changes with water content, which is observed in the field as the
formation of shrinkage cracks and subsidence of ground surface during dry periods, and
the closure of cracks and rising of ground surface during wet periods. This shrinkage and
swelling characteristic affects other soil physical properties, such as soil bulk density and
porosity, thereby affecting soil aeration and water movement. When water is applied to
the dry cracking clay soil by irrigation or rainfall, it transports in two distinct domains
soil matrix and shrinkage cracks. As application begins, water from irrigation or rainfall
is absorbed into the soil matrix.
If and when the application rate exceeds the soil
infiltration rate, the excess free water flows quickly along the cracks down to the subsoil,
which is referred to as preferential flow. If deep cracks are developed or the surface
cracks are connected to other macropores, such as worm holes or dead root holes, the
preferential flows may bypass the root zone and carry chemicals (nutrients and
pesticides), to the shallow groundwater before the chemicals could be absorbed and
degraded in the biologically active root zone. On the other hand, after the surface soil is
saturated, the cracks close and the soil becomes virtually impermeable. With irrigation
under these conditions the ground surface can then become ponded and runoff may occur,
2
potentially carrying chemicals to surface water systems. In pear orchards, growers
currently apply 100-150 kg/ha nitrogen annually near the start of the irrigation season,
and have routinely applied insecticides and miticides at 10 kg/ha active ingredient (a.i.)
and fungicides at 5 kg/ha a.i. during the spring and summer. Impact sprinkler and flood
irrigation are widely used in pear orchards. These irrigation methods are characterized by
high application rate and short duration, separated by relatively long intervals without
irrigation. These characteristics tend to induce preferential flow and surface runoff in
swelling clay soils. However, if the irrigation water could be applied sufficiently slowly
to match the soil matrix infiltration rate, surface ponding could be avoided, and thus the
conditions for both macropore and surface flow would be eliminated. The objectives of
this study were: 1) to examine the shrinkage characteristic and its effects on porosity and
other parameters; 2) to examine a microirrigation system's ability to reduce the
macropore flow in cracking soil, while at the same time supplying adequate water for
pear growth and production of quality fruit for marketing; 3) to examine movement of
several chemical tracers in a cracking soil during the summer irrigation and winter rainy
season to better understand soil and management conditions that contribute to rapid
chemical movement through soil.
3
Chapter 1
Soil Shrinkage Characteristic and its Relation to
Other Soil Physical Properties
Chengci Chen, Richard J. Roseberg, and John S. Selker
4
ABSTRACT
Swelling soils are distinguished from rigid soils by the change of volume with
water content. These volume changes in turn affect soil bulk density, porosity, and pore
geometry. These properties affect the behavior and measurement of water retention and
solute transport in such soil. Thus an investigation of soil shrinkage characteristics is
necessary when studying water availability and chemical transport through a shrink/swell
soil. Shrinkage characteristic curves of heavy clay soil clods were determined in this
study. The bulk density
water content relationship (BD WC relationship) of the soil
clods was compared with that of field soil cores with natural structures. Total and airfilled porosity of the soil clods and soil cores were calculated. Finally, the effect of soil
shrinkage on neutron moisture meter calibration was evaluated. The clay soil tested was
found to have significant shrink/swell with change in water content. Clod volume shrank
18.2% in the range of soil water content between 0.35 to 0.19 g H20/g-soil (equivalent to
-0.03 to -1.5 MPa water potential). The soil showed two shrinkage phases; between 0.35
to 0.19 g H20/g-soil the soil exhibited nearly normal (unitary) shrinkage with a slope of
0.86; and in the range of water content from 0.19 g H20/g-soil to oven dry the soil
showed residual shrinkage with a slope of 0.46. The bulk density
water content
relationship was different for clod and soil cores, with bulk density for soil clods
increasing more for a given decrease in soil water content. The total porosity of the soil
cores decreased less than the soil clods due to the formation of shrinkage cracks. The
porosity due to cracks was calculated from the difference of air-filled porosity between
the soil clods and field soil cores. There was no improvement in the neutron moisture
5
meter calibration curve (p>0.05, t-test for the slope in linear regression analysis) when
using the measured bulk density that varies with water content in place of a fixed value.
INTRODUCTION
Swelling soils are distinguished from rigid soils by the change of volume with
water content. These changes also alter soil bulk density, porosity, and pore geometry
(Newman and Thomasson, 1979). In the field, shrinkage cracks are formed and the
ground surface subsides during dry periods, and cracks close and the ground surface rises
during wet periods. The shrinkage cracks may serve as bypass flow channels (Bouma
and Dekker, 1978) and cause nonuniformity of water application and soil profile wetting
(Van der Tak and Grismer, 1987).
Earlier studies recognized three phases of shrinkage: 1) Structural shrinkage
(Stirk, 1954), is when water is removed from the large stable voids of a saturated soil
during initial drainage, the soil volume changes little; 2) Normal shrinkage (Tempany,
1917; Haines, 1923), also called basic shrinkage (Mitchell and van Genuchten, 1992), is
when the soil water content drops below the lower limit of structural shrinkage, and the
loss of soil volume is equal to the loss of water, with no increase in the air-filled porosity;
3) Residual shrinkage (Haines, 1923), when the water content drops below the lower limit
of normal (basic) shrinkage zone, the loss of soil volume is less than the loss of water
from the voids, and air enters the soil voids. The change from one phase to another is
often quite sharp, with the inflection points representing the limits of each shrinkage
phase.
6
Shrinkage and swelling are principally determined by the mineralogy of the soil
clay fraction (Yong and Warkentin, 1975). Tetrahedral or octahedral silicate layers,
provide the fundamental structural units of silicate clays (Bohn et al., 1979). Based on
the different stacking arrangements and combinations, these clay minerals can be
classified into 1:1-type minerals (one octahedral layer stacks over a tetrahedral layer,
alternatively), and 2:1-type minerals (one octahedral layer is sandwiched between two
tetrahedral layers). The layers within a structural unit are bonded together by a layer of
shared oxygen atoms. Separate structural units are held together by hydrogen bonds or
other forces, depending on the type of crystal and localized charge (either within the
crystal or outside the structural units), which result from the amount of isomorphic
substitution in both the tetrahedral and octahedral layers. The greater the layer charge,
the stronger the bond between the structural units, resulting in less swelling of the clay
mineral. Most kaolin structural units (1:1-type mineral) are held together in the basal
plane by hydrogen bonding between oxygen ions of the tetrahedral sheet and hydroxyl
ions of the octahedral sheet. The bond is so strong that water and other polar molecules
do not enter the interlayer space of the structural units to cause them to expand. The
smectite family of clays (2:1-type mineral), particularly montmorillonite, has a weak
bond between the structural units due to extensive isomorphic substitution.
Polar
molecules, such as water, can enter between the basal planes causing them to expand or
swell. When the water is removed from the interlayer space between the structural units,
the soil shrinks.
The shrinkage characteristic curve varies with the type and percent of clay in soil,
the mode of geological deposition, and the depositional environment.
Therefore, a
7
specific relationship between soil volume and water content is required for a particular
soil under investigation if bulk density is expected to effect parameters of interest.
Shrinkage characteristic curves have been measured on molded soil blocks
(Haines, 1923; Holmes, 1955), natural soil clods (Stirk, 1954; Grossman et al., 1968;
Reeve and Hall, 1978; Bronswijk, 1991), small cores (Berndt and Coughlan, 1977; Yule
and Richie, 1980a), large cores (Yule and Richie, 1980b), soils in lysimeters (Mitchell
and van Genuchten, 1992), and on soils in the field (Aitchison and Holmes, 1953;
Jamison and Thompson, 1967).
In order to quantitatively describe soil shrinkage
characteristics and combine soil shrinkage characteristic curve in the calculation for other
soil physical parameters, several curve fitting models have been proposed to fit shrinkage
characteristic curve, such as the Three Straight Lines model (McGarry and Malafant,
1987), the General Soil Volume Change Equation (Giraldez et al., 1983), and the Logistic
model (McGarry and Malafant, 1987).
The shape of the shrinkage characteristic curve varies with the method by which
shrinkage is measured.
Remolded soil blocks have shown different shrinkage than
natural soil clods, especially when the soil had well-developed crumb structure (Yong
and Warkentin, 1975). Berndt and Coughlan (1976) found different features of the bulk
density
water content relationship (BD-WC relationship) between soil cores dried from
a near saturation and soil cores taken from the field under a range of water contents.
Over the water content range measured in the field soil, the soil cores in the laboratory
showed three-dimensional and normal shrinkage; while the field data showed
unidimensional shrinkage at the high water content range and three-dimensional
shrinkage at the low water content range. The authors attributed these differences to the
8
sampling of soil cracks. They argued that pure soil matrix showed unidimensional curve
if the volume changes was normal with no cracks occurring. Samples taken at higher
water content had infrequent cracks therefore showing unidimensional shrinkage; while
soil cracks were more likely sampled at lower water content and samples showed three-
dimensional shrinkage. The BD WC relationship obtained in the field under a range of
water contents may be more representative of field conditions than that obtained from soil
cores drying from saturation in the laboratory.
The comparison of BD
WC
relationships between field measured soil core under a range of water contents and
laboratory measured soil clod during drying from saturation has not been well
documented.
Because of the difference of shrinkage features by using different
measuring methods, errors may occur by applying laboratory measured BD
WC
relationship from soil clods or small cores to field conditions.
Neutron moisture meter readings in cracking soils have been shown to be affected
by the changes of bulk density due to soil shrinking and swelling (Greacen and Schrale,
1976; Jayawardane et al., 1983; Jarvis and Leeds-Harrison, 1987; Hodgson and Chan,
1987). The influence of soil bulk density on neutron count ratio could arise from the
following sources: first, an increase in density increases the amount of neutron-absorbing
elements per unit volume of soil, such as boron, thus reducing the count ratio. On the
other hand, increase in density also increases the amount of organic matter and bound
water, therefore increasing the count ratio.
In addition, the shrinkage cracks around the neutron probe access tubes might also
change the volume of soil measured. The infiltration of water down to the cracks around
the access tube could also result in nonuniformly distribution of soil water in profile.
9
Furthermore, variation of soil bulk density with water content may cause errors in
calculation soil volumetric water content if a fixed value is used in place of the bulk
density that varied with water content.
The objectives of this study were to: 1) examine the shrinkage characteristic of a
local pear orchard clay soil, 2) compare the bulk density-water content relationship
measured in the field with that measured in the laboratory using soil clods, 3) evaluate the
effects of shrinkage on soil porosity and on calibration of a neutron moisture meter.
MATERIALS AND METHODS
Soil shrinkage curve:
Soil shrinkage was measured first on clods following the procedures of Bronswijk
(1991). Natural clods were taken from a pear orchard at the Kings Highway substation of
the Southern Oregon Research and Extension Center, near Medford, OR. The soil is
classified as Carney clay (Fine, montmorillonitic, mesic Typic Chromoxererts). This soil
is moderately well-drained, and has very low permeability. The soil contained 54% clay,
35% silt, and 11% sand, as measured by the hydrometer method (Gee and Bauder, 1986).
The soil profiles were examined from the trenches which were dug for soil water sampler
installation. A typical soil profile is described in Table 1-1.
Three natural soil clods (3-4 cm diameter) were taken from the 0-20 cm depth in
the field. These soil clods represent soil aggregates without shrinkage cracks. Each clod
was put in a lightweight nylon hair net, placed on three layers of cheese cloth, then laid
on a plastic plate in a shallow pool of water. After imbibition for one week, saturated
weights of the soil clods were obtained. The clods were then coated with a SaranR resin
10
by dipping into a Saran F310 resin solution (resin to solvent 1:5 by weight), air dried and
weighed as soon as the Saran coating solidified, to estimate the mass of added Saran.
Then the clods were air dried further. Saran resin allows vapor, but not liquid water, to
Table 1-1. A typical profile description of the test soil
Depth
Descriptions
0-50 cm
heavy clay. Dark, blocky structure, large cracks (5-10mm), many roots,
firm.
50-117 cm
heavy clay, dark brown, blocky structure, medium cracks (1-5mm),
crack width decreases with depth, few roots, firm, film around peds.
117-145 cm
heavy clay, brown, no structure, few cracks, very few small roots, firm.
>145 cm
layered weathered bedrock, dense, many large fractures.
pass from the clod (Brasher et al., 1966). The water loss of the soil clods was measured
over time by weighing, and the volume of the clod was determined by the water
displacement method (Brasher et al., 1966; Bronswijk, 1991). Finally, the oven-dried
weights of the clods were obtained. By plotting the volume per gram of the soil clod
(specific weight) versus the gravimetric water content, a shrinkage curve was obtained.
Field bulk density:
Undisturbed soil core samples were taken randomly in the field under a range of
water contents at different times. These soil cores represented field average conditions
11
including shrinkage cracks. The samples were taken between 5 and 20 cm depth using an
intact soil core sampler (#0200 Soil Moisture Equipment Corp., Santa Barbara, CA) with
3.00 cm height and 5.40 cm inner diameter. In the laboratory, the water contents and soil
dry mass were determined. Volume of the soil cores was calculated from the diameter
and height of the core sampler. Then the soil bulk density and water content were
calculated. The bulk density was plotted versus water content. Each sample represented
one bulk density at different water contents. Finally, a regression line was drawn and a
relationship between soil bulk density and water content (BD WC) was plotted.
Calculation of porosity:
The total volume (Vt) of a soil aggregate is the sum of the volumes of its three
phase components, i.e. solid phase V, liquid phase VI, and gas phase Va,
vt= vs +
va
(1.1)
For a unit mass of oven dry soil the above equation can be expressed as:
1/p = 1/p5 + w/pw + a/pa
(1.2)
where p is soil bulk density (g/cm3), ps is soil particle density (g/cm3), pw is density of
water (g/cm3), pa is density of the air, w is the mass of water per unit mass of oven dry
soil (g/g), a is the mass of air per unit mass of oven dry soil (g/g). During the normal
(basic) shrinkage phase,
12
A (1/p) = A (w/p,), and A( a/pa ) = 0, also A (1/pa) = 0
which means no increase in air-filled porosity; while during the residual shrinkage phase,
A (1/p) < A (w/pw), and A( a/pa ) > 0,
which means an increase of air-filled porosity. Unlike the rigid soil, the total porosity in
the swelling soil also changes with changing water content. The total porosity can be
calculated by the equation:
St = (Ps
P) /Ps
(1.3)
where ; is the total porosity, ps is the density of soil particles, and p is the bulk density of
the soil. This formula is applicable to the swelling soil too. If the density of the soil
particles is known, then the total porosity can be calculated by the above equation, and
the air-filled porosity Ea can be calculated by subtracting the volumetric water content 0,
from the total porosity, i.e.
Ea= Et
ev
(1.4)
Using the relationship of bulk density versus water content of soil clods and field soil
cores, the total porosity and air-filled porosity can be calculated at different water
contents for soil clods and core samples, respectively. The procedure can be described as
follows:
13
1).
Let s, = Asat
,
where esat is saturated soil water content. The soil bulk density at
saturation Psat was obtained from the shrinkage curve. Substitute pss, into Equation (1.3)
to obtain:
Et
Rewrite the equation as:
°sat = (Ps
Psat)/Ps
(1.5)
Ps = Psat / (1- esat)
2). Assume ps remained constant as the soil water decreased. By combining Equation
(1.3) with soil BD WC relationship, the total porosity s, can be calculated at different
water contents, and air-filled porosity ; obtained as sa = 5, - 0,
3). From a water release curve, the soil porosity
matric water content relationship can
be established.
In this study the water release curve was measured using undisturbed soil cores
taken from a 5 to 20 cm depth in the field using the same soil core sampler as used for
bulk density sampling. The soil cores were contained in brass rings (3.00 cm height, 5.40
cm diameter). The samples were saturated in the laboratory for one week, then placed on
the ceramic plate inside a pressure chamber (#1600G1 Soil Moisture Equipment Corp.,
Santa Barbara, CA), and pressure was applied. After equilibrium at each pressure (no
water coming out), the soil samples were removed, weighed, and oven dried at 105°C to
calculate the gravimetric water content. Three undisturbed soil cores were used for each
pressure point. The water contents at 0.01, 0.03, 0.1, 0.3 MPa were determined. The
14
water content at 1.5 MPa was measured in another chamber (#1500G1) using a
membrane instead of a ceramic plate, and a disturbed soil sample (passed 2 mm sieve)
was used.
Neutron moisture meter calibration in the field:
Field calibration of a neutron probe requires a series of values of moisture content
and neutron thermalization. This can be achieved either at a single site, sampling under
wet and dry conditions, or at several sites with similar soil texture but with a range of
water contents. Calibration from one point is very time consuming and destructive, but
may be more accurate by eliminating the effects of spatial variability. In this study, we
carried out the calibration using samples with different moisture contents collected from
multiple sites during the neutron probe access tube installations. A hydraulic drill with a
60 nun diameter bit was used to generate the tube holes. Disturbed soil samples brought
out with the drill bit were collected at 20 cm intervals down to 200 cm. A PVC tube for
use with the neutron probe (60 mm external diameter, and 5 mm wall) was then installed
with tight contact to the hole wall. Gaps around the tube, if any, were sealed with the
original soil.
Neutron probe readings were taken immediately following installation
using a CPN 503 neutron moisture meter (CPN company, Martinez, CA). Readings were
taken twice at each depth for 30 seconds, at 20 cm intervals down to 200 cm. The
standard count ratio was taken following the manufacturer's instruction. The count ratio
was calculated, and the readings from 20 to 120 cm depth were used for calculation of
count ratio
moisture content relationship. The texture of the soil down to 120 cm was
found to be consistent.
15
Calibration the effect of shrinkage on neutron moisture meter measurement:
Bulk density and volumetric water content: Gravimetric water content can be
converted to volumetric water content by multiplying by soil bulk density (taking water
density to be 1.0 g/cm3). Since bulk density changes with water content as the soil
shrinks, errors occur if an average field measured or fixed bulk density is used to
calculate volumetric water content over a wide range of water contents. The calculation
of volumetric water content at different water contents for a swelling soil must account
for the effects of changes in bulk density.
Bulk density and count ratio: Changes of bulk density during shrinking and
swelling can also affect the count ratio of neutron probe readings, as discussed in the
Introduction section. Greacen and Schrale (1976) proposed an empirical method to
correct the bulk density effects on count ratio, which is refered to as the square root
method. The square root equation is (Greacen and Schrale, 1976):
CS = cf(ps/p)p
(1.6)
where Cs is the corrected count ratio; Cf is the original count ratio; ps is the chosen bulk
density; and p is the measured bulk density; p is a empirical parameter. Greacen and
Schrale (1976) found p has a value close to 0.5 for five Australian soils.
16
RESULTS AND DISCUSSION
Soil shrinkage curve:
The soil shrinkage curves for the three soil clods are shown in Fig. 1-1. Two
phases of shrinkage were found in each of the three Saran coated clods, indicated by
changes in slope of the curve. Using linear regression equations, the parameters of slope
and inflection point were calculated for each shrinkage curve (Table 1-2). When water
content decreased from saturation to the inflection point, the volume of the three
0.75
.-
0
0.70
(1)
a)
E
0.65
0.60
O Clodl
o CIod2
A CIod3
E
0
0.55
5
0.50
0.45
0.00
Pooled
0.10
0.20
0.30
Moisture content (g H20/g-soil)
Fig. 1-1. Soil shrinkage characteristic curve.
0.40
17
Table 1-2. Slope and limit of each shrinkage phase for the three soil clods.
Slope
Normal Shrinkage
Inflection point
Residual Shrinkage
g H20/g-soil
Clod 1
0.88
0.41
0.22
Clod 3
0.83
0.47
0.18
Clod 4
0.98
0.42
0.16
Pooled
0.86
0.46
0.19
soil clods shrank at a slope of 0.88, 0.83, and 0.98, with a mean 0.86. For an ideal
shrinking /swelling soil, the slope in the normal shrinkage phase is 1, indicating that the
loss of soil volume is equal to the loss of water. A slope slightly lower than 1 indicates
that the loss of the volume was slightly less than loss of water, and a small amount of air
had entered the soil. Past the inflection point (about 0.19 g H20/g-soil), the shrinkage
turned into residual shrinkage. The slope in this phase was 0.41, 0.47, and 0.42 for the
three clods, with a slope of 0.46 when fit to all the data. From saturation to oven dryness
the average volume changed from 0.72 to 0.50 cm3 /g -soil, a decrease of 31% from the
original saturated volume. In the range of soil water contents observed in the field (from
0.35 to 0.19 g H20/g-soil, equivalent to -0.03 MPa to -1.5 MPa) the volume changed
from 0.72 to 0.59 cm3 /g -soil, a decrease of 18.2% from the saturated volume. The results
above are similar to the observations of Bronswijk and Evers-Vermeer (1990) in 7 Dutch
soils and Mitchell (1990) in a Holtville sitty clay in California. Bronswijk and Evers-
18
Vermeer (1990) found that the volume change of the natural soil clods ranged from 13%
to 42% for the 7 soils when water content changed from 0 to 1.5 MPa. Structural
shrinkage was not found in the soil clods. Slope of the shrinkage curve for the Holtville
silty clay in California was less than 1.0 in a lysimeter study (Mitchell, 1990).
Soil bulk density:
Fig. 1-2 shows the calculated bulk density of soil clods at different water contents
obtained from the shrinkage curve, compared with the bulk density of undisturbed cores
obtained in the field. In the range of soil water content from 0.35 to 0.19 g H20/g-soil
(equivalent to -0.03 to -1.5 MPa), the bulk density of soil clods changed from 1.40 to 1.70
1.90
M 1.80
E
.!..a), 1.70
D
Fitted
>, 1.60
d
Aggregates
A
AA
1.50
Field BD
Fitted
.g 1.40
A.A
CO 1.30
1.20
0.10
0.15
0.20
0.25
0.30
0.35
0.40
Moisture content (g H20/g-soil)
Fig.1-2. Soil bulk density at different soil moisture contents for both field cores
and clods with fitted relationships for both.
19
g /cm3 and the mean density of soil cores changed from 1.32 to 1.47 g/cm3. For a given
decrease of water content, the bulk density increased more in the soil clods than in soil
cores. The core samples included soil cracks, especially when the soil was dryer. The
BD WC relationship measured in cores is assumed to be more representative of field
conditions. Furthermore, an average field measured bulk density of 1.40 g/cm3 used to
calculate volumetric water content for a wide range of water contents could cause errors
of about 10% (the change in field soil cores).
Soil porosity:
The total porosity and water-filled porosity for soil clods derived from BD WC
relationship is shown in Fig. 1-3, and in Fig.1-4 for field soil cores. The total porosity
here was defined as the total voids in soil including cracks and water filled regions. The
total porosity of the soil clods decreased greatly as it dried, while the decrease of total
porosity in field soil cores was relatively small because of the formation of the shrinkage
cracks. The increase of air-filled porosity was very small (<5%) in soil clods when the
matric potential decreased from 0 to -1.5 MPa. This result has been seen in previous soil
shrinkage curves where little air entered the soil void until the matric potential dropped
down below -1.5 MPa, where the residual shrinkage phase started. After that point the
decrease in soil volume was less than the loss of water, thus the air-filled porosity
increased. However, the air-filled porosity in the field soil cores increased rapidly as the
soil water potential decreased, especially when the water potential dropped below -0.1
MPa. This was because of the formation of shrinkage cracks when the soil clods shrank.
The greatly increase in air-filled porosity between the soil clods in the field soil due to the
20
formation of the shrinkage cracks. This implied that the shrinkage cracks between the
soil clods might play an important role for root zone soil aeration. The importance of
shrinkage cracks for water infiltration into subsoil and root zone aeration has been
addressed by other researchers (Yong and Warkentin, 1975; Mitchell, 1990).
Crack
volume has been determined by either directly measuring the crack dimensions manually
(Dasog and Shashidhara, 1993), or by image analysis of crack photographs (Waller and
Wallender, 1993), or by indirect calculation from soil surface subsidence based on three-
dimensional shrinkage (Bronswijk, 1991). The method of comparing the porosity of soil
clod to field soil core employed in this study provides another way to evaluate the
development of crack voids over a large range of soil water content and potential. This
technique has not been widely used before.
0.55
0.50
0.45
0.40
0.35
0.30 +
0.25
0.001
BTotal porosity
AWater-filled
0.01
0.1
10
Matric potential (MPa)
Fig.1-3. Total, water-filled, and air-filled porosity of the soil clods at
different matric potentials.
21
0.55
0.50
0.45
0.40
0.35
0.30
9Total porosity
AWater-filled
0.25,
0.001
I
0.01
0.1
1
10
- Metric potential (MPa)
Fig.l -4. Total, water-filled, and air-filled porosity of the field soil cores
at different matric potentials.
Effect of shrinkage on neutron moisture meter measurement:
Shrinkage can cause three problems for neutron moisture meter calibration in the
field. As described in the Introduction section of this thesis, errors could arise from: 1)
calculation of volumetric water content using a fixed bulk density instead of a bulk
density that varies as soil shrinks and swells; 2) count ratios that change with bulk density
due to the changes in amount of bound water and other neutron-absorbing elements
within the fixed volume affected by neutron scatter; and 3) the cracks around the neutron
probe access tubes affecting the volume of measurement as well as water infiltration into
22
the cracks when ground surface was saturated. In this study, the soil was not extremely
dry, and no gap was visible around the access tubes. So, the effect of the gap around the
tubes was minimized and is not discussed here.
Calculation of volumetric water content: Plots of neutron probe count ratio versus
volumetric water content calculated based on the fixed bulk density obtained from the
field average data (1.40 g/cm3), and based on the variable bulk density from the BD WC
relationship measured in field cores (Fig. 1-2) show a small difference of slope (p=0.12,
t-test for the slope in linear regression analysis) and intercept (p=0.08, t-test for the
intercept in linear regression analysis) between the two regression lines (Fig. 1-5). The
E a6°
0.55 _ Fixed BD: y = 0.45x 0.18
'5
.23
r2 = 0.81
0.50
0.45
0.40
0.35
rid
Fixed BD
Fitted
o 0.30
co
A
0
*25
0.20
Fitted
Varied BD: y = 0.38x 0.09
N 0.15
r2 = 0.80
.5 0.10
2
0.9
1.0
1.1
1.2
1.3
1.4
1.5
Varied BD
1.6
Count ratio
Fig.1-5. Plot of count ratio versus volumetric water content calculated for
a fixed bulk density and bulk density that varies due to shrinkage.
23
slope of the curve based on the variable bulk density is slightly flatter than the slope of
the curve calculated with fixed bulk density. In this case, significant errors could occur if
using the average bulk density to calculate the volumetric water content only at extremely
wet or dry conditions (p<0.10, t-test for intercept of regression lines). The adjusted data
did not reduce the scatter of the data points, indicating that both curves represented their
data set equally well.
Correction of count ratio: Fig. 1-6 shows the plot of the original and adjusted
count ratio using the square root method. The results indicated that there was little
difference in slopes (p=0.40, t-test for the slope in linear regression analysis) and
0.60
Orig. CR: y = 0.38x - 0.09
0.55
r2 = 0.80
0.50
0.45
®m
0.40
Orig. CR
0.35
Fitted
0.30
a
0.25
Adj. CR
Fitted
0.20
Adj. CR: y = 0.35x - 0.04
r2 = 0.83
0.15
0.10
0.9
1.0
1.1
1.2
1.3
1.4
1.5
1.6
Count ratio
Fig.1-6. Plot of neutron probe calibration curve with and without correction of count
ratio calculated according to Greacen and Schrale (1976).
24
intercept (p=0.32, t-test for the intercept in linear regression analysis) of the regression
lines. There was only slight improvement of the linearity by adjusting for the effects of
bulk density on the count ratio based on the square root equation (r2 changes from 0.80
to0.83). So, correction using the square root equation did not improve the precision of
the neutron probe for these soils. This result is different from the reports of other
researchers in Australian soils (Greacen and Schrale, 1976; Jayawardane et al., 1983).
They found the scatter of data was reduced, and the precision of the calibration curve was
increased, by using the square root equation. However, no effect of bulk density on
neutron count ratio was found in other soils (Long and French, 1967; Luebs et al., 1968;
and Mitchell, 1990). There were several factors that could have caused the conflicting
results of bulk density's effect on the neutron count ratio. As bulk density increases, if
the increase in bound water (which increases count ratio) was greater than the increase of
neutron absorbing elements, such as boron (which decreases count ratio), the overall
count ratio would increase. In contrast, if the increase in bound water was less than the
neutron absorbing elements, the count ratio would decrease. If the increase of the two
factors were equal, then no changes on overall count ratio would be observed as the bulk
density increases. Another possible reason that the effect of bulk density on neutron
count ratio was not seen in this study could have been due to the small changes of bulk
density observed in the field during neutron probe calibration (1.3 to 1.5 g/cm3). Mitchell
(1990) found no effect of bulk density on count ratio for a Holtville silty clay in
California as bulk density changed from 1.4 to 1.6 g/cm3 during the neutron probe
calibration.
25
CONCLUSIONS
The following conclusions can be drawn from the results:
1). The orchard clay soil had high shrink/swell properties. The volume decreased 18.2%
in the range of soil water content between 0.35 to 0.19 g H20/g-soil (equivalent to -0.03
to -1.5 MPa water potential). Although three shrinkage phases are generally shown in
standard shrinkage curves, with a slope equal to 1.0 in the normal shrinkage range, the
soil under investigation showed two distinct shrinkage phases. In the range of soil water
content from 0.35 to 0.19 g H20/g-soil the soil exhibited nearly normal (unitary)
shrinkage with a slope of 0.86. In the range of water content from 0.19 g H20/g-soil to
oven dry the soil showed residual shrinkage with a slope of 0.46.
2). The total porosity of the soil cores decreased less than the clods as water content
decreased due to the formation of shrinkage cracks. Comparing the porosity of soil clods
to field soil cores in this study provided an alternative method to evaluate differences in
crack volume for a wide range of moisture contents.
3). The field soil cores showed different features from the soil clods in the bulk density
water content relationship. The bulk density of soil clods increased more quickly than
soil cores for the same decrease in water content.
4).
The difference in neutron moisture meter calibration curves was not significant
(p>0.05, t-test for the slope and intercept in linear regression analysis) using an average
bulk density compared to using the field measured bulk density (that varies with water
content) in the tested clay soil.
26
REFERENCES
Aitchison, G. D., and J. W. Holmes. 1953. Aspects of swelling in the soil profile. Aust. J.
Appl. Sci. 4:244-259.
Berndt, R. J., and K. J. Coughlan. 1977. The nature of changes in bulk density with water
content in a cracking clay. Aust. J. Soil Res. 15:27-37.
Bohn, H. L., B. L. McNeal, and G. A. O'Connor. 1979. Soil chemistry. John Wiley &
Sons, New York.
Bouma, J., and L. W. Dekker. 1978. A case study on infiltration into dry clay soil.
I. Morphological observations. Geoderma 20:27-40.
Brasher, B. R., D. P. Franzmeier, V. Valassis, and S. E. Davidson. 1966. Use of Saran
resin to coat natural soil clods for bulk-density and water-retention measurements.
Soil Sci. 101:108.
Bronswijk, J. J. B. 1991. Drying, cracking, and subsidence of a clay soil in a lysimeter.
Soil Sci.152:92-99.
Bronswijk, J. J. B., and J. J. Evers-Vermeer. 1990. Shrinkage of Dutch clay soil
aggregates. Netherlands J. Agri. Sci. 38:175-194.
Dasog, G. S., and G. B. Shashidhara. 1993. Dimension and volume of cracks in a vertisol
under different crop covers. Soil Sci. 156:424-429.
Gee, G. W., and J. W. Bauder. 1986. Particle-size analysis. p.91-99. In Arnold Klute (ed)
Methods of soil analysis: Part I. Physical and mineralogical methods (2nd ed.).
ASA and SSSA, Madison, WI.
Giraldez, J. V., G. Sposito, and C. Delgado. 1983. A general soil volume change
equation: I. The two-parameter model. Soil Sci. Soc. Am. J. 47:419-422.
Greacen, E. L., and G. Schrale. 1976. The effect of bulk density on neutron meter
calibration. Aust. J. Soil Res. 14:159-169.
Grossman, R. B., B. R. Brasher, D. P. Franzmeier, and J. L. Walker. 1968. Linear
extensibility as calculated from natural-clod bulk density measurements. Soil Sci.
Soc. Am. Proc. 32:570-573.
Haines, W. B. 1923. The volume-changes associated with variations of water content in
soil. J. Agr. Sci. 13:296-310.
27
Hodgson, A. S., and K. Y. Chan. 1987. Field calibration of a neutron moisture meter in a
cracking grey clay. Irrig. Sci. 8:233-244.
Holmes, J. W. 1955. Water sorption and swelling of clay blocks. J. Soil Sci. 6:200-207.
Jamison, V. C., and G. A. Thompson. 1967. Layer thickness changes in a clay-rich soil in
relation to soil water content changes. Soil Sci. Soc. Am. Proc. 31:441-444.
Jarvis, N. J., and P. B. Leeds-Harrison. 1987. Some problems associated with the use of
the neutron probe in swelling/shrinking clay soils. J. Soil Sci. 38:149-156.
Jayawardane, N. S., W. S. Meyer, and H. D. Barrs. 1983. Moisture measurement in a
swelling clay soil using neutron moisture meters. Aust. J. Soil Res. 22:109-117.
Long, I. F., and B. K. French. 1967. Measurement of soil moisture in the field by neutron
moderation. J. Soil Sci. 18:149-166.
Luebs, R. E., M. J. Brown, and A. E. Laag. 1968. Determining water content of different
soils by the neutron method. Soil Sci. 106:207-212.
McGarry, D., and K. W. J. Malafant. 1987. The analysis of volume change in unconfined
units of soil. Soil Sci. Soc. Am. J. 51:290-297.
Mitchell, A. R. 1990. Water infiltration in a cracked soil during flood irrigation. Doctoral
Dissertation, University of California, Riverside.
Mitchell, A. R., and M. Th. van Genuchten. 1992. Shrinkage of bare and cultivated soil.
Soil Sci. Soc. Am. J. 56:1036-1042.
Newman, A. C. D., and A. J. Thomasson. 1979. Rothamsted studies of soil structure.
III. Pore size distributions and shrinkage processes. J. Soil Sci. 30:415-439.
Reeve, M. J., and D. G. M. Hall. 1978. Shrinkage of clayey subsoils. J. Soil Sci.
29:315-323.
Stirk, G. B. 1954. Some aspects of soil shrinkage and the effect of cracking upon water
entry into the soil. Aust. J. Agr. Res. 5:279-290.
Tempany, H. A. 1917. The shrinkage of soils. J. Agr. Sci. 8:312-333.
Van der Tak, L. D., and M. E. Grismer. 1987. Irrigation, drainage and soil salinity in
cracking soils. Trans. ASAE. 30:740-744.
Waller, P. M., and W. W. Wallender. 1993. Changes in cracking, water content, and bulk
density of salinized swelling clay field soils. Soil Sci. 156:414-423.
28
Yong, R. N., and B. P. Warkentin. 1975. Soil properties and behaviour. Elsevier
Scientific Publishing Co., New York.
Yule, D. F., and J. T. Ritchie. 1980a. Soil shrinkage relationships of Texas vertisols:
I. Small cores. Soil Sci. Soc. Am. J. 44:1285-1291.
Yule, D. F., and J. T. Ritchie. 1980b. Soil shrinkage relationships of Texas vertisols:
IL Large cores. Soil Sci. Soc. Am. J. 44:1291-1295.
29
Chapter 2
Soil Water Availability and Pear Growth and Quality
under Micro and Flood Irrigation
Chengci Chen, Richard J. Roseberg, David Sugar, and John S. Selker
30
ABSTRACT
Irrigation is vital for pear production in southern Oregon due to the characteristic
dry Mediterranean climate in summer. Impact sprinkler and flood irrigation tend to
induce macropore flow and surface runoff which may carry agrichemicals to contaminate
ground and surface water systems. As part of a large study to examine chemical transport
in cracking clay soil, the objective of this study was to examine soil water availability and
pear growth and quality under micro and flood irrigation. Soil available water content
and fruit diameter expansion in Bosc pear (Pyrus communis) were measured under
pulsator (PU, applying 0.5 mm/hr), microsprinlder (MI, applying 2.8 mm/hr), and flood
irrigation (FL) in 1995 and 1996. The postharvest firmness and fungal decay of fruit
from each irrigation treatment were also monitored during storage. The fruit diameter
expansion rate, yield, and fruit firmness decline rate were not significantly different
(p>0.05) between the irrigation treatments for 1996.
In 1995, the pear diameter
expansion rate was lower for PU than that for MI and FL treatments (P<0.05). The 1995
decline of fruit firmness in storage for PU was significantly slower than MI and FL
(p<0.05). The differences between PU and other treatments resulted from the late start of
irrigation in 1995. When soil was dry, the soil water content could not recover to an
adequate level with PU because of the low soil matrix hydraulic conductivity. The pear
trees suffered severe water stress in the growing season of 1995. We conclude that
microsprinkler and pulsator irrigation systems can provide available water comparable to
flood and sufficient for pear growth in a swelling-cracking clay soil if the soil is kept
moist from the beginning of the growing season. These irrigation methods have the
31
advantages of reduced water consumption and lower probability of contaminant transport
in comparison to the presently used flood irrigation (discussed in Chapter 3).
INTRODUCTION
Irrigation is vital for pear production in southern Oregon due to the mediterranean
climate which has dry summer conditions. Summer soil water deficit can cause serious
economic consequences in pear production. Early studies by Lewis et al. (1934) and
Aldrich et al. (1940) concluded that the rate of growth of pear fruit was closely related to
the moisture content of the upper 3 feet of soil.
Larger fruit were produced by
maintaining soil moisture high in the available range throughout the season. Whenever
the moisture content fell below 50% of the available capacity, the rate of fruit growth was
reduced. Fruit dessert quality parameters, such as sugar concentration, juiciness, flavor,
texture, and acidity are also affected by water stress (Aldrich et al., 1940; Cabral et al.,
1995).
Water stress can also affect fruit ripening and storage life. Pears from trees
having the least water deficit near harvest time usually showed a lower firmness during
the harvest period (Aldrich et al., 1940). A type of internal breakdown often found in
ripe pear fruit harvested late in the season was found to be more prevalent in fruit
experiencing greater water deficits near harvest (Aldrich et al., 1940). The effect of water
content on postharvest fruit decay may be related to mineral uptake of the trees
(Bramlage, 1993). Perring and Jackson (1975) found that postharvest quality of apple
was reduced by a low concentration of calcium in fruit. Sugar et al. (1992) found that
combined low nitrogen and high calcium concentration reduced the postharvest fungal
decay of 'Cornice' and 'Bose' pear fruit.
32
Soil physical properties affect water infiltration and availability to plants. In
southern Oregon, most of the pears are grown on clay soils which have a high swelling
and shrinking capacity (Chapter 1 of this thesis). The volume of this soil changes
continuously with changing water content, which is observed in the field as the formation
of shrinkage cracks with high saturated infiltration rates during the dry period and crack
closure with low infiltration rates during the wet period. Currently, impact sprinkler and
flood irrigation are widely used.
These irrigation methods, characterized by high
application rates of short duration and separated by relatively long intervals without
irrigation, tend to induce macropore flow and surface runoff in swelling clay soils (Miller
et al., 1965; Anderson and Bouma, 1977; Beven and Germann, 1982). Microirrigation
systems, such as microsprinlders and pulsators, have been shown to apply water
sufficiently slowly to reduce or eliminate macropore flow (Wu, 1995; Selker et al., 1995;
also Chapter 3 of this thesis). However, whether or not the microirrigation systems can
apply sufficient water for pear growth in such a swelling clay soil is still unknown. Some
authors have argued that shrinkage cracks help the water infiltrate into subsoil (Stirk,
1954; Yong and Warkentin, 1975; Mitchell and van Genuchten, 1993).
The objective of this study was to examine a microsprinkler and a pulsator
irrigation system to determine if they could apply sufficient plant-available water to
produce pears of sufficient size, number, and storage life for quality marketing, as
compared to traditional flood irrigation. In this chapter only the soil water and pear
growth and quality data are reported. This work was part of a larger study examining
water and chemical movement in cracking clay soils in an attempt to reduce surface and
33
groundwater pollution potential by manipulating method of irrigation.
The chemical
transport data will be reported in Chapter 3.
MATERIALS AND METHODS
Experimental site:
The study was conducted at the southern Oregon Research and Extension Center
(SOREC) near Medford, Oregon.
The soil is classified as Carney clay (Fine,
montmorillonitic, mesic Typic Chromoxererts). The typical profile description is shown
in Table 1-1 in Chapter 1 of this thesis.
The soil particle size composition was
determined by hydrometer method (Gee and Bauder, 1986; Table 2-1). This soil is
moderately well-drained, has very low permeability, is underlain by a shallow
groundwater table whose depth fluctuates seasonally from 0.8 to 4 meters.
The
experiment site has an elevation of about 400m, and mean annual precipitation of
479mm, with approximately 76% normally occurring from October through March.
Table 2-1. Particle size composition of the tested soils at three irrigation treatment sites.
Depth
PU
FL
MI
Sand
Silt
Clay
Sand
Silt
Clay
Sand
Silt
Clay
0- 10
17.1
36.4
43.6
11.0
35.0
54.0
8.6
34.0
57.0
10- 60
15.2
33.2
48.6
5.2
37.0
57.0
10.4
31.5
57.0
60-120
28.0
29.2
35.1
8.6
34.8
55.0
7.5
31.0
59.0
cm
34
The plant grown in the tested area is Bosc pear (Pyrus communis), planted in 1935 on a
7.3 X 7.3 meter spacing. Grass was grown in the space between the pear tree rows.
Irrigation systems:
Three irrigation systems, microsprinkler (MI), pulsator (PU), and flood (FL), were
installed in adjoining areas within the orchard. The microsprinkler (Dan 8000 series,
with black round spinner and 1.4 mm green nozzle, 207 kPa pressure, Netafim, New
York, NY) consisted of a spinning nozzle atop a 45.7 cm high stick, applying 2.8 mm
water per hour and wetting an area of 3 m in diameter. The pulsator (PLT-2-20, 207kPa
pressure, Nibco Irrigation, Fresno, CA) differed from the microsprinkler in that each
pulsator head (emitter) was designed with a spinning nozzle sitting atop a cylinder where
a pulse of water was generated. When the pressure of the water inside the cylinder
bladder reached a threshold, the water inside the cylinder was released to the nozzle and
spread out as tiny water drops. Each pulse was generated in about 0.5 second. The
emitter sat on a 45.7 cm stick, and applied 0.5 mm water per hour wetting an area 3.5 m
in diameter.
Pressure regulators and filters were also installed following the
manufacturer's specifications. Two micro-sprinkler or pulsator heads were installed on
the ground between each pair of pear trees within the row. Digital irrigation timers were
used to control the microsprinkler and pulsator systems. During the 1995 irrigation
season, the micro-sprinklers were run 12 hours on a single day weekly, and operated 6
hours twice per week in 1996. The Pulsator was set for 12 hours per day, seven days per
week in the 1995 irrigation season, and 10 hours per day, seven days per week in 1996.
The irrigation was turned off during thunderstorm periods, and the irrigation time was
35
slightly reduced in the late growing season when the air temperature was cooler,
evapotranspiration decreased, and pear growth slowed down. Flood irrigation followed
conventional orchard practice, i.e. the main pipe was set up at one end of the rows and
water moved gravitationally down to the other end of the rows. It ran once every two to
three weeks. Flow was adjusted using gate valves in the FL treatment. Total water
applied was similar among the 3 treatments, although there was less control with FL than
PU and MI.
Soil water measurement:
Two neutron probe access tubes were installed in each irrigation plot in 1995. To
increase the resolution of the measurement, two additional tubes were installed in 1996.
Soil water content was measured once every one to two weeks in the summer and less
frequently in the winter, using a CPN 503 neutron moisture meter (CPN company,
Martinez, CA). All soil and water measurement locations were at least 2 tree intervals
inside of irrigation treatment borders.
Fruit size, weight, and yield measurements:
Four trees were selected in each irrigation plot and 25 fruit in each tree were
randomly labeled. The diameters of the labeled fruit were measured once per two weeks
in the early stage and once per week in the late stage with a caliper. At harvest, the yield
of each labeled tree was obtained, then 100 pears (50 in 1995) were randomly selected to
test the average weight per fruit.
36
Fruit firmness and fungal decay determinations:
Forty pear fruit from each tree were randomly picked. Ten were used to measure
the firmness at harvest, and the other 30 were stored at 0 °C. After 2, 3, and 4 months of
storage, samples of 10 pears each were withdrawn to test firmness using a U.C. firmness
tester with 8 mm plunger (Western Ind. Supply, San Francisco, CA). Two sides of each
of the ten fruit were tested, with the peel removed. The average of the two sides was used
as the firmness index.
Another 10 pears were randomly selected from each tree at harvest, and
inoculated with a suspension of Penicillium expansum containing 104 spores/ml. Five
wounds were made in each fruit by using a 6 mm nail. Each spot was inoculated with 40
IA the Penicillium expansum spore suspension. The inoculated fruit were stored at 0 °C
for 2 months. The diameters of the resulting lesions were measured with a caliper. The
average value of the five lesions on each fruit was obtained as the index of fungal decay.
Statistical analysis:
ANOVA was used to analyze the difference of pear diameter, yield, fruit weight,
and lesion diameter among the irrigation treatments. If the difference was significant,
then the LSD multiple range test was applied to compare the means.
Linear regression
analysis was used to analyze the difference of the rates (slopes) of firmness decline and
pear diameter expansion.
Computer software STATGRAPHICS (Manugistics, Inc.,
Rockville, MD) was used for all statistical analyses.
37
RESULTS AND DISCUSSION
1995 growing season:
Soil water content: Irrigation in southern Oregon generally begins mid June and
continues until harvest or beyond, often into early October. Due to equipment problems,
irrigation treatments in this study did not start until late July in 1995. The pear trees
suffered water stress in the early growing season. Because neutron probe access tubes
were not installed until late August, data showing the degree of soil water deficit is not
available. The water content on September 7 is shown on Fig. 2-1. The plant-available
Percent of available capacity (%)
30
40
50
60
70
80
90
100
0=
20
40
0
60
Q.
80
ft.
100
120
140
Fig. 2-1. Available water profile for pulsator, rnicrosprinkler, and flood irrigation
on September 7, 1995.
38
water was expressed as the percent of available capacity (PAC), i.e. percent of available
capacity = ((soil water content - wilting point)/(field capacity - wilting point))x100%.
The plant-available water under PU was approximately 55 PAC in the top 20 cm, and less
than 50 PAC at 60 cm depth. The available water content under both MI and FL were
each 80-90% in the top 20 cm, and about 70% at 60 cm depth.
The lower available water under PU irrigation might have been caused by high
summer evapotranspiration and the low soil hydraulic conductivity under unsaturated
conditions, i.e., the irrigation water could not infiltrate to the subsoil at the slow rate (0.5
mm/hr) of application by PU. The deficit of available water caused stress on the pear
trees, observed as diminished fruit size and yield.
Fruit size and yield: The cumulative diameter expansion and daily expansion rates
of pear fruit under the three irrigation treatments in 1995 are shown in Fig. 2-2. The fruit
expansion rate and cumulative diameter were smaller under PU than under MI and FL
(p<0.05, t-test for the slopes in linear regression analysis). The cumulative diameter and
expansion rate for MI and FL were similar (p>0.05, t-test for the slope in linear
regression analysis). Because of the lower expansion rate, the size and weight of the
fruits at harvest were significantly smaller for PU than MI and FL (p<0.05, protected
LSD test; Table 2-2). However, the yield of fruit, expressed as the weight per unit trunk
area, was similar (p>0.05, F-test) under the three irrigation treatments. This was due to
the greater number of fruit on each tree for the PU treatment even though the fruit were
smaller than MI and FL.
39
80
2.0
70
Cumulative diameter
1.6
60
50
1.2
40
-PU
Expansion rate
.0-- MI
30
0.8
8-- FL
20-i20
0.4
10
o
0.0
,
U)
CO
CO
0)
ti
CO
Date (month/day)
Fig. 2-2. Cumulative fruit diameter and fruit expansion rate under three irrigation
treatments in 1995.
Table 2-2. Fruit size, weight, yield, and decay lesion diameter under three irrigation
systems in 1995.
Fruit diameter
Fruit weight
g/fruit
Yield
Lesion diameter
kg/cm2 trunk --
PU
56.2 a**
116.5 a
0.077 a
15.7 a
MI
61.9 b
160.0 b
0.058 a
17.9 b
FL
62.9 b
168.5 b
0.060 a
14.6 c
** Mean values within a column followed by different letters are significantly different
at p=0.05 using protected LSD test.
40
Firmness decline and fungal decay: At harvest, fruit from trees under PU
irrigation were significantly firmer (p<0.05, t-test for the intercept in linear regression
analysis) than those under MI and FL (Fig. 2-3). Also, the firmness declined much
slower during storage for fruit from PU than from MI or FL (p<0.05, t-test for slopes in
linear regression analysis). The firmness decline for fruit from MI and FL were similar.
These results correspond to those for fruit size and yield. They indicate that water
stress not only changed the fruit size but also its texture and maturity. The slow decline
of firmness in the storage has two potential consequences: first, fruit in water-stressed
75
A
70
0
65 et-
._
60
0
55
PU y = -0.47x + 71.89
1:1 MI
50
Y = -1.90x + 65.23
0 FL y = -2.43x + 66.99
45 '1
0
1
2
3
4
Time after harvest (month)
Fig. 2-3. Firmness decline during storage for fruit from three irrigation treatments
in 1995.
41
trees may take longer to mature, which would indicate the need to delay picking; on the
other hand, fruit from water stressed trees may have longer storage life.
The diameter of the infected lesions was larger in fruit from the MI treatment than
in fruit from the PU or FL irrigation (95% LSD multiple range test, Table
2-2).
The
mean lesion diameter for PU was larger than FL. This result was not consistent with the
results of fruit size and firmness which showed differences between the water stress and
no stress.
This implies that there were other factors than water stress that directly
determined the fungal decay. Sugar et al.
(1992)
suggested that the nitrogen and calcium
concentration in fruit were important factors that affected the fungal decay of pears in
storage.
1996
growing season:
Soil water content:
maintained between
65
The plant-available water in the upper 120 cm soil was
to 90 PAC during the 1996 summer irrigation season (Fig.
2-4).
The water content fluctuated with the input of water from irrigation and output due to
evapotranspiration and drainage. There were no severe water deficits found throughout
the growing season. The available water was maintained above 70 PAC most of the time
for all three irrigation treatments. The flood irrigation showed greater fluctuation in
PAC, in response to the higher application rates separated by relatively long intervals
without irrigation. While water availability was maintained in all three treatments. In
Chapter 3 of this thesis, the preferential flow and chemical tracer movement will be
shown greater for FL than MI or PU, suggesting a decrease in surface and groundwater
pollution potential with MI and PU systems.
42
°
100
co
cf.
90
ca
c.)
a)
-a
...
co
80
70
ca
.6.,
60
50
C/)
CO
N
ti
CV
CO
Cfl
ti
00
0)
Date (month/day)
Fig. 2-4. Plant-available water in top120 cm soil profile under three irrigation
treatments in 1996.
Fruit size and yield: In 1996, there was no significant difference in cumulative
fruit diameter or daily expansion rate between the irrigation treatments (p>0.05, t-test for
the slopes in linear regression analysis; Fig. 2-5). The fruit grew faster in the early stage
than in the later stage for all three treatments. The yield and fruit diameter of pears at
harvest in 1996 were not significantly different (p>0.05, F-test) between the irrigation
treatments (Table 2-3). Although the fruit weight was slightly greater for FL than for PU,
the yield was not significantly different between the three irrigation treatments (P>0.05,
F-test). Since there was no water stress of trees under any of the three irrigation
43
2.0,
80
70
co
Cumulative diameter
1.6
60
1.2;
50
-PU
40
Expansion rate
- 43- - MI
30
0.8 c
O
G-- FL
20
0.4 as
0.
100
e--
co
co
c7;
Z7I
CD
N.
N.
0.0
0
0)
0)
CN1
05
0)
CN1
0)
Date (month/day)
Fig. 2-5. Cumulative fruit diameter and expansion rate under three irrigation
treatments in 1996.
Table 2-3. Fruit size, weight, yield, and decay lesion diameter under three irrigation
systems in 1996.
Fruit diameter
Fruit weight
g/fruit
Yield
Lesion diameter
kg/cm2 trunk --
PU
60.4 a**
147.2 a
0.124 a
21.7 a
MI
61.3 a
159.7 ab
0.108 a
20.0 b
FL
64.3 a
187.0b
0.122 a
19.9b
** Mean values within a column followed by different letters are significantly different
at p=0.05 using protected LSD test.
44
treatments in 1996, the pear fruit under each irrigation system grew very well. The yield
of the 1996 season was about twice as high as the 1995 season for all three irrigation
treatments (Table 2-2 and Table 2-3). That might be resulted from the water stress in the
early stage in 1995 for all the treatments because of the delay to start irrigation.
Firmness decline and fungal decay: The firmness of fruit at harvest was higher
under MI than under PU and FL (p<0.05, t-test for the intercept in linear regression
analysis, Fig. 2-6). However, the firmness decline rates were not significantly different
among the three irrigation treatments during storage (p>0.05, t-test for slopes in linear
75-.
70
65
A PU
y = -0.94x + 57.76
DMI
y = -1.62x + 61.14
0 FL
y = -1.21x + 57.30
60
50
45
0
1
2
3
4
Time after harvest (month)
Fig. 2-6. Firmness decline during storage for fruit from three irrigation treatments
in 1996.
45
regression analysis). These results are similar to those for fruit size and yield. Thus, with
minimal water stress in 1996, pears under the three irrigation treatments not only
produced similar size and yield, but also had similar quality in storage.
The fungal decay during storage in 1996 showed that the average lesion diameter
was larger in PU than in MI and FL treatments (95% LSD multiple range test, Table 2-3).
The lesion diameter for MI was similar to FL irrigation.
As discussed for the 1995
results, the lesion diameter was not consistant to the water stress. There might be other
factors that directly determined the fungal decay.
As described above, if the irrigation was started after soil became very dry, the
pulsator irrigation system could not restore the soil water to an adequate level. In 1996,
the irrigation was started when soil was moist, the available water of the soil never
dropped down below 60% available capacity. There were large fluctuations of soil water
content in flood irrigation due to the high application rate and long dry period between
two irrigation events. In Chapter 3 of this dissertation, the deep percolation under FL
irrigation was found 100 times more than under PU and MI irrigation.
The deep
percolation under PU and MI were almost zero during the summer irrigation season.
CONCLUSIONS
When initiated under water deficit conditions (1995), pulsator irrigation
treatments were not able to restore water in the clay soil to more than 60 PAC. The lower
water availability under PU irrigation adversely affected the productivity of pear trees
grown in that soil. Fruit size and weight were lower under PU irrigation than under MI or
FL irrigation.
Fruit firmness declined more slowly after harvest in fruit from PU
46
irrigation than in fruit from MI or FL irrigation. There was no strong evidence linking
water stress to the fruit decay in this study. In the absence of water deficit conditions
(1996), PU, MI, or FL irrigation treatments did not differ in their effect on fruit size,
yield, firmness decline, or postharvest decay. Therefore, microsprinkler and pulsator
systems can provide sufficient available water for pear growth in a shrink-swell clay soil
as long as the soil is kept moist from the beginning of the growing season. These systems
are able to provide adequate moisture for optimal crop growth while minimizing potential
of surface and groundwater pollution (the chemical transport will be discussed in Chapter
3). Size and storage quality of pear fruit can be controlled by manipulating irrigation
method and quantities.
REFERENCES
Aldrich, W. W., M. R. Lewis, R. A. Work, A. Lloyd Ryall, and F. C. Reimer. 1940.
Anjou pear responses to irrigation in a clay adobe soil. Station Bulletin 374.
Agricultural Experiment Station, Oregon State College.
Anderson, J. C., and J. Bouma. 1977. Water movement through pedal soils. I. Saturated
flow. Soil Sci. Soc. Am. J. 41:413-418.
Beven, K., and P. Germann. 1982. Macropores and water flow in soils. Water Resour.
Res. 18:1311-1325.
Bramlage, W. J. 1993. Interactions of orchard factors and mineral nutrition on quality of
pome fruit. Acta Horticulturae 326:15-28.
Cabral, M. L., M. G. Barreiro, J. Franco. 1995. Effect of irrigation on storage capability
of 'Rocha' pear. Acta Horticulturae 379:167-174.
Gee, G. W., and J. W. Bauder. 1986. Particle-size analysis. p.91-99. In Arnold Klute (ed.)
Methods of soil analysis: Part I. Physical and mineralogical methods (2nd ed.).
ASA and SSSA, Madison, WI.
47
Lewis, M. R., R. A. Work, and W. W. Aldrich. 1934. Studies of the irrigation of pear
orchards on heavy soil near Medford, Oregon Technical Bulletin 432. United
States Department of Agriculture, Washington, D.C.
Miller, R. J., J. W. Biggar, and D. R. Nielsen. 1965. Chloride displacement in Panoche
clay loam in relation to water movement and distribution. Water Resour. Res.
1:63-73.
Mitchell, A. R., and M. Th. van Genuchten. 1993. Flood irrigation of a cracked soil. Soil
Sci. Soc. Am. J. 57:490-497.
Perring, M. A., and C. H. Jackson. 1975. The mineral composition of apples. Calcium
concentration and bitter pit in relation to mean mass per apple. J. Sci. Food Agric.
20:1493-1502.
Selker, J. S., W. Cao, and R. Roseberg. 1995. Use of ultra-low rate application devices to
eliminate macropore flow during irrigation. Proceedings of the Fifth International
Microirrigation Congress. April 2-6, Orando, Florida. American Society of
Agricultural Engineers.
Stirk, G. B. 1954. Some aspects of soil shrinkage and the effect of cracking upon water
entry into the soil. Aust. J. Agr. Res. 5:279-290.
Sugar, D., T. L. Righetti, E. E. Sanchez, and H. Khemira. 1992. Management of nitrogen
and calcium in pear trees for enhancement of fruit resistance to postharvest decay.
HortTechnology 2:382-387.
Yong, R. N., and B. P. Warkentin. 1975. Soil properties and behaviour. Elsevier
Scientific Publishing Co., New York.
Wu, I. P. 1995. Optimal scheduling and minimizing deep seepage in microirrigation.
Trans. ASAE 38:1385-1392.
48
Chapter 3
Macropore Flow and Chemical Transport under
Micro and Flood Irrigation Systems
Chengci Chen, Richard J. Roseberg, and John S. Selker
49
ABSTRACT
The objective of this study was to better understand how irrigation method,
chemical application timing, and crop management contribute to water and chemical
movement through a cracking clay soil. Macropore flow can accelerate agrichemical
transport to deep subsoil and has been shown contribution to the contamination of
groundwater. Localized ponding at the ground surface is one of the conditions required
to initiate macropore flow. This situation is common in clay soils receiving high rates of
applied irrigation, as occurs when using flood or impact sprinkler systems. To test the
ability of alternative irrigation systems to reduce macropore flow and chemical
movement while maintaining available water the crop, chemical tracers were applied to
an orchard growing in clay soil and were then irrigated using reduced rate and traditional
irrigation systems. Bromide and rubidium tracers were sprayed on November, 1995, and
bromide and blue dye tracers were applied on July, 1996. Pulsator (PU, applying 0.5
mm/hr), Microsprinkler (MI, applying 2.8 mm/hr), and flood irrigation (FL, which is
traditional irrigation method) were applied in the summer.
Soil cores and percolate
samples from passive capillary samplers (PCAPS) were collected to test chemical tracer
transport in the soil matrix and macropores.
agrichemical loading to groundwater.
Microirrigation systems decreased
Preferential flow was greatly reduced under
microsprinkler irrigation in comparison to flood irrigation, and was completely
eliminated under pulsator irrigation. The volume of percolate and mass of Br collected in
the PCAPS installed at a depth of 120 cm was 100 times greater under FL irrigation than
under PU and MI. The mass of sorbed blue dye collected was much less than non-sorbed
50
Br.
Low intensity PU and MI irrigation enhanced chemical movement into the soil
aggregates, thereby reducing the leaching by subsequent water additions. Preferential
flow occurred in all experimental plots during the early part of winter rainy season. The
plume of the November applied Br tracer extended down to 70 cm by preferential flow 24
days after application. The transport of sorbed Rb (a model tracer for ammonium) was
much slower than for non-sorbed Br.
INTRODUCTION
Flow patterns for water and solutes through the vadose zone are often
heterogeneous. The phenomena of nonuniform flow through porous media with a wide
variety of velocities are referred to as preferential flow (Beven, 1991). Preferential flow
has been documented in a wide range of soil textures due to a number of processes. In
sandy soils preferential flow processes have been observed as finger flow in
homogeneous conditions due to unstable wetting fronts (Selker et al., 1992 a, b), and as
funnel flow in layered sandy soil (Kung, 1990, 1993). In structured soils, preferential
flow referred to as "macropore flow" occurs through soil voids such as worm holes, root
holes, and shrinkage cracks (Bouma and Dekker, 1978; Beven and Germann, 1982;
Kneale, 1986; Edwards et al., 1989). Water and solute transport through preferential
pathways can be much faster than through the soil matrix. The saturated hydraulic
conductivity for fine textured soil can be as low as 8.6 mm/day, while that in the
structured clay could be as high as 43200 mm/day (Kneale, 1986).
Bouma (1984)
defined the vertical movement of free water along continuous macropores past an
unsaturated soil matrix as bypass flow. As rapid transport of agrichemicals through the
51
preferential paths, especially macropores, bypasses the biologically active root zone,
reducing the opportunity for degradation of the potentially harmful chemicals within the
soil, preferential flow increases the risks of agrichemical contamination to groundwater.
Steenhuis et al. (1990) pointed out that the concentration in groundwater could exceed 1
lag/1 if 0.1% of a chemical applied at a rate of 2 kg/ha reached groundwater. Many have
shown examples of accelerated movement of a broad variety of chemicals through soil to
groundwater (e.g., Rao et al., 1974; Bowman and Rice, 1986; Everts et al., 1989; Isensee
et al., 1990; Rice et al., 1991; Kladivko et al., 1991; also see review by Jury and Flub ler,
1992).
The degree of connectivity with other macropores may be more important than
their size and volume in determining the ability of macropores to serve as preferential
channels (Bouma, 1981, 1982). Several dye tracer experiments demonstrated that only
those macropores connected to the soil surface conducted water (Kissel et al., 1973;
Bouma and Dekker, 1978; Andreini and Steenhuis, 1990). Bouma and Dekker (1978)
applied Methylene Blue to four clay soils in the Netherlands, then counted the number
and measured the area of stained bands down to 1 m after excavation of the soil. They
found the preferential flow pathways occupied only 2% of the vertical and horizontal
area.
Agricultural practices such as tillage and cropping can change macropore
continuity, thereby changing preferential flow patterns. Traditional plowing destroys the
structure of surface soils, mixes the plow layer and blocks the macropore connections to
the surface, while conservation tillage minimizes plowing, therefore, more continuous
52
macropores and other preferential paths reaching directly from the surface deep into the
subsoil are preserved. Ehlers (1975) found that the number and percentage volume of
earth worm channels near the surface (in the top 20 cm) of a plot under no-till cultivation
for four years was twice that of a similar plot which had been continuously cultivated in
the conventional manner. Andreini and Steenhuis (1990) found that in the no-till soil
column nearly the entire depth of the profile was short-circuited by preferential flow, but
in the tilled column the solute passed through the mixed, unstructured plow layer before
preferential flow below the plow pan occurred. A variety of studies have suggested that
greater chemical transport does occur in no-till than in tilled soils (Hall et al., 1989;
Isensee et al., 1990; Shipitalo and Edwards, 1993). Roseberg and McCoy (1992) found
that macropore air permeability was significantly less under conventional corn than notill corn. The continuity of the macropores also was decreased in tilled soil.
Root systems of different crops may change the macropore patterns, thereby
affecting preferential flows (Mitchell et al., 1995; Kamau et al., 1996). Tap roots tend to
form deeper macropores than fibrous grass roots. Applying dye solution, Mitchell, et al.
(1995) found that the decaying roots of alfalfa produced stable macropores, while wheat
produced no such macropores in a swelling clay soil. Root anchoring also changes the
shrinkage crack patterns in a swelling clay soil (Mitchell and van Genuchten, 1992).
Rain intensity is another factor that affects preferential flow through soil. The dye
experiment of Bouma and Dekker (1978) demonstrated that the number and depth of the
stained bands were the function of application rate and total quantity of applied solution.
Under low (10 mm/hr) and medium (25 mm/hr) simulated rainfall intensity, movement of
Br in the silt loam soil profile was found not significantly different between till and no-
53
till systems. While subjected to a high simulated rainfall intensity, significantly greater
Br movement occurred in the soil profile managed under continuous long-term no-till
(Bicki and Guo, 1991). Preferential flow through macropores can be initiated when high
intensity rainfall or water application rates exceed the soil infiltration rate or when
saturated-flow conditions occur (Wagenet, 1987). Edwards et al. (1992) claimed that
high intensity rainfall moves more atrazine through macropores than low intensity rains
of equal volume. Shipitalo et al. (1990) reported that a light rain following chemical
application helped the chemical to move into the soil matrix, thereby reducing chemical
leaching by subsequent storms. They measured the transport of surface-applied SrBr2 and
atrazine through 30 by 30 by 30 cm undisturbed silty loam soil blocks. They divided the
soil blocks into two groups; one group received a 1 hr 5-mm simulated rain, followed two
days later by a 0.5 hr 30-mm rain, and then followed by another 0.5 hr 30-mm rain a
week later; the other group received only the two 30-mm events. They found that the loss
of Br, Sr, and atrazine was much less from the blocks that received the first 5-mm rain
than the blocks that did not.
Irrigation method has a great effect on chemical transport through soil.
Preferential flow was found to be more pronounced under flood irrigation than under
sprinkler irrigation (Ghodrati and Jury, 1990). Flury et al. (1994) found that cracks and
earthworm channels were only stained when flooded, but not for the unsaturated
conditions occurring under sprinkler irrigation. Flooding resulted in d e
enetration
twice as deep as that for sprinkler. Jaynes and Rice (1993) found that preferential flow
occurred under both intermittent flood and drip irrigation regimes, but breakthrough
curves showed considerably more spreading under intermittent flood irrigation than under
54
drip irrigation. Applying nitrogen fertilizers to dry, clay soils followed by sprinkler
irrigation, Dekker and Bouma (1984) reported that about 50% of N was lost by bypass
flow.
However, an alternative approach that started with a brief wetting the soils,
followed by fertilization, and then sprinkle-irrigating with lower intensity and quantities
greatly reduced the N loss. The strategy of coordinating fertilization and irrigation in
order to reduce the loss of chemicals by preferential flow has not been well established in
cracked clay soils. Cao (1994) tried to use an ultra-low rate irrigation system to eliminate
preferential flow in a cracking clay soil. He compared ultra-low rate pulsator irrigation to
conventional sprinkler and flood irrigation. The preliminary results suggested that the
ultra-low rate pulsator irrigation system had potential to reduce contaminant loading to
groundwater (also Selker et al., 1995).
In shrinking/swelling soil, shrinkage cracks are formed in topsoil when the soil
dries. If water is applied to the surface of a dry, cracked clay soil, it is able to be
transported in two distinct domains
soil matrix and shrinkage cracks. If and when the
application rate exceeds the soil matrix intake rate, excess free water will flow down into
the cracks and contribute to macropore flow. The rate of application at which water flow
into cracks is initiated depends on the soil matrix infiltration capacity and initial soil
water content. Topp and Davis (1981) reported that more than 1 cm of rainfall at rates
greater than 0.1 cm/hr contributed water to the soil cracks. Radulovich et al. (1992)
showed that bypass flow occurred in the non-capillary interpedal pore space whenever
application rate exceeded the infiltration rate of the individual microaggregate. Although
the flow of irrigation water into cracks and other macropores might increase the surface
area used for infiltration into soil matrix (Yong and Warkentin, 1975; Mitchell, 1990), the
55
conditions causing the flow can also increase the amount of water infiltrating into the
subsoil through deep connected cracks. For flood irrigation, due to the existence of the
ponding free water, a significant amount of irrigation water can flow into the cracks as
soon as the irrigation is started.
Theories of water movement through macropores and soil matrix of a swelling
soil have not been completely worked out. Not only does the volume of the soil
aggregates change with water content, the total porosity and pore geometry also change
(Newman and Thomasson, 1979). The traditional Richards equation based on Darcy's
law, which has been used very well in rigid soils, is not applicable to swelling soils.
Several researchers have extended the classical Richards equation to derive a generalized
Richards equation for one-dimensional infiltration into swelling clays and soils (Raats
and Klute, 1968a,b, 1969; Smiles, 1974; Narasimhan and Witherspoon, 1978). The
modification by Smiles (1974) to Richards equation includes: 1) The material coordinate
system was introduced, which measures water movement relative to the soil particle
positions; and 2) Overburden potential was added to soil water potential. However, the
Smiles (1974) one-dimensional approach has several drawbacks (see review in Mitchell,
1990), including: 1) One-dimensional analysis did not address preferential flow; 2) The
one-dimensional analysis lacked a discussion of the scale at which it is valid; 3) Few
experiments have seriously tested the one-dimensional approach; and 4) There is a
question of using Darcy's law for clay systems, because assumptions of homogeneity of
hydraulic properties of the soil over some representative cross-sectional area will no
56
longer be valid. Water fluxes may vary several orders of magnitude over distances of
only a few centimeters, and hydraulic gradient may no longer be properly defined for the
soil as a whole.
Because of the differences between flow in the soil matrix and macropores, two-
domain systems are a common approach to describe water movement in soil with
macropores (Hoogmoed and Bouma, 1980; Beven and Germane, 1981; Jarvis and Leeds-
Harrison, 1987a, b; Jarvis et al., 1991a, b; Gerke and van Genuchten, 1993 ). Water
movement in the soil matrix was predicted by the Richards equation based on Darcy's
law, and water movement in the macropores was modeled by various empirical equations,
including "short-circuiting" (Hoogmoed and Bouma, 1980), Childs (1969) laminar flow
theory (Jarvis and Leeds-Harrison, 1987a, b), kinematic wave approach (Germane and
Beven, 1985), Richards equation for transient water flow and the convection-dispersion
equation for solute transport (Gerke and van Gernuchten, 1993).
Jarvis and Leeds-
Harrison (1987a,b) and Bronswijk (1988) introduced shrinkage characteristic curves to
their models to characterize the occurrence and contribution of shrinkage cracks.
However, based on field measurements, Bronswijk et al. (1995) concluded that water and
chemical transported in three domains in a heavy clay soil, i.e. 1) the large continuous
macropores such as shrinkage cracks, 2) the mesopores, and 3) the pores inside the soil
aggregates. They argued that a significant portion of water and solute was transported
laterally and vertically through tortuous mesopores, and the real matrix transport was the
transport inside the soil aggregates which played only an indirect role in the vertical
solute transport. Therefore, they suggested that the two-domain approach was not valid
for the studied clay soil.
57
Since the theory and mechanism of water and chemical transport through heavy
clay soils are still not clear, added to the effects of different boundary conditions, crop
systems, continuity of macropores, and agricultural practices, there are still difficulties in
using the two-domain model to precisely predict solute transport in the field under a
variety of soil, crop, and irrigation systems. Field experiments are required to better
understand and obtain conclusive results of chemical transport under a particular soil,
crop, and management system.
Many field experiments have been conducted to test the accelerated transport of
chemicals by preferential flow (Ghodrati and Jury, 1990; Steenhuis et al., 1990; Rice et
al., 1991; Ghodrati and Jury, 1992; Flury et al., 1994; Bronswijk et al., 1995; also see
review by Jury and Fluhler, 1992; and Flury, 1996). However, few field experiments has
been aimed at developing new methods to avoid or reduce preferential flow (see review
by Bouma, 1991).
There are many technical difficulties in studying preferential flow at the field
scale. One of the difficulties is sampling the soil solution. The commonly used devices
for soil solution sampling in the field are suction cups and tension-free pans.
The
drawback in using suction cups to sample soil solution is that the cup usually has a small
volume, and if the falling head mode is applied, the time of soil sample extraction is short
in comparison to the time between events (Biggar and Nielsen, 1976; Brandi-Dohrn et al.
1996a). Thus, using a suction cup sampler has a relatively low chance of sampling a
preferential flow event.
58
Tension-free pan samplers have a larger intercept area than suction cups and are
capable of collecting preferential flow (Barbee and Brown, 1986 a, b; Hall et al., 1989;
and Jemison and Fox, 1991). Barbee and Brown (1986 a, b) compared suction cup and
tension-free pan methods in the field. They found that tension-free pans generally
detected solute movement earlier and had higher concentrations than suction cups. One
problem encountered in using tension-free pans is that the soil above them must be
saturated, so that the water arriving at the sampler surface will have the positive pressure
necessary to overcome the capillary force of the soil micropores.
Brown et al. (1986) introduced the wick pan lysimeter, termed the passive
capillary sampler (PCAPS), which combined the ideas of applying tension to the soil
water and intercepting a large area of flow by a pan. PCAPS uses a wick as a hanging
water column to apply capillary suction (Holder et al., 1991; Knutson et al., 1993;
Knutson and Selker, 1994). PCAPS have given results superior to tension-free pan and
suction cup samplers in terms of long-term mass balance of water and chemical loading
(Brown et al., 1986; Boll et al., 1992; Brandi-Dohrn et al., 1996a, b). Brandi-Dohrn et al.
(1996a) compared suction cups to passive capillary samplers (PCAPS) installed in a
loamy soil for 2 years. They concluded that suction cup samplers collected resident
concentration and PCAPS collected flux concentration. However, the utility of using
PCAPS in cracking clay soils under flood and sprinkler irrigation has not been well
documented.
In southern Oregon approximately 4000 ha of pears are grown, about 75% on clay
soils. Nitrogen (N) is often applied near the start of the irrigation season at rates of 100-
150 kg/ha annually. Grower management routinely includes application of insecticides
59
and miticides at 10 kg/ha active ingredient (a.i.), and fungicides at 5 kg/ha a.i. during the
spring and summer.
Based on recent research, many growers are changing the N
application to late summer or early fall using lower rates and/or liquid foliar application
(Sanchez et al., 1992; Sugar et al., 1992). Flood and impact sprinkler irrigation methods
are currently widely used. These high application rate irrigation methods may enhance
the macropore flow phenomenon and surface runoff in the swelling clay soil. After the
harvest in late summer, the residual chemical, if any, may also be transported down to the
water table with the winter rainfall. If the irrigation rate was reduced, the preferential
flow through the cracks and other macropores may be reduced or eliminated.
Cao (1994) tried to apply an ultra-low rate irrigation system in such soil to reduce
the macropore flow. The preliminary results indicated that the pollutant loading to
groundwater can be greatly lowered by using this device (also see Selker et al., 1995).
However, several problems were encountered in Cao's (1994) experiment: 1) The PCAPS
were designed as 25-cell units with a 500 ml capacity for each cell. Although this design
had high spatial resolution, individual cells often overflowed under flood irrigation, so
that the true volume could not be detected; 2) The soil water content and plant response
were not measured, so it was not clear whether or not the ultra-low irrigation device could
provide adequate water for plant growth; 3) The duration of the experiment was too short.
During the three months of experimentation (from September to December, 1992), only
one and a half months were under irrigation (pears harvest and irrigation stopped in mid
October). Therefore, further research was required to confirm the preliminary results that
60
the ultra-low irrigation device could reduce macropore flow, and to ensure that this
device could also provide adequate water for pear growth.
The overall goal of this experiment was to better understand how irrigation
method, application timing, and crop management conditions contribute to rapid
chemical movement through cracking clay soil. The initial objectives of this study were:
1) To examine the ability of a pulsator and microsprinkler system used in Cao's (1994)
experiment to reduce the macropore flow in a cracking clay soil and determine if this can
minimize the potential of chemical movement to surface and groundwater during the
irrigation season; 2) To evaluate the movement of residual or fall-applied chemicals after
pear harvest to groundwater during the winter rainy season; 3) To determine how
irrigation method and crop management affected the contributions of matrix vs.
macropore flow in clay soils.
MATERIALS AND METHODS
Site description:
The study was conducted at the Southern Oregon Research and Extension Center
(SOREC) near Medford, Oregon.
The soil is classified as Carney Clay (Fine,
montmorillonitic, mesic Typic Chromoxererts). The typical profile description is shown
in Table 1-1 in Chapter 1 of this thesis. The soil particle composition was determined by
hydrometer (Gee and Bauder, 1986; Table 2-1 in Chapter 2). This soil is moderately
well-drained, has very low matrix permeability, and is underlain by a shallow
groundwater table whose depth fluctuates seasonally from 0.8 to 4 meters.
The
experimental site has an elevation of about 400 m, mean annual precipitation is 479 mm,
61
with approximately 76% normally occurring from October through March. The crop
grown in the tested area is Bosc pear (Pyrus communis), planted in 1935 on a 7.3 X 7.3
meter spacing. The pear tree rows are oriented from south to north. Grass was grown in
the space between the pear tree rows.
The ground surface is slightly higher on the
southwest side and lower on the northeast side (slope 1-3%). The experiment plot layout
is shown in Fig. 3-1.
Irrigation systems:
Three irrigation systems, micro-sprinkler (MI), pulsator (PU), and flood irrigation
(FL), were installed. The irrigation set up and specifications have been described in
Chapter 2. Two microsprinkler or pulsator heads were installed approximately 25 cm
above the ground in the row between each pair of trees. The microsprinkler (Dan 8000
series, with black round spinner and 1.4 mm green nozzle, 207kPa pressure, Netafim,
New York, NY) applied water at 2.8 mm/hr with a wetted area 3 m in diameter. The
pulsator (PLT-2-20, 207 kPa pressure, Nibco Irrigation, Fresno, CA) applied water at 0.5
mm/hr, wetting an area 3.5 m in diameter. During the 1995 irrigation season, the
microsprinklers operated 12 hours per day and once per week, but operated 6 hours per
day, twice per week in the 1996 season. The pulsator was set 12 hours per day, seven
days per week during the 1995 irrigation season, and 10 hours per day, seven days per
week in the 1996 season. The irrigation was turned off during thunderstorm periods, and
the irrigation time was slightly reduced in the late growing season when the air
temperature was cooler, pear growth slowed down, and evapotranspiration decreased.
Flood irrigation followed conventional orchard practice, i.e. the main pipe was set up at
Pulsator
Irrigation (PU)
Flood
Irrigation (FL)
I
0
0
00
0
@
-111-1
I
1
0
A
Microsprinkler
Irrigation (MI)
PU
(a)
MI
FL
(b)
Fig. 3-1. Schematic of the field experiment: (a) layout of the three irrigation treatments; (b) equipment installation
in each test area. The meaning of the symbols are: pear tree, 0 neutron probe access tube, El PCAPS,
0 ground water observation well,
irrigation area
tracer application and sampling area.
63
the south end of the rows and water moved gravitationally down to the other end. Flow
was adjusted using gate valves. Total water applied was similar among the treatments,
although there was less control with FL than PU and MI.
Soil Moisture:
Two neutron probe access tubes were installed at each replicate in 1995 using a
Giddings hydraulic soil probe (GSRR-ST#723, Giddings Machine Company, Fort
Collins, Colorado). In order to increase the resolution of measurement, two additional
access tubes were installed at each replicate in 1996. Soil moisture was determined using
a CPN 503 neutron moisture meter (CPN company, Martinez, CA) once per week or once
per two weeks.
PCAPS samplers:
PCAPS used in this study were made of a fiberglass box with width x length x
height = 0.35m x 0.85m x 0.67cm. The box was separated into three equal chambers, and
the wall of the box was 0.5 cm thick. The top of the PCAPS was designed as the
intercepting pan with a 1.5 cm high edge about the perimeter. Three holes were drilled in
the top centered over each chamber to allow wick installation. The filaments of the
unbraided top portion of each wick were spread in a symmetrical radial pattern and glued
to the panel of the intercepting pan. The lower braided portion of the wick hung down
through the central hole to the bottom of the chamber, thus applying about 60 kPa tension
to the contacted soil above the PCAPS. Each chamber had a capacity of 0.066 m3.
Similar PCAPS construction can be found in Cao (1994) and Knutson and Selker (1996).
64
Two withdrawal tubes were inserted into each sample collection chamber to withdraw the
water sample from the chambers.
PCAPS were installed under undisturbed soil in the following manner. A trench
(1.3 m width and 2 m depth) was dug parallel to the tree row using a back hoe. A 0.40 m
wide by 1.1 m long by 0.72 m high tunnel perpendicular to the trench at the depth of 1.2
m below the ground surface was then excavated using a power chisel and shovel. The
roof of the tunnel was leveled and smoothed, then two wedges (10 cm wide x 10 cm high
x 100 cm long) were laid on the bottom of the tunnel. The top intercept pan of PCAPS
was filled with sieved, native soil, then the PCAPS was slid into the tunnel on top of the
wedges and lifted by punching the wedges in with a hammer so as to make a firm contact
between the intercept pan and the roof of the tunnel. Areas around the sides of the
PCAPS were filled with native soil, and then the face of the tunnel was sealed with
bentonite clay to isolate the samplers from the trench. The access tubes were attached to
the trench wall and led to the surface of the ground. Finally, the trench was filled with
soil, taking care not to disturb the bentonite clay or the sampling tubes. The location of
each PCAPS within each irrigation plot is shown in Fig. 3-1 (b). Three PCAPS were
installed in the flood irrigation and microsprinkler irrigation plots.
In the pulsator
irrigation plot, two PCAPS were installed in the test area marked as "B". In test area
"A", there were two PCAPS installed by previous researchers (Cao, 1994) which failed to
function. The south one was replaced with a new PCAPS of the same design as those in
the flood and microsprinkler sites.
experiment.
The north one was repaired and used in this
It had a different design from those mentioned above. The old PCAPS
dimension was 32.5 cm x 32.5 cm, and had 25 cells in a 5 by 5 grid. Each of the 25 units
65
was attached to a 65 mm square stainless steel plate that held the unbraided wick, and
each container's capacity was 500 ml (Cao, 1994).
The PCAPS were installed in July of 1995. A vacuum pump which applied 60100 kPa was employed to suck the water sample out from the sample collection chamber
through the access tubes. The water samples were taken once per two weeks during the
summer irrigation season and once per month during the rest of the year.
thunderstorm occurred in summer, samples were taken after the event.
If a
For the FL
treatment the percolate usually was taken after each irrigation event.
Chemical tracers:
Several tracers were used to monitor water and chemical transport. Bromide is a
non-sorbed tracer, used as a surrogate for nitrate, and which has approximately the same
speed as water. Blue dye (FD&C #1) with a reported retardation factor of 5.6 has been
cited as surrogate for atrazine (Andreini and Steenhuis, 1990). Rubidium ion (Rb+) has
one positive charge, and has a hydrated diameter of 0.147 nm, similar to 1("f (0.133nm)
and NH4+ (0.143nm). The ion retention by soil particles is slightly greater for Rb+ than K+
and NH4+ (Bohn et al., 1979). Rb-86 has been used as a tracer for IC' adsorption (Franklin
and Snyder, 1965). Because the radius of Rb+ is similar to NH4+, is monovalent, and
doesn't change its form in soil, Rb+ may be used as a surrogate for NH4+. While Br has
often been used a tracer to simulate NO3 movement, we have not found a previous
example of Rb+ used as a tracer for NH4+.
On November 17, 1995 calcium bromide and rubidium bromide were applied to
the surface of the test area of each irrigation plot. Rubidium was applied only in the test
66
area within the tree row (inside), but bromide was applied in the area both within the tree
row and the grass lane between the tree rows (outside). The bromide was applied at a rate
of 9 gBr/m2, and rubidium at a rate of 1.5g Rb/m2. The calcium bromide and rubidium
bromide were dissolved in water and applied using a bicycle frame herbicide sprayer with
4 nozzles (TEEJET 8003), which was set at the travel speed of 4.0 km/hr and a pressure
of 276 kPa, and the application rate of 32 ml/m2. In order to make the application
uniform, we calculated the volume to be enough to spray back and forth for 4 passes.
On July 12, 1996, the CaBr2 and blue dye (FD&C #1) were applied at the rate of
18 g Br/m2 and 20.0 g dye/m2 in the same manner as 1995 to test the water and chemical
transport during summer irrigation. Both tracers were applied in the tree row (inside) and
grass lane (outside) in the test area of each irrigation plot.
Soil core samples:
Soil core samples were taken on the following dates: September 21, 1995 (before
the tracer application); December 14, 1995 (about one month after the first tracer
application); June 24, 1996 (after the winter rain season); August 5, 1996 (after the first
thunderstorm following the application of the second tracer application); and October 8,
1996 (after the pear harvest). Four replicate soil cores were taken from the inside tree
row and four cores were taken from the outside grass lane in each test area of each
irrigation plot using a Lord Soil Sampler # 225 (Soil Moisture Equipment Corp., Santa
Barbara, CA). The soil samples were taken at 15cm intervals down to 120 cm. The soil
samples were air dried and ground to pass a 2 mm sieve.
67
Chemical Analysis:
Bromide in soil was extracted with water, with a soil to water ratio of 1:2.
Samples were shaken for 30 minutes, then centrifuged. The bromide in the extracted
solution was measured using a Model 94-35 bromide electrode (Orion Research Inc.
Boston, MA). Extractable Rb+ was measured, after extraction with 1 M NH4OAc (pH 7),
by atomic absorption method. Blue dye in water samples was measured at 630 nm using
a Spectronic 20D spectrophotometer (Milton Roy Company, New York).
In order to test the validity of the Br analysis method, a Br recovery experiment
was conducted before the formal analysis started. CaBr2 standard solutions were added to
10 g samples of air-dry soil resulting in 0.0, 2.0, 10.0, and 100.0 f_tg Br/g-soil. Four
replications were prepared for each level. After air-drying the spiked soil samples, the Br
was extracted by adding 20 ml water to each sample and shaking for 30 minutes. The soil
suspensions were centrifuged and the Br concentration was determined using a Br ion
selective electrode as described above. The recovery rate ranged from 94.4% to 116.5%
Table 3-1. Recovery of Br using the ion selective electrode.
Br added
flg Br/g-soil
Recovery
Percent of applied
i.tg Br/g-soil
%
2.0
2.3 ± 0.3
116.5
10.0
9.4 ± 0.2
94.4
100.0
97.2 ± 1.5
97.2
68
(Table 3-1). The recovery rate was over 100% at the lowest level of Br possibly because
of the lower sensitivity of the electrode when the concentration of Br is low in the
solution (near 11.1g Br/g soil for this electrode).
RESULTS AND DISCUSSION
The water stored in the 120 cm soil profile fluctuated seasonally. During the
winter season from late January to late April of 1996, the soil became saturated, and the
water content remained high and constant (Fig.3-2). The water table level in this period
also rose and remained high, with the highest water table level at 80 cm in late February
of 1996. In the summer irrigation season from mid June to late September, soil water
fluctuated with the input of water from irrigation and rainfall, and output from
evapotranspiration and deep percolation. The water table in this period dropped below
250 cm. However, several pulses were seen in the water table curve in the FL plot (Fig.
3-2). These spikes indicate that a significant amount of water recharged the groundwater
at each irrigation event, causing the water table to temporarily rise. The pulse found in
early August was partly caused by the thunderstorm that occurred in late July. The water
stored in the PU plot was always lower than that in the MI or FL plot even in the winter
rainy season when the soil was saturated. This is because of the difference in soil texture
(Table 2-1, in Chapter 2), so that the lower clay particle fraction in the PU plot translated
to lower field capacity of the soil.
In the following paragraphs the results of the water and chemical transport
through the clay soil during the winter rainy season and summer irrigation season will be
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70
discussed. Due to the influence of residual chemical from a previous experiment in the
"A" area of PU plot, only data from the "B" area are used in this report. In addition, one
of the withdrawal tubes in the flood-south (FLS) site failed to function, so only two
chambers were used.
Winter rainy season:
In order to test the transport of after-harvest residual chemical and fall-applied
fertilizer through the clay soil during the winter rainy season, bromide and rubidium
tracers were applied on Nov. 17, 1995. Twenty-four days after application, the depth of
the maximum concentration of Br tracer was located at 0-30 cm (Fig. 3-3). The average
transport speed of Br concentration peak was about 1 cm/day (25cm/24 days). Although
there was high spatial variability, the average concentration of four soil cores showed a
smooth curve for each experimental plot.
The average concentration curve showed
similar transport patterns of Br in the three treatments. The front of the Br plume in some
soil cores had extended to a depth of about 70 cm. Some individual cores had deeper
extension than the others, and some of them even had multiple peaks in the profiles.
These phenomena might have been caused by vertical or lateral preferential flows, such
that the preferential flow carried the chemical tracer from the topsoil through the vertical
crack or other macropores down to the bottom of the cracks, or through the connected
cracks laterally from one site to another. Large effective dispersion coefficients for the
field average solute concentration profiles were also found by Bronswijk et al. (1995) in a
heavy clay soil under natural rainfall. The authors suggested that the large dispersion
resulted from vertical and lateral flow of solute through mesopores in the clay soil. The
71
20
(00) 15-
0
PU-in-1
--a; 10
PU-in-3
:2
E
0
PU-in-2
X
5
PU-in-4
Average
B.G.
X
- ---
0
I
0
20
40
60
80
100
120
140
Depth (cm)
MI-in-1
M1-in-2
M1-in-3
X
MI-in-4
Average
B.G.
0
0
20
40
60
80
100
120
140
Depth (cm)
20
FL-in-1
(90) 15
0
; 10
FL-in-2
%--
FL-in-3
32
2
co
X
5
FL-in-4
Average
B.G.
0
0
20
40
60
80
100
120
140
Depth (cm)
Fig. 3-3. Br distribution in soil profile within the tree row on 12/11/95.
B.G. is background concentration measured in September, 1995.
72
average Br mass recovered in the top 120 cm soil 24 days after application was 58% for
PU plot, 78% for MI plot, and 73% for FL plot (Table 3-2). The difference of the mass
recovered between the experiment plots was not significant (p>0.05, F-test).
Table 3-2. Mean chemical tracers recovered in top120 cm soil for Br, and in top 46 cm
for Rb on December 11, 1995.
Number of
soil cores
Br
Recovery
Rb
Percent of
applied
g /m2
Recovery
Percent of
applied
g /m2
PU
4
5.24a**
58
0.19a
13
MI
4
7.01a
78
0.27a
18
FL
4
6.55a
73
0.26a
17
** Mean values within a column followed by different letters are significantly different
at p=0.05 using protected LSD test.
Unlike Br distribution, Rb was found mainly accumulated in the top 20 cm of soil.
No plume of Rb was found extending down to the subsoil (Fig. 3- 4). This is probably
because of the adsorption of Rb to the soil particles or organic matter causing the ion to
be relatively immobile. Therefore, it could not be easily carried by preferential flow
down to the subsoil like the Br ion. There were no strong differences in the distributions
between the treatments. Large spatial variability was found among the soil cores. Since
the added Rb was located on the top 20 cm of soil, the recovery of Rb in the upper 46 cm
soil was calculated (first three depth increments).
73
4.0
(9a) 3.0
O
PU-in-1
PU-in-2
E 2.0
PU-in-3
=
El 1.0
x
PU-in-4
Average
B.G.
0.0
0
I
i
I
20
40
60
80
100
120
140
Depth (cm)
4.0
C)
a
'?
-
3.0
MI-in-1
MI-in-2
E 2.0
MI-in-3
=
X
1.0
13
MI-in-4
Average
B.G.
0.0
0
20
40
60
80
100
120
140
Depth (cm)
4.0
X30
(9
cm
-x
FL-in-1
A
FL-in-2
E 2.0
=
FL-in-3
_
x
FL-in-4
Average
0.0
B.G.
r
0
20
i
1
40
60
80
100
120
140
Depth (cm)
Fig. 3-4. Rb distribution in soil profile within the tree row on 12/11/95.
B.G. is background concentration measured in September, 1995.
74
Another reason to calculate the Rb mass recovery in the upper 46 cm instead of
120 cm was to avoid the background noise, because the concentration of added Rb tracer
was low in the profile relative to the background, when calculated over the entire profile
depth. Due to the high price of RbBr, we did not apply a sufficiently large amount of Rb
to be able to distinguish it well from the background Rb. Ideally, we would have tested
the background level prior to tracer application, but several long delays in obtaining the
equipment to analyze Rb forced us to make the application without knowing the
background levels, which ended up being much higher than expected based on the limited
literature (Jones, 1992). The average mass of the Rb recovered 24 days after application
was 13% for PU, 18% for MI, and 17% for FL (Table 3-2). The low recovery of Rb
might have been due to a specific adsorption and fixation of Rb by soil minerals. The
soil minerals might exhibit a preferred fixation for rare metals, which rendered them less
extractable than would have been predicted from CEC relations alone, if amounts added
were small (Baham, 1997, personal communication). Jones (1992) only recovered 3% of
the soil total Rb when extracted using 1 M NI-I4OAc solution.
Strong evidence of preferential flow was found from the volume of percolate and
tracer concentrations during the period from 10/6/1995 to 12/20/1995 (Fig. 3-5 and 3-6).
Preferential flow occurred in all three treatments, especially in the FL plot (note the large
variations in percolate amounts). The PCAPS that collected a larger volume of percolate
usually had higher Br concentration. The correlation coefficient of percolate volume
versus Br concentration was 0.99 for PU, 0.34 for MI, and 0.84 for FL. The correlation
coefficient for the pooled data was 0.80 (Table 3-3). The positive correlation between the
percolate volume and Br concentration shortly after the tracer application indicates that
75
PU
1000
800
600
400
PUS
200
0
PUN
2
3
PCAPS cells
MI
1000
800
600
400
200
0
1
3
PCAPS cells
18900 11690
FL
1000
800
600
400
N
200
a)
0
1
2
3
PCAPS cells
Fig. 3-5. Volume of percolate collected in the PCAPS during the period
between 10/6/1995 and 12/20/1995.
76
PU
20
15
10
PUS
cf)
PUN
1
2
cr)
3
PCAPS cells
MI
20
15
10
MIS
MIM
4111414.1"
1
2
MIN
3
PCAPS cells
FL
20
15
10
FLS
FLM
uNi
FLN
1
2
3
PCAPS cells
Fig. 3-6. Concentration of Br in percolate collected in the PCAPS during
the period between 10/6/1995 and 12/20/1995.
77
preferential flow played an important role in Br transport. Brandi-Dohrn et al. (1996a)
applied Br tracer to the surface of a loamy soil and collected soil percolate using PCAPS
for two years. They found that the correlation coefficient between the volume collected
and Br concentration was positive in the early stages and then changed to negative as
time proceeded. They attributed this result to the contribution of preferential flow to the
volume of percolate. The initial higher Br concentration in preferential flow than in
matrix flow resulted in the positive correlation between the volume and Br content. After
the peak concentration in preferential flow passed the PCAPS, the matrix flow played an
increasingly important role in transporting solute, which was reflected in the decreasing
correlation coefficient between the volume and Br concentration.
Table 3-3. The correlation coefficient of percolate volume vs. concentration during the
period from 10/6/1995 to 12/20/1995.
Bromide
Rubidium
PU
0.99
-0.56
MI
0.34
0.01
FL
0.84
-0.57
Pooled
0.80
-0.25
Unfortunately, in this experiment the groundwater rose and the PCAPS were
submerged from February through late May of 1996, thus the percolate volume and Br
concentration in late winter could not be monitored. Therefore, the role of macropore and
78
matrix flow in chemical transport in late winter could not be drawn from the PCAPS data.
It was expected the matrix flow would play an increasing role after the peak
concentration passed the PCAPS in macropore flow as discussed in Brandi-Dohrn et al.
(1996a).
The concentration of Rb in percolate (Fig. 3-7) was different from the Br (Fig. 36).
The Rb concentration did not correspond to percolate volume.
The correlation
coefficient of percolate volume versus Rb concentration was 0.56 for PU, 0.01 for MI,
and 0.57 for FL. The correlation coefficient for the pooled data was 0.25 (Table 3-3).
This might be additional evidence of the adsorption of Rb tracer by soil minerals as
discussed previously. The negative correlation coefficients also indicate the relatively
less transportation by preferential flow for adsorbed chemicals compared to non-adsorbed
chemicals. Unlike the non-adsorbed tracer Br, not much rubidium could be transported
by macropore flow from the surface and edges of soil peds down to the PCAPS. The site
FLS was a typical case where macropore flow carried considerable amounts of Br tracer
down to the PCAPS (0.44 g), but little Rb was found in the percolate (near zero). The
average volume of percolate and mass of the tracers collected in PCAPS are shown in
Table 3-4.
High spatial variability of percolate volumes was found between the PCAPS.
Some PCAPS collected more volume than predicted from water balance, while the others
caught less than predicted. In the FLS site, one chamber of the PCAPS collected 18,900
ml, and another one collected 11,690 ml, 20-30 times more than the maximum volume
collected in MI and PU chambers during the same period. From the water balance, it can
be seen that the precipitation during the period from 10/6/95 to 12/20/95 was 233 mm,
79
PU
0.30
0.25
0.20
0.15
0.10
U)
a)
:.-.
0.05
cf)
0.00
2
3
PCAPS cells
MI
0.30
1 0.25
a)
'IL,
0.20
T.
0.15
.2.
0.10
3
-0
0 05
Ce
0.00
a
2
3
PCAPS cells
FL
0.30
0.25
0.20
0.15
FLS
0.10
FLM
0.05
0.00
FLN
1
2
u)
..
U)
3
PCAPS cells
Fig. 3-7. Concentration of Rb in percolate collected in the PCAPS during
the period between 10/6/1995 and 12/20/1995.
80
and change in soil water in the 120 cm profile was 21 mm in the FL plot. Since the soil
surface was wet most of the time during this period, the potential evaporation of 78 mm
obtained from the weather station was used in the calculations. So, the expected deep
percolation should be 134 mm, assuming no surface runoff occurred. However, one of
chambers for the FLS site PCAPS collected 18,900 ml, which was equivalent to 190 mm.
Some of the excess water might have come from lateral flow from outside the area
directly above the PCAPS. Likewise, the volumes in some other chambers were much
lower than the predicted amount (134 mm), so some of the water above those chambers
was going elsewhere. These results indicate that lateral preferential flow occurred. These
lateral flows could result in lower recovery of water and tracers in PCAPS, because the
lateral flow might bypass the PCAPS if the macropores were not intercepted by the
PCAPS. The average amounts of percolate and tracers collected in PCAPS during the
period from 10/6/1995 to 12/20/1995 were far less than the expected amount estimated
from the mass balance (Table 3-4). This implied that a portion of the water might have
been lost through surface runoff or lateral preferential flow that bypassed the PCAPS,
because no barriers were set up around the PCAPS to prevent the water flowing laterally.
The lateral preferential flow could also result in high spatial variability of
chemical distribution in soil profile. Bronswijk et al. (1995) found high spatial variability
of Br recovery in soil profile (from 65% to 200% in 15 cores) in a heavy clay soil due to
the lateral preferential flow. The soil cores which had higher water contents were found
to have higher Br recovery under the natural rainfall conditions. High spatial variability
and multiple peaks of Br distribution in soil profile due to preferential flow have been
found in Fig. 3-3.
81
Table 3-4. Precipitation, soil water changes, percolate, and recovery of applied Br and
Rb collected during the period from October 6 to December 20 of 1995.
PP
S
V
Recovery
Br
Percent of
applied
Rb
Recovery Percent of
applied
mm
mm
mm
PU
233
33.1
1.9
0.02
0.2
3.9
0.003
MI
233
26.9
2.1
0.01
0.1
21.5
0.014
FL
233
20.9
34.5
0.52
5.8
15.0
0.010
g/m2
%
g/m2x 105
%
Note: PP = precipitation, S = changes of soil water, V = volume of percolate collected.
The average volume of percolate and mass of the Br collected in PCAPS were
higher in the FL plot than in PU and MI plots during the period from 10/6/1995 to
12/20/1995 (Table 3-4). Since there were no differences in water application during this
period, and all three experimental plots were under natural rainfall conditions, the
difference among the plots could be caused by spatial variability of soil structure and
surface microrelief.
As discussed above, one of the PCAPS in FL-south site (FLS)
collected extremely high volumes, while the others collected much less (Fig. 3-5). This
phenomenon implied that the PCAPS in FLS site was connected to preferential flow
channels and led to some sort of water source, such as a lower ponded spot on the ground
surface where water was collected from the surrounding areas. The other PCAPS which
collected little water might either not be well-connected to continuous preferential flow
channels or to a water source. Data collected in summer irrigation season could validate
this hypothesis, and will be discussed below.
82
The difference among the plots in the early winter might imply there were not
enough PCAPS in each site to obtain representative data. In this study, 8 PCAPS were
used in the 0.4 ha experimental area, which is less than 25 PCAPS per hectare proposed
by Brandi-Dohrn et al. (1996b) for a loamy soil. They analyzed Br recovery in 32
PCAPS installed within a 0.9 ha area. They concluded that 25 PCAPS were necessary
per experimental treatment to estimate the mean Br concentration with a 30% bound at
0.05 confidence level.
However, the tested period discussed above (10/6/1995 to 12/20/1995) was a
transition from summer dry season to winter wet season, thus the soil was not saturated
and cracks were not totally closed. The high spatial variability of preferential flow could
be expected due to the spatial variability of soil structure and macropore distributions in
such an orchard clay soil. The difference between the plots was expected to narrow in
late winter when the soil became saturated and cracks closed. However, there were no
data to prove this hypothesis because the water table rose and PCAPS overflowed in late
winter.
Summer irrigation season:
After the water table dropped below the depth of the PCAPS, the PCAPS were
drained and soil core samples were taken on June 24, 1996 to test the residual Br and Rb
tracers in the soil profiles (Fig. 3-8 and Fig. 3-9). The maximum concentration of Br was
found at the depth of 70
80 cm for MI and FL plots, and 40
60 cm depth for PU plot.
These depths coincided with the depth of the winter water table in each plot as shown in
Fig. 3-2. Therefore, the depth of the maximum concentration might relate to the high
83
20
a)
ar) 15
PU-in-1
CD
PU-in-2
ri) 10
PU-in-3
7:5
E
0
m
X
5
PU-in-4
Average
B.G.
0
0
20
60
40
80
100
120
140
Depth (cm)
MI-in-1
MI-in-2
MI-in-3
X
Am;
p
Average
B.G.
00
20
40
60
80
100
120
M1-in-4
140
Depth (cm)
a
(9C7)
O
20
15
FL-in-1
FL-in-2
7; 10
FL-in-3
X
.E
FL-in-4
Average
B.G.
CO
0
r
0
20
40
60
80
100
120
140
Depth (cm)
Fig. 3-8. Br distribution in soil profile within the tree row on 6/24/96.
B.G. is background concentration measured in September, 1995.
84
water table in the winter. In the winter of 1995-1996, the water table rose to the depth of
80 cm (60 cm in PU site), and remained high from mid February to late April. When
chemical tracers moved down to the level of the water table through soil aggregates, they
would have stopped there because there would be no convection flow below the water
table. The chemical would then start to diffuse to groundwater from soil aggregates.
That would be a slow process compared with the convection movement.
Since the
experimental area had a relatively level ground surface, the gradient of the groundwater
level was very small.
So, any lateral flow of groundwater would be very slow.
Therefore, the equilibrium of concentration between the soil aggregates and groundwater
was rapidly established, resulting in the maximum concentration was located at the level
of water table.
When the water table dropped in early May of 1996, the water in macropores
would have drained immediately. However, it would have taken a long time to drain the
water inside soil aggregates due to the low hydraulic conductivity (on the order of 104
mm/day), therefore it was likely there existed a time lag for the water draining from soil
aggregates in such a cracking clay. This phenomenon has been reported by Bouma et al.
(1980). This sequence of events could explain why the maximum concentrations were
located at the depth above 80 cm after the water table dropped in June.
The average recovery of Br on June 24, 1996 was 50% for the PU plot, 34% for
MI, and 37% for FL (Table 3-5). The difference of the Br recovery from the soil profiles
was not significant among the treatment plots (p>0.05, F-test). Compared to the Br data
in the early winter (discussed in the previous section), the loss of Br from the soil profile
during the period from December 11, 1995 to June 24, 1996 was 8-44% of the applied
85
tracer. The average concentration distribution curves in Fig. 3-8 show that the plume of
Br was deeper in MI and FL than in PU. It was expected that the residual Br tracer in MI
and FL would be drained out 120 cm depth earlier than in PU.
Table 3-5. Mean chemical tracers recovered in top 120 cm soil for Br, and in top 46
cm for Rb on June 24, 1996.
Number of
Br
Rb
soil cores
Recovery
g /m2
Percent of
applied
Recovery
Percent of
applied
%
g /m2
%
PU
4
4.53a**
50
0.10a
7
MI
4
3.09a
34
0.06a
4
FL
4
3.35a
37
0.08a
5
** Mean values within a column followed by different letters are significantly different
at p=0.05 using protected LSD test.
The contents of Rb in soil profiles on June 24, 1996 were close to the background
level measured on September 21, 1995 (Fig. 3-9). The recovery of Rb in the upper 46 cm
of soil was 7% for PU, 4% for MI, and 5% for FL (Table 3-5).
No maximum
concentration peaks were found in the profiles. Because little Rb was found in the
percolate during the winter, the loss of Rb was likely due to further fixation by soil
minerals. Further tests for the total amount of Rb in soil are required to prove this
hypothesis.
In order to test chemical transport in the summer irrigation season, bromide and
blue dye tracers were sprayed on July 12, 1996. After tracer application, PU and MI
86
4.0
_
cs)
O
3.0
PU-in-1
PU-in-2
x
E 2.0
PU-in-3
X
:5
15 1.0
Average
=
cc
PU-in-4
B.G.
0.0
0
20
40
60
80
100
120
140
Depth (cm)
4.0
cr)
(9°) 3.0
O
MI-in-1
MI-in-2
E 2.0
=
MI-in-3
X
zi 1.0
=
MI-in-4
Average
B.G.
0.0
0
20
40
60
80
100
120
140
Depth (cm)
4.0
cti*C"
O
3.0
FL-in-1
FL-in-2
E 2.0
x
FL-in-3
x
.172 1.0
cc
FL-in-4
Average
B.G.
0.0
0
20
40
60
80
100
120
140
Depth (cm)
Fig. 3-9. Rb distribution in soil profile within the tree row on 6/24/96.
B.G. is background concentration measured in September, 1995.
87
irrigation treatments were started following the schedules mentioned earlier. The next
flood irrigation was applied on July 26. Before the percolate in PCAPS was collected,
there was a thunderstorm on July 30, 1997, which delivered 33 mm water in a short
period of time. On the day after the thunderstorm, percolate in PCAPS was collected, and
soil core samples were taken on August 5 to examine the tracer distribution in the soil
profile. The tracer distribution in Fig. 3-10, tracer recovery from soil in Table 3-6, and
tracer recovery in PCAPS in Table 3-7 reflected combined effects of irrigation and the
thunderstorm during the period between July 12 and August 5.
The maximum
concentration of Br in PU and MI plots was pushed down to a depth of about 20 cm (Fig.
3-10). The front of the Br plume extended to a depth of 100 cm. The deep extension of
the plume might have been caused by the lateral or vertical preferential flow as discussed
previously.
Table 3-6. Mean bromide tracer recovered in top120 cm soil on August 5, 1996.
Number of
Br
soil cores
Recovery
Percent of
applied
g/m2
PU
4
18.0a*
100
MI
4
17.2a
96
FL
8
10.3b
57
* Mean values within a column followed by different letters are significantly different
at p=0.10 using protected LSD test.
88
70
cr) 60
"PI 50 4
o
Z:.". 40
PU-in-1
'2 30
E 20
0
PU-in-2
A PU-in-3
X PU-in-4
" 10
Average
CO
0-r
i
20
0
40
60
80
100
120
140
Depth (cm)
70
0) 60
,cfn 50
0
7.1.% 40
MI-in-1
a)
-0 30
MI-in-2
E 20
MI-in-3
X MI-in-4
O
CO
10
Average
0
20
0
40
60
80
100
120
140
Depth (cm)
70cn 60 --1En
0
u?
50
Z..". 40
7=3cu
30
E 20
0
8
FL-in-1
x
FL-in-2
x
FL-in-3
x
x
10 -,- ,
X FL-in-4
Average
0
0
20
40
60
80
100
120
140
Depth (cm)
Fig. 3-10. Br distribution in soil profile within the tree row on 8/5/96.
89
Table 3-7. Water applied and percolate collected in the PCAPS during the period
from 7/12/1996 to 8/7/1996.
IR + PP
Percolate
Br
MM
PU
MI
FL
64.1
67.1
Blue dye
g/m2
70.3
16.9
193.5
214.9
Note: IR + PP = Irrigation + Precipitation.
3.49
0.21
5.40
0.02
0.14
0.04
The distribution of Br in the FL plot showed a different pattern from those found
in PU and MI plots. Some cores in the FL plot had maximum concentration located in
the top 10 cm, while some cores had very low concentrations throughout the profile.
There was very high spatial variability from core to core.
This phenomenon was
probably caused by the patterns of irrigation. In this experiment, the flood irrigation
acted more like a furrow irrigation. The main pipe was set up at one end of the pear tree
rows, and two valves were opened in every grassy inter-row area. Water typically moved
along the shallow tractor tracks gravitationally down to the other end of the rows. The
irrigation water infiltrated from the tractor tracks laterally to the adjacent soil. In the
lower spots of the field where the moving water totally covered the soil, the chemical
might have moved overland, resulting in a low concentration in the soil below that point.
However, in the higher spots where the soil was never covered with the irrigation water,
the chemical might not have been washed away or pushed down from the top soil by
lateral overland flow or downward macropore and matrix flow, resulting in a
concentration in the top soil that was extremely high. Due to the likelihood of lateral
flow, chemicals could have been carried from one site to another, so that the Br
90
distribution in soil profiles showed double or multiple peaks. This result confirms the
observations of Bronswijk et al. (1995) that lateral and vertical preferential flow resulted
in spatial variability of Br distribution in soil profile in clay soil, as was discussed earlier
for the winter data in this chapter. The average concentration of Br in soil profiles also
showed different distribution patterns among the treatments (Fig. 3-10). This
phenomenon could also be seen clearly in the data for October, as will be discussed
below.
The Br lost from the top 120 cm soil was significantly greater in the FL plot than
in PU and MI (p<0.10, protected LSD test).
In order to increase the number of
replications to improve statistical analysis, 4 "outside" cores from the grass lane in the FL
plot were included in this calculation. Non-uniform irrigation over the tree row and grass
lane areas in PU and MI prevented use of "outside" cores from those treatments. Fortythree percent of Br was lost from the FL plot, but little was lost from PU and MI (Table
3-6).
The difference between FL and PU or MI may be attributed to the irrigation
methods.
The ultra-low rate irrigation enhanced Br movement into soil aggregates.
Therefore, when the subsequent thunderstorm came, there was little Br on the edges of
the soil aggregates available for leaching. The Br concentration curve in Fig. 3-10 shows
that the maximum concentration of the bromide tracer had been pushed down through the
soil aggregates about 20 cm in the PU and MI plots.
The situation in the FL plot was different. The applied Br tracer would have
stayed on the surface and edges of the aggregates until the first flood irrigation was
applied on July 26, followed by the thunderstorm that occurred on July 30. In this case,
the Br would readily be leached down to the subsoil by macropore flow. These result
91
agree with the observation of Shipitalo et al. (1990) in loamy soil blocks that a small rain
following chemical application could help the chemical to move into soil aggregates,
thereby reducing the chemical loss by the subsequent high rate irrigation. They found
that when 30 mm rain was applied, the loss of Br from blocks that previously received 5
mm rain was 2 to 10 times less than that without receiving it.
The above interpretations are important for irrigation scheduling and chemical
management in the field when aiming at reducing the potential of groundwater
contamination.
The potential for groundwater protection by reduced rate irrigation
systems was not due only to the rate of irrigation per se, but also due to enhancement of
matrix versus preferential flow (the matrix flow here refers to the flow within the soil
aggregates). This enhancement of matrix flow under PU and MI treatments likely moved
the chemicals into locations less amenable to preferential flow caused by subsequent high
intensity rainfall or irrigation events. Furthermore, enhancing matrix flow would not
only slow down the transit time to groundwater, but also possibly reduce the amount
chemical pollution by allowing soil microbes more time to degrade the chemical while
still in the root zone.
Percolate was collected in PCAPS under all three treatments during the period
7/12/1996 to 8/7/1996 including the thunderstorm (Table 3-7). The volume of percolate
collected under the PU plot was slightly more than the water applied by irrigation plus
precipitation. That probably resulted from lateral preferential flow to the PCAPS during
the thunderstorm. This result also supports the interpretation for the early winter data that
when adequate free water was applied, lateral and vertical preferential flow could follow
the connected macropores to the PCAPS. In this experiment, the ground was slightly
92
lower on the north side of the orchard where PU was located than on the south side where
MI was located. When the high intensity storm occurred, the PU site likely accumulated
more water from overland flow than the MI site. The mass recovered from the PCAPS
under the PU plot was 3.5 g/m2 even though the average mass recovered from the
"inside" soil cores was 100% (Table 3-6), indicating that part of the Br came from the
"outside" grass lane area. Because the pulsator irrigation did not cover the "outside"
grass lane area, the applied Br would not have infiltrated into the soil aggregates, and thus
was easily moved laterally by preferential flow and could be charged to the PCAPS.
The blue dye collected in the PCAPS was less than Br under all three treatments
even though more blue dye than Br was initially applied to the soil. Similar to the
discussion about the Rb tracer, less blue dye leached down to the PCAPS was probably
because of the adsorption of blue dye by soil particles. The adsorption slowed down the
velocity of the adsorbed chemical transport to subsoil, thereby also increasing the time for
degradation by soil microbes.
From 8/7/96 to 10/8/96, there was little rainfall, so that the chemical transport in
the soil profile was driven mainly by irrigation water. The Br distribution in the soil
profile on October 8, 1996 is shown in Fig. 3-11. The Br movement in soil under PU
irrigation was more uniform than under MI and FL irrigation. Multiple peaks were found
in the Br distribution curves in MI and FL plots but not in the PU plot, indicating that
macropore flow was more prevalent under MI and FL than under PU irrigation. The Br
pulse peak traveled deeper in PU than in MI and FL although the cumulative irrigation
amounts were similar (Fig. 3-11, Table 3-9). That meant that the daily application of
water at an ultra-low rate by pulsator was more efficient in moving the Br through the soil
93
70
cl') 60
(90)
0
50
40
41 30
PU-in-1
-
PU-in-2
PU-in-3
E 20
x PU-in-4
10
Average
8.3
0
i
20
0
40
60
80
100
120
140
Depth (cm)
70
rg) 60
(90) 50
MI-in-1
40
a)
-0 30
.E 20
MI-in-2
A MI-in-3
X MI-in-4
O
co
10
Average
x
0,
20
0
40
60
80
100
120
140
Depth (cm)
70
-2) 60
0)
50
40
CD
30
73,
E 20
0
`9
Ea
FL-in-1
FL-in-2
FL-in-3
X FL-in-4
io
x
0
A
0
Average
I
20
I
40
60
80
100
120
140
Depth (cm)
Fig. 3-11. Br distribution in soil profile within the tree row on 10/8/96.
94
aggregates than the higher rates of MI or FL irrigation. Since there was no preferential
flow under PU, all the infiltration water went through the soil aggregates.
In FL
irrigation, however, most of water went through macropores bypassing soil aggregates.
Therefore, flood irrigation is less efficient in moving chemical through soil aggregates.
In MI irrigation, most of water went through soil aggregates, but the dry period between
two events was longer then PU because of the twice a week application of water, which
might have resulted in the upward movement of water during the dry period. Therefore,
the peak of Br concentration was shallower in MI than in PU. Miller et al. (1965)
observed that intermittent applications of water were more efficient in moving chloride
through Panoche clay loam than continuous ponding with an equal amount of water
applied. The principle was similar that with an equal amount water applied, more water
was transported through soil aggregates under intermittent application than under
ponding where most of water was transported through macropores bypassing the soil
aggregates.
The chemical transport through soil aggregates of the clay soil was very slow.
For 62 days (from August 7 to October 8), the maximum concentration of bromide tracer
only traveled 20 cm in PU, with an average speed of 4 mm/day. The Br pulse in MI and
FL did not move much (Fig. 3-12). The patterns of Br distribution in soil profiles on
October 8 were very similar to those on August 5 for MI and FL.
There was no
significant difference (p>0.05, t-test) between the average mass of Br recovered on
August 5 and that recovered on October 8 for all three treatments (Table 3-6 and 3-8).
That indicates that little Br was lost from soil profile during the period from August 5 to
October 8 of 1996.
95
70
60
PU
50
40
A 8/5/96
30
8-- 10/8/96
20
10
o,
0
20
40
60
80
100
120
140
Depth (cm)
70
60
50
40
a-- 8/5/96
30
--e- 10/8/96
20
10
20
40
60
80
100
120
140
Depth (cm)
70
60
FL
50
40
At 8/5/96
30
e 10/8/96
20
10
0
0
20
40
60
80
100
120
140
Depth (cm)
Fig. 3-12. Average Br concentration of 4 soil cores within the tree row
on 8/5/96 and 10/8/96.
96
Similar to the situation on August 5, the pattern of average Br concentration in
soil profile was different among the treatments on October 8 (Fig. 3-11). The uneven
application and lateral flow of water in the FL treatment likely contributed to the different
distribution patterns of the Br tracer in those soil profiles. In this case, overland flow
would have carried the Br from lower spots laterally to an adjacent area. This process
could cause the lower concentration of Br detected in some soil cores, as well as the
multiple peaks found in some other cores. Furthermore, some of the soil cores taken
from the high spots, where the flood water never covered the surface, showed an
extremely high concentration in the top 10 cm of soil (Fig. 3-11). On October 8 (after
pear harvest), the recovery of the applied Br tracer was 88% in the PU plot, 86% in MI,
and 53% in FL (Table 3-8). The mass of Br recovered from the FL plot was significantly
lower than that recovered from PU and MI (p<0.10, protected LSD test).
Table 3-8. Mean bromide tracer recovered in top120 cm soil on October 8, 1996.
Number of
soil cores
Br
Recovery
Percent of
applied Br
g /m2
PU
4
15.9a*
88
MI
4
15.4a
86
FL
8
9.5b
53
* Mean values within a column followed by different letters are significantly different
at p=0.10 using protected LSD test.
97
During the period from August 8 to October 7 of 1996, the volume of percolate
collected in the PCAPS under pulsator and microsprinkler irrigation was nearly zero.
However, a considerable amount of percolate was collected under flood irrigation (Fig.
3-13).
Similar results were observed in the 1995 season. The average volume of
percolate and mass of the Br collected under flood irrigation was about 100 times greater
than that collected under microsprinkler or pulsator irrigation (Table 3-9). This result
confirms the preliminary result of Cao (1994) that ultra-low rate pulsator could greatly
reduce the potential of agrichemicals contamination to groundwater.
However, the
percolate collected under microsprinkler in this study was much less than in the study of
Cao (1994). The reason could be that the operation time was shortened and less frequent
of irrigation in this experiment, therefore preferential flow was reduced.
The large amount of water collected in FL was attributed to preferential flow. All
three PCAPS in FL collect a large amount of water, and high spatial variability was found
both within and between the PCAPS (Fig. 3-13). Comparing Fig. 3-13 to Fig. 3-5, it can
be seen that the PCAPS at FLS site collected large amount volumes both in the winter
and in the summer, indicating the presence of stable channels connected to that PCAPS.
The other PCAPS in FL did not collect much water in the winter but collected large
amounts in the summer, indicating that either macropore channels did not connect to the
to the surface water source, or else unstable macropores such as shrinkage cracks closed
during the winter wet season.
Because there was still a considerable amount Br in the soil profile, and the peak
of Br pulses was located above 80 cm in FL by October 8, the water collected in the
98
PU
8000
6000
4000
2000
PUS
PUN
0
1
2
3
PCAPS cells
MI
8000
6000
4000
2000
0
3
PCAPS cells
31500
FL
12450
33
8000
6000
4000
FLS
2000
FLM
FLN
0
2
2
U)
3
PCAPS cells
Fig. 3-13. Volume of percolate collected in the PCAPS during the period
between 8/8/1996 and 10/7/1996.
99
Table 3-9. Water applied and percolate collected in the PCAPS during the summer
irrigation seasons.
8/8/95
IR+PP
mm
215.7
229.0
247.5
10/5/95
Percolate
mm
0.6
IR+PP
mm
PU
241.5
MI
1.5
228.5
FL
190.0
240.2
Note: IR + PP = Irrigation + Precipitation.
8/8/96
Percolate
mm
10/7/96
Br
Blue dye
g /m2
g /m2
0
0
0
1.0
0.01
1.76
0.00
0.02
113.9
PCAPS must have been due to preferential flow. Further evidence of preferential flow
was that the water table temporarily rose after each flood irrigation event as discussed in
the previous sections (Fig. 3-2).
Although a large amount of percolate was collected in the PCAPS under FL
irrigation between 8/8/96 to 10/7/96, the Br collected in the PCAPS was only 1.8 g/m2 for
the 4 flood irrigation events, which was 10% of the applied Br. Compared to 5.4 g /m2
(30% of applied Br) collected on August 7 after one flood irrigation and one
thunderstorm event, it could be concluded that the greatest amount of applied non-sorbed
chemical was transported by preferential flow only during the first few flood irrigation
events.
After the chemical moved into soil aggregates, preferential flow played a
decreasingly important role in chemical movement, and flow within the soil aggregates
played an increasingly important role. This result was analogous to that of Martin et al.
(1978), who applied several herbicides to corn residue and monitored their washing off
by simulated rain. They found that the amount of herbicides washed off by the first 5
mm of rain was equal to that washed off by the next 30 mm.
100
Much less blue dye than Br was recovered from the percolate (Table 3-9) in
comparison to the amount of Br and blue dye originally applied. This indicates that the
downward movement of the adsorbed chemical by irrigation water was much less than
the non-sorbed chemical. The FD&C #1 blue dye has been used to simulate atrazine by
several researchers (Andreini and Steenhuis, 1990; Hatfield et al., 1997; Cao, 1994).
They measured the breakthrough curves of the blue dye using the collected percolate.
Blue dye has also been used to stain the path of preferential flow (Andreini and
Steenhuis, 1990). Because of interference due to soil background color, the concentration
of blue dye in the extract of soil core samples could not be measured using a
spectrophotometer. Thus the blue dye mass in the soil profile was not measured in this
study. An accurate and simple method needs to be developed to accurately measure blue
dye concentration in soil to allow mass balance calculations of blue dye in soil for future
studies. In the literature we found no report of a valid method for measuring the mass of
FD&C #1 blue dye in such a clay soil.
CONCLUSIONS
The results above confirm the preliminary results of Cao (1994) that ultra-low rate
irrigation systems can greatly decrease the potential of agrichemical movement through
soil to groundwater. The volume of percolate and mass of Br collected in the PCAPS
installed at a depth of 120 cm was about 100 times greater under the FL irrigation than
under PU and MI irrigation.
Low intensity irrigation by PU and MI enhanced chemical movement into the
matrix of soil aggregates, thereby reducing leaching by the subsequent irrigation or
101
thunderstorms. Preferential flow was greatly reduced under the microsprinkler irrigation
in comparison to the flood irrigation, and completely eliminated under the pulsator
irrigation.
Thus, the potential for groundwater protection by reduced rate irrigation
systems was not only due to the reduction of preferential flow, but also would be due to
the enhancement of chemical movement into soil aggregates, thus avoiding leaching by
macropore flow and allowing more time for soil microbes to degrade the chemical.
Preferential flow occurred in all experimental plots during the early winter rainy
season. The plume of the November surface-applied Br tracer extended down to 70 cm
depth by preferential flow 24 days after application. Vertical and lateral preferential flow
resulted in high spatial variability of Br concentration in both the soil profile and volume
of percolate collected in PCAPS. The water table rose and remained high throughout the
winter from February to May.
The transport of adsorbed Rb and blue dye tracers were much slower than nonsorbed Br. Due to the low recovery of Rb tracer applied to soil, further studies are
required to test the validity of Rb+ serving as a surrogate of NH4+. The distribution of
blue dye (FD&C#1) tracer in the soil profile was not measured in this study because of
the interference of soil background color with the spectrophotometer measurement. A
simple and accurate method needs to be developed for future studies. Br was shown to be
a good tracer to simulate water and non-sorbed ion transport through soil aggregates and
macropores in the swelling clay soil.
PCAPS can be used in swelling clay soils. The number of PCAPS required to
obtain representative samples needs to be determined in future studies in such a highly
102
structured swelling clay soil under different pear orchard irrigation systems, but is likely
greater than that employed here and in studies in loamy soils (Brandi-Dohrn et al.,
1996b).
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109
Summary
The soil at the experimental site has great shrinkage capacity (Chapter 1). As the
water content decreased, the volume of the tested clay soil shrank 18.2% in the range of
soil water content between 0.35 to 0.19 g/g (equivalent to -0.03 to -1.5 MPa). In this
range, the soil exhibited "nearly unitary shrinkage" with a slope of 0.86, and in the range
of soil water content from 0.19 g/g to oven dry the soil showed residual shrinkage with a
slope of 0.46. The bulk density of the soil aggregates increased from 1.40 to 1.70 g/cm3
and the bulk density for the field bulk soil increased from 1.32 to 1.47 g/cm3 when the
soil water content decreased from 0.35 to 0.19 g/g. The porosity of the tested clay soil
also changed with water content. As the soil dried from 0.35 to 0.19 g/g water content,
the total porosity of the soil aggregates decreased greatly, while the decrease of total
porosity in field bulk soil was relatively small because of the formation of shrinkage
cracks. The increase in air-filled porosity in soil aggregates in the range of soil water
potential from -0.03 to -1.5 MPa was small (from 1% to 5%) but relatively larger in field
bulk soil because of the formation of shrinkage cracks.
Pear fruit expansion and firmness were closely related to soil water availability
(Chapter 2). Lower water availability can adversely affect the productivity of pear trees,
and storage quality of the fruit. In 1995, due to equipment problems, the irrigation was
initiated when soil was dry. In this case the pulsator irrigation treatments were not able to
restore the clay soil to more than 60 percent of available capacity (PAC). In the absence
of water deficit conditions in 1996, PU, MI, or FL irrigation treatments did not differ in
their effect on fruit size, yield, or firmness decline in storage.
Therefore, the
110
microsprinkler and pulsator systems can provide sufficient available water for pear
growth in a shrink-swell clay soil as long as the soil is kept moist from the beginning of
the growing season.
Localized ponding at the ground surface is one of the conditions required to
initiate macropore flow. The results of experiments in Chapter 3 can be summarized as
follows:
During the early winter of 1995
1996, preferential flow occurred in all three
treatment plots, especially in the FL site, where water and chemicals were collected and
carried from the adjacent area, then charged to the PCAPS through macropore channels.
The plume of Br tracer was spread down to 70 cm by macropore flow 24 days after
application. Chemical transport through the soil matrix was much slower than through
macropore flow. Over the winter rainy season 34
50% of Br remained in the top 120
cm soil (as of June 24, 1996). The amount of chemical recovered from percolate was less
than that lost from the soil profile during the period from Nov. 17, 1995 to December 11,
1995, possibly due to loss from surface runoff. Sorbed chemicals moved much slower
than the non-sorbed chemicals. Twenty-four days after application in November, the
peak concentration was located at 0-40 cm for Br, and the front of the Br plume extended
down to 80 cm, but for Rb the peak concentration was located in the top 10 cm, with no
observable plume down to subsoil. Due to the adsorption and fixation by soil minerals,
recovery was lower for Rb than Br both in the soil and percolate. Therefore, non-sorbed
residual chemicals after harvest, or fertilizers applied in fall, can be transported to surface
111
and groundwater in the winter rainy season. The loss of adsorbable chemical was less
than the non-absorbable chemical, suggested a lower pollution potential under all
conditions.
During the summer irrigation season, due to the uneven application and spread of
irrigation water, very high spatial variability of chemical distribution in soil profile was
found in the FL treatment. Chemicals were transported through the soil matrix more
uniformly under PU than under MI and FL irrigation. One flood irrigation event on July
26 plus a thunderstorm on July 30 resulted in 43% of the Br tracer applied on July 12 lost
from the upper 120 cm soil profile, while the thunderstorm had little effect on the
leaching of Br in the PU and MI plots. That indicates that the low intensity irrigation that
followed the chemical application enhanced the movement of the chemical into soil
aggregates, thereby reducing the leaching of the chemical by subsequent thunderstorms.
From August 6 to October 8 of 1996, the peak concentration of Br traveled 20 cm
under the PU irrigation, but moved little under MI and FL. That indicates that the daily
application of ultra-low rate irrigation transported chemicals more efficiently through soil
matrix than the intermittent application of a similar amount of water allied at higher rates.
The higher application rates caused preferential flow in the MI and FL plots. Lateral and
vertical preferential flow resulted in multiple pulses and chemical spread down as deep as
100 cm in MI and FL plots, unlike in the PU plot. The volume of percolate and mass of
chemical collected under the FL irrigation was 100 times greater than under PU and MI
irrigation.
Percolate collected under PU and MI was nearly zero during the period
between August and October in 1995 and 1996. A considerable amount of water
recharged to groundwater during each flood irrigation event resulting in a temporary rise
112
of the water table. Due to adsorption, the mass of blue dye recovered in the percolate was
much less than Br, compared with their initial amount of application. Only small amount
of Br was lost from the soil profile during the period from August 6 to October 8 of 1996
even under flood irrigation, indicating that the majority of chemical was leached out by
preferential flow only in the first one or two flood irrigation events. After the chemical
moved into soil aggregates, macropore flow played a decreasingly important role in the
chemical movement.
In summary, microsprinlder and pulsator can be used as alternative irrigation
methods in such a cracking clay soil to reduce macropore flow and protect groundwater
from contamination by agrichemicals, while at the same time they can provide adequate
available water for pear growth and produce quality fruit, comparable to flood irrigation.
113
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Appendices
123
APPENDIX A. RESULTS OF ANALYSIS OF VARIANCE
124
Table A-1. Analysis of variance for pear fruit diameter at harvest in 1995.
Source of
variation
Main Effects
Sum of
square
Degree of
freedom
Mean
Square
F-ratio
Significant
level
A:Replication
3.15
3
1.05
0.67
0.602
B:Treatment
102.65
2
51.33
32.69
0.001
9.43
6
1.57
115.24
11
Residual
Total
Table A-2. Analysis of variance for pear fruit weight at harvest in 1995.
Sum of
square
Degree of
freedom
Mean
Square
F-ratio
Significant
level
A:Replication
588.0
3
196.0
2.15
0.195
B:Treatment
6224.7
2
3112.3
34.2
0.001
Residual
546.0
6
91.0
Total
7358.7
11
Source of
variation
Main Effects
Table A-3. Analysis of variance for pear yield at harvest in 1995.
Sum of
square
Degree of
freedom
Mean
Square
F-ratio
Significant
level
A:Replication
0.00111
3
0.00037
1.06
0.431
B:Treatment
0.00094
2
0.00047
1.34
0.327
Residual
0.00207
6
0.00035
Total
0.00411
11
Source of
variation
Main Effects
125
Table A-4. Analysis of variance for pear fruit diameter at harvest in 1996.
Source of
variation
Main Effects
Sum of
square
Degree of
freedom
Mean
Square
F-ratio
Significant
level
A:Replication
13.90
3
4.63
0.68
0.597
B:Treatment
34.57
2
17.28
2.53
0.160
Residual
41.01
6
6.84
Total
89.48
11
Table A-5. Analysis of variance for pear fruit weight at harvest in 1996.
Sum of
square
Degree of
freedom
Mean
Square
F-ratio
Significant
level
A:Replication
2422.58
3
807.53
2.70
0.139
B:Treatment
3320.11
2
1660.05
5.55
0.043
Residual
1796.36
6
299.39
Total
7539.04
11
Source of
variation
Main Effects
Table A-6. Analysis of variance for pear yield at harvest in 1996.
Sum of
square
Degree of
freedom
Mean
Square
F-ratio
Significant
level
A:Replication
0.00087
3
0.00029
2.64
0.142
B:Treatment
0.00059
2
0.00029
2.64
0.142
Residual
0.00065
6
0.00011
Total
0.00211
11
Source of
variation
Main Effects
126
Table A-7. Analysis of variance for pear fruit decay in storage in 1995.
Sum of
square
Degree of
freedom
Mean
Square
F-ratio
Significant
level
A:Replication
221.08
3
73.69
15.65
0.000
B:Treatment
216.16
2
108.08
22.95
0.000
Residual
536.90
114
4.71
Total
974.14
119
Source of
variation
Main Effects
Table A-8. Analysis of variance for pear fruit decay in storage in 1996.
Sum of
square
Degree of
freedom
Mean
Square
F-ratio
Significant
level
A:Replication
206.79
3
68.93
8.15
0.000
B:Treatment
82.51
2
41.26
4.88
0.009
Residual
964.49
114
8.46
Total
1253.79
119
Source of
variation
Main Effects
Table A-9. Analysis of variance for Br mass recovered in 120 cm soil on 12/11/1995.
Sum of
square
Degree of
freedom
Mean
Square
F-ratio
Significant
level
A:Replication
15.02
3
5.01
1.05
0.44
B:Treatment
6.78
2
3.39
0.71
0.53
Residual
28.54
6
4.76
Total
50.34
11
Source of
variation
Main Effects
127
Table A-10. Analysis of variance for Br mass recovered in 120 cm soil on 6/24/1996.
Source of
variation
Main Effects
Sum of
square
Degree of
freedom
Mean
Square
F-ratio
Significant
level
A:Replication
4.74
3
1.58
1.43
0.33
B:Treatment
4.73
2
2.36
2.14
0.20
Residual
6.64
6
1.11
Total
16.10
11
Table A-11. Analysis of variance for Br mass recovered in 120 cm soil on 8/5/1996.
Source of
variation
Main Effects
Sum of
square
Degree of
freedom
Mean
Square
F-ratio
Significant
level
A:Replication
155.35
3
51.78
1.77
0.22
B:Treatment
214.68
2
107.34
3.67
0.06
Residual
292.73
10
29.27
Total
662.77
15
Table A-12. Analysis of variance for Br mass recovered in 120 cm soil on 10/8/1996.
(Because of the non-normal distribution, LOG-transform was applied.)
Source of
variation
Main Effects
Sum of
square
Degree of
freedom
Mean
Square
F-ratio
Significant
level
A:Replication
1.668
3
0.556
2.47
0.12
B:Treatment
1.337
2
0.668
2.97
0.09
Residual
2.254
10
0.225
Total
5.259
15
128
Table A-13. Analysis of variance for Rb mass recovered in 46 cm soil on 12/11/1995.
Source of
variation
Main Effects
Sum of
square
Degree of
freedom
Mean
Square
F-ratio
Significant
level
A:Replication
0.0113
3
0.0038
0.069
0.98
B:Treatment
0.0151
2
0.0076
0.137
0.88
Residual
0.3306
6
0.0551
Total
0.3571
11
Table A-14. Analysis of variance for Rb mass recovered in 46 cm soil on 6/24/1996.
Source of
variation
Main Effects
Sum of
square
Degree of
freedom
Mean
Square
F-ratio
Significant
level
A:Replication
0.0262
3
0.0087
1.97
0.22
B:Treatment
0.0029
2
0.0014
0.32
0.74
Residual
0.0266
6
0.0044
Total
0.0557
11
129
APPENDIX B. RESULTS OF REGRESSION ANALYSIS
130
The multiple linear regression model for pear fruit expansion and firmness decline
can be written as:
y = Ro +
t + 132 Ind(treat) +133 Ind(treat) t
(1)
where po, pi, 132, 03 are coefficients, t is time, Ind(treat) is an indicate parameter. For
flood irrigation, Ind(treat) = 0, and the model (1) becomes
(2)
y = Po + pi t
For microsprinkler irrigation, Ind(treat) =1, and the model (1) becomes
y = Po
t
132 + 133 t
(30 + 132) ± (131 +
t
(3)
if P2 and 03 equal zero, then the model (2) and (3) are identical, there are no difference of
intercept and slope between the two linear models. Therefore, to test the difference
between the model (2) and (3) is to use Student t-test for 02 =0, and 133 =0.
Similarly, for pulsator irrigation, the model becomes
Y = (R0 ± 02') + (R1 ± P3' ) t
(4)
and to test the difference between the model (2) and (4) is to use Student t-test for 132' = 0,
and f33' = 0.
The results of the regression analysis for the pear fruit expansion rate in 1995 and
1996 are listed in Table B-1 and B-2, and for firmness decline in the storage in 1995 and
1996 are listed in Table B-3 and B-4.
The multiple linear regression model for neutron probe calibration curves derived
from fixed and varied bulk density can be written as:
Y = (30 + 13i R + r32Ind(BD) +133 Ind(BD) R
(5)
131
where 13o, Pi, 132, i33 are coefficients, R is count ratio, Ind(BD) is an indicate parameter.
For fixed bulk density, Ind(BD) = 0, and the model (5) becomes
Y = 00 + 01 R
(6)
For varied bulk density, Ind(BD) =1, and the model (5) becomes
Y = Po + Pi R 4- 132 ± 133 R = (0o ± p2)± (13i ± 133)R
(7)
if 132 and 03 equal zero, then the model (6) and (7) are identical, there are no difference of
intercept and slope between the two linear models. Therefore, to test the difference
between the model (6) and (7) is to use Student t-test for 02 =0, and 133 =0.
Similarly, the linear regression model for the neutron probe calibration curve derived
from the original and adjusted count ratio can be written as:
Y = Po + pi R + 132 Ind(CR) + 133 Ind(CR) R
(8)
where 13o, 131, 132, 03 are coefficients, R is count ratio, Ind(CR) is an indicate parameter.
For original count ratio, Ind(CR) = 0, and for adjusted count ratio Ind(CR) =1. The
difference of the intercept and slope between the models with Ind(CR) = 0 and
Ind(CR) = 1, can be tested by student t-test for 132 =0, and 133 =0 as described above.
The results of the regression analysis for the neutron probe calibration curves with
fixed and varied bulk density are listed in Table B-5, and for neutron probe calibration
curves with original and adjusted count ratio are listed in Table B-6.
132
Table B-1. Results of linear regression analysis for the pear fruit expansion rate in 1995.
Independent variable
Coefficient
Standard error
t-value
Constant, Po
0.4298
0.0197
21.80
Significant
level
0.000
Time, 131
-0.0043
0.0007
-6.069
0.000
Ind(treat), 132
-0.0136
0.0279
-0.4891
0.626
Ind(treat), P2'
-0.0644
0.0279
-2.3102
0.024
Ind(treat) x time, 133
-0.00002
0.0010
-0.0211
0.983
Ind(treat) x time, P3'
-0.0020
0.0010
-0.0231
0.047
Table B-2. Results of linear regression analysis for the pear fruit expansion rate in 1996.
Independent variable
Coefficient
Standard error
t-value
Constant, 13o
0.5873
0.0371
15.81
Significant
level
0.000
Time, 13i
-0.0034
0.0006
-6.27
0.000
Ind(treat), 132
0.0101
0.0525
0.19
0.847
Ind(treat), 132'
-0.0241
0.0525
-0.46
0.647
Ind(treat) x time, 133
-0.0006
0.0008
-0.81
0.422
Ind(treat) x time, 133'
-0.0002
0.0008
-0.26
0.796
Table B-3. Results of linear regression analysis for the pear fruit firmness decline in
storage in 1995.
Independent variable
Coefficient
Standard error
t-value
Constant, $3o
66.9918
0.9198
72.83
Significant
level
0.000
Time, 131
-2.4271
0.3442
-7.05
0.000
Ind(treat), 132
-1.7660
1.2999
-1.36
0.175
Ind(treat), 132'
4.9012
1.3004
3.77
0.000
Ind(treat) x time, 133
0.5247
0.4847
1.08
0.280
Ind(treat) x time, 133'
1.9613
0.4857
4.04
0.000
133
Table B-4. Results of linear regression analysis for the pear fruit firmness decline in
storage in 1996.
Coefficient
Standard error
t-value
Constant, 130
57.2953
0.8165
70.18
Significant
level
0.000
Time, PI
-1.2047
0.3032
-3.97
0.000
Ind(treat), 132
3.8456
1.1547
3.33
0.001
Ind(treat), 132'
0.4658
1.1547
0.40
0.687
Ind(treat) x time, 133
-0.4143
0.4288
-0.97
0.334
Ind(treat) x time, 133'
0.2621
0.4288
0.61
0.541
Independent variable
Table B-5. Results of linear regression analysis for the neutron probe calibration curve
with fixed and varied bulk density.
Independent variable
t-value
-4.89
Significant
level
0.000
Constant, 13o
-0.1811
Standard
error
0.0370
Count Ratio, 13i
0.4473
0.0303
14.79
0.000
Ind(BD), 132
0.0927
0.0524
1.77
0.080
Ind(BD) x Count Ratio, 133
-0.0674
0.0428
-1.57
0.119
Coefficient
Table B-6. Results of linear regression analysis for the neutron probe calibration curve
with original and adjusted count ratio.
Independent variable
Coefficient
t-value
-2.67
Significant
level
0.009
Constant, 130
-0.0884
Standard
error
0.0331
Count Ratio, Pi
0.3800
0.0270
14.06
0.000
Ind(CR), 132
0.0443
0.0442
1.00
0.319
Ind(CR) x Count Ratio, 133
-0.0308
0.0363
-0.85
0.400
134
APPENDIX C. DISTRIBUTION OF Br IN SOIL IN THE GRASS LANE
135
25
0')
.0) 20
:t3
C
E
o
15
PU-out-1
10
PU-out-3
PU-out-2
X
5
PU-out-4
Average
B.G.
0
40
20
60
80
100
120
Depth (cm)
25
.0) 20
MI-out-1
w - 15
MI-out-2
10
MI-out-3
MI-out-4
-C
X
Average
5
B.G.
0
r
0
20
40
60
80
100
120
140
Depth (cm)
25
C)
a) 20
0
FL-out-1
(9
FL-out-2
15
FL-out-3
CU
7:$ 10
X
FL-out-4
Average
5
B.G.
0
AI
0
20
40
60
80
100
120
140
Depth (cm)
Fig. C-1. Br distribution in the soil profile within the grass lane on 12/11/95
B. G. is background concentration measured in September, 1995.
136
20
C7)
(9C7) 15
O
ci)
10
0
5
PU-out-1
PU-out-2
PU-out-3
x
PU-out-4
Average
B.G.
0
20
40
60
80
100
120
140
Depth (cm)
20
(90,
O
15
MI-out-1
MI-out-2
10
32
E,
co
MI-out-3
X
5_
MI-out-4
Average
B.G.
0
0
20
40
60
80
100
120
140
Depth (cm)
20
0
15
FL-out-1
FL-out-2
"JD 10
0
5
A
FL-out-3
x
FL-out-4
Average
B.G.
0
0
20
40
60
80
100
120
140
Depth (cm)
Fig. C-2. Br distribution in the soil profile within the grass lane on 6/24/96
B. G. is background concentration measured in September, 1995.
137
70
Co 60
(IP0 50
x
PU-out-1
40
cy
30
E 20
PU-out-2
PU-out-3
X PU-out-4
2 10
co
Average
0
I
I
20
40
60
80
100
120
140
Depth (cm)
70
cs) 60
criP) 50
0
MI-out-1
Z.% 40
MI-out-2
30
E 20
MI-out-3
X MI-out-4
x
2
03 io
o,
Average
20
0
40
60
80
100
120
140
Depth (cm)
70
x
cm 60
50
ar?
FL-out-1
40
a)
-0 30
FL-out-2
FL-out-3
.E 20
X FL-out-4
O
ct 10
X
V
0
0
20
40
h1-4-0
60
80
100
Average
I+
120
140
Depth (cm)
Fig. C-3. Br distribution in the soil profile within the grass lane on 8/5/96
138
70
cn 60(9°1 50
0
PU-out-1
40
PU-out-2
a)
30
-0
20
X PU-out-4
" 10
Average
PU-out-3
O
CO
0
20
0
40
60
80
100
120
140
Depth (cm)
70
60
0)
50
40
O
30
P=
20
0
(2
A
MI-out-1
MI-out-2
MI-out-3
X MI-out-4
10-
Average
0,
0
MI-------1117-4-76-47-1111
100 120
40
60
80
I
20
140
Depth (cm)
70
CD 60
0 50-
ci?
FL-out-1
40
FL-out-2
a) 30
E 20
CO
FL-out-3
X FL-out-4
10
Average
0
0
20
40
60
80
100
120
140
Depth (cm)
Fig. C-4. Br distribution in the soil profile within the grass lane on 10/8/96.
139
APPENDIX D. MEDFORD STATION WEATHER, GROUNDWATER,
SOIL WATER, AND PERCOLATE DATA
140
Table D-1. Medford Station weather data.
Max. T = Maximum Temperature
MM. T = Minimum Temperature
PP = precipitaion
ET = Evaporation from water surface
Date
6/1/95
6/2/95
6/3/95
6/4/95
6/5/95
6/6/95
6/7/95
6/8/95
6/9/95
6/10/95
6/11/95
6/12/95
6/13/95
6/14/95
6/15/95
6/16/95
6/17/95
6/18/95
6/19/95
6/20/95
6/21/95
6/22/95
6/23/95
6/24/95
6/25/95
6/26/95
6/27/95
6/28/95
6/29/95
6/30/95
7/1/95
7/2/95
7/3/95
7/4/95
7/5/95
7/6/95
7/7/95
7/8/95
7/9/95
7/10/95
Max.T
Min.T
°C
°C
PP
mm
5.59
0.00
0.00
31.08
27.75
24.42
11.66
9.44
7.22
27.20
6.66
6.66
7.22
4.44
2.29
0.76
6.66
9.99
3.33
5.00
9.44
8.33
9.99
10.55
7.22
7.77
8.88
5.55
6.11
8.88
0.00
2.03
0.00
0.00
8.89
8.64
0.51
1.27
0.76
1.02
8.38
0.00
0.00
0.00
10.55
0.00
0.00
0.00
0.00
0.00
14.99
14.43
19.98
27.20
23.31
21.09
21.65
17.76
18.32
16.65
19.98
18.87
16.10
16.65
19.43
25.53
28.86
32.75
32.75
34.97
34.97
36.08
35.52
32.75
29.97
31.64
31.08
31.08
26.64
26.09
9.44
11.66
8.33
12.21
10.55
13.88
11.10
9.99
12.21
14.43
12.21
11.66
1.78
0.00
1.27
0.00
0.00
0.00
0.00
5.59
1.78
21.59
ET
Date
mm
6.62
7/11/95
6.49
7/12/95
6.01
7/13/95
7/14/95
5.26
7/15/95
5.07
7/16/95
5.07
7/17/95
4.71
7/18/95
7/19/95
7/20/95
3.60
3.55
7/21/95
3.13
7/22/95
2.60
7/23/95
10.81
7/24/95
11.51
7/25/95
11.39
7/26/95
7/27/95
11.32
7/28/95
11.15
7/29/95
11.09
11.46
7/30/95
7/31/95
11.29
10.82
8/1/95
10.23
8/2/95
8/3/95
8/4/95
8.35
8/5/95
7.60
8/6/95
6.95
8/7/95
6.29
8/8/95
5.64
8/9/95
5.03
8/10/95
4.36
8/11/95
8/12/95
4.02
3.44
8/13/95
8/14/95
2.65
10.08
8/15/95
9.56
8/16/95
8/17/95
8/18/95
10.69
8/19/95
Max.T
Min.T
°C
°C
22.76
23.87
22.20
26.64
11.10
13.88
8.33
8.33
34.97
36.63
28.31
33.30
32.19
9.44
19.43
16.65
12.77
14.99
0.00
0.00
0.76
0.00
0.00
7.98
7.34
7.17
31.64
29.97
29.97
29.97
33.86
34.41
23.87
30.53
35.52
34.97
33.30
12.21
11.66
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
4.39
3.75
3.40
2.92
9.27
8.50
7.88
7.59
7.03
6.45
5.82
33.86
26.64
30.53
23.31
26.64
27.20
28.31
27.20
28.31
20.54
21.09
6.11
7.22
12.21
8.33
7.77
7.77
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
3.36
10.99
10.36
9.98
9.18
8.97
8.43
8.23
7.67
7.26
6.85
9.44
12.77
12.21
13.88
5.55
7.22
10.55
12.21
11.66
6.66
9.99
11.66
6.11
4.44
PP
mm
0.00
0.00
0.00
0.00
1.02
ET
mm
10.58
10.15
10.04
9.51
6.71
5.85
141
Table D-1. Medford Station weather data (continued).
Date
Max.T Min.T
PP
ET
Date
°C
°C
mm
mm
8/20/95
10/5/95
8/21/95
32.19
5.55
0.00
5.68
10/6/95
8/22/95
32.19
8.33
0.00
5.13
10/7/95
8/23/95
32.19
9.44
0.00
4.37
10/8/95
8/24/95
24.42
6.11
0.00
4.17
10/9/95
8/25/95
24.98
5.55
0.00
3.80
10/10/95
8/26/95
10/11/95
8/27/95
10/12/95
8/28/95
10/13/95
8/29/95
26.64
5.00
0.00
11.92
10/14/95
8/30/95
23.87
7.22
0.00
10.93
10/15/95
8/31/95
26.64
7.77
0.00
10.75
10/16/95
9/1/95
29.97
8.88
0.00
10.33
10/17/95
9/2/95
10/18/95
9/3/95
10/19/95
9/4/95
10/20/95
9/5/95
32.19
6.11
0.00
8.58
10/21/95
9/6/95
25.53
7.22
0.00
8.24
10/22/95
9/7/95
27.20
9.44
0.00
7.83
10/23/95
9/8/95
25.53
6.11
0.00
7.17
10/24/95
9/9/95
10/25/95
9/10/95
10/26/95
9/11/95
29.97
7.77
10/27/95
0.00
6.33
9/12/95
30.53
8.33
0.00
6.04
10/28/95
9/13/95
32.75
9.44
0.00
5.72
10/29/95
9/14/95
32.75
9.99
0.00
5.13
10/30/95
9/15/95
31.08
11.10
0.00
4.86
10/31/95
9/16/95
11/1/95
9/17/95
11/2/95
9/18/95
31.08
7.22
0.00
4.23
11/3/95
9/19/95
28.31
7.77
0.00
3.81
11/4/95
9/20/95
11/5/95
9/21/95
29.42
8.33
0.00
3.66
11/6/95
9/22/95
11/7/95
9/23/95
11/8/95
9/24/95
11/9/95
9/25/95
31.64
6.66
1.27
2.67
11/10/95
9/26/95
18.87
11.10
1.52
10.28
11/11/95
9/27/95
21.65
12.21
0.00
9.93
11/12/95
9/28/95
20.54
6.11
0.25
9.99
11/13/95
9.44
2.54
9/29/95
18.32
10.12
11/14/95
9/30/95
18.32
5.55
11/15/95
0.00
9.69
10/1/95
11/16/95
10/2/95
20.54
3.33
0.00
9.51
11/17/95
10/3/95
21.09
4.44
0.00
9.16
11/18/95
10/4/95
11/19/95
Max.T
Min.T
°C
°C
ET
mm
9.00
20.54
24.42
-1.11
-0.56
PP
mm
0.00
0.00
20.54
22.76
14.99
15.54
-1.11
7.77
5.00
-1.11
0.00
0.00
4.32
0.00
8.25
8.10
8.47
8.34
23.87
20.54
21.09
-0.56
2.78
3.89
0.00
0.00
0.00
8.06
7.62.
7.64
24.42
17.21
17.76
-4.44
-2.78
-2.22
16.10
17.21
3.89
0.00
0.00
0.00
0.76
0.00
0.00
7.19
7.17
7.27
7.24
19.43
19.43
17.76
0.56
2.78
-5.00
0.00
0.00
0.00
7.03
7.01
0.00
14.43
-6.11
0.00
0.00
13.88
16.65
16.10
-6.66
5.55
8.33
1.27
0.00
8.89
0.00
0.00
0.00
16.10
19.98
14.99
14.43
13.32
3.33
5.55
6.11
4.44
5.00
3.30
0.25
0.25
0.25
0.00
0.00
0.00
0.00
0.00
0.00
1.67
8.81
142
Table D-1. Medford Station weather data (continued).
Date
Max.T Min.T
PP
ET
Date
°C
°C
mm
mm
11/20/95
16.65
-1.11
5.33
0.00
1/5/96
11/21/95
11/22/95
11/23/95
11/24/95
11/25/95
11/26/95
11/27/95
11/28/95
11/29/95
11/30/95
12/1/95
12/2/95
12/3/95
12/4/95
12/5/95
12/6/95
12/7/95
12/8/95
12/9/95
12/10/95
12/11/95
12/12/95
12/13/95
12/14/95
12/15/95
12/16/95
12/17/95
12/18/95
12/19/95
12/20/95
12/21/95
12/22/95
12/23/95
12/24/95
12/25/95
12/26/95
12/27/95
12/28/95
12/29/95
12/30/95
12/31/95
1/1/96
1/2/96
1/3/96
1/4/96
14.43
7.77
12.77
11.66
14.43
10.55
9.44
9.99
10.55
11.66
17.76
17.21
14.43
9.99
8.88
7.22
7.22
8.33
0.56
3.89
4.44
7.22
8.33
9.14
-0.56
5.00
3.89
6.66
14.22
8.64
6.11
6.66
4.44
2.22
0.00
-1.11
-0.56
-1.11
-0.56
1.27
0.25
7.87
15.75
6.86
5.33
0.76
26.92
39.62
25.15
46.23
0.00
0.00
0.25
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
1/6/96
1/7/96
1/8/96
1/9/96
1/10/96
1/11/96
1/12/96
1/13/96
1/14/96
1/15/96
1/16/96
1/17/96
1/18/96
1/19/96
1/20/96
1/21/96
1/22/96
1/23/96
1/24/96
1/25/96
1/26/96
1/27/96
1/28/96
1/29/96
1/30/96
1/31/96
2/1/96
2/2/96
2/3/96
2/4/96
2/5/96
2/6/96
2/7/96
2/8/96
2/9/96
2/10/96
2/11/96
2/12/96
2/13/96
2/14/96
2/15/96
2/16/96
2/17/96
2/18/96
2/19/96
Max.T
Min.T
°C
°C
PP
mm
ET
mm
11.10
5.55
6.66
5.55
-5.00
0.00
0.56
3.33
78.23
4.34
0.00
10.67
0.00
0.00
0.00
0.00
12.21
4.44
-1.67
-0.56
28.45
6.35
0.00
0.00
7.22
-0.56
22.35
0.00
9.99
5.00
6.66
11.10
9.99
-0.56
16.00
8.38
4.32
0.00
0.00
0.00
0.00
0.00
0.00
0.00
13.88
16.65
17.76
20.54
22.20
-4.44
8.88
8.33
8.33
9.44
21.34
0.00
0.00
0.00
14.48
0.00
0.00
0.00
0.00
0.00
17.76
18.87
19.43
17.76
18.32
-0.56
-0.56
-1.11
-1.11
0.56
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
19.43
0.56
15.75
0.00
1.67
1.67
-2.78
-4.44
143
Table D-1. Medford Station weather data (continued).
Date
Max.T Min.T
PP
ET
Date
°C
°C
mm
mm
2/20/96
4/6/96
2/21/96
4/7/96
2/22/96
15.54
0.00
35.56
0.00
4/8/96
2/23/96
8.33
0.56
1.02
0.00
4/9/96
2/24/96
4/10/96
2/25/96
4/11/96
2/26/96
8.33
-3.33
9.65
0.00
4/12/96
2/27/96
5.55
-2.78
0.00
0.00
4/13/96
2/28/96
8.88
-0.56
0.00
0.00
4/14/96
2/29/96
11.10
1.67
0.00
0.00
4/15/96
3/1/96
4/16/96
3/2/96
4/17/96
3/3/96
4/18/96
3/4/96
16.10
-2.22
0.25
0.00
4/19/96
3/5/96
14.99
-0.56
2.54
0.00
4/20/96
3/6/96
9.99
-2.22
0.00
0.00
4/21/96
3/7/96
15.54
3.33
0.25
0.00
4/22/96
3/8/96
4/23/96
3/9/96
4/24/96
3/10/96
4/25/96
3/11/96
21.65
3.89
2.79
0.00
4/26/96
3/12/96
15.54
1.11
0.76
0.00
4/27/96
3/13/96
12.77
3.89
0.00
0.00
4/28/96
14.99
-1.11
0.00
3/14/96
0.00
4/29/96
3/15/96
19.43
1.67
0.00
0.00
4/30/96
3/16/96
5/1/96
3/17/96
5/2/96
3/18/96
5/3/96
3/19/96
23.31
-0.56
0.00
0.00
5/4/96
3/20/96
18.32
-0.56
0.00
0.00
5/5/96
0.00
0.00
0.00
3/21/96
16.65
5/6/96
3/22/96
18.87
3.89
0.25
0.00
5/7/96
3/23/96
5/8/96
3/24/96
5/9/96
0.00
5/10/96
3/25/96
13.88
-1.11
0.25
3/26/96
5/11/96
3/27/96
16.65
-1.67
8.89
0.00
5/12/96
4.44
0.00
16.26
0.00
5/13/96
3/28/96
3/29/96
5/14/96
3/30/96
5/15/96
5/16/96
3/31/96
13.21
0.00
5/17/96
4/1/96
14.43
-1.11
4/2/96
15.54
2.22
0.00
0.00
5/18/96
4/3/96
13.32
3.89
0.25
0.00
5/19/96
4/4/96
16.65
0.00
0.00
0.00
5/20/96
0.00
0.00
5/21/96
4/5/96
21.09
1.67
Max.T
Min.T
°C
°C
PP
mm
ET
mm
26.64
26.09
4.44
6.11
0.00
0.00
0.00
0.00
14.43
17.21
3.33
14.73
1.27
0.00
0.00
22.20
19.43
14.99
11.66
13.32
-0.56
5.00
-0.56
0.56
2.78
0.00
4.06
0.25
1.52
0.25
0.00
0.00
0.00
0.00
0.00
14.99
0.56
17.21
22.76
8.33
9.44
6.86
0.00
15.75
0.00
0.00
0.00
21.09
0.56
0.25
0.00
23.31
24.98
24.98
22.76
17.76
0.00
5.00
5.00
6.66
3.89
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
18.32
-1.11
0.56
0.00
0.00
1.11
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
30.53
22.20
19.98
18.32
19.98
3.33
13.88
11.10
10.55
9.44
0.00
7.87
4.57
3.30
8.89
0.00
0.00
0.00
0.00
0.00
16.65
5.00
18.80
0.00
21.09
18.32
17.76
19.98
2.78
144
Table D-1. Medford Station weather data (continued).
Date
Max.T Min.T
PP
ET 5/25/96
°C
mm
°C
mm
Date
5/22/96
18.87
4.44
17.53
0.00
7/7/96
5/23/96
14.99
5.00
0.00
0.00
7/8/96
5/24/96
16.10
1.67
0.00
0.00
7/9/96
5/25/96
7/10/96
5/26/96
7/11/96
5/27/96
7/12/96
5/28/96
26.09
5.55
0.00
0.00
7/13/96
5/29/96
17.21
2.78
0.00
0.00
7/14/96
5/30/96
19.43
2.22
0.00
0.00
7/15/96
5/31/96
21.09
7.77
0.00
0.00
7/16/96
6/1/96
7/17/96
6/2/96
7/18/96
6/3/96
7/19/96
6/4/96
7/20/96
6/5/96
7/21/96
6/6/96
7/22/96
6/7/96
7/23/96
6/8/96
7/24/96
6/9/96
7/25/96
6/10/96
32.75
5.00
0.00
7/26/96
0.00
6/11/96
26.09
5.00
0.00
0.00
7/27/96
6/12/96
26.64
5.55
0.00
0.00
7/28/96
7.77
6/13/96
29.97
0.00
0.00
7/29/96
6/14/96
24.98
7.22
0.00
0.00
7/30/96
6/15/96
7/31/96
6/16/96
8/1/96
6/17/96
25.53
0.00
0.00
8/2/96
3.89
6/18/96
19.98
1.67
0.00
0.00
8/3/96
6/19/96
22.20
2.22
0.00
0.00
8/4/96
6/20/96
27.20
9.44
0.00
0.00
8/5/96
6/21/96
26.09
5.55
0.00
0.00
8/6/96
6/22/96
8/7/96
6/23/96
8/8/96
6/24/96
8/9/96
6/25/96
24.98
3.89
6.60
0.00
8/10/96
6/26/96
22.20
7.22
0.00
0.00
8/11/96
6/27/96
23.31
12.77
0.00
0.00
8/12/96
6/28/96
21.65
11.66
0.00
0.00
8/13/96
6/29/96
8/14/96
8/15/96
6/30/96
7/1/96
31.64
7.77
0.00
8.99
8/16/96
7/2/96
8/17/96
7/3/96
8/18/96
7/4/96
8/19/96
7/5/96
8/20/96
7/6/96
8/21/96
Max.T
Min.T
°C
°C
35.52
32.75
29.97
32.75
34.41
5.55
12.77
11.10
12.77
13.32
0.00
0.00
0.00
0.00
0.00
4.07
3.33
2.91
38.85
34.41
29.97
21.09
21.09
15.54
10.55
9.99
10.55
6.11
0.51
0.00
0.00
2.03
0.00
8.13
7.37
6.63
6.85
6.27
34.41
37.74
37.19
36.63
37.74
6.66
16.10
0.00
0.00
0.00
0.00
0.00
4.57
3.92
3.22
2.62
11.17
37.74
35.52
32.75
32.75
30.53
14.43
14.43
13.88
12.21
0.51
7.22
33.02
0.00
0.00
0.00
9.61
11.57
10.95
10.28
28.31
22.20
29.97
34.41
35.52
7.77
5.00
8.33
9.44
13.32
0.00
0.00
0.00
0.00
0.00
7.86
7.16
6.99
6.44
5.62
38.30
34.97
37.19
33.86
8.88
14.43
11.10
0.00
0.00
0.00
0.00
4.13
3.69
2.82
0.18
32.75
26.64
26.64
5.55
7.22
7.77
0.00
0.00
0.00
0.00
10.26
9.74
16.65
16.10
14.99
12.21
PP
mm
ET
mm
11.12
10.39
9.49
145
Table D-1. Medford Station weather data (continued).
Date
Max.T Min.T
PP
ET
°C
°C
mm
mm
8/22/96
29.42
8.33
0.00
9.33
8/23/96
33.30
9.44
0.00
8.93
8/24/96
8/25/96
8/26/96
36.63
11.66
0.00
7.56
8/27/96
33.30
13.88
3.81
7.45
8/28/96
26.64
10.55
0.00
7.22
8/29/96
31.08
11.10
0.00
6.61
8/30/96
8/31/96
9/1/96
9/2/96
9/3/96
33.86
7.22
0.00
4.78
9/4/96
26.64
7.22
0.00
4.11
9/5/96
20.54
3.89
0.00
3.98
9/6/96
21.09
2.22
0.00
3.37
9/7/96
9/8/96
9/9/96
29.42
5.00
0.00
0.00
9/10/96
30.53
9.44
0.00
11.49
9/11/96
33.86
7.77
0.00
11.08
9/12/96
27.75
7.77
0.00
10.80
9/13/96
22.20
8.88
1.27
10.72
9/14/96
9/15/96
9/16/96
20.54
7.22
12.70
11.22
9/17/96
17.76
7.77
0.25
11.32
9/18/96
17.76
3.33
0.00
11.10
9/19/96
22.20
5.00
0.51
10.69
9/20/96
19.98
3.33
0.00
10.50
9/21/96
9/22/96
9/23/96
22.20
0.00
0.00
9.68
9/24/96
23.31
1.67
0.00
9.46
9/25/96
24.42
1.67
0.00
9.52
9/26/96
24.98
2.78
0.00
9.28
9/27/96
27.20
3.33
0.00
9.06
9/28/96
9/29/96
9/30/96
30.53
4.44
0.00
8.38
Date
Max.T
Min.T
°C
°C
PP
mm
ET
mm
146
Table D-2. Medford Station groundwater table data.
DATE
9/15/95
9/27/95
10/5/95
10/12/95
10/19/95
10/26/95
11/2/95
11/11/95
11/21/95
11/28/95
12/6/95
12/20/95
12/27/95
1/11/96
1/24/96
2/2/96
2/12/96
2/14/96
2/15/96
2/26/96
2/27/96
2/28/96
3/5/96
3/13/96
4/1/96
4/4/96
4/23/96
5/3/96
5/15/96
5/20/96
5/28/96
6/17/96
6/25/96
7/1/96
7/19/96
7/30/96
8/06/96
8/08/96
8/13/96
8/16/96
8/19/96
8/29/96
9/3/96
9/10/96
9/17/96
9/30/96
10/7/96
10/29/96
11/20/96
PA
236
247
256
227
250
260
>270
>270
>270
265
244
196
198
150
113
95
70
70
68
PB
235
244
247
220
240
250
255
260
260
260
244
200
41
42
41
58
63
56
48
56
44
50
61
80
105
152
149
150
203
210
217
242
FL
256
269
280
183
191
236
266
277
297
296
299
262
260
246
215
244
260
278
284
290
290
290
230
245
210
170
136
105
106
100
60
55
59
55
140
140
128
128
124
72
195
150
144
92
60
64
62
40
34
48
MI
228
254
286
75
102
144
140
148
194
201
212
238
185
180
222
227
236
240
240
257
250
262
265
270
220
220
230
240
237
242
246
250
257
264
270>320
275
>270
275
255
157
81
80
78
112
70
67
75
88
88
123
160
165
170
93
114
128
160
170
175
216
216
233
198
240
250
240
245
246
268
280
285
292
223
250
293
301
309
320
244
257
270
315
238
178
207
222
235
246
252
196
251
260
290
250
DATE
12/13/96
12/16/96
1/3/97
1/10/97
1/15/97
2/10/97
2/25/97
3/11/97
3/18/97
5/12/97
PA
PB
MI
172
180
132
130
135
83
175
173
123
113
260
252
121
181
65
72
60
55
46
60
114
105
85
100
153
70
140
133
211
186
FL
228
231
193
180
181
130
120
100
110
160
Table D-3. Medford Station soil water data.
9-7-95
FL
Depth (cm) N
0-20
1.2570
1.3009
20-45
1.2618
45-75
1.1045
75-105
105-135
135-165
165-195
1.1006
1.0316
1.1237
S
Average
1.2852
1.2942
1.2108
1.1832
1.2015
1.0938
1.0703
1.2711
1.2976
1.2363
1.1439
1.1511
1.0627
1.0970
Theta
0.3998
0.4090
0.3876
0.3553
0.3578
0.3270
0.3390
9-15-95
FL
Depth (cm) N
1.3050
0-20
1.3338
20-45
1.2808
45-75
75-105
1.1082
105-135
135-165
165-195
1.0986
1.0567
1.0987
Average
1.3681
1.3396
1.2479
1.1953
1.2159
1.1165
1.1010
1.3366
1.3367
1.2643
1.1518
1.1573
1.0866
1.0998
Theta
0.4226
0.4227
0.3974
0.3581
0.3600
0.3353
0.3400
9-27-95
FL
Depth (cm) N
1.3104
0-20
1.2809
20-40
1.2280
40-60
1.1901
60-90
1.2016
90-120
120-150
150-180
180-210
1.1843
1.0853
1.1278
Average
1.2589
1.2998
1.2983
1.0762
1.0578
0.9757
1.0640
1.0637
1.2847
1.2904
1.2632
1.1332
1.1297
1.0800
1.0746
1.0958
Theta
0.4045
0.4065
0.3970
0.3516
0.3504
0.3330
0.3312
0.3385
9-7-95
MI
N
1.3186
1.2984
1.1919
1.2084
1.2147
1.1117
1.0298
S
Average
1.3043
1.3739
1.2646
1.2104
1.2058
1.1390
1.1275
1.3115
1.3362
1.2283
1.2094
1.2102
1.1253
1.0786
S
Average
1.3236
1.3035
1.2176
1.2024
1.2361
1.1340
1.0419
1.3248
1.3317
1.2722
1.2273
1.2393
1.1367
1.1279
1.3242
1.3176
1.2449
1.2149
1.2377
1.1353
1.0849
1.2817
1.2468
1.2227
1.1494
1.1405
1.1150
S
Average
1.0572
1.0132
1.0036
1.0146
0.9644
0.9663
0.9954
1.0198
0.9749
0.9503
0.9731
0.9561
0.9657
0.9806
N
S
Average
1.1354
1.1299
1.1082
1.0743
0.9594
0.9787
1.1533
1.0772
1.0468
1.0550
1.0212
1.1443
1.1035
1.0775
1.0647
0.9903
0.9865
0.9977
0.9826
0.9850
S
Average
1.1750
1.1875
1.1539
1.1573
1.0848
1.0247
1.0342
1.0325
1.1838
1.1679
1.1150
1.1143
1.0407
1.0093
1.0176
1.0327
Theta
0.3120
0.2963
0.2877
0.2957
0.2898
0.2931
0.2983
9-15-95
9-15-95
MI
N
9-27-95
MI
N
1.3156
1.3372
Theta
0.4139
0.4225
0.3848
0.3782
0.3785
0.3489
0.3326
9-7-95
PB
N
0.9825
0.9365
0.8969
0.9316
0.9477
0.9652
0.9658
PB
S
Average
1.3078
1.2952
1.2187
1.2041
1.2234
1.1939
1.0828
1.0708
1.3117
1.3162
1.2502
1.2254
1.2231
1.1717
1.1116
1.0929
Theta
0.4183
0.4160
0.3906
0.3801
0.3881
0.3524
0.3347
Theta
0.4139
0.4155
0.3925
0.3838
0.3830
0.3651
0.3441
0.3375
0.9722
9-27-95
PB
N
1.1927
1.1483
1.0761
1.0712
0.9966
0.9938
1.0011
1.0328
Theta
0.3555
0.3412
0.3322
0.3277
0.3017
0.2990
0.2999
Theta
0.3693
0.3637
0.3453
0.3450
0.3193
0.3083
0.3113
0.3165
Table D-3. Medford Station soil water data (continued).
10-04-95
10-04-95
MI
FL
Average Theta
N
S
Depth (cm) N
1.2453
1.2599
0.3907
1.2816
1.2089
0-20
1.2661
1.2728
0.4003
1.2786
20-40
1.2669
1.2455
1.2599
0.3959
1.2244
1.2954
40-60
1.2242
1.1357
0.3525
1.1976
1.0738
60-90
0.3476
1.2265
1.1218
1.0511
1.1924
90-120
1.1477
1.0689
0.3291
1.1615
0.9762
120-150
1.1454
1.0780
0.3323
1.1000
1.0561
150-180
1.1009
0.3404
1.1089
1.0708
1.1311
180-210
1.1962
1.2231
1.1927
1.0796
1.0753
Average
1.2620
1.2713
1.2263
1.2102
1.2248
1.1702
1.1125
1.0921
Theta
0.3966
0.3998
0.3841
0.3785
0.3836
0.3645
0.3444
0.3373
1.3799
1.3402
1.2458
1.2209
1.1979
1.1544
1.1054
1.1898
Average
1.3403
1.3601
1.3312
1.3281
1.1010
1.1094
1.0344
1.2052
1.1225
1.3357
1.2869
1.1610
1.1537
1.0944
1.1553
1.1561
Theta
0.4309
0.4223
0.4053
0.3613
0.3588
0.3381
0.3593
0.3596
N
S
Average
1.4047
1.3899
1.3063
1.2732
1.2739
1.2144
1.2028
1.1620
1.3671
1.3298
1.2455
1.2226
1.2821
1.2191
1.0965
1.1789
1.3859
1.3598
1.2759
1.2479
1.2780
1.2168
1.1497
1.1704
Theta
0.4399
0.4308
0.4014
0.3917
0.4022
0.3808
0.3574
0.3646
FL
Depth (cm) N
1.3213
0-20
1.3164
20-40
1.2345
40-60
1.1850
60-90
1.1894
90-120
1.1484
1.0975
1.1208
S
1.2872
1.2979
1.2935
1.0650
1.0424
0.9741
1.0559
1.0818
Average
1.3043
1.3071
1.2640
1.1250
1.1159
1.0612
1.0767
1.1013
Theta
0.4114
0.4123
0.3973
0.3487
0.3456
0.3265
0.3319
0.3405
1.2834
1.2913
1.2679
1.2583
1.2547
1.1411
1.1455
1.1169
S
1.0802
Average
1.0903
1.0906
1.0221
1.0526
0.9843
1.0059
1.0046
1.0434
1.0850
1.0587
1.0663
1.0238
0.9804
1.0235
0.9759
1.0878
1.0404
1.0595
1.0040
0.9931
1.0141
1.0097
N
S
Average
1.1716
1.1748
1.1428
1.1636
1.0225
1.0139
1.0169
1.0598
1.1472
1.1283
1.1148
1.1254
1.0894
1.0409
1.0392
1.0344
1.1594
1.1516
1.1288
1.1445
1.0560
1.0274
1.0280
1.0471
S
1.0947
1.1016
Average
1.0788
1.0917
1.0580
1.0160
1.0186
1.1068
1.1106
1.0305
1.0090
1.0126
1.0071
Theta
0.3366
0.3358
0.3192
0.3259
0.3065
0.3027
0.3100
0.3085
Theta
0.3607
0.3580
0.3501
0.3556
0.3246
0.3147
0.3149
0.3215
10-19-95
PB
10-19-95
MI
N
N
1.1003
10-12-95
PB
MI
10-19-95
120-150
150-180
180-210
1.2641
1.2765
1.2072
10-12-95
10-12-95
FL
Depth (cm) N
0-20
20-40
40-60
60-90
90-120
120-150
150-180
180-210
10-04-95
PB
S
Average
1.2958
1.2917
1.2108
1.1817
1.2452
1.1919
1.0678
1.2896
1.2915
1.2394
1.2200
1.2499
1.1665
1.1067
1.0940
1.0710
Theta
0.4062
0.4069
0.3887
0.3819
0.3924
0.3632
0.3423
0.3379
N
1.1453
1.1447
1.1348
1.1294
1.0030
1.0019
1.0065
1.0422
0.9720
1.1200
1.1231
Theta
0.3470
0.3481
0.3424
0.3437
0.3157
0.3082
0.3095
0.3076
Table D-3. Medford Station soil water data (continued).
10-26-95
MI
10-26-95
FL
Depth (cm) N
0-20
1.3208
1.3030
20-40
1.2420
40-60
1.2104
60-90
1.2082
90-120
120-150
150-180
180-210
1.1523
1.1012
1.1365
S
Average
1.2752
1.2885
1.2954
1.0704
1.0560
0.9725
1.0779
1.0708
1.2980
1.2957
1.2687
1.1404
1.1321
1.0624
1.0895
1.1037
Theta
0,4092
0.4084
0.3989
0.3541
0.3512
0.3269
0.3364
0.3413
Depth (cm) N
0-20
1.3152
1.3009
20-40
1.2414
40-60
1.2018
60-90
1.2202
90-120
1.1635
1.1052
1.1338
S
Average
1.2660
1.2967
1.2906
1.2988
1.2677
1.1332
1.1345
1.0706
1.0888
1.0959
Average
1.2774
1.2972
1.2173
1.1959
1.2686
1.1919
1.0692
1.0765
1.2658
1.2901
1.2384
1.2276
1.2624
1.1863
1.1183
1.0950
1.2941
1.0645
1.0488
0.9777
1.0724
1.0581
N
S
0.3521
0.3298
0.3361
0.3386
1.2341
1.2757
1.2470
1.2642
1.2702
1.2023
1.1568
1.1221
1.2639
1.2869
1.2167
1.2028
1.2739
1.2042
1.0730
1.0719
Theta
0.4038
0.4067
0.3980
0.3532
0.3524
0.3298
0.3326
0.3393
11-11-95
MI
N
1.2489
1.2595
1.2546
1.2553
1.2684
1.1878
1.1527
1.1054
Theta
0.4066
0.4094
0.3986
0.3516
11-11-95
FL
Depth (cm) N
1.3148
0-20
1.3034
20-40
1.2442
40-60
1.2058
60-90
1.2205
90-120
120-150
150-180
180-210
S
1.2543
1.2830
1.2596
1.2594
1.2563
1.1807
1.1673
1.1135
Theta
0.3979
0.4064
0.3884
0.3846
0.3967
0.3702
0.3464
0.3383
11-02-95
MI
11-02-95
FL
120-150
150-180
180-210
N
1.1623
1.1028
1.1197
Average
1.2503
1.2782
1.2879
1.0696
1.0504
0.9789
1.0548
1.0761
1.2825
1.2908
1.2660
1.1377
1.1355
1.0706
1.0788
1.0979
Average
1.2490
1.2813
1.2319
1.2335
1.2721
1.2033
1.1149
1.0970
S
Average
1.2970
1.2941
1.2334
1.2030
1.2602
1.2033
1.0747
1.0887
1.2729
1.2768
1.2440
1.2292
1.2643
1.1956
1.1137
1.0970
10-26-95
PB
N
1.1474
1.1440
1.1403
1.1382
1.0087
1.0100
1.0130
1.0499
0.3921
0.4033
0.3861
0.3866
0.4001
0.3761
0.3452
0.3390
11-02-95
PB
N
1.1512
1.1381
1.1396
1.1476
1.0038
1.0156
1.0145
1.0446
Theta
0.4004
0.4018
0.3903
0.3851
0.3974
0.3734
0.3448
0.3390
11-11-95
PB
N
1.1386
1.1268
1.1289
1.1469
0.9998
1.0156
1.0136
1.0478
Theta
S
Average
1.0963
1.1046
1.0758
1.0984
1.0765
1.0370
1.0299
0.9722
1.1218
1.1243
1.1081
1.1183
1.0426
1.0235
1.0215
1.0111
S
Average
1.0795
1.0922
1.0767
1.0933
1.0768
1.0313
1.0404
0.9866
1.1153
1.1151
1.1081
1.1204
1.0403
1.0235
1.0274
1.0156
S
Average
1.0687
1.0817
1.0610
1.0782
1.0697
1.0309
1.0377
0.9809
1.1037
1.1043
1.0950
1.1126
1.0348
1.0233
1.0256
1.0144
Theta
0.3476
0.3485
0.3428
0.3464
0.3200
0.3133
0.3126
0.3090
Theta
0.3454
0.3453
0.3429
0.3472
0.3192
0.3133
0.3147
0.3106
Theta
0.3413
0.3415
0.3383
0.3444
0.3172
0.3132
0.3141
0.3101
Table D-3. Medford Station soil water data (continued).
Depth (cm) N
1.3276
0-20
20-40
1.3036
40-60
1.2413
1.2022
60-90
90-120
1.2140
120-150
150-180
180-210
1.1546
1.1025
1.1249
S
Average
1.2369
1.2862
1.2875
1.0601
1.0611
0.9702
1.0608
1.2823
1.2949
1.2644
1.1312
1.1375
1.0624
1.0817
1.0945
1.0641
N
S
Average
0.3531
0.3269
0.3336
0.3381
1.2309
1.2587
1.2393
1.2520
1.2537
1.1858
1.1603
1.1113
1.3032
1.2844
1.2287
1.2062
1.2498
1.1988
1.0772
1.0786
1.2670
1.2716
1.2340
1.2291
1.2518
1.1923
1.1188
1.0949
Theta
0.4080
0.4056
0.3982
0.3542
0.3495
0.3290
0.3336
0.3420
11-21-95
MI
N
1.2563
1.2591
1.2526
1.2597
1.2597
1.1771
1.1628
1.1094
Theta
0.4037
0.4081
0.3974
0.3509
11-21-95
FL
Depth (cm) N
1.3235
0-20
1.3039
20-40
40-60
1.2336
1.2089
60-90
1.2043
90-120
120-150
150-180
180-210
1.1773
1.1030
1.1396
S
Average
1.2660
1.2719
1.2994
1.0725
1.0501
1.2948
1.2879
1.2665
1.1407
1.1272
1.0686
1.0817
1.1057
0.9599
L0604
1.0718
12-06-95
FL
Depth (cm) N
0-20
1.3880
1.3351
20-40
1.2400
40-60
1.2040
60-90
1.2041
90-120
1.1592
120-150
1.0945
150-180
180-210
Theta
0.3984
0.3999
0.3868
0.3851
0.3930
0.3722
0.3466
0.3383
11-13-95
PB
N
1.1329
1.1334
1.1326
1.1381
0.9982
1.0058
1.0106
1.0437
Theta
0.4020
0.4003
0.3870
0.3857
0.3964
0.3732
0.3455
0.3400
11-21-95
PB
N
1.1289
1.1393
1.1242
1.1259
1.0101
1.0105
1.0099
1.0423
11-13-95
MI
11-13-95
FL
1.1363
S
Average
1.3831
1.3714
1.3308
1.1123
1.0777
1.3855
1.3533
1.2854
0.9838
1.0728
1.0730
1.1581
1.1409
1.0715
1.0836
1.1047
Theta
0.4397
0.4285
0.4048
0.3603
0.3543
0.3301
0.3343
0.3416
12-06-95
MI
N
1.4559
1.3866
1.3127
1.2563
1.2641
1.1803
1.1509
1.1031
S
Average
1.2985
1.2863
1.2162
1.2020
1.2630
1.2126
1.0687
1.0903
1.2774
1.2727
1.2344
1.2309
1.2614
1.1949
1.1157
1.0999
S
Average
1.3817
1.3317
1.2660
1.2327
1.2657
1.2074
1.0861
1.0811
1.4188
1.3591
1.2893
1.2445
1.2649
1.1938
1.1185
1.0921
Theta
0.4513
0.4305
0.4061
0.3905
0.3976
0.3728
0.3465
0.3373
12-06-95
PB
N
1.1876
1.1873
1.1612
1.1586
1.0271
1.0116
1.0219
1.0582
S
Average
1.0725
1.0697
1.0588
1.0949
1.0579
1.0232
1.0243
1.1027
1.1016
1.0957
1.1165
1.0280
1.0145
1.0175
1.0098
0.9758
Average
1.0787
1.0869
1.0635
1.0743
1.0593
1.0287
1.0335
0.9779
1.1038
1.1131
1.0938
1.1001
1.0347
1.0196
1.0217
1.0101
S
Average
1.2525
1.1976
1.1659
1.1765
1.0952
1.0425
1.0457
1.0568
1.2200
1.1924
1.1635
1.1675
1.0611
1.0270
1.0338
1.0575
Theta
0.3410
0.3406
0.3385
0.3458
0.3149
0.3101
0.3112
0.3085
Theta
0.3413
0.3446
0.3379
0.3401
0.3172
0.3119
0.3127
0.3086
Theta
0.3819
0.3723
0.3622
0.3636
0.3264
0.3145
0.3169
0.3252
Table D-3. Medford Station soil water data (continued).
12-27-95
FL
Depth (cm) N
1.3695
0-20
1.3395
20-40
1.3214
40-60
1.2231
60-90
1.2131
90-120
120-150
150-180
180-210
1.1747
1.1033
1.1361
S
1.3259
1.3397
1.3380
1.0918
1.0666
0.9777
1.0755
1.2078
Average
1.3477
1.3396
1.3297
1.1574
1.1398
1.0762
1.0894
1.1719
Theta
0.4265
0.4237
0.4202
0.3601
0.3539
0.3317
0.3363
0.3651
1-11-96
FL
Depth (cm) N
1.3953
0-20
20-40
1.3574
1.3239
40-60
1.2670
60-90
1.2211
90-120
120-150
150-180
180-210
1.1794
1.1064
1.1636
S
1.3852
1.3757
1.3263
1.1125
1.0935
1.0376
1.1982
1.2952
Average
1.3902
1.3665
1.3251
1.1898
1.1573
1.1085
1.1523
1.2294
Theta
0.4414
0.4331
0.4186
0.3714
0.3600
0.3430
0.3583
0.3852
12-27-95
MI
N
S
1.3234
1.3433
1.3214
1.3216
1.2992
1.3090
1.2804
1.2880
1.2737
1.2756
1.2070
1.1911
1.1608
1.0837
1.0979
1.1431
1-11-96
MI
N
1.4294
1.3666
1.3252
1.2951
1.2821
1.2103
1.1745
1.1873
2-02-96
2-02-96
FL
MI
N
1.4206
1.3676
1.3163
1.3021
1.2804
1.2227
1.1981
1.1786
Depth (cm) N
1.3980
0-20
1.3568
20-40
1.3458
40-60
1.3138
60-90
1.2795
90-120
1.2751
120-150
1.1718
150-180
1.2049
180-210
S
Average
1.3959
1.3670
1.3412
1.1035
1.2260
1.0590
1.1954
1.3306
1.3970
1.3619
1.3435
1.2087
1.2528
1.1671
1.1836
1.2678
Theta
0.4437
0.4315
0.4251
0.3780
0.3934
0.3634
0.3692
0.3986
Average
1.3334
1.3215
1.3041
1.2842
1.2746
1.1990
1.1223
1.1205
S
Average
1.3763
1.3508
1.3027
1.2932
1.2861
1.2111
1.0750
1.0650
1.4028
1.3587
1.3139
1.2942
1.2841
1.2107
1.1248
1.1261
Theta
0.4215
0.4174
0.4113
0.4043
0.4010
0.3746
0.3478
0.3472
Theta
0.4458
0.4303
0.4147
0.4078
0.4043
0.3787
0.3487
0.3491
12-27-95
PB
N
1.1760
1.1588
1.1542
1.1560
1.0156
1.0100
1.0339
1.0738
1-11-96
PB
N
1.1826
1.1833
1.1739
1.1768
1.0214
1.0132
1.0523
1.0752
S
Average
1.1385
1.1381
1.1544
1.1681
1.0959
1.0357
1.0583
1.1145
1.1572
1.1484
1.1543
1.1620
1.0557
1.0228
1.0461
1.0941
S
Average
1.2370
1.2102
1.1082
1.1711
1.0888
1.1594
1.2098
1.1967
1.1755
1.1822
1.0648
1.0921
1.0705
1.1173
S
Average
1.2391
1.2112
1.1978
1.2191
1.1907
1.1863
1.1888
1.0953
1.1771
1.1877
Theta
0.3600
0.3569
0.3590
0.3617
0.3246
0.3131
0.3212
0.3380
Theta
0.3784
0.3738
0.3664
0.3687
0.3277
0.3373
0.3297
0.3461
2-02-96
S
Average
Theta
1.3757
1.3510
1.3158
1.3043
1.2959
1.2344
1.1745
1.2375
1.3982
1.3593
1.3161
1.3032
1.2882
1.2286
1.1863
1.2081
0.4441
0.4306
0.4155
0.4110
0.4057
0.3849
0.3702
0.3778
PB
N
1.1990
1.1702
1.1747
1.1711
1.0251
1.0450
1.0558
1.0973
1.2064
1.1655
1.1723
1.0964
water
1.1087
1.0761
1.0973
Theta
0.3816
0.3717
0.3701
0.3710
0.3384
0.3430
0.3317
0.3391
Table D-3. Medford Station soil water data (continued).
2-14-96
2-14-96
MI
FL
N
Theta
Average
S
Depth (cm) N
1.3462
0.4363
1.3758
1.3657
1.3858
0-20
1.3624
0.4334
1.3674
1.3672
1.3675
20-40
1.3234
0.4238
1.3400
1.3439
1.3360
40-60
1.2891
0.3828
1.2225
1.1191
1.3259
60-90
1.2792
0.4001
1.2720
1.2233
1.3206
90-120
1.2223
0.3570
1.1487
1.0317
1.2657
120-150
1.1857
0.3688
1.1823
1.1566 1.2080
150-180
1.1691
0.3611
1.1604
1.1134
1.2074
180-210
Depth (cm) N
1.3917
0-20
1.3593
20-40
1.3567
40-60
1.3192
60-90
1.3272
90-120
1.2753
1.1688
1.1947
S
Average
1.3675
1.3628
1.3347
1.1294
1.2160
1.0476
1.1987
1.1381
1.3796
1.3611
1.3457
1.2243
1.2716
1.1615
1.1838
1.1664
Theta
0.4377
0.4312
0.4258
0.3834
0.3999
0.3615
0.3693
0.3632
Average
1.3709
1.3391
1.3170
1.3211
1.2857
1.2285
1.1927
1.2030
1.3586
1.3508
1.3202
1.3051
1.2825
1.2254
1.1892
1.1861
Theta
0.4303
0.4276
0.4169
0.4116
0.4037
0.3838
0.3712
0.3701
MI
N
1.4050
1.3646
1.3289
1.3108
1.2889
1.2372
1.2140
1.1694
S
Average
1.3894
1.3496
1.3201
1.3104
1.2930
1.2444
1.2051
1.2211
1.3972
1.3571
1.3245
1.3106
1.2910
1.2408
1.2096
1.1953
Theta
0.4438
0.4298
0.4184
0.4136
0.4067
0.3892
0.3783
0.3733
3-13-96
MI
3-13-96
FL
Depth (cm) N
1.3879
0-20
1.3548
20-40
1.3489
40-60
1.3311
60-90
1.3161
90-120
120-150
150-180
180-210
S
2-28-96
2-28-96
FL
120-150
150-180
180-210
2-14-96
1.2604
1.1915
1.1875
S
Average
1.3524
1.3382
1.3400
1.1792
1.2089
1.3702
1.3465
1.3445
1.2552
1.2625
1.1528
1.1960
1.0451
1.2005
1.1607
1.1741
Theta
0.4344
0.4261
0.4254
0.3942
0.3968
0.3584
0.3735
0.3659
N
1.3381
1.3302
1.3374
1.2974
1.2924
1.2211
1.2094
1.1636
S
Average
1.3542
1.3412
1.3258
1.3029
1.2936
1.2226
1.2006
1.2251
1.3462
1.3357
1.3316
1.3002
1.2930
1.2219
1.2050
1.1944
Theta
0.4260
0.4223
0.4209
0.4099
0.4074
0.3826
0.3767
0.3730
PB
N
1.1864
1.1799
1.1794
1.1860
1.0175
1.0656
1.0444
1.0642
S
Average
1.1810
1.2116
1.1962
1.1999
1.1648
1.1735
1.1044
1.0620
1.1837
1.1958
1.1878
1.1930
1.0912
1.1196
1.0744
1.0631
2-28-96
PB
N
S
Average
1.1801
1.1753
1.1822
1.1642
1.0281
1.0693
1.0625
1.0570
1.2176
1.2403
1.2161
1.2065
1.1470
1.1664
1.1094
1.0471
1.1989
1.2078
1.1992
1.1854
1.0876
1.1179
1.0860
1.0521
3-13-96
PB
N
S
Average
1.1952
1.1753
1.1764
1.1568
1.0370
1.0528
1.0593
1.0824
1.1854
1.2053
1.1986
1.1907
1.1644
1.1744
1.0975
1.0706
1.1903
1.1903
1.1875
1.1738
1.1007
1.1136
1.0784
1.0765
Theta
0.3692
0.3735
0.3707
0.3725
0.3369
0.3468
0.3311
0.3271
Theta
0.3745
0.3777
0.3746
0.3698
0.3357
0.3463
0.3351
0.3233
Theta
0.3716
0.3716
0.3706
0.3658
0.3403
0.3448
0.3325
0.3318
Table D-3. Medford Station soil water data (continued).
4-04-96
4-04-96
MI
FL
N
S
Average Theta
Depth (cm) N
1.3984
1.3544
1.3764
0.4365
1.3560
0-20
1.3556
1.3499
0.4273
1.3665
20-40
1.3442
0.4274
1.3435
40-60
1.3493
1.3511
1.3502
1.2227
0.3828
1.3079
60-90
1.3204
1.1249
1.2855
1.2206
1.2768
0.4018
90-120
1.3330
0.3575
1.2330
1.2563
1.0438
1.1501
120-150
1.1985
1.1936
0.3727
1.2061
150-180
1.1886
0.3627
1.1597
1.1915
1.1384
1.1650
180-210
4-23-96
FL
Depth (cm) N
0-20
1.3814
1.3489
20-40
1.3308
40-60
1.3201
60-90
1.3225
90-120
1.2652
120-150
1.1841
150-180
180-210
1.1855
PB
S
Average
1.3647
1.3377
1.3055
1.2880
1.2965
1.2324
1.2202
1.2197
1.3604
1.3521
1.3245
1.2980
1.2910
1.2327
1.2132
1.1897
Theta
0.4309
0.4281
0.4184
0.4091
0.4067
0.3864
0.3795
0.3713
4-23-96
MI
S
Average
1.3390
1.3475
1.3203
1.1334
1.2140
1.0301
1.2011
1.1409
1.3602
1.3482
1.3256
1.2268
1.2683
1.1477
1.1926
1.1632
Theta
0.4309
0.4267
0.4188
0.3843
0.3988
0.3567
0.3724
0.3621
N
S
Average
1.2521
1.3187
1.3237
1.3170
1.2989
1.2155
1.2099
1.1670
1.3449
1.3250
1.3198
1.2970
1.2882
1.2223
1.2352
1.2235
1.2985
1.3219
1.3218
1.3070
1.2936
1.2189
1.2226
1.1953
Theta
0.4093
0.4175
0.4175
0.4123
0.4076
0.3815
0.3828
0.3733
1.1873
1.1700
Average
1.3205
1.3210
1.3287
1.1009
1.1404
1.0473
1.2027
1.1569
1.3334
1.3304
1.3334
1.2079
1.2318
1.1602
1.1950
1.1635
Theta
0.4215
0.4205
0.4215
0.3777
0.3860
0.3610
0.3732
0.3622
S
1.1952
1.2059
1.1657
1.1708
1.0266
1.0528
1.0552
1.0722
1.1884
1.2202
Average
1.1918
1.2231
1.2042
1.1550
1.1702
1.0998
1.0653
1.2131
1.1944
1.1875
1.0908
1.1115
1.0775
1.0688
S
Average
1.1209
1.1756
1.2114
1.1921
1.1588
1.1696
1.0867
1.0721
1.1638
1.1805
1.1978
1.1741
1.0943
1.1094
1.0728
1.0680
S
Average
1.0960
1.1705
1.1788
1.1884
1.1613
1.1644
1.0924
1.0514
1.1364
1.1803
1.1751
1.1789
1.0913
1.1092
1.0722
Theta
0.3721
0.3795
0.3730
0.3706
0.3368
0.3440
0.3322
0.3291
PB
N
1.2066
1.1853
1.1841
1.1560
1.0298
1.0492
1.0588
1.0638
Theta
0.3623
0.3681
0.3742
0.3659
0.3380
0.3433
0.3305
0.3288
5-03-96
PB
MI
Depth (cm) N
1.3462
0-20
1.3398
20-40
1.3380
40-60
1.3149
60-90
1.3232
90-120
1.2731
120-150
N
4-23-96
5-03-96
5-03-96
FL
150-180
180-210
4-04-96
N
S
Average
1.2077
1.2985
1.3165
1.3089
1.2783
1.2079
1.1971
1.1630
1.3302
1.3310
1.3196
1.2917
1.2941
1.2282
1.2185
1.2185
1.2690
1.3148
1.3181
1.3003
1.2862
1.2181
1.2078
1.1908
Theta
0.3990
0.4150
0.4162
0.4100
0.4050
0.3812
0.3777
0.3717
N
1.1767
1.1901
1.1714
1.1693
1.0213
1.0540
1.0519
1.0667
1.0591
Theta
0.3527
0.3681
0.3662
0.3676
0.3370
0.3432
0.3303
0.3257
Table D-3. Medford Station soil water data (continued).
5-28-96
5-28-96
FL
Depth (cm) N
0-20
1.3710
20-40
1.3203
1.2974
40-60
1.3003
60-90
1.3224
90-120
120-150
150-180
180-210
1.2621
1.1853
1.1851
S
Average
1.3409
1.3285
1.3205
1.0744
1.0887
1.3560
1.3244
1.3090
1.1874
1.2056
1.1199
1.1882
1.1771
0.9777
1.1910
1.1690
Theta
0.4294
0.4184
0.4130
0.3705
0.3769
0.3470
0.3708
0.3669
5-28-96
S
Average
1.3455
1.3189
1.2814
1.2742
1.2684
1.2176
1.1355
1.2203
1.3117
1.3128
1.2986
1.2765
1.2779
1.2203
1.1727
1.1918
Theta
0.4139
0.4143
0.4094
0.4016
0.4021
0.3820
0.3654
0.3721
Depth (cm) N
1.1241
0-20
1.1752
20-40
1.2340
40-60
1.2666
60-90
1.3120
90-120
1.2457
120-150
1.1325
150-180
1.1884
180-210
6-25-96
FL
Depth (cm) N
0-20
1.3712
1.3350
20-40
1.3174
40-60
1.2819
60-90
1.3050
90-120
1.2273
120-150
1.1675
150-180
1.1759
S
Average
1.1011
1.2602
1.2839
1.0870
1.0677
1.1126
1.2177
1.2590
1.1768
1.1899
1.1067
1.1040
1.1768
0.9677
1.0755
1.1651
Theta
0.3444
0.3811
0.3955
0.3668
0.3714
0.3424
0.3414
0.3668
MI
N
1.1305
1.2042
1.2369
1.2455
1.2699
1.2006
1.1523
1.1543
S
Average
1.1610
1.2374
1.2703
1.2579
1.2691
1.1864
1.0851
1.1016
1.1458
1.2208
1.2536
1.2517
1.2695
1.1935
1.1187
1.1280
Theta
0.3560
0.3822
0.3937
0.3930
0.3992
0.3727
0.3466
0.3498
Average
1.3555
1.3369
1.3389
1.1060
1.0936
1.0445
1.1900
1.1672
1.3634
1.3360
1.3282
1.1940
1.1993
1.1359
1.1788
1.1716
Theta
0.4320
0.4224
0.4197
0.3728
0.3747
0.3526
0.3675
0.3650
MI
N
1.1621
1.1475
1.1467
1.2155
1.2578
1.1830
1.1540
1.1388
S
Average
1.1278
1.1433
1.1380
1.1552
1.1087
1.1491
1.1033
1.0572
1.1505
1.1586
1.1487
1.1545
1.0671
1.1030
1.0855
1.0641
S
Average
0.9788
1.0149
1.0358
1.0979
1.0824
1.0249
1.0704
1.0570
1.0394
1.0600
1.0838
1.1258
1.0451
1.0352
1.0541
1.0591
S
Average
1.1268
1.0534
1.0193
1.0787
1.0658
1.0456
1.0400
1.0817
1.1697
1.1186
1.0951
1.1201
1.0441
1.0267
1.0324
1.0719
Theta
0.3577
0.3605
0.3570
0.3590
0.3285
0.3411
0.3349
0.3275
PB
N
1.0999
1.1050
1.1317
1.1536
1.0077
1.0454
1.0377
1.0612
Theta
0.3188
0.3260
0.3343
0.3490
0.3208
0.3174
0.3240
0.3257
6-25-96
6-25-96
S
PB
N
1.1732
1.1739
1.1593
1.1537
1.0254
1.0568
1.0676
1.0710
6-17-96
6-17-96
6-17-96
FL
180-210
MI
N
1.2778
1.3066
1.3158
1.2787
1.2873
1.2229
1.2099
1.1633
S
Average
1.3351
1.2889
1.2908
1.2661
1.2594
1.2027
1.0882
1.0946
1.2486
1.2182
1.2188
1.2408
1.2586
1.1929
1.1211
1.1167
Theta
0.3919
0.3813
0.3815
0.3892
0.3954
0.3724
0.3474
0.3459
PB
N
1.2126
1.1838
1.1709
1.1615
1.0223
1.0078
1.0247
1.0621
Theta
0.3644
0.3465
0.3383
0.3470
0.3205
0.3144
0.3164
0.3302
Table D-3. Medford Station soil water data (continued).
7-19-96
FL
Depth
0-20
20-40
40-60
60-90
90-120
120-150
150-180
180-210
N
1.2743
1.2657
1.2821
1.2832
1.2681
1.2266
1.1138
1.1362
7-30-96
FL
Depth
N
0-20
1.4015
20-40
1.3639
40-60
1.3515
1.3081
60-90
90-120
1.3000
120-150 1.2117
150-180 1.1125
180-210 1.1538
MN
1.3171
1.3015
1.2532
1.2880
1.2528
MS
1.2367
1.2969
1.2451
1.2300
S
Average
1.2808
1.3100
1.3051
1.0837
1.0680
1.2772
1.2935
1.2714
1.2212
1.1963
1,1031
1.0924
1.1368
0.9796
1.0709
1.1374
MN
1.4180
1.3752
1.3392
1.3153
1.3255
MS
1.3576
1.3344
1.3175
1.3053
S
Average
1.3734
1.3728
1.3439
1.1604
1.2103
1.0480
1.1889
1.1889
1.3876
1.3616
1.3380
1.2723
1.2786
1.1299
1.1507
1.1714
7-19-96
Theta
0.4019
0.4076
0.3999
0.3824
0.3736
0.3411
0.3373
0.3529
Theta
0.4405
0.4314
0.4231
0.4002
0.4024
0.3504
0.3577
0.3649
8-06-96
FL
Depth
0-20
20-40
40-60
60-90
90-120
120-150
150-180
180-210
N
1.3589
1.3490
1.3142
1.2833
1.2675
1.2169
1.1421
1.1804
MN
1.3737
1.3424
1.3256
1.3104
1.3082
MS
1.3147
1.3335
1.3066
1.2902
Average
1.3374
1.3528
1.3361
1.0842
1.0829
1.0311
1.1963
1.2020
1.3462
1.3444
1.3206
1.2420
1.2195
1.1240
1.1692
1.1912
Theta
0.4260
0.4254
0.4171
0.3896
0.3818
0.3484
0.3642
0.3719
MI
Depth
0-20
20-40
40-60
60-90
90-120
120-150
150-180
180-210
7-30-96
MI
Depth
0-20
20-40
40-60
60-90
90-120
120-150
150-180
180-210
8-06-96
MI
Depth
0-20
20-40
40-60
60-90
90-120
120-150
150-180
180-210
NN
1.1874
1.1268
1.0518
1.0209
0.9613
NN
1.1940
1.1572
1.0647
1.0121
0.9513
NN
1.0577
1.0764
1.0456
1.0169
0.9455
N
1.3360
1.3338
1.2908
1.2708
1.2390
1.1758
1.1556
1.1793
MS
1.3309
1.3396
1.3289
1.3115
1.3035
S
Average
1.3510
1.3295
1.2960
1.2215
1.2378
1.1932
1.0633
1.1094
1.3393
1.3343
1.3052
1.2679
1.2601
1.1845
1.1095
1.1444
N
1.4118
1.3612
1.3122
1.2856
1.2447
1.2009
1.1945
MS
1.3913
1.3423
1.3594
1.3254
1.3469
S
Average
1.3740
1.3270
1.3263
1.2033
1.2297
1.2212
1.0867
1.3924
1.3435
1.3326
1.2714
1.2738
1.2111
1.1406
N
1.2648
1.2780
1.2573
1.2291
1.2480
1.2006
1.1568
MS
1.3172
1.3218
1.3261
1.3189
1.3581
S
Average
1.2548
1.2834
1.2778
1.1972
1.2219
1.1996
1.0881
1.2789
1.2944
1.2871
1.2484
1.2760
1.2001
1.1225
Theta
0.4236
0.4218
0.4117
0.3987
0.3959
0.3695
0.3433
0.3555
Theta
0.4421
0.4251
0.4213
0.3999
0.4007
0.3788
0.3542
Theta
0.4025
0.4079
0.4053
0.3918
0.4015
0.3750
0.3479
Table D-3. Medford Station soil water data (continued)
8-08-96
FL
Depth
N
0-20
1.3457
20-40
1.3230
1.2930
40-60
60-90
1.2667
90-120
1.2903
120-150 1.2372
150-180 1.1257
180-210 1.1824
MS
MN
1.3569 1.2859
1.3606 1.3118
1.3141 1.2863
1.3103 1.2854
1.3074
S
Average
1.3181
1.3306
1.3196
1.0930
1.0755
1.3267
1.3315
1.3033
1.2389
1.2244
1.1084
1.1523
1.1829
0.9796
1.1789
1.1833
8-08-96
Theta
0.4192
0.4209
0.4110
0.3885
0.3835
0.3430
0.3583
0.3690
8-13-96
FL
Depth
0-20
20-40
40-60
60-90
90-120
120-150
150-180
180-210
N
1.2897
1.2769
1.2453
1.2438
1.2742
1.2179
1.1289
1.1361
MN
1.3052
1.3158
1.3014
1.2776
1.2886
MS
1.2343
1.3041
1.2803
1.2386
Average
1.2680
1.3032
1.3001
1.0793
1.0829
0.9646
1.0730
1.1194
1.2743
1.3000
1.2818
1.2098
1.2152
1.0913
1.1010
1.1278
Theta
0.4009
0.4099
0.4035
0.3784
0.3803
0.3370
0.3404
0.3497
20-40
40-60
60-90
90-120
120-150
150-180
180-210
8-13-96
MI
Depth
0-20
20-40
40-60
60-90
90-120
120-150
150-180
180-210
NN
1.0407
1.0370
1.0283
1.0092
0.9495
NN
1.1084
0.9884
1.0195
1.0165
0.9524
N
1.2244
MS
1.2998
1.3200
1.3038
1.2983
1.3407
S
Average
1.1796
1.2444
1.2609
1.2042
1.2197
1.1974
1.0650
1.2346
1.2752
1.2683
1.2431
1.2627
1.1872
1.1134
N
1.3126
1.2936
1.2708
1.2329
1.2336
1.1848
1.1608
1.1255
MS
1.3493
1.3145
1.3145
1.2822
1.2824
S
Average
1.3160
1.2976
1.2693
1.1911
1.2183
1.1946
1.0732
1.0893
1.3260
1.3019
1.2849
1.2354
1.2448
1.1897
1.1170
1.1074
N
1.3213
1.3103
1.2792
1.2562
1.2369
1.1804
1.1593
1.1057
MS
1.3457
1.3281
1.3222
1.2948
1.2930
S
Average
1.3267
1.3141
1.2608
1.1912
1.2214
1.1877
1.0721
1.0823
1.3312
1.3175
1.2874
1.2474
1.2504
1.1841
1.1157
1.0940
1.2611
1.2403
1.2267
1.2277
1.1770
1.1618
Theta
0.3870
0.4012
0.3988
0.3900
0.3968
0.3705
0.3447
Theta
0.4189
0.4105
0.4046
0.3873
0.3906
0.3713
0.3460
0.3426
8-16-96
8-16-96
FL
Depth
0-20
MI
Depth
0-20
MI
N
1.2271
1.2221
20-40
1.1980
40-60
60-90
1.2216
1.2556
90-120
120-150 1.2172
150-180 1.1208
180-210 1.1237
MN
MS
1.2778 1.1925
1.3187 1.2926
1.2926 1.2497
1.2602 1.2300
1.2774
Average
1.2290
1.2771
1.3099
1.0838
1.0802
1.9876
1.0763
1.0951
1.2316
1.2776
1.2626
1.1989
1.2044
1.6024
1.0986
1.1094
Theta
0.3860
0.4020
0.3968
0.3746
0.3765
0.5155
0.3395
0.3433
Depth
0-20
20-40
40-60
60-90
90-120
120-150
150-180
180-210
NN
1.1430
1.1160
1.0839
0.9988
0.9434
Theta
0.4208
0.4160
0.4055
0.3915
0.3926
0.3694
0.3455
0.3379
Table D-3. Medford Station soil water data (continued).
8-19-96
FL
Depth
N
MN
MS
0-20
1.1815 1.2520 1.1598
20-40
1.1822 1.2917 1.2769
40-60
1.1731 1.2787 1.2269
1.2122 1.2555 1.2051
60-90
90-120
1.2436 1.2648
120-150 1.2019
150-180 1.1281
180-210 1.1209
8-19-96
MI
S
Average
1.2033
1.2583
1.3163
1.0698
1.0554
0.9741
1.0719
1.1079
1.1992
1.2523
1.2488
1.1857
1.1879
1.0880
1.1000
1.1144
Theta
0.3746
0.3932
0.3920
0.3699
0.3707
0.3358
0.3400
0.3450
Depth
0-20
20-40
40-60
60-90
90-120
120-150
150-180
180-210
Theta
0.4292
0.4245
0.4200
0.3954
0.3954
0.3493
0.3606
0.3593
8-27-96
MI
Depth
0-20
20-40
40-60
60-90
90-120
120-150
150-180
180-210
8-29-96
FL
N
MN
MS
Depth
0-20
1.3677 1.3834 1.3252
20-40
1.3558 1.3406 1.3272
40-60
1.3424 1.3467 1.2910
60-90
1.2947 1.3186 1.3018
1.2652 1.2978
90-120
120-150 1.2141
150-180 1.1238
180-210 1.1675
S
Average
1.3450
1.3443
1.3360
1.1192
1.2132
1.0392
1.1942
1.1428
1.3553
1.3420
1.3290
1.2586
1.2587
1.1267
1.1590
1.1552
20-40
40-60
60-90
90-120
120-150
150-180
180-210
1.0573
1.0442
1.0561
1.0127
0.9471
NN
1.1493
1.1187
1.0622
1.0045
0.9424
N
1.2619
1.2487
1.2154
1.2092
1.2051
1.1572
1.1499
1.1218
MS
S
Average
1.3451
1.3124
1.3056
1.2850
1.2740
1.2714
1.2621
1.2585
1.1955
1.2107
1.1942
1.0869
1.0702
1.2928
1.2744
1.2598
1.2299
1.2299
1.1757
1.1184
1.0960
N
1.3339
1.3171
1.3168
1.2650
1.2239
1.1685
1.1633
1.1056
MS
1.3740
1.3164
1.3398
1.2972
1.2950
S
Average
1.3625
1.3334
1.2684
1.1884
1.2201
1.1904
1.0872
1.0835
1.3568
1.3223
1.3083
1.2502
1.2463
1.1795
1.1253
1.0946
N
1.3202
1.3023
1.2991
1.2677
1.2070
1.1568
1.1615
1.1120
MS
1.3728
1.3434
1.3240
1.2894
1.2848
S
Average
Theta
1.3290
1.3118
1.2626
1.1792
1.2183
1.1830
1.0678
1.0835
1.3407
1.3192
1.2952
1.2454
1.2367
1.1699
1.1147
1.0978
0.4241
0.4166
0.4082
0.3908
0.3878
0.3644
0.3451
0.3392
Theta
0.4073
0.4009
0.3958
0.3854
0.3854
0.3665
0.3464
0.3386
Theta
0.4297
0.4176
0.4128
0.3925
0.3911
0.3678
0.3488
0.3381
9-03-96
9-03-96
FL
Depth
0-20
NN
N
1.3336
1.3160
1.3017
1.2608
1.2870
1.1920
1.1069
1.1332
MN
1.3464
1.3396
1.3262
1.2983
1.2788
MS
1.2794
1.3205
1.2736
1.2861
S
Average
1.3034
1.3281
1.3145
1.0851
1.0750
1.3157
1.3261
1.3040
1.2326
1.2136
1.0850
1.0779
1.1278
0.9779
1.0489
1.1224
Theta
0.4153
0.4190
0.4113
0.3863
0.3797
0.3348
0.3323
0.3497
MI
Depth
0-20
20-40
40-60
60-90
90-120
120-150
150-180
180-210
NN
1.0036
1.0004
1.0122
1.0009
0.9441
Table D-3. Medford Station soil water data (continued).
9-10-96
FL
N
MN
MS
Depth
0-20
1.2714 1.2638 1.2091
1.2808 1.2936 1.2972
20-40
1.2440 1.2852 1.2651
40-60
1.2420 1.2596 1.2390
60-90
1.2545 1.2688
90-120
120-150 1.2004
150-180 1.0921
180-210 1.1316
9-17-96
FL
MN
MS
N
Depth
0-20
1.2891 1.2661 1.1593
1.2099 1.2868 1.2508
20-40
40-60
1.2170 1.2569 1.2374
1.2185 1.2556 1.2140
60-90
1.2509 1.2688
90-120
120-150 1.2039
150-180 1.1065
180-210 1.1210
S
Average
1.2616
1.2818
1.3000
1.0679
1.0646
0.9811
1.0584
1.1065
1.2515
1.2884
1.2736
1.2021
1.1960
1.0908
1.0753
1.1191
S
1.2432
1.2644
1.2879
1.0664
1.0709
0.9732
1.0676
1.1000
Average
1.2394
1.2530
1.2498
1.1886
1.1969
1.0886
1.0871
1.1105
Theta
0.3929
0.4058
0.4006
0.3757
0.3735
0.3368
0.3314
0.3467
9-10-96
MI
Depth
0-20
20-40
40-60
60-90
90-120
120-150
150-180
180-210
Theta
0.3887
0.3934
0.3923
0.3710
0.3738
0.3360
0.3355
0.3437
9-17-96
MI
Depth
0-20
20-40
40-60
60-90
90-120
120-150
150-180
180-210
9-30-96
FL
Depth
0-20
N
MN
1.3028 1.2824
1.3245 1.3250
1.3103 1.2777
1.0827 1.2721
1.0727
20-40
40-60
60-90
90-120
120-150 0.9798
150-180 1.1810
180-210 1.1144
MS
1.3400
1.3212
1.3111
1.3086
1.2805
Average
1.3387
1.3429
1.2900
1.2361
1.2170
1.1797
1.1172
1.1356
1.3160
1.3284
1.2973
1.2249
1.1901
1.0798
1.1491
1.1250
Theta
0.4154
0.4198
0.4089
0.3836
0.3715
0.3329
0.:3.5"7-2
0.3488
9-30-96
MI
Depth
0-20
20-40
40-60
60-90
90-120
120-150
150-180
180-210
NN
0.9598
0.9938
1.0001
0.9939
0.9365
NN
1.0125
0.9692
0.9872
0.9688
0.9413
NN
0.9340
0.9386
0.9740
0.9884
0.9464
N
1.2929
1.2590
1.2293
1.1822
1.1736
1.1410
1.1648
1.1062
MS
1.3735
1.3312
1.3151
1.2748
1.2932
S
Average
1.3289
1.3143
1.2446
1.1689
1.1880
1.1853
1.0548
1.0861
1.3318
1.3015
1.2630
1.2086
1.2183
1.1632
1.1098
1.0962
N
1.2130
1.1812
1.1658
1.1345
1.1274
1.1358
1.1419
1.1098
MS
1.3504
1.3227
1.2946
1.2792
1.2468
S
Average
1.2824
N
1.1478
1.1446
1.0994
1.0605
1.1038
1.0989
1.1436
1.0851
MS
1.3092
1.2971
1.2771
1.2547
1.2336
1.2837
1.2223
1.2285
1.1812
1.2027
1.1882
1.0755
1.0744
1.2421
1.2296
1.1983
1.1923
1.1620
1.1087
1.0921
S
Average
1.2269
1.2358
1.2369
1.1756
1.1852
1.1781
1.0672
1.0777
1.2280
1.2258
1.2045
1.1636
1.1742
1.1385
1.1054
1.0814
Theta
0.4210
0.4104
0.3969
0.3780
0.3813
0.3621
0.3434
0.3387
Theta
0.4037
0.3896
0.3853
0.3743
0.3723
0.3617
0.3431
0.3373
Theta
0.3847
0.3840
0.3765
0.3622
0.3659
0.3535
0.3419
0.3335
Table D-3. Medford Station soil water data (continued).
10-29-96
FL
Average
S
MS
N
MN
Depth
1.3495
1.3502
0-20
1.3681 1.3666 1.3165
1.3392
1.3478
20-40
1.3464 1.3373 1.3252
1.2323 1.3146 1.2919
1.3175
1.2891
40-60
1.1064
1.2067
1.1861 1.2841 1.2501
60-90
1.0805
1.1941
90-120
1.2228 1.2790
0.9712 1.0651
120-150 1.1590
1.0678
1.0856
150-180 1.1034
180-210
12-16-96
FL
Depth
0-20
20-40
40-60
60-90
90-120
120-150
150-180
180-210
1.1260
MS
N
MN
1.3767 1.4026 1.3386
1.3603 1.3650 1.3295
1.3611 1.3389 1.3171
1.3143 1.3183 1.3024
1.2257 1.3255
1.1635
1.0908
1.1428
1-16-97
FL
MS
MN
N
Depth
1.3610 1.3672 1.3102
0-20
1.3455 1.3550 1.3255
20-40
1.3456 1.3472 1.3234
40-60
1.3181 1.3434 1.3057
60-90
1.3157 1.3652
90-120
120-150 1.2397
150-180 1.1899
180-210 1.1923
1.1001
1.1131
Theta
0.4274
0.4235
0.4060
0.3773
0.3729
0.3278
0.3350
0.3446
S
Average
Theta
1.3941
1.3726
1.3461
1.1171
1.0626
0.9671
1.1646
1.1736
1.3780
1.3569
1.3408
1.2630
1.2046
1.0653
1.1277
1.1582
0.4371
0.4297
0.4241
0.3969
0.3765
0.3279
0.3497
0.3603
S
Average
1.3418
1.3467
1.3241
1.0950
1.0690
1.3451
1.3432
1.3351
1.2656
1.2500
1.1095
1.1880
1.2493
0.9792
1.1861
1.3063
Theta
0.4256
0.4249
0.4221
0.3978
0.3924
0.3433
0.3707
0.3922
10-29-96
MI
Depth
0-20
20-40
40-60
60-90
90-120
120-150
150-180
180-210
12-16-96
MI
Depth
0-20
20-40
40-60
60-90
90-120
120-150
150-180
180-210
1-16-97
MI
Depth
0-20
20-40
40-60
60-90
90-120
120-150
150-180
180-210
NN
1.1493
1.0811
0.9782
0.9788
0.9440
NN
1.2088
1.1596
1.1633
1.1557
0.9916
NN
1.1673
1.1623
1.1675
1.1484
1.0294
S
1.3151
1.2731
1.1569
1.1439
1.1867
1.1310
1.0753
1.0622
Average
MS
1.3654
1.3647
1.3425
1.3185
1.3324
S
Average
1.3724
1.3563
1.3336
1.3048
1.2522
1.1687
1.0679
1.0970
1.3618
1.3607
1.3358
1.3099
1.2688
1.1531
1.1142
1.1149
MS
1.3399
1.3236
S
Average
1.3490
1.3360
1.3241
1.3034
1.2915
1.2151
1.1078
1.2392
1.3359
1.3265
1.3239
1.3156
1.3070
1.2105
1.1466
1.2030
N
1.2904
1.2482
1.0582
1.0356
1.0988
1.0846
1.1210
1.0729
MS
N
1.3475
1.3612
1.3313
1.3065
1.2219
1.1374
1.1604
1.1327
N
1.3188
1.3198
1.3084
1.3014
1.2975
1.2058
1.1853
1.1668
1.3531
1.2788
1.2662
1.2205
1.1884
1.3391
1.3421
1.3320
1.3195
1.2667
1.1604
1.1333
1.1580
1.1078
1.0982
1.0676
Theta
0.4167
0.3982
0.3611
0.3517
0.3603
0.3427
0.3394
0.3287
Theta
0.4314
0.4311
0.4224
0.4133
0.3990
0.3585
0.3450
0.3452
Theta
0.4224
0.4191
0.4182
0.4153
0.4123
0.3786
0.3563
0.3760
Table D-3. Medford Station soil water data (continued).
3-18-97
FL
Depth
0-20
20-40
40-60
60-90
90-120
120-150
150-180
180-210
N
1.3716
1.3600
1.3382
1.3200
1.3258
1.2488
1.1710
1.1839
MN
1.3762
1.3741
1.3556
1.3410
1.3647
MS
1.3094
1.3370
1.3203
1.3390
S
Average
1.3399
1.3389
1.3378
1.1210
1.1964
1.0342
1.1920
1.3841
1.3493
1.3525
1.3380
1.2803
1.2956
1.1415
1.1815
1.2840
3-18-97
Theta
0.4271
0.4282
0.4231
0.4030
0.4083
0.3545
0.3685
0.4043
MI
Depth
0-20
20-40
40-60
60-90
90-120
120-150
150-180
180-210
NN
1.1952
1.1820
1.1550
1.1518
1.1066
N
1.3322
1.3587
1.3453
1.3198
1.2991
1.2182
1.2050
1.1686
MS
1.3714
1.3499
1.3510
1.3476
1.3515
S
Average
1.3625
1.3445
1.3297
1.2936
1.2958
1.2297
1.2424
1.2419
1.3554
1.3510
1.3420
1.3203
1.3155
1.2240
1.2237
1.2053
Theta
0.4292
0.4277
0.4245
0.4170
0.4153
0.3833
0.3832
0.3768
Table D-3. Medford Station soil water data (continued).
7-19-96
7-19-96
PA
PB
Depth
0-20
20-40
40-60
60-90
90-120
120-150
150-180
180-210
E
0.9384
0.9144
0.9563
1.0413
0.9952
W
1.0856
1.0763
1.0957
1.1202
1.0409
Average
1.0120
0.9954
1.0260
1.0808
1.0181
Theta
0.3093
0.3035
0.3142
0.3333
0.3114
N
1.1316
1.0698
1.1485
1.1801
1.1667
1.0711
1.1261
0.9961
1.0286
1.0247
1.0480
MS
0.9728
0.9150
0.9081
0.9691
1.0303
1.0837
S
Average
0.9437
0.9556
0.9577
0.9817
1.0523
1.0168
1.0214
1.0643
1.0542
1.0473
1.0258
1.0480
1.0237
1.0295
1.0268
Theta
0.3234
0.3110
0.3126
0.3275
0.3240
0.3216
0.3141
0.3219
PB
E
1.2457
1.1822
1.1832
1.1669
1.1060
W
1.2123
1.2073
1.2040
1.1738
1.0796
Average
1.2290
1.1948
1.1936
1.1704
1.0928
Theta
0.3851
0.3731
0.3727
0.3646
0.3375
Depth
0-20
20-40
40-60
60-90
90-120
120-150
150-180
180-210
NN
1.3606
1.3225
1.3039
1.2710
1.2010
N
1.1881
1.1860
1.1729
1.1729
1.0280
1.0233
1.0667
MS
1.2221
NN
1.2360
1.2664
N
1.1506
1.1649
1.1722
1.1646
MS
1.0509
1.1071
1.1150
1.1347
1.1171
1.1851
1.1785
1.1498
1.1646
S
Average
1.2570
1.2381
1.1759
1.1967
1.1732
1.1720
1.1189
1.2224
1.2031
1.1758
1.1731
1.1219
1.0977
1.0928
S
Average
1.0970
1.0994
1.1040
1.1285
1.0799
1.0299
1.0649
1.0995
1.1238
1.1304
1.1426
1.0704
1.0300
1.0440
Theta
0.3828
0.3760
0.3665
0.3656
0.3477
0.3392
0.3375
8-06-96
8-06-96
PB
PA
Depth
0-20
20-40
40-60
60-90
90-120
120-150
150-180
180-210
NN
1.1612
1.1269
7-30-96
7-30-96
PA
Depth
0-20
20-40
40-60
60-90
90-120
120-150
150-180
180-210
Depth
0-20
20-40
40-60
60-90
90-120
120-150
150-180
180-210
E
1.0595
1.0960
1.1143
1.1563
1.0800
W
1.1265
1.1558
1.1763
1.1548
1.0755
Average
1.0930
1.1259
1.1453
1.1556
1.0778
Theta
0.3376
0.3491
0.3558
0.3594
0.3323
Depth
0-20
20-40
40-60
60-90
90-120
120-150
150-180
180-210
1.2531
1.2552
1.0141
1.0301
1.0231
Theta
0.3398
0.3483
0.3506
0.3549
0.3297
0.3156
0.3205
Table D-3. Medford Station soil water data (continued).
8-08-96
PA
E
W
Average
Theta
Depth
1.0104
1.1104
1.0604
0.3262
0-20
20-40
1.0642
1.1385
1.1014
0.3405
40-60
1.1073
1.1547
1.1310
0.3508
1.1587
1.1557
1.1616
0.3605
60-90
0.3260
1.0626
1.0572
1.0599
90-120
120-150
150-180
180-210
8-13-96
PA
Depth
0-20
20-40
40-60
60-90
90-120
120-150
150-180
NN
1.2188
1.2650
1.2607
1.2462
N
1.1451
1.1461
1.1621
1.1572
1.0117
1.0103
1.0354
MS
1.0336
1.0655
1.0915
1.1233
1.1096
S
Average
1.0619
1.0887
1.0750
1.1197
1.0692
1.0399
1.0437
1.0802
1.1001
1.1095
1.1334
1.0635
Average
1.1286
1.0251
1.0396
Theta
0.3331
0.3401
0.3433
0.3517
0.3273
0.3139
0.3189
8-13-96
PB
E
1.1006
1.0653
1.0796
1.1404
1.0355
1.0908
W
1.1484
1.1645
1.1527
1.1603
1.0676
1.1431
Average
1.1245
1.1149
1.1162
1.1504
1.0516
1.1170
Theta
0.3486
0.3452
0.3457
0.3576
0.3231
0.3459
180-210
Depth
0-20
20-40
40-60
60-90
90-120
120-150
150-180
180-210
NN
1.1570
1.2139
1.2219
1.2137
1.1671
N
1.1867
1.1752
1.1625
1.1633
1.0111
1.0263
1.0188
1.0531
MS
1.0052
1.0206
1.0297
1.1098
1.0889
1.0884
S
N
1.1568
1.1601
1.1556
1.1563
1.0074
1.0246
MS
1.0690
1.1294
1.0864
1.0864
1.0775
1.0875
S
Average
1.1728
1.1694
1.1610
1.1687
1.1001
1.0644
1.0458
1.0299
1.1334
1.1634
1.1498
1.1526
1.0855
1.0445
1.0315
1.0446
1.1656
1.1758
1.1488
1.1503
1.0843
1.0471
1.0496
1.0122
1.1464
1.1407
1.1593
1.0879
1.0367
1.0342
1.0327
Theta
0.3500
0.3562
0.3542
0.3607
0.3358
0.3179
0.3170
0.3165
8-16-96
8-16-96
PA
Depth
0-20
20-40
40-60
60-90
90-120
120-150
150-180
180-210
8-08-96
PB
Depth
0-20
20-40
40-60
60-90
90-120
120-150
150-180
180-210
E
1.0381
1.0289
1.0507
1.1240
1.0424
1.0843
W
Average
1.1429
1.1476
1.1255
1.1433
1.0656
1.1403
1.0905
1.0883
1.0881
1.1337
1.0540
1.1123
Theta
0.3367
0.3359
0.3359
0.3518
0.3240
0.3443
PB
Depth
0-20
20-40
40-60
60-90
90-120
120-150
150-180
180-210
NN
1.1350
1.1945
1.1961
1.1988
1.1569
11
.Vn
.1
/in4
1.0593
Theta
0.3517
0.3621
0.3574
0.3584
0.3349
0.3206
0.3161
0.3207
Table D-3. Medford Station soil water data (continued).
8-19-96
PA
Depth
0-20
20-40
40-60
60-90
90-120
120-150
150-180
180-210
E
0.9809
1.0006
1.0267
1.1249
1.0292
1.0950
W
1.1179
1.1250
1.1582
1.1282
1.0516
1.1243
Average
1.0494
1.0628
1.0925
1.1266
1.0404
1.1097
Theta
0.3224
0.3270
0.3374
0.3493
0.3192
0.3434
8-27-96
PA
Depth
0-20
20-40
40-60
60-90
90-120
120-150
150-180
180-210
8-19-96
PB
Depth
0-20
20-40
40-60
60-90
90-120
120-150
150-180
180-210
1.1203
1.1747
1.1837
1.2089
1.1478
N
1.1610
1.1459
1.1456
1.1372
1.0045
1.0187
1.0213
1.0438
MS
1.0692
1.1097
1.1221
1.1152
1.0864
1.0869
N
S
Average
1.1318
1.1373
1.1307
1.1335
1.0846
1.0363
1.0467
0.9853
1.1206
1.1419
1.1455
1.1487
1.0808
1.0275
1.0340
1.0146
MS
0.9706
1.0100
1.0084
1.0550
1.0572
1.0807
S
Average
1.0152
1.0327
1.0294
1.0651
1.0692
1.0353
1.0310
1.0020
1.0530
1.0784
1.0784
1.1145
1.0699
1.0222
1.0243
1.0304
MS
1.0541
1.0878
1.0952
1.1174
1.1085
1.0912
S
Average
1.0869
1.0705
1.1000
1.0920
1.1237
1.0975
1.0651
Theta
0.3472
0.3547
0.3559
0.3570
0.3333
0.3147
0.3170
0.3102
8-27-96
PB
E
0.9544
0.9659
1.0077
1.0786
1.0133
1.0761
W
1.0905
1.0840
1.1080
1.1020
1.0532
1.1455
Average
1.0225
1.0250
1.0579
1.0903
1.0333
1.1108
Theta
0.3129
0.3138
0.3253
0.3366
0.3167
0.3438
Depth
0-20
20-40
40-60
60-90
90-120
120-150
150-180
180-210
9-03-96
9-03-96
PA
Depth
0-20
20-40
PB
Depth
0-20
40-60
60-90
90-120
120-150
150-180
180-210
NN
E
W
0.9361
0.9543
1.0510
1.0531
1.0797
1.1188
1.0456
1.1330
0.9806
1.0510
1.0107
1.0986
Average
0.9936
1.0037
1.0302
1.0849
1.0282
1.1158
Theta
0.3028
0.3064
0.3156
0.3347
0.3149
0.3455
20-40
40-60
60-90
90-120
120-150
150-180
180-210
NN
1.0820
1.1353
1.1630
1.1952
1.1561
1.1441
1.1356
1.1129
1.1427
0.9972
1.0090
1.0176
1.0587
NN
1.2689
1.2531
1.2430
1.2378
1.1740
N
1.1775
1.1793
1.1748
1.1723
0.9997
1.0180
1.0321
1.0368
1.1121
1.0887
1.1300
1.0864
1.0390
1.0459
0.9823
0.5230
0.4912
Theta
0.3236
0.3325
0.3325
0.3451
0.3295
0.3128
0.3136
0.3157
Theta
0.3297
0.3400
0.3372
0.3483
0.3391
0.3278
0.1385
0.1274
Table D-3. Medford Station soil water data (continued).
9-10-96
PA
Depth
0-20
20-40
40-60
60-90
90-120
120-150
150-180
180-210
9-17-96
PA
Depth
0-20
20-40
40-60
60-90
90-120
120-150
150-180
180-210
E
0.9154
0.9397
0.9664
1.0420
0.9845
1.0829
W
1.0121
1.0359
1.0370
1.0939
1.0520
1.1202
Average
0.9638
0.9878
1.0017
1.0680
1.0183
1.1016
Theta
0.2924
0.3008
0.3057
0.3288
0.3115
0.3406
0-20
20-40
40-60
60-90
90-120
120-150
150-180
180-210
20-40
40-60
60-90
90-120
120-150
150-180
180-210
NN
1.1686
1.2233
1.2043
1.2284
1.1523
S
Average
1.0216
1.0361
1.0477
1.0584
1.0704
1.0418
1.0296
0.9969
1.0569
1.0651
1.0694
1.0935
1.0541
1.0517
0.6835
0.6789
S
Average
1.0454
1.0105
1.0335
1.0381
1.0330
1.0276
1.0333
0.9846
1.0632
1.0416
1.0515
1.0774
1.0295
1.0352
0.6801
MS
S
Average
0.9404
0.9477
0.9485
0.9569
0.9692
0.9865
1.0106
1.0195
1.0704
1.0029
1.0418
1.0096
1.0242
0.9797
1.0179
1.0391
1.0440
1.0728
1.0472
1.0059
1.0174
1.0147
N
1.1332
1.1531
1.1368
1.1393
1.0098
1.0087
1.0209
1.0397
MS
1.0160
1.0061
1.0236
1.0828
1.0822
1.1046
N
1.1498
1.1401
1.1319
1.1346
0.9917
1.0023
1.0071
1.0508
MS
0.9945
0.9741
0.9892
N
1.0941
1.1056
1.0983
1.1022
Theta
0.3250
0.3278
0.3293
0.3378
0.3240
0.3232
0.1946
0.1930
9-17-96
PB
E
0.9632
0.9295
0.9668
1.0106
0.9798
1.0962
W
1.0528
1.0290
1.0362
1.0749
1.0279
1.1285
Average
1.0080
0.9793
1.0015
1.0428
1.0039
1.1124
Theta
0.3079
0.2979
0.3056
0.3200
0.3064
0.3443
Depth
0-20
20-40
40-60
60-90
90-120
120-150
150-180
180-210
NN
1.1670
1.1821
1.1925
1.1877
1.1430
1.0595
1.0637
1.0757
0.6785
Theta
0.3272
0.3196
0.3231
0.3321
0.3154
0.3174
0.1934
0.1928
9-30-96
9-30-96
PA
Depth
9-10-96
PB
Depth
0-20
E
0.9069
0.9180
0.9327
0.9920
0.9413
1.0829
W
0.9471
0.9539
0.9826
1.0456
1.0334
1.1294
Average
0.9270
0.9360
0.9577
1.0188
0.9874
1.1062
Theta
0.2796
0.2827
0.2903
0.3117
0.3007
0.3422
PB
Depth
0-20
20-40
40-60
60-90
90-120
120-150
150-180
180-210
NN
1.0802
1.1338
1.1427
1.1756
1.1348
0.9927
1.0022
1.0106
1.0496
Theta
0.3114
0.3187
0.3205
0.3305
0.3216
0.3072
0.3112
0.3102
Table D-3. Medford Station soil water data (continued).
10-29-96
PA
Depth
0-20
20-40
40-60
60-90
90-120
120-150
150-180
180-210
12-16-96
PA
Depth
0-20
20-40
40-60
60-90
90-120
120-150
150-180
180-210
1-16-97
PA
Depth
0-20
20-40
40-60
60-90
90-120
120-150
150-180
180-210
E
1.0255
0.9648
0.9352
0.9704
0.9263
1.0620
E
1.1621
1.1986
1.1777
1.1792
1.1192
1.1186
W
1.1148
1.0101
0.9170
0.9766
1.0113
1.1129
W
1.1884
1.1795
1.1822
1.1664
1.1246
1.1855
Average
1.0702
0.9875
0.9261
0.9735
0.9688
1.0875
Average
1.1753
1.1891
1.1800
1.1728
1.1219
1.1521
Theta
0.3296
0.3007
0.2793
0.2958
0.2942
0.3356
Theta
0.3663
0.3711
0.3679
0.3654
0.3477
0.3582
10-29-96
PB
Depth
0-20
20-40
40-60
60-90
90-120
120-150
150-180
180-210
12-16-96
PB
Depth
0-20
20-40
40-60
60-90
90-120
120-150
150-180
180-210
S
Average
1.1104
1.0507
0.9695
0.9838
1.0016
0.9951
1.0251
1.1188
1.0506
1.0105
1.0080
0.9836
MS
1.1168
1.1852
1.1673
1.1673
1.1472
S
Average
1.1944
1.2039
1.1884
1.1792
1.1065
1.1663
1.1108
1.0688
1.1623
1.1891
1.1745
1.1670
1.0886
1.0922
1.0724
1.0659
MS
1.1111
1.1583
1.1832
1.1434
1.1654
S
Average
1.1764
1.1689
1.1702
1.1702
1.1495
1.1574
1.1050
1.0840
1.1521
1.1649
1.1757
1.1548
1.1152
1.0982
1.0727
1.0793
N
1.1600
1.1403
1.1197
1.0909
0.9752
0.9920
1.0226
MS
1.0861
0.9609
0.9424
0.9493
0.9740
NN
1.3501
1.3180
1.3162
1.2971
1.2523
N
1.1756
1.1781
1.1678
1.1545
1.0122
1.0181
1.0340
1.0630
NN
N
1.1689
1.1675
1.1736
1.1509
1.0308
1.0390
1.0404
1.0746
NN
1.2821
1.2226
1.1214
1.1330
1.1275
0.9936
1.0239
Theta
0.3466
0.3228
0.3088
0.3079
0.2994
0.3028
0.3134
Theta
0.3618
0.3711
0.3660
0.3634
0.3361
0.3373
0.3304
0.3281
1-16-97
PB
E
1.1126
1.1558
1.1626
1.1852
1.0973
1.1257
W
1.1728
1.1806
1.1997
1.1617
1.1215
1.1867
Average
1.1427
1.1682
1.1812
1.1735
1.1094
1.1562
Theta
0.3549
0.3638
0.3684
0.3657
0.3433
0.3596
Depth
0-20
20-40
40-60
60-90
90-120
120-150
150-180
180-210
1.3381
1.2933
1.3365
1.3007
Theta
0.3582
0.3627
0.3664
0.3592
0.3453
0.3394
0.3305
0.3328
Table D-3. Medford Station soil water data (continued).
3-18-97
PA
Depth
0-20
20-40
40-60
60-90
90-120
120-150
150-180
180-210
E
1.1454
1.2034
1.1729
1.1589
1.0930
1.1551
W
1.1879
1.2070
1.1979
1.1589
1.1242
Average
1.1667
1.2052
1.1854
1.1589
1.1086
Theta
0.3633
0.3768
0.3698
0.3606
0.3430
3-18-97
PB
Depth
0-20
20-40
40-60
60-90
90-120
120-150
150-180
180-210
NN
1.3392
1.3475
1.3369
1.3148
N
1.1919
1.1803
1.1887
1.1682
1.0333
1.0537
1.0678
1.0709
MS
1.1495
1.1947
1.1858
1.1649
1.1590
S
Average
1.2019
1.2242
1.1763
1.1804
1.1616
1.1588
1.0693
1.0912
1.1811
1.1997
1.1836
1.1712
1.1180
1.1063
1.0686
1.0811
Theta
0.3683
0.3748
0.3692
0.3649
0.3463
0.3422
0.3290
Table D-4. Volume and chemical concentration of percolate collected in PCAPS at the Medford Station:
V (ml)
MIN
0
0
0
0
0
0
0
0
0
0
0
0
0
0
150
0
0
0
0
0
0
0
0
80
0.13
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
252
0
0
0
0
0
0
0
0
0
0
0
0
0
0
3
0
250
0.12
1120
0.11
2
0
0
3
1
0
0
MIS
2
3
1
1
MIM
2
0
3
3
0
Well
2
0
2
0
1
8-8-95
PBS
PBN
Date
Br ((4 /m1)
1
Well
Rb (p.g /m1)
Blue dye(pg /ml)
8-26-95 V (m1)
Br ((ps /m1)
Rb (lig /ml)
Blue dye(vg /ml)
9-17-95 V (m1)
Br ((jig /ml)
Rb (pg /m1)
Blue dye(pg /ml)
10-5-95 V (ml)
Br ((.4 /m1)
Rb (pg /ml)
0.15
0.21
Blue dye(pg /ml)
11-3-95 V (mL)
Br (ppm)
Rb (ppm)
Blue dye(ppm)
11-28-95 V (ml)
Br ((pg /m1)
Rb (11g /m1)
Blue dye(pg /ml)
155
1.27
125
57
75
1.63
90
2.64
150
1.08
2.72
2
0
0
0
0
0
0
0
0
0
0
450
0.42
225
0.44
0
0
0
0
0
0.29
0
0
Table D-4. Volume and chemical concentration of percolate collected in PCAPS at the Medford Station (continued):
3
0.085
0.023 0.012
50
2.35
0.052
70
12-20-95 V (ml)
Br ((pg /m1)
Rb (pg /ml)
Blue dye(pg /ml)
0
1-24-96 V (m1)
Br ((pg /ml)
2700
1350
3500
10.71
3.01
12.41
Rb (pg /m1)
0.001
0.003
flood
25.17
0
800
9.91
MIM
MIN
Well
PBS
225
3.75
PBN
Date
255
795
5.17 2.46
0.221 0.004
460
3.92
0.281
1520
125
0
0.68
0.017
Well
MIS
180
65
0.66
0.012
0.92
0.022
0
0
25
375
700
1500
1.98
1.13
0.59
50
0.63
0.005 0.165
0.004
0
0.003
flood
flood flood
flood
flood flood flood
1.84
5.06
5.51
7.58
1.18
mix=
0.006
mix= 0.004
flood
flood flood
flood
flood flood flood
6.28
6.47
9.9
1.91
mix=
2.77
0.009
mix=
0.009
flood
flood
flood flood
flood
flood flood flood
11.54
2.28
0.002
0.06
0.001 0.002 0.005 0.004
19800
27500 26500 22600
3500 5150
11.18 21
0.007 0.01
1520 2000
1.61
2.47 3.86
0.025 0.004 0.004
1.3
750
0.66
0.002
4000
8.69
0.003
0.001
flood
flood
flood
flood flood
flood
flood
25.46
24.88
14.25
14.65 19.85 5.73
1.85
1.71
0.6
0.89
0.005
Blue dye(pg /ml)
2-27-96 V (ml)
Br ((pg /ml)
Rb (pg /m1)
1.29
1.04
1.42
Blue dye(pg /ml)
4-4-96
flood
V (ml)
flood
19.43
flood
18.92
19.07
Br ((pg /m1)
Rb (pg /ml)
Blue dye(pg /ml)
mix=
0.012
flood
flood
flood
5-20-96 V (ml)
flood
flood flood
flood flood
13.82
15.92 18.56 6.44
3.03
mix= 0.009 0.013
flood
flood flood
flood
3.95
Br Wig /ml)
0.005
Rb (pg /m1)
Blue dye(pg /m1)0.09
5-29-96 V (ml)
Br ((4 /m1)
Rb
/m1)
Blue dye(pg /ml)
12500
2.74
3.51
0.008 0.005 0.006 0.005 0.003
0.004
0.06
0.002
0.06
0.006
0.06
15000
15000
24300 20300 28500
0.05
0.06
0.07
0.05
0.05
43500 16300
7.49
3.16
0.004
0.05
7.21
49000
48000 47000
0.002 0.003
0.05
0.05
1.67
2.2
2.22
mix= 0.006 0.008
0.05
2.04
0.04
2.69
0.06
2.27
0.06
Table D-4. Volume and chemical concentration of percolate collected in PCAPS at the Medford Station (continued):
Date
7-1-96
PBN
V (m1)
800
26.64
0.004
Br ((lig /m1)
Rb (jig /ml)
Blue dye(pg /m0 0.04
7-25-96 V (m1)
0
0.004
0.09
730
23.41
0.005
0.04
0.005
0.06
0
0
0
1000
23.5
1200
14.14
PBS
1150
Well
1600
7000
55.45
Br ((..tg /m1)
0.004
Rb (lig /m1)
Blue dye(p.g /m1)0.58
2500
52.11
0.005
0.41
2500
63.64
Br ((vtg /m1)
0.006
Rb (p.g /ml)
Blue dye(p.g /m1)0.61
2700
66.47
0.007
V (m1)
0
2000
48.77
0.004
0.22
0.04
0.05
0
0
650
960
22.42 13.06
11500 2000 3000
48.4
0.004
0.05
39.54 50.31
0.003 0.007
Br ((.1.g /ml)
Rb (i.tg /ml)
Blue dye([tg /ml)
0
Well
MIS
0
170
0
0
13.8
9.48
2400
7.32
3000
11.31
0.004 0.004
0
0
0
0
0
0
1600
14.45
0
0
0
680
0
0
0
0
0
8.34
8.90
0.004
8.80
1975
1830
0
3700
37.45
0.009
0.13
33.92 29.54 0.69
0.007 0.005 0.005
110
11.61
375
12.87
0.007
0.006
0.71
63.39
0.006
0.44
0.10
0.11
12.1
12.9
0
0
0
0
0
0
0
1500
0
710
2.85
0.006
1.52
0.03
0.33
0
1
0
0
0
145
20.13
0.006
0.99
0
0
0
0
15.08
0.005
2.25
0
0
4.73
0.007
2.89
Br ((ttg /m1)
/m1)
Rb
Blue dye(pg /m1)
8-27-96 V (m1)
MIM
0
3.09
0.006
0.04
0.005 0.005
7-31-96 V (m1)
8-20-96 V (ml)
0
14.64 8.4
0.006 0.003
Br ((lig /m1)
Rb (i.tg /ml)
Blue dye([1g /m1)
8-7-96
MIN
0
0
0
0
0
0
0
9.34
0.005
0.82
0
0
0
0
0
0
0
0
0
Table D-4. Volume and chemical concentration of percolate collected in PCAPS at the Medford Station (continued):
Date
9-4-96
PBN
V (ml)
0
0
Well
PBS
0
0
0
0
0
0.009
0.66
Blue dye(lig /m1)
0
0
0
0
0
0
MIM
275 0
13.93
0.007
0.93
0
0
0
0
0
0
0
190
105
11.61 17.45
0
0
0.008
Blue dye(ag /m1)
1.92
0
0
0
0
0
0
Well
0
8.07
0.005
0.39
315
0
7.14
0.005
0.24
0
0
30
0
11.57
0.65
0
0
2200 400
260
36.05 29.76 30.46 4.91
0.222 0.084
Rb (.1g /m1)
MIS
310 0
9.02
0.004
0.15
0
10.15
Rb (.1g /m1)
10-31-96 V (ml)
Br ((ttg /m1)
0
12.18
Br ((pg /ml)
Rb (pg /ml)
10-7-96 V (ml)
Br ((4, /m1)
MIN
0
Blue dye(tg /ml)
11-20-96 V (m1)
Br ((4 /m1)
Rb Gig /ml)
Blue dye(lig /m1)0.93
12-16-96 V (m1)
Br ((f.tg /m1)
44.37
19500 7400 6600
57.69 57.48 61.91 5.21
0.89
0.20
48.06
38800
39.81
25000 11600 8000
44.5
47.69 45.54 3.7
0.74
0.82
0.14
15100 8400
47.62 47.25
0.83
10000 7100
45.19
Rb (pg /m1)
Blue dye(pg /m1)0.73
13400
11000 15000 7600
32.35 31.73 32.97
Br ((.tg /m1)
Rb (lig /ml)
0.56
0.42
Blue dye(ig /m1)0.51
1-15-97 V (m1)
0.15
0.12
0.16
0.14
0.08
0.07
0
1.40
0.86
75
7.85
175
16.8
3.14
0.23
350
790
19.18 25.59
610
20.01
850 400
18.82 22.37
290
22.45
2000 490
2.79
2.47
1.53
0.07
0.05
0.02
0.23
3000
3800
32.47
2600
28.82
930
22.8
575
13.01
26.69
410
26.18
2900 425
850
15.35 15.06 14.27 2.54
1.6
1.32
1.01
0.05
0.07
0.01
0.13
3.05
11500 6000 6600
28.39 32.22 29.05 19.1
0.08
0
0
0.29
0.31
19.48 13.73
0.30
0.16
0.31
2.67
355
14.88 4.96
0.27
0.20
0.97
0.48
Table D-4. Volume and chemical concentration of percolate collected in PCAPS at the Medford Station (continued):
1
8-8-95
8-26-95
FLM
FLN
Date
FLS
Well
2
3
1
2
3
1
2
3
5000
4900
6900
6000
5000
1.12
1.16
1.12
6000
0.37
100
490
0.85
1025
0
600
0.33
0
260
0.64
850
0.65
350
0.34
8000
0.33
4000
0
0
sealed
46700
39500
0.33
0.31
V (ml)
Br ((pg /m1)
Rb (pg /ml)
Blue dye(pg /m1)
22400
1.14
4550
0.87
6600
0.68
V (ml)
Br ((pg /m1)
0
0
0
0.76
1.11
Rb (pg /ml)
Blue dye(pg /ml)
9-17-95
2100
0.94
0
V (ml)
Br ((Ag /m1)
Rb (p.g /ml)
Blue dye(pg /mI)
0
0
(nil)
Br Wig /m1)
Rb (pg /m1)
20000
0.27
0
0
0
0
0
sealed
16500
0.24
0
0
0
0
0
0
0
sealed
7950
0
V (m1)
Br ((pg /m1)
0
0
0.31
Rb (pg /ml)
Blue dye(pg /mI)
10-5-95
1 1-3-95
V
0
0
Blue dye(pg /ml)
11-28-95
V (ml)
Br ((pg /m1)
Rb (pg /m1)
Blue dye(lig /ml)
Table D-4. Volume and chemical concentration of percolate collected in PCAPS at the Medford Station (continued):
Date
12-20-95
FLN
V (ml)
Br ((p.g /m1)
0
0
0
0
330
0.53
0.005
320
0.65
0.004
340
0.98
0.006
360
0.46
0.004
800
0.56
0.005
1500
0.85
0.005
sealed
flood
5.66
flood
3.59
mix=
flood
3.47
0.002
flood
5.66
flood
flood
flood
9.73
8.13
0.005
flood
3.39
mix=
flood
3.73
0.003
flood
flood
10.06
12.27
mix=
flood
4.06
0.004
0.11
flood
4.04
0.006
0.12
flood
10.29
0.004
0.05
flood
Br ((pg /m1)
Rb (lig /m1)
Blue dye(pg /m1)
flood
6.91
0.005
0.06
V (m1)
18000
10300
10000
31600
V (m1)
Br ((lig /m1)
Rb (pg /m1)
Blue dye(pg /m1)
2-27-96
sealed
0.056
415
0.63
0.004
1.2
Rb (pg /ml)
Blue dye(pg /ml)
1-24-96
FLM
42
V (ml)
Br ((pg /m1)
Rb (pg /m1)
mix=
FLS
18900
13.02
0.003
26100
Well
11690
18.27
0.005
13000
10.19
0.005
2.92
0.002
mix=
flood
4.45
0.004
4.54
0.007
flood
4.86
mix=
flood
4.76
0.002
flood
4.73
0.005
0.09
flood
4.23
0.004
0.06
46500
30000
10.96
0.003
flood
5.43
Blue dye(pg /ml)
4-4-96
V (ml)
Br ((pg /m1)
Rb (lig /m1)
flood
6.91
flood
9.53
0.004
flood
flood
0.004
0.05
flood
9.98
0.004
0.05
35900
60600
sealed
5.7
0.012
Blue dye(pg /ml)
5-20-96
5-29-96
V (m1)
Br ((p.g /m1)
Rb (pg /ml)
Blue dye(pg /ml)
12.09
6.04
0.009
0.11
Table D-4. Volume and chemical concentration of percolate collected in PCAPS at the Medford Station (continued):
Date
7-1-96
7-25-96
7-31-96
8-7-96
8-20-96
V (ml)
Br ((ug /m1)
Rb (lig /ml)
Blue dye(pg /m1)
20300
6.39
0.004
0.05
FLN
2500
4.55
0.005
0.05
V (ml)
Br ((lig /m1)
Rb (lig /m1)
Blue dye(tig /m1)
0
0
V (m1)
0
Br ((iig /m1)
Rb (lig /m1)
Blue dye(p.g /m1)
7200
14.97
0.004
0.17
V (ml)
Br ((,ig /m1)
Rb (gig /ml)
Blue dye(pg /m1)
55500
22.04
0.004
0.10
3500
V (m1)
0
4.71
0.003
0.10
6000
4.69
0.003
0.06
FLM
6500
7.02
0.003
0.06
0
0
0
2600
0.11
2700
22.04
0.005
0.05
0
0
19.5
0.006
Rb (pg /ml)
Blue dye(lig /m1)
V (ml)
Br ((lig /ml)
/ml)
Rb
Blue dye(lig /ml)
sealed
325
8.55
sealed
10000
3.27
0.006
2000
4.32
0.004
0
0
sealed
11000
10.07
0.006
0.13
8000
15000
19.04
7000
0
21.4
0.006
0.75
Br ((lig /m1)
8-27-96
0
0
0
0.006
0.76
6500
52.43
0.003
0.66
7100
46.56
0.005
0
0
0
12900
57.65
4.12
0.004
0.04
6300
8.84
0.004
0.10
0.004
155
Well
FLS
25000
3.68
0.002
0.04
sealed
0.004
0.14
0.61
sealed
7000
18.02
0.004
0.26
15400
13.48
0.005
0.31
17.25
0.003
0.17
65.95
0.008
10.4
0
48.06
0.004
3.14
Table D-4. Volume and chemical concentration of percolate collected in PCAPS at the Medford Station (continued):
Date
9-4-96
10-7-96
10-31-96
11-20-96
0.003
0.14
11.94
0.005
0.28
6100
24.82
0.001
0.29
FLM
7000
22.66
0.007
0.23
0
0
0
0
V (ml)
Br ((1g /m1)
Rb (pg /m1)
Blue dye(pg /m1)
33900
FLN
2000
17.25
16.71
0.008
0.19
V (ml)
Br ((pg /m1)
Rb (Rg /m1)
Blue dye(pg /m1)
0
V (ml)
Br ((pg /ml)
Rb (p.g /ml)
Blue dye(pg /m1)
0
V (ml)
Br ((ug /m1)
0
2000
7500
25.02
0.005
0.22
sealed
100
17.32
sealed
0
0
0
0
1-15-97
sealed
5100
4.64
Well
5500
11.61
0.004
0.20
6950
5.63
0.004
0.23
24.43
0.009
2.88
14.49
0.011
2.36
0
0.26
0
0
0
0
0
Rb (ug /ml)
Blue dye(ug /m1)
12-16-96
11450
5.5
0.008
0.29
0.007
0.39
0
FLS
13050
12.77
0.004
0.27
sealed
7400
7200
10.45
17.6
17.88
0.22
0.24
0.84
100
160
Br ((p.g /m1)
Rb (ug /m1)
34.93
35.47
10500
17.36
14500
19.03
17.76
Blue dye(pg /m1)
0.14
0.13
0.18
0.21
0.76
1100
V (m1)
0
0
0
0
V (m1)
100
125
225
145
Br ((vtg /m1)
22.71
16.7
36.02
580
34.4
30.07
8650
17.29
3200
33.87
17.69
16.64
Rb (pg /ml)
Blue dye(ug /m1)
0.13
0.09
0.08
0.01
0.05
0.04
0.15
0.13
1.04