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dissertation entitled
SPATIAL AND TEMPORAL SOIL WATER CONTENT
CHANGES WITHIN A SLOPING LANDSCAPE

presented by

Martin John Rosek

has been accepted towards fulfillment
of the requirements for

 

 

Doctoral degree in Crop and Soil Sciences

Dr. James R. Crum

 

Major professor

Date October 8, 1994

 

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SPATIAL AND TEMPORAL SOIL WATER CONTENT CHANGES WITHIN A
SLOPING LANDSCAPE

By

Martin John Rosek

A DISSERTATION

Submitted to
Michigan State University
in partial fulﬁllment of the requirements
for the degree of

DOCTOR OF PHILOSOPHY

Department of Crop and Soil Sciences

] 994

 

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30';

ABSTRACT

SPATIAL AND TEMPORAL SOIL WATER CONTENT CHANGES WITHIN
A SLOPING LANDSCAPE.

By

Martin John Rosek

Soil physical properties and the amount of soil water within a sloping landscape are
largely determined by landscape position. This study determined temporal dynamics of
soil water within a sloping landscape by (l) examining the spatial variability of selected
soil properties that regulate water retention; (2) quantifying water balance by slope
position; (3) determining the minimum amount of stored soil water data required to
estimate the amount of soil water within a sloping landscape using geostatistics.
Neutron probe access tubes were placed at two meter intervals, in two transects,
across a sloping topography of Kalamazoo loam (ﬁne-loamy, mixed, mesic, Typic
Hapludalfs) and Oshtemo sandy loam (coarse-loamy, mixed mesic, Typic Hapludalfs)
at Kellogg Biological Station in southwestern Michigan. Volumetric water content of
the soil was monitored approximately weekly in the spring, summer and autumn of
1990 and 1991 at 15, 30, 60, 90, 120, and 150 cm by neutron attenuation. Soil
samples from a 48 by 34 meter grid between the access tubes were described and

sampled. Water content of each sample point was estimated with CERES Maize for

two sample dates. Selected volumetric water per 150 cm soil depth values were
removed from the data sets, then kriged and cokriged for m soil water at locations
where data points were removed. The Ap horizon of the lower backslope, footslope,
and toeslope display a greater mean thickness, percent silt and organic carbon, relative
to upslope soils. The Btl horizon and control-section display a greater mean silt and
clay below the middle of the backslope. The amount of soil water was least within the
upper backslope position, moderate within the summit and lower backslope positions,
and greatest within the footslope and toeslope positions. Cokriging estimation of
stored soil water, using mm soil water per 150 cm soil depth at ﬁeld capacity as the
auxiliary variable, reduced the required sample distance to twice the range of spatial
dependence in the direction parallel to the contour of the slope. Variogram models of
the amount of soil water from large data sets could be used to predict the amount of

soil water in other studies with similar landscape and soil conditions.

ACKNOWLEDGMENTS

I wish to express my appreciation and gratitude to:

Dr. James Crum, my major advisor, for his patience and guidance throughout the
research project.

The graduate committee:

Dr. Delbert Mokma, Dr. Fran Pierce, and Dr. James Hart.

Jim Bronson, the Kellogg Biological Station farm manager, and his crew; Greg
Parker, Sam Akough, and Jim Przewosniak for their help and assistance.

My loving wife, Janet, and our two children, Alyssa and Jacob, who have made all
my efforts worth while.

My parents, Edward and Marie Rosek, for their ﬁnancial support and
encouragement.

My mother-in-law, Alice Heim, for her ﬁnancial support and the purchase of the
computer that made this dissertation possible.

My sister, Debbie F rechette, for her expression of faith in me during the duration of

this project.

iv

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TABLE OF CONTENTS

List of Tables ............................................................................................... vii
List of Figures ............................................................................................. viii
Introduction ................................................................................................... 1

References .............................................................................................. 10

Chapter 1. Literature Review.

Movement of Water On and Within Slopes ............................................. 11
Soil Water Balance ................................................................................. 15
Relationships of Soil Development and Landscape .................................. 17
Soil Spatial Variability and Geostatistics ................................................. 19
References .............................................................................................. 28

Chapter 2. Spatial Variability of Sand, Silt, and Clay Content, and Horizon Thickness
of Soils Within a Sloping Landscape.

Abstract ................................................................................................. 34
Introduction ........................................................................................... 35
Materials and Methods ....................................................... . .............. ....36
Results and Discussion ........................................................................... 43
Summary and Conclusions ..................................................................... 83
References ............................................................................................. 84

Chapter 3. Soil Water Balance and Geostatistical Estimation of Stored Soil Water
in a Sloping Landscape.

Abstract ........... . ...................................................................................... 87
Introduction ............................................................................................ 88
Materials and Methods ............................................................................ 91
Results and Discussion .......................................................................... 99
Summary and Conclusions ..................................................................... 124
References ............................................................................................. l 26
General Conclusions .................................................................................... 131

Appendices.

Appendix A. Soil Proﬁle Horizon Depth, Particle Size Distribution,
Control Section Clay Content, and Soil Series Data ................................. 134

Appendix B. Soil Moisture Retention Input for CERES Maize simulation
of Soil-Water Content ............................................................................. 154

vi

LIST OF TABLES
Table 2.1. Location of slope units at the study site ................................................... 36

Table 2.2. Descriptive statistics for variables determined in the

ﬁeld and laboratory ............................................................................................. 51
Table 2.3. Descriptive statistics as a function of slope position for

selected soil properities ....................................................................................... 53
Table 2.4. Semivariance statistics for soil properties ................................................ 60
Table 2.5. Pooled estimation variance of block kriging ............................................. 80

Table 3.1. Average soil proﬁle water retention (0 to 150 cm) at ﬁeld
capacity for each landscape position ................................................................. 102

Table 3.2. Changes in Runoﬂ‘ Curve Numbers ........................................................ 109

Table 3.3. Changes in average ﬁeld capacity volumetric moisture content
for the south transect ....................................................................................... 112

Table 3.4. Changes in average ﬁeld capacity volumetric moisture content
for the north transect ........................................................................................ 113

Table 3.5. Statistical comparison of measured and simulated values

of mm soil water per 150 cm soil ...................................................................... 118
Table 3.6. Water ﬂux amounts for each slope position ........................................... 120
Table 3.7. Semivariance and cross-semivariance statistics ...................................... 123

Table 3.8. Statistical comparison of CERES mm soil water values of
mm soil water per 150cm soil with kriged and cokriged estimates ........................... 123

Table 3.9. Pooled kriging estimation variance ........................................................ 124

vii

LIST OF FIGURES

Figure i. 1. General conceptual model for the LTER project ....................................... 2
Figure i.2. Location of Kellogg Biological Station (KBS) .......................................... 5
Figure i.3. Schematic diagram of the LTER with the location of the study area .......... 6
Figure i.4. Topography of the study area, looking south ............................................ 7
Figure 1.1. Components of the hillslope hydrological cycle ...................................... 12
Figure 1.2. Portion of a hypothetical grid, illustrating semivariance

computation for given lags ........................................................................................ 21
Figure 1.3. Hypothetical semivariogram ................................................................... 21
Figure 1.4. Weights for kriging point P ........................... . ........................................ 24
Figure 1.5. Geometric anisotropy about a sample ..................................................... 24
Figure 2.1. Typical Kalamazoo and Oshtemo soil proﬁles ........................................ 37
Figure 2.2. Study site surface 3 dimentional plot ...................................................... 38
Figure 2.3. Control—section percent clay of the study site ......................................... 40
Figure 2.4. Hypothetical semivariogram ................................................................... 42
Figure 2.5. Frequency of Ap, Btl and ZBt2 horizon percent clay ............................. 44
Figure 2.6. Frequency fo conntrol-section percent clay and clay mass ...................... 45
Figure 2.7. Frequency of Ap, Btl , and 2Bt2 horizon percent sand ............................ 46
Figure 2.8. Frequency of Ap, Btl, and ZBtZ percent silt ........................................... 47
Figure 2.9. Frequency of Ap, Btl, And ZBt2 horizon thickness ................................ 48
Figure 2.10. Frequency of Btl, ZBt2, and soil proﬁle clay mass ............................... 49
Figure 2.11. Frequency of Ap percent organic carbon and solum thickness .............. 50

viii

Figure 2.12. Semivariograrns for Ap and Btl percent clay, sand, and silt; and ZBt2
percent sand and silt ........................................................................................... 57
Figure 2.13 Semivariograms for Ap percent organic carbon; Ap, Btl, ZBt2, and
solum thickness .................................................................................................. 58
Figure 2.14 Semivariograms for control-section percent clay, Btl, ZBt2, control-
section, and soil proﬁle clay mass ....................................................................... 59
Figure 2.15 Block-kriged map of Ap horizon percent organic carbon ....................... 62
Figure 2.16 Block-kriged map of Ap horizon percent clay ....................................... 63
Figure 2.17 Block-kriged map of Btl horizon percent clay ...................................... 64
Figure 2.18. Block-kriged map of 2Bt2 horizon percent clay .................................... 65
Figure 2.19. Block-kriged map of control-section percent clay ................................. 66
Figure 2.20. Block-kriged map of Ap horizon percent sand ...................................... 67
Figure 2.21. Block-kriged map of Btl horizon percent sand ..................................... 68
Figure 2.22. Block-kriged map of Ap horizon percent silt ........................................ 69
Figure 2.23. Block-kriged map of Btl horizon percent silt ....................................... 70
Figure 2.24. Block-kriged map of Ap horizon thickness ........................................... 71
Figure 2.25. Block-kriged map of Btl horizon thickness .......................................... 72
Figure 2.26. Block-kriged map of 2Bt2 horizon thickness ........................................ 73
Figure 2.27. Block-kriged map of solum thickness ...................... . ............................ 74
Figure 2.28. Block-kriged map of Btl horizon clay mass ......................................... 75
Figure 2.29. Block-kriged map of 2Bt2 horizon clay mass ....................................... 76
Figure 2.30. Block-kriged map of control-section clay mass ..................................... 77
Figure 2.31. Block-kriged map of soil proﬁle clay mass ........................................... 78
Figure 2.32. Estimation variance of Ap horizon percent clay .................................. 81

ix

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F11

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Figure 2.33. Estimation variance of Ap horizon percent silt ...................................... 82

Figure 3.1. Study site surface 3 dimentional plot ...................................................... 92

Figure 3.2. Typical Kalamazoo and Oshtemo soil proﬁles ........................................ 94

Figure 3.3. Topography (relative meters) of the study site with sample
point locations .................................................................................................... 97

Figure 3.4. Slope proﬁle of the south transect, showing the location
of each neutron probe access tube ..................................................................... 100

Figure 3.5. Slope proﬁle of the north transect, showing the location
of each neutron probe access tube ..................................................................... 101

Figure 3.6. Precipitation and average daily temperature for the 1990

ﬁeld study period .............................................................................................. 103
Figure 3.7. Precipitation and average daily temperature for the 1991

ﬁeld study period .............................................................................................. 104
Figure 3.8. Average total soil water of the south transect for 1990 ......................... 105
Figure 3.9. Average total soil water of the north transect for 1990 ......................... 106
Figure 3.10. Average total soil water of the south transect for 1991 ....................... 107
Figure 3.11. Average total soil water of the north transect for 1991 ....................... 108
Figure 3.12. Simulated total soil water of the south transect for 1990 .................... 114
Figure 3.13. Simulated total soil water of the north transect for 1990 ..................... 115
Figure 3.14. Simulated total soil water of the south transect for 1991 .................... 116
Figure 3.15. Simulated total soil water of the north transect for 1991 ..................... 117
Figure 3.16. Semivariograms and cross-semivariograms for

soil water properties ......................................................................................... 122

 

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INTRODUCTION

In 1987 a Long Term Ecological Research (LTER) project in agroecosystems was
established at the Kellogg Biological Station (KBS) in southwest Michigan. The goal
of this research was to understand interactions among organisms and between
organisms and their environment in agricultural ecosystems sufﬁciently well to manage
these interactions for levels of agronomic yield that are economically and
environmentally sound. The global hypothesis of the LTER project was that
agronomic management based on ecological concepts can substitute for reliance on
chemical subsidies in production-level agriculture (Robertson et al., 1986).
Management of soil-water, on an ecological basis (i.e., cropping systems and soil
management practices), can substitute for or reduce producer water inputs (irrigation)
and reduce soil-water outputs. Effective crop management should incorporate
landscape position based practices (i.e., variable planting and fertility rates for each
slope position, contour plowing, grassed waterways) to reduce losses of water,
nutrients, and pesticides, from the cropping system to groundwater and atmospheric
outputs. This is illustrated in the conceptual model for the LTER project (Figure i. 1).

Effective management of soil-water within agricultural landscapes, which minimize
external inputs and outputs and optimize yield, requires a solid understanding of the
mechanisms that regulate soil-water-landscape interactions. Soil productivity, water
movement, and nutrient losses are inherently governed by landscape position.

Water is the medium in which biological and chemical transformations of nutrients
occur and in which different nutrient forms move and are transported in the soil

proﬁle, either to plant roots or out of the proﬁle and eventually into the ground water

 

Chemical subsidies
Natural Inputs

 

 

 

 

Management practice
‘ Landscape position

 

 

 

 

 
  
 

  

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Substrate/$0M availability
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Herbicide resistance

Herbivore pop'n shifts
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I Management practices
Landscape position
Groundwater. runoit,
and atmospheric outputs

 

 

 

 

Figure i. 1. General conceptual model for the LTER project.

(Nielsen et al., 1973). To predict nutrient behavior in soil, therefore, one must ﬁrst be
able to predict water retention and distribution. Water distribution studies are made
more complex soil by characteristics common to most soils. These characteristics
complicate the prediction of water distribution under a variety of landscape conditions.

Much of the literature in soil spatial variability suggests that most soil proﬁle
characteristics contain components that are spatially dependent within single map units
and even individual ﬁelds (Campbell, 1977, 1978; Burgess and Webster, 1980; Gajem
et al., 1981; Vieira et al., 1981; Yost et al., 1982). Since soil-water distribution is a
function of soil proﬁle characteristics, the quantiﬁcation of the spatial variability of
those proﬁle characteristics should make it possible to predict the spatial variability of
water distribution for a given set of soil and landscape conditions. This study makes
such a quantiﬁcation and comparison between soil proﬁle and soil-water properties for
the characterization of soil-water distribution.

Water can be a major limiting factor for crop production in sandy soils of
southwest Michigan. Since these soils are formed in glacial materials, they can be
quite variable, and have signiﬁcant differences in water holding capacity within the
landscape. Many of the landscapes where these soils are found have complex
topographies, which contributes to the differential drying patterns. These soils tend to
loose water ﬁrst on the more steeply sloping (backslope) positions, followed by the
upper more level area (summit), while the lower portion of the landscape below the
backslope (toeslope) tends to dry last (Helvey et al., 1972; Hall, 1983). Knowledge of
water retention and distribution in soils can be used to more efﬁciently manage
agricultural ecosystems. For example, the yield potential of soils within sloping
landscapes varies dramatically, mainly because of differences in the ability to retain and
supply plant available water. To more efficiently manage such systems, different

amounts of inputs (i.e. plant population, fertilizer, pesticides, etc.) should be made to

the 1

land

Stud

4

the different soils, that have variable productivity's, on the various parts of the

landscape.

Study Site

The study was conducted at the W. K. Kellogg Biological Station (KBS), in the
northeast corner of Kalamazoo County, Michigan (Figure i.2). KBS is situated on the
pitted Galesburg-Vicksburg outwash plain (Monahan et al., 1983). The study area is
located at the east end of the north (reserve) ﬁeld of the LTER (Figure i.3). A small
north-south valley dissects a level plain where the valley ﬂoor dips downslope north to
an outlet (Figure i.4). The valley is approximately 4.4 meters deep and ﬁ'om 90 to 140
meters wide. The study site consisted of distinct summit, backslope, and toeslope
components (Ruhe, 1960) and the research was conducted on the east side of the
valley where the gradient of the backslope ranged from 4.6% to 5.6%. The backslope
on the west side of the valley ranged from 8% to 10%. The dominant soils on this
landscape are Kalamazoo Loam (Fine-loamy, mixed, mesic, Typic Hapludalfs) and
Oshtemo Sandy Loam (Coarse-loamy, mixed, mesic, Typic Hapludalfs). Stratiﬁed
sand and gravel is found from the lower proﬁle of these soils to the contact with
glacial till, which is approximately 15 meters below the surface, as indicated by well
logs from the area. Both Kalamazoo and Oshtemo soils are well drained and are

found on all positions of the landscape, including the toeslope.

Hypotheses

It is the hypothesis of this study that landscape position controls soil physical
properties through soil formation (i.e. organic matter accumulation, formation of soil

horizon and soil structure, and clay translocation) which in turn effects soil moisture.

Fi

 

 

Kalamazoo County

 

 

 

Figure i.2. Location of Kellogg Biological Station (KB S).

 

KBS LTER Site

1:]

Study Area

 

100m

Figure i.3. Schematic diagram of the LTER with the location of the study area.

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Figure i.4. T0pography of the study area, looking south.

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8

Landscape position, in part, determines how much precipitation inﬁltrates into the soil
proﬁle. Inﬁltration of precipitation is a major factor in soil development and soil-water
content. On a landscape with summit, backslope, and toeslope components, overland
and lateral subsurface ﬂow of water is most likely to be small on the summit and
toeslope positions, while possibly signiﬁcant on the backslope. Overland and lateral
subsurface ﬂow from the backslope is likely to become overland and subsurface ﬂow
to the toeslope, adding water to the soils in the toeslope position. Thus, in a sloping
landscape where all of the soils are well drained, such as the study site, inﬁltration of
precipitation may be lowest in the backslope soils, moderate in the summit soils, and
greatest in the toeslope soils. From this the following corollaries of this study are
made:

1. Soil water content is affected by landscape position in the following modes:

3. Soil water content is directly affected by landscape position due to the effect
of runoﬂ‘ and runon.

b. Within a given landscape where the parent material is the same throughtout
the landscape, soil-water content is indirectly affected by landscape position
because the degree of soil development, erosion, and deposition effect
soil water holding capacity.

The more developed the soil proﬁle (on a given landscape) the greater its
water holding capacity. Soil development is dependent on the amount of
precipitation and inﬁltration. Thus, in this sloping landscape where all the
soils are well drained, soil development is greatest in the toeslope soils,
moderate in the summit soils, and least in backslope soils.

Therefore, for much of any given year, the amount of soil water will be greatest
in the toeslope soils, moderate in the summit soils, and lowest in the backslope

soils.

9

2. Soil development and the amount of soil water vary spatially on this sloping

landscape.

Objectives

The goal of this research was to detemrine the temporal dynamics of soil water

within a leping landscape. This goal was achieved by the following objectives:

1. Characterize the spatial distribution of soils within a sloping, erosional landscape
at Kellogg Biological Station (KBS) in southwest Michigan.

2. Determine water balance that occurs within each slope component of the
landscape of the study site.

3. Determine the minimum amount of sample data required to characterize the
amount of soil water within a sloping landscape at KBS, using soil proﬁle

variability.

10

REFERENCES

Burgess, TM. and R. Webster. 1980. Optimal interpolation and isarithmic mapping
of soil properties. I. The semi-variogram and punctual kriging. J. Soil Sci.
3 1 :3 15-331 .

Campbell, J .B. 1977. Variation of selected soil properties across a soil boundary.
Soil Sci. Soc. Am. J. 41:578-582.

Campbell, 1.3 1978. Spatial variation of sand content and pH within single
contiguous delineations of two soil mapping units. Soil Sci. Soc. Am. J.
42:460-464.

Gajem, Y.M., A.W. Warrick, and DE. Myers. 1981. Spatial dependence of physical
properties of a Typic Torriﬂuvent soil. Soil Sci. Soc. Am. J. 45:709-715.

Hall, GE 1983. Pedology and geomorphology. In Wilding, L.P., NE. Smeck, and
GE Hall (eds), Pedogenesis and soil taxonomy. 1. Concepts and interactions.
Elsevier, Amsterdam. pl 1 7- 140.

Helvey, J.D., J .D. Hewlett, and J .E. Douglass. 1972. Predicting soil moisture in the
southern Appalachians. Soil Sci. Soc. Am. Proc. 36:954-959.

Monahan, G.W., G.J. Larson, D.W. Forstat, and H0. Sorensen. 1983. Selected
geologic maps of Kalamazoo County, Michigan. Mich. Dept. of Nat. Res,
Geol. Surv. Div., Lansing, Mich.

Nielsen, D.R., J.W. Biggar, and KT. Erh. 1973. Spatial variability of ﬁeld-measured
soil-water properties. Hilgardia 42:215-259.

Robertson, G.P., E.A. Paul, M]. King. 1986. Organisms in the agricultural
landscape: Long Term Ecological Research. Unpublished.

Ruhe, R.V. 1960. Elements of the soil landscape. Trans. 7th Int. Congress Soil Sci,
Madison Wise, 4: 165-170.

Vieira, S.R., J.L. Nielsen, and J.W. Biggar. 1981. Spatial variability of ﬁeld-measured
inﬁltration rate. Soil Sci. Soc. Am. J. 45: 1040-1048.

Yost, R.S., G. Uehara, and KL. Fox. 1982. Geostatistical analysis of soil chemical
properties of large land areas. I. Semi-variogriograms. Soil Sci. Soc. Am. J.
46:1028-1032.

11

CHAPTER 1

LITERATURE REVIEW

MOVEMENT OF WATER ON AND WITHIN SLOPES

The distribution of water in soils is governed by a complex set of interrelated
factors. After climatic effects, the major controlling factors are determined by soil and
vegetative properties, topographic characteristics such as slope form and gradient, and
positional attributes such as relative height and distance from the slope base (Gerrard,
1981). Water can move across, through, and be stored in soil in a variety of ways as
illustrated in Figure 1.1. Of those in Figure 1.1, inﬁltration, Horton overland ﬂow,
saturated overland ﬂow, saturated throughﬂow, return ﬂow, pipe ﬂow, and deep
seepage are the major pathways for water movement on and within slopes.

Inﬁltration is simply the process of water entering the soil. In general,capacity for
inﬁltration displays a rapid initial rate which drops quickly to some constant value.
This decrease in inﬁltration capacity occurs primarily for two reasons. First, as soil-
water content increases, wetting causes a reduction of the hydraulic gradient near the
surface. Second, reduction of soil pore diameter by clay mineral swelling upon
wetting, combined with the washing of ﬁnes into soil pores, impede inﬁltration
(Gerrard, 1981). Inﬁltration rate is determined by external factors such as rainfall
intensity and duration and rain drop size, and soil characteristics such as texture,
structure, slope, proﬁle depth, type and proportion of clay minerals, vegetation, and
land-use (Gerrard, 1981). When water moves through soil, it displaces water
previously retained in the soil pores. Water moves into and within soil under the
inﬂuence of gravitational and capillary forces, the latter being due to attractive
molecular forces between soil particles and water which yields very slow water

movement (Baver, 193 7). At low soil moisture, most water movement is due to

  
 
   
 

Humus

Unsaturated
Soil

Saturated

 

 

 

Water table ]Bcdrock

 

 

 

Precipitation (gross rainfall) P Horton overland flow q,,
Channel precipitation PC Saturated overland flow q,
Precipitation intensity 1' Return flow q,
Evapotranspiration e, Pipe flow I
Canopy interception loss at Pipe storage 7'
Interception and canopy storage I Unsaturated throughflow mu
Stemflow and drip 5 Saturated throughflow m,
Litter flow / Soil-moisture storage M
Litter interception loss 8, Seepage into bedrock so
Litter storage L lntertlow in bedrock a
Evaporation e Aeration zone storage A
Depression storage RP Deep seepage d
Detention storage R7 Baseflow b
Infiltration f Groundwater storage 8

Figure 1.1. Components of the hillslope hydrological cycle.
(from Chorley, 1978)

l3

capillarity and takes place in micropores. When soil moisture is between ﬁeld capacity
(soil-moisture content where excess water has drained) and saturation, most water
movement is due to gravitational pull, and takes place in macropores. When the ability
of the soil to intake water is not surpassed, the amount of water inﬁltrated is
contingent upon the rainfall rate, and is called ﬂux controlled inﬁltration. Ifthe rainfall
rate exceeds the inﬁltration rate, ponded, or proﬁle-controlled inﬁltration occurs.

When the inﬁltration capacity of the soil is surpassed, surface ponding occurs and
this ponded water moves downslope as surface ﬂow or Horton overland ﬂow (Horton,
1935). This surface ﬂow rarely occurs as a uniform sheet of water and most of the
water travels downslope in lateral concentrations. It is generally accepted that these
lateral concentrations possess characteristics of sheet ﬂow (Emmett, 1970). At a
critical distance downslope overland ﬂow becomes deep enough to cause sheer stress
which can dislodge and move surface soil particles causing erosion to occur as rills.
Cook (1946) presented a sequence of events that occurs with overland water ﬂow on
slopes as follows: a. A thin water layer forms on the surface and downslope surface
ﬂow begins; b. The ﬂowing water gathers in surface depressions. c; When ﬁrll these
depressions overflow; d. Overland ﬂow enters microchannels which coalesce to form
rivulets which discharge into gullies; e. Along each microchannel, lateral inﬂow from
the land surface takes place. Horton overland ﬂow happens relatively instantaneously
over a basin only if the basin is small and has homogeneous soil, soil moisture, rain
interception, and inﬁltration conditions.

Also important, is the lateral downslope movement of water (throughﬂow) within
soil layers (Freeze, 1972, 1974). In soils where there is a discontinuous decrease of
hydraulic conductivity with depth, saturation may build up from the base of a soil
horizon within which saturated throughflow may occur downslope (Chorley, 1978).
Temporary zones of saturation above the groundwater surface have been noted by

Burt and Butcher (1985). In this type of water ﬂow soil physical properties and depth

l4

assume a large role (Hoover and Hursh, 1943). In coarse-textured soils, vertical ﬂow
dominates, while in ﬁne textured soils there is resistance to vertical ﬂow, initiating
saturated throughﬂow. Of major importance is soil structure, especially in ﬁne-
textured soils or soil layers, where ﬁssures, cracks, and channels replace textural voids
as the main avenues of water ﬂow. The effect of cracks and channels on water
movement is enhanced if they penetrate different soil horizons, and lithologic
discontinuities (Gerrard, 1981). Differing permeability's greatly enhance lateral
downslope throughﬂow. Differences in soil horizons, dense layers, weathered and
unweathered bedrock cause hydraulic discontinuities.

Early in a storm event, a saturated wedge forms at the slope base, and throughﬂow
begins. This saturated throughﬂow increases as the saturated layer becomes thicker,
intersecting the ground surface, initiating return ﬂow (Dunne, 1978: Gerrard, 1981),
causing saturated overland ﬂow (Kirkby and Chorley, 1967; Kirkby, 1969; Calver et
al., 1972; Chorley, 1978). This surface ﬂow is supplemented by direct precipitation
onto the saturated area. As the storm continues the saturated wedge increases upslope
and the amount of saturated overland ﬂow also increases.

Zaslavsky and Sinai (1977, 1981a, b, c) and Sinai et a1. (1981) noted four forms of
lateral throughﬂow (saturated and unsaturated) are induced by rainfall and inﬁltration:
1. Splash of rain drops lead to larger splash downhill and result in a net lateral ﬂow.
2. Lateral ﬂow is formed in a transition layer between the soil and the air due to its

nonuniforrnity, anisotropy, and slope.

3. When the layers of a soil are slanted, lateral ﬂow occurs. This occurs in many
alluvial deposits, gemetically formed A and B horizons, and soil layers formed by
cultivation.

4. Lateral ﬂow will form in the unsaturated zone immediately above a sloped phreatic

surface.

15

These forms of lateral ﬂow start almost immediately after the beginning of the rainfall,
but may lag for an increasingly longer time after the rain at increasingly greater soil
depths. The lateral ﬂux component is proportional to the slope of the surface or to the
slope of the soil layers. As a result, water will accumulate in concave parts of the
landscape and diverge from convex positions.

Piping provides a macropore network for the quick transmission of throughﬂow
water. Pipe networks are usually discontinuous and may discharge onto the same
slope segment as the pipe inlet (Gilman and Newson, 1980). Beasley (1976) noted
subsurface ﬂow oﬁen began shortly after rainfall began even when there was neither
saturation at the point of outﬂow nor high antecedent soil moisture and attributed this
phenomena to interconnected channels through the soil formed by decayed roots and
animal burrows. Soils most likely to produce pipes are peaty surface horizons and
impermeable layers at shallow depth, loamy soils on a steep slope (Gerrard, 1981), and
highly dispersive soil layers with a high exchangeable sodium percentage (Omodt et
al., 1975). Eluviation in highly dispersive soils forms pipes by allowing the ﬁne earth
fraction to be removed progressively through the soil matrix. This is indicated by the
deposition of clay and silt where the pipes emerge (Gerrard, 1981). Desiccation

creates cracks that act as pipes in cohesive clay soils (Parker, 1964).

SOIL WATER BALANCE

Water in soils is either in a ﬂowing or stored state. Soil retention storage relies on
the concept of ﬁeld capacity, the amount of water that a soil can permanently hold
against the downward pull of gravity (Horton, 1933). Conversely, soil-detention
storage consists of soil-water in excess of ﬁeld capacity which is slowly draining

through large, non-capillary pores (Fletcher, 1952: Hoover, 1962).

16

In general, the concept of soil water balance, as outlined by Rouse (1970) is that
the change in stored soil water (dS) is the difference between input water (Iw) to the
soil and output water ﬁom the soil (Ow) or;

d8 = Iw - Ow.

Separating the input and output water into components, the following equation is
obtained:

dS=P+Ro-Rf-ET-D
where the change in soil proﬁle water content, dS, is the result of the input of
precipitation, P, and surface and subsurface runon, Ro, minus surface and subsurface
runoff, Rf, evapotranspiration, ET, and drainage from the proﬁle, D. Since soil proﬁle
drainage is much more difﬁcult to measure than the change in soil moisture content,
the above equation can be rearranged to estimate drainage as follows:

D=P+Ro-Rf-dS-ET.
To determine ET, potential evapotranspiration (PET) may be estimated. There have
been several methods developed to estimate PET, among which the Thomthwaite
(1948), Penman (1948), and Priestley and Taylor (1972) methods are most widely
accepted. Once PET is estimated, it is incorporated into the water balance equation as
follows:

in periods where D > 0, and AET = PET;
D=P+Ro-Rf-dS-PET:
in periods where D = 0, and ET 3 PET;
ET = P + Ro -Rf- dS.

Many computer models have been developed to simulate hydrologic processes
associated with water balance in the vadose zone (Baire et al., 1972; M012 and
Remsorr, 1971; Parkes and O'Callaghan, 1980; Francis and Pidgeon, 1982; Belmans et
al., 1983; Jones and Kiniry, 1986; Workman et al., 1990). Conceptually, mathematical

computer models of soil-water balance have been developed using either a parametric

17

or deterministic approach. Each model has strengths and weaknesses, depending on
what the user needs the model for and what hydrologic circumstances the model is

used to simulate.

RELATIONSHIPS OF SOIL DEVELOPMENT AND LANDSCAPE

The distribution of water on slopes has a substantial inﬂuence on the properties of
soils, and water movement integrates soils existing on different parts of the landscape
(Gerrard, 1981). This gives rise to the catina concept, ﬁrst proposed by Milne (1935a,
b). A catena is considered to be the interlocking of soils on the landscape. The catena
concept has been use interchangeably with the toposequence concept, which relates
morphologic changes (especially color) with relative elevation, and thus to water table
depth and ﬂuctuation. But catena is also a process-response concept. Not only do the
soils of a catena differ morphologically, but differ as a result of erosion, transport and
deposition of sediments, as well as leaching, translocation (vertically and laterally), of
chemical and particulate matter in the soil (Hall, 1983). Thus, the processes of each
soil member of a catena are related to every other soil member, and are continuously .
adjusting to the environmental changes of the landscape (Dan and Yaalon, 1964).

Moving water is the principal cause of movement of material overland and within
sloping soils. The distribution of water and water movement are the primary reasons
that different soils are found on a landscape composed of the same parent material
(Hall, 1983).

Slope gradient and length are very important in regards to movement of water and
materials in water on landscapes. As slope gradient increases, ﬂow velocity of surface
runoﬁ' increases, and the force of the overland ﬂow increases exponentially (Zingg,
1940). Amemiya (1970) noted that as a given straight slope element increases in

length, the ﬂow velocity and volume of water that reach the lower portion is greater.

 

 

 

18

The ability to erode increases as a ﬁrnction of increased water ﬂow volume
(Wischrneier, 1975).

As discussed previously, within a landscape, ﬂowlines of water exist both on the
surface and within the soil. These ﬂowlines run straight only where the soil is
homogeneous and the contour lines of a slope are parallel. Concave downslope
contour lines (coves and headslopes) make for convergent ﬂowlines, and convex
downslope contour lines (spurs and noseslopes) make for divergent ﬂowlines (Hall,
1983)

There are signiﬁcant differences in water movement and erosion between convex,
concave and straight portions of a slope (Acton, 1965; Gerrard, 1981; King et al.,
1983). Water velocity and soil erosion increase on convex segments as slope
steepness increases downslope (Meyer and Kramer, 1969). The opposite happens on
concave slopes as water velocity and soil erosion decrease with gentler downslope
angles.

The amount of water that ﬂows over and through (vertically and laterally) soils
effects the depth and morphology of the soil. Water that vertically percolates through
the soil can leach salts, elements, and oxides in soil-solution as well as translocate silts
and clays, which leads to development and deepening of the soil proﬁle. Overland
water ﬂow causes erosion which removes material from sloping areas and deposits
them on gentler areas downslope, causing thinner proﬁles on the slopes and thicker
proﬁles in the depressions downslope. Lateral translocation downslope of silts and
clays as well as salts and oxides and hydroxides of A1, Fe, Mn, and Si in throughﬂow
water has also been observed (Glazovskaya, 1968; Huggett, 1976).

Much research has attempted to relate processes to the occurrence of soils on
speciﬁc landscape positions (Acton, 1965; Beckett, 1968; Ruhe and Walker, 1968;
Walker and Ruhe, 1968; Malo et al., 1974; Huggett, 1975; Conacher and Dalrymple,
1977; Davidson, 1977; Krikby, 1977; King et al., 1983). Ruhe (1960) developed the

19

most widely used system for describing landscape units. These include the summit,
shoulder, backslope, footslope, and toeslope. On summits, water movement in soils is
predominantly vertical, except near the transition to the shoulder. Solum thickness is
dependent upon soil permeability and amount and frequency of rainfall. As a result,
the summit is a very stable element of the landscape (Hall, 1983). Shoulder positions
are almost always convex. This increases surface runoff and decreases inﬁltration,
resulting in a highly erosional and unstable surface with thin soil proﬁles. Lateral mass
movement downslope of surface material (soil creep) may occur. Lateral throughﬂow
may also be an important process within this position (Hall, 1983). Lateral transport
of water and material (both surface and subsurface) is very important on and within
the backslope position. Soil creep may also occur. If the backslope is relatively
smooth, surface transport of material will be uniform. The soils of the backslope are
thinner than the other hillslope elements except the shoulder. Footslopes are almost
always concave, resulting in increased inﬁltration and deposition of material.
Thickness of soil proﬁles vary, but tend to increase downslope. Toeslope positions are
constructional in nature and thus unstable. Alluvial material from up valley and/or the
adjacent footslopes are frequently being deposited on this position, resulting in very

thick A horizons.

SOIL SPATIAL VARIABILITY AND GEOSTATISTICS

Soil variability consists of systematic and random components (Trangmar et al.,
1985). Wilding and Drees (1983) describe systematic soil variation as a gradual or
distinct change in soil properties as a ﬁrnction of landform, geomorphic elements and
soil forming factors, and/or man induced management. Observed differences in soil
properties that cannot be related to known causes is termed "random" variation.
Systematic soil forming processes and landscape element position determine soil

occurrence. As such, classical statistics may not be appropriate to analyze soil

:‘V

and

20

properties, which vary spatially. The theory of regionalized variables (Matheron,
1971), the basis for geostatistics, takes into account both systematic and random
variation of spatially distributed variables.

Interpolation of spatially dependent variables was ﬁrst developed by Krige (1966)
to estimate gold content of ore deposits in the South Aﬁican mining industry. Krige's
procedures were expanded by Matheron (1971) into the theory of regionalized
variables which forms the basis of techniques for estimation of spatially dependent
variables. These techniques are known as geostatistics.

Geostatistics are founded on three concepts; regionalized variables, random
functions, and stationarity. If a set of a measured property of individuals is
characterized by some probability distribution law, then it is a random variable (2).
Examples of random variables in soil research include percent clay, pH, organic matter
content, and bulk density. If the value of the random variable is dependent on the
position (x) it was sampled, it is a regionalized variable and its location can be used in
statistical analysis. If an inﬁnite set of random variables are considered with their
sample locations, then the regionalized variable becomes a member of an inﬁnite set of
random variables for all locations within the considered region (Trangmar et al.,
1985). Such a set is called a random function Z(x).

If the expected value of the random function Z(x) is the same in all locations in the
considered region, then it has ﬁrst-order stationary. Expressed statistically

E[Z(x)] = m = mean
and
E[Z(x)-Z(x+h)] = 0
where h is the vector of separation between sample positions, termed the lag (Figure
1.2) (Trangmar et al., 1985).
For all observation pairs separated by lag h, the intrinsic hypothesis requires the

variance of the increment Z(x)-Z(x+h) be ﬁnite and independent of position within the

ill-

teed .,
”It:

 

II

in

 

f

°//

i n

éure I 3

 
 
  

21
I I I I
I I I
Lag 1 .§o Lag 1.4
.eeeeeeee.eeeeele- I

LagZD

Figure 1.2. Portion of a hypothetical grid, illustrating

semivariance computation for given lags.
(from Johnson, 1990)

 

 

 

 

it
sm -— ................ 1k”-
15$:
Explained _
Variance I" 1.0
Nugget
Variance " Range
— T I r j t 1 1 T

 

 

 

 

O 2 4 6 8

Figure 1.3. Hypothetical semivariogram. Numbers refer to lags.
(from Johnson, 1990)

considered r

Tris deﬁb‘
their dlilde‘
mIiSIiC “h ’

01.39”” 13:

music hi?‘

I
5" M I
1313371 3110.3

there there 3
The plot (

Emir?” '
(S. a;

‘N

large). the r.
13) The sill
of reiatit e1} c
attabie ex tit

Fitch '
es the Si

.rianance

22

considered region:
VAR[Z(x)-Z(x-h)]=E[Z(x)-Z(x-h)]2
=21(h)
This describes the variance of the difference between pairs of observations, which
when divided by two, yields a per-observation variance known as the semivariance
statistic t(h). The semivariance is a measure of the average similarity between points
of a given lag distance apart. The more alike the measurements of the points are, the
smaller the semivariance (Burgess and Webster, 1980a). Semivariance provides the
basis for kriging and cokriging techniques, which are used for unbiased, optimal
interpolation between known points of data (Burgess and Webster, 1980a). When the
intrinsic hypothesis is assumed, the semivariance for a lag h distance between all
observations separated by the lag is:
t(h)=l/2Nh2 [Z(X)—Z(x+h)]2
where there are Nh sample observations separated by lag h.

The plot of semivariance versus lag distance h is known as the semivariogram. The
semivariogram consists of four basic parts; the sill, the range of spatial dependence
(range), the nugget variance (nugget), and the structural or explained variance (Figure
1.3). The sill approximates the sample variance of classical statistics, and is the region
of relatively constant semivariance. The range is the lag distance over which the
variable exhibits spatial dependence, and is deﬁned by the value at which the curve
reaches the sill. The nugget is the y-intercept value of the semivariogram. Ideally, the
semivariance at zero lag is zero, but often is not. The nugget represents unexplained
or random variance, which is caused by sampling error, or variability which cannot be
detected by the sampling scale used (Trangmar et al., 1985). The explained variance is
the portion of the total variation correlated with distance.

A continuous increase in semivariance without an apparent sill or range indicates a

broader regional trend and nonstationarity, thus not allowing for deﬁnition of a spatial

trainee. An
of spatial de;
determined a'

Plotted se
52/21131le for 1
fitting obsen
anode! are i.
19%)

Iliere are
5.9% and a

being the e-

Where Z] ‘

Z(xii

I

23

variance. An absence of spatial structure in the semivariogram indicates either a lack
of spatial dependence between sample values, or that the spatial structure cannot be
determined at the sampling scale used (Trangmar et al., 1985).

Plotted semivariance points must be ﬁtted to a mathematical model to produce
statistics for kriging procedures. There exists no set mathematical procedure for
ﬁtting observed semivariograms (Webster, 1985). In general, the criteria for choosing
a model are high correlation coeﬂieient, small nugget, and a large range (Johnson,
1990)

There are two basic kriging procedures; simple point estimation, or punctual
kriging, and average estimates for discrete areas, or block kriging. In punctual
kriging, the estimated value of the regionalized variable 2 at location x is:

n

Z'(XO)=ZLiZ(Xi)
where Z'(xo) = kriged estimate
Z(xi) = sample value
Li = weight applied to sample value Z(xi)
n = number of neighboring samples used in interpolation
The kriged estimate for point P in Figure 1.4 is calculated by multiplying each
sample value in the estimation neighborhood by its concomitant weight (Li), then sum
the results for all sample locations in the neighborhood. The fact that near sample
points carry much more weight than far samples (Figure 1.4) means that kriging is
essentially a local estimation procedure (Webster, 1985). The conﬁguration of sample
points near the estimation point can modify the effect of distance on kriging. The
eﬁ‘ect of distant samples tend to be dampened by samples near the estimation point,
and lone points have more weight than individual points found in clusters.
Soil properties are anisotropic if they do not vary in a similar manner in all

directions. The effect of anisotropy can be seen in Figure 1.4. Variance is greatest in

24

0.032 0.006 - 0.001
0.095 0.130 0.076 0.019
0.019 0.009 0.251. 0.107

-0.002. 0.005 g 0.036 0.079

0

Figure 1.4. Weights for kriging point P.
(from Webster, 1985)

’2

 

Figure 1.5. Geometric anisotropy about a sample.
(from Journel and Huijbregts, 1978)

the 100 e1 ‘11
the mon 11
115 \ersa
lfa pro;
applies to 21
occurs aroo
Limce h 11
111311011 [1;
decadence.

Hul'bt’ﬁ‘ﬂ S.

25

the lower left to top right direction, and least in a perpendicular direction, resulting in
the most weight being placed on sample points in the direction of least variability and
vis versa.

If a property varies the same in all directions, it is isotropic, and one semivariogram
applies to all parts of the study region where a circular range of spatial dependence (h)
occurs around each sample location. If the magnitude for variance of a property is at a
distance h in one direction, and a distance kh in another direction for an equivalent
variation, then the property varies anisotropically where an ellipsoidal range of spatial
dependence, elongated in the direction of minimum variance, occurs (Journel and
Huijbregts, 1978) (Figure 1.5). The anisotropy ratio k is a measure of the magnitude
of directional differences in variation, and is calculated by dividing the explained
variance by the range in the direction of greatest variation by the explained variance by
the range perpendicular to it (Trangmar et al., 1985).

In the calculation of estimates, the only difference between punctual and block
kriging is how the weighting coefﬁcients are determined. An average semivariance
between sample points and all points in a block is calculated for the determination of
sample point weight (Trangmar et al., 1985). Block kriging has the effect of
smoothing local discontinuities, which is desirable when the investigator is more
interested in regional patterns than local detail.

The spatial distribution of a variable can be closely related to that of other variables
affected by the same spatial process. Such properties are co-regionalized and are
spatially dependent on each other (Trangmar et al., 1985). Cokriging uses two or more
correlated random variables simultaneously in such a manner that the spatial
information ﬁom each parameter aids in the estimation process. If a correlation exists
between the two random variables then one method of improving the sampling
efﬁciency is to increase the sampling of the covariable with respect to the under

sampled (primary) variable. Using cokriging, the spatial information of the covariable

(Simsfetted 1‘
quahh' ofthe E
roost e...cien
line to 6.1.99?”
liftosmw 9‘ a

The co—re‘gi

21311211103311:

:lll’hitil
there .\'1' hi is
Smi's'aﬁograo
mtaszred Lt
te‘ ‘ionship hr

The prime.

ot the cox’ana

Pit kriged p

26

is transferred to the primary through the cross-correlation ﬁrnction, thus improving the
quality of the estimates of the primary variable (Yates and Warrick, 1987). Cokriging
is most efﬁciently used where one variable may not have been sampled sufficiently
(due to experimental difﬁculties, high costs, ect.) to provide enough estimates
(Trangmar et al., 1985).

The co-regionalization of variables 21 and Z2 is described by a cross-
semivariogram:

n
112(h)=(2N(h))'1Z[Z1(xi)-Zl(xi+h)][ZZ(xi)-22(xi+h)]

where N(h) is the number of pairs of variables separated by vector h. The cross-
semivariogram is calculated using only the locations where both variables are
measured. Unlike semivariances, cross-semivariances can be negative if the
relationship between the primary and covariables are negative (Trangmar et al.,1985).

The primary variable is calculated as the weighted average of the observed values
of the covariable and primary variable that occur in the estimation neighborhood at
each kriged point:

n1 n2
Z'2(xo)=ZLiZ 1 (X1 )+ZL222(X2)

where L1 and L2 are the weights associated with Z1 and 22, and n] and n2 are the
number of neighbors of Z] and Z2 involved in estimating Z'2 at each xo location
(Trangmar et al.,1985). The above equations can be extended to include additional
covariables.

Kriging has been used to evaluate soil variability for soil delineation of map units
(Burgess and Webster, 1980a, b; Webster and Burgess, 1980; McBratney and
Webster, 1983; Ovalles and Collins, 1988; Di et al., 1989; Webster and Oliver, 1989;
McBratney et al., 1991). Kriging has also been used to spatially quantify soil chemical

properties (Yost et al., 1982; Samra et al., 1988), soil structural properties (Reinert,

27

1990), and soil hydraulic properties (Vieira et al., 1981; Van Kuilenberg et al., 1982;
Russo and Bresler, 1982).

Yates and Warrick (1987) and Mulla (1988) used soil surface temperature with
sand content and penetrometer resistance, respectively, as covariables to cokrig for
soil water content. Nash et al. (1992) cokriged for vegetative cover using soil
moisture as the covariable. Stein et a1. (1988) used mean high water table as the

covariable to estimate soil moisture deﬁcit.

me:

28

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Amemiya, M. 1970. Land and water management for minimizing sediment. In
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Baier, W., D.Z. Chaput, A. Russello, and W.R. Sharp. 1972 Soil moisture estimator
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Baver, L.D. 193 7. Soil characteristics inﬂuencing the movement and balance of soil
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Beasley, RS. 1976. Contribution of subsurface ﬂow from the upper slopes of
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Belmans, C., J .C. Wesseling, and RA. Feddes. 1983. Simulation model of the water
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Cr

'3

’

he:

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Chorley, R]. 1978. The hillslope hydrological cycle. In Krikby, M.J. (Ed), Hillslope
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Davidson, DA. 1977. The subdivision of a slope proﬁle on the basis of soil
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Emmett, W.W. 1970. The hydraulics of overland ﬂow on hillslopes. U.S. Geol.
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Francis, PE, and J .D. Pidgeon. 1982. A model for estimating soil moisture deﬁcits
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Freeze, R.A. 1972. Role of subsurface ﬂow in generating surface runoff. II.
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Freeze, RA. 1974. Streamﬂow generation. Rev. Geophys. Space Phys. 12:627-647.
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Gilrnan, K., and MD. Newson. 1980. Soil pipes and pipeﬂow. Br. Geomorph. Res.
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Glazovskaya, MA. 1968. Geochemical landscapes and types of geochemical soil
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Hall, GP. 1983. Pedology and geomorphology. In Wilding, L.P., NE. Smeck, and
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31

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Pot

Rea.

32

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Ii.-

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117;:

33

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Engr. 21:59-64.

34

CHAPTER 2

SPATIAL VARIABILITY OF SAND, SILT, AND CLAY CONTENT, AND
HORIZON THICKNESS OF SOILS WITHIN A SLOPING LANDSCAPE

ABSTRACT

Spatial studies of soil properties have been primarily conducted on relatively level
landscapes. This study determined the spatial relationships of selected important soil
morphological properties within a sloping landscape. Soil proﬁles of Kalamazoo loam
(ﬁne-loamy, mixed, mesic, Typic Hapludalfs), from a 52 by 34 meter area with 4.25 by
4.00 meter grid cells on a sloping landscape (backslopes range ﬁ'om 4.6 to 5.6 %) at
Kellogg Biological Station in southwest Michigan were described and sampled.
Statistical and geostatistical analyses were performed on percent organic carbon of the
Ap horizon, percent sand, silt, clay, and thickness (cm) of the Ap, Btl, and 2Bt2
horizons, and amount of clay (kg) in the Btl , ZBt2, control-section, and soil proﬁle.
The range of spatial dependence for the soil properties varied from 6.4 to 26.1 meters.
All soil properties, except the 2Bt2 horizon properties, exhibit anisotropy associated
with slope direction. The Ap horizon of the lower backslope, footslope, and toeslope
displayed greater mean thickness, percent silt and organic carbon, relative to the
summit and upper backslope position Ap horizons. The Btl horizon and control-
section displayed a greater mean percent silt and clay below the middle of the
backslope. Solum thickness increased downslope from the upper backslope to the
toeslope. These results indicate erosional and depositional processes may have
aﬂ‘ected the morphology of the Ap and Btl horizons. Differential glacio-ﬂuvial sorting
of material at each position of the landscape and water movement on and through the
landscape likely caused the diﬁ‘erences in soil proﬁle morphology at different positions

of the landscape.

35

INTRODUCTION

Topography plays a major role in processes that create soil variability within a
landscape (Gerrard, 1981; Jenny, 1941; Ruhe, 1960). In order to understand how
topography controls the distribution of soil properties within a landscape, the spatial
relationships of these variables need to be examined. An increased knowledge of
spatial variability of soil properties can enhance interpretation of soils and lead to a
better understanding of the complex topographical-soil relationships.

Soil forming processes do not behave uniformly but vary with hillslope component
(Hall, 1983; Ruhe, 1960). Soil thickness and particle-size distribution are highly
related to slope position (Acton, 1965; King et al., 1983; Merrnut et al., 1983; Miller
et al., 1988). Soil thickness and particle size distribution effect water holding capacity,
nutrient supply, and rooting depth. Hanna et al. (1982) found water content to be
greatest in the backslope and footslope position soils, and least in the summit and
shoulder position soils.

Geostatistics is a very useful approach to study spatial variability of soils
(Trangmar et al., 1985; Webster, 1985). Although many studies involve spatial
variability of soil physical properties on relatively level landscapes (Campbell, 1977,
1978; Burgess and Webster, 1980; Gajem et al., 1981; Vieira et al., 1981) there have
been few spatial studies conducted on sloping landscapes (Miller et al., 1988).

It is the hypothesis of this study that landscape position controls soil formation (i.e.
organic matter accumulation, formation of soil horizons and soil structure, and clay
translocation) which effects soil morphological properties. The objective of this study
was to characterize the spatial variability of selected important soil morphological

properties within a sloping landscape of southwest Michigan.

36

MATERIALS AND METHODS
Study Site

The study was conducted at the WK. Kellogg Biological Station (KBS) in
southwest Michigan. KBS is situated on a pitted outwash plain and the major soils
found there are Kalamazoo Loam (F ine-loamy, mixed, mesic, Typic Hapludalfs) and
Oshtemo Sandy Loam (Coarse-loamy, mixed, mesic, Typic Hapludalfs) (Figure 2.1).

, Both soils are well drained. A typical Kalamazoo soil proﬁle from the study site has a
loam Ap horizon, from O to 20 cm, a loam E horizon , from 20 to 25 cm, a clay loam
Btl horizon, ﬁ'om 25 to 56 cm, a sandy loam ZBt2 horizon, from 56 to 112 cm, and a
3E/Bt horizon of sand and loamy sand lamellae, from 112 to 150 cm. A typical
Oshtemo soil proﬁle from the study site has a sandy loam Ap horizon, from O to 18
cm, a sandy loam Btl horizon from 18 to 56 cm, and a 2E/Bt horizon of sand and
loamy sand lamellae, from 56 to 150 cm. Both soils probably formed in glacio-ﬂuvial
outwash in which the parent material becomes coarser with depth. The area was
deglaciated approximately 14,000 b.p. (Wayne and Zumberge, 1965).

The study site was located on a west facing slope with distinct summit, backslope
(4.6% to 5.6% slopes), and toeslope components (Ruhe, 1960) (Figure 2.2). There is
no distinct shoulder component to this landscape, as the upper portion of the

backslope is linear, except near the transition to the summit. The location of the slope

units are given in Table 2.1.

Table 2.1. Location of slope units at the study site.

Slope Position Position east of west border of site Width of slope position
---Meters--- Meters

Summit 27.6 to 34.0 4.0

Upper Backslope 19.1 to 27.6 2.4

Lower Backslope 6.4 to 19.1 12.7

Footslope 4.0 to 6.4 8.5

Toeslope 0.0 to 4.0 6.4

37

Os htemo

Depth

Kalamazoo

Depth

Texture

cm

Texture

cm

SL

LS

LS

LS

L5

L5

 

 

 

Btl

ZE/Bt

 

 

 

 

 

 

 

 

 

 

 

 

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0000000000000000000000
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0 00000000000000 00000
.0000000000000000000000.
000 0000000000000 00000
v000000000000000000000 0000.
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.000 00. .000000000L
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....... A .%.~.....
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0.000000000000000000000
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0000000000000000 00000
- 000000 0 0 0000000 0 00000.
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00 00000 00 00 0000.
000000000 00 00 00000
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00005000 000 000000
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.wkannnn.
0

.56

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S

LS

150

 

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0 I I
:-'::-‘.-:-.-. .
I
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.
0 00 0 0 0 00 00 0
...... ..............................

1.6%.". .

 

O

0
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3E/Bt

 

 

 

 

 

 

112

150

Figure 2.1. Typical Kalamazoo and Oshtemo soil proﬁles.

38

 

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39

A 34 meter by 68 meter rectangular grid of sampling points was established on the
site, using a 4.25 meter (east-west) by 4 meter (north-south) grid cell. Grid points
were located and ﬂagged using a WILD Distomat and Theodolite (Total Station), and
elevations were recorded for topographic map production. The raw survey data were
converted to coordinate data using the WILDSOFT computer program (Wild
Heerbrug Instruments, Inc., 1987). Soil descriptions and samples at each point were
taken using a Giddings hydraulic probe mounted on a pickup truck. Additionally, soils
were sampled at 2 meter intervals on the north and south boarders of the site. This
made for a total of 180 soil proﬁles sampled. Soil proﬁles were described using
standard procedures (Soil Survey Staff, 1984) and sampled to a depth of 150 cm, or to
the base of the ZBtZ horizon if it was deeper than 150 cm. Percent sand, silt, and clay,
of the samples were determined by a hydrometer method (Grigal, 1973). The percent
organic carbon of the Ap horizon samples were determined colormetrically by a
routine organic matter method (Graham, 1948).

In order to delineate the Kalamazoo and Oshtemo soils on the landscape, a map of
the control-section clay content, the average clay content of the upper 50 cm of the
argillic horizon, or the entire argillic horizon if less than 50 cm thick (Soil Survey
Staff, 1975), was generated for the study site (Figure 2.3) using geostatistical methods
(Trangmar et al., 1985; Webster, 1985). The 18% clay line separates Kalamazoo soils
which are classiﬁed as ﬁne-loamy, from Oshtemo soils, which are classiﬁed as coarse-
loamy. Most of the Oshtemo soils occur in the north 12 meters of the site.

Statistical Approach

In order to perform statistical analyses on a single sample population where
topography alone regulates the major trends, the soil samples from the north 16 meters
were eliminated from ﬁrrther examination (Figure 2.3), leaving 135 soil proﬁles for

statistical analyses.

 

South - North (m)

 

‘Q _.
p
l l

 

 

 

32

West - East (m)

Figure 2.3. Control-section percent clay of the study site.

 

ll!

0

136‘
l“
1‘.
4:3, 4_
but]
‘
' I
GI

41

Statistical analyses were performed on the percent organic carbon of the Ap
horizon; percent sand, silt, and clay, of the Ap, Btl, and 2Bt2 horizons; percent clay in
the control-section; thickness of the Btl, 2Bt2, and solum (the surface to the base of
the 2Bt2 horizon in this study); and amount of clay (kg) in the Btl, ZBt2, control-
section, and soil proﬁle (0 to 150 cm). These variables were chosen for study because
of there relationship to soil development and water holding capacity.

Each variable was ﬁrst subjected to classical statistical analysis to obtain the mean,
variance, standard deviation (SD), and coefﬁcient of variation (CV) of each horizon.

‘ Mean and SD of the variables within each landscape position were calculated. A one-
way ANOVA was performed on each variable for all ﬁve landscape positions to
determine if the means of the variable were signiﬁcantly different, and least signiﬁcant
difference (LSD) values were obtained to determine which means of the variable were
signiﬁcantly different. The degree of spatial variability for each variable was
determined by geostatistical methods (Trangmar et al., 1985; Webster, 1985). A
semivariogram for each property to ascertain the degree of spatial variability between
neighboring observations, and a appropriate model was ﬁt to the semivariogram. The
semivariance is a measure of the average similarity between points of a given lag
distance apart. The more alike the measurements of the points are, the smaller the
semivariance (Burgess and Webster, 1980).

The plot of semivariance versus lag distance, 11, is known as the semivariogram.
The semivariogram consists of four basic parts; the sill, the range of spatial
dependence (range), the nugget variance (nugget) and the explained variance (Figure
2.4). The sill approximates the sample variance, and is the region of relatively
constant semivariance. The range is the distance over which the variable exhibits
spatial dependence, and is deﬁned by the value at which the curve reaches the sill. The
nugget is the y-intercept value of the semivariogram. The nugget represents

unexplained or random variance, which is caused by sampling error, or variability of

42

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43

the variable which cannot be detected by the sampling scale used (Trangmar et al.,
1985). The explained variance is the portion of the total variation correlated with
distance.

Plotted semivariance points must be ﬁtted to a mathematical model to produce
statistics for kriging procedures. There exists no set mathematical procedure for
ﬁtting observed semivariograms (Webster, 1985). In general, the criteria for choosing
a model are high correlation coefﬁcient, small nugget, and a large range. Semivariance
data in this study were ﬁtted to exponential, spherical, linear, and gaussian models.
Semivariance provides the basis for kriging and cokriging techniques, which are used
for unbiased, optimal interpolation between known points of data (Burgess and
Webster, 1980). Semivariograms and block kriging interpolation data for each
variable were calculated using GEOPACK (Yates and Yates, 1989). Each property
was block-kriged with the statistics generated by the chosen semivariogram model. A
width of two meters was chosen for the block size, which deﬁned 486 blocks within
the study area. A maximum search radius of 62. 13 meters was used, and the 16
nearest data points ("neighbors") were used for kriging. The generated block kriged
data for each variable was gridded in SURFER (Golden Software, 1989). The gridded

estimates were used to produce maps of the variables with SURFER.

RESULTS AND DISCUSSION

The distributions for the studied variables of the south 52 meters of the site , under
visual inspection, were approximately normal (Figures 2.5 to 2.11) except for the
amount of sand and silt in the 2Bt2 horizon, which were eliminated from geostatistical
analysis. The descriptive statistics for the soil properties studied are given in Table
2.2. Johnson (1990) found similar mean, SD, and CV values for percent clay of the
Btl (25.6, 4.5, and 17.6 %, respectively) and 2Bt2 (10.0, 3.0, and 30.0 %,

 

Ap Clay (°/o)

 

 

 

      
 

   

     
   
     

  

    

 

 

 

 

 

 

n «m u
N a s u .4.
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s§\\\\\\\\\\\\\\\\\a 2m H \\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\S 3W W. m
\\\\\\\\\\\\\\\\\\\\. mm w \\\\\\\\\\\\\\\\\\\\\ a m ..
xx.....\....._....._w w... \\\\\\\\m\\\\\\\\\\\\\\\\\ m P H“ SW2 6 P w 2
\\ \ 2 1
\\\\\\\\\ m B Sn 2 \\\\\\\\\.m
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. m .. m .. 6
m w m. w m w m 5 lo a w. a w w m s w m w m a m ...... m 5 o
3:302“. 3:302“. accuses“.

Percont Cl08y
Figure 2.5. Frequency of Ap, Btl, and 2Bt2 horizon percent clay.

45

Control Section Clay (°/o)

 

 

15 18 21 24 27 3O 33 36 39

 

 

Percent Clay

Control Section Clay (kg)

 

 

Sm
.\\\\\\\\\.m
\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\Sm
\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\.m

Kg Clay
Figure 2.6. Frequency of control-section percent clay and clay mass.

S\\\\\\\ o
5
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00v

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Ap Sand (%)

 

 

  

 

25 '30

 

 

   

Percent Sand

Bt1 Sand (%)

 

 

   

 

 

111111111

2Bt Sand (%)

 

 

   

   

SS”
\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\Sm
S\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\.u

5560657075

 

Percent Sa

Figure 2.7. Frequency of Ap, Btl, and ZBt2 horizon percent sand.

 

 

 

47

Ap Silt (%)

 

 

    
   

           

 

 

 

 

 

 

R.W. S u S 7
SS\\\\\\\\\\\\\\\ m n \/W S\\\\\\\\\\\\\\\\\\ a t \/W \S 5
SSSS\\\\\\\\\\\\\\\S a w... m\ .. . . .. S: - . t w ml \\\\\\\\x 4

. .. . . S\\\\\\\\\\\\\\\\\\\\S m. m m §§ m m m \ . .
. \ m \SSSSSSSSSSSSSSSS - m. SSSSSSSSSSSSSSSS ..
SSSSS M S\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\S m S\\\\S\S\\\\\\\\\\\\\\\ 1

Scene!“— >oceao£u 3:302“.

Percent Silt
Figure 2.8. Frequency of Ap, Btl, and 2Bt2 percent silt.

48

Ap Thickness

 

 

\

   

28

22

19

 

60

o mu m o o
4 3 2 1|
5:03.600“.

Horizon Thickness (cm)
Bt1 Thickness

 

 

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36 42 48 54 6O 66

30
rckness (cm)
28t Thickness

Horizon Th

4
2

8
1

O

 

 

4 q
5 o 5

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3 2 2 0| 1
35:60....

 

 

  

126

108

 
 

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SSS‘SS

90

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S
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72

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SSSS\\\\\\\\\\\\\\\\\\\\\\\\. a.
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63 61 99 117

45
Horizon Thickneea (cm)

Figure 2.9. Frequency of Ap, Btl, and 2Bt2 horizon thickness.

49

Bt1 Clay Mass

 

.\\.\\\\\\\\\.M
S\\\\\\.SSSS\\\.\\\\\\\\\\\\\.
.\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\.
S w. \\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\
SSS.SSSS\Q\\\\\\\\SS

        

 

 

210 280 350 420

140

245 315 365

Kg Clay

28t Clay Mass

175

105

 

 

 

210 240 270 300 330

   

SSSSS
SSSSSSS m
SSSSSSSSSS m
SSSSSSSSSSSS m
SSSSSSSS m

S\\\\\Sw

 
 
 
  
 

O30

 

 

4O

>05:er

Kg Clay

Clay Mass (0 to 150 cm)

 

 

 

 

Kg Clay

Figure 2.10. Frequency of Btl, 2Bt2, and soil proﬁle clay mass.

50

Organic Carbon (%)

 

 

    

1.35

S
SSSSSSSSSSSS m.
SSSSSSSSSSSSS m

5
2.
1

 
 

 

 

Organic Carbon (96)
Solum Thickness
To base of 28t2 horizon

 

 

 

 

80 100 120 140 160 180

60

90 1 10 130 150 170
Solum Thickness (cm)

70

Figure 2.11. Frequency of Ap percent organic carbon and solum thickness.

Table 2.2. Descriptive statistics for variables determined in the ﬁeld and laboratory.

 

 

V_ariable Min. Max. Mean Vaaiance SD CV (%)
O.C. (%) Ap 0.65 1.29 0.93 0.017 0.13 13.8
Clay (%) Ap 18.0 27.0 21.8 3.1 1.8 8.1
Btl 0.0 39.0 29.9 22.4 4.7 15.7
ZBtZ 0.0 26.0 13.8 13.4 3.7 26.8
Control Sec. 15.0 39.0 24.2 22.4 4.7 19.6
Sand (%) Ap 25.0 65.0 45.9 38.4 6.2 13.5
Btl 27.0 79.0 55.2 102.4 10.2 18.4
ZBt2 57.0 94.0 84.1 28.6 5.4 6.4
Silt (%) Ap 13.0 55.0 32.2 40.2 6.4 19.7
Btl 1.0 34.0 14.8 47.7 6.9 46.9
ZBt2 0.0 7.0 1.9 2.9 1.7 91.6
Thick. (cm) Ap 13.0 33.0 22.6 15.8 4.0 17.6
Btl 0.0 63.0 30.9 112.8 10.7 34.5
ZBt2 0.0 120.0 54.7 431.7 20.9 38.1
Solum 69.0 173.0 113.3 550.5 23.5 20.8
Clay (kg in m2 x m depth )
Btl 0.0 405.4 155.4 3834.0 62.2 40.0
ZBt2 0.0 326.0 123.4 2665.9 51.8 42.0
Control Sec. 120.1 321.7 199.0 1524.1 39.2 19.7
0 to 150 cm 275.8 633.9 405.2 5023.4 71.1 17.6

52

respectively) horizons on a relatively level landscape at KBS. Johnson also found
similar means for control-section clay (20.4%) and Btl thickness (34.1 cm), but
greater SD and CV values (6.0 and 29.9 percent for control-section clay content and
18.3 and 53.7 percent for Btl thickness) for these variables. The mean ZBt2 thickness
of Johnson's study was less (43.1 cm) while the SD and CV values were substantially
greater (28.1 and 65.9 %). The greater SD and CV values of these variables in
Johnson's study could be due to the larger study area (440 by 140 meters) and sample
grid cells (20 by 20 meters). Also, Johnson's study had both Kalamazoo and Oshtemo
soils in the data set, and exhibited a bimodal population, which may contribute to the
greater SD and CV values of control-section clay content.

The descriptive statistics for the soil properties as a ﬁrnction of landscape position
are given in Table 2.3. There is no signiﬁcant difference (or = 0.05) between the means
of all the slope positions for the ZBtZ thickness and 2Bt2 amount of clay (kg),
therefore LSD values were not calculated for those variables. Organic carbon
displayed a small but steady increase ﬁ'om the upper backslope to the toeslope soils.
Ovalles and Collins (1986) and Miller et al. (1988) found a similar trend from the
summit to backslope soils and the shoulder to the toeslope soils, respectively. The
summit and upper backslope position Ap horizons have signiﬁcantly less O.C. than do
those of the footslope and toeslope positions. The lower backslope position Ap
horizons have signiﬁcantly less O.C. than those of the toeslope positions. This may
reﬂect the greater amount of water which enters the soils on the lower portions of the
landscape via surface and subsurface run-on from upslope and throughﬂow (Rosek
and Crum, 1994). The mean percent sand in the Ap horizon of the toeslope position is
signiﬁcantly less than in Ap horizons of upslope positions. The percent sand in the Btl
horizon of the lower backslope, footslope, and toeslope positions are signiﬁcantly
lower than the Btl horizon of the upper backslope position. The ZBtZ horizon of the

upper backslope had signiﬁcantly more sand than the 2Bt2 horizon of the footslope

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54

and toeslope positions. The trend of percent sand to decrease downslope could be due
to glacio-ﬂuvial sorting of the parent material at the time of deposition. This trend in
the Ap horizon could also be due to erosion, where the silt fraction is transported
downslope, increasing the proportion of sand in the summit and backslope soils and
decreasing the proportion of sand in the toeslope soils.

The trend of percent silt of the Ap, Btl, and 2Bt2 horizon, with landscape position,
is to increase downslope. The toeslope position Ap horizons have signiﬁcantly more
silt than Ap horizons upslope of the footslope position. The Btl horizon of the
summit and upper backslope have signiﬁcantly less silt than the Btl horizons of
downslope positions. The 2Bt2 horizon of the upper backslope position had
signiﬁcantly less silt than of the toeslope position. This is further indication that
differential glacio-ﬂuvial sorting occurred at deposition. Also, there is evidence of
erosion and transportation of the silt ﬁ'action, which is the most highly erodible
ﬁ'action (Hjulstrom, 193 9), from the soils of the summit and upper backslope positions
to the footslope and toeslope.

There are statistically different means of Ap percent clay, but the differences are
small, and the signiﬁcance is most likely due, in part, to the low CV (8.1 %) of this
variable. The mean percent clay of the Btl horizon of the upper backslope position is
signiﬁcantly less than mean percent clay of downslope positions. The summit position
mean percent clay of the Btl horizon is signiﬁcantly less than the lower backslope Btl
mean percent clay. The mean percent clay of the Btl horizon is least in the upper
backslope position, greatest in the lower backslope, footslope, and toeslope positions,
with the summit mean clay percent between the upper backslope and lower slope
positions. The mean percent clay of the ZBt2 horizon and control-section of the upper
backslope position is signiﬁcantly less than the footslope and toeslope, and lower
backslope and toeslope positions, respectively. The percent clay in the argillic horizon

of this landscape appears to decrease from the summit position to the upper backslope

55

position and increase downslope. Malo et al. (1974) found a similar pattern of percent
clay in the solum of a toposequence within a glacial till plain of North Dakota (the
shoulder position of their study is analogous to the upper backslope position of this
study).

The Ap horizon of the footslope and toeslope positions is signiﬁcantly thicker than
the Ap horizon thickness of the upslope positions. This is further evidence that
erosion and transport from the upper backslope to the footslope and toeslope positions
has taken place. The Btl horizon of the toeslope horizon is signiﬁcantly thicker than
the upper backslope Btl. There are no signiﬁcant differences in ZBtZ horizon
thickness associated with landscape position. The mean solum thickness decreases
ﬁ'om the summit to the backslope positions, and then increases downslope. The
toeslope position mean solum thickness is signiﬁcantly greater than the upper and
lower backslope solum thickness. The greater solum thickness of the footslope and
toeslope positions is due to a thicker Ap horizon, the presence of an B horizon in most
soil proﬁles (Appendix 1), and a thicker Btl horizon. King et al. (1983) noted solum
thickness increases greatly below the point downslope where the slope becomes
concave. In this study, the slope becomes concave at the backslope-footslope
juncture. The trend in Btl and solum thickness may be due to water moving from the
upper backslope position via overland ﬂow and subsurface lateral downslope
throughﬂow of water to the footslope and toeslope soils (Rosek and Crum, 1994),
increasing the amount of leaching and translocation of clay in the footslope and
toeslope soils. This is indicated by the presence of E horizons in the footslope and
toeslope positions.

The mean amount of clay (kg) in the Btl, control-section, and soil proﬁle (0 to 150
cm) decreases from the summit to the upper backslope, and then increases downslope,
with the footslope position having slightly less clay in the Btl and control-section than

the lower backslope. The mean amount of clay in the Btl horizon of the toeslope

56

position is signiﬁcantly greater than in the upper backslope position. The mean
amount of clay in the control-section of the upper backslope is signiﬁcantly less than
the lower backslope and toeslope positions. The mean amount of clay from O to 150
cm in the upper backslope position is signiﬁcantly less than in the downslope positions.
The mean amount of clay from O to 150 cm in the summit position is signiﬁcantly less
than in the toeslope position. The trends of the mean amount of clay as a ﬁinction of
landscape position noted above are probably due to both differential glacio-ﬂuvial
sorting which may have occurred between the landscape positions at deposition, and
pedogenic clay translocation. Water moving from the backslope via overland ﬂow and
subsurface downslope lateral throughﬂow could transport clay to the soils downslope.
Glazovskaya (1968) observed lateral subsurface translocation of silt and clay in
throughﬂow water. Overland ﬂow ﬁ'om upslope can also transport clay, which can
inﬁltrate into the soils of the lower backslope.

The semivariograms for the soil properties are presented in Figures 2.12 to 2.14.
The spatial dependence of the soil properties are summarized in Table 2.4. The
"explained" variation (that portion of the total variation correlated with distance)
ranged from 27.7 to 100 percent. The "unexplained" variation is attributable to the
nugget variance. The range of spatial dependence values were adequately large to
provide for valid block kriging within the 4.25 by 4.00 meter grid cells. All variables
except the ZBt2 horizon properties exhibited signiﬁcant cast-west anisotropy (Journel
and Huijbregts, 1978). This is expected since the slope components are aligned in the
north-south direction, and the greater amount of variability should occur up/down
slope. The absence of anisotropy for the 2Bt2 horizon variables indicate these
processes affecting these variables are acting somewhat independent of landscape
position. Fewer signiﬁcant differences among the 2Bt2 variables occur than for other

soil layers (Table 2.3). Miller et al.(1988) found Ap percent sand, silt, clay, silt + very

Somlvurlanco (96 Clay) " 2

Semivariance (96 Sand) " 2

Semivariance (96 Sllt) " 2

57

Percent Clay

 

25

20'

15"

 

 

10‘

 

 

 

o 5 1? 115 2'0 25 so
Lag (meters)

Percent Sand

 

140

120q

100*

80‘

 

 

 

 

o 5 1'0 1'5 2'0 25 30
Lag (meters)

Percent Silt

 

70

501
401
30‘

205

 

 

10‘

 

 

 

o 3 1'0 1'5 20 25 30
Lag (meters)

 

[-Ap x811 A280]

 

Figure 2.12. Semivariograms for Ap and Btl percent clay, sand, and silt;
and ZBt2 percent sand and silt.

58
Ap Organic Carbon (%)

0.022 ;

0.02‘
0.018"
0.016“
0.014‘1
0.0121

0.01-
0.0082
0.006‘
0.004
0.002‘

 

 

Semivariance (96 0C) " 2

 

 

 

o 5 1'0 15 {o 25 30
Lag (meters)

Thickness of Soil Layer

 

700
630-
560-
490‘
420- .
350«
2801
21 o‘
140‘
70-

__¥__‘l_ 4.; A A
o r fs—ﬁ—iv
T

0 1'0 1'5 2'0 25 30
Lag (meters)

L+ Ap - an A 2&1

Solum Thickness
To base of 2Bt2 horizon

Semivariance (cm) " 2

 

 

 

 

 

 

 

700

630% +

5601 +

490‘ '0'

420‘

350‘

280‘

210‘

140J
70"

Semlverlence (cm) " 2

 

 

 

I

o 5 1 o 75 2‘0 25 30
Leg (meters)

Figure 2.13. Semivariograms for Ap percent organic carbon; Ap, Btl, ZBt2,
and solum thickness.

59
Control Section Percent Clay

 

24

20‘

16‘

 

121

Semlverlance (96 Clay) " 2

 

 

 

0 5 1'0 1'5 20 2‘5 30
Leg (meters)

Clay Mass (kg)

400

 

 

35° " + + ‘ 4-
300« t
250- " '

 

200‘

 

150‘ ‘ — L A a

Semivariance (kg) " 2

100‘
50‘

 

 

 

o 3 1'0 1'5 2‘0 25 30
Leg (meters)

 

‘0' Btl I 28t A Control Section 1

Clay Mass (kg)
0-150 cm

 

 

 

5000 ‘

4000‘

3000‘

2000‘

Semivariance (1:9)" 2
v

1000‘

 

 

 

o 5 1'0 15 20 25 30
Leg (meters)

Figure 2.14. Serrrivariograms for control-section percent clay, Btl, ZBt2,
control-section, and soil proﬁle clay mass.

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61

ﬁne sand, organic carbon, and thickness to be isotropic for soils on a sloping
landscape.

Johnson (1990) found a similar nugget and sill (3.7 and 19.0 (% clay)2) of the Btl
clay content for a relatively level landscape at KBS, though the range of spatial
dependence (22.9 meters) is more than twice that of this study. Johnson found little
spatial dependence for the 2Bt2 clay content. Johnson found the Btl and 2Bt2
thickness (cm) exhibited substantially greater sill (315.9 and 837.2 cm2) and range
(11.7 and 27.5 meters) values than those of this study. The nugget value in J ohnson's
study for the Btl thickness was much lower (0.0 cmz), while much higher for the ZBt2
thickness (125.6 cm2). The greater range of spatial dependencies Johnson found were
most likely due to the level landscape and larger sample grid cells (20 by 20 meters) of
that study. Reinert (1990) found the range of spatial dependence for Ap bulk density,
porosity, and saturated hydraulic conductivity was from 10.2 to 43.2 meters on a
relatively level landscape at KBS. All ranges of the soil properties were greater than
the width of the footslope and toeslope positions that were sampled, and most ranges
were greater than the width of the portion of the summit position that was sampled.

Maps of the soil properties for the south 52 meters of the site, generated by
kriging, are presented in Figures 2.15 to 2.31. The kriged estimation maps indicate a
progressive downslope increase in Ap percent organic carbon, percent clay in the Btl
and control-section, percent silt in the Ap and Btl, thickness of the Ap, and amount of
clay (kg) in the Btl, control-section, and soil proﬁle from O to 150 cm. These
variables decrease from the summit to lower backslope in the south 12 to 16 meters of
the site. Kriged estimation maps of Ap and Btl percent sand (Figures 2.20 and 2.21)
indicate a progressive downslope decrease, except the south 12 to 16 meters, where
percent sand increases from the summit to the upper backslope. Most of the increase
in Ap percent organic carbon, silt, and thickness (cm), and decrease in Ap percent silt,

occurs at the toeslope, footslope, and lower backslope positions. This indicates

 

 

 

 

 

st (m)

3..
r.

I

 

4o

32

24

63

 

    

 

 

as:

 

   

15

West - East (m)

Figure 2.16. Block-kriged map of Ap horizon percent clay.

South - North (m)

:0
..

 

64

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4.

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.

  

 

 

 

 

West - East (m)

Figure 2.17. Block-kriged map of Btl horizon percent clay.

 

 

 

 

 

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16

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West - East (m)
Figure 2.19. Block-kriged map of control—section percent clay.

South - North (m)

.r.

67

 

Lo k» 448

/
,9— 4O

 

 

 

 

 

C57 X
is}:

\:// 8

West - East (m)

 

 

 

 

Figure 2.20. Block-kriged map of Ap horizon percent sand.

South - North (m)

:0

68

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West - East (m)

Block-kriged map of Btl horizon percent sand.

Figure 2.21.

I»

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69

 

 

 

 

gcmsspﬁ

 

 

 

West - East (m)

Figure 2.22. Block-kriged map of Ap horizon percent silt.

South - North (m)

(n

 

 

 

 

 

71

 

South - North (m)

 

 

 

 

West - East (m)

Figure 2.24. Block-kriged map of Ap horizon thickness.

 

J

 

 
    

 

 

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to
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1 6 2 4 3 2
p of Btl horizon thickness.

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West - East (m)

Figure 2.26. Block-kriged map of ZBt2 horizon thickness.

(Al

(I!

74

2
3

:5 5.32 - 5:8

8

 

 

 

 

 

West - East (m)

Figure 2.27. Block-kriged map of solum thickness.

48

4O

32

24

16

8

O

75

 

          

 

 

 

48
4o
32
\ 24
O ’20 16
— m J
[)0 Q Q
9 8’ O 8
790W/// «Q /\
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m. ,/ M‘W? f0
0 8 16 24 32

West - East (m)

Figure 2.28. Block-kriged map of Btl hon'zon clay mass.

South - North (m)

I.

A»

76

:5 5.52 - 5.3m

 

 

 

 

 

West - East (m)

Figure 2.29. Block-kriged map of 2Bt2 horizon clay mass.

U

U

77

 

 

 

 

Figure 2.30

 

West - East (m)

. Block-kriged map of control-section clay mass.

South - North (m)

78

 

 
    
 
  

80:

 

 

 

 

 

M

West - East (m)

Figure 2.31. Block-kriged map of soil proﬁle clay mass.

South - North (m)

79

deposition of Ap material via overland ﬂow from upslope may be signiﬁcant,
increasing the Ap thickness and amount of organic carbon and silt at the lower
backslope, footslope, and toeslope positions relative to the upper backslope and
summit positions. Most of the increase in Btl percent clay and decrease of Btl
percent sand occurs at the middle of the backslope. This may be due to glacio-ﬂuvial
sorting of material differentially, above and below the middle of the backslope at
deposition; and/or increased inﬁltration of water at the middle of the backslope and
downslope via overland ﬂow and subsurface lateral downslope throughﬂow ﬁom
upslope, which could increase the amount of clay translocated to the Btl of the lower
portion of this landscape.

In the north 36 to 42 meters of the site that was studied, clay content decreased
downslope. Since the summit portion of the study site is near the transition to the
backslope, surface and subsurface lateral downslope movement of water may be
occurring (Hall, 1983), causing reduced leaching and clay translocation. Incorporation
of the Btl into the Ap of the upper backslope (no E horizons exist in the upper
backslope position soils, Appendix 1), could have increased the clay percentage of Ap
horizon at that position. Increased wetting and drying cycles may have contributed to
the upper backslope Btl having a greater clay content than the summit. Hall (1983)
noted summit soils have less distinct horizonation, and thicker and more continuous
cutans occur on ped surfaces of backslope than summit argillic horizons.

The 2Bt2 horizon thickness and amount of clay (kg), and solum thickness did not
vary with depth (Figures 2.26, 2.27, and 2.29). In the center and north portions of the
site, there appear to be "ﬁmnels" for preferential water flow, as indicated by relatively
deep solum depths in irregular circular patterns on the backslope (Figures 2.26 and
2.27). This is also expressed with a greater amount of clay in the 2Bt2 horizon
(Figure 2.29). Mokma and Doolittle (1993) observed the common occurrence of

"ﬁlnnels" expressed in soil proﬁle segments of southwest Michigan.

Ta

Clay “(2)

(Tong/f
0 [0 I

80

The pooled block estimation variances of the kriged soil properties are given in
Table 2.5. The kriging estimation variances display either a repetitive spatial pattern,
which is characteristic of grid sampling, as shown by the estimation variance of Ap
clay content in Figure 2.32; or a relatively smooth spatial pattern where the variance is
much greater at the edges and corners of the ﬁeld, where less variable data is available
for kriging, as shown by the estimation variance of Ap silt content in Figure 2.33. The
south border of the site has much lower estimation variances (Figures 2.32 and 2.33)
backslope at deposition; and/or increased inﬁltration of water at the middle of the
backslope and downslope via overland ﬂow and subsurface lateral downslope because
the 2 meter sample spacing was much closer than the 4.25 meters for the rest of the

kriged portion of the site.

Table 2.5. Pooled estimation variance of block kriging.

 

Property Pooled
Estimation

Variance

O.C. (%)2 0.0021

Clay (%)2 Ap 0.33
Btl 2.70

2Bt2 3.07

Control Sec. 3 .37
Sand (%)2 Ap 2.01
Btl 2.81

Silt (%)2 Ap 2.01
Btl 2.40

Thick (cm)2 Ap 1.59
Btl 25.30

ZBt2 85.68

Solum 19.31

Clay (kg)2 Btl 395.04
2Bt2 513.00

Control Sec. 60.95

0 to 150 cm 679.73

(Z C/oy)2

81

      
  

    
  

  
 

 

         
    

       

 

    
  
       
 
 

   
  

 

   
   
     
 
 

 

 

     

 

   

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SUMMARY AND CONCLUSIONS

The soil properties of a sloping landscape were shown to be spatially dependent.
Only the ZBt2 horizon soil properties did not display signiﬁcant anisotropy.

The results of the analyses of the soil variables indicate soil morphology is, in part,
a function of landscape position. Three processes which may have or are occurring
within this landscape probably cause differences in soil morphology at each landscape
position. Depositional processes at the lower backslope, footslope, and toeslope may
contribute to thicker Ap horizons with more silt and less sand from the lower
backslope downslope, relative to the summit and upper backslope position soils.
Diﬁ‘erential glacio-ﬂuvial sorting of material at deposition may, in part, be responsible
for the greater percent silt and clay in the soils below the middle of the backslope than
the soils upslope. Overland ﬂow and subsurface lateral downslope throughﬂow of
water may be contributing to greater solum thickness and percent clay in the Btl
horizon below the middle of the backslope by increasing the amount leaching and clay
translocation that occurs at these positions. Overland ﬂow and subsurface lateral
downslope thoughﬂow from the upper backslope can carry clay to downslope, where
it can be incorporated into the soils upon inﬁltration. Evidence of preferential water
ﬂow occuring within the study area is expressed morphologically by deep, circular

ﬂannel shaped soil proﬁles found within various parts of the landscape.

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84

REFERENCES

Acton, DP. 1965. The relationship of pattern and gradient of slopes to soil type.
Can. J. Soil Sci. 45:96-10].

Burgess, T.M., and R. Webster. 1980. Optimal interpolation and isarithmic mapping
of soil properties. I. The semivariogram and punctual kriging. J. Soil Sci.
31:315-331.

Campbell, J .B. 1977. Variation of selected soil properties across a soil boundary.
Soil Sci. Soc. Am. J. 41:578-582.

Campbell, J .B. 1978. Spatial variation of sand content and pH within single
contiguous delilneations of two soil mapping units. Soil Sci. Soc. Am. J.
41:460-464. ‘

Gajem, Y.M., A.W. Warrick, and DE. Myers. 1981. Spatial dependence of physical
properties of a Typic Torriﬂuvent soil. Soil Sci. Soc. Am. J. 45:709-715.

Gerrard, A]. 1981. Soils and landforms. George Allen and Unwin. London, p. 219.

Glazovskaya, MA. 1968. Geochemical landscapes and types of geochemical soil
sequences. Trans. 9th Int. Congress Soil Sci, Adelaide, 4:303-312.

Golden Soﬁware, Inc. 1989. SURFER Computer Program, version 4.0. Golden
Colorado.

Graham, ER. 1948. Determination of soil organic matter by means of a photoelectric
colorimeter. Soil Sci. 65: 181-183.

Grigal, DP. 1973. Note on the hydrometer method of particle-size analysis.
Minnesota Forestry Research Notes, No. 245. Univ. of Minnesota, St. Paul. 4

p.

Hall, GP. 1983. Pedology and geomorphology. In L.P. Wilding, NE. Smeck, and
GP. Hall, (eds), Pedogenesis and Soil Taxonomy. 1. Concepts and
Interactions. Elsevier, Amsterdam. p. 117-140.

Hj l

Jem

John
Journ

King

31310, L

Mennur.

Miller‘ M
an

MOkma E
SOU

‘71

Oldies. F1:
in n(
Reine”. D I
Haplt

RM. M 1..
301} u

Ruhea R ‘
Mad}.

 

85

Hanna, A.Y., PW. Harlan, and D.T. Lewis. 1982. Soil available water as inﬂuenced
by landscape position and aspect. Agron. J. 74:999-1004.

Hjulstrom, F. 1939. Transportation of detritus by moving water. In P.D. Trask,
(Ed.), Recent marine sediments. Am. Assoc. Petrol. Geol. p. 5-31.

Jenny, H. 1941. Factors of soil formation. McGraw-Hill, New York.

Johnson, B.K. 1990. Nitrate leaching potential as affected by the spatial variability of
Bt horizon morphology. MS. Thesis. Michigan State University, E. Lansing.

Journel, AG, and Ch]. Huijbregts. 1978. Mining geostatistics. Acad. Press. New
York. 600 p.

King, G.J., D.F. Acton, and R.J. St. Amaud. 1983. Soil-landscape analysis in relation
to soil distribution and mapping at a site within the Weyburn Association. Can.
J. Soil Sci. 63:657-670.

Malo, D.D., B.K. Worcester, D.K. Cassal, and K.D. Matzdorf. 1974. Soil-landscape
relationships in a closed drainage basin. Soil Sci. Soc. Am. Proc. 38:813-818.

Mermut, A.R., D.F. Acton, and W.D. Eilers. 1983. Estimation of soil erosion and

deposition by a landscape analysis technique on clay soils in southwestern
Saskatchewan. Can. J. Soil Sci. 63:727-739.

Miller, M.P., M.J. Singer, and DR. Nielsen. 1988. Spatial variability of wheat yield
and soil properties on complex hills. Soil Sci. Soc. Am. J. 52: 1 133-1 141.

Mokma, BL, and J .A. Doolittle. 1993. Mapping soils and soil properties in
southwest Michigan using ground-penetrating radar. Soil Surv. Horiz. 34: 13-
22.

Ovalles, FA, and ME. Collins. 1986. Soil-landscape relationships and soil variability
in north central Florida. Soil Sci. Soc. Am. J. 50:401-408.

Reinert, DJ. 1990. Soil structural form and stability induced by tillage in a Typic
Hapludalf. Ph.D. Dissertation. Michigan State University. E. Lansing.

Rosek, M.J., and J .R. Crum. 1994. Soil-water balance and geostatistical estimation of
soil water content within a sloping landscape. (in preparation).

Ruhe, R.V. 1960. Elements of the soil landscape. Trans. 7th Int. Congress Soil Sci.,
Madison Wisc. 42165-170.

So

Tra

V'iei

We)?

Webs:

lilLDs

Yates, 5

 

86

Soil Survey Staff. 1975. Soil taxonomy. USDA-SCS Agric Handb. 436. US. Govt.
Printing Office, Washington, DC.

Soil Survey Staff. 1984. Soil survey manual. USDA - SCS, US. Govt. Printing
Ofﬁce, Washington, DC.

Trangmar, 33., RS. Yost, and G. Uehara. 1985. Application of geostatistics to
spatial studies of soil properties. Advances in Agronomy, 38:45-93.

Vieira, S.R., J .L. Nielsen, and J .W. Biggar. 1981. Spatial variability of ﬁeld-measured
inﬁltration rate. Soil Sci. Soc. Am. J. 45:1040-1048.

Wayne, W.J., and J .H. Zumberge. 1965. Pleistocene geology of Indiana and
Michigan, pp. 63-84. In HE. Wright Jr. and D.G. Frey (ed), The Quaternary
of the United States. Princeton University Press. Princeton, NJ.

Webster, R. 1985. Quantitative spatial analysis of soil in the ﬁeld. Advances in Soil
Science, 3: 1-70.

WILDsoﬁ Surveying System Software, Version 1.3. Wild Heerbrug Instruments, Inc.
Norcross, GA. 1987.

Yates, SR, and M.V. Yates. 1989. GEOPACK: Geostatistics for waste
management. U.S. Salinity Laboratory. Riverside, CA 92501.

87

CHAPTER 3

SOIL WATER BALANCE AND GEOSTATISTICAL ESTIMATION OF
STORED SOIL WATER WITHIN A SLOPING LANDSCAPE

ABSTRACT

The amount of stored water available for crop use in a particular soil of a sloping
landscape is in part determined by landscape position. This study was conducted to
estimate water balance that occurs in soil within each slope position of the landscape,
and determine the minimum data set required to geostatistically estimate stored soil
water on a sloping landscape with a backslope gradient of 4.6 to 5.6%. Two transects
of 18 neutron probe access tubes, at 2 meter intervals, were established on a sloping
topography of Kalamazoo loam (ﬁne-loamy, mixed, mesic, Typic Hapludalfs) and
Oshtemo sandy loam (coarse-loamy, mixed, mesic, Typic Hapludalfs). Volumetric
water content of the soil was monitored approximately weekly in the spring, summer,
and autumn of 1990 and 1991 at 15, 30, 60, 90, 120, and 150 cm by neutron
attenuation. Water balance was quantiﬁed for the summit, upper backslope, lower
backslope, and footslope-toeslope positions of each access tube transect. The CERES
Maize model was used to estimate potential evapotranspiration and surface and
subsurface runoff at each position of the landscape. Soil samples ﬁ'om a 48 by 34
meter grid, with a 4.25 by 4.00 meter grid density, between the access tube transects
were used in geostatistical estimation of stored soil water within the landscape. Water
content of each sample point was estimated with CERES Maize for August 6 and
October 17, 1991 Selected stored soil water (mm per 150 cm soil depth) sample
locations were removed from the data sets, and then kriged and cokriged the data
points. Semivariograrns and cross-semivariograms for the entire data set were used to

estimate stored soil water (mm per 150 cm soil depth). The amount of soil water per

 

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150 cm soil depth throughout the study period was least within the upper backslope
position, moderate within the summit and lower backslope positions, and greatest
within the footslope-toeslope position, which was at or near ﬁeld capacity throughout
the study period. Cokriging estimation of stored soil water, using the m of soil
water per 150 cm soil depth at ﬁeld capacity as the auxiliary variable, reduced the
required sample distance to 44 meters in the direction parallel to the contour of the

slope.

INTRODUCTION

Water content in soils of sloping landscapes is controlled by elements that are both
external and internal to the soil-landscape system (Gerrard, 1981). External factors
include rainfall duration and intensity. Internal factors are determined by soil physical
properties such as soil texture and structure, amount and type of vegetation, and
topographic properties such as slope form and angle, and positional properties such as
relative height and distance from the base of the slope.

Stored soil water is an important source of plant available water for crop
production on well drained soils of southwest Michigan. When fertility, growing
season, and management practices are suﬁicient, the ability of a soil to produce crops
can be limited by the capacity of the soil to supply and store water (Leeper et al.,
1974). The amount of stored water available for crop use in a particular soil of a
sloping landscape is inﬂuenced by it's position on the landscape (F ranzrneier et al.,
1969; Hanna et al., 1982). Therefore, crop management practices and soil-moisture
simulation models should take slope position into account.

The use of changes in stored soil water content to estimate actual
evapotranspiration and drainage is well established (Hall and Heaven, 1970; Rouse,
1970; Day et a1, 1978; Mc Gowan and Williams, 1980a, b, c; Francis and Pidgeon,

89

1982a, b; Maule and Chanasyk, 1987). In sloping landscapes where surface and
subsurface runoff may be signiﬁcant, the water balance equation is as follows:
D=P+Ro-Rf-dS-ET.
where drainage of water ﬁ'om the soil proﬁle (D) is the result of the inputs of
precipitation (P) and surface and subsurface run-on ﬁ'om upslope (Ro) minus surface
and subsurface runoff (Rt), change in soil water content (dS), and evapotranspiration,
(ET). To determine ET, the amount of water that has been removed from the soil by
evaporation and transpiring plants during the time period in question, potential
evapotranspiration (PET) must be estimated. Several methods have been developed to
estimate PET, among which the Thomthwaite (1948), Penman (1948), and Priestley
and Taylor (1972) methods are widely accepted. Once PET is estimated, it is
incorporated into the water balance equation as follows:
D > 0 if:
PET<P+Ro-Rf-dS;
and
D=P+Ro-Rf-dS-PET:
D = 0, if;
PET3P+Ro-Rf-dS;
and
Et=P+Ro-Rf-dS;
where R0 = Rf from upslope.

In a sloping landscape, these equations can be used for the soils within each position of
the landscape.

Geostatistical methods using spatial correlation (i.e., the semivariogram) and kriging
estimation have been used to characterize soil-water properties (Burgess and Webster,
1980a, b; Webster and Burgess, 1980; Burgess et al., 1980; Russo and Bresler, 1981,
1982; Sisson and Wierenga, 1981; Vieira et al., 1981; Van Kuilenburg et al., 1982;

90

Vauclin et al., 1983; Byers and Stephens, 1983; McBratney and Webster, 1983;
Morkoc et al., 1985). Estimation of the amount of soil water using the amount of soil
water of samples near the estimation points (kriging) is useful when a sufﬁciently large
number of samples are taken within the landscape in question.

If the spatial relationships between soil and landscape properties (i.e., clay content,
landscape position, etc.) and soil water content can be established, then those soil and
landscape properties can be used to estimate soil water content over time, using
cokriging. The spatial distribution of a variable can be closely related to that of other
variables affected by the same spatial process. Such properties are co-regionalized and
are spatially dependent on each other (Trangmar et al., 1985). Cokriging uses two or
more correlated random variables simultaneously in such a manner that the spatial
information ﬁom each parameter aids in the estimation process. If a correlation exists
between the two random variables then one method of improving the sampling
efﬁciency is to increase the sampling of the covariable with respect to the under
sampled (primary) variable. Using cokriging, the spatial information of the covariable
is transferred to the primary through the cross-correlation ﬁinction, thus improving the
quality of the estimates of the primary variable (Yates and Warrick, 1987). Cokriging
is most efﬁciently used where one variable may not have been sampled sufficiently
(due to experimental difﬁculties, high costs, etc.) to provide enough estimates
(Trangmar et al., 1985). Unlike semivariances, cross-semivariances can be negative if
the relationship between the primary and covariables are negative (Trangmar et al.,
1985). Since cokriging requires a known cross-correlation ﬁrnction, there must be a
large number of locations where both ﬁmctions are sampled (Yates and Warrick,
1987). Vauclin et al. (1983) used sand content to improve the estimation of plant
available water content. Yates and Warrick (1987) used ordinary kriging and
cokriging in the analysis of surface soil water contents on a level landscape using bare

surface temperature and sand content as auxiliary functions. Mulla (1988) used

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91

surface temperature and penetrometer resistance as auxiliary variables in the cokriging
estimation process of soil-water content of two transects located within a sloping
landscape.

Two objectives were investigatedin this study: (1), computer model the amount of
surface and subsurface runoff and run-on using soil physical properties, precipitation
and other climatic data, changes in the amount of stored soil water, and simulated crop
growth, and calculate water balance that occurs in the soils at each slope component
within the landscape of the study site: (2) estimate stored soil water within a sloping

landscape with a minimum data set using geostatistics (kriging and cokriging).

MATERIALS AND METHODS
Study Area

The study was conducted at the W. K. Kellogg Biological Station (KBS) in
southwest Michigan (latitude 42°25' N, longitude 85°25' W). The average annual
temperature is 99°C, with Januaiy the coldest month at -4.0°C, and July the warmest
month at 228°C. The mean annual precipitation is 874 mm with 58 % occurring
during April through September (Austin, 1979).

KBS is situated on a pitted outwash plain. The study site is located where a small
north-south valley dissects a level plain. The valley ﬂoor tilts downslope north to an
outlet opening to a larger valley. The valley is approximately 4.4 meters deep and
from 90 to 140 meters wide. The study was conducted on the east side of the valley
where the slope of the backslope position ranged from 4.6 % to 5.6 %. The backslope
on the west side of the valley ranged form 8 % to 10 %. The study site consisted of
distinct summit, backslope, footslope, and toeslope components (Ruhe, 1960) (Figure
3.1). There is no distinct shoulder component to this landscape, as the upper portion
of the backslope is linear, except near the transition to the summit. The dominant soils

on this landscape are Kalamazoo Loam (Fine-loamy, mixed, mesic, Typic Hapludalfs)

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and Oshtemo Sandy Loam (Coarse-loamy, mixed, mesic, Typic Hapludalfs) (Figure
3.2). Both soils are formed in loamy material overlying sand and gravel. Because of
the presence of stratiﬁed sand and gravel from the lower soil proﬁle to the contact
with glacial till, which is approximately 15 meters below the surface, as indicated by
well logs from the area, both Kalamazoo and Oshtemo soils, which are well drained,
are found on all positions of the landscape, including the toeslope. A typical
Kalamazoo soil proﬁle from the study site has a loam Ap horizon, from 0 to 23 cm, a
loam E horizon, ﬁom 23 to 31 cm, a clay loam Btl horizon, from 31 to 59 cm, a sandy
loam 2Bt2 horizon, ﬁ'om 59 to 112 cm, and a 3E/Bt horizon of sand and loamy sand
lamellae, from 112 to 150 cm. A typical Oshtemo soil proﬁle from the study site has a
sandy loam Ap horizon, from 0 to 18 cm, a sandy loam Btl horizon from 18 to 56 cm,

and a 2E/Bt horizon of sand and loamy sand lamellae, ﬁom 56 to 150 cm.

Stored Soil Water Sampling and Analysis

Two east-west transects of neutron probe access tubes, 68 meters apart, were
established within the site (Figure 3.1). The south transect is dominated by
Kalamazoo soils, as are the summit and toeslope soils of the north transect. The
backslope of the north transect is dominated by Oshtemo soils. Eighteen access tubes
were installed at two meter intervals down each transect of the hillslope. Soil moisture
was measured approximately weekly from mid April through mid November, 1990,
and from early April through mid October, 1991. The site, which is part of a
cultivated ﬁeld, was left idle with glyphosate herbicide applied to prevent weed grth
in 1990, and was planted to corn under conventional tillage in 1991. Soil water
content was monitored, by neutron attenuation, at 30 cm intervals to a depth of 150
cm. In 1991 a 15 cm reading was added to more accurately determine near surface
soil water content. Three neutron probe calibration curves were prepared by the ﬁeld

calibration method outlined by Campbell Paciﬁc Nuclear (1984), one for the ﬁne-

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95

loamy Ap and Btl horizons of the Kalamazoo soil, a second for the coarse-loamy Ap
and Btl horizons of the Oshtemo soil and ZBt2 horizon of the Kalamazoo soil, and a
third for the sandy E/Bt horizon of both soils. The curves were developed by
averaging the volumetric moisture content and count ratio data for each of the ﬁne-
loamy, coarse-loamy, and sandy portions of all the access tubes.

The CERES Maize (version 2.1) (Jones et al., 1986) crop growth model was used
to obtain values for runoff, run-on, and potential evapotranspiration (PET). CERES
Maize uses the Priestley and Taylor (1972) model to estimate PET, and the Soil
Conservation Service Runoff Curve Number method to estimate runoff (Soil
Conservation Service, 1972).

Simulation accuracy of CERES Maize was evaluated by statistically comparing
model estimates with m soil water per 150 cm soil, averaged by slope position. Four
combinations of statistical criteria were used to asses the simulation ability of CERES
(Addiscott and Whitmore, 1987; Jabro et al., 1994). The association between
simulated and measured values was determined from the correlation coefﬁcient (r).
The average deviation of the simulated and measured values was determined by

calculating the mean difference (Md):

Md = Z(S-U)/n

where S is the simulated value, U is the measured value, and n is the number of
observations. Positive Md values indicate overestimated simulation, and negative
values indicate underestimated simulation values. A t-test was used to determine
whether Md was signiﬁcantly different ﬁom zero. The deviation of the simulated
values ﬁ'om observed values, reported on an observed mean basis was determined by

the root mean square error (RMSE):

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96

RMS =((z(s-U)2/n)0-5 x (loo/L3)

where U is the measured mean. Lower RMSE values suggest greater simulation

accuracy than higher values (J abro et al., 1994).

Grid Sampling and Analysis

A 34 by 60 meter rectangular grid of sample points was established between the
access tube transects, using a 4.25 (east-west) by 4.00 meter (north-south) grid cell
(Figure 3.3). Grid points were located and ﬂagged using a WILD Distomat and
Theodolite (Total Station), and elevations were recorded for topographic map
production. The raw survey data were converted to coordinate data using the
WILDSOF T computer program (Wild Heerbrug Instruments, Inc., 1987). Soil
sampling at each point was accomplished using a Giddings hydraulic probe mounted
on a pickup truck. This made for a total of 180 soil proﬁles sampled including the
access tube transects. Soil proﬁles of the access tube cores and grid were described
using standard procedures (Soil Survey Staff, 1984) and sampled to a depth of 150
cm, or to the base of the ZBt2 horizon if it was deeper than 150 cm. Percent sand, silt,
and clay, of the samples were determined by the hydrometer method (Grigal, 1973).

A total of 117 soil proﬁles were used in the geostatistical estimation of soil water.
Because the north 12 meters of the site consist mostly of Oshtemo soils, the north 16
meters of the site were eliminated from the study. This allowed study of a single soil
population, where only topography causes major trends. The south access tube
transect was also eliminated from this procedure because the access tubes are 2 meters
apart while the grid proﬁles are 4.25 meters apart.

Two soil moisture sampling dates, August 6 and October 17, 1991, were selected

for geostatistical estimation of soil water on the landscape. The mm soil water per 150

97

 

 

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98

cm soil depth of all soil proﬁles from the sample grid of the south 52 meters of the site
were simulated with CERES Maize (version 2.1) (Jones et al., 1986) based on the
simulation techniques for the access tube transects. The east two soil proﬁles of each
row (34 and 29.75 meters from the west edge of the site) are located on the summit,
and mm soil water per 150 cm soil depth was simulated for Hydrologic Condition B
soils (Soil Conservation Service, 1972) on 0% to 2% slopes. The two soil proﬁles of
each row (25.5 meters and 21.25 meters from the west edge of the site) are located on
the upper backslope, and mm soil water per 150 cm soil was simulated for Hydrologic
Condition C soils on 5% to 6% slopes. The three soil proﬁles of each row (17, 12.75,
and 8.5 meters from the west edge of the site) were found on the lower backslope and
mm soil water per 150 cm soil depth was simulated for Hydrologic Condition B soils
on 0% to 2% slopes. The two farthest west soil proﬁles of each row (0 and 4.25
meters from the west edge of the study site) were found on the footslope or toeslope,
and mm soil water per 150 cm soil depth was simulated for Hydrologic Condition B
soils on 0% to 2% slopes with the addition of 608.7 mm of surface and subusrface
run-on water from both the east and west backslopes. Field capacity water content of
the access tube transect soils was determined ﬁ'om soil-water contents 2 to 3 days
after rain events in April, 1990 and 1991 (Hall and Heaven, 1979). Field capacity
water content of the grid soil proﬁles was determined from texture (Ritchie and Crum,
1989). The total mm soil water per 150 cm soil of all soil proﬁles at -15 bar was
estimated from texture (Soil Survey Staff, 1991).

Semivariograms were developed for m soil water per 150 cm soil depth at ﬁeld
capacity and for August 6 and October 17, 1991, using all soil proﬁles from the the
transect and grid of the south 52 meters of the site. Cross-semivariograrns of mm soil
water for August 6 and October 17 by ﬁeld capacity mm soil water per 150 cm soil
depth were also developed. CERES estimates of total mm soil water were

successively removed from selected rows in the North-South and East-West directions

99

and geostatistical procedures, kriging and cokriging, were used to estimate total mm
soil water at locations where data points were removed from the data set until the
estimation procedure could no longer produce values that were signiﬁcantly close to
the CERES values. In the cokriging procedure, total mm soil water per 150 cm soil
depth at ﬁeld capacity was used as the auxiliary variable. All geostatistical analyses
were performed using the semivariograms and cross-semivariograms of the entire data
set of the south 52 meters of the site. Since mm soil water was estimated at speciﬁc
points on the landscape, punctual kriging and cokrignig was used. Soil water
estimates were derived using a maximum of 16 nearest neighbors for both the primary
and auxiliary variables. Semivariograms and geostatistical interpolation data were
calculated using GEOPACK (Yates and Yates, 1989). All semivariograms and cross-
semivariograms were validated using the jackkniﬁng method (Vauclin et al., 1983;

Russo, 1984).

RESULTS AND DISCUSSION
Slope Position and Soil-Water Content

The neutron probe access tube transects were divided into summit, upper
backslope, lower backslope, and footslope-toeslope components based on slope
position G’igures 3.4 and 3.5) and the average total mm soil water per 150 cm soil at
each access tube. The mm soil water per 150 cm soil depth of each access tube within
each slope position was averaged in order to simulate mean mm soil water per 150 cm
soil depth and calculate the average water balance of the slope unit. Soil water data
from three and ﬁve access tubes of the south and north access tube transects,
respectively, were not averaged into the slope component soil water data because
there locations (Figures 3.4 and 3.5) and soil moisture data indicated they were

transitional between slope components.

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The average maximum amount of water that can be held in the soil from 0 to 150
cm after drainage (ﬁeld capacity) for each landscape position of both transects is given
in Table 3.1. This table suggests the footslope and toeslope positions can hold the
most water, while the upper backslopes hold the least.

Rainfall and average daily temperature data for the 1990 and 1991 study periods
are presented in Figures 3.6 and 3.7. The mm soil water per 150 cm soil depth varied
appreciably with slope position of each transect for 1990 and 1991 (Figures 3.6, 3.7,
3.8, and 3.9). In soils of all positions of both transects, the greatest amount of soil
water existed in April and May, and October and November of 1990 and ﬂuctuated
widely from June through August (Figures 3.8 and 3.9). During the 1991 study
period, the greater amount of soil water, for all soils, existed in April and October, and
the least amount occurred in late July and early August (Figures 3.10 and 3.11). The
reason, in part, for the differences in mm soil water for these two years was that in
1990 the study site was fallow, and no transpiration to remove soil water occurred,
while in 1991 the site was planted to corn, with transpiration occurring during the

growing season. In both 1990 and 1991 the m soil water per 150 cm soil depth for

Table 3.1 Average soil proﬁle water retention (0 to 150 cm) at ﬁeld capacity for each
landscape position.

Transect Topographic Position Soil Water Content
mm
South Summit Kalamazoo 282
Upper Backslope Kalamazoo 216
Lower Backslope Kalamazoo 288
Footslope-Toeslope Kalamazoo 343
North Summit Kalamazoo 207
Upper Backslope Oshtemo 194
Lower Backslope Oshtemo 250

Footslope-Toeslope Kalamazoo 374

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Table 3.2 Changes in Runoff Curve Numbers.

Transect Topographic Original Runoff Runoff Curve

Position Curve Number Number Used in
Simulation

South Summit 75.92 75.92
Upper Backslope 86.4 9504*
Lower Backslope 86.4 7592*
Footslope-Toeslope 75.92 75.92

North Summit 75.92 75.92
Upper Backslope 86.4 9504*
Lower Backslope 86.4 7592*
Footslope-Toeslope 7 5.92 75.92
Opposite Backslope 89.64 9828*

* Changed Runoff Curve Number

the footslope and toeslope positions was the greatest of all positions, and did not vary
as widely as the m soil water of the other positions. In fact, the footslope and
toeslope soils were at or near ﬁeld capacity most of the year due to the large input of
water from the backslopes east and west of the toeslope. The lowest mm soil water
per 150 cm soil depth occurred in the upper backslope positions, which was well
below ﬁeld capacity during the growing season in 1991. The mm soil water per 150
cm soil depth of the summit and lower backslope positions were between the
footslope-toeslope and upper backslope mm soil water. The mm soil water per 150
cm soil depth of the summit and lower backslope of the south transect were similar (as
was water retention at ﬁeld capacity), and both were somewhat below ﬁeld capacity
during the growing season. The greater mm soil water in the footslope-toeslope and
lower backslope positions may be due to runoff and subsurface lateral downslope
movement of water, or throughﬂow (Hoover and Hursh, 1943; Chorley, 1978;

Gerrard, 1981; Burt and Butcher, 1985; Daniels and Hamer, 1992), from the summit

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110

and upper backslope positions. Throughﬂow may occur in the Kalamazoo soil
because as percent clay increases from the Ap to Btl horizon, the hydraulic
conductivity may decrease (Daniels and Hammer, 1992). Water may accumulate
above the Btl horizon during periods of high inﬁltration, and ﬂow laterally downslope.
In their studies of soil water content in sloping landscapes, Bhargava et al. (1976) and
Hanna et al. (1982) found the amount of stored soil to be greatest in the backslope and

footslope position soils, and least in the summit and shoulder position soils.

Soil Water Balance

In order to obtain estimated values of potential evapotranspiration, surface and
subsurface runoff and run-on, the CERES Maize computer model (version 2.1) was
used to simulate these parameters for each slope position of both transects. The
model was ﬁrst used to simulate soil water conditions for each slope position, except
toeslopes. It was assumed that if simulated volumetric moisture content (VMC)
values of each soil layer for each slope position were close to the average soil layer
content from the access tube transects, then the runoff estimates obtained from
CERES were probably valid. Since the slope gradient of the summit position is similar
(0 to 2%) both toward the west and north (Figure 3.3), it is difﬁcult to determine
where surface and subsurface runoff from the summit position moves. Therefore,
runoff from the summit position was not added to water entering the upper backslope
position. Changes to the inputs were necessary to make CERES estimates similar to
ﬁeld measured values. First, since the VMC values of the lower backslope soil layers
were similar to those of the summit soil layers, it was assumed that overland plus
subsurface throughﬂow from the upper backslope soils to the lower backslope soils
equaled runoff plus subsurface throughﬂow from the lower backslope soils to the
toeslope soils. Therefore, the Runoff Curve Numbers of the lower backslope soils

were changed to be the same values as the summit soils, and runoff ﬁ'om the upper

 

 

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backslope was not added to precipitation. Second, since ﬁeld VMC values still did not
compare well with CERES VMC estimates, the Runoff Curve Numbers were
determined for Hydrologic Condition C soils (clay loam textures) instead of
Hydrologic Condition B soils (loam and sandy loam textures) (Table 3.2). Also, ﬁeld
capacity soil moisture input was modiﬁed (Tables 3.3 and 3.4), until CERES VMC
estimates were as close to ﬁeld VMC values. Next, overland ﬂow plus subsurface
throughﬂow from the backslope soils to the toeslope soils was estimated as follows.
Since there is a hillslope (backslope = 8 % to 10 %) to the west, which converges with
the toeslope of the study site, the runoff from this backslope was simulated and
combined with the simulated runoff values from the upper backslope of the study site
to obtain estimated values for water ﬂow to the toeslope. Soil proﬁle data of the
upper backslope of the north transect was used as CERES input for simulating runoff
from the backslope opposite the study site because both slope positions have similar
soil proﬁles. The toeslope soils of each transect
were then simulated for VMC by adding runoff ﬁom the study site upper backslope
and the opposite backslope to precipitation. Simulated VMC values for the toeslope
soils of both the south and north transects were similar to ﬁeld data only aﬁer runoff
from the backslopes were simulated using Hydrologic Condition C soil values for the
backslopes. Simulated mm soil water per 150 cm soil estimates are presented in
Figures 3.12, 3.13, 3.14, and 3.15.

Statistical assessment of the simulation accuracy of CERES to estimate mm soil
water per 150 cm soil is summarized in Table 3.5. The Md values are all small except
for the 1990 toeslope positions, which are moderately overestimated. The RMSE
values are low compared to those reported by Jabro et al. (1994) using Br- simulation
models. Their RMSE values ranged from 14 to 51 percent. The r values for 1991
were higher than those of 1990. This might be expected since CERES was developed

as a corn grth model. All Md values were not statistically different from zero at the

112

Table 3.3 Changes in average ﬁeld capacity volumetric moisture content for the south

transect.

Position Depth (cm) Field capacity Field capacity
volumetric volumetric
moisture moisture used

in simulation

Summit 0-21 0.259 0.259

21-45 0.280 0.307
45-69 0.222 0.199
69-107 0.152 0.130
107-145 0.119 0.100
145-150 0.097 0.080
Upper Backslope 0-25 0.253 0.257
25-44 0.250 0.274
44-77 0.131 0.100
77-101 0.080 0.070
101-125 0.093 0.070
125-150 0.082 0.070
Lower Backslope 0-23 0.265 0.265
23-58 0.283 0.296
58-83 0.181 0.150
83-108 0.128 0.110
108-129 0.123 0.105
129-150 0.120 0.095
Footslope-Toeslope 0-26 0.280 0.287
26-44 0.292 0.267
44-63 0.281 0.286
63-100 0.207 0.181
100-125 0.181 0.165
125-150 0.169 0.150

113

Table 3.4. Changes in average ﬁeld capacity volumetric moisture content for the north

transect.
Position Depth (cm) Field Capacity Field Capacity used
Moisture Conent in simulation
Summit 0-16 0.237 0.243
16-36 0.223 0.257
36-55 0.180 0.154
55-84 0.101 0.075
84-117 0.094 0.075
117-150 0.092 0.075
Upper Backslope 0-15 0.169 0.184
15-46 0.146 0.130
46-76 0.130 0.111
76-106 0.134 0.111
106-128 0.099 0.073
128-150 0.100 0.073
Lower Backslope 0-20 0.213 0.216
20-30 0.188 0.216
30-61 0.151 0.121
61-92 0.174 0.173
92-124 0.135 0.115
124-150 0.180 0.170
Footslope-Toeslope 0-20 0.282 0.254
20-30 0.26 0.268
30-61 0.293 0.289
61-92 0.222 0.190
92-124 0.213 0.148
124-150 0.237 0.225

114

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118

Table 3.5. Statistical comparison of measured and simulated values of mm soil water
per 150 cm soil.

 

Year Transect Slope Md RMSE Corr. P(Tgt)
Position Coeﬁ‘.
mm % r
1990 South Summit 5.8 8.2 0.62 0.172
Upper Back. 2.2 10.3 0.60 0.569
Lower Back. -1.9 3.8 0.60 0.611
Foot-Toe 10.8 8.5 0.44 0.047
North Summit 0.7 8.4 0.55 0.830
Upper Back. -3.9 4.4 0.63 0.177
Lower Back. 3.3 2.8 0.73 0.348
Foot-Toe 10.5 7 .0 0.60 0.027
1991 South Summit 7.1 7.9 0.87 0.038
Upper Back. -3.6 12.8 0.82 0.390
Lower Back. 4.4 7.5 0.83 0.207
Foot-Toe 0.6 5.9 0.71 0.872
North Summit -1.9 7.1 0.71 0.455
Upper Back. -1.5 11.9 0.47 0.700
Lower Back. -4.4 7.9 0.76 0.203
Foot-Toe. -0.7 3.5 0.81 0.781

119

0.05 probability level, except the 1990 toeslope values, which were not statistically
diﬂ‘erent ﬁom zero at the 0.01 probability level.

There are two possible reasons why the Runoff Curve Numbers and ﬁeld capacity
moisture values needed to be changed. First, the Soil Conservation Service, Runoﬂ‘
Curve Number method assumes that daily precipitation occurs over the entire 24 hour
span. Thus, rainfall intensity is underestimated. Second, CERES Maize does not take
preferential water ﬂow into account, which is signiﬁcant in both well structured soils,
(like the Btl horizon of the Kalamazoo soils), and sandy soils, (like the ZBt2 and
3E/Bt horizons of the Kalamazoo and Oshtemo soils) (Steenhuis and Parlange, 1991).

Surface and subsurface runoff estimates for the summit positions (1.9% to 4.7% of
ppt) were similar to subsurface and subsurface runoff estimates for the lower
backslope positions (0.7% to 3.3% of ppt), while surface and subsurface runoff
estimates for the upper backslope positions were greater (10.0% to 23.2% of ppt)
(Table 3.6). Surface and subsurface ﬂow to the footslope-toeslope of both transects
was 1.8 times ppt in 1990 and 1.6 times ppt in 1991. Surface and subsurface runoff
from the footslope-toeslope (there is an outlet of the toeslope on the north end of the
site) ranged from 12.3% to 20.2% of ppt + surface and subsurface run-on (Table 3.6).

Evapotranspiration values (calculated by CERES when drainage > 0, or the water
balance equation when drainage = 0) for the summit (66.7% to 82.7% of ppt), upper
backslope (60.1% to 78.2% of ppt), and lower backslope (66.8% to 83.7% of ppt)
positions were similar (Table 3 .6). Evapotranspiration values for the footslope-
toeslope ranged from 41.9% to 55.6% of ppt + run-on.

Drainage values (calculated by the water balance equation) for the summit soils
(15.1% to 30.6% of ppt) were similar to the lower backslope soils (15.7% to 32.1% of
ppt), while drainage values for the upper backslope soils (6.9% to 19.3% of ppt) were
less (Table 3.6). Drainage values of the footslope and toeslope soils ranged from

31.2% to 39.6% of ppt + run-on.

120

Table 3.6 Water ﬂux amounts for each slope position.

 

 

mm
Transect Position Pricip. + Runoﬂ' and Change in Et Drainage
and Year Run-on and Throughflow Soil Water
Throughflow
South Summit 767.8 36 -15.1 512.5 234.4 mm
1990 4.7 -2.0 66.7 30.6 % of PPT
Upper Back. 767.8 178.2 -19.6 461.4 147.8 mm
23.2 -2.6 60.1 19.3 % of PPT
Lower Back. 767.8 25.5 -12.5 547.8 207.0 mm
3.3 -1.6 71.3 27.0 %ofPPT
Foot-Toe. 1414.5 268.9 -6.9 592.3 560.2 mm
1.8X ppt. 19.0 -0.5 41.9 39.6 % ofPPT
North Summit 767.8 16.3 -8.5 542.0 218.0 mm
1990 2.1 -l.1 70.5 28.4 %ofPPT
Upper Back. 767.8 137.5 -12.8 511.1 132.0 mm
17.9 -1.7 66.6 17.2 %ofPPT
Lower Back. 767.8 12.9 -4.6 513.2 246.3 mm
1.7 -().6 66.8 32.1 % of PPT
Foot-Toe. 1376.5 277.8 -0.4 658.1 441.0 mm
1.8X ppt. 20.18 -0.03 47.81 32.04 % of PPT
South Summit 751.3 14.1 4.6 598.9 133.7 mm
1991 1.9 0.6 79.7 17.8 % ofPPT
Upper Back. 751.3 75.4 2.6 587.4 85.9 mm
10.0 0.3 78.2 11.5 % of PPT
Lower Back. 751.3 5.4 -6.4 629.0 123.3 mm
0.7 -0.8 83.7 16.4 % ofPPT
Foot-Toe. 1215.0 149.8 1.7 675.8 387.7 mm
1.6X ppt. 12.3 0.2 55.6 31.9 % of PPT
North Summit 751.3 14.6 2.1 621.5 113.1 mm
1991 1.9 0.2 82.7 15.1 % ofPPT
Upper Back. 751.3 142.3 9.2 547.7 52.1 mm
19.0 1.2 72.9 6.9 % ofPPT
Lower Back. 751.3 11.4 7.5 614.1 118.3 mm
1.5 1.0 81.8 15.7%ofPPT
Foot-Toe. 1213.4 166.6 -5.5 674.3 378.1 mm
1.6X ppt 13.7 -0.5 55.6 31.2 % ofPPT

121

Geostatistical Analysis

Semivariograms and cross-semivariograms for the soil water properties are
presented in Figure 3.16. All semivariograms and cross-semivariograms were ﬁtted to
linear models. The spatial dependence for the soil water properties are summarized in
Table 3.7. The "explained" variance (the portion of the total variance correlated with
distance) ranged from 63.1 to 87.7 percent. The range of spatial dependence varied
from 22.0 to 26.1 meters. Signiﬁcant anisotropy in the east-west direction (up/down
the slope) is exhibited for all soil water variables.

Geostatistical estimation of mm soil water per 150 cm soil were performed on the
soil proﬁles from the grid between 4 and 52 meters north of the south access tube
transect. All soil water estimates in this grid were estimated by CERES Maize as
previously described. CERES estimates of mm soil water were removed ﬁ'om selected
rows in the North-South and East-West directions from the data sets of August 6 and
October 17, 1991. The number of X coordinate rows removed ﬁ'om the data sets was
increased until the minimum number of data required to estimate mm soil water via
kriging and cokriging was determined. A statistical comparison of the minimum
number of CERES input data used to geostatistically estimate mm soil water per 150
cm soil are presented in Table 3.8. The maximum distance that X coordinate rows
were separated to reliably estimate mm soil water at the 0.05 probability level using
kriging was 16 meters for August 6 and October 17. The maximum distance that X
coordinate rows could be separated to reliably estimate mm soil at the 0.05 probability
level using cokriging, with m soil water at ﬁeld capacity as the auxiliary function,
was 24 and 44 meters for August 6 and October 17, respectively. The maximum
distance that X coordinate rows could be separated to reliably estimate mm soil water
at the 0.01 probability level using cokriging was 44 meters. Other combinations of
rows and columns deleated ﬁ'om the data set did not yield reliable estimates of mm soil

water with fewer soil water data than those above. The pooled estimation variance

122

Semivariograrns
Water Content (mm)

 

 

 

 

 

 

 

 

N
(
‘2‘
E,
8
C
8
ﬂ
3
E
O
(0
c U 1 1 ﬁ
0 5 10 15 20 25
Lag (meters)
I I Field Capacity x 8-6-91 A 10-17-91 ]
Cross-semivariograms
Water Content by Field Capacity
N
(
E
E.
8
.3
B
3
E
O
0‘)

 

 

 

 

3 9 1 5 21 27
Lag (meters)

 

[- 8-6-91 A 1047.91 ]

 

Figure 3.16. Semivariograms and cross-semivariograms for soil water properties.

123

Table 3.7. Semivariance and cross-semivariance statistics.

 

Property: Nugget Sill Variance Corr. Range Anisotropy

Water Variance Explained Coeﬁ‘. Ratio

Content East-West
(MY (“11102 (%) r (m)

F.C. 455.0 1233.2 63.1 0.97 24.1 1.92

8-6-91 455.5 3276.8 86.1 0.92 22.0 7.77

10-17-91 513.1 3220.1 84.1 0.89 22.0 3.13

8-6-91

by F.C. 325.3 1638.6 80.1 0.94 22.0 4.27

10-17-91

by F.C. 260.9 1681.9 87.7 0.93 26.1 2.87

Table 3.8. Statistical comparison of CERES mm soil water values of mm soil water
per 150 cm soil with kriged and cokriged estimates.

 

Date X coordinate rows used in n* Md RSME Corr. P(T_<_t)
geostatistical estimation Coeff.
meters north of south border mm % r
Kriged
8-6-91 4, 20, 36, 52 36 6.5 17.0 0.84 0.052
10-17-91 4, 20, 36, 52 36 3.9 13.2 0.87 0.272
Cokriged
8-6-91 4, 28, 52 27 1.4 11.7 0.92 0.520
8-6-91 4, 48 18 -7.7 18.1 0.82 0.026
10-17-91 4, 48 18 -3.5 16.5 0.71 0.391

* n = number of mm soil water per 150 cm soil data points used in estimation.

124

values of mm soil water estimates are reported in Table 3 .9.

Table 3.9. Pooled kriging estimation variance.

Property: Water content Transects used in Pooled estimation
in 150 cm soil geostatistical estimation variance

 

meters north of south border (mm)2

Kriged

8-6-91 4, 20, 36, 52 787.9
10-17—91 4, 20, 36, 52 1698.7
Cokriged

8-6-91 4, 28, 52 934.4
8-6-91 4, 48 633.2
10-17-91 4, 48 1505.1

SUMMARY AND CONCLUSIONS

The lowest mm soil water per 150 cm soil depth occurred in the soils of the upper
backslope positions, and the highest in the soils of the footslope and toeslope
positions, which were at or near ﬁeld capacity during most of the study period. The
mm soil water of the lower backslope and summit positions were between the m soil
water of the upper backslope and footslope-toeslope positions. The amount of water
entering the lower backslope via inﬁltration from precipitation and run-on, and
subsurface lateral downslope throughﬂow may be similar to that inﬁltrating into the
summit soils from precipitation, as they both have similar total soil water contents.
The necessity to make the Runoﬁ‘ Curve Number of the lower backslope soils the
same as that of the summit soils, in order to simulate ﬁeld moisture conditions with
CERES Maize is further evidence the summit and lower backslope soils are receiving
similar quantities of water. The mm soil water per 150 cm soil depth of the footslope

and toeslope positions can be simulated with CERES Maize by adding simulated

125

estimates of surface and subsurface runoff from the upper backslope positions to
precipitation.

The results of this research show geostatistics can be used to estimate stored soil
water within a sloping landscape. Data sets of stored soil water can be reduced by
using semivariograms and cross-semivariograms from a large data set. The variogram
models used in this study could possibly be used in other stored soil water prediction
studies that have similar soils and landscapes. By using mm soil water at ﬁeld capacity
as the auxiliary variable, the distance between measurements of soil water could be as
far apart as twice the range of spatial dependence, parallel to the contour of the slope.
Therefore, stored soil water of the study site can be characterized geostatistically by
monitoring changes in soil water content at intervals of approximately 4.25 meters

up/down the slope and 44 meters apart on the same landscape position.

126

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131

GENERAL CONCLUSIONS

The results of this research show landscape position, in part, control soil formation,
(i.e. Organic matter accumulation, formation of soil horizons and soil structure, and
clay translocation) morphology, and amount of water in the soil proﬁle. In general,
within a sloping landscape where all soils are well drained, percent organic carbon,
percent clay and silt, soil thickness, and water holding capacity decrease from the
summit position to the upper backslope position, and then increase downslope.
Deposition of material at the lower backslope, footslope, and toeslope from upslope
contribute to thicker Ap horizons with more organic carbon, clay, and silt from the
lower backslope position downslope, relative to the summit and upper backslope
positions. Overland ﬂow and subsurface lateral downslope throughﬂow of water
contribute to greater soil thickness and percent clay of the argillic horizon below the
middle of the backslope by increasing leaching and clay translocation. Sorting of
material at deposition probably can contribute to differences in the amounts of sand,
silt, and clay seen at various parts of the landscape.

The amount of soil water within a sloping landscape with Kalamazoo and Oshtemo
soils is least within the upper backslope position, moderate within the summit and
lower backslope positions, and greatest within the footslope and toeslope positions.
The amount of water in the soils of a sloping landscape can be simulated by accounting
for precipitation, ﬁeld capacity moisture content, potential evapotranspiration, and
surface and subsurface ﬂow. The amount of soil water in the footslope and toeslope
positions can be simulated by combining overland ﬂow from the upper backslope (or
shoulder) position with precipitation. Because the lower backslope and summit
position soils seem to behave similarly with respect to soil water in the proﬁle, the
amount of soil water in the lower backslope and summit positions can be simulated
similarly with respect to degree of slope, which inﬂuences the amount of surface and

subsurface ﬂow from these positions.

132

The results of this research show geostatistics can be used to estimate the amount
of soil water within a sloping landscape. By using mm soil water at ﬁeld capacity as
the auxiliary variable, the distance between measurements of soil water could be as far
apart as twice the range of spatial dependence, parallel to the contour of the slope.
Variogram models of the amount of soil water from large data sets could be used to
predict the amount of soil water in other studies with similar landscape and soil

conditions.

APPENDIX A.

Soil Proﬁle Horizon Depth, Particle Size Distribution, Control Section Clay Content,
and Soil Series Data

133

APPENDIX A.

Soil proﬁle horizon depth, particle size distribution, control section clay content, and
soil series. The southwest corner of the ﬁeld is the origin of the sample points at 0
meters in the east and north directions.

Sample point location

East North Horizon Depth Percent Percent Percent Control Soil
meters meters cm Sand Clay Silt Section Series
Clay%
0.00 0.00 Ap 0-33 33 24 43 30 Kal.
E 33-50 33 24 43
Btl 50—71 55 30 15
Bt2 71-107 74 20 6
2Bt3 107-173 89 9 2
2.00 0.00 Ap 0-23 34 23 43 33 Kal.
B 23-40 34 23 43
Btl 40-64 50 33 17
Bt2 64-97 74 18 8
2Bt3 97-173 88 11 1
4.00 0.00 Ap 0-23 41 22 37 28 Kal.
E 23-40 41 22 37
Btl 40-64 55 28 17
Bt2 64-97 74 22 4
2Bt3 97-173 90 10 0
6.00 0.00 Ap 0-23 39 21 40 26 Kal.
Btl 23-58 53 31 16
2Bt2 58-122 83 15 2
3E/Bt 122-150 94 6 0
8.00 0.00 Ap 0-20 39 21 40 27 Kal.
E 20-28 31 29 4O
Btl 28-58 43 35 22
2Bt2 58-86 83 16 1
3E/Bt 86-150 94 6 0

East
meters

10.00

12.00

14.00

16.00

18.00

20.00

22.00

24.00

26.00

North
meters

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

Horizon

Ap
Btl
Bt2
ZBt3
3E/Bt
Ap
Btl
Bt2
213:3
313/13:
Ap
Btl
Bt2
ZBt3
3E/Bt
Ap
Btl
Bt2
2Bt3
3E/Bt
Ap
Btl
Bt2
ZBt3
313/13:
Ap
Btl
2Bt2
3E/Bt
Ap
Btl
213a
3E/Bt
Ap
Btl
2Bt2
3E/Bt
Ap
Btl
ZBt2
3E/Bt

Depth
cm

0-20
20-40
40-53
53-91
91-150
0-20
20-46
46-64
64-122
122-150
0-23
23-43
43-56
56-104
104-1 50
0-23
23-43
43-58
58-102
102-1 50
0-20
20-43
43-61
61-122
122-150
0-23
23-38
38-74
74-150
0-23
23-38
38-79
79-150
0-25
25-43
43-74
74-150
0-28
28-50
50-75
75-150

134

Percent Percent Percent Control

Sand

41
44
78
89
94
41
31
76
81
94
47
57
77
85
94
45
47
78
85
94
46
63
76
90
94
47
52
87
94
51
67
89
94
47
66
87
94
45
57
87
94

Clay

21
36
21
11
6

22
37
22
16
6

23
28
21
13
6

24
33
20
13
6

26
28
21
10
6

23
31
12
6

23
27
10
6

21
29
12
6

21
25
10
6

Silt

38
20
l
0
O
37
32
2
3
0
30
15
2
2
0
31
20
2

N

00

\10

N

ow—wo—mwo~o\No——woow~owo
00-h 0

Soil

Section Series

Clay %
23

34

23

27

25

18

15

18

17

Kal.

Kal.

Kal.

Kal.

Kal.

Kal.

Osh.

Kal.

Osh.

East
meters

28.00

30.00

32.00

34.00

0.00

4.25

8.50

12.75

17.00

North
meters

0.00

0.00

0.00

0.00

4.00

4.00

4.00

4.00

4.00

Horizon

A9
Btl
21312
313/13:
Ap
Btl
312
21313
3E/Bt
Ap

E

Btl
Bt2
2133
AP

Bt 1
Bt2
ZBt3

Btl
21312
Ap

Bt l
2Bt2
3E/Bt

Btl
213a
313/13:
Ap
1311
21312
3E/Bt
Ap
Btl
2131.2
315/13:

Depth
cm

0-23
23-38
38-86
86-150
0-23
23-36
36-48
48-137
137-150
0-20
20-28
28-48
48-69
69-157
0-20
20-28
28-58
58-91
91-157
0-28
28-43
43-84
84-150
0-25
25-43
43-69
69-142
142-150
0-20
20-56
56-91
91-150
0-23
23-58
58-112
112-150
0-23
23-66
66-112
112-150

135

Percent Percent Percent

Sand

41
69
81
94
41
49
76
82
94
25
25
5 1
72
87
41
22
27
74
89
34
36
53
87
4o
33
45
84
94
4o
44
85
94
44
43
84
94
45
54
87
94

Clay

22
25
16
6

21
29
20
ll
6

20
20
34
20
11
21
21
39
20
11
23
24
31
11
21
27
32
15
6

21
36
14
6

22
32
14
6

24
31
12
6

Silt

37
6
3
0
38
22
4
7
0
55
55
15
8
2
38
57
34
6
0
43
40
16
2
39
40
23
1
O
39
20
1
0
34
25
2
0
31
15
l
0

Control
Section
Clay %
1 9

20

30

39

27

24

30

27

28

Soil

Series

Kal.

Kal.

Kal.

Kal.

Kal.

Kal.

Kal.

Kal.

East
meters

21.25

25.50

29.75

34.00

0.00

4.25

8.50

12.75

17.00

21.25

North
meters

4.00

4.00

4.00

4.00

8.00

8.00

8.00

8.00

8.00

8.00

Horizon Depth

Ap
311
2312
33/31
Ap
311
2312
33/31
A3
311
2312
33/31
Ap
311
2312
A9

3

311
2312
Ap

E

311
2312
33/31
A3
311
2312
313/31

311
2312
33/31
Ap
311
2312
33/31

Bt 1
ZBtZ
3E/Bt

cm

0-23
23-53
53-86
86-1 50
0-25
25-71
71-102
102-150
0-23
23-43
43-1 17

1 17-150
0-20
20-76
76-150
0-28
28-46
46-81
81-150
0-25
25-46
46-69
69-132
132-150
0-23
23-56
56-94
94-150
0-23
23-61
61-1 14

1 14-150
0-23
23-66
66-1 14

1 14-150
0-23
23-56
56-83
83-150

136

Percent
Sand

49
59
87
94
47
63
87
94
42
60
81
94
35
39
88
35
37
55
85
4o
35
51
86
94
4o
44
84
94
44
48
85
94
45
52
86
94
48
58
84
94

Percent Percent

Clay

23
29
13
6

21
27
11
6

21
27
14
6

20
36
11
23
25
31
12
21
25
31
13
6

21
36
15
6

21
32
13
6

23
32
12
6

22
30
14
6

Silt

28
12
0
0
32
10
2
0
37
13
5
O
45
25
l
42
38
14
3
39
40
18
1
0
39
20
1
0
35
20
2
0
32
16
2
0
30
12
2
0

Control
Section
Clay %
23

26

19

36

25

21

29

27

29

25

Soil

Series

Kal.

Kal.

Kal.

Kal.

Kal.

Kal.

Kal.

Kal.

Kal.

Kal.

East
meters

25.5

29.75

34.00

0.00

4.25

8.50

12.75

17.00

21.25

North
meters

8.00

8.00

8.00

12.00

12.00

12.00

12.00

12.00

12.00

Horizon

311
2312
33/31
Ap
311
2312
313/31
AP
311
2312
33/31
A1)

311
2312
33/31
Ap

Bt l
2Bt2
3E/Bt

Bt 1
ZBt2
3E/Bt

311
2312
313/31
Ap
311
2312
33/31

Bt 1
2Bt2
3E/Bt

Depth
cm

0-23
23-66
66-109
109-150
0-23
23-41
41-114
114-150
0-23
23-71
71-142
142-150
0-30
30-43
43-76
76-102
102-150
0-30
30-46
46-66
66-102
102-150
0-25
25-58
58-102
102-150
0-25
25-38
38-63
63-1 12
112-150
0-25
25-61
61-1 17
117-150
0-20
20-61
61-74
74-150

137

Percent Percent Percent Control

Sand

48
65
87
94
45
63
81
94
39
39
87
94
38
37
61
23
94
40
35
47
85
94
41
45
80
94
45
34
56
89
94
45
47
84
454
47
55
75
94

Clay

21
27
11
6
19
27
15
6
20
35
11
6
22
28
27
77
6
212
27
33
13
6
21
36
17
6
19
28
32
11
6
20
34
13
19
22
31
21
6

Silt

31
8
2
0
36
10
4
0
41
26
2
O
40
35
12
17
0
39
38
20
2
0
38
19
3
0
36
38
12
0
0
35
19
3
36
31
14
4
0

Section Series

Clay %
25

19

34

24

21

30

22

28

29

Soil

Kal.

Kal.

Kal.

Kal.

Kal.

Kal.

Kal.

Kal.

Kal.

East
meters

25.50

29.75

34.00

0.00

4.25

8.50

17.00

21.25

25.50

North

meters

12.00

12.00

12.00

16.00

16.00

16.00

16.00

16.00

16.00

16.00

Horizon Depth

AP
311
2312
313/31
A9
311
2312
315/31
Ap
311
2312
33/31
Ap

3

311
2312
313/31
Ap

E

311
2312
33/31
Ap
311
2312
33/31
Ap
311
2312
3E/Bt
Ap
311
2312
33/31
Ap
311
2312
313/31
Ap
311
2312
33/31

cm

0-20
20—56
56-132
132-150
0-20
20-61
61-102
102-150
0-28
28-61
61-1 17

1 17-150
0-33
33-46
46-79
79-109
109-150
0-28
28-36
36-66
66-104
104-150
0-28
28-63
63-102
102-150
0-25
25-66
66-104
104-150
0-20
20-56
56-127
127-150
0-25
25-61
61-137
137—150
0-20
20-43
43-79
79-150

138

Percent Percent Percent Control Soil

Sand

51
71
88
94
53
71
79
51
52
75
86
94
41
37
61
77
94
41
29
43
76
94
49
45
82
94
47
38
82
94
55
49
86
94
55
52
81
94
57
74
89
94

Clay

22
23
12
6

23
24
18
22
20
20
13
6

23
28
27
17
6

21
28
35
17
6

19
35
15
6

19
33
14
6

20
31
11
6

21
31
15
6

23
22
11
6

Silt

27
6
0
0
24
5
3
27
28
5
1
0
36
35
12
6
0
38
43
22
7
0
32
20
3
0
34
29
4
0
25
20
3
0
24
17

Section Series

Clay %

20 Kal.
23 Kal.
18 Kal.
24 Kal.
28 Kal.
29 Kal.
3O Kal.
25 Kal.
27 Kal.
16 Osh.

East
meters

29.75

34.00

0.00

4.25

8.50

12.75

17.00

21.25

25.50

North
meters

16.00

16.00

20.00

20.00

20.00

20.00

20.00

20.00

20.00

Horizon

A3
311
2312
33/31
Ap
311
2312
313/31

311
2312
33/31
AP

311
2312
33/31
Ap

311
2312
33/31
Ap

Bt 1
ZBt2
3E/Bt

311
2312
33/31
Ap
311
2312
33/31
Ap
311
2312
33/31

Depth
cm

0-20
20-43
43-122
122-150
0-20
20-61

61 -1 14

1 14-150
0-28
28-69
69-124
124-150
0-28
28-41
41-69
69-1 17

1 17-150
0-23
23-38
38-69
69-1 19

1 19-150
0-23
23-38
38-75
75-109
109-150
0-20
20-58
58-102
102-150
0-20
20-50
50-86
86-150
0-20
20-50
50-94
94-150

139

Percent Percent

Sand

53
67
83
94
47
62
85
94
33
44
79
94
41
27
41
57
94
47
29
44
86
94
51
51
55
85
94
48
53
84
94
57
79
91
94
53
73
91
94

Clay

24
25
15
6

21
23
12
6

24
33
17
6

21
28
33
22
6

19
30
35
14
6

19
19
29
13
6

22
31
15
6

22
20
9

6

25
21

Percent
Silt

23
8
2
0
32
15
3
0
43
23
4
0
38
45
26
21
0
34
41
21
0
0
3O
30
16
2
0
30
16

Control
Section
Clay %
20

21

30

28

27

25

27

16

16

Soil
Series

Kal.

Kal.

Kal.

Kal.

Kal.

Kal.

Kal.

Osh.

Osh.

 

East
meters

29.75

34.00

0.00

4.25

8.50

12.75

17.00

21.25

25.50

29.75

North
meters

20.00

20.00

24.00

24.00

24.00

24.00

24.00

24.00

24.00

24.00

Horizon Depth

AP
311
2312
313/31
Ap
311
2312
33/31
Ap

3

311
2312
313/31
Ap

E

311
2312
33/31
Ap
311
2312
33/31
A9
311
2312
33/31
Ap .
311
2312
Ap
311
2312
Ap
311
2312
33/31
A9
311
2312
33/31

cm

0-23
23-48
48-91
91-150
0-23
23-46
46-74
74-150
0-33
33-48
48-71
71-119
119-150
0-30
30-48
48-71
71-112
112-150
0-30
30-51
51-114
114-150
0-23
23-71
71-102
102-150
0-20
20-53
53-150
0-18
18-32
32-150
0-23
23-66
66-104
104-150
0-23
23-46
46-104
104-150

140

Percent Percent Percent Control Soil

Sand

48
68
86
94
5 1
66
89
94
3 1
28
54
85
94
45
26
34
75
94
46
45
87
94
48
46
85
94
47
40
82
49
62
82
46
69
89
94
41
63
83
94

Clay

24
27
13
6

23
28
11
6

24
31
29
13
6

23
30
34
19
6

20
31
13
6

20
33
14
6

22
36
17
23
3O
15
25
23
8

6

27
29
13
6

Silt

W

OOOROHUIN

45

NWOH
AH

00

\O

ObOOSOMOONWOONH

Section Series

Clay %

20 Kal.
l9 Kal.
20 Kal.
26 Kal.
21 Kal.
32 Kal.
30 Kal.
19 Kal.
21 Kal.
20 Kal.

 

East
meters

34.00

0.00

4.25

8.50

12.75

17.00

21.25

25.50

29.75

34.00

North
meters

24.00

28.00

28.00

28.00

28.00

28.00

28.00

28.00

28.00

28.00

Horizon

A9
311
2312
33/31
Ap

311
2312
Ap

Ht 1
2Bt2
3E/Bt

Bt 1
2Bt2

Bt 1
2Bt2
3E/Bt

Bt 1
ZBt2

311
2312
33/31
Ap
311
2312
313/31

Bt 1
ZBt2
3E/Bt

Btl
ZBt2
3E/Bt

Depth
cm

0-20
20-41
41-1 14
1 14-150
0-25
25-46
46-71
71-150
0-28
28-43
43-66
66-102
102-150
0-20
20-36
36-63
63-150
0-20
20-33
33-66
66-107
107-150
0-30
30-56
56-107
107-173
0-15
15-69
69-102
102-150
0-15
15-50
50-102
102-150
0-23
23-46
46-89
89-150
0-23
23-53
53-104
104-150

141

Percent Percent Percent

Sand

53
66
85
94
33
29
51
83
45
41
62
85
94
49
27
47
85
48
31
43
85
94
49
41
61
90
53
72
89
94
50
69
89
94
49
65
81
94
48
61
87
94

Clay

23
26
13
6

26
31
33
13
22
27
27
14
6

19
31
34
14
19
29
35
12
6

21
23
26
10
23
26
10
6

24
29
9

6

25
29
18
6

24
29
12
6

Silt

24
8
2
0
41
40
16
4
33
32
11
1
0
32
42
19
1
33
40
22
3
0
30
36
13
0

N
A

O\

Or-‘v-‘No—‘QNONNNOU-‘N
000 ON

Control
Section
Clay %
1 8

23

20

25

27

26

26

23

23

22

Soil

Series

Kal.

Kal.

Kal.

Kal.

Kal.

Kal.

Kal.

Kal.

Kal.

Kal.

 

East

meters

0.00

4.25

8.50

12.75

17.00

21.25

25.50

29.75

34.00

0.00

North

meters

32.00

32.00

32.00

32.00

32.00

32.00

32.00

32.00

32.00

36.00

Horizon

Ap

311
2312
A9

311
2312
33/31
Ap

311
2312
Ap
311
2312
313/31
Ap
311
2312
313/31
Ap
311
2312

Bt 1
ZBt2

311
2312
313/31
A9
311
2312

Ht 1
2Bt2
3E/Bt

Depth
cm

0-33
33-38
38-91
91-150
0-33
33-53
53-69
69-97
97- 1 50
0-20
20-33
33-74
74-150
0-18
18-69
69- 138
138-150
0-18
18-48
48-94
94-150
0-20
20-48
48-150
0-20
20-40
40-150
0-20
20-53
53-107
107-150
0-20
20-48
48-150
0-28
28-41
41 -79
79-97
97-150

142

Percent Percent Percent Control

Sand

36
27
4o
80
44
38
51
80
47
48
81
44
38
65
49
83
94
57
52
82
94
49
65
92
48
71
89
49
63
88
94
45
53
89
34
27
42
77
94

Clay

22
28
32
17
21
26
32
17
21
35
17
21
26
22
31
14
6

23
31
13
6

25
29
8

25
23
9

24
29
12
6

25
33
11
25
29
36
19
6

Silt

42
45
28
3
35
36
17
3
32
17
2
35
36
13
20
3
0
20
17
5
0
26
6
O
27
6
2
27
8
0
0
30
14
0
41
44
22
4
0

Soil

Section Series

Clay %
32

22

32

31

24

20

15

23

23

32

Kal.

Kal.

Kal.

Kal.

Kal.

Kal.

Osh.

Kal.

Kal.

Kal.

East
meters

4.25

8.50

17.00

21.25

25.50

29.75

34.00

0.00

4.25

North
meters

36.00

36.00

36.00

36.00

36.00

36.00

36.00

36.00

40.00

40.00

Horizon Depth

Ap

3

311
2312
313/31
AP

3

311
2312
33/31
Ap
311
2312
33/31
Ap
311
2312
313/31
Ap
311
313/31
Ap
311
2312
Ap
311
2312
313/31
Ap
311
2312
33/31
Ap

3

311
2312
33/31
AP

Bt 1
ZBtZ
3E/Bt

cm

0-25
25-38
38-61
61-1 14
1 14-150
0-23
23-33
33-58
58-104
104-150
0-20
20-43
43-91
91-150
0-23
23-38
38-89
89-150
0-23
23-114
114-150
0-15
15-30
30-150
0-20
20-56
56-1 17
117-150
0-18
18-38
38-119
119-150
0-25
25-36
36-56
56-122
122-150
0-20
20-28
28-56
56-102
102-150

143

Percent Percent Percent Control
Section Series

Sand

39
3 1
55
87
94
47
47
45
85
94
47
60
86
94
50
42
76
94
51
79
94
49
61
87
46
60
86
94
43
55
86
46
37
30
46
76
94
45
31
41
85
94

Clay

19
31
31
11
6

21
21
34
14
6

21
30
12
6

24
3O
21
6

24
18
6

23
29
13
23
28
13
6

23
29
14
23
23
30
36
19
6

21
32
36
15
6

Silt

42
38
14
2
0
32
32
21
1
0
32
10
2
0
26
28
3
0
25
3
0
28
10
0
31
12
l
0
34
16
0
31
40
40
18
5
0
34
37
23
0
0

Clay %
20

24

20

24

18

18

24

20

26

27

Soil

Kal.

Kal.

Kal.

Kal.

Kal.

Kal.

Kal.

Kal.

Kal.

 

East

meters

8.50

12.75

17.00

21.25

25.50

29.75

34.00

0.00

4.25

8.50

North

meters

40.00

40.00

40.00

40.00

40.00

40.00

40.00

44.00

44.00

44.00

Horizon Depth

Ap
311
2312
33/31
Ap
311
2312
313/31
Ap
311
2312
33/31
Ap
311
2312
315/31
Ap
311
2312
313/31
A9
311
2312
313/31
Ap
311
2312
33/31
Ap
311
2312
33/31
Ap
311
2312
313/31
Ap
311
2312
33/31

cm

0-18
18-46
46-109
109-150
0-15
15-36
36-94
94-150
0-13
13-36
36-79
79-150
0-18
18-33
33-84
84-150
0-23
23-46
46-1 14
1 14-150
0-18
18-46
46—79
79-150
0-18
18-56
56-1 19

1 19-150
0-28
28-58
58-122
122-150
0-25
25-56
56-1 12

1 12-150
0-25
25-53
53-99
99-150

144

Percent Percent Percent Control

Sand

49
5 l
81
94
47
57
89
94
49
59
73
94
54
71
80
94
52
58
86
94
49
58
86
94
49
59
76
94
3 7
49
91
94
46
52
81
94
47
55
80
94

Clay

22
33
16
6

22
30
11
6

23
29
22
6

23
23
18
6

23
31
13
6

21
31
13
6

21
30
17
6

21
32
9

6

18
3O
15
6

19
31
17
6

Silt

29
16
3
0
31
13
0
0
28
12
5
O
23
6
2
0
25
11
l
0
30
11
1
0
30
11
7
0
42
19
O
0
36
18
4
0
34
14
3
0

Section Series

Clay %
26

19

25

20

21

27

24

23

24

25

Soil

Kal.

Kal.

Kal.

Kal.

Kal.

Kal.

Kal.

Kal.

Kal.

Kal.

 

East
meters

12.75

17.00

21.25

25.50

29.75

34.00

0.00

4.25

8.50

12.75

North

meters

44.00

44.00

44.00

44.00

44.00

44.00

48.00

48.00

48.00

48.00

Horizon Depth

A9
311
2312
313/31
A3
311
2312
313/31
Ap
311
2312
313/31
Ap
311
2312
313/31
A9
311
2312
313/31
Ap
311
23/31
Ap

13

311
2312
313/31
Ap

13

311
2312
313/31
Ap
311
2312
313/31
Ap
311
2312
313/31

cm

0-20
20-58
58-1 17

1 17-150
0-18
18-48
48-102
102-150
020
20-38
38-84
84-150
0-18
18-50
50-124
124-150
0-20
20-50
50-107
107-150
0-20
20-69
69-150
0-28
28-38
38-74
74-1 17

1 17-150
0-23
23-36
36-61

61 -1 19

1 19-150
0-23
23-56
56—1 12

1 12-150
0-20
20-48
48-97
97-150

145

Percent Percent Percent Control Soil

Sand

51
53
9O
94
49
53
75
94
54
52
84
94
53
63
89
94
55
71
86
94
53
63
94
38
28
43
78
94
49
29
53
81
94
47
47
81
94
49
55
87
94

Clay

2]
32
10
6

22
32
21
6

21
21
15
6

21
29
11
6

20
17
14
6

21
29
6

22
31
35
19
6

19
31
33
17
6

19
31
17
6

20
33
13
6

Silt

28
15
0
0
29
15
4
0
25
27
1
0
26
8
0
0
25
12
0
0
26
8
0
4O
41
22
3
0
32
40
14
2
0
34
22
2
0
31
12
0
0

Section Series

Clay %

27 Kal.
28 Kal.
17 Osh.
23 Kal.
16 Osh.
29 Kal.
31 Kal.
25 Kal.
26 Kal.
24 Kal.

East
meters

17.00

21.25

25.5

29.75

34.00

0.00

4.25

8.50

12.75

North
meters

48.00

48.00

48.00

48.00

48.00

52.00

52.00

52.00

52.00

Horizon

A9
311
2312
313/31
A9
311
2312

311
2312
33/31
AP
311
2312
313/31

311
2312
313/31
Ap

311
2312
33/31
AP

Bt 1
2Bt2
3E/Bt

311
2312
313/31
Ap

Bt 1
2Bt2
3E/Bt

Depth
cm

0-20
20-48
48-112
112-150
0-23
23441
41-150
0-20
20-46
46-122
122-150
0-23
23-38
38-122
122-150
0-18
18-48
48-86
86-150
0-25
25-36
36-63
63-112
112-150
0-25
25-38
38-66
66-114
114-150
0-25
25-38
38-58
58-107
107-150
0-23
23-33
33-61
61-102
102-150

146

Percent Percent Percent Control
Section Series

Sand

49
55
87
94
47
49
89
51
63
93
94
52
61
82
51
49
62
89
94
37
41
61
78
94
47
35
58
88
94
48
36
55
81
94
48
35
45
83
94

Clay

20
33
13
6

21
33
10
21
28
7

6

22
30
16
21
21
28
11
6

22
25
27
19
6

19
28
30
12
6

19
28
30
18
6

20
29
30
15
6

Silt

31
12
0
0
32
18
1
28
9
O
O
26
9
2
28
30
10
0
0
41
34
12
3
0
34
37
12
O
0
33
36
15
1
0
32
36
25
2
0

Clay %
23

15

27

20

21

23

22

23

23

Soil

Kal.

Osh.

Kal.

Kal.

Kal.

Kal.

Kal.

Kal.

Kal.

 

Ikun

meters

17.00

21.25

25.50

29.75

34.00

0.00

4.25

8.50

12.75

North

meters

52.00

52.00

52.00

52.00

52.00

56.00

56.00

56.00

56.00

Horizon

Ap

3

311
2312
313/31
Ap
311
2312
313/31
Ap
311
2312
Ap
311
2312
33/31
Ap
311
2312
313/31
Ap
311
2312
313/31
A9

13

311
2312
313/31
Ap

13

311
2312
313/31
A9

3

311
2312
313/31

Depth
cm

0-23
23-30
30-61
61-97
97-150
0-18
18-41
41-112
112-150
0-18
18-61
61-150
0-18
18-36
36-79
79-150
0-20
20-48
48-127
127-150
0-30
30-61
61-119
119-150
0-30
30-46
46-61
61-119
119-150
0-28
28-41
41-69
69-117
117-150
0-18
18-33
33-61
61-91
91-150

147

Percent Percent Percent

Sand

48
37
50
82
94
53
67
92
94
51
67
91
55
62
81
94
41
59
85
94
41
48
76
94
47
41
59
73
94
52
40
52
79
94
51
37
47
79
94

Clay

22
30
38
17
6

21
28
8

6

23
25
9

21
30
17
6

22
29
13
6

20
35
20
6

18
21
28
20
6

18
26
33
18
6

19
27
31
17
6

Silt

30
33
12
1
0
26
5
0
0
26
8
0
24
8
2
0
37
12
2
0
39
17
4
0
35
38
13
7
0
30
34
15
3
0
30
36
22
4
0

Control
Section
Clay %
3 1

17

23

22

22

29

22

26

25

Soil
Series

Kal.

Osh.

Kal.

Kal. “-
Kal.
Kal.

Kal.

Kal.

Kal.

East

meters

17.00

21.25

25.50

29.75

34.00

0.00

4.25

8.50

12.75

North

meters

56.00

56.00

56.00

56.00

56.00

60.00

60.00

60.00

60.00

Horizon

Ap

3

311
2312
313/31
Ap
311
2312
33/31
Ap
311
2312
313/31
Ap
311
2312
313/31
Ap

13

311
2312
313/31
Ap
311
2312
313/31
Ap

13

311
2312
313/31
Ap

13

311
213/31
Ap

13

311
2312
313/31

Depth
cm

0-23
23-38
38-66
66-79
79-150
0-18
18-61
61-119
119-150
0-20
20-61
61-122
122-150
0-20
20-61
61-81
81-150
0-23
23-38
38-56
56-81
81-150
0-30
30-61
61-124
124-150
0-30
30-41
41-66
66—102
102-150
0-25
25-56
56-81
81-150
0-20
20-30
30-46
46-109
109-150

148

Percent
Sand

55
45
61
79
94
51
67
89
94
47
58
85
94
48
65
84
94
41
41
61
81
94
45
55
85
94
52
64
54
81
94
60
57
71
94
59
51
44
90
96

Percent Percent

Clay

20
25
31
20
6

20
25
11
6

20
30
13
6

19
28
15
6

19
25
27
15
6

21
30
14
6

16
18
24
17
6

17
21
23
6

18
24
27
10
4

Silt

25
30
8
1

O
Nb) \0

OHQSON—‘WOOOON

Control
Section
Clay %
28

23

27

26

20

24

21

23

15

Soil

Series

Kal.

Kal.

Kal.

Kal.

Kal.

Kal.

Kal.

Kal.

Osh.

East
meters

17.00

21.25

25.50

29.75

34.00

0.00

4.25

8.50

12.75

17.00

21.25

North

meters

60.00

60.00

60.00

60.00

60.00

64.00

64.00

64.00

64.00

64.00

64.00

Horizon Depth

Ap
311
23/31
AP
311
213/31
A9
311
2312
33/31
Ap

13

311
2312
33/31
Ap

13

311
2312
313/31
Ap

13

311
2312
33/31

cm

0-20
20-61
61-150
0-20
20-48
48-150
0-20
20-41
41 -79
79-150
0-23
23-36
36-58
58-90
90-150
0-18
18-30
30-69
69-102
102-150
0-48
48-58
58-71
71-1 17
1 17-150
0-31

3 1-48
48-150
0-23
23-41
41-135
135-150
0-20
20-33
33-102
102-150
0-20
20—79
79-150
0-23
23-46
46-150

149

Percent Percent Percent Control

Sand

61
81
94
59
79
94
49
63
79
94
45
39
62
81
94
42
30
51
87
94
41
51
57
82
94
61
59
94
62
63
83
94
65
71
88
94
71
86
94
61
85
94

Clay

18
18
6

20
19
6

22
30
19
6

18
27
27
15
6

19
27
32
11
6

22
21
29
17
6

15
21
6

15
16
16
6

19
25
12
6

17
14
6

19
14
60

Silt

Soil

Section Series

Clay %
1 8

19

24

22

28

20

10

16

15

14

14

Kal.

Kal.

Kal.

Kal.

Kal.

Kal.

Spinks

Osh.

Osh.

Osh.

Osh.

 

 

East
meters

25.50

29.75

34.00

0.00

2.00

4.00

6.00

8.00

10.00

North

meters

64.00

64.00

64.00

68.00

68.00

68.00

68.00

68.00

68.00

Horizon

Ap
311
2312
313/31

Ht 1
2Bt2
3E/Bt

311
2312
313/31
Ap

Bt 1
Bt2
2Bt3

311
312
313/31
A3

311
312
2313
313/31
Ap

2311
213/31
A9

311
23/31
Ap

ZBtl
3E/Bt

Depth
cm

0-20
20-38
38-74
74-150
0-18
18-56
56-89
89-150
0-18
18-30
30-69
69-102
102-150
0-28
28-53
53-75
75-102
102-150
0-25
25-53
53-71
71-94
94-150
0-28
28-56
56-84
84-1 12
1 12-142
142-150
0-20
20-30
30-97
97-150
0-20
20-30
30-86
86-150
0-15
15-51
51-99
99-150

150

Percent Percent Percent

Sand

41
39
76
94
41
48
79
41
48
43
62
86
94
41
57
73
83
94
47
41
57
75
94
51
31
24
74
91
94
66
73
90
94
66
66
89
94
67
61
88
94

Clay

22
37
19
6

20
34
17
22
19
25
29
14
6

23
28
18
15
6

23
24
24
22
6

18
29
38
29
9

6

15
13
8

6

13
13
10
6

15
19
12
6

Silt

37
24
5
0
39
18
4
37
33
32
9
0
0
36
15
9
2
0
3O
35
19
3
0
31
40
38
6
0
0
19
14
O
0
21
21
1
0
18
20
0
0

Control
Section
Clay %
25

30

26

28

22

38

10

12

Soil
Series

Kal.

Kal.

Kal.

Kal.

Kal.

Kal.

Osh.

Osh.

Osh.

East
meters

121M)

14100

16100

15100

201K)

221K)

241K)

261K)

281K)

3C100

32IX)

341K)

North
meters

681K)

681K)

681K)

681X)

681M)

681K)

684K)

68LK)

684K)

681K)

68(X)

681K)

Horizon Depth

A9
311
2312
313/31
Ap
311
23/31
AP
2311
213/31
Ap
311
213/31
A9
2311
313/31
A9
2311
313/31
AP
2311
313/31
A9
311
2312
313/31
Ap
311
2312
313/31
Ap
311
2312
313/31
Ap
311
2312
313/31
A3
311
2312
313/31

cm

0-15
15-66
66-117
117-150
0-15
15-102
102-150
0-15
15-117
117-150
0-15
15-137
137-150
0-15
15-117
117-150
0-18
18-56
56-150
0-20
20-75
75-150
0-23
23-46
46-124
124-150
0-20
20-56
56-84
84-150
0-15
15-43
43-71
71-150
0-15
15-58
58-86
86-150
0-15
15-63
63-94
94-173

151

Percent Percent Percent Control

Sand

71
54
91
94
69
89
94
69
90
94
71
88
94
47
80
94
59
83
94
55
88
94
49
63
86
94
51
77
86
94
29
65
87
94
51
79
87
94
50
35
86
94

Clay

14
29
9
6
14
11
6
14
10
6
13
12
6
19
20
6
20
15
6
19
12
6
19
28
10
6
19
21
10
6
24
21
13
6
19
19
13
6
19
34
14
6

Sﬂt

15
17
0
0
17
0
0
17
0
0
16
O
0
34
0
0
21
2
O
26
0
0
32
9
4

O
0

AN

OOWOOONgoo—‘hO-D-NW
~

Soil

Section Series

Clay %
29

11

20

15

12

18

18

17

18

33

I(a1

()sh.

()sh.

()sh.

1(a1

()sh.

Osh.

1(al

1(a1

Osh.

1(a1

1(a1

 

APPENDIX B

Soil Moisture Retention Input for CERES Maize Simulation of Soil-Water Cotent.

 

152

APPENDIX B

Volumetric soil moisture retention input for CERES Maize simulation of soil-water
content for the south 52 meters of the grid. The southwest comer of the ﬁeld is the
origin of the sample points at 0 meters in the east and north directions.

Sample point location

East North Horizon Depth Water Content Water Content
meters meters cm -15 bar (m) -1/3 bar (mm)
0.00 0.00 Ap 0-33 0.096 0.291
E 33-50 0.12 0.299
Btl 50-71 0.036 0.221
Bt2 71-107 0.080 0.208
2Bt3 107-150 0.036 0.196
2.00 0.00 Ap 0-23 0.092 0.292
E 23-40 0.092 0.302
Btl 40-64 0.132 0.274
Bt2 64-97 0.072 0. 193
2Bt3 97-150 0.044 0.148
4.00 0.00 Ap 0-23 0.088 0.267
E 23-40 0.088 0.278
Btl 40-64 0.112 0.269
Bt2 64-97 0.088 0.206
2Bt3 97-150 0.040 0.174
6.00 0.00 Ap 0-23 0.084 0.269
Btl 23-58 0.124 0.280
2Bt2 58-122 0.060 0.190
3E/Bt 122-150 0.024 0.116
8.00 0.00 Ap 0-20 0.084 0.262
B 20-28 0.116 0.290
Btl 28-58 0.140 0.214
2Bt2 58-86 0.064 0. 123
3E/Bt 86-150 0.024 0.120

East

meters

10.00

12.00

14.00

16.00

18.00

20.00

22.00

24.00

26.00

North
meters
0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

Horizon Depth

AP
311
312
2313
313/31
A1)
311
312
2313
33/31
Ap
311
312
2313
313/31
Ap
311
312
2313

Ap
311
312
2313
313/31
A3
311
2312
313/31
Ap
311
2312
33/31
Ap
311
2312
33/31
Ap
311
2312
313/31

3E/Bt

cm
0-20
20-40
40-53
53-91
91-150
0-20
20-46
46-64
64-122
122-150
0-23
23-43
43-56
56-104
104-150
0-23
23-43
43-58
58-102
102-150
0-20
20-43
43-61
61-122
122-150
0-23
23-38
38-74
74-150
0-23
23-38
38-79
79-150
0-25
25-43
43-74
74-150
0-28
28-50
50-75
75-150

153

Water Content
-15 bar (mm)

0.084
0.144
0.084
0.044
0.024
0.088
0.148
0.088
0.064
0.024
0.092
0.112
0.084
0.052
0.024
0.096
0.132
0.080
0.052
0.024
0.104
0.112
0.084
0.040
0.024
0.092
0.124
0.048
0.024
0.092
0.108
0.040
0.024
0.084
0.116
0.048
0.024
0.084
0.100
0.040
0.024

Water Content
-1/3 bar (mm)

0.263
0.274
0.162
0.137
0.109
0.266
0.295
0.211
0.169
0.118
0.274
0.292
0.182
0.106
0.101
0.274
0.283
0.205
0.120
0.096
0.267
0.265
0.154
0.107
0.096
0.265
0.276
0.142
0.081
0.260
0.241
01096
0.085
0.259
0.233
0.120
0.076
0.256
0.240
0.160
0.093

 

154

East North Horizon Depth Water Content Water Content
meters meters cm -15 bar (m) -1/3 bar (m)
28.00 0.00 Ap 0-23 0.088 0.264
Btl 23-38 0.100 0.235
2Bt2 38-86 0.064 0.179
3E/Bt 86-150 0.024 0.121
30.00 0.00 Ap 0-23 0.084 0.263
Btl 23-36 0.116 0.262
Bt2 36-48 0.080 0.159
ZBt3 48-137 0.044 0.121
3E/Bt 137-150 0.024 0.077
32.00 0.00 Ap 0-20 0.080 0.255
B 20-28 0.080 0.255
Btl 28-48 0.136 0.288
Bt2 48-69 0.080 0.221
2Bt3 69-150 0.044 0. 109
34.00 0.00 Ap 0-20 0.084 0.261
E 20-28 0.084 0.287
Btl 28-58 0.156 0.281
Bt2 58-91 0.080 0.190
2Bt3 91-150 0.044 0.132
0.00 4.00 Ap 0-28 0.092 0.268
E 28-43 0.096 0.271
Btl 43-84 0.124 0.290
2Bt2 84-150 0.044 0.133
4.25 4.00 Ap 0-25 0.084 0.257
E 25-43 0.108 0.284
Btl 43-69 0.128 0.298
2Bt2 69-142 0.060 0.150
3E/Bt 142-150 0.024 0.095
8.50 4.00 Ap 0-20 0.084 0.257
Btl 20-56 0.144 0.314
2Bt2 56-91 0.056 0.144
3E/Bt 91-150 0.024 0.095
12.75 4.00 Ap 0-23 0.088 0.259
Btl 23-58 0.128 0.299
2Bt2 58-112 0.056 0.150
3E/Bt 112-150 0.024 0.095
17.00 4.00 Ap 0-23 0.096 0.266
Btl 23-66 0.124 0.289
2Bt2 66-112 0.048 0.133
3E/Bt 112-150 0.024 0.095

East

meters
21 .25

25.50

29.75

34.00

0.00

4.25

8.50

12.75

17.00

21.25

North

meters

4.00

4.00

4.00

4.00

8.00

8.00

8.00

8.00

8.00

8.00

Horizon Depth

Ap
311
2312
313/31
Ap
Btl
2312
313/31
AP
311
2312
313/31
Ap
311
2312
A9

E

311
2312
AP

13

311
2312
313/31

Bt 1
2Bt2
3E/Bt

Bt 1
ZBt2
3E/Bt

311
2312
313/31
Ap
311
2312
313/31

cm

0-23
23-53
53-86
86-150
0-25
25-71
71-102
102-150
0-23
23-43
43-1 17
1 17-150
0-20
20-76
76-150
0-28
28-46
46-81
81-150
0-25
25-46
46-69
69-132
132-150
0-23
23-56
56-94
94-150
0-23
23-61
61-1 14

1 14-150
0-23
23-66
66-1 14
1 14-150
0-23
23-56
56-83
83-150

155

Water Content
-15 bar (mm)

0.092
0.116
0.052
0.024
0.084
0.108
0.044
0.024
0.084
0.108
0.056
0.024
0.080
0.144
0.044
0.092

0.0.100

0.124
0.048
0.084
0.100
0.124
0.052
0.024
0.084
0.144
0.060
0.024
0.084
0.128
0.052
0.024
0.092
0.128
0.048
0.024
0.088
0.120
0.056
0.024

Water Content
-1/3 bar (mm)

0.260
0.279
0.133
0.095
0.253
0.269
0.133
0.095
0.256
0.270
0.166
0.095
0.255
0.316
0.128
0.267
0.274
0.289
0.144
0.257
0.275
0.291
0.139
0.095
0.257
0.314
0.150
0.095
0.255
0296

0.144
0.095
0.262
0.294
0.139
0.095
0.257
0.283
0.150
0.095

East

meters

25.5

29.75

34.00

0.00

4.25

8.50

12.75

17.00

21.25

25.50

North

meters

8.00

8.00

8.00

12.00

12.00

12.00

12.00

12.00

12.00

12.00

Horizon

Ap
311
2312
313/31
AP
311
2312
33/31
Ap
311
2312
313/31
Ap

311
2312
33/31
Ap

311
2312
313/31
Ap
311
2312
313/31
Ap

Btl
ZBt2
3E/Bt

311
2312
313/31
A9
311
2312
313/31
Ap
311
2312
313/31

Depth
cm

0-23
23-66
66-109
109-150
0-23
23-41
41-1 14

1 14-150
0-23
23-71
71-142
142-150
0-30
30-43
43-76
76-102
102-150
0-30
30-46
46-66
66-102
102-150
0-25
25-58
58-102
102-150
0-25
25-38
38-63
63-1 12

1 12-150
0-25
25-61
61-1 17

1 17-150
0-20
20-61
61-74
74-150
0-20
20-56
56-132
132-150

156

Water Content
-15 bar (mm)

0.084
0.108
0.044
0.024
0.076
0.108
0.060
0.024
0.080
0.140
0.044
0.024
0.088
0.122
0.108
0.024
0.084
0.108
0.132
0.052
0.024
0.084
0.084
0.144
0.068
0.024
0.076
0.112
0.128
0.044
0.024
0.080
0.136
0.052
0.024
0.088
0.124
0.084
0.024
0.088
0.092
0.048
0.024

Water Content
-1/3 bar (mm)

0.253
0.268
0.133
0.095
0.246
0.269
0.166
0.095
0.253
0.313
0.133
0.095
0.262
0.286
0.270
0.095
0.257
0.283
0.301
0.144
0.095
0.256
0.256
0.313
0.172
0.095
0.246
0.287
0.292
0.122
0.095
0.250
0.305
0.150
0.095
0.257
0.289
0.199
0.095
0.255
0.249
0.128
0.095

East

meters

29.75

34.00

0.00

4.25

8.50

12.75

17.00

21.25

25.50

29.75

North

meters

12.00

12.00

16.00

16.00

16.00

16.00

16.00

16.00

16.00

16.00

Horizon Depth

A9
311
2312
313/31
Ap
311
2312
313/31
A3

13

311
2312
313/31
Ap

3

311
2312
33/31
Ap
311
2312
313/31
Ap
311
2312
33/31
Ap
311
2312
313/31
A3
311
2312
313/31
Ap
311
2312
313/31
Ap
311
2312
313/31

cm

0-20
20-61
61-102
102-150
0-28
28-61
61-1 17

1 17-150
0-33
33-46
46-79
79-109
109-150
0-28
28-36
36-66
66-104
104-150
0-28
28-63
63-102
102-150
0-25
25-66
66-104
104-150
0-20
20-56
56-127
127-150
0-25
25-61
61-137
137-150
0-20
20-43
43-79
79-150
0-20
20-43
43-122
122-150

157

Water Content
-15 bar (mm)

0.092
0.096
0.072
0.024
0.080
0.080
0.052
0.024
0.092
0.112
0.108
0.068
0.024
0.084
0.112
0.140
0.068
0.024
0.076
0.140
0.060
0.024
0.076
0.132
0.056
0.024
0.080
0.124
0.044
0.024
0.084
0.124
0.060
0.024
0.092
0.088
0.044
0.024
0.096
0.100
0.060
0.024

Water Content
-1/3 bar (mm)

0.258
0.253
0.177
0.095
0.247
0.199
0.139
0.095
0.264
0.286
0.270
0.188
0.095
0.256
0.290
0.311
0.194
0.095
0.244
0.310
0.161
0.095
0.245
0.305
0.161
0.095
0.245
0.292
0.139
0.095
0.249
0.290
0.166
0.095
0.256
0.244
0.122
0.095
0.262
0.259
0.155
0.095

East

meters

34.00

0.00

4.25

8.50

12.75

17.00

21.25

25.50

29.75

34.00

North

meters

16.00

20.00

20.00

20.00

20.00

20.00

20.00

20.00

20.00

20.00

Horizon Depth

Ap
311
2312
313/31
Ap
311
2312
313/31
Ap

3

311
2312
313/31
AP

13

311
2312
313/31

311
2312
313/31
AP
311
2312
313/31

Bt l
2Bt2
3E/Bt

Ht 1
2Bt2
3E/Bt

311
2312
313/31
Ap
311
2312
313/31

cm

0-20
20-61
61-1 14

1 14-150
0-28
28-69
69-124
124-150
0-28
28-41
41-69
69-1 17

1 17-150
0-23
23-38
38-69
69-1 19

1 19-150
0-23
23-38
38-75
75-109
109-150
0-20
20-58
58-102
102-150
0-20
20-50
50-86
86-150
0-20
20-50
50-94
94-150
0-23
23-48
48-91
91-150
0-23
23-46
46-74
74-150

158

Water Content
-15 bar (mm)

0.084
0.092
0.048
0.024
0.096
0.132
0.068
0.024
0.084
0.112
0.132
0.088
0.024
0.076
0.120
0.140
0.056
0.024
0.076
0.076
0.116
0.052
0.024
0.088
0.124
0.060
0.024
0.088
0.080
0.036
0.024
0.100
0.084
0.036
0.024
0.096
0.108
0.052
0.024
0.092
0.112
0.044
0.024

Water Content
-1/3 bar (mm)

0.253
0.254
0.144
0.095
0.225
0.251
0.190
0.095
0.211
0.242
0.253
0.206
0.095
0.201
0.248
0.258
0.151
0.095
0.199
0.199
0.232
0.151
0.095
0.211
0.240
0.163
0.095
0.206
0.202
0.112
0.095
0.219
0.195
0.112
0.095
0.218
0.218
0.147
0.095
0.213
0.223
0.128
0.095

East

meters

0.00

4.25

8.50

12.75

17.00

21.25

25.50

29.75

34.00

0.00

North

meters

24.00

24.00

24.00

24.00

24.00

24.00

24.00

24.00

24.00

28.00

Horizon
Ap

Btl
2Bt2
3E/Bt

Bt 1
ZBt2
3E/Bt

Bt l
ZBt2
3E/Bt

Bt 1
ZBt2
3E/Bt

311
2312
Ap
311
2312
Ap
311
2312
313/31

Bt l
2Bt2
3E/Bt

Bt 1
2Bt2
3E/Bt

Bt 1
ZBt2

Depth
cm

0-33
33-48
48-71
71-1 19
119-150
0-30
30-48
48-71
71-112
112-150
0-30
30-51
51-114
114-150
0-23
23-71
71-102
102-150
0-20
20-53
53-150
0-18
18-32
32-150
0-23
23-66
66-104
104-150
0-23
23-46
46-104
104-150
0-20
20-41
41-114
1 14-150
0-25
25-46
46-71
71-150

159

Water Content
-15 bar (mm)

0.096
0.124
0.116
0.052
0.024
0.092
0.120
0.136
0.076
0.024
0.080
0.124
0.052
0.024
0.080
0.132
0.056
0.024
0.088
0.144
0.068
0.092
0.120
0.060
0.100
0.092
0.032
0.024
0.108
0.116
0.052
0.024
0.092
0.104
0.052
0.024
0.104
0.124
0.132
0.052

Water Content
-1/3 bar (mm)

0.226
0.252
0.232
0.151
0.095
0.216
0.250
0.260
0.213
0.095
0.205
0.244
0.144
0.095
0.204
0.250
0.155
0.095
0.211
0.264
0.179
0.214
0.232
0.171
0.222
0.204
0.116
0.095
0.232
0.228
0.159
0.095
0.212
0.216
0.151
0.095
0.232
0.252
0.248
0.159

East

meters

4.25

8.50

12.75

17.00

21.25

25.50

29.75

34.00

0.00

North

meters

28.00

28.00

28.00

28.00

28.00

28.00

28.00

28.00

32.00

Horizon
Ap

311
2312
313/31
AP

Bt 1
2Bt2

Btl
2Bt2
3E/Bt

311
2312
Ap
311
2312
313/31
Ap
311
2312
33/31

Btl
2Bt2
3E/Bt

Bt 1
ZBt2
3E/Bt

Btl
2Bt2

Depth
cm

0-28
28-43
43-66
66-102
102-150
0-20
20-36
36-63
63-150
0-20
20-33
33-66
66-107
107-150
0-30
30-56
56— 107
107-150
0-15
15-69
69-102
102-150
0-15
15-50
50-102
102-150
0-23
23-46
46-89
89-150
0-23
23-53
53-104
104-150
0-33
33-38
38-91
91-150

160

Water Content
-15 bar (mm)

0.088
0.108
0.108
0.056
0.024
0.076
0.124
0.136
0.056
0.076
0.116
0.140
0.048
0.024
0.084
0.092
0.104
0.040
0.092
0.104
0.040
0.024
0.096
0.116
0.036
0.024
0.100
0.116
0.072
0.024
0.096
0.116
0.048
0.024
0.088
0.112
0.128
0.092

Water Content
-1/3 bar (mm)

0.212
0.232
0.221
0.155
0.095
0.200
0.253
0.253
0.155
0.200
0.244
0.259
0.147
0.095
0.207
0.218

0.218 '

0.120
0.212
0.213
0.124
0.095
0.217
0.225
0.120
0.095
0.221
0.227
0.186
0.095
0.218
0.229
0.140
0.095
0.217
0.242
0.250
0.217

161

East North Horizon Depth Water Content Water Content
meters meters cm -15 bar (m) -1/3 bar (mm)
4.25 32.00 Ap 0-33 0.084 0.209
E 33-53 0.104 0.230
Btl 53-69 0.128 0.244
2Bt2 69-97 0.068 0. 186
3E/Bt 97-150 0.024 0.095
8.50 32.00 Ap 0-20 0.084 0.208
E 20-33 0.084 0.208
Btl 33-74 0.140 0.256
2Bt2 74-150 0.068 0.182
12.75 32.00 Ap 0-18 0.088 0.202
Btl 18-69 0.124 0.242
2Bt2 69-138 0.056 0.163
3E/Bt 138-150 0.024 0.095
17.00 32.00 Ap 0-18 0.092 0.210
Btl 18-48 0.124 0.240
2Bt2 48-94 0.052 0.163
3E/Bt 94-150 0.024 0.095
21.25 32.00 Ap 0-20 0.100 0.221
Btl 20-48 0.116 0.227
2Bt2 48-150 0.032 0.104
25.50 32.00 Ap 0-20 0.100 0.221
Btl 20-40 0.092 0.203
2Bt2 40-150 0.036 0.120
29.75 32.00 Ap 0-20 0.096 0.217
Btl 20-53 0.116 0.228
2Bt2 53-107 0.048 0.136
3E/Bt 107-150 0.024 0.095
34.00 32.00 Ap 0-20 0.100 0.223
Btl 20-48 0.132 0.247
2Bt2 48-150 0.044 0.128
0.00 36.00 Ap 0-28 0.100 0.228
E 28-41 0.116 0.246
Btl 41-79 0.144 0.263
ZBt2 79-97 0.076 0.206
3E/Bt 97-150 0.024 0.095
4.25 36.00 Ap 0-25 0.076 0.205
E 25-38 0.124 0.251
Btl 38-61 0.124 0.239
2Bt2 61-114 0.044 0.136
3E/Bt 114-150 0.024 0.095

162

East North Horizon Depth Water Content Water Content
meters meters cm -15 bar (m) -1/3 bar (mm)
8.50 36.00 Ap 0-23 0.084 0.208
E 23-33 0.084 0.208
Btl 33-58 0.136 0.254
2Bt2 58-104 0.056 0.155
3E/Bt 104-150 0.024 0.095
12.75 36.00 Ap 0-20 0.084 0.208
Btl 20-43 0.120 0.233
2Bt2 43-91 0.048 0.143
3E/Bt 91-150 0.024 0.095
17.00 36.00 Ap 0-23 0.096 0.217
Btl 23-38 0.120 0.242
2Bt2 38-89 0.084 0.217
3E/Bt 89-150 0.024 0.095
21 .25 36.00 Ap 0-23 0.096 0.216
Btl 23-114 0.072 0.194
3E/Bt 114-150 0.024 0.095
25.50 36.00 Ap 0-15 0.092 0.214
Btl 15-30 0.116 0.229
2Bt2 30-150 0.052 0.144
29.75 36.00 Ap 0-20 0.092 0.215
Btl 20-56 0.112 0.226
ZBt2 56-117 0.052 0.147
3E/Bt 117-150 0.024 0.095
34.00 36.00 Ap 0-18 0.092 0.217
Btl 18-38 0.116 0.232
2Bt2 38-119 0.056 0.151
3E/Bt 119-150 0.024 0.095
0.00 40.00 Ap 0-25 0.092 0.220
B 25-36 0.120 0.248
Btl 36-56 0.144 0.261
2Bt2 56-122 0.076 0.209
3E/Bt 122-150 0.024 0.095
4.25 40.00 Ap 0-20 0.084 0.209
B 20-28 0. 128 0.254
Btl 28-56 0.144 0.263
2Bt2 56-102 0.060 0.159
3E/Bt 102-150 0.024 0.095
8.50 40.00 Ap 0-18 0.088 0.210
Btl 18-46 0.132 0.248
2Bt2 46-109 0.064 0.178
3E/Bt 109-150 0.024 0.095

 

163

East North Horizon Depth Water Content Water Content
meters meters cm -15 bar (m) -1/3 bar (m)
12.75 40.00 Ap 0-15 0.088 0.211
Btl 15-36 0.120 0.234
2Bt2 36-94 0.044 0. 128
3E/Bt 94-150 0.024 0.095
17.00 40.00 Ap 0-13 0.092 0.214
Btl 13-36 0.116 0.230
2Bt2 36-79 0.088 0.198
3E/Bt 79-150 0.024 0.095
21.25 40.00 Ap 0-18 0.092 0.211
Btl 18-33 0.092 0.203
2Bt2 33-84 0.072 0.190
3E/Bt 84-150 0.024 0.095
25.50 40.00 Ap 0-23 0.092 0.212
Btl 23-46 0.124 0.237
2Bt2 46-114 0.052 0.147
3E/Bt 114-150 0.024 0.095
29.75 40.00 Ap 0-18 0.084 0.207
Btl 18-46 0.124 0.237
ZBt2 46-79 0.052 0.147
3E/Bt 79-150 0.024 0.095
34.00 40.00 Ap 0-18 0.084 0.207
Btl 18-56 0.120 0.233
2Bt2 56-119 0.068 0.201
3E/Bt 1 19-150 0.024 0.095
0.00 44.00 Ap 0-28 0.084 0.213
Btl 28-58 0.128 0.245
2Bt2 58-122 0.036 0.112
3E/Bt 122-150 0.024 0.095
4.25 44.00 Ap 0-25 0.072 0.198
Btl 25-56 0.120 0.237
2Bt2 56-112 0.060 0.174
3E/Bt 112-150 0.024 0.095
8.50 44.00 Ap 0-25 0.076 0.201
Btl 25-53 0.124 0.239
2Bt2 53-99 0.068 0. 186
3E/Bt 99-150 0.024 0.095
12.75 44.00 Ap 020 0.084 0.206
Btl 20-58 0.128 0.243
2Bt2 58-1 17 0.040 0.120
3E/Bt 117-150 0.024 0.095

164

East North Horizon Depth Water Content Water Content
meters meters cm -15 bar (m) -1/3 bar (m)
17.00 44.00 Ap 0-18 0.088 0.210
Btl 18-48 0.128 0.243
2Bt2 48-102 0.084 0.221
3E/Bt 102-150 0.024 0.095
21.25 44.00 Ap 0-20 0.084 0.204
Btl 20-38 0.084 0.205
ZBt2 38-84 0.060 0. 163
3E/Bt 84-150 0.024 0.095
25.50 44.00 Ap 0-18 0.084 0.205
Btl 18-50 0.116 0.228
2Bt2 50-124 0.044 0.128
3E/Bt 124-150 0.024 0.095
29.75 44.00 Ap 0-20 0.080 0.200
Btl 20-50 0.068 0.182
2Bt2 50-107 0.056 0.151
3E/Bt 107-150 0.024 0.095
34.00 44.00 Ap 0-20 0.084 0.205
Btl 20-69 0.1 16 0.228
2E/Bt 69-150 0.024 0.095
0.00 48.00 Ap 0-28 0.088 0.216
E 28-38 0.124 0.252
Btl 38-74 0.140 0.259
2Bt2 74-1 17 0.076 0.202
3E/Bt 117-150 0.024 0.095
4.25 48.00 Ap 0-23 0.076 0.200
E 23-36 0.124 0.252
Btl 36-61 0.132 0.247
2Bt2 61-119 0.068 0.182
3E/Bt 119-150 0.024 0.095
8.50 48.00 Ap 0-23 0.076 0.201
Btl 23-56 0.124 0.243
2Bt2 56-112 0.068 0.182
3E/Bt 112-150 0.024 0.095
12.75 48.00 Ap 0-20 0.080 0.203
Btl 20-48 0.132 0.246
2Bt2 48-97 0.052 0.144
3E/Bt 97-150 0.024 0.095
17.00 48.00 Ap 0-20 0.084 0.208
Btl 20-48 0.132 0.249
2Bt2 48-112 0.040 0.124
3E/Bt 112-150 0.024 0.095

East

meters

21.25

25.5

29.75

34.00

0.00

4.25

8.50

12.75

17.00

North

meters

48.00

48.00

48.00

48.00

52.00

52.00

52.00

52.00

52.00

Horizon

Ap
311

2312
Ap
311
2312
313/31
Ap
311
2312
313/31

311
2312
33/31
A9

Ht 1
2Bt2
3E/Bt

Btl
2Bt2
3E/Bt

311
2312
313/31
Ap

311
2312
33/31
Ap

Bt 1
ZBt2
3E/Bt

Depth
cm

0-23
23-41
41-150
0-20
20-46
46-122
122-150
0-23
23-38
38-122
122-150
0-18
18-48
48-86
86-150
0-25
25-36
36-63
63-1 12

1 12-150
0-25
25-38
38-66
66-1 14
1 14-150
0-25
25-38
38-58
58-107
107-150
0-23
23-33
33-61
61-102
102-150
0-23
23-30
30-61
61-97
97-150

165

Water Content
-15 bar (mm)
0.084
0.112
0.028
0.084
0.108
0.104
0.024
0.088
0.120
0.064
0.024
0.084
0.112
0.044
0.024
0.088
0.100
0.108
0.057
0.024
0.076
0.1 12
0.120
0.040
0.024
0.076
0.112
0.120
0.052
0.024
0.080
0.116
0.120
0.049
0.024
0.088
0.120
0.152
0.050
0.024

Water Content
-1/3 bar (mm)
0.206
0.224
0.097
0.206
0.219
0.264
0.095
0.209
0.232
0.175
0.095
0.207
0.225
0.128
0.095
0.262
0.272
0.270
0.183
0.095
0.245
0.287
0.283
0.128
0.095
0.245
0.286
0.285
0.166
0.095
0.249
0.291
0.290
0.155
0.095
0.257
0.294
0.319
0.161
0.095

 

166

East North Horizon Depth Water Content Water Content
meters meters cm -15 bar (m) -1/3 bar (m)
21.25 52.00 Ap 0-18 0.084 0.250

Btl 18-41 0.112 0.271

2Bt2 41-112 0.032 0.106

3E/Bt 112-150 0.024 0.095
25.50 52.00 Ap 0-18 0.092 0.259

Btl 18-61 0.100 0.259

2Bt2 61-150 0.035 0.111
29.74 52.00 Ap 0-18 0.084 0.249

Btl 18-36 0.120 0.281

2Bt2 36-79 0.052 0.166

3E/Bt 79-150 0.024 0.095
34.00 52.00 Ap 0-20 0.088 0.260

Btl 20-48 0.1 16 0.279

2Bt2 48-127 0.045 0.144

3E/Bt 127-150 0.084 0.249

 

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