UNIVERSITY OF CALIFORNIA, SANTA CRUZ Comparison of Cone Penetration and Soil Texture Data at a Site being Considered for Managed Aquifer Recharge of Stormwater A thesis submitted in partial satisfaction of the requirements for the degree of BACHELOR OF SCIENCE in EARTH AND PLANETARY SCIENCES Dominique A. van den Dries 8 June 2018 The thesis of Dominique A. van den Dries is approved by __________________________________ Andrew T. Fisher, Professor of Earth and Planetary Sciences
Transcript
UNIVERSITY OF CALIFORNIA,
SANTA CRUZ
Comparison of Cone Penetration and Soil Texture Data at a Site being Considered for Managed Aquifer Recharge of Stormwater
A thesis submitted in partial satisfaction of the requirements for the degree of
BACHELOR OF SCIENCE
in
EARTH AND PLANETARY SCIENCES
Dominique A. van den Dries
8 June 2018
The thesis of Dominique A. van den Dries is approved by
__________________________________ Andrew T. Fisher, Professor of Earth and Planetary Sciences
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Abstract
California relies heavily on groundwater stored within aquifers, especially during recent
drought conditions. Aquifers are becoming overdrawn, so finding methods to recharge them is
crucial. Managed Aquifer Recharge redirects runoff to areas where it can quickly percolate into
the subsurface. For an area to be a good candidate for MAR, the nearby soil profile must meet
certain geologic requirements: coarse sediments with a high hydraulic conductivity capped with
a clay layer. We evaluated Kelly Thompson Ranch, a potential site for MAR, using two different
methodologies in order to determine the area’s soil profile.
I. Introduction
A. Motivation and Goals
California has grown increasingly dependent on groundwater resources in recent years.
Depletion of groundwater resources is unsustainable, and can cause a myriad of issues: lowering
of water levels, aquifer contamination, seawater intrusion, subsidence, and permanent loss of
storage. The limited water resources of California combined with changing land use and periodic
drought conditions have inspired the development and use of innovative, new methods of water
management and reclamation.
Managed aquifer recharge refers to the “the movement of water via man-made systems
from the surface of the earth to underground water-bearing strata where it may be stored for
future use” (Mortimer 2014). Through modification of the surrounding landscape, resource
managers can apply surface water from many different sources and route this water into an
aquifer for environmental benefit and later use. Some forms of MAR rely on gravity and surface
tension to draw the water into the subsurface, and some use direct injection with wells. In order
for infiltration to occur the surrounding soils must be porous and permeable, so the water can
percolate down. The chemical and biological activity within the surrounding soils also provides
an element of filtration to the introduced water (Mortimer 2014). Under ideal conditions, MAR
yields both volume and quality of usable water that would have otherwise become runoff. Areas
that are good candidates for MAR will adhere to a certain soil texture profile, especially access
to coarse textures with high hydraulic conductivity that are able to accommodate large flow
rates.
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This thesis describes techniques used to evaluate a field site, and presents and interprets
these results to assess suitability of this site for a MAR project. In this study, we aim to establish
a ground truth at the field site by contrasting two soil profiles determined by two different
methods: one from cone penetration, and one from soil texture analysis based on sampling of
cores. We combine results of both methods and settle on a truthful, aggregated soil profile. Once
we determine the soil profile, we calculate hydraulic conductivity and assess whether the area is
suitable for an MAR project.
B. Regional Setting
Kelly Thompson Ranch is located in Watsonville, CA within the Pajaro Valley
Groundwater Basin (PVGB). Aquifers in this area compromise a mixture of marine and
terrestrial deposits, including the following water-bearing geologic units (starting with the
oldest): Purisima Formation, the Aromas Red Sand, Terrace and Pleistocene Eolian Deposits,
Quaternary alluvium and Dune Deposits. The Aromas Sand is the most widely used aquifer in
this area, and generally has excellent transmissive and storage properties. Recharge within the
PVGB occurs through “direct percolation of rainfall and streamflow seepage from the Pajaro
River and its tributaries and percolation of irrigation water (PVWMA 2006)." The field site is
located ~2.2 km from the base of the Santa Cruz Mountains, to the east (Fig I-1), allowing it to
receive considerable volumes of runoff during heavy rain events. This region has a coastal and
highly seasonal climate, with rainy winters and dry, but foggy summers, and an annual average
precipitation of 23.51 inches (PVWMA 2006).
Due to outflows (including pumping) that are greater than inflows over the long term,
groundwater levels have been lowered in many parts of the PVGB. Periodic droughts have
further reduced groundwater resources, and now more than 51 square miles of the basin have
water levels below sea level. Raines, Melton, and Carella described how this has affected the
storativity of the area in their 2006 PVWMA article:
“The total storage capacity of the basin is estimated to be 2,000,000 af above the
Purisima Formation. If the storage from the upper Purisima Formation is included, then
the estimate of total storage capacity of the basin is 7,770,000 af. Between 1964 and
1997, there has been an estimated loss of 300,000 af of freshwater storage from the basin.
Approximately 200,000 af of this freshwater storage loss is due to seawater intrusion,
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while 100,000 af is due to conditions of chronic overdraft and resultant falling
groundwater levels.”
The PVGB was added to the California Department of Water Resources’ list of basins
facing “critical overdraft” in 2008. To combat overdraft, serious efforts must be made to balance
outputs and inputs within the basin. Provided the area meets the geologic requirements to support
MAR, the PVGB could benefit from the enhanced infiltration.
II. Methods
A. CPT Overview
The Cone Penetration Test (CPT) is widely used to assess soil texture and property
(Robertson, 2009; Been, 2010) (Fig. II-1). The test is economical, repeatable, and returns a
continuous column of high resolution (cm scale) data. CPT predicts the Soil Behavior Type
(SBT) by imposing boundary conditions on soils. The cone responds to the in-situ mechanical
behavior of the soil, and returns data based on empirical relationships between the parameters.
Throughout the duration of the test, in-situ measurements of uncorrected tip resistance (𝑞"),
sleeve friction (𝑓𝑠), and dynamic pore pressure (µ%) are relayed back to the data collection
system.
Before beginning a test, the cone is saturated with a viscous liquid, either glycerin or
silicone oil, and a baseline measurement is taken with the cone hanging freely in a vertical
orientation. Baseline readings are checked with an independent multimeter. The piezocone is
advanced into the ground at a rate of 2 cm/s. The test may be paused at certain depths to take
pore pressure dissipation readings, useful in evaluating groundwater conditions and permeability.
The cone penetration test continues until either: 1) a pre-determined target depth has been
reached 2) refusal occurs, indicating a phreatic surface has been reached. After cessation of the
test, tip resistance is normalized by cone area 𝑞& = 𝑞" + µ% 1 − 𝑎 and friction ratio is
calculated 𝑅𝑓 = 100% ∗ 1234
. These two parameters, 𝑞& and 𝑅𝑓, are multiplied by the tip area to
achieve linear normalization, and are compared to reference data to determine the lithology
encountered at each measurement depth (Fig II-2).
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B. Field Methods
On 12 November 2015, California Push Technologies conducted six cone penetration
tests at Kelly Thompson Ranch, using a 20-ton deployment system (Fig II-3; Table II-1). Two
holes (KT2 and KT4) were drilled to refusal, and the rest were drilled to a target depth between
20 and 25 feet below ground surface (ft-bgs). In addition, push cores were collected at location
KT5, allowing analysis and direct comparison between soil and CPT data.
C. Laboratory Methods
The sediment core from KT5 was collected in six sections (DP1-DP6) and subsampled at
5-10 cm intervals (Table II-2). These samples were digested using 2-4 mL of 30% hydrogen
peroxide and left inside a fume hood to vent for three days in order to digest (remove) organic
material. Digested samples were frozen solid and placed inside a freeze dryer to sublimate the
frozen fluid, leaving behind only the sediment in a powdered form. Freeze dried samples were
sieved (≤1.0 mm) and analyzed for grain size distribution with a Beckman Coulter LS 13320
Particle Size Analyzer, which returned grain size distribution percentages in 92 bins ranging
from 0.375 - 2000 um. Replicate and duplicate samples were periodically analyzed to ensure
both instrument and sampling accuracy. A total of 82 grain-size subsamples were analyzed from
the KT5 core.
D. Analytical Methods
1. CPT Analytical Methods
The CPT calculations are based on values of tip resistance, sleeve friction and pore
pressures considered at each measurement depth or averaged over a specified layer thickness.
Corrected and area-normalized values are used for all calculations. The SBTn category is
determined by the ratio of friction to tip resistance, and returns a value based on the SBTn
diagram (Fig II-2). This value is indicative of how the soil behaves, which may differ from the
soil’s physical composition.
2. PSA Analytical Methods
PSA output files comprise 92 grain-size bins arranged on a logarithmic scale. Data were
processed with Matlab and Python scripts that compiled the data across the diameter range of 0.4
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um to 1 mm and combined them into a smaller number of bins. Data were compiled in a
spreadsheet and examined by the six subsections (DP1-DP6). A sample of the naming
conventions can be seen in Table II-2. The average percentages for each bin were computed to
plot a histogram for each section.
Each sample was paired to a corresponding CPT data-point at an equivalent depth,
allowing us to compare grain size analyses with the SBTn assignment from the cone penetration
survey. In addition, grain size data were run through a script to calculate porosity, void ratio, and
hydraulic conductivity, using standard relations for estimating these values from texture
information (Table II-3) (Chapuis 2003).
III. Results
A. Direct Push Results
The direct push results (Fig III-1) suggest the majority of the KT5 core behaves as clay,
with thin (cm-scale) siltier layers. Between 20 and 25 ft-bgs, the soil becomes sandier and there
is a small spike in pore pressure. The sudden shift from fines to coarser particles suggests the top
of an aquifer may occur near 19 ft-bgs (5.8 m) beneath the ground surface. Core recovery for
KT-5 was incomplete, with section 2 having the lowest recovery, 61.5%, and section 5 having
the highest, almost 100% (Table III-1).
B. Particle Size Analysis Results
The KT5 core includes two main soil lithologies. The d10, d50 and d90 all increase
throughout the core, and at the deepest part, the soil becomes particularly coarse (Fig III-2). The
recovered sections were assigned to corresponding depths of penetration with the coring tube.
Where recovery was less than 100%, the core sample depths were assigned to the top of each
cored section (Table III-3).
Most of the DP1 sediment falls between 5-120 um, which is fine silt and fine sand (Fig
III-3). The graph appears semilog-normal, aside from a spike in coarse sands around 775 um.
DP1 samples came from the top 0.46 m of the core.
DP2 exhibits slight bimodality (Fig III-4). It has a very fine silt peak, as well as a fine
sand peak. Most of these samples are within the 2-120 um range and are considered “silty
sands.” DP2 samples came from the upper 0.75 m of section 2 of KT5.
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DP3 makes up the next 0.88 m of the core. The histogram from this section appears to
have three peaks: a fine silt hump around 7 um, a fine sand hump spanning 80-160 um, and a
coarse sand hump near 900 um (Fig III-5).
The next 0.97 m belong to DP4. The histogram from DP4 looks like a less noisy version
of that from DP3 (Fig III-6). It clearly shows the three peaks at fine silt, fine sand, and coarse
sand boundaries at 9 um, 180 um and 1 mm, respectively.
DP5 is from the penultimate 1.2 m of the KT5 core. The data are bimodal, with two
distinct humps near 7 um and 250 um (Fig III-7). DP5 is composed primarily of sand and silt.
The final 0.86 m of the KT5 core belong to DP6. Particle size analysis determined
most of this data falls between 100 um and 1 mm, making it primarily sand (Fig III-8). The peak
volume occurs within diameter range 280-320 um.
IV. Discussion
A. Comparing Core and CPT data
To compare the PSA results with the CPT results, I paired each PSA file with a
corresponding CPT file based on depth. The three statistically significant SBTn types are “Clay
to Silty Clay” (hereby referred to as SBTn-3), “Clayey Silt to Silty Clay” (SBTn-4), and “Clean
Sands to Silty Sands” (SBTn-6). SBTn-3 contains 58 grain size data points, SBTn-4 has 10, and
SBTn-6 has 8. SBTn-5, -8, and -9 had n ≤ 3 data points, and are not discussed.
With 70% of datapoints correlating to SBTn-3, this category contained 4x as much data
as the other SBTn values. We expected most of these grains to fall in the 0-45 um range. About
16% of this SBTn was indeed “clay” and had grains ≤2 um in diameter (Fig IV-1). Coarse clay
and “Silt” (diameter = 2-63 um) made up the majority with 65%. With a somewhat high standard
deviation, the remaining ~20% is composed of sand, which causes the distribution to appear
bimodal. The coarser hump is responsible for skewing the average grain size higher. Both the
clay and silt portions have averages similar to their medians, and standard deviations less than
17, suggesting a somewhat normal distribution for the smaller um sections. Over 80% of this
SBTn lies within clay and silt boundaries.
About 12% of the data belongs to SBTn-4 (Fig IV-2). We expected to see something
similar to SBTn-3, but skewed more towards silt, with higher average grain sizes. There was less
variability than seen with SBTn-3, in part because of smaller sample size. The medians are quite
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close to the averages in SBTn-4, with low standard deviations spanning throughout the clay, silt,
and sand portions. This suggests normal, accurate and predictable data patterns. The sand
percentages were somewhat higher than expected, with sand fractions (~22%) exceeding clay
fractions (~14%).
The last statistically significant category, SBTn-6, contains 10% of grain size data points.
We predicted this dataset would skew coarser, as sand dominates this soil category (Fig IV-3).
The percentage of sand spanned 61-88% of these samples. This SBTn is made up
overwhelmingly of large grains, with sand composing 76% on average. The medians of all three
sections are nearly identical to their averages, indicating a normal distribution.
B. Conductivity calculations
The hydraulic conductivity within the KT5 core spans three orders of magnitude (Fig IV-
4). The first 5.5 meters of the core maintain a hydraulic conductivity of 10^-8 m/s. About 5.6
meters below the ground surface, the conductivity begins to increase in magnitude, reaching a
maximum of 2e-6 m/s at depths of 6.1 to 6.2 m. Peak conductivity occurs within SBTn-6, “Clean
Sands to Silty Sands”. The effective hydraulic conductivity of this core is 5.0e-8 m/s, dominated
by the lower values associated with finer grained layers.
C. Accuracy of lithologic assignment based on CPT data
There will sometimes be a discrepancy when comparing soil types as determined by CPT
versus traditional grain size analysis due to the complex nature of soil. Robertson (2009) outlines
a few examples where this difference arises: highly plastic fines and very stiff, heavily
overconsolidated fines both tend to have CPT-based SBTs that do not match their USCS-based
SBTs. For engineering and experimental purposes, the actual behavior of the soil is needed,
which makes CPT the more logical choice for soil determination.
In the case of the Kelly Thompson Ranch site investigation, the CPT results closely
match the results from the particle size analysis. Fig IV-5 shows the histogram of the final 0.86
m of the KT5 core (determined by particle size analysis) overlaid with the architype of SBTn-6
(determined using cone penetration). The two histograms are nearly identical, suggesting the
ground truth is consistent through both methods of determination, at least for the sandier portion
of the core. Robertson (2009) states the CPT method is increasingly accurate as the soil becomes
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coarser, and these data support his assertion. Bearing in mind the benefits of relying on Soil
Behavior Type, the Cone Penetration Test seems like the more pragmatic and reliable of the two
methods.
D. Suitability of the field site for managed recharge
Based on the consistency between sampling methods within the final 0.86 m of the KT5
core, it appears that the top of the shallow aquifer unit may be between 5.5 and 5.8 m beneath the
ground surface. For an aquifer to be present in this zone, the soils would need to be a mixture of
silts and sands: coarse sediment in which fluids can flow. Both the Cone Penetration Test and
Particle Size Analysis suggest this layer to be composed of aquifer-conducive soils.
This can be further confirmed by examining Fig IV-4. Beginning around 5.5 m beneath
the ground surface, the hydraulic conductivity increases abruptly by two orders of magnitude. As
we reach larger K values, the ease of fluid flow increases. This location is likely part of the
saturated zone, or the outermost reaches of the aquifer.
Assuming these findings from the KT5 core can be applied to the greater field site, the
Kelly Thompson Ranch project site appears to be appropriate for location of a managed recharge
infiltration basin, provided water is permitted to bypass the shallowest, fine-grained layers.
These would impede infiltration. In contrast, deeper layers appear to be more suitable for
infiltration and recharge. Both the CPT and the particle size data indicate this soil texture profile
to begin with a clay layer, that eventually transitions to a coarser, sandier layer. Removal of the
overlying clay should expose highly conductive, deeper layers to infiltration and recharge.
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V. References cited
Been, K. & Quinonez, A. (2010) Interpretation of the CPT in engineering practice.
Chapuis, R.P, Aubertin, M., 2003. On the use of the Koenzy Carman equation to predict the
hydraulic conductivity of soils. Can. Geotech. J. 40 (3), 616-628.
Greig, Jim (2015) CALCULATED CPT GEOTECHNICAL PARAMETERS: A Detailed
Description of the Methods Used in CPT Inc.’s CPT Geotechnical Parameter Calculation and
Plotting Software.
Mortimer, Evan (2014) Managed Aquifer Recharge. The Water Report, 127.
Pajaro Valley Water Management Association (2006) Central Coast Hydrologic Region Pajaro
Valley Groundwater Basin. California’s Groundwater Bulletin 118.
Robertson, P.K. (2009) Interpretation of cone penetration tests - a unified approach. Canadian
Geotechnical Journal, 46, 11.
Robertson, P.K. (1990) “Soil Classification Using the Cone Penetration Test”, Canadian Geotechnical Journal, Volume 27: 151-158.
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Figure Captions Fig I-1 – Regional and soil map of PVGB, Watsonville. Fig II-1 – Schematic of the rig used to drill the six boreholes. It has a cross sectional area of 15 cm2, and a sleeve area of 225 cm2. Fig II-2 - The SBTn is determined using the ratio of friction to cone resistance. Friction and resistance have been normalized by the area of the tip. Fig II-3 – Aerial photograph of field site. On November 12th 2015, California Push Technologies drilled six boreholes at the Kelly Thompson Ranch. Fig III-1 - The Soil Behavior Type results from the cone penetration test extend 22 feet subsurface. The majority of the core is clay, with some sands at the bottom. Fig III-2 - The d10, d50, and d90 all increase with depth in the KT5 core. Fig III-3 - DP1 spans 0-1000 um and composes the initial .4575 m of KT5. Fig III-4 - DP2 spans 0-500 um and composes the subsequent .75 m of KT5. Fig III-5 - DP3 spans 0-1000 um and composes the subsequent .8825 m of KT5. Fig III-6 - DP4 spans 0-1200 um and composes the subsequent .965 m of KT5. Fig III-7 - DP5 spans 0-1000 um and composes the subsequent 1.2125 m of KT5. Fig III-8 - DP5 spans 0-1000 um and composes the final .8575 m of KT5 Fig IV-1 – The distribution histogram of SBTn3 (Clay to Silty Clay) Fig IV-2 – The distribution histogram of SBTn4 (Clayey Silt to Silty Clay) Fig IV-3 – The distribution histogram of SBTn6 (Clean Sand to Silty Sand) Fig IV-4 – The hydraulic conductivity of KT5 spans 3 orders of magnitude. Keff = 5.0e-8 m/s Fig IV-5 – Section DP6 from texture analysis is nearly identical to SBTn6 from the cone penetration test.
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Table Titles
Table II-1. Cone Penetration Borehole Metadata
Table II-2. Example of direct push core sample sections and depths.
Table II-3. Equations used to calculate n, e, and K from grain size data
Table III-1. Core recovery and assigned depths
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Fig II-1
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Fig II-2
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Fig II-3
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Fig III-1 - KT5 Soil Behavior Results from CPT
Fig III-1
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Fig III-2
0
5
10
15
20
25
1 10 100 1000
Depth Be
low Su
rface (ft)
Grain Size [um]
Grain Size Distribution by Depth
d10 d50 d90
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Fig III-3
0
0.5
1
1.5
2
2.5
0 1 10 100 1000 10000
Vol %
Bin Size (um)
DP1
18
Fig III-4
0
0.5
1
1.5
2
2.5
3
0 1 10 100 1000 10000
Vol %
Bin Size (um)
DP2
19
Fig III-5
0
0.5
1
1.5
2
2.5
3
3.5
0 1 10 100 1000 10000
Vol %
Bin Size (um)
DP3
20
Fig III-6
0
0.5
1
1.5
2
2.5
3
3.5
0 1 10 100 1000 10000
Vol %
Bin Size (um)
DP4
21
Fig III-7
0
0.5
1
1.5
2
2.5
3
3.5
4
4.5
0 1 10 100 1000 10000
Vol %
Bin Size (um)
DP5
22
Fig III-8
0
1
2
3
4
5
6
7
8
9
0 1 10 100 1000 10000
Vol %
Bin Size (um)
DP6
23
Fig IV-1
0
1
2
3
4
5
6
7
0 1 10 100 1000 10000
Percen
tage
Particle diameter (um)
Clay to Silty Clay (SBTn-‐3)
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Fig IV-2
0
0.5
1
1.5
2
2.5
3
0 1 10 100 1000 10000
Percen
tage
Particle diameter (um)
Clayey Silt to Silty Clay (SBTn-‐4)
25
Fig IV-3
0
1
2
3
4
5
6
7
8
9
0 1 10 100 1000 10000
Percen
tage
Particle diameter (um)
Clean Sand to Silty Sand (SBTn-‐6)
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Fig IV-4
0.00E+00
5.00E-‐07
1.00E-‐06
1.50E-‐06
2.00E-‐06
2.50E-‐06
0 1 2 3 4 5 6 7
K (m
/s)
Depth below Surface (m)
Hydraulic Conductivity within KT5
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Fig IV-5
0
1
2
3
4
5
6
0 1 10 100 1000 10000
Vol %
Bin Size um
SBTn-‐6 vs DP6
Particle Size Analysis Cone Penetration
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Table II-1. Cone Penetration Borehole Metadata
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Table II-2. Example of direct push core sample sections and depths.
Note: “DepTOS” refers to depth – Top of Section. “DepBGS” refers to depth – Beneath Ground Surface.
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Table II-3. Equations used to calculate n, e, and K from grain size data
