CORRELATIONS OF HYPORHEIC PERMEABILITY AND GRAIN SIZE
DISTRIBUTIONS IN RIVER GRAVELS
A Thesis
Presented to the faculty of the Department of Geology
California State University, Sacramento
Submitted in partial satisfaction of
the requirements for the degree of
MASTER OF SCIENCE
in
Geology
by
Joseph Warren Rosenbery II
SPRING
2014
© 2014
Joseph Warren Rosenbery II
ALL RIGHTS RESERVED
ii
CORRELATIONS OF HYPORHEIC PERMEABILITY AND GRAIN SIZE
DISTRIBUTIONS IN RIVER GRAVELS
A Thesis
by
Joseph Warren Rosenbery II
Approved by:
__________________________________, Committee Chair
Dr. Timothy Horner
__________________________________, Second Reader
Dr. Kevin Cornwell
____________________________
Date
iii
Student: Joseph Warren Rosenbery II
I certify that this student has met the requirements for format contained in the University
format manual, and that this thesis is suitable for shelving in the Library and credit is to
be awarded for the thesis.
__________________________, Department Chair ___________________
Dr. Timothy Horner
Date
Department of Geology
iv
Abstract
of
CORRELATIONS OF HYPORHEIC PERMEABILITY AND GRAIN SIZE
DISTRIBUTIONS IN RIVER GRAVELS
by
Joseph Warren Rosenbery II
Salmonid spawning habitat restoration projects have been an effective method of
mitigating the negative effects of anthropogenic influence on the Lower American River,
Near Sacramento, California. Embryonic mortality rates of salmonid species are greatly
affected by gravel permeability and grain size distributions within the host gravel. The
goal of this research is to further understand how the composition of the hyporheic river
gravels affects permeability.
Using Sodium-Chloride tracers, standpipe drawdown tests and bulk samples,
relationships were analyzed between measured seepage velocities and grain size
distribution. These statistics include mean grain size, sorting, skewness and kurtosis.
Measurements were recorded at approximately 30cm depth in the gravel, where salmonid
species typically lay their eggs. Results of permeability measurements and grain size
distributions were compared in both restored and un-restored spawning gravels.
v
A clear relationship exists between the sorting (Standard Deviation) of gain size
population and the seepage velocity. As restoration sites age seepage velocities degrade
and become more unpredictable. Variability of seepage velocities with respect to grain
sorting is the result of other factors such as grain orientation and packing, which
influence permeability by control porosity. In this respect, permeability may be used as a
proxy for the relative health of a particular spawning site.
_______________________, Committee Chair
Dr. Timothy Horner
_______________________
Date
vi
DEDICATION
This thesis is dedicated to my parents for their love, endless support, and
encouragement.
vii
ACKNOWLEDGEMENTS
This thesis was completed with the assistance of:








Dr. Tim Horner
Dr. Kevin Cornwell
Dr. Dave Evans
Jay Heffernan
Katy Janes
Jessica Bean
Mike O’Connor
And many other people who helped in the field
Thanks to Tim Hulett, who showed me how cool geology really is.
Kelly, I love you.
viii
TABLE OF CONTENTS
Page
Dedication .................................................................................................................. vii
Acknowledgements ................................................................................................... viii
List of Tables .............................................................................................................. xi
List of Figures ........................................................................................................... xiii
1. INTRODUCTION ...................................................................................................1
1.1 Background ................................................................................................. 1
1.2 Study Objectives ......................................................................................... 4
1.3 Study Area .................................................................................................. 5
2. METHODS ............................................................................................................. 7
2.1 Sodium-Chloride Tracers ............................................................................ 7
2.2 Standpipe Drawdown Testing ................................................................... 11
2.3 Bulk Samples... ..........................................................................................19
3. RESULTS ............................................................................................................. 22
3.1 Sodium-Chloride Tracers .......................................................................... 22
3.2 Standpipe Drawdown Testing ................................................................... 27
3.3 Bulk Samples... ..........................................................................................42
4. ANALYSIS OF RESULTS .................................................................................. 48
4.1 Comparison of Results: Seepage Velocity vs. Hydraulic Conductivity... .48
ix
4.2 Seepage Velocity vs. Grain Size Distribution............................................54
4.3 Additional Factors That Affect Permeability... ..........................................61
4.4 Equipment Factors... ..................................................................................63
5. CONCLUSION... ...................................................................................................67
5.1 Conclusion .................................................................................................67
REFERENCES ........................................................................................................... 71
x
Tables
Page
2.1 Hydraulic conductivity values in terms of standpipe inflow components .............. 18
3.1 Table showing the seepage velocities from NaCl tracer tests conducted at two sites
on the American River ............................................................................................ 26
3.2 Drawdown test results for the River Bend Park control site conducted on the
American River prior to augmentation ................................................................... 30
3.3 Drawdown test results for the US Spit conducted on the American River ............. 32
3.4 Drawdown test results for the Upper Sailor Bar 2008 site conducted on the
American River ....................................................................................................... 34
3.5 Drawdown test results for the Upper sailor Bar 2009 site on the American River 35
3.6 Drawdown test results for the Upper Sunrise 2010/2011 site conducted on the
American River ....................................................................................................... 36
3.7 Drawdown test results for Lower Sailor Bar 2012 site conducted on the American
River........................................................................................................................ 38
3.8 Drawdown test results for the River Bend Park 2013 Site conducted on the
American River ....................................................................................................... 40
3.9 Results for small bulk samples by site with associated hydraulic conductivity (K)
and calculated seepage velocity (Vs) ...................................................................... 42
3.10 Conversion table for grain size ranges .................................................................. 45
3.11 Interpretations concerning sorting based on phi standard deviation ..................... 46
xi
4.1 The representative values for total porosity and effective porosity values for
selected sedimentary materials ............................................................................... 50
4.2 Data from NaCl tracer tests for 2 sites on the LAR ................................................ 53
xii
Figures
Page
1.1 The hyporheic zone where surface water interacts with ground water ..........................3
1.2 Augmentation locations on the American River ............................................................6
2.1 Schematic showing the construction of the standpipes used for the sodium-chloride
tracer tests ......................................................................................................................8
2.2 Drawing showing a profile view of the sodium-chloride tracer test setup ..................10
2.3 The empirical calibration chart recreated from Terhune (1958) and Barnard and
McBain (1994) .............................................................................................................12
2.4 An annotated picture of the pump rig used for the standpipe drawdown test..............14
2.5 Diagram showing the various components of the sump rig used for the standpipe
drawdown test ..............................................................................................................15
2.6 An engineering drawing showing the dimensions of the modified Terhune Mark VI
standpipe ......................................................................................................................16
2.7 Chart showing minimum sample weight for sediment of different sizes at different
sample accuracy intervals ............................................................................................20
3.1 Plotted results from the NaCl tracer test from the Upper Sunrise 2010/ 2011 site
showing electrical conductivity over the duration of the test ......................................23
3.2 Plotted results from the NaCl tracer test from the Upper Sunrise 2010/ 2011 site
showing electrical conductivity over the duration of the test ......................................24
xiii
3.3 Location of 8 NaCl tracer tests (yellow points) at the Upper sunrise 2010/ 2011
restoration site (red dashed line) ..................................................................................25
3.4 - Location of 3 NaCl tracer tests (yellow points) at the Upper Sailor Bar 2009
restoration site (red dashed line) ..................................................................................27
3.5 River Bend Park 2013 pre augmentation (yellow dashed line) before augmentation .28
3.6 Upper Sunrise 2010/ 2011 (red dashed line) and Upper Sunrise Spit (yellow dashed
line) ..............................................................................................................................31
3.7 Upper Sailor Bar 2008 (right; red dashed line) and Upper Sailor Bar 2009 (left; red
dashed line) ..................................................................................................................33
3.8 Lower Sailor Bar 2012 (red dashed line). Blue dots indicate location where
drawdown test was performed .....................................................................................37
3.9 River Bent Park 2013 post augmentation (red dashed line) ........................................39
3.10 Average hydraulic conductivity compared to the age of the gravel addition ............41
4.1 Mean Grain Size in mm vs. apparent seepage velocity ...............................................55
4.2 Visual depictions of various sorting values .................................................................56
4.3 Sorting value in phi units vs. apparent seepage velocity. ............................................57
4.4 Sorting vs. apparent seepage velocity ..........................................................................58
4.5 Skewness in phi units vs. apparent seepage velocity ...................................................59
4.6 Kurtosis vs. apparent seepage velocity ........................................................................60
4.7 Graphical depiction of hoe packing affects pore space between grains ......................62
xiv
4.8 As water is removed during the development stage of the drawdown tests, the rate of
standpipe inflow increases until the well is developed and measurements stabilize
xv
1
Chapter 1
Introduction
1.1 Background
The American River is crucially important for a large population of pacific
salmon. Salmon are an anadromous fish species. Born in fresh water, salmon migrate to
the ocean to mature after a few months (Lackey, 2000). Salmon typically return to their
parental fresh water spawning ground (Cooper and Mangel, 1999). Female salmon create
nests, called redds, approximately 12" (30 cm) deep in the gravel where eggs are laid.
Eggs are fertilized and then buried (Lackey, 2000; Merz et al., 2008).
Survival of eggs deposited by salmon depend largely upon the supply of
oxygenated water available to them (Terhune, 1958). Human activity often degrades
natural spawning habitat, so there is a need to assess the quality of spawning gravels and
determine whether gravel quality limits spawning success (Kondolf et al., 2008). Dams
located on the American River trap sediment, limiting replenishment of downstream
spawning beds (Watry and Merz, 2009). Since the installation of these upstream dams,
the lower reaches have incised through the accumulated hydraulic mining debris left over
from the gold rush days, to its earlier bed elevation and are now eroding laterally (Watry
and Merz, 2009). The LAR continues to incise as material leaves the system without
being replenished, leaving the gravel budget in deficit (Fairman, 2007). The absence of
sufficient gravel downstream of the dams causes the finer material to leave the system
2
leaving only coarse grains. The coarse material forms an armored layer, which often traps
fine material underneath (Graf, 2006).
This study focuses on the area in which surface water interacts with the ground
water, called the hyporheic zone (Figure 1.1) (Briddock, 2009). In this zone, incubating
eggs and alevins must obtain oxygen from hyporheic water and dispose of metabolic
wastes in the gravel, which requires that hyporheic water in the redd be renewed by
subsurface flow (Kondolf et al., 2008). Water flowing through this zone was
characterized in two ways, as seepage velocity, and as hydraulic conductivity. The term
permeability is used in this paper to describe properties of a material where a fluid can
move freely, not to be confused with the intrinsic permeability of a material, which is a
function of the size of the openings (pores) through which fluid moves (Fetter, 1994).
Hydraulic conductivity is the rate potential at which a fluid can move through a porous
material.
3
Figure 1.1 - The hyporheic zone where surface water interacts with groundwater. In the
fluvial sediments, which make up streambeds, water exchanges between stream and
subsurface (from Briddock, 2009)
Many methods are used for determining hydraulic conductivity values for aquifers
where material is often cemented, well sorted, and homogeneous (Masch and Denny,
1966; Shepherd, 2005) and is also used to describe the discharge velocity of a liquid
through a porous medium at a specific hydraulic gradient (Cedergren, 1997). The seepage
velocity of water through river gravels is dependent on hydraulic head and the hydraulic
conductivity of the gravel (Pollard, 1955). The apparent velocity of a liquid moving
through a porous medium is the rate of seepage, or the seepage velocity (Terhune, 1958).
4
The relatively poorly sorted nature of river gravels makes it difficult to apply most of
those techniques so an empirical method was applied to study this problem.
Gravel particle size distribution and permeability are inter-dependent (Barnard
and McBain, 1994). There is an understood link between gravel properties and
permeability (Shepherd, 2005). Summers and Weber (1984) state two fundamental
characteristics about clastic sediments:
1. Sands and gravels have higher permeability values than silts and clays
2. Clean (well sorted) sands and gravels have higher hydraulic conductivities
than dirty (poorly sorted) sands and gravels.
Even though these fundamental rules seem clear, there is no universally accepted
relationship between grain-size frequency distributions and hydraulic conductivities in
clastic river sediments (Summers and Weber, 1984).
1.2 Study Objectives
The goal of this study is to evaluate the relationship between grain-size
distribution, seepage velocity and hydraulic conductivity. NaCl tracer test and standpipe
drawdown tests were used to determine seepage velocity and hydraulic conductivity
values. Bulk samples of stream sediments were obtained to determine grain size
distribution. Tests were performed at habitat restoration project sites of various ages as
well as unmodified locations on the American River.
5
1.3 Study Area
The Lower American River (LAR) is located near Sacramento, California and
flows 23 miles west from Nimbus dam to its confluence with the Sacramento River.
Folsom and Nimbus dams are located above this reach, and both dampen the effects of
winter storms. These dams also facilitate storage and delivery of water during the
irrigation season (Merz and Setka, 2004)
The upper 6 mile section of the LAR is responsible for one third of the salmon
spawning on the river and this reach is highly degraded (Horner et al., 2009). Gravel
augmentation has become the standard method of restoring spawning habitat for
anadromous salmonid species in the central valley (Figure 1.2) (Wheaton et al., 2004).
Spawning gravel has been added to the LAR every year since 2008, producing five new
augmentation sites that are intended to promote the health of salmonid populations (Merz
et al., 2008). Each restoration site is an engineered project. Water depth and velocity
were measured prior to restoration and up to 8,000 cubic yards of spawning gravel were
added to each site. Physical site conditions and hyporheic water quality were also
monitored after each gravel addition. The portion of the study covering the American
River focuses one natural high use site, one augmentation site prior to restoration, and all
five of the restoration locations (Figure 1.2).
6
Figure 1.2 - Augmentation locations on the American River The yellow are areas where
gravel has been added to help improve spawning habitat. Testing was conducted at all of
the sites in yellow as well gravel spit located adjacent to the Upper Sunrise 2010/2011
site (yellow arrow). The River Bend Park 2013 site was studied before and after the
addition of gravel.
7
Chapter 2
Methods
Several methods were used to determine sediment properties at natural and
restoration sites on the Lower American River.
2.1 Sodium-Chloride Tracers
Sodium-Chloride (NaCl) tracer tests were used to determine seepage velocity
(Horner, 2005). These tests use a main injection well and several monitoring wells
(standpipes). The measurements were collected using five 1 ¼ inch steel standpipes
(Figure 2.1). These standpipes were 4 feet long with a pointed plug at the bottom to make
insertion into the gravel easier. At the bottom of the standpipes, there were eight
apertures, 4 inches long and .030 inches wide, cut every 45 degrees parallel to the
primary axis of the standpipe. These apertures allow for water to flow into the standpipe.
In a typical installation, five standpipes were inserted 30cm into the gravel at ~30cm
intervals aligned parallel to flow of the river (Figure 2.2). After installation, the true
separation of the standpipes was measured and recorded. The standpipes were then
pumped to develop each well and clear the standpipe apertures of debris, which may
inhibit the flow and detection of NaCl solution.
8
Figure 2.3- Schematic showing the construction of the standpipes used for the
Sodium-Chloride tracer tests. The drawing is shortened along the longitudinal axis to
better show the details at both ends. Cut away parts show details of construction.
9
Orion electrical conductivity (E.C.) meters were used to measure NaCl
concentration and were calibrated within 30 minutes of each experiment. Electrical
conductivity probes were inserted into the four downstream standpipes with each probe at
the well’s screened interval. Water flowing through the gravel will pass through the
apertures at the bottom of each standpipe, flowing over the probes sensor. After insertion,
a base line E.C. measurement was recorded in each standpipe; this served as a reference
(zero) for comparison within the experiment. The NaCl solution used as a tracer had
electrical conductivity properties several orders of magnitude higher than natural waters
in the river system.
To start each seepage test, 2000mL of NaCl solution was slowly introduced into
the upstream standpipe. Values shown on each electrical conductivity meter in each
downstream well were recorded every 15 seconds. Recording continued until the
electrical conductivity meters returned to their respective baseline measurements or until
the test time had elapsed. Test time was determined on situational basis.
10
Figure 2.2- Drawing showing a profile view of the Sodium-Chloride tracer test setup.
River water flows from left to right. Arrows, labeled NaCl, depict the path of the supersaturated NaCl solution as it travels from the injection site down through the gravel
arriving at each downstream standpipe. The decrease in arrow size graphically illustrates
the dilution of the solution as time progresses.
The results of each test were then plotted on a graph showing electrical
conductivity vs. time (Figure 3.1). Electrical conductivity values peaked at different times
in each of the downstream standpipes as the tracer migrated through the gravel. The time
(ΔTn) was recorded for each standpipe at which the peak electrical conductivity was
11
observed. The peak concentration is recognized as the highest recorded electrical
conductivity and is assumed to represent the average arrival time of the plume. For the
purposes of this experiment, the distance between the injection well and a downstream
monitoring well is defined as a sector. Using the distance between the nth standpipe and
the injection point as measured in the field (Δdn), a sector velocity (𝑉𝑠𝑛 ) was calculated
with this equation:
∆𝒅
𝑽𝒔𝒏 = ∆𝑻𝒏
𝒏
Equation 2.1
The sector velocity (𝑉𝑠𝑛 ) is the seepage velocity for the sediment that lies between
the injection well and the nth monitoring well. The average of the sector velocities was
calculated at each test site to estimate the mean seepage velocity at that test location.
2.2 Standpipe Drawdown Testing
Standpipe drawdown tests were used to estimate hydraulic conductivity. This
method was pioneered by Pollard (1955) and Terhune (1958) and modified by Barnard
and McBain (1994). This test uses a single standpipe and a pumping apparatus to
maintain a constant one-inch (2.5 cm) drawdown within the standpipe. Over the duration
of the test, water flows into the standpipe and attempts to fill the portion of the standpipe
which had been previously evacuated (Barnard and McBain, 1994). Hydraulic
conductivity (K) of the sediment is empirically related to the volume of water that flows
into the standpipe over a given amount of time (Q) (Figure 2.3).
12
100000
10000
K- Hydraulic Conductivity
K = 2E-06Q5 + 0.0004Q4 - 0.0579Q3
+ 3.3705Q2 + 60.354Q - 38.398
R² = 1
K
1000
Polynomial Equation
Line
100
1
10
Q- Standpipe Inflow
100
Figure 2.3- The empirical calibration chart recreated with from Terhune (1958) and
Barnard and McBain (1994). Chart uses the rate of standpipe inflow (Q) to determine
hydraulic conductivity (K). The blue line represents the best-fit line for the empirical data
sets and the black line represents the equation developed in this paper to calculate K
based on Q.
13
Where:
𝑸=
𝑻𝒆𝒔𝒕 𝑽𝒐𝒍𝒖𝒎𝒆 𝒊𝒏 𝒎𝑳
𝑻𝒆𝒔𝒕 𝑻𝒊𝒎𝒆 𝒊𝒏 𝑺𝒆𝒄.
Equation 2.2
And:
𝑲 = (𝟐𝒙𝟏𝟎−𝟔 𝑸𝟓 ) + (𝟑𝒙𝟏𝟎−𝟒 𝑸𝟒 ) + (−𝟎. 𝟎𝟓𝟎𝟐𝑸𝟑 ) + (𝟑. 𝟏𝟎𝟒𝟓𝑸𝟐 ) + (𝟔𝟐. 𝟔𝟖𝟏𝑸) −
𝟒𝟑
Equation 2.3
Equation 2.3 was developed with permeability data given in Terhune (1958) and
Pollard (1955) using a solver program developed in Excel.
The equipment used to perform this test was slightly modified from the method
outlined by Barnard and McBain(1994). The hand pump (Barnard and McBain, 1994) has
been replaced by a battery powered electric vacuum pump and sample collection tanks
(Figure 2.4). This vacuum pump was used to create a low pressure in two sample capture
tanks (Figure 2.5). One tank was used to collect the test sample and the second tank was
used to collect the residual water. This residual water was a byproduct of the initial
drawdown volume and the water collected after the test when the vacuum was bled off in
the system. Both tanks used a single vacuum source and valves on the intake sides to
switch between tanks. The valves were connected to a single extraction hose that was
used to remove the sample water from the standpipe. The calibrated standpipe was
recreated exactly from drawings provided by Barnard and McBain (1994)(Figure 2.6). A
4000mL graduated cylinder was used to measure the sample volume in the sample
14
collection tank. The pump, valves, sample reservoirs, and battery were fitted to an
external frame backpack so it could be worn in the stream.
Figure 2.4- An annotated picture of the Pump rig used for the standpipe
drawdown test.
15
Figure 2.5- Diagram showing the various components of pump rig used for the standpipe
drawdown test. The blue lines indicate pathways for water to travel. The red lines
indicate the vacuum pathways for air. The filter is necessary to protect the vacuum pump
from water and sediment.
16
Figure 2.6- A engineering drawing showing the dimensions of the Modified Terhune
Mark VI Standpipe (from Barnard and McBain, 1994). This is the design for the
standpipe drawdown.
During each test, the standpipe is inserted into the gravel so that the screened
interval is at a depth of 30cm and developed. To develop the well, the pump wand was
placed at screen depth and approximately 4 gallons of gravel pore water was removed
17
through the screened interval of the standpipe. This served to clear the well screen of
debris and stabilize the recorded measurements. In cases where this volume of water
could not be extracted, water was removed until the water became sufficiently clear. The
depth to water was measured in the standpipe by lowering the extraction hose down the
pipe until a “slurp” was heard, which indicates the top of the water in the pipe (Barnard
and McBain, 1994). After the depth to water was measured, a clamp was placed on the
extraction hose so that the end was 1 inch below static water level. When the pump is
activated the valves were arranged so that the first water extracted entered the residual
tank. After the one inch drawdown was achieved, the tank valves were switched so
extracted water flowed into the sample tank and the timer was started. During the test,
water was removed from the standpipe at the same rate at which it entered through the
apertures at the bottom. 3-3.5 L of water was collected during each test, after which the
tank valves were switched and the timer stopped. The volume of water extracted was
measured and a ratio of mL/sec (Q) was calculated (Equation 2.2). This ratio was then
used to determine a hydraulic conductivity (K) using an equation (Equation 2.3) derived
from a calibration chart (Barnard and McBain, 1994). This calibration chart (Figure 2.3)
was empirically determined using various materials with different permeability in a
permeameter (flume) (Pollard, 1955; Terhune, 1958). Table 2.1 demonstrates how the
output, K, changes when the components of the input, Q, are altered.
48
47
46
45
44
43
42
41
40
39
38
37
36
35
34
33
32
31
30
29
28
27
26
25
24
2500
7,525
7,773
8,040
8,330
8,644
8,986
9,361
9,774
10,231
10,739
11,308
11,950
12,677
13,507
14,462
15,569
16,862
18,385
20,194
22,362
24,985
28,189
32,142
37,070
43,282
2600
7,998
8,272
8,569
8,891
9,242
9,626
10,049
10,517
11,037
11,619
12,273
13,014
13,858
14,826
15,945
17,247
18,774
20,580
22,733
25,322
28,464
32,312
37,070
43,015
50,521
2700
8,501
8,805
9,134
9,494
9,888
10,321
10,799
11,331
11,924
12,591
13,345
14,201
15,181
16,310
17,619
19,149
20,950
23,087
25,642
28,723
32,470
37,070
42,769
49,901
58,919
2800
9,037
9,375
9,743
10,146
10,588
11,077
11,619
12,224
12,903
13,668
14,536
15,526
16,664
17,979
19,511
21,305
23,424
25,945
28,966
32,619
37,070
42,543
49,335
57,845
68,616
2900
9,612
9,988
10,400
10,852
11,350
11,903
12,518
13,208
13,984
14,862
15,862
17,008
18,328
19,858
21,645
23,746
26,232
29,196
32,758
37,070
42,335
48,817
56,871
66,971
79,766
Standpipe Inflow Volume (mL)
3000
3100
3200
3300
10,231
10,898
11,619
12,401
10,650
11,367
12,145
12,990
11,111
11,884
12,725
13,643
11,619
12,456
13,370
14,369
12,182
13,091
14,088
15,181
12,807
13,800
14,892
16,092
13,507
14,596
15,796
17,120
14,293
15,492
16,818
18,285
15,181
16,508
17,979
19,611
16,190
17,665
19,306
21,130
17,341
18,990
20,829
22,877
18,664
20,517
22,587
24,898
20,194
22,286
24,628
27,249
21,972
24,347
27,013
30,000
24,053
26,765
29,815
33,237
26,505
29,619
33,127
37,070
29,414
33,011
37,070
41,638
32,888
37,070
41,794
47,117
37,070
41,962
47,494
53,733
42,141
47,901
54,422
61,782
48,341
55,169
62,907
71,647
55,982
64,136
73,383
83,833
65,485
75,296
86,428
99,014
77,412
89,311 102,817 118,093
92,530 107,083 123,608 142,301
3400
13,251
13,911
14,645
15,464
16,382
17,414
18,581
19,907
21,420
23,156
25,156
27,474
30,176
33,341
37,070
41,491
46,765
53,097
60,749
70,064
81,487
95,603
113,195
135,309
163,372
3500
14,175
14,916
15,741
16,664
17,700
18,869
20,194
21,701
23,424
25,404
27,690
30,343
33,439
37,070
41,354
46,438
52,506
59,798
68,616
79,356
92,530
108,818
129,119
154,645
187,039
3600
15,181
16,012
16,940
17,979
19,149
20,471
21,972
23,683
25,642
27,896
30,503
33,532
37,070
41,225
46,131
51,958
58,919
67,287
77,412
89,749
104,887
123,608
146,945
176,291
213,535
3700
16,277
17,209
18,251
19,422
20,741
22,234
23,932
25,870
28,093
30,655
33,620
37,070
41,104
45,844
51,446
58,104
66,062
75,634
87,220
101,341
118,674
140,111
166,838
200,449
243,106
3800
17,472
18,516
19,686
21,002
22,488
24,172
26,090
28,283
30,800
33,705
37,070
40,989
45,575
50,968
57,346
64,930
74,000
84,913
98,127
114,235
134,011
158,473
188,974
227,330
276,010
18
Table 2.1- Hydraulic conductivity values in terms of standpipe inflow components
Test Duration (seconds)
19
2.3 Bulk Samples
Bulk samples were used to extract a predefined volume of sediment from the
stream bed and were analyzed to determine grain size distribution (Bunte and Abt, 2001).
Bulk samples were collected at specific locations to better understand the grain size
distribution at those discrete points. Bulk samples are effective at characterizing extremes
in fine or coarse sediment distribution. The sub-surface grain size analysis is especially
useful for understanding gravel permeability as it relates to gravel composition and was
the primary material used in this study (Gale and Hoare, 1992).
After a site was selected for the bulk sample, a marker was dropped to mark the
location and a waypoint was recorded with a high-resolution GPS receiver. The largest
grain within one meter of the marker was located and measured. The intermediate axis of
this largest grain is used to determine the sample size by weight (Figure 2.7) (Bunte and
Abt, 2001). For the samples collected in this report, a 95% accuracy sample was be
collected. With the target weight identified, gravel was removed from the sample location
with shovels, using care to preserve the finer material. In most cases a baffle device was
used to divert water flow and minimize these losses (Bunte and Abt, 2001). The surface
sample was collected first and the total weight was obtained. The surface material was
removed until a noticeable change in grain size or composition is observed, or to a depth
equal to the B-axis diameter of the largest surface grain. The sub-surface sample was
collected until the target weight for the sample was reached. The surface and sub-surface
samples were kept separate and left to dry for several hours on tarps. The grains for each
20
sample were sorted using rocker sieves and categorized based on size. After the sample
was sorted, each size category was weighed. The results were used to create a cumulative
percent curve. This is done by plotting grain size against cumulative weight percent
(frequency). This was done separately for both the surface and the subsurface samples
(Boggs, 1995).
Figure 2.7- Chart showing minimum sample weight for sediment of different sizes at
different sample accuracy intervals. Dmax represents the largest grain in the sample area in
millimeters. (from Bunte and Abt, 2001)
For data presented in this report, 2-3 gallon subsurface gravel samples were
collected at many of the locations where a drawdown measurement was taken. This was
not always possible due to factors such as surface water depth, river velocity, or
21
proximity to biologically sensitive areas. These samples were analyzed using standard
bulk sample procedures and data is presented in the same format. This sampling was used
to compare grain-size information between testing methods and testing locations.
22
Chapter 3
Results
3.1 Sodium- Chloride Tracers
NaCl tracer tests provided a quantitative estimate for the seepage velocity (vs) of
water flowing through gravel in a streambed. Gravel at the study sites was composed
primarily of rounded to well-rounded course to very coarse gravels. The seepage of river
water through these gravels is a passive process dependent on stream flow, hydraulic
head, sorting, armoring, organic content, siltation, and biogenic alteration.
The NaCl tracer test can be a very useful tool for directly measuring seepage
velocities in river gravels. The NaCl solution is non-toxic, environmentally friendly, and
dissipates to undetectable levels shortly after the test. The easy of set-up and simple
recording procedures make it ideal for a small sampling team with little experience.
Results of the NaCl tracer tests have a wide range of signatures. The ideal result
(Figure 3.1) clearly shows sequential peaks in electrical conductivity as the tracer
migrates, followed by a gradual decay in electrical conductivity toward the baseline
measurement at each point. Peak electrical conductivity decreased with increasing
distance downstream because the tracer dissipated. In this ideal test, the time between
peaks was consistent. These test results were uncommon due to the natural variation in
river gravels. Some tests in this data set were classified as failures. A failed test saw no
change in electrical conductivity at any of the downstream monitoring wells, indicating
23
subsurface water flow was nonexistent or behaved in an atypical manner. Strong lateral
or vertical gradients may have influenced some of these atypical tests, so results could
not be determined.
Electrical Conductivity (mS)
SWT 4
2000
1500
W1
1000
W2
500
W3
0
W4
0
200
400
600
800
1000
1200
1400
1600
Time (seconds)
Figure 3.1- Plotted results from a NaCl tracer test from the Upper Sunrise 2010/2011 site
showing Electrical Conductivity over the duration of the test. SWT 4 is the ideal result
from testing conducted. Well 1, well 2, and well 3 sense the NaCl solution in succession
with similar time gaps separating those values. Well 4 does not sense the plume.
Typical tracer test results were erratic and can be difficult to interpret (Figure 3.2).
Sometimes the tracer solution affected wells in a apparently random order. Tracers
sometimes missed wells completely, affected only the first and last monitoring points, or
caused a reading in only one well. In rare cases electrical conductivity in monitoring
wells did not decay and instead remained at a conductivity value well above normal for
the duration of the test. These anomalies in some test data sets require adjustments by
identifying good signals and excluding poor ones. These inconsistencies are the weak
points in this kind of experiment.
24
Electrical Conductivity
(mS)
SWT 2
1000
800
600
400
200
0
W1
W2
W3
0
500
1000
1500
2000
2500
3000
W4
Time (seconds)
Figure 3.2- Plotted results from a NaCl tracer test from the Upper Sunrise 2010/2011 site
showing Electrical Conductivity over the duration of the test. SWT 2 is the typical result
from testing conducted. The signals from the sensors are noisy and the peaks are unclear.
Testing on the American River included eleven tests across two restored salmon
habitat sites. The majority of the tests were concentrated on the Upper Sunrise 2010/2011
site where eight tests were performed (Figure 3.3), six yielding usable results. The results
of the testing (Table 3.1) show seepage velocities ranging from 226- 1899 cm/hr. The
remainder of the tracer tests were conducted at the Upper Sailor Bar 2009 site (Figure
3.4). Three tests were executed and two of those were successful (Table 3.1). Seepage
velocities measured at those test sites were 732 cm/hr and 2594 cm/hr.
25
Figure 3.3- Location of 8 NaCl tracer tests (yellow points) at the Upper sunrise 2010/
2011 restoration site (red dashed line). The Upper Sunrise Spit is also shown (yellow
dashed line)
26
Sailor Bar Upper Sunrise 2010/2011
2009
Table 3.1- Table showing the seepage velocities from the NaCl tracer tests conducted at
two sites on the American River. Velocities given for all successful tests.
SWT 1
SWT 2
SWT 3
SWT 4
SWT 5
SWT 6
SWT 7
SWT 8
SWT 9
Seepage
Velocity (Vs)
cm/hr
Failure
226
1900
1507
862
Failure
840
11901
733
SWT 10
SWT 11
Failure
2595
27
Figure 3.4- Location of 3 NaCl tracer tests (yellow points) at the Upper Sailor Bar 2009
restoration site (red dashed line).
3.2 Standpipe Drawdown Testing
Drawdown testing provided a quantitative measurement of the hydraulic
conductivity of gravels tested in the study. The hydraulic conductivity of the river gravels
is determined by flow to a well under a known hydraulic gradient and may be used as a
gage for the health of the river (Terhune, 1958). This is an active process, independent of
stream flow, and relies on the induced hydraulic head created by the pumping apparatus
for the measurement.
28
This method relies on a stead 1in. (2.54 cm) drawdown inside the well during the
entire test. Due to limitations of the pumping apparatus, 1 inch of drawdown was not
always possible in highly permeable gravel. Lab testing provided an upper limit for the
average pumping ability of the apparatus. Using this lab testing, a value of >95,000 cm/hr
was applied to tests in cases where that hydraulic head could not be obtained or
maintained due to high permeability. Problems inherent with installation and properties
of the material tested can also contribute to error. Some tests in areas of extremely low
permeability caused the well not to recover in response to the induced hydraulic head. In
this case a value of 1cm/hr was assigned to the test.
One hundred seventeen drawdown measurements were made at seven sites
(Figure 1.2). Five of the seven sites represent augmented riffles where highly permeable
gravel has been added to help restore spawning habitat. The remaining 2 locations are in
un-restored areas. The gravel spit (US spit), located on the south bank of the river
adjacent to the Upper Sunrise 2010/2011 and the River Bend Park 2013 site (RBP13),
tested in the summer of 2013 are unaltered locations served as, both high and low
spawning use, controls for the natural condition of the LAR. The US spit control site
received high spawning use, and the River Bend Park site had historically received
relatively low spawning use. This site was restored in September 2013, after initial
measurements were taken.
The control sites showed the lowest hydraulic conductivities of the sites tested.
Before restoration, the RPB13 site (Figure 3.5) was tested in 18 locations (Table 3.2) and
29
had a maximum hydraulic conductivity of 32,000 cm/hr and 4 tests which did not
recover. The site had an average hydraulic conductivity of 4,800 cm/hr with a standard
deviation of 8,600 cm/hr. The US spit control site (Figure 3.6) was tested in 19 locations
(Table 3.3) . The maximum hydraulic conductivity was 15,000 cm/hr and the minimum
was 30 cm/hr. The average hydraulic conductivity was 4,300 cm/hr with a standard
deviation of 4,500 cm/hr.
Figure 3.5- River Bend Park 2013 pre augmentation (yellow dashed line) before
augmentation. Magenta dots indicate locations where a drawdown test was performed
and a small bulk sample was taken.
30
Table 3.2 Drawdown test results for the River Bend Park control site conducted on the
American River prior to the augmentation. Hydraulic conductivity (K) results are given
in cm/hr.
Site
RBP 13 Pre
RBP 13 Pre
RBP 13 Pre
RBP 13 Pre
RBP 13 Pre
RBP 13 Pre
RBP 13 Pre
RBP 13 Pre
RBP 13 Pre
RBP 13 Pre
RBP 13 Pre
RBP 13 Pre
RBP 13 Pre
RBP 13 Pre
RBP 13 Pre
RBP 13 Pre
RBP 13 Pre
RBP 13 Pre
Test
no.
1
2
3
4
5
6
7
8
9
10
11
12
13
14
16
17
28
26
K
1
384
185
1
16580
904
16050
1
4089
9813
31624
312
235
340
240
5522
1
535
cm/hr
cm/hr
cm/hr
cm/hr
cm/hr
cm/hr
cm/hr
cm/hr
cm/hr
cm/hr
cm/hr
cm/hr
cm/hr
cm/hr
cm/hr
cm/hr
cm/hr
cm/hr
31
Figure 3.6- Upper Sunrise 2010/ 2011 (red dashed line) and Upper Sunrise Spit (yellow
dashed line). Blue dots indicate location where drawdown test was performed. Magenta
dots indicate locations where a drawdown test was performed and a small bulk sample
was taken.
32
Table 3.3 Drawdown test results for the US Spit control site conducted on the American
River. Hydraulic conductivity (K) results are given in cm/hr.
Site
US Spit
US Spit
US Spit
US Spit
US Spit
US Spit
US Spit
US Spit
US Spit
US Spit
US Spit
US Spit
US Spit
US Spit
US Spit
US Spit
US Spit
US Spit
US Spit
Test
no.
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
K
1135
12282
1205
4626
33
584
3189
9330
15329
7003
306
736
98
5780
6092
1397
8764
1444
2654
cm/hr
cm/hr
cm/hr
cm/hr
cm/hr
cm/hr
cm/hr
cm/hr
cm/hr
cm/hr
cm/hr
cm/hr
cm/hr
cm/hr
cm/hr
cm/hr
cm/hr
cm/hr
cm/hr
Most of the restoration sites have higher permeability; however as sites age they
trend toward lower hydraulic conductivity values. The oldest site studied, Upper Sailor
Bar 2008 (USB08), was constructed in 2008 adjacent to the Nimbus Fish Hatchery
(Figure 3.7). Drawdown testing was conducted at 17 test locations across this site (Table
3.4) . The average hydraulic conductivity observed was 17,000 cm/hr with a standard
deviation of 30,000 cm/ hr. The maximum rate was >95,000 cm/hr and 3 wells failed to
recover.
33
Figure 3.7- Upper Sailor Bar 2008 (right; red dashed line) and Upper Sailor Bar 2009
(left; red dashed line). Blue dots indicate location where drawdown test was performed.
Magenta dots indicate locations where a drawdown test was performed and a small bulk
sample was taken.
34
Table 3.4 Drawdown test results for the Upper Sailor Bar 2008 site conducted on the
American River. Hydraulic conductivity (K) results are given in cm/hr.
Site
USB 08
USB 08
USB 08
USB 08
USB 08
USB 08
USB 08
USB 08
USB 08
USB 08
USB 08
USB 08
USB 08
USB 08
USB 08
USB 08
USB 08
Test
no.
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
K
5376
1
14906
626
773
>95000
6002
7281
1832
15643
2512
1
3588
>95000
19214
18120
1
cm/ hr
cm/ hr
cm/ hr
cm/ hr
cm/ hr
cm/ hr
cm/ hr
cm/ hr
cm/ hr
cm/ hr
cm/ hr
cm/ hr
cm/ hr
cm/ hr
cm/ hr
cm/ hr
cm/ hr
The 2009 augmentation is shown in Figure 3.7 (Table 3.5). Upper Sailor Bar 2009
(USB09), had a higher average hydraulic conductivity of 41,000 cm/ hr and a standard
deviation of 41,000 cm/hr. Hydraulic conductivity values ranged of 1 to >95,000 cm/hr.
35
Table 3.5 Drawdown test results for the Upper Sailor Bar 2009 site conducted on the
American River. Hydraulic conductivity (K) results are given in cm/hr.
Site
USB 09
USB 09
USB 09
USB 09
USB 09
USB 09
USB 09
USB 09
USB 09
USB 09
USB 09
USB 09
USB 09
USB 09
USB 09
Test
no.
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
K
5682
5490
17920
39981
>95000
580
>95000
>95000
18339
>95000
>95000
>95000
19026
8803
24057
cm/ hr
cm/ hr
cm/ hr
cm/ hr
cm/ hr
cm/ hr
cm/ hr
cm/ hr
cm/ hr
cm/ hr
cm/ hr
cm/ hr
cm/ hr
cm/ hr
cm/ hr
The Upper Sunrise (US10/11) site was augmented in 2010, followed by another
addition in the same place in 2011 (Figure 3.6). The range of values at this site was
measured from 1 to >95,000 cm/hr. The average hydraulic conductivity at US10/11 was
62,000 with a standard deviation of 36,000 cm/hr (Table 3.6).
36
Table 3.6 Drawdown test results for the Upper Sunrise 2010/ 2011 site conducted on the
American River. Hydraulic conductivity (K) results are given in cm/hr.
Site
US 10/11
US 10/11
US 10/11
US 10/11
US 10/11
US 10/11
US 10/11
US 10/11
US 10/11
US 10/11
US 10/11
Test
no.
1
2
3
4
5
6
7
8
9
10
11
K
>95000
>95000
>95000
>95000
>95000
>95000
29414
39218
1
33886
44377
cm/hr
cm/hr
cm/hr
cm/hr
cm/hr
cm/hr
cm/hr
cm/hr
cm/hr
cm/hr
cm/hr
The Lower Sailor Bar 2012 (LSB12) had 16 drawdown measurements (Table 3.7)
. These measurements covered the site and were conducted 6 months after the addition,
results ranged from 1 to >95,000 cm/ hr (Figure 3.8). The average hydraulic conductivity
at LSB12 was 64,000 cm/hr and the standard deviation was 28,000 cm/hr.
37
Figure 3.8- Lower Sailor Bar 2012 (red dashed line). Blue dots indicate location where
drawdown test was performed.
38
Table 3.7 Drawdown test results for the Lower Sailor Bar 2012 site conducted on the
American River. Hydraulic conductivity (K) results are given in cm/hr.
Site
LSB 12
LSB 12
LSB 12
LSB 12
LSB 12
LSB 12
LSB 12
LSB 12
LSB 12
LSB 12
LSB 12
LSB 12
LSB 12
LSB 12
LSB 12
LSB 12
Test
no.
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
K
22960
>95000
55031
69272
>95000
>95000
>95000
55544
86851
68616
80573
48931
29898
57992
1
64572
cm/hr
cm/hr
cm/hr
cm/hr
cm/hr
cm/hr
cm/hr
cm/hr
cm/hr
cm/hr
cm/hr
cm/hr
cm/hr
cm/hr
cm/hr
cm/hr
The newest addition, RBP13, was a large channel-spanning feature. 21 tests were
conducted across the augmented gravel site (Table 3.8). New gravel was sourced from
the banks adjacent to the riffle and was of considerably lesser volume and thickness than
previous augmentations (Figure 3.9). As a result, the gravel in some areas of the
augmentation area was thinner than 30cm and the screened interval in the standpipe was
inserted into gravel that was not part of the augmentation. For this reason, the augmented
RBP13 site has a lower average hydraulic conductivity, and a wider standard deviation,
60,000 cm/hr and 55,000 cm/hr respectfully, than slightly older sites. The maximum
value was 190,000 cm/hr and 3 tests failed to recover.
39
Figure 3.9- River Bent Park 2013 post augmentation (red dashed line). Magenta dots
indicate locations where a drawdown test was performed and a small bulk sample was
taken.
40
Table 3.8 Drawdown test results for the River Bend Park 2013 site conducted on the
American River. Hydraulic conductivity (K) results are given in cm/hr.
Site
Test
K
no.
1
>95000 cm/hr
RBP 13 Post
2
>95000 cm/hr
RBP 13 Post
3
>95000 cm/hr
RBP 13 Post
4
>95000 cm/hr
RBP 13 Post
5
>95000 cm/hr
RBP 13 Post
6
9037
cm/hr
RBP 13 Post
7
688
cm/hr
RBP 13 Post
8
46765
cm/hr
RBP 13 Post
9
104887 cm/hr
RBP 13 Post
10
98538
cm/hr
RBP 13 Post
11
145
cm/hr
RBP 13 Post
12
3770
cm/hr
RBP 13 Post
13
23
cm/hr
RBP 13 Post
14
121204 cm/hr
RBP 13 Post
15
189839 cm/hr
RBP 13 Post
16
29414
cm/hr
RBP 13 Post
17
92530
cm/hr
RBP 13 Post
18
58
cm/hr
RBP 13 Post
19
23
cm/hr
RBP 13 Post
20
>95000 cm/hr
RBP 13 Post
21
3045
cm/hr
RBP 13 Post
41
When compared, these averages show a degradation relationship between the age
of a restoration and the hydraulic conductivity (Figure 3.10). As these gravel additions
age, the pore spaces between larger cobbles becomes filled with sand, silt, clay, and
organic material that lowers the capability of fluids to migrate. This was apparent to field
crews when they developed wells at older sites prior to testing. Turbidity at these sites
was initially high, although this observation was not quantified.
Hydraulic Conductivity (cm/hr)
Average Hydraulic Conductivity vs. Age
80000
70000
60000
50000
40000
30000
20000
10000
0
0
1
2
3
4
5
Natural Natural
High Use Low Use
Years Since Augmentation
Figure 3.10- Average hydraulic conductivity compared to the age of the gravel addition.
As the augmentations age, there is a gradual decline in hydraulic conductivity values
toward natural, un-restored levels.
42
3.3 Bulk Samples
Small bulk samples were used to characterize the gravel material tested during the
drawdown test. The grain size distribution of fluvial sediments affects properties such as
porosity, hydraulic conductivity and seepage velocity (Boggs, 1995). These methods
were used to summaries large amounts of gravel material and present it in a statistical
form so it may be more easily examined (Boggs, 1995).
Table 3.9- Results for small bulk samples by site with associated hydraulic conductivity
(K) and calculated seepage velocity (Vs).
mm
𝑑ℎ
𝑑𝑙
𝑛𝑒
RBP13_pre_02
0.0012
RBP13_pre_03
Phi
𝑋̅
𝑋̅
σ
Sk
k
Mean
Mean
Standard Dev.
Skewness
Kurtosis
0.24
13.5
-3.75
1.91
1.45
3.53
384.42
1.92
0.0012
0.24
23.9
-4.58
1.72
0.41
2.79
184.51
0.92
RBP13_pre_05
0.0012
0.24
33.8
-5.08
1.39
-0.69
1.69
16580.26
82.90
RBP13_pre_06
0.0012
0.24
25.4
-4.67
1.19
0.32
4.03
904.49
4.52
RBP13_pre_07
0.0012
0.24
31.0
-4.96
1.64
-0.90
2.13
16050.38
80.25
RBP13_pre_09
0.0012
0.24
22.2
-4.48
0.93
-0.23
2.22
1470.57
7.35
RBP13_pre_10
0.0012
0.24
52.6
-5.72
1.98
-0.99
1.44
9813.38
49.07
RBP13_pre_11
0.0012
0.24
39.1
-5.29
1.60
-0.63
1.64
31623.75
158.12
RBP13_pre_12
0.0012
0.24
40.7
-5.35
1.99
-0.38
1.98
311.53
1.56
RBP13_pre_13
0.0012
0.24
27.9
-4.80
2.11
0.52
2.56
235.46
1.18
RBP13_pre_14
0.0012
0.24
44.8
-5.49
1.91
-0.08
2.77
339.99
1.70
RBP13_pre_16
0.0012
0.24
49.5
-5.63
1.93
-0.63
1.84
239.84
1.20
RBP13_pre_26
0.0012
0.24
43.5
-5.44
1.83
-0.40
1.81
535.10
2.68
LSB09-01
0.0017
0.24
33.1
-5.05
0.67
0.65
5.33
18339.14
133.49
LSB09-02
0.0017
0.24
37.6
-5.23
1.05
1.25
4.34
95000.00
691.52
LSB09-03
0.0017
0.24
24.0
-4.59
0.87
0.78
4.26
95000.00
691.52
LSB09-04
0.0047
0.24
30.2
-4.92
0.96
0.81
4.71
95000.00
1850.92
LSB09-05
0.0047
0.24
49.1
-5.62
0.45
0.77
8.08
19025.94
370.69
LSB09-06
0.0012
0.24
31.7
-4.99
0.68
1.15
5.51
8803.07
44.82
LSB09-07
0.0012
0.24
25.1
-4.65
0.88
1.81
6.93
24056.70
122.49
US1011_Spit_01
0.0006
0.24
24.0
-4.58
0.98
1.14
3.83
5779.61
13.82
Test no.
K (cm/hr)
Vs(cm/hr)
DD
Seepage
43
US1011_Spit_02
0.0002
0.24
17.5
-4.13
1.65
0.95
2.14
6091.93
3.88
US1011_Spit_03
0.0003
0.24
22.5
-4.49
1.29
1.14
2.93
1396.71
1.52
US1011_Spit_04
0.0003
0.24
14.1
-3.82
1.72
1.37
2.42
8764.20
9.53
US1011_Spit_05
0.0003
0.24
11.8
-3.56
1.77
1.47
2.44
1443.50
1.57
US1011_Spit_06
0.0006
0.24
14.3
-3.83
1.55
1.39
2.55
2653.56
6.35
USB08-01
0.0011
0.24
12.6
-3.66
1.58
0.28
2.76
5375.72
25.40
USB08-03
0.0011
0.24
25.8
-4.69
1.72
1.07
3.56
14906.40
70.43
USB08-04
0.0013
0.24
12.8
-3.67
1.29
0.14
2.33
625.59
3.45
USB08-05
0.0013
0.24
21.7
-4.44
1.20
0.47
1.84
773.28
4.27
USB08-06
0.0013
0.24
15.5
-3.96
1.37
0.47
2.37
95000.00
524.08
US1011-upper
0.0018
0.24
19.8
-4.30
1.08
0.56
2.50
90000.00
675.00
US1011 Middle
0.0010
0.24
31.7
-4.99
0.63
-0.25
2.92
90000.00
375.00
RBP13_Post_01
0.0012
0.24
5.3
-2.40
1.23
-0.17
3.34
95000.00
475.00
RBP13_Post_03
0.0012
0.24
16.2
-4.01
0.99
0.94
4.15
95000.00
475.00
RBP13_Post_04
0.0012
0.24
5.7
-2.50
1.19
0.31
4.05
95000.00
475.00
RBP13_Post_05
0.0012
0.24
8.6
-3.11
1.26
0.24
2.49
95000.00
475.00
RBP13_Post_06
0.0012
0.24
40.5
-5.34
1.12
1.81
7.11
9037.39
45.19
RBP13_Post_07
0.0012
0.24
12.3
-3.63
1.83
1.33
5.04
687.51
3.44
RBP13_Post_08
0.0012
0.24
8.5
-3.09
1.22
0.01
2.49
46765.22
233.83
RBP13_Post_09
0.0012
0.24
12.2
-3.61
1.14
0.34
2.55
104887.47
524.44
RBP13_Post_10
0.0012
0.24
8.7
-3.13
1.61
-0.08
1.90
98537.67
492.69
RBP13_Post_11
0.0012
0.24
16.8
-4.07
1.75
1.74
7.51
144.98
0.72
RBP13_Post_12
0.0012
0.24
2.9
-1.55
2.03
1.47
5.70
3770.35
18.85
RBP13_Post_14
0.0012
0.24
24.2
-4.60
0.54
1.46
6.60
121203.94
606.02
RBP13_Post_15
0.0012
0.24
11.5
-3.53
1.34
0.20
2.35
189838.87
949.19
RBP13_Post_16
0.0012
0.24
24.5
-4.61
1.51
0.31
2.77
29413.68
147.07
RBP13_Post_17
0.0012
0.24
23.3
-4.54
0.94
3.68
25.39
92530.41
462.65
63 small bulk samples were analyzed in conjunction with drawdown tests (3.9).
Using 16 size categories (Table 3.10) from -7.4Φ (177.8mm) to 4Φ (0.062mm), each
sample was processed to produce a weight percent (f) for each category. The
mathematical or moment method of analysis was chosen for this study, due to its greater
accuracy and convenience. Using this grain size distribution information, mean, standard
44
deviation (sorting), skewness, and kurtosis were calculated using the following (Boggs,
1995):
Mean:
𝑥Φ =
Standard Deviation:
Skewness:
Kurtosis:
Where:
∑ 𝑓𝑚
𝑛
∑ 𝑓(𝑚 − ̅̅̅)
𝑥Φ 2
𝜎Φ = √
𝑛
Equation 3.1
Equation 3.2
𝑆𝑘Φ =
∑ 𝑓(𝑚 − 𝑥Φ )3
𝑛 𝜎Φ 3
Equation 3.3
𝐾𝑡Φ =
∑ 𝑓(𝑚 − 𝑥Φ )4
𝑛 𝜎Φ 4
Equation 3.4
m= midpoint of each grain size range in phi
n= total number in sample; 100 when f is percent
These calculations were used to process all of the small samples used in this
report. The mean size is the mathematical average grain size for the sample. Sorting is the
measure of the range of grain sizes and the magnitude of the scatter around the mean
grain size (Boggs, 1995). The verbal interpretations of sorting values in this report were
derived from Folk (1974) (Figure 3.11). Skewness shows the degree of asymmetry in a
particular sample. Positive skewness values greater than 0.10 are skewed toward fine and
the degree of skewness is proportional to its magnitude. Conversely, negative skewness
45
values less than -0.10 are coarsely skewed and the degree of skewness shares the same
relationship. Kurtosis is the term used for the degree of peakedness of a sample data and
is commonly calculated as part of the grain size analysis process but its geologic
significance is unknown (Boggs, 1995).
Table 3.10- Conversion table for grain size ranges. All grain sizes refer to the
intermediate axis.
Size (Phi) Size (mm) Size (inches)
5.299
0.025
0.001
3.006
0.124
0.005
2.006
0.249
0.010
0.999
0.500
0.020
-0.001
1.001
0.039
-0.986
1.981
0.078
-1.986
3.962
0.156
-2.989
7.938
0.313
-3.989
15.875
0.625
-4.474
22.225
0.875
-4.989
31.750
1.250
-5.474
44.450
1.750
-5.989
63.500
2.500
-6.474
88.900
3.500
-6.989
127.000
5.000
-7.474
177.800
7.000
A graphical method, using a cumulative frequency curve, is commonly used to
determine these statistical parameters. While graphic plots are simple to construct, the
mathematical methods proved to be a faster method of yielding accurate results. The
graphical method uses percentile values from the cumulative frequency curve to calculate
the aforementioned statistics. The median grain size (d50) is commonly used describe
46
sediments; however, mean grain size is used for this report. The mean grain size and the
d50 for a given gravel sample are not typically the same and are dependent on the degree
of skewness.
Table 3.11- Interpretations concerning sorting based on phi standard deviation (Folk,
1974)
Standard Deviation
Very Well Sorted
Well Sorted
Moderately Well Sorted
Moderately Sorted
Poorly Sorted
Very Poorly Sorted
Extremely Poorly Sorted
<0.35
0.35-0.50
0.50-0.71
.071-1.00
1.00-2.00
2.00-4.00
>4.00
The grain size distributions at the two unrestored sites (RBP13 Pre and US Spit)
were significantly different. At the Upper Sunrise Spit, 6 bulk samples showed the
average grain size to be -0.01Φ (~1mm) and this site was classified as poorly sorted with
a mean sorting value of 1.63Φ. Before the restoration, 17 bulk samples at the River Bend
Park Site showed a much coarser mean grain size of -5.00Φ (~32mm). The mean sorting
at this site was poor, but less so then the US Spit with a value of 1.38Φ. These values
show that the majority of grains at the US Spit were considerably finer than at the RBP13
site with a wider range in size.
The augmentation sites are engineered features and material placed during the
restoration process is presorted to represent a specific range in grain sizes which are
deemed appropriate for spawning salmonid species. 6 bulk samples at the Upper Sailor
47
Bar 2008 Site (USB08) had an overall mean grain size of -3.97Φ (~16mm) and a average
sorting value of 1.42Φ. At the Upper Sailor Bar 2009 augmentation 7 bulk samples in the
gravel showed an overall mean grain size of -5.01Φ (~32mm) and moderate mean sorting
with a value of 0.79Φ. At the Upper Sunrise 2010/ 2011 augmentation, 2 bulk samples
showed an overall mean grain size of -4.65Φ (~25mm) and a moderate mean sorting
value of 0.86Φ. After Augmentation, 21 bulk samples at the River Bend Park 2013
represent the site as a whole; however, not all of the test locations were located within
augmented gravels. The overall mean grain size at this site was -3.82Φ (~14mm) and was
found to be poorly sorted with a value of 1.63Φ. This is atypical for a newly restored
riffle as overall the site is composed of fine material used for the gravel addition
surrounded by coarse material on the periphery, which were present before the
augmentation.
The grain size distribution within the restoration sites is largely dependent on the
material used in the augmentation. For this reason, an aging trend based on grain size,
which includes of all of the augmented riffles could not be determined. The USB08 and
USB09 restoration sites demonstrate this degradation of the restored materials. Over
time, the amount of fine material increases with respect to the overall composition
lowering the mean grain size. Sorting values were also affected by this change in overall
composition, as sorting tends to become more poor with time. This is also apparent when
comparing restored riffles to natural riffles.
48
Chapter 4
Analysis of Results
4.1 Comparison of Results: Seepage Velocity vs. Hydraulic Conductivity
Tracer tests from this study provided seepage velocities, and standpipe drawdown
tests provided hydraulic conductivity values. Because of this difference, standpipe
drawdown tests were converted to seepage velocities. This allowed results from different
tests to be compared. Seepage velocity (Vs) was chosen as the comparative measurement,
to show how river water flows through the gravel. The velocity of seepage is dependent
on the hydraulic head and the permeability of the gravel (Pollard, 1955). Pollard (1955)
used a flume experiment to conduct a similar tracer measurement in order to compare
results from a single standpipe drawdown test. The resulting comparison confirmed the
viability of the drawdown method for determining hydraulic conductivity and
intrinsically related to a seepage velocity.
Discharge velocity is the speed at which a fluid would move through a material if
it were an open conduit (Fetter, 1994). The drawdown tests produced permeability values
in terms of hydraulic conductivity (K), which is equal to the discharge velocity (vd) under
a hydraulic gradient (𝑑ℎ
) of 1 (Cedergren, 1997).
𝑑𝑙
Where:
𝑣𝑑 = 𝐾
𝑑ℎ
𝑑𝑙
Equation 4.1
49
Or:
𝐾 = 𝑣𝑑
If:
𝑑ℎ
𝑑𝑙
Equation 4.2
=1
The hydraulic conductivity coefficient (K) demonstrates the capacity for water to
flow through the gravel (Cedergren, 1997), and is a combination of sediment and fluid
properties (Terhune, 1958).
One of those properties is the given hydraulic gradient at any given point or test
𝑑ℎ
location. The gradient coefficient ( 𝑑𝑙 ) represents change in head between two points.
This was estimated by measuring the water surface elevation at each sub-reach in the
study using a total station survey tool. A longitudinal transect was traversed and water
surface elevation was recorded at ~10m intervals. Gradient zones were created (using
GIS software) and those zone values were assigned to the test locations for individual
seepage calculations (Figure 3.9)
There are many properties that control porosity in sediments. Effective porosity is
defines as the sum of interconnected pore space through which a fluid may pass
(Cedergren, 1997). Effective porosity (ne) was not measured in situ, so a standard
assumption was made for effective porosity in all calculations. Based on representative
effective porosity values presented by Mcwhorter and Sunada (1977), the arithmetic
mean porosity for medium gravel (Table 4.1) was used in all calculations where this
variable was required. A standard value of 24% (𝑛𝑒 = 0.24) for was assumed for all
50
sample sites. This may have introduced a systematic error to the seepage velocity
calculations. This error in seepage velocity calculations was 14.3% if the effective
porosity was at either the upper or lower limit, 28% and 21% respectively, provided by
McWhorter and Sunada (1977).
Table 4.1- The representative values for total porosity and effective porosity values for
selected sedimentary materials. The ranges of values are used to calculate the arithmetic
mean. The highlighted line shows the value used for the seepage velocity calculations
(from McWhorter and Sunada, 1977).
Representative Porosity Values
Total Porosity, nt
Effective Porosity, ne
Range
Arithmetic Mean
Range
Arithmetic Mean
-
-
0.02 - 0.40
0.21
Sandstone (medium)
0.14 - 0.49
0.34
0.12 - 0.41
0.27
Siltstone
0.21 - 0.41
0.35
0.01 - 0.33
0.12
Sand (fine)
0.25 - 0.53
0.43
0.01 - 0.46
0.33
-
-
0.16 - 0.46
0.32
Sand (coarse)
0.31 - 0.46
0.39
0.18 - 0.43
0.3
Gravel (fine)
0.25 - 0.38
0.34
0.13 - 0.40
0.28
-
-
0.17 - 0.44
0.24
Gravel (coarse)
0.24 - 0.36
0.28
0.13 - 0.25
0.21
Silt
0.34 - 0.51
0.45
0.01 - 0.39
0.2
Clay
0.34 - 0.57
0.42
0.01 - 0.18
0.06
Limestone
0.07 - 0.56
0.3
~0 - 0.36
0.14
Loess
-
-
0.14 - 0.22
0.18
Eolian sand
-
-
0.32 - 0.47
0.38
Material
Sandstone (fine)
Sand (medium)
Gravel (medium)
51
Cedergren (1997) relates hydraulic conductivity to seepage velocity by the
following:
𝑣𝑠 =
𝐾 𝑑ℎ
( )
𝑛𝑒 𝑑𝑙
Equation 4.3
ne = effective porosity
Example calculation for hydraulic conductivity to seepage velocity:
Sample: LSB09-05 (from table 3.9)
𝑣𝑠 =
K
19025 cm/hr
ne
0.24
𝒅𝒉
𝒅𝒍
0.0047
19025(0.0047)
= 370𝑐𝑚/ℎ𝑟
0.24
Assuming that for short periods of time the effective porosity and hydraulic
conductivity are static. Meaning 𝐾⁄𝑛𝑒 remains constant. Thus, equation 4.3 demonstrates
that seepage velocity under static hyporheic conditions is proportional to gradient of the
river (𝑑ℎ
). This does not take into account external inputs such as ground water
𝑑𝑙
contribution or loss. Change in river gradients can occur at different river discharge levels
or when the riffle complex above or below the site are modified.
52
All drawdown tests, which were performed in conjunction with bulk samples,
were converted into seepage velocities using the aforementioned process. Results shown
in Table 3.9.
To verify that the results of conversion were reasonable they were compared to
the estimations of seepage velocities observed during the NaCl tracer tests. The data
(Table 4.2) showed that seepage velocities calculated from hydraulic conductivities using
equation 4.1 correspond with those measured during the NaCl tracer tests at both the US
10/ 11 and USB 09 sites. While results of this comparison show that the tracer tests
results provided a higher velocity, the range is acceptable when considering local
variation at the sites and the natural aging, as velocities tend to degrade with time.
53
Table 4.2- Data from NaCl tracer tests for 2 sites on the LAR. Tracer tests and converted
standpipe drawdown tests (DD) show that the conversions of hydraulic conductivities
from DD tests are similar to seepage velocities estimated using the NaCl method.
Site
US 10/11
US 10/11
US 10/11
US 10/11
US 10/11
US 10/11
US 10/11
US 10/11
USB 09
USB 09
USB 09
USB 09
USB 09
USB 09
USB 09
USB 09
USB 09
Test Type
Tracer
Tracer
Tracer
Tracer
Tracer
Tracer
DD
DD
Tracer
Tracer
DD
DD
DD
DD
DD
DD
DD
Test
SWT 2
SWT 3
SWT 4
SWT 5
SWT 7
SWT 8
US1011-upper
US1011 Middle
SWT 9
SWT 11
LSB09-01
LSB09-02
LSB09-03
LSB09-04
LSB09-05
LSB09-06
LSB09-07
Vs
226
1900
1507
862
840
1191
713
396
732
2595
133
692
692
1851
371
45
122
54
4.2 Seepage Velocity vs. Grain Size Distribution
Seepage velocities on the American River vary from 1 cm/hr up to 1,800 cm/hr.
While hydraulic gradient is a key component in the variations of seepage velocities
(Pollard, 1955; Terhune, 1958), other relationships exist between permeability and
parameters that describe grain size distributions including mean, standard deviation
(sorting), skewness, and kurtosis (Masch and Denny, 1966; Summers and Weber, 1984).
The distribution statistics, discussed in chapter 3.3, were plotted against the estimated
seepage velocity to examine the relationship permeability and grain size.
Certain results were removed from the data set due to problematic sampling
conditions. These conditions were typically the result of a difficult standpipe installation
due to site or material conditions, causing abnormally high or low readings. Questionable
tests/ installations were denoted during field research and eliminated during the
comparative analysis.
Mean grain size values represent the arithmetic average of all grains in the sample
(Boggs, 1995). This statistic contains no information concerning the way the particles
are distributed around the mean particle size. A well sorted sample and a poorly sorted
samples can have the same mean grain size, but the permeability of these materials will
be different. As expected, no overall trend emerged when mean particle size was
compared to seepage velocity (Figure 4.1).
55
Seepage Velocity (cm/hr)
10000.00
1000.00
USB08
100.00
LSB09
US 10/11 Spit
10.00
US 10/11
RBP13 Pre
1.00
RBP13 Post
0.10
0.0
10.0
20.0
30.0
40.0
Mean Grain Size (mm)
50.0
60.0
Figure 4.1- Mean Grain Size in mm vs. apparent seepage velocity. Each point represents
an individual test where a drawdown test was performed in conjunction with a bulk
sample.
The standard deviation (𝜎), or sorting of a grain population is the measure of the
range of sizes present and the degree of spread of the grain sizes around the mean
(Boggs, 1995). Poorly sorted samples (𝜎 > 1.00) contain a wide range of grain sizes,
which can fit together more closely than a well sorted material(𝜎 < 0.71), reducing the
amount of pore space which can then inhibit the flow of fluid (Figure 4.2). Based on the
fundamental idea that sorting of material relates to directly to permeability, and as the
sorting value increases (becomes more poorly sorted) the permeability of that material
decreases. This simple relationship is present in samples taken during this study (Figure
4.3). An exponential trend can be seen in the plot that shows a decrease in seepage
velocities as the sorting of the gravel decreases (Figure 4.4).
56
Figure 4.2- Visual depictions of various sorting values. Well sorted material (SF&W =
0.35) maintains lager pore spaces when compared to poorly sorted material (SF&W = 2.00)
as fine-grained material fills areas between larger grains. (From Bunte and Abt, 2001)
57
Seepage Velocity (cm/hr)
10000.00
1000.00
USB 08
100.00
USB 09
US 10/11 Spit
10.00
US 10/11
RBP 13 Pre
1.00
0.10
0.00
RBP 13 Post
0.50
1.00
1.50
Sorting (phi)
2.00
2.50
Figure 4.3- Sorting value in phi units vs. apparent seepage velocity. Each point represents
an individual test where a drawdown test was performed in conjunction with a bulk
sample. A general trend can be seen where seepage velocity decreases as the sample
becomes more poorly sorted.
58
Seepage Velocity (cm/hr)
10000.00
1000.00
100.00
10.00
R² = 0.3809
1.00
0.10
0.00
0.50
1.00
1.50
Sorting (phi)
2.00
2.50
Figure 4.4- Sorting vs. apparent seepage velocity. Each point represents an individual test
where a drawdown test was performed in conjunction with a bulk sample. Best fit line
has an R2= 0.3809.
59
Seepage Velocity (cm/hr)
10000.00
1000.00
USB 08
100.00
USB 09
US 10/11
10.00
US 10/11 Spit
RBP 13 Pre
1.00
0.10
-2.00
RBP 13 Post
-1.00
0.00
1.00
2.00
Skewness (phi)
3.00
4.00
Figure 4.5- Skewness in phi units vs. apparent seepage velocity. Each point represents an
individual test where a drawdown test was performed in conjunction with a bulk sample.
Positive skewness values represent a finely skewed sample and negative values are
skewed toward coarse material.
60
Seepage Velocity (cm/hr)
10000.00
1000.00
USB 08
100.00
USB 09
US 10/11 Spit
10.00
US 10/11
RBP 13 Pre
1.00
0.10
0.00
RBP 13 Post
5.00
10.00 15.00 20.00
Kurtosis (phi)
25.00
30.00
Figure 4.2.4- Kurtosis vs. apparent seepage velocity. Each point represents an individual
test where a drawdown test was performed in conjunction with a bulk sample.
Skewness shows the degree of asymmetry present in the population. In geologic
applications, this indicates whether a sample has excess fine material (positively skewed)
or excess coarse material (negatively skewed) (Bunte and Abt, 2001). Kurtosis indicated
the degree of peakedness in a population. Higher kurtosis values indicate a higher degree
of peakedness (Boggs, 1995). Skewness and kurtosis failed to show any trend when
plotted against seepage velocities (Figure 4.5, 4.6).
All of these gravel properties have an effect of the way fluids move through the
material. This study found that the only clear relationship between permeability and
61
gravel composition was sorting. Multi-axis or 3d plots using more than one statistic were
analyzed but failed to yield any multidimensional correlation.
4.3 Additional Factors That Affect Permeability
Permeability of sediments is highly variable, and seepage velocities are subject to
even greater variations (Cedergren, 1997). The fitment of the trend line (𝑅 2 = 0.3809)
in figure 4.4 suggests that there are factors in addition to sorting which influence
movement of pore fluid through the gravel. Grain orientation, isotropy, and packing
control some physical properties of sediments such as porosity and permeability (Boggs,
1995; Pollard, 1955).
Preferential grain orientation and imbrication is are common features in fluvial
sediments. This orientation is a product of transport and deposition and is related to the
flow direction and velocity of the river (Boggs, 1995). Imbrication of bed surface causes
grains to be deposited into shingle-like patterns. Flat particles are more susceptible to this
kind of fabric (Bunte and Abt, 2001). Flat disc or blade shaped grains can also have a
tendency to lie flat creating a barrier to flow in the vertical direction. This can cause
vertical permeability to be different than horizontal permeability. As grains are shuffled
around, inter-granular pore space can be reduced and it can become more difficult for
surface water to interact with hyporheic water (Buss et al., 2009).
Some parts of this study make the assumption that hydraulic conductivity of river
gravels is identical in all directions. The single standpipe drawdown method relies on
62
hyporheic water to be drawn equally from all directions, called radial flow (Hantush,
1964). Pollard (1955) found that non-spherical gravels within which orientation is not
completely random will have permeability values which differ in all directions.
Orientation of a non uniform gravel caused by the unidirectional flow of the river have
preferentially aligned grains or create alternating layers of different grain sizes.
Laboratory seepage measurements also showed that randomly pooled non-uniform gravel
in a flume test does not behave in a uniform manner (Pollard, 1955). Grain orientation of
gravels tested was not measured.
Grain packing is type of sedimentary fabric, which describes the spacing of grains
and is a function of grain size and shape (Figure 4.7) (Kahn, 1956). Packing strongly
affects the porosity and permeability of sediments (Boggs, 1995). Poorly sorted
sediments tend to have lower permeability because grains are packed more tightly, with
the finer material filling in the pore space between larger grains (Boggs, 1995; Kahn,
1956).
Figure 4.7- Graphical depiction of how packing affects pore space between grains. In this
case, the packing geometry is identical. When grains are of similar size simple packing
produces larger pore spaces (a) than grains of different sizes (b) (from Kahn, 1956)
63
Pollard (1955) used a mixture of sand and gravel in a flume to test the effects of
compaction on permeability. After 3 successive packing events followed by testing,
results showed that compaction had caused a 93% reduction in permeability, from 730
cm/hr down to 35 cm/hr. After the compaction tests, the gravel was removed from the
flume and replaced, loosely, back into the flume and retested. The exact same gravel as
tested before compaction yielded a permeability value of 370 cm/hr, half as high of the
initial measurement. These experiments demonstrate the effects of packing on gravels.
Grain packing could not be quantified during sample collection since samples were
collected under moving water.
Natural processes that are responsible for deposition and transportation of fluvial
sediments have created complex grain relationships. In addition to the grain size
distribution of gravel, the way those grains fit together on multiple scales affects porosity
and therefore permeability. It is impossible to measure the in situ streambed to properly
characterize the true inter-granular relationships, which control porosity.
4.4 Equipment Factors
Equipment installation creates another variable that affects permeability. The
equipment used to conduct these tests and collect gravel samples disrupted the site and
material to be tested. Material is displaced, wells are developed to varying degrees, and
pumped.
64
The installation of standpipes equipment into the gravel displaces material and
may provide conduits for non-pore water to enter the standpipe (ie. piping). Both the
tracer tests and the drawdown tests require standpipes to be driven ~30cm into the gravel.
Due to different grain size distributions, the standpipe can be difficult to install. This can
force the standpipe to be installed at a slight angle due to deflection by larger grains. As
the length of standpipe is deflected it may disturb more gravel than a simple vertical
insertion. Typically, several attempts were made to properly install the standpipe, but
some site conditions made this impossible, resulting in a standpipe that "leaned" slightly.
14
12
Q (ml/sec)
10
8
6
4
2
0
0
1
2
3
Test No.
4
5
6
Figure 4.8- As water is removed during the development stage of the drawdown tests.
The rate of standpipe inflow increases until the well is developed and measurements
stabilize. Points show standpipe inflow rates and error bars show 10% of total rate for
that test.
65
During the initial testing of the drawdown method, it was revealed that
developing the well provided higher permeability values, which usually stabilized (Figure
4.8). This process stabilized the resulting measurements, but also cleared out sand and silt
from the area surrounding the well screen. Fine material is part of sediment packing and
pore space reduction, thus developing the well may result in higher than actual
permeability values due to an artificial clearing of pore space. Finely skewed samples did
not make up a significant proportion of high permeability tests so this hypothesis could
not be tested. A standard well development protocol was used at all sites, but it may not
have the same effect in all locations where testing was conducted.
The pumping equipment was also a potential source of error in this study. The
vacuum style system, which draws water into the sample tanks, is a mechanized version
of the original design pioneered by Barnard and McBain (1994). It allows a larger sample
to be taken over a longer period of time, which provides greater sample confidence
because of the complexity of the pumping rig. Vacuum leaks were a constant problem. A
small rechargeable 12v battery was used to provide power for the vacuum pump, and this
may also have affected some test results. Over the period of time the device is used in the
field, power in the battery is depleted and the strength of vacuum produced by the pump
is reduced. These issues only affected some of the very high permeability tests.
These methods proved to be very useful for estimating hydraulic conductivity and
calculating seepage velocities. The low cost and minimal amount of equipment make this
ideal for small group with basic training to produce quality results. Hyporheic
66
interactions are an important part the larger ecosystem and these measurements work
toward a better understanding of those interactions.
67
Chapter 5
Conclusion
5.1 Conclusion
The methods used in this study provided an effective way for determining gravel
permeability. Each method has strengths and weaknesses, but each helps characterize
salmon spawning habitat. A comparison of the methods helps choose the right tool for
permeability analysis.
The single standpipe drawdown method is an efficient and cost effective way of
measuring hydraulic conductivity in the field. Portability and ease of use are the strengths
of this method. An external frame backpack makes it possible to survey large areas
relatively quickly, so field sites can be blanked with measurements. The method is simple
and can easily be taught to small groups of inexperienced people, who can then produce
accurate results with relatively little training. It provides valuable information about
radial flow to a well and hydraulic conductivity values in the shallow subsurface.
The drawdown method does have some drawbacks. The equipment used to extract
the water from the standpipe during the test relies on a complex vacuum system and can
be difficult to maintain. Pumping rates are affected by leaks in the vacuum system. The
lead-acid battery that powers the unit has limited storage capacity, and, pumping rates
tend to decline over the course of a field day. The largest issue with this assessment
method is the heterogeneity of stream systems. River gravels are highly variable, and this
68
method tests a discrete point in the river about the size of a basketball. A large number of
measurements must be collected at each site to accurately characterize the streambed.
Lateral continuity is limited, and values cannot be inferred between test points.
The sodium chloride tracer tests are very useful for directly measuring seepage
velocities. The equipment used for the experiment is simple, inexpensive, and durable.
The straightforward nature of the experiment makes it easy for a small field team to
conduct with little training.
Tracer tests can provide clear and useful results, but a large proportion of the tests
fail. This is due to lateral or vertical flow in the subsurface or low permeability units.
Some tests also have weak breakthrough curves, making it difficult to determine seepage
velocities. This erratic character is amplified when the experiment is conducted in gravels
with lower permeability. Test time is also a factor. Test times can range from 45 minutes
to as long as 24 hours in some cases, making this method very impractical in terms or
cost per test when labor in taken into account. Permitting may be an issue at some sites,
presenting some problems with the legality of the method. Regulations may require a
permit in order to introduce a foreign material into the river and/or ground water system.
If a permit is required for each test, it could become impractical to use with any
regularity.
Bulk samples proved to be a good way to characterize the grain size distribution
of the gravel. Mathematical tools provide a wealth of statistics about grain size
distribution, and are used to some characteristics of the spawning gravels. For this study,
69
fewer larger bulk samples were traded for many smaller bulk samples. These smaller
sample sizes allowed for many more samples to be taken across the site, making it more
effective at characterizing grain size distributions across sites as a whole. This more
detailed characterization provided a better understanding about the heterogeneity of the
gravels on smaller scales.
Collecting the bulk samples in moving water presents some problems. When the
gravel is disturbed, there can be a loss of the finer material during the transfer the sample
container. Losing the fine material can have an impact on the grain size analysis, shifting
the statistics in a more coarse direction. The bulk samples are only able to characterize
the grain size distribution. No inference can be made about seepage velocity or hydraulic
conductivity based solely on the grain size distribution.
A clear relationship exists between sorting of river gravels and the ability of
hyporheic water to flow through the streambed, so sorting measurements can be used to
characterize spawning habitat. Well sorted gravel is generally more suited to spawning
than moderately or poorly sorted gravel. Information about sorting has limits, because
permeability is affected by several other factors. Grains mobilize over time as natural
river processes affect the restoration sites. This causes grain align and preferential flow
through the gravel, and limits permeability. Sediment packing changes as sites age, and a
higher degree of packing produces lower permeability. These physical changes are not
reported in the sorting value. There are also issues with heterogeneity in stream beds, so a
70
large number of grain size samples are required to determine the hyporheic properties of
a site.
This study examined three methods that were used to evaluate permeability in
salmon habitat restoration projects on the Lower American River. Grain sorting was
found to have a measureable effect on hyporheic permeability. Sites where the gravel is
well sorted have the highest permeability. Sites with poorly sorted gravels have lower
permeability. As the restoration projects age permeability tends to degrade. Sites that are
restored with well sorted coarse gravel may have a longer lifespan that those sites which
are restored with moderately sorted gravel.
71
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