MEASUREMENT OF SEDIMENT AND
CONTAMINANT LOADS FROM THE
GUADALUPE RIVER WATERSHED
SAMPLING AND ANALYSIS PLAN
Lester McKee and Jon Leatherbarrow
October 2002
A technical contribution from the Watershed Program
San Francisco Estuary Institute ( SFEI)
Oakland, CA
Report prepared for the Clean Estuary Partnership ( CEP)
CEP Work Plan Task #: PCB- SA- 4
CEP Short Title: Small Tributary Loads Assessment
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Table of Contents
BACKGROUND .......................................................................... 1
Project objective.............................................................................................................. 1
Timeline .......................................................................................................................... 1
Oversight ......................................................................................................................... 2
Location .......................................................................................................................... 3
Geographic location ................................................................................................... 3
Sampling location ....................................................................................................... 4
Watershed characteristics ............................................................................................. 5
Physiology ................................................................................................................... 5
Climate and hydrology ................................................................................................ 5
Geology and soils ........................................................................................................ 7
Watershed and stream morphology and habitat ......................................................... 8
Land use and population.............................................................................................. 8
Known contaminant sources ....................................................................................... 9
Channel modifications ( past and ongoing) ............................................................... 10
Watershed character downstream of the sampling location ..................................... 10
Previous and ongoing investigations of PCBs, OC pesticides and Hg .................... 10
DATA QUALITY OBJECTIVES ............................................ 11
Data uses ....................................................................................................................... 11
Expected measurements .............................................................................................. 12
Expected quality ........................................................................................................... 12
Data quality indicators ................................................................................................ 14
Data management ........................................................................................................ 15
Final report outline ...................................................................................................... 15
SAMPLING DESIGN ............................................................... 16
Bridge description ........................................................................................................ 16
Reach character ........................................................................................................... 17
Field health and safety ................................................................................................. 18
Field equipment ( description, calibration and maintenance) .................................. 19
Turbidity .................................................................................................................... 19
Suspended sediments ................................................................................................. 20
Trace contaminants ................................................................................................... 21
Sampling procedures ................................................................................................... 22
The sampling team .................................................................................................... 22
Sample collection....................................................................................................... 24
Sample documentation and shipment ........................................................................ 25
Labeling .................................................................................................................... 25
Sample storage and shipment ................................................................................... 25
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ANALYTICAL METHODS ..................................................... 26
Turbidity...................................................................................................................... . 26
Suspended sediments ................................................................................................... 26
Trace contaminants ...................................................................................................... 27
Mercury and methyl mercury .................................................................................... 27
Trace metals .............................................................................................................. 27
Trace organics .......................................................................................................... 27
Ancillary data ............................................................................................................ 27
REFERENCES .......................................................................... 28
APPENDIX ................................................................................. 31
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BACKGROUND
Project objective
The main objective of this project is to improve our knowledge on the magnitude
of contaminant loads entering the Bay from local tributaries and in doing so improve our
understanding of contaminant process in the Bay ( such as described by the PCB single
box mass balance model ( Davis, 2002). Thereby, this project is designed to assist in the
development of TMDLs and the management of the Bay. The project also has a number
of secondary objectives. These include a) the demonstration of an integrated
methodology for accurately determining loads of PCBs and other trace contaminants in a
key contaminated watershed, b) an analysis of the performance of the method in order to
make recommendations on how best to sample other watersheds in the future, and c) a
comparison of the results with the SIMPLE MODEL ( Davis et at. 2000) in order to
accept or reject its use as a tool for estimating loads for management purposes.
Timeline
This Sampling and Analysis Plan ( SAP) constitutes the written deliverable of
Project Implementation ( Table 1). Other activities have included a) the development and
negotiation of the required sub- contracts, b) site reconnaissance, c) confirmation of
equipment costs, d) budget reevaluation e) equipment purchase, f) turbidity probe
installation and testing, and g) web programming to make the turbidity data available real
time.
Each year the project continues ( 2002, 2003, 2004, and 2005) sampling will occur
in the winter months each time the watershed sustains storm rainfall that causes flow to
increase beyond 200 cubic feet per second ( cfs) and an increase in turbidity indicating
sediment and contaminant transport ( see sections below for definitions and rationale).
Each spring, samples will be analyzed in the laboratory and following delivery of results
back to San Francisco Estuary Institute ( SFEI), the main effort in analysis and reporting
will be carried out and completed by late summer.
Table 1. Generalized timeline for the Project.
2002- 2003 2003- 2004 2004- 2005 2005- 2006
F W S S F W S S F W S S F W S S
Project implementation
Sampling
Laboratory analysis
Funding request
Reporting
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Oversight
Project oversight will consist of members of the CEP technical committee,
consulting groups, universities, and members of the Sources Pathways and Loadings
Workgroup ( SPLWG) of the Regional Monitoring Program for Trace Substances ( RMP).
The oversight group, their main roles and their affiliations are listed ( Table 2). Oversight
will occur through four main mechanisms: 1. Monthly CEP technical meetings, 2.
Quarterly SPLWG meetings, 3. Mercury and PCB TMDL workgroup meetings, and 4.
Solicitations of external peer- review.
Table 2. Oversight group members. Note, where a person has several roles they have
been listed more than once.
Name and affiliation Name and affiliation
CEP technical committee RMP SPLWG
David Tucker, CSJ, BACWA ( Chair) Tom Mumley, SF RWQCB
Arlene Feng, AC, BASMAA Khalil Abu- Saba, AMS, CEP
Geoff Brosseau, BASMAA Andy Gunther, AMS, CEP
Andy Gunther, CEP Program Coordinator Jim Kuwabara, USGS
Khalil Abu- Saba, AMS Trish Mulvey CSB, SFEI Board
Fred Hetzel, SF RWQCB Tom Hall, EOA
Karen Taberski, SF RWQCB Terry Cooke, URS
Jon Konnan, EOA, SCVURPPP Russ Flegal, UC Santa Cruz
Chris Sommers, EOA Jim McGrath, Port of Oakland
Jay Davis, SFEI Dave Tucker, City of San Jose
Jim Scanlin, Alameda County
Mercury TMDL Workgroup Geoff Brosseau, BASMAA
Richard Looker, SF RWQCB Joseph Domagalski, USGS
Dave Drury, BASMAA Mike Nolan, USGS
Bill Elgas, BACWA Fred Hetzel SFBRWQCB
Khalil Abu- Saba, AMS, CEP Don Yee, SFEI
Carrie Austin, SF RWQCB Jay Davis SFEI
PCBs TMDL Workgroup External Peer- review
Fred Hetzel, SF RWQCB Mike Stenstrom, UCLA
Jon Konnan, BASMAA
Dan Watson, BACWA
Andy Jan, Port of Oakland
Jay Davis, SFEI
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Location
Geographic location
The Guadalupe River watershed is located in the Santa Clara Valley basin and
drains to Lower South San Francisco Bay ( south of Dumbarton Bridge) ( Figure 1). The
Guadalupe River watershed is one of 13 drainages that constitute the basin and the
second largest in terms of area. The Guadalupe River watershed is bounded on the west
by the San Tomas Creek watershed, on the east by the Coyote Creek watershed and to the
south by coastal watersheds.
Figure 1. The geographic location of the Guadalupe River watershed.
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Sampling location
The Guadalupe River study sampling site is located approximately 0.06 km
( 0.036 miles) upstream from where US Highway 101 passes over the Guadalupe River
( Figure 2). This location is on the northeast side of San Jose International Airport on a
bridge that connects the main airport grounds to a rental car service center.
Driving directions: From the northeast entrance of the airport on Airport Parkway, turn
right onto Airport Blvd. Follow Airport Blvd. approximately 1 km ( 0.6 mi) to the
sampling location at the bridge that connects the main airport grounds to a rental car
service center. From the southwest entrance of the airport on Coleman Ave, turn onto
Airport Blvd. Follow Airport Blvd. past Airport Parkway approximately 1 km ( 0.6 mi) to
the sampling location at the bridge that connects the main airport grounds to a rental car
service center.
Figure 2. Aerial view ( USGS DOQ) of Guadalupe River study sampling location.
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Watershed characteristics
Physiology
Guadalupe Creek flows from its headwaters in the eastern Santa Cruz Mountains
to its confluence with Alamitos Creek at Coleman Road in the city of San Jose where it
becomes Guadalupe River and continues its journey through the city, past the San Jose
International Airport and beyond Highway 101. The influence from the ocean tides
begins between the Montague Expressway and Highway 237 before the River ultimately
discharges to the South Bay via Alviso Slough. The Guadalupe River watershed
encompasses approximately 556 km2 ( 200 mi2). The watershed is the 4th largest in the
Bay Area by area and the 5th largest in terms of annual discharge volume to the Bay.
There are five main tributaries in the Guadalupe watershed: Los Gatos Creek, Ross
Creek, Guadalupe Creek, Alamitos Creek, and Canaos Creek. The subwatersheds of Los
Gatos Creek, Ross Creek, Guadalupe Creek, Alamitos Creek gather runoff from the Santa
Cruz Mountains, notable high points being Mt. Thayer ( elevation 1,063 m [ 3,486 ft]) and
Mt. Umunum ( elevation 1,062 m [ 3,483 ft]), and the summit of Loma Prieta ( elevation
1,155 m [ 3,790 ft]).
Climate and hydrology
The residents of the Guadalupe River water enjoy a mild climate similar to other
locations in the Bay Area that have only limited influence from maritime fogs. Average
monthly temperatures have reached a maximum of 27.8 ° C ( 82.1 ° F) in San Jose in July
and a minimum of 14.4 ° C ( 57.9 ° F) in January. Rainfall in the Guadalupe River
watershed is predominantly maritime, with regional- scale weather systems moving on
shore in response to the position of the Pacific high- pressure zone and westerly winds
that bring moist air from the Pacific Ocean. Rainfall measurements began in San Jose in
1898 making that location one of the longest running records in the Bay Area. Annual
rainfall in San Jose averages 368 mm ( 14.5 inches) with the maximum annual rainfall at
200% of the average and the minimum at 40% of the average. Locations in the highest
extremities of the watershed can receive in excess of 1,500 mm ( 60 inches) annually. In
addition to annual and spatial rainfall variability, the watershed undergoes periods of
drought, the most recent of which occurred from 1987- 92 ( six years of below average
rainfall) and “ deluge”, most recently 1993- 2000 ( eight wetter than average years with
only one intervening dry year). Rainfall follows a seasonal pattern with a pronounced wet
season that generally begins in November and can last through to May. During this
period an average of 89% of the annual rainfall occurs. The wettest month on average is
January with an average rainfall of 78 mm or 21% of the annual. On average, rain occurs
on 58 days at a depth of ≥ 0.254 mm ( 0.01 in), on 33 days at a depth ≥ 0.254 mm ( 0.1 in),
on 9 days at a depth ≥ 12.7 mm ( 0.5 in) and on only 2 days annually at a depth of ≥ 25.4
mm ( 1 in).
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Runoff in the Guadalupe River watershed exhibits similar patterns to rainfall;
high interannual variability ( C. V. = 117), successive years of low or high runoff, and a
highly seasonal runoff pattern. To a small extent, the runoff pattern is dampened by the
operation of storage reservoirs in the upper parts of tributary creeks. There are five major
reservoirs in the watershed with a total storage capacity of 44 Mm3 35,778 acre- feet) or
about 100% mean annual runoff ( MAR). The reservoirs occur on Los Gatos Creek
( Lexington Reservoir, and Vasona Reservoir), Guadalupe Creek ( Guadalupe Reservoir),
Alamitos Creek ( Almaden Reservoir), and Calero Creek ( Calero Reservoir). The
reservoirs were built for water supply but they also provide some flood mitigation.
Gauging on the Guadalupe River at San Jose began in 1930. Since that time
annual discharge has varied from 1 mm of runoff ( 0.422 Mm3) to 638 mm of runoff ( 241
Mm3) or about 600 times. The driest year on record occurred in water year ( WY) 1933
and the wettest year was WY 1983. MAR is 110 mm ( 42 Mm3 or 34,050 acre- feet). Daily
discharge varies from zero to 223 m3s- 1 ( 7,870 cfs). The largest in the past decade
occurred in 1995 ( Figure 3). In fact the 1995 flood is the largest on record with a peak
gauge height of 17.4 feet ( 5.3 m), 11,000 cfs ( 311 m3s- 1) and a mean daily discharge of
7,870 cfs ( 223 m3s- 1). During the past decade, the Guadalupe River has averaged seven
floods per year with an average daily discharge in excess of 200 cfs ( 5.7 m3s- 1). On
average, five of these were single peak events and two were events with three to five
peaks less than seven days apart. These floods are caused by intense rainfall in the
watershed over the preceding days ( Table 3). Depending on the rainfall in the season- to-date
and the rainfall intensity during a particular storm event, a rainfall of only 1.3 inches
in a 24 to 48- hour period can cause a small flood to route through the watershed. Rainfall
and stream flow information is collected by the Santa Clara Valley Water District as part
of their water management and flood alert system and is readily available on the internet
http:// alert. valleywater. org/ .
These observations have important implications for flood sampling for suspended
sediment and trace contaminants. Sampling teams will need to be responsive to weather
forecasts and be willing to remobilize for subsequent peaks that commonly occur less
than 7- 10 days apart especially later in the wet season. On average, there is a 17% chance
that the first flood will occur in September or October, a 45% chance of the first flood
being before November 30th and a 76% change that the flood season will begin prior to
New Year.
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0
50
100
150
200
250
1 2 3 4 5 6 7 8 9 10
Day
Daily mean discharge ( m3/ s)
WY 1991
WY 1992
WY 1993
WY 1994
WY 1995
WY 1996
WY 1997
WY 1998
WY 1999
WY 2000
Figure 3. Daily discharge on Guadalupe River at San Jose ( USGS 11169000) during the
largest flood of the year for each water year during the past decade.
Table 3. A comparison of rainfall and runoff during the largest flood of each water
year over the past decade.
9am Rainfall at Mt Umunhum
Water Year Date
Instantaneous
Peak
( cfs)
Daily
Average
( cfs)
Peak Gauge
Height
( ft)
Preceding
24 hours
( in)
Preceding
48 hours
( in)
Season to
Date
( in)
1991 3/ 24/ 1991 3,330 1,120 6.5 1.6 1.6 27.9
1992 2/ 12/ 1992 4,640 1,500 8.3 2.7 5.4 23.7
1993 1/ 13/ 1993 4,920 2,380 8.7 5.4 5.5 33.6
1994 12/ 11/ 1993 1,510 330 4.1 1.0 1.3 10.6
1995 3/ 10/ 1995 11,000 7,870 17.4 6.4 10.4 61.2
1996 2/ 20/ 1996 4,720 1,990 8.4 3.5 7.4 41.6
1997 1/ 26/ 1997 5,470 3,450 9.4 2.6 5.4 61.1
1998 2/ 3/ 1998 7,510 3,010 12.6 4.6 6.7 44.7
1999 11/ 30/ 1998 1,300 492 4.0 2.5 2.7 8.9
2000 2/ 11/ 2000 3,340 570 6.5 1.3 2.6 34.1
Geology and soils
The Guadalupe River watershed is comprised predominately of flood basin
Holocene deposits in the lower watershed, and alluvial fan Holocene and Pleistocene
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deposits in the upper watershed. The watershed lies on a series of faults with
northwesterly trends: San Jose, Palo Alto, Stanford/ Cascade, Monte Vista, and San
Andreas. Bedrock that underlies the Guadalupe River watershed northeast of the San
Andreas Fault is a composite of the Franciscan Complex, the Coast Range ophiolite, and
parts of the Great Valley Sequence. Mineralized mercury is widespread throughout the
New Almaden region, which is associated with siliceous and calcareous deposits from
hydrothermal alteration of serpentinite. Other metals that are widely distributed in the
watershed include magnesium, iron, nickel, and chromium, which are typically found at
high concentrations in serpentinized ultramafic rocks.
Watershed and stream geomorphology and habitat
Based on a public access level reconnaissance ( McKee and Leatherbarrow,
October 2002), sediment supply to the channels appears to be sourced from urban runoff,
bed and bank erosion and agricultural erosion. Very little fresh or even recently active
hillslope colluvial processes were observed in the areas visited ( excluding Los Gatos
Creek watershed) indicating that sediment supply to the streams is confined more to
localized failures rather than from the diffuse landscape. There were a number of ranches
running cattle and/ or horses observed where over grazing, yard areas or laneways had
exposed soils. New developments on hillsides where new roads have been cut also
showed evidence of erosion in isolated instances. There were also a number of tree crop
areas managed for zero vegetation cover. Areas either managed or accidentally left with
exposed soils in rural areas of the watershed will play a role in the overall sediment
budget for the watershed.
Riparian areas on the valley floor support native arroyo willow, Fremont
cottonwood, box elder, western sycamore, red willow, and sandbar willow ( SCBWMI,
2000). Species of oak around upper watershed riparian and hillslope areas and the native
meadow grasses and flowers have been the pride of the watershed throughout the mission
and mining eras. A steelhead run still exists in the mainstem of the Guadalupe River and
lower Los Gatos Creek. Work is presently underway to enhance the habitat by removal of
barriers and installation of fish ladders ( SCBWMI, 2000). Presently, out of a total survey
length of 81 miles of creek lines within the Guadalupe, 21% are concrete or rock- lined
culverted, 38% have been straightened, rerouted, or contained by levees, and 40% remain
in an “ unmodified” state.
Land use and population
The Santa Clara Valley was almost exclusively used for agriculture before the
World War II era. As the electronics industry began to develop in the 1960’ s, the valley
experienced large and rapid- paced population growth and subsequent urban development.
Current land uses in the Guadalupe River watershed are comprised of a mix of
agricultural and rangeland activities in the upper watershed and high- density urban land
use in the lower watershed ( Table 4). Urban development in the lower watershed has
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dramatically increased impervious surface cover, which typically hastens the transport of
sediment and associated contaminants via urban runoff in response to storm events.
Between 1940 and 2000, population in Santa Clara County has increased from
approximately 175,000 to 1.68 million people ( 800%) ( MTC and ABAG, 2002). As of
2000, approximately 53% of the people in Santa Clara County lived in the City of San
Jose, much of which lies within the Guadalupe River watershed. Estimates of projected
population in Santa Clara County for the year suggest that population will increase by
approximately 480,000 more people or 130% between 2000 and 2025 ( SCDF, 2001).
Table 4. Land use in the Guadalupe River watershed based on 1995 statistics
( SCBWMI, 2000).
Area Area
Land use ( acres) (%) Land use ( acres) (%)
Residential 32230 30.7 Agriculture 3120 3.0
Commercial 4888 4.7 Forest 37810 36.0
Public/ Quasi- public 2777 2.6 Rangeland 16859 16.1
Industry - Heavy 1556 1.5 Urban Recreation 2500 2.4
Industry - Light 996 0.9 Vacant/ Undeveloped 1145 1.1
Transportation and utilities 1027 1.0 61434 58.5
Mines and Quarries 28 0.0
43502 41.5
Known contaminant sources
Historic agricultural and mercury mining activities and more recent urban
development and population growth in the Guadalupe River watershed have resulted in
widespread distribution of contaminant sources in the watershed that are associated with
various land uses. The inoperative mining district of New Almaden ( currently within the
Alameda Quicksilver County Park), which at one time was the largest supplier of
mercury in North America, is responsible for historic deposits of mercury that continue to
flow to the Bay via a drainage network ( Abu- Saba and Tang, 2000). Urban conveyance
systems also continue to transport PCBs and OC pesticides ( DDT, chlordane, and
dieldrin) through the Guadalupe River watershed ( KLI, 2002; Leatherbarrow et al.,
2002). The Silicon Valley Toxics Coalition ( SVTC) currently displays maps that identify
locations of known point sources of contamination throughout the Santa Clara Valley on
their website ( SVTC, 2002).
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Channel modifications ( past and ongoing)
Interpretation of study results may require evaluation of bed and bank disturbance
associated with channel modifications that might impact water column concentrations of
trace contaminants and suspended sediments at the study location. The Guadalupe River
has been subject to morphological modifications since 1866, when a canal was dug to
relieve flooding from a then rapidly expanding orchard agriculture ( SCBWMI, 2000). In
the 1960s, Canoas and Ross Creeks were realigned. In 1975, about 3,000 feet of the
Guadalupe River channel was widened and moved eastward and the original channel was
filled to make way for the Almaden Expressway. In the late 1970s, Alamitos Creek was
widened and levees were built from Bertram Bridge downstream to its confluence with
Guadalupe Creek, a distance of approximately 6 miles. Recently, the U. S. Army Corps of
Engineers has begun a series of three flood control projects along the length of
Guadalupe River from Alviso Slough to just upstream of Almaden Lake on Guadalupe
Creek. Estimated construction time lines are August 2002 to December 2004 for the
Lower Guadalupe River Project, May 2002 to November 2004 for the Guadalupe River
Park and Flood Protection Project, and June 2003 to March 2010 for the Upper
Guadalupe River Project. Project partners include the Santa Clara Valley Water District,
the City of San Jose, and the San Jose Redevelopment Agency. The objectives of the
projects are to provide flood protection, protect fish and migratory bird habitat, and
provide recreational and open space benefits. Other ongoing or proposed projects in the
watershed include; the Los Capitancillos Freshwater Wetlands Project proposed to create
wetland habitat next to Guadalupe Creek near the Los Capitancillos Percolation Ponds
and compensate for sediment removal from the creek, the Guadalupe Creek Project
which will provide a flood protection berm to protect the Los Capitancillos Project, and
an ongoing bank stabilization project on Canaos Creek. Several federal and state funded
transportation projects are also in various stages of development in the Guadalupe River
watershed ( MTC, 2002).
Watershed character downstream of the sampling location
The area downstream of the sampling location ( and hence that will not be
measured) is characterized mainly by industrial and commercial land use with small areas
of residential and open space. This area is flood- prone and mostly less than 20 feet above
sea level. During large floods it may be difficult to accurately define where in fact the
watershed boundary lies. At low flow however, the area is about 10 square miles or less
than 1% of the total watershed area.
Previous and ongoing investigations of PCBs, OC pesticides and Hg
Several studies have investigated the distribution and extent of contamination in
the Guadalupe River. These previous results will provide context for analysis of data
generated in this study. From 1996 to 2001, the RMP conducted seasonal sampling of
water and sediment in the tidal reach of the Guadalupe River ( Alviso Slough) to
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determine that wet- season concentrations of PCBs, OC pesticides and mercury were
relatively high in surface water entering the Bay ( Leatherbarrow et al., 2002). In an
ongoing effort to assist TMDL development that began in 2000, the Santa Clara Valley
Urban Runoff Pollution Prevention Program has been monitoring sediment in urban
conveyance systems and creeks for PCBs and mercury ( KLI, 2002). Both contaminants
have been measured at high concentrations in urban/ industrial sites within the watershed.
A mercury TMDL for the Guadalupe River is currently being developed under the
guidance of the Santa Clara Basin Watershed Management Initiative with collaboration
from the Santa Clara Valley Water District, Tetra Tech, Inc. and EOA, Inc. A final
TMDL report is due by June 2003.
DATA QUALITY OBJECTIVES
Data uses
Section 303( d) of the Clean Water Act requires that impaired water bodies be
identified. Impaired water bodies are those where water quality standards are not
expected to be met after implementation of best available technological controls, with
respect to permitted wastewater. Water quality standards include: ( 1) designated uses
( such as fish and wildlife habitat and recreational use); ( 2) any narrative or numeric water
quality objectives; and ( 3) anti- degradation or maintenance of ambient water quality.
San Francisco Bay is listed as impaired by the State ( Clean Water Act 303( d)) for
PCBs, OC pesticides ( DDT, chlordane, and dieldrin), and mercury. Once a water body is
listed under Section 303( d), the State is required to determine the amount that the
contaminants of concern must be reduced to meet the applicable water quality standard
and eliminate beneficial use impairment. This allocation of allowable contaminant
discharge from various sources is called a Total Maximum Daily Load, or TMDL.
As part of TMDL implementation, the San Francisco Regional Water Quality
Control Board ( SF RWQCB) and its environmental management partners has specifically
requested better estimates of loads of TMDL listed substances from local urbanized small
tributaries to inform strategies for water quality attainment. For example, the PCB one-box
model for the Bay ( Davis, 2002) currently suggests that external annual loads of just
10 kg of PCBs would prevent the total PCB mass in the Bay from ever dropping below
one- tenth of the present mass, thus maintaining concentrations in some sport fish that
may continue to pose human health concerns. An estimate of loads for PCBs from one of
the major urban drainages of the Bay Area will allow environmental managers to focus
management on specific sources and pools. In the case of mercury, assessment of
concentrations and loads in the Guadalupe River will provide valuable baseline data to
quantify ongoing impacts to the Bay in the context of legacy loads and to assess
concentration and load trends in a watershed that is itself listed as impaired for mercury.
At present there are no estimates of current inputs of OC pesticides. This study will
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provide a valuable data set to begin the process of determining current loads of persistent
organochlorine contaminants to the Bay.
Therefore in the context of these outlined management needs, the data collected
during this study will be used to characterize water, suspended sediment, and trace
contaminant transport processes at a downstream cross- section on the Guadalupe River
channel. The interest is mainly in the accurate characterization of changes in
concentrations of each contaminant during the passing of a storm hydrograph and
between storm hydrographs. However, there will also be some effort expended to
quantify concentration variations of suspended sediment and trace contaminants at
various points in the X- section during selected storm events. Afer QA/ QCOnce trace
contaminants and suspended sediment concentrations will be combined with estimates of
discharge provided by the USGS to estimate loads of contaminants and sediments
entering the tidal sloughs and South San Francisco Bay.
Expected measurements
Measurements made during this study will include concentrations determined
through laboratory analyses of appropriately sampled and preserved stream water, optical
backscatterance measured using a turbidity probe, and ancillary data measured using
various calibrated field and laboratory instruments. All expected measurements are listed
in the following tables ( Table 5). To aid in the interpretation of the expected
measurements made in this study, additional hydrological data including precipitation
and stream flow will be requested from the Santa Clara Valley Water District. Additional
ancillary data may include qualitative visual observations in the watershed after flood
events to better understand subwatershed erosion and point source activation processes
and their influences on sediment and contaminant supply and transmission to the
watershed outlet ( sampling location). There is also the possibility of collecting or
collating satellite or aerial images of the receiving waters ( the South Bay) to obtain a
qualitative view of contaminant fate. However it should be emphasized that the processes
of source activation and fate are outside the current scope of the project.
Expected quality
Data quality refers to the level of uncertainty associated with a particular data
point. All the elements of the sampling event, from the sampling design through the
laboratory analysis and reporting, affect the quality of the data. The management
questions this project aims to assist in answering help determine what level of uncertainty
is acceptable or appropriate. The following decisions on acceptable detection limits,
accuracy and precision ( Table 6) were derived from existing knowledge of expected
concentrations in the immediate receiving water body ( Alviso Slough), concentrations of
each contaminant known to be toxic or detrimental to beneficial uses, and the cost
associated with laboratory processing at higher detection limits.
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Table 5. Parameters to be analyzed for or measured in the laboratory or field in
Guadalupe River water over the 4- year study program. Units are
concentrations ( mass per unit volume) unless otherwise stated.
PCB
Congeners
Organochlorine
Pesticides
1PAHs
Trace
Metals
Ancillary
Measurements
8, 18, 28, 31, 33, 44, 49, 52, 56, 4 Cyclopentadienes 1- Methylnaphthalene Total Mercury Optical back scatter ( NTU)
60, 66, 70, 74, 87, 95, 97, 99, Dieldrin 2,3,5- Trimethylnaphthalene Dissolved Mercury 3 Suspended sediment
101, 105, 110, 118, 128, 132, 2,6- Dimethylnaphthalene Methyl Mercury Particulate Organic Carbon
138, 141, 149, 151, 153, 156, Chlordanes 2- Methylnaphthalene Dissolved Organic Carbon
158, 170, 174, 177, 180, 183, alpha- Chlordane Biphenyl 2 Silver Nutrients
187, 194, 195, 201, 203 cis- Nonachlor Naphthalene 2 Copper pH
gamma- Chlordane 1- Methylphenanthrene 2 Lead Conductivity ( ms cm- 1)
Heptachlor Acenaphthene 2 Nickel Temperature (° C)
Heptachlor Epoxide Acenaphthylene 2 Cadmium
Oxychlordane Anthracene
trans- Nonachlor Fluorene
Phenanthrene
DDTs Benz( a) anthracene
o, p’- DDD Chrysene
o, p’- DDE Fluoranthene
o, p’- DDT Pyrene
p, p’- DDD Benzo( a) pyrene
p, p’- DDE Benzo( b) fluoranthene
p, p’- DDT Benzo( e) pyrene
Benzo( k) fluoranthene
Dibenz( a, h) anthracene
Perylene
Benzo( ghi) perylene
Indeno( 1,2,3- cd) pyrene
Dibenzothiophene
Notes
1. PAHs will not be analyzed for in the
first year of the study ( Water Year
2003) unless the CEP approves an
increase in the budget.
2. Silver, Copper, Lead, Nickel, and
Cadmium will be analyzed for as
budget allows.
3. Water samples for analysis of
suspended sediment concentration
will be collected by the contaminant
sampling team ( UCSC and SFEI) as
well as the sediment loads sampling
team ( USGS).
4. If budget allows.
Table 6. Anticipated data quality of primary data.
Number of
Samples
Precision Accuracy Detection
Limit ( DL)
Field Blank
PCBs < 30 ± 25% Within 10% of reference 1- 5 pg l- 1 Within 10% of DL
OC pesticides < 30 ± 25% Within 10% of reference 1- 5 pg l- 1 Within 10% of DL
PAHs < 30 ± 25% Within 10% of reference 200- 500 pg l- 1 Within 10% of DL
Mercury 30 ± 25% Within 10% of reference 0.1 ng l- 1 Within 10% of DL
Trace metals 30 ± 25% Within 10% of reference < 0.1 μg l- 1 Within 10% of DL
Suspended sediments < 150 ± 5% Within 10% of reference 0.1 mg l- 1 Within 10% of DL
Turbidity Every 15 minutes ± 2% Within 10% of reference 0.0 NTU Within 10% of DL
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Data quality indicators
The data quality indicators, precision, accuracy, completeness, detection limits,
representativeness and comparability, relate to various aspects of the data gathering, or
sampling and analysis. Quality assurance and quality control procedures for laboratory
analyses are conducted in accordance with the Quality Assurance Project Plan for the
RMP ( Yee et al., 2001). Quality control criteria for analyses of trace elements, trace
organics, and ancillary water quality parameters are listed in the Appendix. Brief
summaries of each indicator are provided in the following paragraphs:
Accuracy is the degree of agreement of a measurement with a known or true
value. To determine accuracy, a laboratory or field calibration value is compared to the
known or true concentration. Accuracy is usually assessed through the use of spiked
samples ( e. g., matrix spikes or surrogate spikes) or the analysis of a sample of known
concentration ( e. g., a performance evaluation sample or laboratory control sample
[ LCS].) In the field, calibration with prepared standards provides information about the
accuracy, or bias, of a field instrument. If the data provided from the laboratory does not
meet the required accuracy listed in Table 6, the data will be tagged with a qualifier.
Precision is the degree of mutual agreement between or among independent
measurements of a similar property ( standard deviation [ SD] or relative percent
difference [ RPD]). This indicator relates to the analysis of duplicate laboratory or field
samples. If the precision of the data does not meet the criteria laid out in Table 6, the data
will be tagged with a qualifier.
Completeness is expressed as the amount of usable data obtained compared to the
amount that was expected to have been obtained. Due to a variety of circumstances,
sometimes not all samples collected can be analyzed. The percent completeness required
will depend on data use and decisions to be made based on those data. Expectation of
completeness will be higher the fewer the number of samples taken per event.
Representativeness is the expression of the degree to which data accurately and
precisely represent a characteristic of an environmental condition or a population. It
relates both to the sampling area and to the sampling procedures. The sampling
methodology was designed to assess representativeness via two main mechanisms. 1. We
will collect both point data and depth/ X- sectionally integrated samples ( DCS). The DCS
samples will be used to test the degree to which the point sampling explains both the
temporal and spatial variation of concentration in the water column. The issue of
representativeness will be incorporated into interpretation and discussion of the results in
the Final Report.
Comparability expresses the confidence with which one data set can be
compared to another. The use of standard, published methods allows the data to be
compared to data from other projects; using the same methods throughout allows for
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comparison of data within a project. Expressing data using consistent units also addresses
comparability. The project aim to collect data using standard published methods and
briefly outlined in this Sampling and Analysis Plan. The aim is to ensure that the data
collected is specifically comparable with other mercury and PCB data collected in the
Bay, and Guadalupe River during the development and implementation of TMDLs.
Data Management
Both the UCSC and AXYS analytical labs provide data to SFEI in both written
and electronic form. Electronic data files are provided in Excel spreadsheet format. Once
the data is checked for quality control, SFEI will upload the data into an Access Data
Base and then into Oracle Data Base. It can then be extracted at will and on request via
appropriate staff at SFEI or via the web ( www. sfei. org). The data will also be formatted
and provided in raw tables within the final report. The following check list provides a
brief overview of data management procedures.
1. Data Manager: Receipt of data – conduct an inventory to check that all types of
data have been provided
2. QA Officer: Carryout QA/ QC procedure
3. Data Manager: Format the data ready for archiving
4. Data Manager: Archive data in Access Data Base and Oracle
5. Lead Scientist: Carry out interpretation and prepare draft report
6. Lead Scientist: Submit draft report for management and external peer- review
7. Lead Scientist: Address reviewers comments and prepare final report
8. Lead Scientist: Submit final report and a reply to the reviewers
9. Lead Scientist: Give oral presentation to Science Oversight Group
10. Lead Scientist: Prepare report as a peer- reviewed Journal article
Final report outline
The final 1st year report will be completed in late Fall, 2003. It is anticipated that
it will be approximately 30 pages in length with additional appendices as necessary
containing raw data. It is anticipated that the report will contain the following sections:
Cover ( with site photograph)
Abstract
Acknowledgements
Table of contents
Introduction
Methods
Turbidity
Suspended sediments
Trace metals
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Trace organics
Results
Turbidity
Suspended sediments
Trace metals
Trace organics
Discussion
Recommendations
References
Appendices
SAMPLING DESIGN
Bridge description
All sampling during high flow will occur off the “ Rental Car Return Bridge”
located on the property of the San Jose International Airport. The bridge was built and is
maintained by the airport authority. The bridge is a two lane bi- directional all- concrete
steel reinforced structure with a slight arch and a single center pillar support in the middle
of the river channel ( Figure 4A. and 4B.). Traffic speed on the bridge is subdued by a
traffic light on the western end of the bridge. There is a raised footpath with a width of
1.5 m ( 4.8 ft) on each side of the carriageway. The footpath on the downstream side of
the bridge will be used for operating the field equipment and collecting samples. The
bridge rail measures 9.0 m ( 29.4 ft) above the current thalweg. The rail has a height of
1.1 m ( 3.7 ft) above the footpath.
A. B.
Figure 4. A view of the “ Rental Car Return Bridge” ( the study sampling location)
looking from ( A) the bottom of left bank, and ( B) the top of the left bank of
the Guadalupe River.
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Reach character
The reach has been straightened and widened and the X- section geometry has
been modified to a trapezoid to improve the transmission of flood discharge. The upper
banks in the vicinity of the bridge have been secured from erosion by wire covered rock
gabion. Presently the low- flow channel meanders left to right as it passes downstream
( Figure 5A and 5B). The main features of the channel at the sampling location include the
low- flow channel, a low- flow channel partially submerged bar, a low- flow channel left
bank, an in- channel floodplain that marks the height of the bankfull discharge
( approximately 1.5 year return interval flood), and the upper ( high flow) trapezoidal
banks ( Figure 6). The bed at the sampling location consists of poorly sorted gravels,
sands and silts with a median grainsize ( D50) of 10 mm ( visual estimate). The in- channel
floodplain is vegetated with grasses, reeds and other soft- stemmed riparian plants. There
are a number of larger trees both upstream and downstream that were perhaps part of the
original riparian vegetation before the channel was modified. The turbidity sensor and
USGS box sampler ( suspended sediment point samples) are presently positioned to
sample the thalweg of the current low- flow channel ( Figure 6). Under moderate or high
flood conditions it is likely that the thalweg may move laterally. This may necessitate the
repositioning of the point sampling locations for turbidity and suspended sediments.
Although the sampling location is relatively free of trash and other urban debris, during a
reconnaissance upstream ( October 2000), there were a number of reaches that were
littered with trash such as bottles, cans, and various types of plastic and metal objects,
such as a shopping trolley. These may pose a problem should they catch on the turbidity
sensor housing.
A. B.
Figure 5. The character of the low- flow channel at the sampling location ( A) looking
upstream and ( B) looking downstream with the Highway 101 Bridge near the
top of the photo.
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0
2
4
6
8
Depth ( m)
0 4 8 12 16 20 24 28 32 36 40 44 48 52 56 60 64 meters
0 15 30 45 60 75 90 105 120 135 150 165 180 195 210
0
6
12
18
24
Depth ( ft)
feet
USGS box- sampler
Turbidity Bridge pillar
sensor
Water depth
10/ 25/ 02
Bankfull
depth
Rock gabion
USGS staff plate
Figure 6. Scale X- section of the sampling location indicating the main channel features.
Field health and safety
The sampling location on Guadalupe River presents a suite of hazards that must
be addressed by any field investigator. During the wet season, stream flows will be too
high to enter and all sampling will occur from the bridge. If field personnel must enter the
channel ( in particular during the maintenance of the turbidity probe) there are localized
hazards due to steep and potentially unstable banks, unsure footing, perhaps unstable
recently deposited large debris, exhaustive work, urban pollution, and crime that might
pose problems. To counter these hazards, SFEI has developed a “ Safety Sheet” for
fieldwork ( Table 7). It presents general guidelines for health and safety in the field that
will be followed during this Project; however, “ common sense”, concentration on the job
at hand, and care for others remain the best defense against potential and real field
hazards.
Table 7. Field health and safety guidelines for the Guadalupe River watershed Study.
General When using chemicals
1. Always have at least two people in the field at any time. 1. Wear safety glasses and gloves.
2. Always notify Airport Security prior to or upon arrival. 2. Know your equipment/ sampling methods before you begin.
3. Carry a first aid kit. 3. Avoid contact between reagents and shin, eye, nose, and mouth.
4. If possible, carry a cellular phone. 4. Do not eat or drink while monitoring.
5. Be aware of team members with allergies to insects or
vegetation.
5. DO NOT pour chemicals or samples containing reagents onto the
ground or into the creek.
6. Never drink the stream water. 6. Close all reagent containers after use to avoid accidental spills.
7. Take care on unstable stream banks. 7. Wipe up spill immediately if they occur.
8. DO NOT attempt to wade swift flowing water.
9. If you are afraid for your safety, stop monitoring.
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Field equipment ( description, calibration and maintenance)
Turbidity
Turbidity Sensor
This component of the study is being led by Rand Eads of the USDA Forest
Service, Redwood Sciences Laboratory. Recent advances in turbidity sensors have
reduced biofouling by employing a mechanical wiper that is activated before each
turbidity measurement ( Eads, 2002). Biofouling by macroinvertebrates and algae occlude
the sensor’s optical window and can quickly degrade data quality in streams that have
warm temperatures and high nutrient loads. We have purchased and installed a DTS- 12
turbidity sensor ( Figure 7A), manufactured by Forest Technology Systems Limited
( FTS), at the Guadalupe site. Digital communication between the sensor and data logger
allows for long cable runs ( 160 feet from the instrument shelter) without signal
degradation. We anticipate that the sensor’s wiper will successfully remove small
contaminates from the optical sensor. Field crews will need to remove larger organic
debris if material becomes lodged near the sensor. Field trials, laboratory testing, and
statistical analysis at Redwood Sciences Laboratory has led us to conclude that a median
turbidity value ( from 100 samples in the case of the DTS- 12) is more robust in rejecting
outliers than the mean or other commonly collected parameters. We will store the median
value from each 15- minute wakeup in the USGS Design Analyses data logger ( these
values, in addition to water stage, will also be available on the USGS web site). The
DTS- 12 records turbidity in NTUs and is auto- scaling from 0- 200 and 0- 2000 ( the DTS-
12 manual is available in electronic form). The DTS- 12 will be compared periodically,
and only at lower turbidities, to a Hach 2100P portable turbidimeter ( widely considered a
standard device for field measurements). This will provide assurance that the sensor is
operating correctly. The DTS- 12 will be returned periodically to the factory for a 6- point
calibration in Formazin standards.
Sensor Deployment
Two methods of deployment for the turbidity sensor were discussed at length with
the study team. The original method entailed mounting an articulated sampling boom
( plans and photos published on the Redwood Sciences Laboratory web site at:
www. rsl. psw. fs. fed. us/ projects/ water/ tts_ webpage) on the bridge ( access to the car rental
facilities) and routing the cable to the USGS instrument shelter. A second deployment
method was selected that would allow the sensor and boom to be installed in a more
timely fashion ( the boom and sensor ( Figure 7B) were installed and connected to the
USGS data logger on 10/ 9/ 2002). The deployment that was selected is based on a prior
design concept that uses a depth- proportional boom that is anchored to the streambed
( Eads and Thomas, 1983). The boom was modified from its original design to incorporate
the turbidity sensor. The geology of the basin and the potential effects on bedload
transport on the sampling boom were discussed with Tom Lisle, a fluvial
geomorphologist with Redwood Sciences Laboratory. The conclusion was that dune, or
bed form, migration during storms would not be a likely occurrence and therefore the
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predicted height of sensor above the bed is thought to be suitable. An advantage of a bed-mounted
boom is that debris is less likely to foul the sensor. A disadvantage is that the
bed- mounted boom cannot be accessed during storm flows should the equipment require
servicing. Another potential disadvantage is that the bed- mounted boom may only have
an effective angle in the water column during high flow of about 30 degrees ( when
velocity and depth overcome flotation). We expect that the 13 foot- long boom will be
fully submerged at storm flows about six feet of stage, and greater, placing the sensor at a
maximum distance of about 3 feet above the bed. The boom is anchored to the streambed
and protected from impacts by a large block of concrete immediately upstream. In
addition to the anchor, a safety stainless steel cable attaches the boom to the concrete
block. The boom is constructed of non- rusting aluminum and flotation is provided by two
high- density foam floats.
A. B.
Figure 7. The DTS- 12 turbidity sensor. A) The DTS- 12 Turbidity Sensor and purpose-built
housing, and B) Photo of the installed sensor and bed- mounted boom at
the Guadalupe River sampling location.
Suspended sediments
The purpose of sampling the water column for suspended sediment analysis is to
determine the instantaneous mean discharge- weighted suspended sediment concentration
in the water column. When such concentrations are combined with estimates of
discharge, suspended sediment loads are computed. There are a number of sampling
devices that have been developed by the Federal Interagency Sedimentation Project
( FISP) and its industry partners for sampling wadeable streams ( Handheld samplers) and
non- wadeable streams ( Cable and Real Samplers). For a description of the full range of
devices, the reader is referred to Edwards and Glysson ( 1999). The USGS ( Larry
Freeman) will lead this part of the Guadalupe River project. They own and maintain two
samplers that will be used in this project. During periods of high flow when the
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Guadalupe River in not wadeable at the sampling location, a US D- 74 depth- integrating
sampler ( Figure 8A). The D- 74 is designed for sampling stream of less than 4.5 m ( 15
feet) depth. The D- 74 weighs 62 pounds and will be deployed from the bridge footpath
using a four- wheel boom truck and a cable- and- real system ( Figure 8B). The D- 74 has a
streamlined cast body that completely encloses a pint bottle. A lower flows when the
stream is wadeable, the US DH- 48 hand- held depth- integrating sampler will be used
( Figure 8C). This sampler is a streamlined aluminum casing about 13 in long that partly
encloses the pint sample bottle. Including the sampling container, the whole device
weighs 4.5 lbs. During this study we will use a ¼ inch sampling nozzle on both the US
D- 74 and the US DH- 48.
A. B. C.
Figure 8. The suspended sediment samplers employed by the USGS at the Guadalupe
River sampling location. A) US D- 74 depth- integrating sampler, B) USGS
Type A Crane with Type A Four- Wheel Truck and C) US DH- 48 hand- held
depth- integrating sampler.
Trace contaminants
Description of Sampling Equipment
The equipment used for sampling water for analysis of trace contaminants and
ancillary water quality parameters is similar to equipment used for RMP Status and
Trends Monitoring as outlined in the RMP Field Sampling Manual ( David et al., 2001).
Field operations procedures and equipment are slightly modified to adapt to logistical
factors for conducting stationary sampling from the above- channel bridge location. Major
modifications to routine RMP sampling equipment include the addition of a US D- 96
depth- integrating collapsible bag suspended- sediment/ water quality sampler ( Figure 9).
An operation manual for the D- 96 sampler is accessible via the Internet from the Federal
Interagency Sedimentation Project ( FISP, 2002). Other primary components of sampling
equipment include Teflon ™ , C- flex ™ and polypropylene sample tubing and fittings,
trace metals filter ( for dissolved trace metals sampling) and assorted sample containers.
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Figure 9. US D- 96 depth- integrating collapsible bag suspended- sediment/ water
quality sampler
Preparation of Sampling Equipment
Sampling equipment and containers used for collecting samples for analysis of
trace elements and ancillary parameters are prepared by UCSC prior to sampling using
trace metal clean techniques described by Flegal et al. ( 1991) in accordance with the
RMP Field Sampling Manual ( David et al., 2001).
Samples collected for analysis of PCBs, OC pesticides, and PAHs are collected
using the same apparatus used for trace element samples. Sample containers for trace
organic samples are prepared by AXYS and shipped to SFEI prior to the date of sample
collection. Sample containers are 4- liter amber- colored glass bottles prepared by AXYS
prior to sampling by washing and baking or solvent- rinsing using standard laboratory
operating procedures. Sample bottles are then shipped to SFEI for sample collection.
Sampling procedures
The sampling team
Turbidity
SFEI will collaborate with colleagues at Redwood Sciences Laboratory ( RSL) to
achieve the goals of this project task. Rand Eads ( RSL) has experience in deploying
optical probes for continuous suspended sediment monitoring in more than 25 watersheds
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on the west coast. SFEI has assisted RSL with the installation of the sensor, logger and
other equipment at the USGS gauge. RSL will train SFEI in the protocols for probe
maintenance during the first months of probe operation. Henceforth, SFEI will be
responsible for probe maintenance include cleaning any accumulated materials from
either the sensor or boom housing. Electronic data from the gauging station will
periodically be retrieved by USGS and sent to Redwood Sciences Laboratory. RSL will
perform data cleanup and quality assurance. RSL will also receive the raw suspended
sediment data set from USGS after the USGS has completed quality assurance. A second
sediment data set will be collected by UCSC/ SFEI as part of the ancillary data set of the
trace contaminants sampling program ( see below). RSL will use both of these sediment
data sets to compute daily- suspended sediment concentrations and loads. Both finalized
turbidity and daily- suspended sediment data sets will then be provided back to SFEI for
interpretation and reporting.
Suspended sediments
The USGS has been collecting data on the discharge of sediment in Bay Area
watersheds for the past 40 years and are recognized local experts in the collection and
analysis of water discharge and suspended sediment loads in small tributaries of the Bay
Area. There are 18 locations in the Bay Area where the USGS has collected at least one
full wet season of data and three locations where there is more than 15 years of data. In
addition, the same teams that collect sediment data also maintain the discharge gauging in
the Bay Area that includes continual reassessment of cross- sectional geometry and rating.
The USGS ( Larry Freeman and his team) will be responsible for collection and
interpretation of suspended sediment data at the Guadalupe gauge. The USGS has a
standard protocol called “ seasonal daily suspended sediment loads” that they will initiate
to achieve this goal. USGS will seek, train and pay a local “ observer” ( usually a local
landowner, local resident or university student). Once QA/ QC is complete, the USGS
will provide sediment data to RSL for comparisons to the turbidity method and to SFEI
for interpretation and reporting in the context of the contaminant data.
Trace contaminants and ancillary data
This task will be completed by collaboration with UCSC, led by Dr. Russ Flegal.
They have been working with SFEI and other Bay Area groups for more than a decade.
UCSC has been primarily responsible for the collection and analysis of trace metals and
ancillary data for both the “ Status and Trends Program” and the “ Special Studies”
components of the Regional Monitoring Program for Trace Substances ( RMP). They
have a set of standard protocols for “ Clean” data collection, have years of experience
working with the RMP and its partners, and have demonstrated important contributions to
improved management of the Bay as well as numerous technical and peer- reviewed
publications. The contaminant field team will consist of two team members from UCSC
and one team member from SFEI. One person will carry out the “ clean hands” field
duties, one person will carry out “ dirty hands” field duties, and the third person will be
responsible for general duties and site logistics. Given the fast response time of the
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Guadalupe River, real- time data including rainfall, discharge gauging in the upper
watershed and turbidity from this study will be accessed via the Internet for the team
members.
Sample Collection
Turbidity
The DTS- 12 turbidity sensor has been set to wake up every 15 minutes and send
data to the data logger located in the USGS gauge house. The position that the sensor
takes the data within the water column is fixed horizontally in the thalweg; however, the
vertical position will change depending on the stage height but will remain no greater
than about 1 m ( 3.28 ft) above the bed at maximum stage.
Suspended sediments
The USGS will collect water samples for suspended sediment analysis using two
methods. On a routine basis ( 2- 3 times per week) and during floods ( up to 2- 3 times per
day), the “ observer” will collect single vertical samples ( Edwards and Glysson, 1999).
The objective of collecting a single- vertical sample is to obtain a sample that represents
the mean discharge- weighted suspended- sediment concentration in the vertical being
sampled at the time the sample was collected. Depending on the stage height, the US DH-
48 or the US D- 74 will be used. The sampling is taken be passing either sampler down
and then up through the water column at an even rate so that the sample bottle fills to the
base of the neck at the time the device reaches the surface.
In addition to the single vertical samples, the USGS will also collect 10- 20
samples using the “ Equal- Width- Increment” ( EWI) method ( Edwards and Glysson,
1999). A cross- sectional suspended- sediment sample obtained by the equal- width-increment
( EWI) method requires a sample volume proportional to the amount of flow at
each of several equally spaced verticals in the cross section. This equal spacing between
the verticals ( EWI) across the stream and sampling at an equal transit rate at all verticals
yields a gross sample volume proportional to the total stream flow. It is important,
obviously, to keep the same size nozzle in the sampler for a given measurement. The
Guadalupe River sampling location will be divided into 15- 20 verticals. The estimated
volume of the composite sample therefore will be about 5- 6 pints.
Trace contaminants and ancillary water quality parameters
Collection of water samples for trace contaminant analyses is performed by
UCSC staff using trace metal- clean sampling techniques ( EPA, 1996) in accordance with
the RMP QAPP ( Yee et al., 2001). A ‘ clean hands/ dirty hands’ approach is used when
collecting samples in this manner. The ‘ dirty hands’ person assists the primary ‘ clean
hands’ sampler by controlling the flow controller for the peristaltic pump, holding on to
or adjusting the sampler components, adjusting the outlet tubing or filter cartridge, and
handing sample containers to the ‘ clean hands’ person. The ‘ dirty hands’ person does not
touch the trace- metal clean bottles, but opens the Ziploc ™ bags so that the “ clean hands”
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person may remove them from the bags. The “ clean hands” person, wearing at least one
pair of polyethylene gloves, does not touch anything with her/ his hands except the inner
Ziploc ™ bag and trace metal clean sampling components. The clean hands/ dirty hands
system is not critical for the ancillary samples, and these bottles may be rinsed just three
times with sample water before collecting the sample.
Unfiltered samples are collected for analysis of SSC, particulate organic carbon,
total trace elements ( including mercury and methyl mercury) and total PCBs, PAHs, and
OC pesticides. Filtered samples are collected for analysis of dissolved trace elements
( including mercury and methyl mercury), dissolved nutrients, and dissolved organic
carbon ( DOC). Collection of filtered samples involves using a 0.45 μm filtration
cartridge attached to the sample tubing outlet and secured to sampler components.
Sample documentation and shipment
Labeling
A sample record is maintained for each sampling event. The sample record
contains the following information:
1. Site name
2. Collection date
3. Arrival and departure time at each station
4. Station coordinates ( latitude and longitude)
5. Water depth at time of sampling
6. A record of every sample bottle filled, with discrete bottle identification code number
and quantity of bottles
7. Collecting personnel’s names
8. Other remarks ( i. e. any conditions that could possibly influence sample analysis or
data interpretation, including present and past weather conditions)
The sample collection form, coupled with a chain of custody record and a
laboratory analysis record, allows tracing of the complete history of a sample from time
of collection to final entry of data to a computer database.
Sample storage and shipment to the laboratory
Water samples collected for analysis of trace metals ( including mercury and
methyl mercury), nutrients, DOC, POC, and SSC are maintained by UCSC personnel and
transported to the UCSC laboratory immediately following the sampling event. Nutrient
samples and mercury samples are frozen on dry ice and maintained frozen until they are
transferred to laboratory freezers. All other trace metal and related samples are stored in
sealed buckets at room temperature during the sampling event and transferred to the
laboratory at the conclusion of the event. Sample contamination is avoided by double
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bagging the sample containers, handling the containers with clean gloves, and
transferring the samples into sealed buckets/ coolers immediately after sampling.
Water samples collected for analysis of PCBs, PAHs, and OC pesticides are
maintained by SFEI staff during the sampling event and shipped to AXYS within 48
hours of collection. Sample bottles are stored and shipped in coolers using ice packs to
maintain a nominal temperature of 4 ± 2 ° C ( 39.2 ° F).
ANALYTICAL METHODS
Turbidity
Turbidity will be plotted and checked for outliers. In some cases, outliers can be
identified from experience and in other cases a corresponding SSC is required to
determine whether a spike is a valid rise in turbidity. Once the physical samples are
analyzed in the USGS water lab the SSC data will be forwarded to Redwood Sciences
Laboratory. The density and timing of SSC samples will determine both the validity of
the turbidity spikes and the goodness of the relationship of SSC and turbidity. A
regression of SSC versus turbidity will be done on an annual basis. This relationship will
then be used to estimate SSC from the nearly continuous record of turbidity. Once an
estimated SSC for each 15- minute record exists the load can be computed from the sum
of the product of each SSC and water discharge pair for any desired period. Redwood
Sciences Laboratory has developed analysis software for plotting, error correction, and
load estimates that operate on a UNIX platform running Splus.
Suspended sediments
There are two categories of laboratory measurement of suspended sediments in
water – total suspended solids ( TSS) and suspended sediments concentration ( SSC). The
method of analysis for TSS usually entailed filtration of a sub- sample of water, and then
drying and re- weighing the filter and retained sediment to produce a mass per unit
volume. The process of sub- sampling either in the field or in the laboratory has been
found to cause major analytical bias ( Gray et al., 2000). The method that shall be used in
the Guadalupe River study is the SSC method and the standard method of the USGS
( Guy, 1969) now designated ASTM standard test method D 3977- 97 ( Gray et al., 2000).
This method differs from the TSS method in that it does not allow for sub- sampling
either in the field or in the lab. This ensures that all particle sized in the sample are
represented in the final determination of concentration. Once suspended sediment
concentration is determined the daily loads record will be calculated using the methods
outlined in Porterfield ( 1972). These methods have been adopted by the USGS as the
standard methods for computation of the sediment record.
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Trace contaminants
Mercury and methyl mercury
Water samples are analyzed for mercury and methyl mercury by UCSC using cold
vapor atomic fluorescence spectrometry ( CVAFS). Total mercury is measured in
accordance with methods outlined in previously published studies ( Bloom and Crecelius,
1983; Bloom and Fitzgerald, 1988; Mason and Fitzgerald, 1990; USEPA, 1999). Methyl
mercury is separated from water samples using distillation techniques described in
Horvat et al. ( 1993). The distillate is analyzed for methyl mercury using direct ethylation
purge- and- trap techniques ( Bloom, 1989).
Trace metals
Water samples are analyzed for trace metals by UCSC using graphite furnace
atomic absorption spectroscopy ( GFAAS) or inductively coupled plasma- atomic
emission spectrometry ( ICP/ AES). Prior to analysis, samples are prepared with a near-total
extraction using an ammonium 1- pyrollidine dithiocarbonate/ diethylammonium
diethlydithiocarbonate ( APDC/ DDDC) procedure described by Bruland et al. ( 1985).
Trace organics
Water samples are analyzed for organic contaminants ( PCBs, PAHs, and OC
pesticides) by AXYS Analytical Services, LTD. PCBs and OC pesticides are measured in
accordance with EPA method 1668 revision A ( USEPA, 1999) using high resolution gas
chromotagraphy/ high resolution mass spectrometry ( HRGC/ HRMS). PAHs are measured
in accordance with a method comparable to EPA Method 8270 using gas
chromotography/ mass spectrometry ( GC/ MS).
Ancillary data
Water samples are analyzed for dissolved nutrients ( phosphate, silicate, nitrate,
nitrite, and ammonia), dissolved organic carbon ( DOC), and suspended sediment
concentrations ( SSC) by UCSC following methods outlined by Flegal et al. ( 1991).
Conventional water quality parameters ( conductivity, salinity, dissolved oxygen, pH, and
temperature) are measured onsite by UCSC using a Solomat ™ 520C multi- functional
chemistry and water quality monitor. This hand- held monitor has several probes, which
are submerged approximately 3 feet into the water column to collect readings. The meter
is calibrated for conductivity with a KCl standard, dissolved oxygen using a mixture of
CoCl2 and NaSO3 and for pH using buffers of pH 7 and 10.
SFEI draft for review – do not quote McKee and Leatherbarrow
28
REFERENCES
Abu- Saba, K. E. and L. W. Tang. 2000. Watershed management of mercury in the San
Francisco Bay Estuary: Total Maximum Daily Load Report to U. S. EPA.
California Regional Water Quality Control Board, San Francisco Bay region.
Oakland, CA.
Bloom, N. S. 1989. Determination of picogram levels of methylmercury by aqueous phase
ethylation, followed by cryogenic gas chomotography with cold vapour atomic
fluorescence detection. Canadian Journal of Fisheries and Aquatic Science. 46.
pp. 1131- 1140
Bloom, N. S and E. A. Crecelius. 1983. Determination of mercury in seawater at
subnanogram per liter levels. Marine Chemistry. 14. pp. 49- 59.
Bloom, N. S and W. F. Fitzgerald. 1988. Determination of volatile mercury species at the
pico- gram level by low- temperature gas chromatography with cold vapour atomic
fluorescence detection. Anal. Chim. Acta. 208. pp. 151- 161.
Bruland, K. H., K. H. Coale and L. Mart, 1985. Analysis of seawater for dissolved
cadmium, copper and lead: intercomparison of votammetric and atomic
absorption methods. Marine Chemistry. 17. pp. 285- 300.
David, N., D. Bell, and J. Gold. 2001. Field sampling manual for the Regional
Monitoring Program for Trace Substances. San Francisco Estuary Institute.
Oakland, CA. http:// www. sfei. org/ rmp/ documentation/ fom/ FOM2001. pdf
Davis, J. A., McKee, L. J., Leatherbarrow, J. E., and Daum, T. H., 2000. Contaminant loads
from stormwater to coastal waters in the San Francisco Bay region: Comparison
to other pathways and recommended approach for future evaluation. San
Francisco Estuary Institute, September 2000. 77pp.
Davis, J. A. 2002. The long term fate of PCBs in San Francisco Bay. San Francisco
Estuary Institute, Oakland, CA.
Eads, Rand. 2002. Continuous turbidity monitoring in streams of northwest California.
In Workshop on turbidity and other sediment surrogates, Apr 29- Mar2, 2002,
Reno, Nevada.
Eads, Rand and Lewis, Jack, and. 2001. Turbidity threshold sampling: methods and
instrumentation. In: Proceedings, 7th Federal Interagency Sedimentation
Conference, 25- 29 Mar 2001, Reno Nevada.
Eads, Rand E. and Thomas Robert B. 1983. Evaluation of a depth proportional intake
device for automatic pumping samplers. Water Resources Bulletin, Report No.
82094, April 1983.
Edwards T. K., and G. D. Glysson. 1999. Field methods for measurement of fluvial
sediment. Techniques of Water- Resources Investigations of the U. S. Geological
Survey: Book 3, Applications of Hydraulics.
http:// water. usgs. gov/ pubs/ twri/ twri3- c2/ pdf/ TWRI_ 3- C2. pdf
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FISP. 2002. Operating instructions for the US D- 96 depth- integrating collapsible bag
suspended- sediment sampler. Federal Interagency Sedimentation Project.
Vicksburg, MS. http:// fisp. wes. army. mil/ Operators_ Manual_ US_ D-
96_ 020709. pdf
Gray, J. R., Glysson, G. D., Turcios, L. M., and Schwarz, G. E., 2000. Comparitibility of
suspended- sediment concentration and total suspended solids data. USGS Water
Resources Investigations Report 00- 4191. United States Geological Survey,
Reston, Virginia.
Guy, H. P., 1969. Laboratory theory and methods for sediment analysis. Techniques of
Water- Resources Investigations of the U. S. Geological Survey: Book 3,
Applications of Hydraulics.
Horvat M., L. Liang, N. S. Bloom. 1993. Comparison of distillation with other current
isolation methods for the determination of methyl mercury compounds in low
level environmental samples. Anal. Chim. Acta. 282. pp. 53- 68.
KLI, 2002. Administrative Draft: Joint stormwater agency project to study urban sources
of mercury, PCBs, and organochlorine pesticides. Report prepared by Kinnetic
Laboratories, Inc. for Santa Clara Valley Urban Runoff Pollution Prevention
Program, Contra Costa Clean Water Program, San Mateo Countywide
Stormwater Pollution Prevention Program, Marin County Stormwater Pollution
Prevention Program, Vallejo Flood Control and Sanitation District, Fairfield-
Suisun Sewer District. 71pp.
Leatherbarrow, J. E., R. Hoenicke, and L. J. McKee. 2002. Results of the Estuary Interface
Pilot Study, 1996- 1999. A technical report of the RMP Sources Pathways and
Loadings Workgroup. San Francisco Estuary Regional Monitoring Program for
Trace Substances. San Francisco Estuary Institute. Oakland, CA.
Lewis, Jack, and Eads, Rand. 2001. Turbidity threshold sampling for suspended sediment
load estimation. In: Proceedings, 7th Federal Interagency Sedimentation
Conference, 25- 29 Mar 2001, Reno Nevada.
Lewis, Jack, and Eads, Rand. 1996. Turbidity- controlled suspended sediment sampling.
Watershed Management Council Networker, Vol. 6, Number 4, Summer 1996.
Mason, R. P. and W. F. Fitzgerald. 1990 Alkylmercury species in the equatorial Pacific.
Nature. 347. pp. 457- 459.
MTC. 2002. TEA 21: A proven record of success. California reaches consensus on TEA
21 reauthorization. Metropolitan Transportation Commission 23rd Annual Report
to Congress, March 2002.
http:// www. mtc. ca. gov/ publications/ leg_ reports/ Fed2002/ santaclara. pdf
MTC and ABAG. 2002. Selected census 2000 data for the San Francisco Bay Area.
Provided by the Metropolitan Transportation Commission ( MTC) and the
Association of Bay Area Governments ( ABAG).
http:// census. abag. ca. gov/ index. html
Porterfield, G., 1972. Computation of fluvial- sediment discharge. Techniques of Water-
Resources Investigations of the U. S. Geological Survey: Book 3, Applications of
Hydraulics.
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SCBWMI. 2000. Watershed characteristics report. Watershed Management Report
Volume 1. Santa Clara Basin Watershed Management Initiative. C/ O City of San
Jose. San Jose, CA. 139pp.
SCDF. 2001. Interim county population projections. State of California, Department of
Finance. Sacramento, CA. http:// www. dof. ca. gov/ HTML/ DEMOGRAP/ P1. doc
SVTC. 2002. SVTC toxic chemical point sources. Silicon Valley Toxics Coalition. San
Jose, CA. http:// www. svtc. org/ ecomaps/ svtc_ mult/
USEPA. 1996. Method 1669. Sampling ambient water for trace metals at EPA water
quality criteria levels. United States Environmental Protection Agency. EPA No.
EPA- 821- R- 96- 011.
USEPA. 1999. Method 1668, Revision A: Chlorinated biphenyl congeners in water, soil,
sediment, and tissue by HRGC/ HRMS. United States Environmental Protection
Agency. EPA No. EPA- 821- R- 00- 002.
http:// www. state. nj. us/ drbc/ EPA1668a5. pdf
USEPA. 1999. Method 1631, Revision B: Mercury in water by oxidation, purge and trap,
and cold vapor atomic fluorescence spectrometry. United States Environmental
Protection Agency. EPA No. EPA- 821- R- 99- 005.
http:// www. epa. gov/ waterscience/ methods/ 1631final. pdf
Yee, D., S. Lowe, J. A. Davis, R. Hoenicke, and G. Scelfo. 2001. 2001 Quality Assurance
Project Plan. Regional Monitoring Program for Trace Substances. San Francisco
Estuary Institute. Oakland, CA.
http:// www. sfei. org/ rmp/ reports/ 2001_ QAPP_ v2. PDF
SFEI draft for review – do not quote McKee and Leatherbarrow
31
APPENDIX
Table A. Quality control criteria for analysis of organic compounds.
QA SAMPLE
QA MEASURE
MINIMUM
FREQUENCY
CRITERIA
CORRECTIVE ACTION
Method Blank Contamination by
reagents,
laboratory ware,
etc.
One per batch < MDL or
< 10% of lowest sample
Identify and eliminate
contamination source.
Reanalyze all samples in
batch.
Qualify data as needed.
Instrument Blank Cross
contamination
NA Set by laboratory NA
Certified Reference Material
( CRM)
Accuracy NA NA NA
Replicates:
( analytical and/ or laboratory)
Applies to replicates of field
samples, CRMs, matrix spike
samples, etc.
Precision
Instrument and/ or
overall
reproducibility of
a result.
One per batch RPD or RSD
< 35%
Check calculations and
instruments. Recalibrate and
reanalyze.
If problem persists, identify
and eliminate source of
imprecision and reanalyze.
Matrix Spike Accuracy 1 per 20 field
samples
Recovery > 50% Check CRM or LCS
recovery.
Review chromatograms and
raw data quantitation
reports.
Check instrument response
using calibration standard.
Attempt to correct matrix
problem and reanalyze
sample.
Qualify data as needed.
Surrogate Spike % Recovery
used to
adjust sample
results
One per sample Set by analyzing
laboratory
( Report surrogate
recovery and acceptance
criteria in final report)
Check CRM or LCS
recovery.
Attempt to correct matrix
problem and reanalyze
sample.
Qualify data as needed
Continuing Calibration
Check solutions
Accuracy
&
Precision
At least every 12
hours
Known values for 90%
of analytes shall not
deviate more than ±
25% for PAHs, and ±
20% for PCBs and
Pesticides.
Beginning with last sample
before failure, recalibrate
and reanalyze.
Compare RPD and
reanalyze.
MDL = method detection limit; RPD = relative percent difference; RSD = relative standard deviation ( see
page24 for equations)
SFEI draft for review – do not quote McKee and Leatherbarrow
32
Table B. Quality control criteria for analysis of trace elements.
QA SAMPLE
QA MEASURE
MINIMUM
FREQUENCY
CRITERIA
CORRECTIVE ACTION
Method Blank Contamination by
reagents, laboratory
ware, etc.
One per batch < MDL or
< 10% of lowest
sample
Identify and eliminate
contamination source.
Reanalyze all samples in
batch.
Qualify data as needed.
Certified Reference
Material ( CRM)
Accuracy 1 per 20 field
samples
Within 20– 25% of
the certified 95%
confidence interval
Review raw data
quanitation reports.
Check instrument response
using calibration standard.
Recalibrate and reanalyze
CRM and samples.
Repeat analysis until control
limits are met.
Replicates:
( analytical and/ or laboratory)
Applies to replicates of field
samples, CRMs, matrix
spike samples, etc.
Precision One per batch RPD or RSD
< 15%;
Hg, As, Se < 25%
RSD of last 7 CRMs
< 35%
Check calculations and
instruments. Recalibrate
and reanalyze.
If problem persists, then
identify and eliminate
source of imprecision and
reanalyze.
Matrix Spike Accuracy 1 per 20 field
samples
Recovery > 50% Check CRM or LCS
recovery.
Review raw data
quantitation reports.
Check instrument response
using calibration standard.
Attempt to correct matrix
problem and reanalyze
sample.
Qualify data as needed.
Laboratory Control
Material ( LCM; optional)
Accuracy,
Laboratory precision
1 per 20 field
samples
Within 20– 25% of
consensus value
Review raw data
quanitation reports.
Check instrument response
using calibration standard.
Recalibrate and reanalyze
LCM and samples.
Repeat analysis until control
limits are met.
MDL = method detection limit; RPD = relative percent difference; RSD = relative standard deviation
SFEI draft for review – do not quote McKee and Leatherbarrow
33
Table C. Quality control criteria for analysis of cognates.
QA SAMPLE
QA MEASURE
MINIMUM
FREQUENCY
CRITERIA
CORRECTIVE ACTION
Toxicity
Ammonia, nitrate, nitrite, phosphate, silicate, chlorophyll a, TSS
Method Blank Contamination by
reagents, laboratory
ware, etc.
One per batch < MDL or
< 10% of lowest
sample
Identify and eliminate
contamination source.
Reanalyze all samples in
batch.
Qualify data as needed.
Certified Reference
Material ( CRM)
Accuracy Once per sample
set.
NA for chlorophyll
a or TSS
NA NA
Replicates:
( analytical and / or laboratory)
Applies to replicates, CRMs,
matrix spike samples, etc.
Precision One per batch.
NA for TSS
RPD or RSD
< 5%
Check calculations and
instruments. Recalibrate
and reanalyze.
If problem persists, then
identify and eliminate
source of imprecision and
reanalyze.
Matrix Spike Accuracy 1 per 20 field
samples
Recovery > 50% Review data reports and
chromatographs.
Check instruments.
DOC ( Dissolved Organic Carbon)
Method Blank Contamination One per batch < MDL or
< 10% of lowest
sample
Reanalyze samples
Certified Reference
Material ( CRM)
Accuracy Once per sample
set
RPD < 5% Recalibrate and reanalyze
Replicates Precision One per batch RPD or RSD
< 5%
Check calculations and
instruments. Recalibrate
and reanalyze.
If problem persists, then
identify and eliminate
source of imprecision and
reanalyze.
MDL = method detection limit; RPD = relative percent difference; RSD = relative standard deviation