Summary of Suspended-Sediment 

Concentration Data, San Francisco Bay, 

California, Water Year 2005

By Paul A. Buchanan and Megan A. Lionberger

Prepared in cooperation with the CALFED Bay–Delta Authority and the 

U.S. Army Corps of Engineers, San Francisco District

Data Series 282

U.S. Department of the Interior

U.S. Geological Survey
U.S. Department of the Interior

Dirk Kempthorne, Secretary

U.S. Geological Survey

Mark D. Myers, Director

U.S. Geological Survey, Reston, Virginia: 2007

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reproduce any copyrighted materials contained within this report.

Suggested citation:

Buchanan, P.A., and Lionberger, M.A., 2007, Summary of Suspended-Sediment Concentration Data, San Francisco Bay, California, Water 

Year 2005: U.S. Geological Survey Data Series 282, 46 p.
iii

Contents

Abstract...........................................................................................................................................................1

Introduction.....................................................................................................................................................1

Purpose and Scope ..............................................................................................................................1

Study Area..............................................................................................................................................2

Acknowledgments................................................................................................................................2

Methods...........................................................................................................................................................2

Instrument Description and Operation..............................................................................................2

Establishment of Monitoring Sites.....................................................................................................5

Suisun Bay Installations .............................................................................................................5

San Pablo Bay Installations .......................................................................................................6

Central San Francisco Bay Installations..................................................................................6

South San Francisco Bay Installations ....................................................................................6

Water-Sample Collection.....................................................................................................................6

Data Processing....................................................................................................................................7

Sensor Calibration and Suspended-Sediment Concentration Data......................................................8

Suisun Bay ...........................................................................................................................................11

Mallard Island.............................................................................................................................11

Benicia Bridge............................................................................................................................13

San Pablo Bay .....................................................................................................................................17

Carquinez Bridge .......................................................................................................................17

Mare Island Causeway.............................................................................................................20

Channel Marker 1.......................................................................................................................24

Central San Francisco Bay................................................................................................................27

Point San Pablo..........................................................................................................................27

Alcatraz Island............................................................................................................................30

South San Francisco Bay ..................................................................................................................33

San Mateo Bridge......................................................................................................................33

Dumbarton Bridge .....................................................................................................................36

Channel Marker 17.....................................................................................................................40

Summary........................................................................................................................................................44

References Cited..........................................................................................................................................44
iv

Figures

Figure 1. Map showing San Francisco Bay study area, California .............................. 3

Figure 2. Schematic showing typical monitoring installation, San Francisco Bay study ...... 4

Figure 3. Graphs showing example of raw and processed optical data, mid-depth sensor, 

Mare Island Causeway, San Pablo Bay, California, water year 2005.................. 7

Figure 4. Graphs showing calibration of near-surface and near-bottom optical sensors 

at Mallard Island, Suisun Bay, California, water year 2005 ........................... 10

Figure 5. Graphs showing time series of near-surface and near-bottom suspendedsediment concentrations calculated from sensor readings at Mallard Island, 

Suisun Bay, California, water year 2005 ................................................ 12

Figure 6. Graph showing calibration of near-surface optical sensor at Benicia Bridge, 

Suisun Bay, California, water year 2005 ................................................ 14

Figure 7. Graphs showing calibration of near-bottom optical sensors, October 1–November 23 

and November 23–September 30 at Benicia Bridge, Suisun Bay, California, 

water year 2005 ........................................................................... 15

Figure 8. Graphs showing time series of near-surface and near-bottom suspendedsediment concentrations calculated from sensor readings at Benicia Bridge, 

Suisun Bay, California, water year 2005 ................................................ 16

Figure 9. Graphs showing calibration of mid-depth and near-bottom optical sensors at 

Carquinez Bridge, San Pablo Bay, California, water year 2005 ........................ 18

Figure 10. Graphs showing time series of mid-depth and near-bottom suspendedsediment concentrations calculated from sensor readings at Carquinez Bridge, 

San Pablo Bay, California, water year 2005 ............................................. 19

Figure 11. Graph showing calibration of mid-depth optical sensor at Mare Island 

Causeway, San Pablo Bay, California, water year 2005................................. 21

Figure 12. Graphs showing calibrations of near-bottom optical sensors, October 1–

March 29 and March 29–September 30 at Mare Island Causeway, San Pablo Bay, 

California, water year 2005 ............................................................... 22

Figure 13. Graphs showing time series of mid-depth and near-bottom suspendedsediment concentrations calculated from sensor readings at Mare Island 

Causeway, San Pablo Bay, California, water year 2005................................. 23

Figure 14. Graph showing calibration of mid-depth optical sensor at Channel Marker 1, 

San Pablo Bay, California, water year 2005 ............................................. 25

Figure 15. Graph showing time series of mid-depth suspended-sediment concentrations 

calculated from sensor readings at Channel Marker 1, San Pablo Bay, California, 

water year 2005 .............................................................................. 26

Figure 16. Graphs showing calibration of mid-depth and near-bottom optical sensors at 

Point San Pablo, Central San Francisco Bay, California, water year 2005............ 28

Figure 17. Graphs showing time series of mid-depth and near-bottom suspendedsediment concentrations calculated from sensor readings at Point San Pablo, 

Central San Francisco Bay, California, water year 2005 .............................. 29

Figure 18. Graph showing calibration of mid-depth optical sensor at Alcatraz Island, 

Central San Francisco Bay, California, water year 2005 .............................. 31

Figure 19. Graph showing time series of mid-depth suspended-sediment concentrations 

calculated from sensor readings at Alcatraz Island, Central San Francisco Bay, 

California, water year 2005 ............................................................... 32

Figure 20. Graphs showing calibration of mid-depth and near-bottom optical sensors at 

San Mateo Bridge, South San Francisco Bay, California, water year 2005 ......... 34
Figure 21. Graphs showing time series of mid-depth and near-bottom suspendedsediment concentrations calculated from sensor readings at San Mateo Bridge, 

South San Francisco Bay, California, water year 2005 ................................. 35

Figure 22. Graphs showing calibration of mid-depth optical sensors, October 1–July 28 

and July 28 –September 30 at Dumbarton Bridge, South San Francisco Bay, 

California, water year 2005 ............................................................... 37

Figure 23. Graphs showing calibration of near-bottom optical sensors, October 1–March 30, 

March 30–July 28 and July 28 –September 30 at Dumbarton Bridge, South 

San Francisco Bay, California, water year 2005 ....................................... 38

Figure 24. Graphs showing time series of mid-depth and near-bottom suspendedsediment concentrations calculated from sensor readings at Dumbarton Bridge, 

South San Francisco Bay, California, water year 2005 ................................. 39

Figure 25. Graphs showing calibration of mid-depth optical sensors, October 13–April 20 

and April 20–September 30 at Channel Marker 17, South San Francisco Bay, 

California, water year 2005 ............................................................... 41

Figure 26. Graphs showing calibration of near-bottom optical sensors, October 1–

March 30 and April 20 –September 30 at Channel Marker 17, South San Francisco 

Bay, California, water year 2005 ......................................................... 42

Figure 27. Graphs showing time series of mid-depth and near-bottom suspendedsediment concentrations calculated from sensor readings at Channel Marker 17, 

South San Francisco Bay, California, water year 2005 ................................. 43

Tables

Table 1. Optical sensor depths (in feet) below mean lower low water (MLLW), Suisun Bay, 

San Pablo Bay, and Central and South San Francisco Bays, California, 

water year 2005 .............................................................................. 5

 Table 2. Statistical summary of calculated suspended-sediment concentration data and 

usable percentage of a complete year of valid data (96 data points per day x 365 

days) collected using optical sensors, Suisun Bay, San Pablo Bay, and Central 

and South San Francisco Bays, California, water year 2005 ........................... 9
vi

Conversion Factors, Datum, Abbreviations, and Acronyms

Multiply By To obtain

inch (in.) 25.40 millimeter

foot (ft) .3048 meter

foot per second (ft/s) .3048 meter per second

Vertical coordinate information is referenced to the North American Vertical Datum of 1988 

(NAVD 88); horizontal coordinate information is referenced to the North American Datum of 

1927 (NAD 27).

Concentrations of chemical constituents in water are given in milligrams per liter (mg/L).

Mean lower low water (MLLW): The average of the lower low water height above the bottom, 

in feet, of each tidal day observed during the National Tidal Datum Epoch. The National Tidal 

Datum Epoch is the specific 19-year period (1960–1978 for values given in this report) adopted 

by the National Ocean Service as the official time segment during which tide observations are 

taken and reduced to obtain mean values.

Abbreviations and Acronyms

ADAPS automated data-processing system

DWR California Department of Water Resources

mV millivolt

FTS Forest Technology Systems

NTU nephelometric turbidity units

PInp nonparametric prediction interval

PVC polyvinyl chloride

RMS root-mean-squared (error)

SSC suspended-sediment concentration

USCG U.S. Coast Guard

USGS U.S. Geological Survey

WY water year (October 1–September 30)
Summary of Suspended-Sediment Concentration Data, 

San Francisco Bay, California, Water Year 2005

By Paul A. Buchanan and Megan A. Lionberger

Abstract

Suspended-sediment concentration data were collected by the U.S. Geological Survey in San Francisco Bay during water 

year 2005 (October 1, 2004–September 30, 2005). Optical sensors and water samples were used to monitor suspended-sediment 

concentration at two sites in Suisun Bay, three sites in San Pablo Bay, two sites in Central San Francisco Bay, and three sites in 

South San Francisco Bay. Sensors were positioned at two depths at most sites. Water samples were collected periodically and 

analyzed for concentrations of suspended sediment. The results of the analyses were used to calibrate the output of the optical 

sensors so that a record of suspended-sediment concentrations could be derived. This report presents the data-collection methods 

used and summarizes, in graphs, the suspended-sediment concentration data collected from October 2004 through September 

2005. Calibration curves and plots of the processed data for each sensor also are presented.

Introduction

Sediments are an important component of the San Francisco Bay estuarine system. Bottom sediments provide habitat for 

benthic organisms and are a reservoir for nutrients that contribute to estuarine productivity (Hammond and others, 1985). Potentially toxic substances, such as metals and pesticides, can adsorb to sediment particles (Kuwabara and others, 1989; Domagalski 

and Kuivila, 1993; Flegal and others, 1996). Benthic organisms can then ingest these substances and introduce them into the 

food web (Luoma and others, 1985; Brown and Luoma, 1995; Luoma, 1996). Large tidal-induced current velocities and wind 

waves in shallow water are capable of resuspending bottom sedi­ments (Powell and others, 1989; Schoellhamer, 1996).

The mobilization, resuspension and deposition of suspended sediments are important factors in determining the transport 

and fate of sediment-associated contaminants. In Suisun Bay, the maximum suspended-sediment concentration (SSC) typically 

marks the position of the turbidity maxi­mum—a crucial ecological zone where suspended sediments, nutrients, phytoplankton, 

zooplankton, larvae, and juvenile fish accumulate (Peterson and others, 1975; Arthur and Ball, 1979; Kimmerer, 1992; Jassby 

and Powell, 1994; Schoellhamer and Burau, 1998; Schoellhamer, 2001).

Suspended sediments limit the penetration of light into San Francisco Bay, which affects photosynthesis and primary phytosynthetic carbon production (Cole and Cloern, 1987; Cloern, 1987, 1996). Sediments also are deposited in ports and shipping 

channels, which then require dredging in order to remain navigable (U.S. Environmental Protection Agency, 1992). The U.S. 

Geological Survey (USGS), in cooperation with the CALFED Bay-Delta Authority, and the U.S. Army Corps of Engineers, is 

studying the factors that affect SSC in San Fran­cisco Bay.

Purpose and Scope

This report summarizes SSC data collected by the USGS in San Francisco Bay dur­ing water year (WY) 2005 and is the 

latest in a series of reports that present the data collected beginning in WY 1992 (Buchanan and Schoellhamer, 1995, 1996, 

1998, 1999; Buchanan and oth­ers, 1996; Buchanan and Ruhl, 2000, 2001; Buchanan and Ganju, 2002, 2003, 2004, 2005; and 

Buchanan and Lionberger, 2006). Collection of SSC data in San Francisco Bay required development of monitoring meth­ods 

and calibration techniques that are presented in this report. SSC were monitored at two sites in Suisun Bay, three sites in San 

Pablo Bay, two sites in Central San Francisco Bay, and three sites in South San Francisco Bay. SSC data from WY 1992 through 

WY 2005 were used to help determine the factors that affect SSC in San Francisco Bay (Schoellhamer and others, 2003; for the 

current bibliography of reports see U.S. Geological Survey, accessed February 26, 2007). Numerical SSC data for WY 1992 

through 2005 are available from the U.S. Geological Survey (accessed February 26, 2007).
Study Area

San Francisco Bay (fig. 1) comprises several major subembayments: Suisun Bay, San Pablo Bay, Central San Francisco 

Bay (Central Bay), and South San Francisco Bay (South Bay). In San Francisco Bay, tides are semidiurnal (two high and two 

low tides per day) and have a range of about 5.5 feet (ft) in Suisun Bay, 6.5 ft at the Golden Gate and Central Bay, and about 

10 ft in South Bay. The tides also follow a 14-day spring-neap cycle. Typ­ical tidal currents range from 0.6 foot per second (ft/s) 

in shallow water to more than 3 ft/s in deep channels (Cheng and Gartner, 1984; Smith, 1987). The strongest winds typically are 

sea breezes that blow onshore during summer afternoons. Most precipitation occurs from late autumn to early spring. Freshwater 

discharge into San Francisco Bay is greatest in the spring as a result of runoff from snowmelt. About 90 percent of the discharge 

into the Bay is from the Sacramento-San Joaquin River Delta, which drains the Central Valley of Cali­fornia (Smith, 1987).

Typically, discharge from the Delta contains about 60 percent of the fluvial sediments that enter the Bay (McKee and 

others, 2006), though this percentage varies from year to year. During wet winters, turbid plumes of water from the Delta have 

extended into South Bay (Carlson and McCulloch, 1974). The bottom sediments in South Bay and in the shal­low water areas 

(about 12 ft or less) of Central, San Pablo, and Suisun Bays are composed mostly of silts and clays. Silts and sands are present in 

the deeper parts of Central, San Pablo, and Suisun Bays and in Carquinez Strait (Conomos and Peterson, 1977).

Acknowledgments

The authors gratefully acknowledge Gregory Brewster, Brad Sullivan and Heather Ramil of the USGS for their assistance 

with sample collection and maintenance of the data-collection network. The authors also wish to acknowledge the U.S. Coast 

Guard (USCG), the National Park Service, California Depart­ment of Transportation, California Department of Water Resources 

(DWR), EAI Interna­tional, and the City of Vallejo for their permission and assistance in establishing the monitoring sites used in 

this study.

The project was done in cooperation with the CALFED Bay–Delta Authority, and the U.S. Army Corps of Engineers, as 

part of the San Francisco Estuary Regional Monitoring Program for Trace Substances. Additional funding was supplied by the 

USGS Priority Ecosystem Science Program.

Methods

Instrument Description and Operation

Three different types of optical sensors were used to monitor SSC during WY 2005. The first type of sensor is manufactured by D & A Instrument Company and is a cylinder approximately 7 inches (in.) long and 1 in. in diameter with an optical 

window at one end, a cable connection at the other end, and an encased circuit board. A high-intensity infrared-emitting diode 

produces a beam through the optical window that is scattered, or reflected, by particles that are about 0.2–12 in. in front of the 

window. A detector (four photodiodes) receives backscatter from a field of 140–165 degrees which is converted to a voltage 

output and recorded on a separate data logger. The sec­ond type of sensor, manufactured by Forest Technology Systems (FTS), 

is self-cleaning and differs from the D & A Instrument Company sensor in that it measures the intensity of light scattered at 90 

degrees between a laser diode and a high-sensitivity silicon photodiode detector. The output, in nephelometric turbidity units 

(NTU), is recorded on a separate data logger. The third type of sensor, versions of which are used by both Hydrolab and YSI 

instruments, mea­sures the intensity of light scattered at 90 degrees between a light-emitting diode and a high-sensitivity photodiode detector, and the output (NTU) is processed by internal software. The Hydrolab and YSI instruments (sondes) are self-contained, including a power source, data logger, and the capability of supporting additional sensors.

Optical sensors were positioned in the water column by using polyvinyl chloride (PVC) pipe carriages coated with an 

antifoulant paint to impede biological growth. Car­riages were designed to align with the direction of flow and to ride along a 

stainless steel suspension line attached to an anchor weight, which allowed sensors to be easily raised and lowered for servicing 

(fig. 2). The plane of the optical window maintained a position parallel to the direction of flow as the carriage aligned itself with 

the changing direction of flow. Optical sensor depths in the water column are listed in table 1.

Biological growth (fouling) interferes with the collection of accurate optical-sensor data. Fouling generally was greatest on 

the sensor closest to the water sur­face; however, at shallower sites where the upper sensor was set 10 ft above the lower sensor, 

fouling was similar on both sensors. Self-cleaning optical sensors were used where conditions allowed. Because of the difficulty 

in servicing some of the monitoring stations, sensors were cleaned manually every 1–5 (usually 3) weeks. Fouling would begin 

to affect sensor output from 2 days to several weeks after cleaning, depending on the level of biological activity in the bay. 

Generally, biological fouling was greatest during spring and summer.

   Summary of Suspended-Sediment Concentration Data, San Francisco Bay, California, Water Year 2005
Figure 1. San Francisco Bay study area, California.

Suisun Bay

Carquinez Strait

San Pablo Bay

 Central

 San Francisco

 Bay

P a c i

f i c O c e a

n

0 5

0 5 10 Miles

10 Kilometers

EXPLANATION

Continuous suspended-sediment 

concentration monitoring site

San Mateo Discontinued monitoring site Bridge

Golden Gate

 Bridge Bay

 Bridge 

San Pablo Strait

122 30' 122 15' 122 00'

38 00'

37 45'

37 30'

Napa River

Richmond/San Rafael

 Bridge

CENTRAL VALLEY

C A L I F O R N I A

San Francisco Bay/

Sacramento-San Joaquin

River Delta

STUDY

 AREA

Petaluma

River

Dumbarton Bridge

Channel Marker 17

Mallard Island

Point San Pablo

Pier 24

 Benicia

Carquinez Bridge

 Bridge

Mare Island

 Causeway

Channel

Marker 1

South

San Francisco

Bay

Martinez

° ° °

°

°

°

Alcatraz

Island

Channel

Marker 9

Methods 
Figure 2. Typical monitoring installation, San Francisco Bay study. 

Instrument

Shelter Davit

Sensor cable

Suspension line

Mid-depth sensor

and carriage

Near-bottom sensor

and carriage

Weight

Sensor

head

SENSOR CARRIAGE

(Schematic not to scale) 

(Not to scale)

 Summary of Suspended-Sediment Concentration Data, San Francisco Bay, California, Water Year 2005
Table 1. Optical sensor depths (in feet) below mean lower low water (MLLW), Suisun Bay, San Pablo Bay, and Central and 

South San Francisco Bays, California, water year 2005.

[For definition of MLLW, see Conversion Factors, Datum, Abbreviations, and Acronyms entry at front of this report]

Site Station No. Latitude Longitude Sensor

depth

Depth below

MLLW1

Water depth 

at

MLLW

Mallard Island 11185185 38°02 ́34 ̋ 121°55 ́09 ̋ Near-surface 3.3 25

Near-bottom 20

Benicia Bridge 11455780 38°02 ́42 ̋ 122°07 ́32 ̋ Near-surface 9 80

Near-bottom 61

Carquinez Bridge 11455820 38°03 ́41 ̋ 122°13 ́53 ̋ Mid-depth 40 88

Near-bottom 83

Mare Island Causeway 11458370 38°06 ́40 ̋ 122°16 ́25 ̋ Mid-depth 3 30

Near-bottom 25

Channel Marker 1 380240122255701 38°02 ́40 ̋ 122°25 ́57 ̋ Mid-depth 2 8

Point San Pablo 11181360 37°07 ́53 ̋ 122°42 ́42 ̋ Mid-depth 8 26

Near-bottom 23

Alcatraz Island 374938122251801 37°49 ́38 ̋ 122°25 ́18 ̋ Mid-depth 6 16

San Mateo Bridge 11162765 37°35 ́04 ̋ 122°14 ́59 ̋ Mid-depth 19 48

Near-bottom 40

Dumbarton Bridge 373015122071000 37°30 ́15 ̋ 122°07 ́10 ̋ Mid-depth 20 45

Near-bottom 41

Channel Marker 17 372844122043800 37°28 ́44 ̋ 122°04 ́38 ̋ Mid-depth 11 25

Near-bottom 21

1

Depth below water surface.

On-site checks of sensor accuracy were performed using turbidity solutions pre­pared from a 4,000-NTU formazin standard. 

Formazin is an aque­ous suspension of an insoluble polymer and is the primary turbidity standard (Greenberg and others, 1992). 

The turbidity solutions were prepared by diluting a 4,000-NTU stock standard with de-ionized water in a clean, sealable container. Pre­pared solutions ranged from 20 to 180 NTU. Pre­pared solutions were checked with a Hach Drel 2000 Spectrophotometer for accuracy. At the field site, the cleaned sensors were immersed in the solution and the output was recorded on the station 

log. Monitor­ing a period of sensor performance in a known standard helps to identify output drift or sensor malfunction.

Data acquisition was controlled by electronic data loggers. The logger used with the D & A Instrument Company sensor 

was pro­grammed to power the optical sensor every 15 minutes, collect data each second for 1 minute, then average and store the 

output voltage for that 1-minute period. The Hydrolab, YSI and FTS data loggers collect instantaneous values every 15 minutes. 

Power was supplied by 12-volt batteries.

Establishment of Monitoring Sites

Suisun Bay Installations

SSC data were collected in Suisun Bay at Mallard Island and at Benicia Bridge (fig. 1, table 1). Optical sensors were 

installed at the DWR Mallard Island Compliance Monitoring Station on February 8, 1994. Optical sensors were positioned to 

coincide with DWR near-bottom electrical conductance and temperature sensors and the near-surface pump intake. The pump 

intake is attached to a float and draws water from about 3 ft below the surface. The near-surface optical sensor is attached to a 

separate float and positioned at the same depth as the pump intake.

Optical sensors were installed at Pier 7 on the Benicia Bridge on March 15, 1996. The Beni­cia Bridge site was shut down 

August 7, 1998, for seismic retrofitting of the bridge and was reestablished with sondes equiped with optical, conductance, 

and temperature sensors on May 1, 2001. A monitoring site at the Martinez Marina fishing pier was discontinued in WY 1996 

because data from the Benicia Bridge site were considered more representative of SSC in the Carquinez Strait area of Suisun 

Bay (Buchanan and Schoellhamer, 1998).

Methods   
San Pablo Bay Installations

SSC data were collected in Carquinez Strait at Carquinez Bridge, Napa River at Mare Island Causeway, and San Pablo Bay 

at Channel Marker 1 (fig. 1, table 1). Sondes with optical, conductance, and temperature sensors were installed at the center pier 

structure at Carquinez Bridge on April 21, 1998. Optical sensors were installed off a catwalk beneath Mare Island Causeway 

on October 1, 1998. A sonde with optical, con­ductance, and temperature sensors was installed at USCG Channel Marker 1 on 

October 7, 2003. A monitoring site at USCG Channel Marker 9 was discontinued in WY 2003 because data from the USCG 

Channel Marker 1 site were considered less affected by the processes that occur at the mouth of the Petaluma River (Ganju and 

others, 2004).

Central San Francisco Bay Installations

SSC data were collected in San Pablo Strait at Point San Pablo and San Francisco Bay at Alcatraz Island (fig. 1, table 1). 

Optical sensors were installed in San Pablo Strait at the northern end of the Richmond Terminal no. 4 pier on the western side 

of Point San Pablo on December 1, 1992. The station at Point San Pablo was shut down on January 2, 2001, and reestablished 

on December 11, 2001, at a pier-adjacent structure approximately 25 ft from the previ­ous deployment site. A sonde with optical, 

con­ductance, and temperature sensors was installed on the northeast side of Alcatraz Island on November 6, 2003. A monitoring station at San Francisco Bay at Pier 24 was discon­tinued on January 3, 2002. The USGS assumed operation of the stations at 

Point San Pablo and Pier 24 from DWR in October 1989, although the collection of conductivity and temperature data continued to be cooperatively funded by DWR and the USGS. A monitoring station at the south tower of the Golden Gate Bridge was 

operational during water years 1996 and 1997. Conductivity and tem­perature data collected at Point San Pablo and Pier 24 prior 

to October 1, 1989, can be obtained from DWR.

South San Francisco Bay Installations

SSC data were collected in South San Francisco Bay at San Mateo Bridge, Dumb­arton Bridge, and USCG Channel Marker 

17 (fig. 1, table 1). Optical sensors were installed at Pier 20 on the San Mateo Bridge, on the east side of the ship channel, on 

December 23, 1991. In addition to SSC, specific conductance and tempera­ture were monitored at near-bottom and near-surface 

depths at San Mateo Bridge. The USGS assumed operation of this station from DWR in October 1989, although the collection 

of specific conductance and temperature data continued to be cooperatively funded by DWR and USGS. Specific conductance 

and temperature data collected at San Mateo Bridge prior to October 1, 1989, can be obtained from DWR. Optical sensors were 

installed at Pier 23 on the Dumbarton Bridge on the west side of the ship channel on October 21, 1992. Optical sensors were 

installed at USCG Channel Marker 17 on February 26, 1992.

Water-Sample Collection

Water samples, used to calibrate the output of the optical sensors to SSC, were collected by using a horizontally positioned 

Van Dorn sampler before and after the sen­sors were cleaned. The Van Dorn sampler is a plastic tube with rubber stoppers at 

each end that snap shut when triggered by a small weight dropped down a suspension cable. The Van Dorn sampler was lowered 

to the depth of the sensor by a reel and crane assembly and trig­gered while the sensor was collecting data. After collection, the 

water sample was marked for identification and placed in a clean, 1-liter plastic bottle for transport. The SSC of water samples 

collected with a Van Dorn sampler and a P-72 point sampler, used until WY 1994, were virtually identical (Buchanan and others, 1996).

Samples were sent to the USGS Sediment Laboratory in Marina, California, for analysis of SSC. Suspended sediment 

includes all particles in the sam­ple that do not pass through a 0.45-micrometer membrane filter. The analytical method used 

to quantify concentrations of suspended solid-phase material was consistent from 1992 through the present study; however, 

the nomenclature used to describe sediment data was changed (Gray and others, 2000). Suspended-sediment concentrations 

were referred to as suspended-solids concentrations in previous reports (Buchanan and Schoellhamer, 1995, 1996, 1998, 1999; 

Buchanan and others, 1996; Buchanan and Ruhl, 2000, 2001). Water samples collected for this study were analyzed for SSC, in 

milligrams per liter (mg/L), by filtering samples through a pre-weighed, tared, 0.45-micrometer membrane filter. The filtrate was 

rinsed with de-ionized water to remove salts, and the insoluble material and filter were dried at 103°C and weighed (Fishman 

and Friedman, 1989).

 Summary of Suspended-Sediment Concentration Data, San Francisco Bay, California, Water Year 2005
Data Processing

Data loggers stored the optical-sensor output at 15-minute intervals (96 data points per day). Recorded data were downloaded from the data loggers onto either a storage module or laptop computer during site visits. Raw data from the storage 

modules or laptop computer were loaded into the USGS Automated Data-Processing System (ADAPS).

The time-series data were retrieved from ADAPS and processed to remove invalid data. Invalid data included rapidly 

increasing voltage outputs and unusually high voltage outputs of short duration. As biological growth accumulated on the optical sen­sors, the voltage output of the sensors increased (except for the Hydrolab’s optical sensor out­put, which decreased). An 

example time-series of raw and processed optical sensor data is presented in figure 3. After sensors were cleaned, sensor output 

immediately decreased (fig. 3A: July 20, August 8, 29, and September 19; dates represented by vertical dashed lines). Efforts to 

correct for biofouling proved to be unsuc­cessful because the signal often was highly variable. Thus, data affected by biofouling 

often were unusable and were removed from the record (fig. 3B). Identifying the point at which fouling begins to affect optical 

sensor data is some­what subjective. Indicators, such as an elevated baseline, increasingly variable signal, and comparisons with 

the other sensor at the site, are used to help define the point at which fouling begins to take place. Spikes in the data, which are 

anomalously high voltages probably caused by debris temporarily wrapped around the sensor or by large marine organisms (fish, 

crabs) on or near the sensor, also were removed from the raw data record (fig. 3B). Sometimes, incomplete cleaning of a sensor 

would cause a small, constant shift in sensor output that could be corrected by using water-sample data that had been collected 

for calibration of the sensors.

Figure 3. Example of raw and processed optical data, mid-depth sensor, Mare Island Causeway, San Pablo Bay, 

California, water year 2005.

Methods 

1,500

1,500

500

0

1,000

500

0

1,000

RAW DATA, IN MILLIVOLTS PROCESSED DATA, IN MILLIVOLTS

JULY AUG. SEPT.

2005

A

B
Sensor Calibration and Suspended-Sediment Concentration Data

The output from each of the three types of sensors used for this study is proportional to the SSC in the water col­umn at 

the depth of the sensor. SSC calculated from the output of side-by-side sensors with different instrument designs were virtually 

identical (Buchanan and Schoellhamer, 1998). Calibration of the sensor output to SSC will vary according to the size and optical properties of the suspended sed­iment; therefore, the sensors must be calibrated by using suspended material from the field 

(Levesque and Schoellhamer, 1995).

The output from the optical sensors was used to calculate SSC by linear regression using the robust, nonparametric, 

repeated median method (Siegel, 1982) rather than ordinary least squares (OLS) regression. Constant variance of residuals is 

a necessary condition for use of OLS regression to obtain the best linear unbiased estimator of a variable (Helsel and Hirsch, 

1992, p.225). The variance of the residuals for some datasets in this study increased with voltage and was not constant; therefore, robust regression was considered to be more appropriate than OLS regression for the development of calibration curves in 

most cases.

 The prediction interval and the 95-percent confidence interval were calculated and presented for each calibration equation. 

Whenever possible, water-sample data collected in previous water years were included in the calibrations to incorporate the largest range of observed concentrations. Previously collected water-sample data were disgarded if a sensor’s calibration had drifted.

The repeated-median method calculates the calibration slope in a two-part process. First, for each point (X,Y) in a set of n

data points, the median of all possible “point i” to “point j” slopes was calculated

βi

j i

j i

median

Y Y

X X = −−

( )

( )

for j = 1...n, j I�

 (1)

The calibration slope was calculated as the median of βi

1 ( ) ˆ fori=1...n i slope = = β β median (2)

Finally, the calibration intercept was calculated as the median of all possible intercepts by using the slope calculated above

( ) ˆ ˆ fori=1...n = = βo median Y X i − βi i intercept (3)

The final linear calibration equation is

1

ˆ ˆ Y X = + β βo (4)

The nonparametric prediction interval (PInp) (Helsel and Hirsch, 1992, p. 76) is a constant-width error band that contains 

about 68-percent, or one standard deviation, of the calibration data set. The 68-percent value was selected because essentially it 

has the same error prediction limits as the root-mean-squared (RMS) error of prediction that was used to describe the error associated with parametric OLS regression methods in previous data reports (Buchanan and Schoellhamer, 1995, 1996, 1998, 1999; 

Buchanan and others, 1996) to analyze random sets of normally distributed data. The prediction interval describes the likelihood 

that a new observation comes from the same distribution as the previously collected data set.

The PInp, unlike the RMS error of prediction, frequently is not symmetrical about the regression line. For example, the 

PInp may be reported as +10 and -7 mg/L. This asymmetry about the regression line is a result of the distribution of the data set. 

The PInp is calculated by computing and sorting, from least to greatest, the residuals for each point. Then, based on the sorted 

list of residuals

( )( )1 (1 )( )1

2 2

ˆ ˆ nonparametric prediction interval Y to Y

where

Y i ˆ s the residual value,

is the number of data points, and

is the confidence level of 0.068.

np n n

PI

n

α α

α

+ − +

= =

 (5)

 Summary of Suspended-Sediment Concentration Data, San Francisco Bay, California, Water Year 2005
To calculate the confidence interval for the regression line slope, all possible point-to-point slopes must be sorted in ascending order. On the basis of the confidence interval desired, 95-percent for the purposes of this report, the ranks of the upper and 

lower INTERVALs are calculated as follows:

Ru =

n n( ) − n n n

+

 ( ) − ( ) +











+





























1

2

1 96

1 2 5

18

2

1

.

, (6)

and

( ) ( )( )

where 

 is the rank of the upper INTERVAL slope,

 is the rank of the lower INTERVAL slope, and

 is the number of samples.

1 1 2 5

1.96

2 18 = , 2

Ru

Rl

n

n n n n n

Rl

−  − +  −     (7)

To establish the 95-percent confidence interval, the ranks calculated above are rounded to the nearest integer and the slope 

associated with each rank in the sorted list is identified. Equations (6) and (7), which represent large-sample approximations for 

the ranks, were used for each of the confidence intervals presented in this report. However, for those sites that had fewer than 10 

samples, an alternative and presumably slightly more accurate method described by Helsel and Hirsch (1992, p. 273-274) could 

have been used to calculate upper and lower bound ranks.

A statistical summary of the SSC calculated from optical sensor data is presented in table 2. The usable percentage of a 

complete year of valid data (96 data points per day × 365 days) for each site also is presented in table 2

 Table 2. Statistical summary of calculated suspended-sediment concentration data and usable percentage of a complete year 

of valid data (96 data points per day x 365 days) collected using optical sensors, Suisun Bay, San Pablo Bay, and Central and South 

San Francisco Bays, California, water year 2005.

[All values are in milligrams per liter except percent valid data. Lower quartile is 25th percentile; upper quartile is 75th percentile]

Site Depth Mean Median Lower quartile Upper quartile Percent valid data

Mallard Island Near-surface 27 24 20 30 99

Near-bottom 28 25 21 31 99

Benicia Bridge Near-surface 37 31 23 46 65

Near-bottom 67 61 44 82 74

Carquinez Bridge Mid-depth 42 30 19 52 87

Near-bottom 66 50 31 84 73

Mare Island Causeway Mid-depth 55 42 27 70 74

Near-bottom 109 82 51 141 59

Channel Marker 1 Mid-depth 38 27 17 47 45

Point San Pablo Mid-depth 32 25 17 40 62

Near-bottom 37 28 20 44 86

Alcatraz Island Mid-depth 18 15 12 21 71

San Mateo Bridge Mid-depth 47 43 35 57 37

Near-bottom 45 38 28 53 16

Dumbarton Bridge Mid-depth 48 43 23 62 45

Near-bottom 43 32 24 51 30

Channel Marker 17 Mid-depth 51 40 31 57 50

Near-bottom 56 36 25 65 41

Sensor Calibration and Suspended-Sediment Concentration Data 
0 20 40 60 80 100 120

0

20

40

60

80

100

120

SENSOR OUTPUT, IN NEPHELOMETRIC TURBIDITY UNITS

SUSPENDED-SEDIMENT CONCENTRATIONS, IN MILLIGRAMS PER LITER

Number of data points = 36

Calibration equation: SSC = 0.723 x NTU + 7.6

Non-parametric prediction interval: + 6 to -3

95 percent confidence interval on equation slope (0.723): 0.636 to 0.875

0 20 40 60 80 100 120

0

20

40

60

80

100

120

SENSOR OUTPUT, IN NEPHELOMETRIC TURBIDITY UNITS

Number of data points = 37

Calibration equation: SSC = 0.735 x NTU + 5.3

Non-parametric prediction interval: + 11 to -3

95 percent confidence interval on equation slope (0.735): 0.641 to 1.001

B

A

Figure 4. Calibration of near-surface and near-bottom optical sensors at Mallard Island, Suisun Bay, California, water 

year 2005. 

.This section of the report also includes figures showing graphical results of the regression analysis (calibration) relating 

SSC (in mg/L) to optical sensor output. The calibration figures (for example, fig. 4) include the number of water samples (data 

points) (all water samples used to develop calibration, including those from previous water years), the linear regression equation, 

the nonparametric prediction interval (shown on the calibration figures as a grey band), and the 95-percent confidence interval 

for the regression-line slope. In addition, the time-series plots of calculated SSC data are shown for each site.

10 Summary of Suspended-Sediment Concentration Data, San Francisco Bay, California, Water Year 2005
Suisun Bay

Mallard Island

PERIOD OF CALIBRATION.—

NEAR-SURFACE SENSOR: WY 2005 (fig. 4A).

NEAR-BOTTOM SENSOR: WY 2005 (fig. 4B).

NUMBER OF DATA POINTS (WATER SAMPLES) USED FOR CALIBRATION.—

NEAR-SURFACE SENSOR: 36 (15 from WY 2005).

NEAR-BOTTOM SENSOR: 37 (16 from WY 2005).

LINEAR REGRESSION EQUATION.—

NEAR-SURFACE SENSOR: SSC = 0.723 × millivolt (mV) + 7.6.

NEAR-BOTTOM SENSOR: SSC = 0.735 × mV + 5.3.

NONPARAMETRIC PREDICTION INTERVAL.—

NEAR-SURFACE SENSOR: +6 to -3 mg/L.

NEAR-BOTTOM SENSOR: +11 to -3 mg/L.

95-PERCENT CONFIDENCE INTERVAL ON SLOPE CALCULATION.—

NEAR-SURFACE SENSOR: 0.636 to 0.875.

NEAR-BOTTOM SENSOR: 0.641 to 1.001.

REMARKS.—There were no interruptions in the record. Sensors were positioned at near-surface (attached to float assembly) and near-bottom depths to coincide with DWR near-surface pump intake and the near-bottom electrical conductance and 

temperature sensors. The calculated SSC time-series data collected for WY 2005 are presented in figure 5.

Sensor Calibration and Suspended-Sediment Concentration Data 11
0

20

40

60

80

100

120

OCT. NOV. DEC. JAN. FEB. MAR. APR. MAY JUNE JULY AUG. SEPT.

2 0 0 4 2 0 0 5

0

20

40

60

80

100

120

SUSPENDED SEDIMENT CONCENTRATION, IN MILLIGRAMS PER LITER

2 0 0 4 2 0 0 5

OCT NOV DEC JAN FEB MAR APR MAY JUNE JULY AUG SEPT

B

A

Figure 5. Graphs showing time series of near-surface and near-bottom suspended-sediment concentrations 

calculated from sensor readings at Mallard Island, Suisun Bay, California, water year 2005.

12 Summary of Suspended-Sediment Concentration Data, San Francisco Bay, California, Water Year 2005
Benicia Bridge

PERIOD OF CALIBRATION.—

NEAR-SURFACE SENSOR: WY 2005 (fig. 6).

NEAR-BOTTOM SENSOR (A): October 1, 2004, to November 23, 2004 (fig. 7A).

NEAR-BOTTOM SENSOR (B): November 23, 2004, through September 30, 2005 (fig. 7B).

NUMBER OF DATA POINTS (WATER SAMPLES) USED FOR CALIBRATION.— 

NEAR-SURFACE SENSOR: 33 (15 from WY 2005, 1 from WY 2006).

NEAR-BOTTOM SENSOR (A): 33 (2 from WY 2005).

NEAR-BOTTOM SENSOR (B): 25 (13 from WY 2005).

LINEAR REGRESSION EQUATION.—

NEAR-SURFACE SENSOR: SSC = 0.916 × NTU + 6.5.

NEAR-BOTTOM SENSOR (A): SSC = 1.138 × NTU + 10.1.

NEAR-BOTTOM SENSOR (B): SSC = 1.125 × NTU + 21.3.

NONPARAMETRIC PREDICTION INTERVAL.—

NEAR-SURFACE SENSOR: +8 to -6 mg/L.

NEAR-BOTTOM SENSOR (A): +22 to -9 mg/L.

NEAR-BOTTOM SENSOR (B): +11 to -18 mg/L.

95-PERCENT CONFIDENCE INTERVAL ON SLOPE CALCULATION.—

NEAR-SURFACE SENSOR: 0.824 to 1.100.

NEAR-BOTTOM SENSOR (A): 1.044 to 1.352.

NEAR-BOTTOM SENSOR (B): 0.909 to 1.259.

REMARKS.—Interruptions in record were caused by fouling or malfunction of the sensing and(or) recording instruments. 

MLLW was approximately 80 ft at the site but approximately 60 ft immediately adjacent. Therefore, the near-bottom sonde was 

set approximately 25 ft above the bottom so that the data are representative of the surrounding area. The near-surface sonde malfunctioned and was replaced on July 29, 2005. Because the two near-surface optical sensors responded similarly to the uniform 

sediment characteristics of San Francisco Bay (Schoellhamer and others, 2003), the calibration was developed by combining 

water samples collected during each sensor deployment (including two samples from WY 2006). The near-bottom sonde was 

replaced on November 23, 2004, with a sonde from a different manufacturer. On May 18, 2005, the near-bottom sonde was 

determined to be reading erratically and was replaced. Because the two optical sensors (both YSI’s) deployed at the near-bottom 

position from November 23, 2004, through September 30, 2005, responded similarly to the uniform sediment characteristics of 

San Francisco Bay (Schoellhamer and others, 2003), the calibration was developed by combining water samples collected during 

each sensor deployment. The calculated SSC time-series data collected for WY 2005 are presented in figure 8.

Sensor Calibration and Suspended-Sediment Concentration Data 13
0 20 40 60 80 100 120 140 160

0

20

40

60

80

100

120

140

160

180

SENSOR OUTPUT, IN NEPHELOMETRIC TURBIDITY UNITS

SUSPENDED-SEDIMENT CONCENTRATIONS, IN MILLIGRAMS PER LITER

Number of data points = 33

Calibration equation: SSC = 0.916 x NTU + 6.5

Non-parametric prediction interval: + 8 to -6

95 percent confidence interval on equation slope (0.916): 0.824 to 1.100

Figure 6. Graph showing calibration of near-surface optical sensor at Benicia Bridge, Suisun Bay, California, water 

year 2005. 

14  Summary of Suspended-Sediment Concentration Data, San Francisco Bay, California, Water Year 2005
0 20 40 60 80 100 120 140

0

50

100

150

200

250

SENSOR OUTPUT, IN NEPHELOMETRIC TURBIDITY UNITS

SUSPENDED-SEDIMENT CONCENTRATIONS, IN MILLIGRAMS PER LITER

Number of data points = 33

Calibration equation: SSC = 1.138 x NTU + 10.1

Non-parametric prediction interval: + 22 to -9

95 percent confidence interval on equation slope (1.138): 1.044 to 1.352

0 20 40 60 80 100 120 140 160 180 200

0

50

100

150

200

250

300

SENSOR OUTPUT, IN NEPHELOMETRIC TURBIDITY UNITS

Number of data points = 25

Calibration equation: SSC = 1.125 x NTU + 21.3

Non-parametric prediction interval: + 11 to -18

95 percent confidence interval on equation slope (1.125): 0.909 to 1.259

A

B

Figure 7. Graphs showing calibration of near-bottom optical sensors, October 1–November 23 and November 

23–September 30 at Benicia Bridge, Suisun Bay, California, water year 2005. 

Sensor Calibration and Suspended-Sediment Concentration Data 15
0

50

100

150

200

250

300

0

50

100

150

200

250

300

SUSPENDED-SEDIMENT CONCENTRATION, IN MILLIGRAMS PER LITER

2 0 0 4 2 0 0 5

2 0 0 4 2 0 0 5

OCT. NOV. DEC. JAN. FEB. MAR. APR. MAY JUNE JULY AUG. SEPT.

OCT. NOV. DEC. JAN. FEB. MAR. APR. MAY JUNE JULY AUG. SEPT.

A

B

Figure 8. Graphs showing time series of near-surface and near-bottom suspended-sediment concentrations 

calculated from sensor readings at Benicia Bridge, Suisun Bay, California, water year 2005. 

16  Summary of Suspended-Sediment Concentration Data, San Francisco Bay, California, Water Year 2005
San Pablo Bay

Carquinez Bridge

PERIOD OF CALIBRATION.—

MID-DEPTH SENSOR: WY 2005 (fig. 9A).

NEAR-BOTTOM SENSOR: WY 2005 (fig. 9B).

NUMBER OF DATA POINTS (WATER SAMPLES) USED FOR CALIBRATION.— 

MID-DEPTH SENSOR: 18 (17 from WY 2005).

NEAR-BOTTOM SENSOR: 27 (13 from WY 2005).

LINEAR REGRESSION EQUATION.—

MID-DEPTH SENSOR: SSC = 1.297 × NTU + 3.6.

NEAR-BOTTOM SENSOR: SSC = 1.173 × NTU + 8.8.

NONPARAMETRIC PREDICTION INTERVAL.—

MID-DEPTH SENSOR: +7 to -6 mg/L.

NEAR-BOTTOM SENSOR: +18 to -13 mg/L.

95-PERCENT CONFIDENCE INTERVAL ON SLOPE CALCULATION.—

MID-DEPTH SENSOR: 1.111 to 1.481.

NEAR-BOTTOM SENSOR: 1.035 to 1.333.

REMARKS.—Interruptions in record were caused by fouling or malfunction of the sensing and(or) recording instruments. 

The suspension cable failed on April 29, 2005, and was replaced on May 20, 2005. The near-bottom sonde malfunctioned during 

the site visit on August 18, 2005, and was replaced on September 7, 2005, with a sonde without a turbidity sensor. The calculated SSC time-series data collected for water year 2005 are presented in figure 10.

Sensor Calibration and Suspended-Sediment Concentration Data 17
0 20 40 60 80 100 120

0

20

40

60

80

100

120

140

160

180

200

SENSOR OUTPUT, IN NEPHELOMETRIC TURBIDITY UNITS

SUSPENDED-SEDIMENT CONCENTRATIONS, IN MILLIGRAMS PER LITER

Number of data points = 18

Calibration equation: SSC = 1.297 x NTU + 3.6

Non-parametric prediction interval: + 7 to -6

95 percent confidence interval on equation slope (1.297): 1.111 to 1.481

0 20 40 60 80 100 120 140

0

20

40

60

80

100

120

140

160

180

200

220

SENSOR OUTPUT, IN NEPHELOMETRIC TURBIDITY UNITS

Number of data points = 27

Calibration equation: SSC = 1.173 x NTU + 8.8

Non-parametric prediction interval: + 18 to -13

95 percent confidence interval on equation slope (1.173): 1.035 to 1.333

A

B

Figure 9. Graphs showing calibration of mid-depth and near-bottom optical sensors at Carquinez Bridge, San 

Pablo Bay, California, water year 2005. 

18  Summary of Suspended-Sediment Concentration Data, San Francisco Bay, California, Water Year 2005
0

50

100

150

200

250

300

350

400

450

500

SUSPENDED-SEDIMENT CONCENTRATION, IN MILLIGRAMS PER LITER

2 0 0 4 2 0 0 5

0

50

100

150

200

250

300

350

400

450

500

2 0 0 4 2 0 0 5

A

B

OCT. NOV. DEC. JAN. FEB. MAR. APR. MAY JUNE JULY AUG. SEPT.

OCT. NOV. DEC. JAN. FEB. MAR. APR. MAY JUNE JULY AUG. SEPT.

Figure 10. Graphs showing time series of mid-depth and near-bottom suspended-sediment concentrations 

calculated from sensor readings at Carquinez Bridge, San Pablo Bay, California, water year 2005.

Sensor Calibration and Suspended-Sediment Concentration Data 19
Mare Island Causeway

PERIOD OF CALIBRATION.—

MID-DEPTH SENSOR: WY 2005 (fig. 11).

NEAR-BOTTOM SENSOR (A): October 1, 2004, to March 29, 2005 (fig. 12A).

NEAR-BOTTOM SENSOR (B): March 29, 2005, through September 30, 2005 (fig. 12B).

NUMBER OF DATA POINTS (WATER SAMPLES) USED FOR CALIBRATION.—

MID-DEPTH SENSOR: 39 (19 from WY 2005).

NEAR-BOTTOM SENSOR (A): 7 (5 from WY 2005).

NEAR-BOTTOM SENSOR (B): 9 (9 from WY 2005).

LINEAR REGRESSION EQUATION.—

MID-DEPTH SENSOR: SSC = 0.640 × mV – 10.8.

NEAR-BOTTOM SENSOR (A): SSC = 0.919 × mV - 39.6.

NEAR-BOTTOM SENSOR (B): SSC = 0.633 × mV - 4.1.

NONPARAMETRIC PREDICTION INTERVAL.—

MID-DEPTH SENSOR: +13 to -8 mg/L.

NEAR-BOTTOM SENSOR (A): +20 to -24 mg/L.

NEAR-BOTTOM SENSOR (B): +13 to -22 mg/L.

95-PERCENT CONFIDENCE INTERVAL ON SLOPE CALCULATION.—

MID-DEPTH SENSOR: 0.573 to 0.685.

NEAR-BOTTOM SENSOR (A): 0.811 to 1.657.

NEAR-BOTTOM SENSOR (B): 0.303 to 0.848.

REMARKS.—Interruptions in record were caused by fouling or malfunction of the sensing and(or) recording instruments. 

The near-bottom optical sensor output began to drift in late January but the drift was not recognized until March 29, 2005, when 

the sensor was replaced with another optical sensor. The calculated SSC time-series data collected for WY 2005 are presented in 

figure 13.

20 Summary of Suspended-Sediment Concentration Data, San Francisco Bay, California, Water Year 2005
0 50 100 150 200 250 300

0

20

40

60

80

100

120

140

160

180

200

SENSOR OUTPUT, IN MILLIVOLTS

SUSPENDED-SEDIMENT CONCENTRATIONS, IN MILLIGRAMS PER LITER

Number of data points = 39

Calibration equation: SSC = 0.640 x mV - 10.8

Non-parametric prediction interval: + 13 to -8

95 percent confidence interval on equation slope (0.640): 0.573 to 0.685

Figure 11. Graph showing calibration of mid-depth optical sensor at Mare Island Causeway, San Pablo Bay, 

California, water year 2005 .

Sensor Calibration and Suspended-Sediment Concentration Data 21
0 50 100 150 200 250 300 350

0

50

100

150

200

250

300

SENSOR OUTPUT, IN MILLIVOLTS

Number of data points = 9

Calibration equation: SSC = 0.633 x mV - 4.1

Non-parametric prediction interval: + 13 to -22

95 percent confidence interval on equation slope (0.633): 0.303 to 0.848

Kendall tau used for confidence interval calculation with small data set

0 50 100 150

0

50

100

150

SENSOR OUTPUT, IN MILLIVOLTS

SUSPENDED-SEDIMENT CONCENTRATIONS, IN MILLIGRAMS PER LITER

Number of data points = 7

Calibration equation: SSC = 0.919 x mV - 39.6

Non-parametric prediction interval: + 20 to -24

95 percent confidence interval on equation slope (0.919):-0.811 to 1.657

Kendall tau used for confidence interval calculation with small data set

B

A

Figure 12. Graphs showing calibrations of near-bottom optical sensors, October 1–March 29 and March 29–

September 30 at Mare Island Causeway, San Pablo Bay, California, water year 2005. 

22 Summary of Suspended-Sediment Concentration Data, San Francisco Bay, California, Water Year 2005
0

100

200

300

400

500

600

700

800

900

SUSPENDED-SEDIMENT CONCENTRATION, IN MILLIGRAMS PER LITER

2 0 0 4 2 0 0 5

0

100

200

300

400

500

600

700

800

900

2 0 0 4 2 0 0 5

A

B

OCT. NOV. DEC. JAN. FEB. MAR. APR. MAY JUNE JULY AUG. SEPT.

OCT. NOV. DEC. JAN. FEB. MAR. APR. MAY JUNE JULY AUG. SEPT.

Figure 13. Graphs showing time series of mid-depth and near-bottom suspended-sediment concentrations 

calculated from sensor readings at Mare Island Causeway, San Pablo Bay, California, water year 2005.

Sensor Calibration and Suspended-Sediment Concentration Data 23
Channel Marker 1

PERIOD OF CALIBRATION.—

MID-DEPTH SENSOR: October 1, 2004 to September 28, 2005 (fig. 14).

NUMBER OF DATA POINTS (WATER SAMPLES) USED FOR CALIBRATION.—

MID-DEPTH SENSOR: 27 (11 from WY 2005).

LINEAR REGRESSION EQUATION.—

MID-DEPTH SENSOR: SSC = 1.787 × NTU + 1.9

NONPARAMETRIC PREDICTION INTERVAL.—

MID-DEPTH SENSOR: +19 to -14 mg/L.

95-PERCENT CONFIDENCE INTERVAL ON SLOPE CALCULATION.—

MID-DEPTH SENSOR (A): 1.111 to 2.031.

REMARKS.—Interruptions in record caused by fouling or malfunction of the sensing and(or) recording instruments. During periods of heavy fouling the optical sensor wiper was ineffective in keeping the optical ports clean because of biological 

growth on the wiper itself obscuring the optical ports. The site was discontinued on September 28, 2005. The calculated SSC 

time-series data collected for WY 2005 are presented in figure 15.

24  Summary of Suspended-Sediment Concentration Data, San Francisco Bay, California, Water Year 2005
0 10 20 30 40 50 60 70 80 90

0

20

40

60

80

100

120

140

160

180

SENSOR OUTPUT, IN NEPHELOMETRIC TURBIDITY UNITS

SUSPENDED-SEDIMENT CONCENTRATIONS, IN MILLIGRAMS PER LITER

Number of data points = 27

Calibration equation: SSC = 1.787 x NTU + 1.9

Non-parametric prediction interval: + 19 to -14

95 percent confidence interval on equation slope (1.787): 1.111 to 2.031

Figure 14. Graph showing calibration of mid-depth optical sensor at Channel Marker 1, San Pablo Bay, California, 

water year 2005.

Sensor Calibration and Suspended-Sediment Concentration Data 25
0

50

100

150

200

250

300

350

400

SUSPENDED-SEDIMENT CONCENTRATION, IN MILLIGRAMS PER LITER

2 0 0 4 2 0 0 5

OCT. NOV. DEC. JAN. FEB. MAR. APR. MAY JUNE JULY AUG. SEPT.

Figure 15. Graph showing time series of mid-depth suspended-sediment concentrations calculated from sensor 

readings at Channel Marker 1, San Pablo Bay, California, water year 2005.

26  Summary of Suspended-Sediment Concentration Data, San Francisco Bay, California, Water Year 2005
Central San Francisco Bay

Point San Pablo

PERIOD OF CALIBRATION.—

MID-DEPTH SENSOR: WY 2005 (fig. 16A).

NEAR-BOTTOM SENSOR: WY 2005 (fig. 16B).

NUMBER OF DATA POINTS (WATER SAMPLES) USED FOR CALIBRATION.—

MID-DEPTH SENSOR: 29 (13 from WY 2005).

NEAR-BOTTOM SENSOR: 35 (15 from WY 2005).

LINEAR REGRESSION EQUATION.—

MID-DEPTH SENSOR: SSC = 1.755 × NTU + 0.9.

NEAR-BOTTOM SENSOR: SSC = 1.537 × NTU + 4.4.

NONPARAMETRIC PREDICTION INTERVAL.—

MID-DEPTH SENSOR: +14 to -10 mg/L.

NEAR-BOTTOM SENSOR: +25 to -10 mg/L.

95-PERCENT CONFIDENCE INTERVAL ON SLOPE CALCULATION.—

MID-DEPTH SENSOR: 1.330 to 2.213.

NEAR-BOTTOM SENSOR: 1.166 to 1.931.

REMARKS.—Interruptions in record were caused by fouling or malfunction of the sensing and(or) recording instruments. 

The mid-depth sonde was removed on June 28, 2005, because of a broken communication pin and redeployed on July 21, 2005. 

The near-bottom sonde was removed on June 7, 2005, because of a flooded battery compartment and a replacement sonde was 

deployed on June 9, 2005. Because the two optical sensors deployed at the near-bottom position responded similarly to the 

uniform sediment characteristics of San Francisco Bay (Schoellhamer and others, 2003), the calibration was developed by combining water samples collected during each sensor deployment.The calculated SSC time-series data collected for WY 2005 are 

presented in figure 17.

Sensor Calibration and Suspended-Sediment Concentration Data 27
0 10 20 30 40 50 60 70

0

20

40

60

80

100

120

140

160

SENSOR OUTPUT, IN NEPHELOMETRIC TURBIDITY UNITS

SUSPENDED-SEDIMENT CONCENTRATIONS, IN MILLIGRAMS PER LITER

Number of data points = 29

Calibration equation: SSC = 1.755 x NTU + 0.9

Non-parametric prediction interval: + 14 to -10

95 percent confidence interval on equation slope (1.755): 1.330 to 2.213

0 10 20 30 40 50 60 70

0

20

40

60

80

100

120

140

160

180

200

SENSOR OUTPUT, IN NEPHELOMETRIC TURBIDITY UNITS

Number of data points = 35

Calibration equation: SSC = 1.537 x NTU + 4.4

Non-parametric prediction interval: + 25 to -10

95 percent confidence interval on equation slope (1.537): 1.166 to 1.931

A

B

Figure 16. Graphs showing calibration of mid-depth and near-bottom optical sensors at Point San Pablo, Central San 

Francisco Bay, California, water year 2005.

28  Summary of Suspended-Sediment Concentration Data, San Francisco Bay, California, Water Year 2005
0

50

100

150

200

250

300

350

400

450

500

SUSPENDED-SEDIMENT CONCENTRATION, IN MILLIGRAMS PER LITER

2 0 0 4 2 0 0 5

0

50

100

150

200

250

300

350

400

450

500

2 0 0 4 2 0 0 5

A

B

OCT. NOV. DEC. JAN. FEB. MAR. APR. MAY JUNE JULY AUG. SEPT.

OCT. NOV. DEC. JAN. FEB. MAR. APR. MAY JUNE JULY AUG. SEPT.

Figure 17. Graphs showing time series of mid-depth and near-bottom suspended-sediment concentrations calculated 

from sensor readings at Point San Pablo, Central San Francisco Bay, California, water year 2005.

Sensor Calibration and Suspended-Sediment Concentration Data 29
Alcatraz Island

PERIOD OF CALIBRATION.—

MID-DEPTH SENSOR: WY 2005 (fig. 18).

NUMBER OF DATA POINTS (WATER SAMPLES) USED FOR CALIBRATION.— 

MID-DEPTH SENSOR: 17 (17 from WY 2005).

LINEAR REGRESSION EQUATION.—

MID-DEPTH SENSOR: SSC = 2.357 × NTU - 8.4.

NONPARAMETRIC PREDICTION INTERVAL.—

MID-DEPTH SENSOR: +9 to -4 mg/L.

95-PERCENT CONFIDENCE INTERVAL ON SLOPE CALCULATION.—

MID-DEPTH SENSOR: 1.538 to 4.286.

REMARKS.—Interruptions in record caused by fouling or malfunction of the sensing and(or) recording instruments. The 

optical sensor wiper was ineffective during periods of heavy fouling because of biological growth on the wiper obscuring the 

optical ports. The calculated SSC time-series data collected for WY 2005 are presented in figure 19.

30 Summary of Suspended-Sediment Concentration Data, San Francisco Bay, California, Water Year 2005
0 2 4 6 8 10 12 14 16 18

0

5

10

15

20

25

30

35

40

45

50

55

SENSOR OUTPUT, IN NEPHELOMETRIC TURBIDITY UNITS

SUSPENDED-SEDIMENT CONCENTRATIONS, IN MILLIGRAMS PER LITER

Number of data points = 17

Calibration equation: SSC = 2.357 x NTU - 8.4

Non-parametric prediction interval: + 9 to -4

95 percent confidence interval on equation slope (2.357): 1.538 to 4.286

Figure 18. Graph showing calibration of mid-depth optical sensor at Alcatraz Island, Central San Francisco Bay, 

California, water year 2005.

Sensor Calibration and Suspended-Sediment Concentration Data  31
0

20

40

60

80

100

120

140

160

SUSPENDED-SEDIMENT CONCENTRATION, IN MILLIGRAMS PER LITER

2 0 0 4 2 0 0 5

OCT. NOV. DEC. JAN. FEB. MAR. APR. MAY JUNE JULY AUG. SEPT.

Figure 19. Graph showing time series of mid-depth suspended-sediment concentrations calculated from sensor 

readings at Alcatraz Island, Central San Francisco Bay, California, water year 2005.

32 Summary of Suspended-Sediment Concentration Data, San Francisco Bay, California, Water Year 2005
South San Francisco Bay

San Mateo Bridge

PERIOD OF CALIBRATION.—

MID-DEPTH SENSOR: WY 2005 (fig. 20A).

NEAR-BOTTOM SENSOR: October 1, 2004 to July 22, 2005 (fig. 20B).

NUMBER OF DATA POINTS (WATER SAMPLES) USED FOR CALIBRATION.—

MID-DEPTH SENSOR: 70 (16 from WY 2005).

NEAR-BOTTOM SENSOR: 57 (10 from WY 2005).

LINEAR REGRESSION EQUATION.—

MID-DEPTH SENSOR: SSC = 0.445 × mV + 5.2.

NEAR-BOTTOM SENSOR: SSC = 0.591 × mV + 1.8.

NONPARAMETRIC PREDICTION INTERVAL.—

MID-DEPTH SENSOR: +10 to -12 mg/L.

NEAR-BOTTOM SENSOR: +9 to -9 mg/L.

95-PERCENT CONFIDENCE INTERVAL ON SLOPE CALCULATION.—

MID-DEPTH SENSOR: 0.435 to 0.656.

NEAR-BOTTOM SENSOR: 0.509 to 0.720.

REMARKS.— Interruptions in record were caused by fouling or malfunction of the sensing and(or) recording instruments. 

Biological fouling in South San Francisco Bay is extreme, especially during the summer months, resulting in a fragmented data 

set. The near-bottom sensor malfunctioned on July 22, 2005, and a replacement sensor was deployed on July 27, 2005. The nearbottom sensor deployed from July 27, 2005 through September 30, 2005, did not operate properly and the data were deleted. 

The calculated SSC time-series data collected for WY 2005 are presented in figure 21.

Sensor Calibration and Suspended-Sediment Concentration Data  33
0 50 100 150 200 250

0

20

40

60

80

100

120

140

160

SENSOR OUTPUT, IN MILLIVOLTS

SUSPENDED-SEDIMENT CONCENTRATIONS, IN MILLIGRAMS PER LITER

Number of data points = 70

Calibration equation: SSC = 0.445 x mV + 5.2

Non-parametric prediction interval: + 10 to -12

95 percent confidence interval on equation slope (0.445): 0.435 to 0.656

0 50 100 150

0

20

40

60

80

100

120

SENSOR OUTPUT, IN MILLIVOLTS

Number of data points = 57

Calibration equation: SSC = 0.591 x mV + 1.8

Non-parametric prediction interval: + 9 to - 9

95 percent confidence interval on equation slope (0.591): 0.509 to 0.720

A

B

Figure 20. Graphs showing calibration of mid-depth and near-bottom optical sensors at San Mateo Bridge, South San 

Francisco Bay, California, water year 2005.

34  Summary of Suspended-Sediment Concentration Data, San Francisco Bay, California, Water Year 2005
0

50

100

150

200

250

300

2 0 0 4 2 0 0 5

0

50

100

150

200

250

300

SUSPENDED-SEDIMENT CONCENTRATION, IN MILLIGRAMS PER LITER

2 0 0 4 2 0 0 5

A

B

OCT. NOV. DEC. JAN. FEB. MAR. APR. MAY JUNE JULY AUG. SEPT.

OCT. NOV. DEC. JAN. FEB. MAR. APR. MAY JUNE JULY AUG. SEPT.

Figure 21. Graphs showing time series of mid-depth and near-bottom suspended-sediment concentrations 

calculated from sensor readings at San Mateo Bridge, South San Francisco Bay, California, water year 2005.

Sensor Calibration and Suspended-Sediment Concentration Data  35
Dumbarton Bridge

PERIOD OF CALIBRATION.—

 MID-DEPTH SENSOR (A): October 1, 2004, to July 28, 2005 (fig. 22A).

MID-DEPTH SENSOR (B): July 28, 2005, through September 30, 2005 (fig. 22B).

 NEAR-BOTTOM SENSOR (A): October 1, 2004, to March 30, 2005 (fig. 23A).

NEAR-BOTTOM SENSOR (B): March 30, 2005, to July 28, 2005 (fig. 23B).

NEAR-BOTTOM SENSOR (C): July 28, 2005, through September 30, 2005 (fig. 23C).

NUMBER OF DATA POINTS (WATER SAMPLES) USED FOR CALIBRATION.— 

MID-DEPTH SENSOR (A): 49 (9 from WY 2005).

MID-DEPTH SENSOR (B): 12 (4 from WY 2005, 8 from WY 2006).

NEAR-BOTTOM SENSOR (A): 16 (5 from WY 2005).

NEAR-BOTTOM SENSOR (B): 4 (4 from WY 2005).

NEAR-BOTTOM SENSOR (C): 12 (4 from WY 2005, 8 from WY 2006).

LINEAR REGRESSION EQUATION.—`

MID-DEPTH SENSOR (A): SSC = 0.629 × mV - 2.6.

MID-DEPTH SENSOR (B): SSC = 0.386 × NTU +14.5.

NEAR-BOTTOM SENSOR (A): SSC = 0.685 × mV - 13.8.

NEAR-BOTTOM SENSOR (B): SSC = 0.798 × mV - 14.4.

NEAR-BOTTOM SENSOR (C): SSC = 0.803 × NTU - 14.0.

NONPARAMETRIC PREDICTION INTERVAL.—

MID-DEPTH SENSOR (A): +9 to -9 mg/L.

MID-DEPTH SENSOR (B): +5 to -3 mg/L.

NEAR-BOTTOM SENSOR (A): +12 to -11 mg/L.

NEAR-BOTTOM SENSOR (B): Undeterminable with four samples.

NEAR-BOTTOM SENSOR (C): +8 to -7 mg/L.

95-PERCENT CONFIDENCE INTERVAL ON SLOPE CALCULATION.—

MID-DEPTH SENSOR (A): 0.562 to 0.742.

MID-DEPTH SENSOR (B): 0.133 to 0.990.

NEAR-BOTTOM SENSOR (A): 0.503 to 0.871.

NEAR-BOTTOM SENSOR (B): 0.094 to 1.667.

NEAR-BOTTOM SENSOR (C): 0.330 to 1.105.

REMARKS.—Interruptions in record were caused by fouling or malfunction of the sensing and(or) recording instruments. 

The mid-depth optical sensor was replaced with an optical sensor with wiper on July 28, 2005. The near-bottom optical sensor 

malfunctioned and was replaced on March 30, 2005. The near-bottom optical sensor was replaced with an optical sensor with 

wiper on July 28, 2005. The calculated SSC time-series data collected for WY 2005 are presented in figure 24.

36  Summary of Suspended-Sediment Concentration Data, San Francisco Bay, California, Water Year 2005
0 50 100 150 200 250

0

20

40

60

80

100

120

140

160

180

200

SENSOR OUTPUT, IN MILLIVOLTS

SUSPENDED-SEDIMENT CONCENTRATIONS, IN MILLIGRAMS PER LITER

Number of data points = 49

Calibration equation: SSC = 0.629 x mV - 2.6

Non-parametric prediction interval: + 9 to -9

95 percent confidence interval on equation slope (0.629): 0.562 to 0.742

0 10 20 30 40 50 60 70 80

0

10

20

30

40

50

60

SENSOR OUTPUT, IN NEPHELOMETRIC TURBIDITY UNITS

Number of data points = 12

Calibration equation: SSC = 0.386 x NTU + 14.5

Non-parametric prediction interval: +5 to -3

95 percent confidence interval on equation slope (0.386): 0.133 to 0.990

A

B

Figure 22. Graphs showing calibration of mid-depth optical sensors, October 1–July 28 and July 28 –September 30 

at Dumbarton Bridge, South San Francisco Bay, California, water year 2005.

Sensor Calibration and Suspended-Sediment Concentration Data  37
0 50 100 150 200 250

0

50

100

150

200

250

SENSOR OUTPUT, IN MILLIVOLTS

Number of data points = 16

Calibration equation: SSC = 0.685 x mV - 13.8

Non-parametric prediction interval: + 12 to -11

95 percent confidence interval on equation slope (0.685): 0.503 to 0.871

0 50 100 150 200 250

0

50

100

150

200

250

SENSOR OUTPUT, IN MILLIVOLTS

SUSPENDED-SEDIMENT CONCENTRATIONS, IN MILLIGRAMS PER LITER

Number of data points = 4

Calibration equation: SSC = 0.798 x mV - 14.4

Non-parametric prediction interval undeterminable with only 4 samples

95 percent confidence interval on equation slope (0.798): 0.094 to 1.667

Kendall tau used for confidence interval calculation with small data set

0 10 20 30 40 50 60 70

0

20

40

60

80

100

120

SENSOR OUTPUT, IN NEPHELOMETRIC TURBIDITY UNITS

Number of data points = 12

Calibration equation: SSC = 0.803 x NTU + 14.0

Non-parametric prediction interval: + 8 to -7

95 percent confidence interval on equation slope (0.803): 0.330 to 1.105

A

B

C

Figure 23. Graphs showing calibration of near-bottom optical sensors, October 1–March 30, March 30–July 28 and 

July 28 –September 30 at Dumbarton Bridge, South San Francisco Bay, California, water year 2005 .

38  Summary of Suspended-Sediment Concentration Data, San Francisco Bay, California, Water Year 2005
0

50

100

150

200

250

300

350

400

450

500

2 0 0 4 2 0 0 5

0

50

100

150

200

250

300

350

400

450

500

SUSPENDED-SEDIMENT CONCENTRATION, IN MILLIGRAMS PER LITER

2 0 0 4 2 0 0 5

A

B

OCT. NOV. DEC. JAN. FEB. MAR. APR. MAY JUNE JULY AUG. SEPT.

OCT. NOV. DEC. JAN. FEB. MAR. APR. MAY JUNE JULY AUG. SEPT.

Figure 24. Graphs showing time series of mid-depth and near-bottom suspended-sediment concentrations 

calculated from sensor readings at Dumbarton Bridge, South San Francisco Bay, California, water year 2005 .

Sensor Calibration and Suspended-Sediment Concentration Data  39
Channel Marker 17

PERIOD OF CALIBRATION.—

MID-DEPTH SENSOR (A): October 13, 2004, to April 20, 2005 (fig. 25A).

MID-DEPTH SENSOR (B): April 20, 2005, through September 30, 2005 (fig. 25B).

NEAR-BOTTOM SENSOR (A): October 1, 2004, to March 30, 2005 (fig. 26A).

NEAR-BOTTOM SENSOR (B): April 20, 2005, through September 30, 2005 (fig. 26B).

NUMBER OF DATA POINTS (WATER SAMPLES) USED FOR CALIBRATION.— 

MID-DEPTH SENSOR (A): 8 (7 from WY 2005).

MID-DEPTH SENSOR (B): 7 (7 from WY 2005).

NEAR-BOTTOM SENSOR (A): 23 (7 from WY 2005).

NEAR-BOTTOM SENSOR (B): 16 (7 from WY 2005).

LINEAR REGRESSION EQUATION.—

MID-DEPTH SENSOR (A): SSC = 0.768 × NTU + 15.5.

MID-DEPTH SENSOR (B): SSC = 0.486 × mV + 4.3.

NEAR-BOTTOM SENSOR (A): SSC = 1.193 × NTU + 4.5.

NEAR-BOTTOM SENSOR (B): SSC = 0.620 × mV - 17.6.

NONPARAMETRIC PREDICTION INTERVAL.—

MID-DEPTH SENSOR (A): +3 to -12 mg/L.

MID-DEPTH SENSOR (B): +20 to -9 mg/L.

NEAR-BOTTOM SENSOR (A): +16 to -7 mg/L.

NEAR-BOTTOM SENSOR (B): +15 to -16 mg/L.

95-PERCENT CONFIDENCE INTERVAL ON SLOPE CALCULATION.—

MID-DEPTH SENSOR (A): -0.208 to 1.243.

MID-DEPTH SENSOR (B): 0.100 to 0.650.

NEAR-BOTTOM SENSOR (A): 0.889 to 1.491.

NEAR-BOTTOM SENSOR (B): 0.499 to 0.700.

REMARKS.—Interruptions in record were caused by fouling or malfunction of the sensing and(or) recording instruments. 

The mid-depth sonde was replaced with an optical sensor on April 20, 2005. The near-bottom sonde malfunctioned and was 

replaced on January 6, 2005. The near-bottom sonde malfunctioned on March 30, 2005 and was replaced with an optical sensor on April 20, 2005. Because the sondes optical sensors responded similarly to the uniform sediment characteristics of San 

Francisco Bay (Schoellhamer and others, 2003), the near-bottom calibration used from October 1, 2004, to March 30, 2005 was 

developed by combining water samples collected during each optical sensor deployment. The calculated SSC time-series data 

collected for WY 2005 are presented in figure 27.

40 Summary of Suspended-Sediment Concentration Data, San Francisco Bay, California, Water Year 2005
0 10 20 30 40 50 60

0

10

20

30

40

50

60

70

80

SENSOR OUTPUT, IN NEPHELOMETRIC TURBIDITY UNITS

Number of data points = 8

Calibration equation: SSC = 0.768 x NTU + 15.5

Non-parametric prediction interval: + 3 to -12

95 percent confidence interval on equation slope (0.768): -0.208 to 1.243

Kendall tau used for confidence interval calculation with small data set

0 50 100 150 200 250

0

60

120

180

SENSOR OUTPUT, IN MILLIVOLTS

SUSPENDED-SEDIMENT CONCENTRATIONS, IN MILLIGRAMS PER LITER

Number of data points = 7

Calibration equation: SSC = 0.486 x mV + 4.3

Non-parametric prediction interval: + 20 to -9

95 percent confidence interval on equation slope (0.486): 0.100 to 0.650

Kendall tau used for confidence interval calculation with small data set

A

B

Figure 25. Graphs showing calibration of mid-depth optical sensors, October 13–April 20 and April 20–

September 30 at Channel Marker 17, South San Francisco Bay, California, water year 2005.

Sensor Calibration and Suspended-Sediment Concentration Data  41
0 20 40 60 80 100 120 140

0

50

100

150

200

250

SENSOR OUTPUT, IN NEPHELOMETRIC TURBIDITY UNITS

SUSPENDED-SEDIMENT CONCENTRATIONS, IN MILLIGRAMS PER LITER

Number of data points = 23

Calibration equation: SSC = 1.193 x NTU + 4.5

Non-parametric prediction interval: + 16 to -7

95 percent confidence interval on equation slope (1.193): 0.889 to 1.491

0 50 100 150 200 250 300 350 400

0

50

100

150

200

250

300

SENSOR OUTPUT, IN MILLIVOLTS

Number of data points = 16

Calibration equation: SSC = 0.620 x mV - 17.6

Non-parametric prediction interval: + 15 to -16

95 percent confidence interval on equation slope (0.620): 0.499 to 0.700

A

B

Figure 26. Graphs showing calibration of near-bottom optical sensors, October 1–March 30 and April 20 –September 30 

at Channel Marker 17, South San Francisco Bay, California, water year 2005.

42 Summary of Suspended-Sediment Concentration Data, San Francisco Bay, California, Water Year 2005
0

100

200

300

400

500

600

700

800

SUSPENDED-SEDIMENT CONCENTRATION, IN MILLIGRAMS PER LITER

2 0 0 4 2 0 0 5

0

100

200

300

400

500

600

700

800

2 0 0 4 2 0 0 5

A

B

OCT. NOV. DEC. JAN. FEB. MAR. APR. MAY JUNE JULY AUG. SEPT.

OCT. NOV. DEC. JAN. FEB. MAR. APR. MAY JUNE JULY AUG. SEPT.

Figure 27. Graphs showing time series of mid-depth and near-bottom suspended-sediment concentrations calculated 

from sensor readings at Channel Marker 17, South San Francisco Bay, California, water year 2005.

Sensor Calibration and Suspended-Sediment Concentration Data  43
Summary

Suspended-sediment concentration (SSC) data were collected by the U.S. Geological Survey (USGS) at two sites in Suisun 

Bay, three sites in San Pablo Bay, two sites in Central San Francisco Bay, and three sites in South San Francisco Bay during 

water year 2005. Three types of optical sensors, each controlled by electronic data loggers, were used to monitor suspended 

sediment. Water samples were collected to calibrate the output of the optical sensors to SSC by using robust, nonparametric 

regression. Water-sample sediment-concentration data are available in the USGS Sediment Laboratory Environmental Database. 

Time-series data are available in the USGS sediment database and the USGS automated data-processing system database. The 

calculated SSC data are available from the USGS (accessed February 26, 2007).

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46  Summary of Suspended-Sediment Concentration Data, San Francisco Bay, California, Water Year 2005