National Park Service

U.S. Department of the Interior

Natural Resource Program Center

Fort Collins, Colorado

San Francisco Bay Area Network Freshwater Quality 

Monitoring Protocol

Version 2.11 October 2006

Natural Resource Report NPS/SFAN/NRR—2006/016

 
ON THE COVER 

Watercourses in the San Francisco Bay Area Inventory and Monitoring Netowork 

Digital images courtesy of NPS. 
San Francisco Bay Area Network Freshwater Quality 

Monitoring Protocol

Natural Resource Report NPS/SFAN/NRR—2006/016

Mary A. Cooprider (Water Quality Specialist) and Rob G. Carson (Water Quality Specialist)

Inventory and Monitoring Program 

San Francisco Bay Area Network (SFAN)

Golden Gate National Recreation Area

Fort Cronkhite

Sausalito, CA 94965

October 2006

U.S. Department of the Interior

National Park Service

Natural Resource Program Center

Fort Collins, Colorado
ii

The Natural Resource Publication series addresses natural resource topics that are of interest and 

applicability to a broad readership in the National Park Service and to others in the management 

of natural resources, including the scientific community, the public, and the NPS conservation 

and environmental constituencies. Manuscripts are peer-reviewed to ensure that the information 

is scientifically credible, technically accurate, appropriately written for the intended audience, 

and is designed and published in a professional manner.

Natural Resource Reports are the designated medium for disseminating high priority, current 

natural resource management information with managerial application. The series targets a 

general, diverse audience, and may contain NPS policy considerations or address sensitive issues 

of management applicability. Examples of the diverse array of reports published in this series 

include vital signs monitoring plans; "how to" resource management papers; proceedings of 

resource management workshops or conferences; annual reports of resource programs or

divisions of the Natural Resource Program Center; resource action plans; fact sheets; and 

regularly-published newsletters.

Views and conclusions in this report are those of the authors and do not necessarily reflect 

policies of the National Park Service. Mention of trade names or commercial products does not 

constitute endorsement or recommendation for use by the National Park Service.

Printed copies of reports in these series may be produced in a limited quantity and they are only 

available as long as the supply lasts. This report is also available from the Natural Resource 

Publications Management website (http://www.nature.nps.gov/im/units/SFAN) on the Internet or 

by sending a request to the address on the back cover.

Please cite this publication as:

Cooprider, M.A. and R.G. Carson. 2006. San Francisco Bay Area Network Freshwater Quality 

Monitor Protocol Version 2.11. NPS/SFAN/NRR – 2006/016. National Park Service, Fort 

Collins, Colorado.

NPS D-39, October 2006
iii

Change History

Prev. 

Version #

Revision 

Date

Author Changes Made Reason for Change New 

Version #

1.00 2-16-05 Mary 

Cooprider

Added stream miles table 

for GPRA goals, addressed 

comments from WRD on 

QA/QC, added SOP 1

Clarification of existing 

information, minor edits 

1.01

1.01 5-13-05 Mary 

Cooprider

Incorporated comments 

from internal peer view. 

Several small changes; 

sampling design change; 

QAPP changes

Clarification of existing 

information, addition of 

information, refining 

methods and parameters

2.0

2.0 7-29-05 Mary 

Cooprider

Added abstract and maps; 

updated tables; 

incorporated comments 

from technical peer review

Finalizing draft for 

formal peer review

2.01

2.01 3/9/06 Rob Carson Edits to text and tables Addressing peer 

reviewer comments

2.02

2.02 9/28/06 Rob Carson Addresses Sampling 

Design Issues & Data 

Management Section

Addressing peer 

reviewer concerns

2.1

2.1 10/12/06 Rob Carson Minor clarification of 

Table 2.5, the discussion of 

table 2.9, and some text in 

section 2.4

Suggestions from WRD 

prior to approval

2.11

1. ―Version numbers increase incrementally by hundredths (e.g. version 1.01, version 1.02 

...etc) for minor changes. Major revisions should be designated with the next whole number 

(e.g., version 2.0, 3.0, 4.0 ...). Record the previous version number, date of revision, author 

of the revision, identify paragraphs and pages where changes are made, and the reason for 

making the changes along with the new version number‖ (Peitz et al., 2002).

2. Notify the SFAN Lead Data Manager of any changes to the Protocol Narrative or SOP so 

that the new version number can be incorporated in the Metadata of the NPSTORET 

database. The Data Manager will then edit the database per any changes to the Protocol 

Narrative and SOPs.

3. Post new versions on the internet and forward copies to all individuals with a previous 

version of the Protocol Narrative or SOP.
iv

Contents

Page

Change History ..............................................................................................................................iii

Contents......................................................................................................................................... iv

Figures............................................................................................................................................ vi

Tables............................................................................................................................................ vii

Appendixes .................................................................................................................................... ix

Acronyms and Abbreviations ......................................................................................................... x

Acknowledgements....................................................................................................................... xii

Abstract........................................................................................................................................ xiii

1.0 Background and Objectives...................................................................................................... 1

1.1 Introduction & Purpose........................................................................................................ 1

1.2 Rationale for Selecting this Resource to Monitor.............................................................. 15

1.3 Measurable Results and Deliverables................................................................................ 17

2.0 Sampling Design..................................................................................................................... 19

2.1 Rationale For Selecting This Sampling Design Over Others ............................................ 19

2.2 Site Selection ..................................................................................................................... 22

2.3 Selection of parameters and protocols............................................................................... 28

2.4 Sampling Frequency and Replication ................................................................................ 34

3.0 Field and Laboratory Methods................................................................................................ 39

3.1 Standard Operating Procedures......................................................................................... 39

3.2 Field and Laboratory Methods Overview.......................................................................... 42

4.0 Data Handling, Analysis and Reporting ................................................................................. 45

4.1 Metadata Procedures.......................................................................................................... 45

4.2 Overview of Database Design ........................................................................................... 45
v

Contents (continued)

Page

4.3 Data entry, verification and editing ................................................................................... 48

4.4 Routine data summaries and statistical analyses to detect change .................................... 49

4.5 Reporting schedule and format .......................................................................................... 52

4.6 Data archiving procedures ................................................................................................. 54

5.0 Personnel Requirements and Training .................................................................................... 55

5.1 Roles and responsibilities .................................................................................................. 55

5.2 Qualifications and training................................................................................................. 57

6.0 Operational Requirements ...................................................................................................... 59

6.1 Annual workload and field schedule.................................................................................. 59

6. 2 Key Partnerships and Access Requirements..................................................................... 59

6.3 Facility and equipment needs............................................................................................. 59

6.4 Startup costs and budget considerations............................................................................ 60

7.0 References............................................................................................................................... 63
vi

Figures

Page

Figure 1. Map of San Francisco Bay Area Network Parks (created by Jason Herynk, National 

Park Service, 2005).......................................................................................................... 2
vii

Tables

Page

Table 1. Collective beneficial uses of SFAN water bodies. ........................................................... 5

Table 2. General numeric objectives for physical parameters in surface waters in the San 

Francisco Bay Area (from San Francisco Bay Regional Water Quality Control Board, 

1995). ................................................................................................................................ 6

Table 3. Recommended criteria for nutrients. ................................................................................ 7

Table 4. Recommended criteria for sediment. ................................................................................ 7

Table 5. U.S. EPA bacteriological criteria for contact recreation (REC1). .................................... 8

Table 6. Water quality objectives for coliform bacteria (from San Francisco Bay Regional Water 

Quality Control Board, 1995). .......................................................................................... 9

Table 7. Stream and shoreline miles of impaired waters within SFAN........................................ 11

Table 8. Impaired water bodies in the SFAN. .............................................................................. 12

Table 9. San Francisco Bay Regional Water Quality Control Board TMDL Project Timeline as 

of June 2005.................................................................................................................... 13

Table 10. Choosing a sampling design based on monitoring questions. ...................................... 20

Table 11. High priority streams. ................................................................................................... 26

Table 12. Medium priority streams............................................................................................... 27

Table 13. Low Priority Streams. ................................................................................................... 27

Table 14. Target streams, parameters, and protocols to be monitored. ........................................ 30

Table 15. Overview of SFAN Data Quality Assurance................................................................ 33

Table 16. Habitat Sampling .......................................................................................................... 35

Table 17. General Water Quality Monitoring Schedule. .............................................................. 35

Table 18. Sample Size Summary for SFAN Priority Streams. ..................................................... 36

Table 19. Minimum Detectable Differences for 1-year intervals of SFAN Sampling Design..... 37

Table 20. Overview of NPSTORET Database Structure.............................................................. 46

Table 21. Sampling Designs and Data Analysis Based on Monitoring Questions....................... 51
viii

Tables (continued) 

Table 22. Summary of reporting and communication products. .................................................. 53
ix

Appendixes

Appendix A. Beneficial Uses of the SFAN Water Bodies

Appendix B. Water Quality Monitoring Stages

Appendix C. Selection Criteria of the SFAN ―Target‖ Water Bodies

Appendix D. Specific Monitoring Questions and Related Sample Location and Monitoring 

Questions for Each Stream

Appendix E. Water Quality Monitoring Site Location and Access and Site History and Site ID 

Selection

.

Appendix F. Maps of Watersheds and Sampling Locations

Appendix H. Standard Operating Procedures
x

Acronyms and Abbreviations

ASBS Area of Special Biological Significance

AWAG Alhambra Watershed Action Group, Martinez, CA

BMP Best Management Practice

BO Biological Opinion

BU Beneficial Use

CALM Consolidated Assessment and Listing Methodology (EPA)

CCCR Central California Coast Biosphere Reserve

CCSF City and County of San Francisco

CDFG California Department of Fish and Game

COE Army Corps of Engineers

CSRP Coho and Steelhead Restoration Project

CWA Clean Water Act

DDT Dichloro-Diphenyl-Trichloroethane

DHS California Department of Health Services

DMMO Dredged Materials Management Office

DO Dissolved Oxygen

EBRPD East Bay Regional Park District

ENSO El Niño Southern Oscillation

EPA (United States) Environmental Protection Agency

EUON Eugene O’Neill National Historic Site

FDA (United States) Food and Drug Administration

FIB Fecal Indicator Bacteria

FOPO Fort Point National Historic Site

GFNMS Gulf of the Farallones National Marine Sanctuary

GMA General Minerals Analysis

GOGA Golden Gate National Recreation Area 

GPRA Government Performance and Results Act

HI Headlands Institute

HUC Hydrologic Unit Code

I&M Inventory & Monitoring 

IPM Integrated Pest Management

IQR Interquartile Range (statistical value)

MDL Method Detection Limit

MMC Marine Mammal Center, Sausalito, CA

MMWD Marin Municipal Water District

MPA Marine Protected Areas

MPN Most Probable Number (of bacteria)

MQO Measurement Quality Objective

ML Minimum Level of Quantitation

MUWO Muir Woods National Monument

NAWQA National Water Quality Assessment (USGS Program)

NFM National Field Manual (USGS)

NMFS National Marine Fisheries Service

NOAA National Oceanic and Atmospheric Administration
xi

Acronyms and Abbreviations (continued)

NPSTORET National Park Service version of EPA’s STORET database

ONRW Outstanding Natural Resource Water

PCB Polychlorinated Biphenyls

PINN Pinnacles National Monument

PORE Point Reyes National Seashore 

PQL Practical Quantitation Limit

PRBO Point Reyes Bird Observatory

PRES Presidio of San Francisco

QAPP Quality Assurance Project Plan

QA/QC Quality Assurance/Quality Control

RWQCB Regional Water Quality Control Board

SBWD Stinson Beach Water District

SCCWRP Southern California Coastal Water Research Project

SFAN San Francisco Bay Area Network 

SFEI San Francisco Estuary Institute

SFRWQCB San Francisco Bay Regional Water Quality Control Board

SOP Standard Operating Procedure

SSC Suspended Sediment Concentration

STORET Storage and Retrieval (EPA’s Water Quality database)

SWAMP Surface Water Ambient Monitoring Program

SWRCB State (CA) Water Resources Control Board

TBAG Tomales Bay Agricultural Group

TBSTAC Tomales Bay Shellfish Technical Advisory Committee

TBWC Tomales Bay Watershed Council

T&E Threatened and Endangered Species

TKN Total Kjeldahl Nitrogen

TMDL Total Maximum Daily Load

TSS Total Suspended Solids

TTS Turbidity Threshold Sampling

UCB University of California-Berkeley

UCCE University of California Cooperative Extension

UNESCO United Nations Educational, Scientific, and Cultural Organization

USGS United States Geological Survey

UWP Urban Watershed Project

WRD Water Resources Division (National Park Service)

WTP Water Treatment Plant
xii

Acknowledgements

Authors would like to thank the following individuals for their expertise and guidance during the 

development of this monitoring plan: Dawn Adams, Marie Denn, Darren Fong, Jason Herynk, 

Alex Horne, Roy Irwin, Brannon Ketcham, Randy Klein, Peter Krottje, David Lewis, Susan 

O’Neil, Susan O’Neil, Dave Press, Dale Roberts, Sarah Stafford, Kristen Ward, and Tamara 

Williams. 
xiii

Abstract

The National Park Service Inventory and Monitoring (I&M) Program measures long-term 

changes in the condition of natural resources throughout the National Park System. As part of 

this effort, the San Francisco Bay Area Network (SFAN), which encompasses Eugene O’Neil 

National Historic Site, Fort Point National Historic Site, Golden Gate National Recreation Area, 

John Muir National Historic Site, Muir Woods National Monument, Pinnacles National 

Monument, Point Reyes National Seashore, and the Presidio of San Francisco, has developed a 

detailed water quality monitoring plan. The plan consists of three sections: 1) a protocol 

narrative, 2) standard operating procedures (SOPs), and 3) supplementary materials. The 

protocol narrative summarizes the significance of aquatic resources in the SFAN with a focus on 

beneficial uses of freshwater streams. The narrative also discusses the SFAN waters listed as 

impaired under the Clean Water Act section 303d and describes associated Total Maximum 

Daily Load (TMDL) projects. The narrative defines the network’s water quality criteria and 

monitoring questions and discusses the use of a rotating basin design and a decision table for 

selecting streams and monitoring sites. The protocol narrative addresses all aspects of data 

management and storage and provides an overview of water quality data analysis. Finally, the 

narrative discusses the expected program budget and personnel qualifications. Specific SOPs 

prescribe personnel training procedures, methods of protocol revision, field equipment 

preparations, quality assurance/quality control, data analysis and reporting, and monitoring site 

establishment. Additional SOPs address procedures for sampling specific parameters including 

core water chemistry (temperature, pH, dissolved oxygen, and conductivity), bacteria, nutrients, 

sediment, and stream flow. The protocol narrative and SOPs follow techniques outlined by the 

U.S. Geological Survey (USGS), the State Water Resources Control Board Surface Water 

Ambient Monitoring Program, and the U.S. Environmental Protection Agency’s Western Pilot 

Study Field Manual for Wadeable Streams. Supplementary materials include a preliminary 

water quality status report for the SFAN, the USGS National Field Manual (on CD), and a USGS 

tutorial (on CD) for taking flow measurements. The comprehensive collection of information in 

the protocol narrative, SOPs, and supplementary materials is intended to standardize water 

quality monitoring and ensure that methods and data are comparable and effective in the longterm.
xiv
1

1.0 Background and Objectives

1.1 Introduction & Purpose

Ecosystem vital signs are key to the National Park Service’s (NPS) Inventory and Monitoring 

Program (I&M). A vital sign is a physical, chemical, or biological component of the air, water, 

or land. It is rarely possible to monitor all components, or indicators, of ecosystem health; 

therefore, vital signs are chosen since they are the most representative of the ecosystem as a 

whole and/or are most critical to ecosystem function. A goal of NPS Vital Signs Monitoring is 

to report ecosystem status and trends and to document how much confidence there is in the 

results. A good summary of vital signs monitoring is provided in An Overview of Vital Signs 

Monitoring and its Central Role in Natural Resource Stewardship and Performance Management 

(Fancy, 2005). It states that:

Knowing the condition of natural resources in national parks is fundamental to the 

National Park Service’s ability to manage park resources. Vital signs monitoring is a key 

component in the Service’s strategy to provide scientific data and information needed for 

management decision-making and education. Vital signs monitoring also contributes 

information needed to understand and to measure performance regarding the condition of 

watersheds, landscapes, marine resources, and biological communities. 

Through the NPS I&M program, 270 national park units were organized into 32 networks. In 

order to improve efficiency and reduce costs, parks were organized into networks that share 

similar geographic and natural resource characteristics. These networks share funding and a core 

professional staff to conduct long-term ecological monitoring (Fancy, 2005). The San Francisco 

Bay Area Network (SFAN) includes Eugene O’Neill (EUON) and John Muir (JOMU) National 

Historic Sites in Contra Costa County, Fort Point National Historic Site (FOPO) and the Presidio 

of San Francisco (PRES) in San Francisco County, and Muir Woods National Monument 

(MUWO) and Point Reyes National Seashore (PORE) in Marin County. Golden Gate National 

Recreation (GOGA) is located in Marin, San Francisco, and San Mateo Counties. Pinnacles 

National Monument (PINN) is located southeast of Monterey in San Benito County. Figure 1.1 

shows the location of each of the parks. 

Freshwater quality monitoring was funded through a NPS Water Resources Division (WRD) 

initiative and was also recognized as significant at the network level. The significance of water 

resources within SFAN is reflected in the network’s ranking of freshwater quality as 3rd among 

all of the potential vital signs identified and prioritized by the SFAN. Freshwater quality has 

direct impact on several other indicators including: marine water quality, stream threatened and 

endangered (T&E) species and fish assemblages, T&E amphibians and reptiles, riparian habitat, 

wetlands, and aquatic macroinvertebrates. Freshwater quality has indirect impacts on all plant 

and animal life as well as human consumption, recreation, and enjoyment (i.e., the intrinsic value 

of water). Much of what is on the land is transferred to water via surface runoff, subsurface 

flow, and base flow (groundwater). Therefore, not only is water quality an indicator of the 

health of aquatic systems, but it is an important indicator of overall ecosystem health.
2

Figure 1. Map of San Francisco Bay Area Network Parks (created by Jason Herynk, National 

Park Service, 2005). 

San Francisco Area Network Nat1ona1 Park serv1ce ·,~ ·: · ~..-. 

Fresh Water Qual1ty Mon1tonng us Department of the Intenor .., 

D Watersheds 

- Point Reyes Administrative Boundary 

c::::J Golden Gate Legislative Boundary 

John Muir Legislative Boundary 

10 20 30 

Miles 

Monterey 
3

SFAN has many unique aquatic resources that are significant in an ecological and socioeconomic context. Aquatic resources in the SFAN include streams, bays, estuaries, lagoons, 

lakes, reservoirs, freshwater and estuarine marshes, seeps, and springs. The combination of 

marine and freshwater aquatic systems within the network supports a variety of federal and state 

listed threatened and endangered aquatic species including the California freshwater shrimp 

(Syncharis pacifica), coho salmon (Oncorhynchus kisutch), steelhead trout (Oncorhynchus 

mykiss), the California red-legged frog (Rana aurora draytonii), tidewater goby (Eucyclogobius 

newberryi ), Tomales roach (Lavinina symmetricus ssp 2), and northwest pond turtle (Clemmys 

marmorata mormorata). Commercial operations include a significant herring fishery in 

Tomales Bay and San Francisco Bay, oyster growing/harvesting in Tomales Bay and Drakes 

Estero, and clam and mussel operations in Tomales Bay. Oysters have not been commercially 

harvested in San Francisco Bay since 1910. 

Watershed conditions vary from coastal watersheds in wilderness areas to an urbanized 

watershed managed as public water supply. Lobos Creek in the Presidio of San Francisco is the 

only free-flowing (above ground) creek in the city and is the public water supply for the Presidio. 

Land uses within the more rural watersheds include agricultural and commercial operations (e.g., 

beef and dairy cattle ranching, vegetable farming, viticulture, oyster harvesting, and equestrian 

use) as well as predominantly wilderness areas.

The Mediterranean climate of the San Francisco Bay Region creates wet winters followed by dry 

summers. The resulting hydrology is flashy, with high runoff in the winter, and very low to 

intermittent flow dominating summer conditions. In response to flashy hydrologic conditions 

and the highly active geologic processes associated with the San Andreas Fault system, most 

stream channels are geomorphically dynamic. Chalone Creek in PINN includes a highly mobile 

sand bed that typically dries in the summer months. Watersheds within JOMU and the 

developed portions of GOGA are highly altered by development and urbanization. These 

systems are highly confined/constrained, with many natural processes engineered out of the 

stream systems. Within the Marin and San Mateo Counties portions of GOGA, as well as 

PORE, watersheds are fairly stable and support threatened coho salmon and steelhead trout. 

Although generally unaltered, stream systems in these areas have been impacted by historic and 

current agricultural activities as well as more dispersed development including roads and trails. 

Several NPS efforts to improve water resources within SFAN are underway. The Redwood 

Creek watershed (GOGA/MUWO) is currently the focus of a variety of activities including 

watershed planning, transportation planning, water quality and water rights evaluations, sensitive 

species monitoring, aquatic system and riparian restoration, invasive non-native plant removal 

and habitat restoration, and GIS mapping of all watershed features. Similar activities are 

occurring throughout the network. Several stream restoration projects are on-going at PORE 

including bank stabilization, dam removal, and culvert removal projects. Restoration efforts for 

Chalone Creek (PINN) and its floodplain have also been initiated. Streambank restoration 

(including removal of invasive plants, erosion control, and bank stabilization) is proposed along 

Franklin Creek (JOMU), as well as a dam removal project in the Strentzel Creek (JOMU) 

watershed. Tidal wetland restoration efforts are on-going at PORE, GOGA, and PRES. 

Wetlands inventories and functional assessments are being conducted at GOGA (funded by the 

I&M program), as well as PORE (funding through NPS-WRD). In addition, a watershed project 
4

aimed at ―daylighting‖ Tennessee Hollow Creek (PRES) and improving its ecological integrity is 

underway. Restoration efforts have primarily focused on the protection and restoration of natural 

physical processes, habitat known to benefit T&E aquatic species, and water quality. 

The purpose of this Protocol Narrative is to address all of the significant issues that need to be 

considered when developing a long-term monitoring plan for freshwater quality. It documents 

the decision making processes involved in prioritizing streams, selecting sites, and selecting 

parameters to monitor and associated methods. The Protocol Narrative also provides a summary 

of monitoring methods, data management and reporting, and staff and budget considerations. 

This document provides a brief summary of SFAN water resources and an overview of water 

quality monitoring efforts. A more thorough review of surface hydrology and water resources, 

water quality monitoring efforts, and water quality issues and priorities is included in the ―SFAN 

Preliminary Water Quality Status Report‖ (Cooprider, 2004). Details related to sampling 

methods, including safety and quality assurance/quality control (QA/QC) are included in 

individual Standard Operating Procedures (SOP) on each water quality parameter or group of 

parameters. 

Many of the SOPs in the SFAN Freshwater Quality Protocol rely heavily on State and Federal 

protocols such as those published by the California State Water Resources Control Board 

(SWRCB), U.S. Geological Survey (USGS), and the U.S. Environmental Protection Agency 

(EPA). In most cases, when protocols differed among agencies, the State protocol was followed 

since they are most involved in monitoring on park lands. Other I&M network protocols were 

also consulted for consistency in protocol format and content. Ultimately, protocols were chosen 

based on the monitoring objectives. ―Parks are encouraged to use or modify standard protocols 

and partner with existing programs wherever possible to allow comparability and synthesis of 

data at multiple scales, but the primary use of the data is at the park level for management 

decisions‖ (Fancy, 2005). 

1.1.1 Beneficial Uses

All of the park units except PINN are regulated by the San Francisco Bay Regional Water 

Quality Control Board. There are nine Regional Water Quality Control Boards (―Regional 

Boards‖) that are part of the California State Water Resources Control Board, a department of 

the California Environmental Protection Agency. Pinnacles NM is within the Central California 

Coast Regional Water Quality Control Board. Management criteria for water bodies within the 

state of California are established by the Regional Boards. Through their water quality control 

plans (also referred to as basin plans), the Regional Boards established beneficial uses for 

streams and set numeric and narrative criteria to meet those surface water use objectives.

The primary water quality issues within SFAN relate to whether or not streams are supporting 

the beneficial uses established by the Regional Boards. Table 1 includes the beneficial uses of 

all SFAN water bodies combined (streams, Pacific Ocean, etc). The beneficial uses of SFAN 

water bodies are numerous and this is a testament to the significance of water resources within 

the network. A list of beneficial uses for individual SFAN water bodies is included in Appendix 

A. The full definitions of beneficial uses are also included in Appendix A. 
5

Table 1. Collective beneficial uses of SFAN water bodies.

Acronym Definition

AGR Agricultural Supply 

COLD Cold Freshwater Habitat

COMM Commercial and Sport Fishing

EST Estuarine Habitat

FRSH Freshwater Replenishment

GWR Groundwater Recharge

IND Industrial Service Supply

MAR Marine Habitat

MIGR Fish Migration

MUN Municipal Supply

NAV Navigation

PROC Industrial Process Supply

RARE Preservation of Rare and Endangered Species

REC1 Contact Water Recreation

REC2 Non-contact Water Recreation

SHELL Shellfish Harvesting

SPWN Fish Spawning

WARM Warm Freshwater Habitat

WILD Wildlife Habitat

1.1.2 Water Quality Criteria

Water quality standards are key components of the water quality-based control program 

mandated by the Clean Water Act (CWA). Designated use classifications and numerical and/or 

narrative water quality criteria are two types of water quality standards. The CWA requires all 

States to establish use classifications for all water bodies within the State. These beneficial uses 

were discussed in Section 1.1.1. Water quality criteria are numeric descriptions of the physical, 

chemical, and biological characteristics of waters necessary to support these designated 

beneficial uses.

The RWQCB Basin Plans include numeric and narrative water quality objectives for surface 

water. General water quality objectives for estuarine and marine waters are also included. 

However, a separate document, the Ocean Plan, was produced by the California SWRCB to 

regulate ocean waters (California State Water Resources Control Board, 2001). 

Table 2 lists general numeric objectives for all inland surface waters, enclosed bays, and 

estuaries in the San Francisco Bay Area (San Francisco Bay Regional Water Quality Control 

Board, 1995). These general objectives can be used to determine whether water bodies are 

meeting specific beneficial uses. For example, un-ionized ammonia levels above the water 

quality objective would hinder the ability of a stream to support healthy aquatic life (e.g., fish 

spawning). This would then trigger a management action to reduce the inputs of nitrogen to the 

streams. It may also dictate more frequent sampling of nutrients, pH, and temperature – factors 

that affect the amount of ammonia in a stream. 

Some of the water quality objectives for inland surface waters, enclosed bays, and estuaries 

within the Central Coast Regional Water Quality Control Board where PINN is located are 

slightly different than those listed in Table 2. For example, the numeric objective for pH is 7.0 

to 8.5. The general objective for dissolved oxygen is > 5.0 mg/L (Central Coast Regional Water 
6

Quality Control Board, 1998). However, for the specific beneficial uses COLD and SPWN, the 

objective is 7.0 mg/L.

Table 2. General numeric objectives for physical parameters in surface waters in the San 

Francisco Bay Area (from San Francisco Bay Regional Water Quality Control Board, 1995).

Parameter Water Quality Objective 

Dissolved oxygen 

(tidal waters)

Downstream of Carquinez bridge:

5.0 milligrams per liter (mg/L) minimum

Upstream* of Carquinez bridge: 

7.0 mg/L minimum

Dissolved oxygen

(non-tidal waters)

Cold water habitat 7.0 mg/L minimum

Warm water habitat 5.0 mg/L minimum

pH Less than 8.5 and greater than 6.5

Un-ionized ammonia Annual Median 0.025 mg/L as nitrogen (N) (freshwater) 

Maximum Central San Francisco Bay 0.16 mg/L (N) (estuarine)

* A more stringent minimum objective is desirable for the northern reach of the Bay for the 

protection of cold water fish habitat as well as protection of the migratory corridor running 

through Central Bay, San Pablo Bay, and upstream reaches.

Several other parameters that are important to the SFAN water quality monitoring program do 

not have ambient surface water quality objectives established by the Regional Boards. In these 

cases, Tables 3 and 4 can be consulted. Table 3 lists nutrient criteria and recommendations from 

several different sources. 

The numbers are based on both human health criteria and overall aquatic health. Chronic human 

toxicity for nitrate occurs at 10 mg/L (San Francisco Bay Regional Water Quality Control Board, 

1995). However, this may not be stringent enough for aquatic life (San Francisco Bay Regional 

Water Quality Control Board, 2003b). Chronic toxicity to aquatic life, especially fish and 

amphibian eggs, can occur at 1.1 mg/L (Kincheloe et al., 1979; Crunkilton, 2000). Nutrient 

levels at which algal growth limitation begins are less than 0.5 mg/L for total nitrogen and 0.1 

mg/L for total phosphorus (Bowie et al., 1985).

Recent EPA criteria are based on Ambient Water Quality Criteria Recommendations for 

Ecoregions across the country (U.S. Environmental Protection Agency, 2000). A map of the 

ecoregions can be found at: http://www.epa.gov/waterscience/criteria/nutrient/ecomap.html.

During the development of nutrient criteria for the ecoregions, several sources of data were 

consulted including historical and recent nutrient data and reference sites. Ecoregion III (Xeric 

West) covers PINN and JOMU while Ecoregion II (Western Forested Mountains) covers PORE 

and GOGA. Recommended criteria for Ecoregions II and III are listed in Table 3. These are 

not regulations but are intended to be ―starting points‖ for states and tribes developing water 

quality standards (U.S. Environmental Protection Agency, 2000a). The EPA Ecoregion values in 

Table 3 represent nutrient levels that are generally protective of nutrient over enrichment. 

However, ―States and Tribes should evaluate the information in light of the specific designated 

uses that need to be protected‖ (U.S. Environmental Protection Agency, 2000a). Conversely, 
7

overly stringent criteria may actually fall below levels of nutrient loading that naturally occur. 

The EPA encourages the states to develop more refined criteria through the use of local data. 

There are also various recommendations for the sediment parameters total suspended solids and 

turbidity (Table 4). Similarly, nutrient levels can be compared to several different thresholds 

until targets or Total Maximum Daily Loads (TMDL) are set. SFAN will utilize this ―multiple 

thresholds‖ concept for data analysis. The effects of nutrients and sediment on water quality are 

discussed further in standard operating procedures in Appendix H.

Table 3. Recommended criteria for nutrients.

Parameter EPA Quality 

Criteria for 

Water (1986)

EPA 

Aggregate 

Ecoregion II 

Criteria 

(2000b)

EPA 

Aggregate 

Ecoregion III 

Criteria 

(2000a)

Kincheloe et 

al., 1979; 

Crunkilton, 

2000

Bowie et 

al., 1985

Total Phosphorus

(P)

0.1 mg/L 10 ug/L 21.88 ug/L 0.1 mg/L

Total Phosphates 

as P

50 ug/L

Total Nitrogen 0.12 mg/L 0.38 mg/L 0.5 mg/L

Nitrate 10 mg/L 1.1 mg/L

Table 4. Recommended criteria for sediment.

Sigler et al., 

1984

Newcomb and 

Jensen, 1996

EPA 

Aggregate 

Ecoregion II 

Criteria (2003)

EPA 

Aggregate 

Ecoregion III 

Criteria (2003)

Acute Total Suspended Solids > 50 mg/L

Chronic (>6 days) Total 

Suspended Solids (TSS)

> 10 mg/L

Turbidity 25 NTU 1.30 NTU 2.34 NTU

Total suspended solids are listed in milligrams per liter (mg/L)



Turbidity is listed as nephelometric turbidity units (NTU)

Only three beneficial uses within SFAN have specified bacterial objectives. These include 

contact recreation, non-contact recreation, and shellfish harvesting (Table 5). Many water bodies 

in SFAN meet the definition of non-contact recreation and some meet the definition for contact 

recreation (see Appendix A for complete list). The Regional Boards define contact recreation 

(REC1) as: 

Uses of water for recreational activities involving body contact with water where 

ingestion of water is reasonably possible. These uses include but are not limited to, 
8

swimming, wading, water-skiing, skin and scuba diving, surfing, whitewater activities,

fishing, and uses of natural hot springs.‖ Non-contact water recreation (REC2) is defined 

as: ―Uses of water for recreational activities involving proximity to water, but not 

normally involving contact with water where ingestion is reasonably possible. These 

uses include but are not limited to, picnicking, sunbathing, hiking, beachcombing, 

camping, boating, tide pool and marine life study, hunting, sightseeing, or aesthetic 

enjoyment in conjunction with the above activities. 

 San Francisco Bay Regional Water Quality Control Board, 1995 

Additional detailed criteria specifically for contact recreation are relevant for SFAN lakes, 

freshwater lagoons, and some streams where swimming or other contact recreation occurs (Table 

6). The California SWQCB’s use total and fecal coliforms as criteria for determining whether 

waters are in compliance with beneficial uses, while the US EPA has established criteria using E. 

coli and Enterococcus as fecal indicator bacteria (FIB). Studies have suggested that E. coli and 

Enterococci have a much more significant correlation to the occurrence of swimming-related 

gastrointestinal illness (USEPA, 1986). Enterococcus typically has greater survival in marine 

waters and is therefore a better indicator of fecal contamination in coastal areas. E. coli is a 

subset of the fecal coliform group, and is judged to be a better indicator of pathogenic bacterial 

contamination in freshwaters. Also, analytical methods for these two indicator bacteria are often 

more efficient and cost effective than those for fecal coliforms alone. 

Consecutive sampling (e.g., five consecutive weeks) to obtain a 30-day geometric mean is a 

necessary component of any monitoring scheme related to the REC1 beneficial use. 

Table 5. U.S. EPA bacteriological criteria for contact recreation (REC1).

Fecal Indicator Bacteria Bacterial Colonies/100mL (MPN)

Total Coliform

Single Day Sample

*30 Day Geometric Mean

10,000

1,000

Fecal coliform

Single Day Sample

*30 Day Geometric Mean

400

200

E. Coli**

Single Day Sample

*30 Day Geometric Mean

235

126

Enterococcus**

Single Day Sample

*30 Day Geometric Mean

61

33

* Geometric mean of five consecutive weeks

**These bacteriological tests are considered ―ancillary‖ for the SFBRWQC; however the EPA 

has adopted E. Coli as the primary test for freshwater recreational uses, and Enterococcus testing 

for marine water recreational uses because they have determined that these tests correlate more 

closely with contact-related illnesses.

Tomales Bay and Drakes Bay support commercial shellfish harvesting. The State Department of 

Health Services (DHS) tests these waters for compliance with the National Shellfish Sanitation 

Program. Since the U.S. Food and Drug Administration (FDA) regulates shellfish consumption 
9

based on fecal coliforms, they are used instead of other fecal indicator bacteria (FIB) such as 

Escherichia coli (E. coli).

Table 6. Water quality objectives for coliform bacteria (from San Francisco Bay Regional Water 

Quality Control Board, 1995).

Beneficial Use Fecal Coliform 

(MPN/100mL)

Total Coliform (MPN/100mL)

Non-contact recreation (REC2) Mean < 2000

90th percentile < 4000

Shellfish harvesting (SHELL) Median < 14

90th percentile < 43

Median < 70

90th percentile < 230

1.1.3 Significant Waters

Some water bodies have been specifically designated as significant due to a variety of factors 

including: biodiversity, ability to support a unique habitat or species, or status as relatively 

undisturbed. There are several significant and unique coastal waters within the San Francisco 

Bay Region. Recognizing the extraordinary significance and exposure to threats in the region, 

United Nations Educational, Scientific, and Cultural Organization (UNESCO) Man in the 

Biosphere program designated the Golden Gate Biosphere Reserve in 1988. This reserve 

encompasses six of the eight SFAN parks and includes coastal waters. The California coast is 

only one of five areas of eastern boundary coastal upwelling oceanic currents worldwide and the 

only one in North America. 

The State Water Resources Control Board established Areas of Special Biological Significance 

(ASBS) in 1974. Five of these are within the legislative boundaries of the SFAN parks. These 

include the Point Reyes Headlands, Bird Rock, Double Point, Duxbury Reef, and the James 

Fitzgerald Marine Preserve. These areas were chosen through a nomination process based 

primarily on habitat quality and limited to coastal areas. The ASBS are all coastal areas since 

inland areas have not yet been assessed. Although this protocol focuses on freshwater quality, it 

is critical to know the significance of coastal ―receiving waters‖ for the freshwater streams 

within SFAN. The procedure for this nomination process is outlined in the California Ocean 

Plan (2001) developed by the State Water Resources Control Board. A Southern California 

Coastal Water Research Project (SCCWRP) report to the State Water Resources Control Board 

addresses issues related to current and potential discharges into these ASBS (SCCWRP, 2003). 

In 2000, the California Department of Fish and Game drafted a Marine Protected Area (MPA) 

plan that proposed including ASBS as primary reserve areas. In January 2003, legislation took 

effect that incorporated previously-designated Areas of Special Biological Significance (ASBS) 

into an established system of State Water Quality Protection Areas (SWQPA). ASBS/SWQPA

are designated as no discharge zones and the SWRCB has established a program to enforce the 

no discharge requirements.

A state publication detailing the location and included resources of State Water Quality 

Protection Areas / Areas of Special Biological Significance can be found at: 

http://www.waterboards.ca.gov/plnspols/oplans/docs/asbs_swqpa_publication03.doc. Maps of 

the five ASBS that are within the legislative boundaries of SFAN parks can be viewed 
10

electronically on the SWRCB website at:

http://www.waterboards.ca.gov/plnspols/asbs_info.html

In addition to the above designations and associated marine protection, several marine 

sanctuaries are located offshore of PORE and GOGA. These include the Gulf of the Farallones 

National Marine Sanctuary, Cordell Bank National Marine Sanctuary, and Monterrey Bay 

National Marine Sanctuary.

1.1.4 Clean Water Act Section 303d Impaired Waters

The EPA requires that States submit a list of water bodies that fail to meet water quality 

standards. These lists are referred to as "303(d) lists" after the section of the CWA which 

contains the requirement. The EPA approves the list only if it meets applicable requirements. 

Water bodies on an approved 303(d) list require the establishment of a total maximum daily load 

(TMDL). A TMDL specifies the amount of a particular pollutant that may be present in a water 

body, allocates allowable pollutant loads among sources, and provides the basis for attaining or 

maintaining water quality standards. 

Water bodies within and adjacent to NPS lands have specifically been identified as impaired by 

the San Francisco Bay Water Quality Control Regional Board and in some cases, the EPA. 

Table 8 lists these water bodies. The Regional Board has established a timeline for development 

of Total Maximum Daily Loads (TMDLs) associated with the highest priority impairment 

listings (Table 9). Not all impaired (Section 303d listed) water bodies currently have TMDL 

projects. For a complete listing of impaired water bodies and a map of current projects see 

Regional Board’s website at:

http://www.waterboards.ca.gov/sanfranciscobay/TMDL/303dlist.htm

The list of impaired miles of water bodies in Table 7 is taken from the NPS Water Resources 

Division (WRD) website http://www1.nrintra.nps.gov/wrd/dui/. It is based on GIS coverage of 

the Section 303d listed water bodies. It is important to note that tributaries of listed water 

bodies are also impaired even though the tributaries themselves may not be listed. Tributary 

miles are not included in the table. In addition, PORE manages the north district GOGA lands 

that include the impaired Lagunitas Creek. The numbers listed in the table below reflect 

management divisions between GOGA and PORE (i.e. north district GOGA lands are included 

in the PORE totals). 

The SFBRWQCB listed all SF Bay area urban streams as impaired by diazinon, although these 

creeks are not specifically listed by name and the presence of this contaminant has not been 

verified. The NPS is currently coordinating with the USGS to conduct baseline monitoring for 

pesticides in these urban creeks. So, while these streams (which include streams in JOMU, 

PRES and GOGA) are potentially impaired, they are not included in 303(d) impaired stream 

miles in the table below.

1.1.4.1 Sediment, Nutrients, and Pathogens: The San Francisco Bay Regional Water Quality 

Control Board has identified Tomales Bay and its tributaries Lagunitas Creek and Walker Creek 

as impaired by fecal coliform, sediment, and nutrients (Table 1.8). Health concerns have arisen 

due to contamination of shellfish with pathogenic bacteria. SFAN and PORE staffs have
11

Table 7. Stream and shoreline miles of impaired waters within SFAN.

Total Stream 

Miles 

(intermittent/p

erennial)

303(d)

Impaired 

Stream 

Miles

Lakes and 

Reservoirs 

Acres

303(d) 

Impaired 

Acres

Sea/Ocean 

Shoreline 

Miles

303(d) Impaired 

Shoreline Miles

FOPO* 0 0 0 0 0.37 0.37

GOGA† 33.44 0.73 43.53 0 53.99 22.54

JOMU 0.28 0 0 0 0 0

MUWO* 2.07 0 0 0 0 0

PINN 90.98 0 1.18 0 0 0

PORE† 153.56 3.45 559.79 0 113.12 27.89

PRES* 0.71 0 5 0 3.2 3.2

*These park units are, in part, managed by GOGA, and their miles and impaired mile numbers 

are included within the GOGA numbers in this table.

†The totals listed for both GOGA and PORE reflect management boundaries rather than 

legislative boundaries. This means that GOGA north lands that are managed by PORE are 

included in the PORE numbers.

collaborated with the Regional Board regarding monitoring of indicator bacteria in Olema Creek, 

a tributary to Lagunitas. The Regional Board recently completed a final TMDL project report for 

pathogens in Tomales Bay (San Francisco Bay Regional Water Quality Control Board, 2005). 

Implementation of monitoring (by NPS and others) for the Tomales Bay Pathogen TMDL 

program includes monthly monitoring plus five consecutive weeks of monitoring during both the 

winter and summer. NPS has also monitored sediment (total suspended solids and turbidity) and 

nutrients (nitrates and ammonia) in Olema Creek. Sediment and nutrient TMDL projects have 

not yet been completed for Tomales Bay (see Table 1.8 for completion dates). The Regional 

Board developed a conceptual approach for developing sediment TMDLs in San Francisco Bay 

Area streams (San Francisco Bay Regional Water Quality Control Board, 2003a). A conceptual 

approach was also developed for nutrient TMDLs in San Francisco Bay area water bodies (San 

Francisco Bay Regional Water Quality Control Board, 2003b). These reports provide 

background information about the pollutant and preliminary plans for monitoring. 

A portion of the San Francisquito Creek watershed is located within GOGA’s Phleger Estate in 

San Mateo County. This creek is listed as sediment impaired. The type and extent of impairment 

is unknown at this point. SFAN recently began baseline water quality monitoring (including 

sediment) in West Union Creek, one of the San Francisquito Creek tributaries.
12

1.1.4.2 Metals, Pesticides, and Other Chemicals: Tomales Bay is also listed as impaired by 

mercury due to an abandoned mercury mine in the Walker Creek watershed. In 2000, Marin 

County announced a fish consumption advisory for Tomales Bay due to mercury 

bioaccumulation. San Francisco Bay is also impaired by mercury in bedded sediments that are a 

legacy of historical mercury and gold mining activities. Current TMDL projects in the Bay 

include mercury and polychlorinated biphenyls (PCBs). Potential sources of mercury include 

industrial and municipal point sources, resource extraction, and atmospheric deposition. Sources 

of PCBs are unknown (non-point sources). Other pollutants listed by the Regional Board include 

exotic species and selenium; EPA has also added several pollutants to the list including the 

pesticides chlordane and dichloro-diphenyl-trichloroethane (DDT). 

All urban creeks in the San Francisco Bay area are considered impaired by diazinon. Potential 

for contamination by this pesticide exists in all urban areas. The most urbanized areas within 

NPS lands include water bodies in the Presidio (Lobos Creek, Dragonfly Creek, Tennessee 

Hollow Creek), JOMU (Franklin Creek), and GOGA (Milagra Creek, Calera Creek, Sanchez 

Creek, and San Pedro Creek). With the exception of the Presidio creeks, significant portions of 

these watersheds are located outside NPS land. City water treatment plants monitor diazinon; 

data is available from the Baker Beach Treatment Plant that tests Lobos Creek. Recent data from 

the treatment plant has not indicated contamination of Lobos Creek by diazinon. A Final Project 

Report for Diazinon and Pesticide-Related Toxicity in Bay Area Urban Creeks was also 

completed by the San Francisco Bay Regional Water Quality Control Board (2004). More 

recently, the Regional Board has turned its focus to pyrethroid based pesticides since they are 

replacing the phased-out diazinon based pesticides. Information on pyrethroids in the San 

Francisco Bay Area can be found in Pesticides in Surface Water: Annual Research and 

Monitoring Update 2005 (TDC Environmental, 2005). 

Table 8. Impaired water bodies in the SFAN.

Water body (Watershed) Park Unit Pollutant 

Coyote Creek (Richardson Bay) GOGA Diazinon

Lagunitas Creek (Tomales Bay) PORE, GOGA Pathogens, Sediment, Nutrients

Richardson Bay* GOGA High Coliform, Mercury, PCBs, Pesticides, 

Exotic Species

San Francisco Bay* GOGA, PRES Mercury, PCBs, Nickel, Pesticides, Exotic 

Species, Dioxin, Selenium

San Francisco Bay Urban Creeks GOGA, PRES, JOMU Diazinon

San Francisquito Creek (SF Bay) GOGA Diazinon, Sediment

San Pedro Creek (Pacific Ocean) GOGA High Coliform

Tomales Bay PORE, GOGA Pathogens, Sediment, Nutrients, Mercury

*See Appendix A of the SFAN Preliminary Water Quality Status Report (Cooprider, 2004) for 

details on pollutants
13

Table 9. San Francisco Bay Regional Water Quality Control Board TMDL Project Timeline as 

of June 2005.

Water body Park Unit Pollutant Project Report 

Completion

Regional Board 

Adoption Date

San Francisco Bay GOGA, PRES Mercury June 2003 Sept. 2004

San Francisco Bay GOGA, PRES PCBs Jan. 2006 Mar. 2006

Tomales Bay GOGA, PORE Pathogens April 2005 June 2005

SF Bay Urban Creeks GOGA, PRES, JOMU Diazinon Aug. 2005 Oct. 2005

San Francisco Bay GOGA, PRES Nickel Dec. 2004 Aug. 2005

San Francisquito Creek GOGA Sediment Dec. 2005 Dec. 2006

Tomales Bay GOGA, PORE Mercury Aug. 2006 Dec. 2007

San Francisco Bay GOGA, PRES Pesticide Toxicity Oct. 2006 Aug. 2007

Lagunitas Creek PORE, GOGA Sediment Dec. 2006 Feb. 2008

San Francisco Bay GOGA, PRES Legacy pesticides Dec. 2007 Dec. 2008

Tomales Bay GOGA, PORE Sediment Dec. 2007 Dec. 2008

1.1.5 Water Quality Monitoring History

A summary of water quality issues, monitoring activities, and data is provided in the SFAN 

Preliminary Water Quality Status Report (Cooprider, 2004). Section 1.1.5.1 below provides a 

summary of water quality issues. Refer to the water quality status report for a review of 

hydrology and location water bodies in the network, and for an analysis of past data. SFAN 

parks and water bodies are in various stages of monitoring. While some watersheds are in need 

of comprehensive baseline data, others are in need of more strategic data focused on suspected 

pollution sources. A summary of water quality monitoring activities for the major water bodies 

within the network is included in a table in Appendix B.
14

1.1.5.1 SFAN Land Uses and Related Water Quality Issues:

Golden Gate National Recreation Area (GOGA) and Muir Woods National Monument

(MUWO).

Muir Woods NM is located within the legislative boundary of GOGA. Therefore, although the 

two parks were established separately (i.e., by different enabling legislation), they are often 

included together. In addition, MUWO is located entirely within the Redwood Creek watershed 

and GOGA encompasses much of the lower part of this watershed. GOGA manages a large area 

but very few complete watersheds. Many of the lands have been managed and altered through 

agricultural and military uses. Due to the size and nature of the park including high visitor use, 

proximity to the urban interface, and multitude of recreation and land uses, there are several 

water quality related issues. Accelerated erosion due to roads, trails, and other uses and 

developments threatens the sediment balance and ecological health of several watersheds. Cattle 

grazing is no longer allowed on GOGA managed lands (National Park Service, 1999) but some 

of the impacts remain. Bacteria and nutrient inputs from equestrian operations, pet waste, 

agricultural operations, sewer and septic systems can impact wildlife and public health as well as 

the overall ecological balance of water resources. Channel alteration such as dams and culverts 

impacts the ecological health of park watersheds. Many park water quality issues are related to 

facilities and structures. Water quality issues occur to varying extents within multiple park 

watersheds.

John Muir National Historic Site (JOMU)

Potential or existing issues in the JOMU sub-watersheds include impacts of flooding and 

pollution by fecal coliforms, nutrients, and sediment. Potential sources of pollutants in Franklin 

Creek include illegal garbage dumping (including appliances, tires, etc.), highway runoff, 

equestrian operations, a nursery, and residential septic systems. Due to excessive erosion and the 

associated reduction of channel capacity, flooding frequently occurs in the Strentzel Lane 

neighborhood adjacent to the park and erosion is a major concern at the John Muir gravesite 

within JOMU. 

Pinnacles National Monument (PINN)

Pinnacles NM shares some of the same water quality issues as other SFAN parks; however, due 

to drier conditions, groundwater issues are a proportionally larger concern at PINN than in the 

coastal parks. Reduction and contamination of groundwater and elevated levels of sediment, 

bacteria, and nutrients in surface waters are current issues. Due to past land uses (particularly a 

former landfill site), threats of heavy metal contamination are also a concern. Some of these 

concerns are not well documented; therefore, one goal of a long-term monitoring plan is to 

clearly identify threats to water quality in order to better understand the extent of contamination 

so that it can be addressed.

Point Reyes National Seashore (PORE)

There are several water quality issues within PORE. These issues relate to the beneficial uses of 

fish migration and spawning, shellfish harvesting, and contact recreation. Sediment, pathogens, 

and nutrients are the most significant issues which can affect these beneficial uses. Erosion due 

to the presence of a major earthquake fault, cattle grazing, roads, culverts, and trails threatens the 

sediment balance and ecological health of several watersheds. Excess sediment has detrimental 
15

effects on salmonids including clogging of their gills, embedding of gravel beds used for 

spawning, and reduced visibility leading to an inability to locate food sources. Due primarily to 

the significant acreage of pastoral land within park boundaries, bacterial contamination is also a 

very serious and prevalent issue. Bacteria inputs are primarily dairy and beef cattle operations, 

but pet waste, particularly at beaches, stable operations, and septic systems may also be 

contributing. 

Presidio of San Francisco (PRES)

Freshwater quality issues within the Presidio are related to pesticides, other chemicals, landfills, 

hazardous waste, heavy metal contamination, nutrient inputs, public health (contact recreation), 

sanitary sewers, and storm drains. One of the main threats to Lobos Creek is leaky storm and 

sanitary sewer lines that cross the creek. There is also a landfill above the source of Lobos 

Creek. Ground disturbance and contamination are potential issues with this landfill. Lobos 

Creek also has had high bacteria numbers at the Baker Beach outfall. Warning signs have been 

posted at Baker Beach due to water samples exceeding the criteria for contact recreation. Heavy 

metal contamination problems are prevalent throughout the Presidio; metals are mainly a concern 

in sediments. At Mountain Lake high levels of lead have been found in the sediments. 

Remediation plans are underway to address the sediment contamination issue. Also, nutrients 

from waterfowl waste have caused excessive algal growth in the lake.

1.2 Rationale for Selecting this Resource to Monitor

Freshwater quality has high ecological, management, and legal significance within SFAN parks. 

Freshwater systems within the network support a variety of threatened and endangered species 

including California freshwater shrimp (Syncharis pacifica), coho salmon (Oncorhynchus 

kisutch), steelhead trout (Oncorhynchus mykiss), California red-legged frog (Rana aurora 

draytonii), and northwest pond turtle (Clemmys marmorata mormorata). Beneficial uses of 

freshwater bodies include contact recreation and non-contact recreation, fish spawning, 

agricultural water supply, and wildlife habitat (see Section 1.1.1). Some streams do not support, 

or only partially support, these beneficial uses due to impairment. For watersheds that are 

located primarily on parklands, significant tangible management actions can be taken to improve 

water quality of these impaired streams. Implementation of this monitoring protocol will provide 

park management with the data necessary to make effective decisions to ameliorate poor water 

quality and maintain good water quality of SFAN water bodies. 

1.2.1 Measurable Objectives 

1. Determine the variability and long-term trends in water quality through monthly summaries 

of select parameters (water temperature, pH, conductivity, dissolved oxygen, flow, E. coli, 

fecal and total coliforms, nitrate, ammonia, and total nitrogen) at selected sites in priority 

streams within SFAN.

2. Determine the existing ranges and diurnal variability of water temperature, pH, conductivity, 

and dissolved oxygen at selected sites in priority streams within SFAN.

3. Determine the extent that selected sites in priority streams within SFAN meet federal and 

state water quality criteria for fecal indicator bacteria, un-ionized ammonia, dissolved 
16

oxygen, and pH through monthly sampling. 

4. Determine the annual, seasonal, and 30-day mean fecal coliform load to Tomales Bay (an 

impaired water body) from Olema Creek as required by the San Francisco Bay Regional 

Water Quality Control Board’s Tomales Bay Pathogen TMDL program.

Specific objectives or criteria for chemical and biological parameters are listed in Section 1.1.2 

(Water Quality Criteria). These numeric objectives will be used to determine when waters are 

outside their natural range and whether or not they meet federal and state water quality criteria. 

They will also be used to inform local park staff of potential areas warranting management 

actions, or source differentiation sampling.

1.2.2 Overall Monitoring Questions 

 What are the existing chemical and biological ranges in water quality at selected sites within 

priority SFAN streams? 

 What are the long-term trends in water quality at selected sites in priority SFAN streams?

 Is the water quality of priority SFAN streams in compliance with designated beneficial uses?

 What are the point and non-point pollution sources within the watersheds?

 Are specific management actions reducing pollution loads? 

Specific monitoring questions for each site and parameter are discussed in Chapter 2 (Sampling 

Design). Questions will also be augmented and refined during the protocol testing phase. Also, 

as this protocol is implemented it will become clearer what the I&M program can provide to park 

managers and what specific issues the parks may need to address individually. In other words, 

the I&M program will help provide a link between broad monitoring and source 

differentiation/effectiveness monitoring for management practices. For source differentiation a 

longer time period and greater sampling frequency is needed. The I&M program can make 

recommendations to park management but may not necessarily cover all source differentiation 

monitoring from a budget and staff perspective.

1.2.3 Other Regional Water Quality Monitoring Programs 

Within the SFAN, several monitoring programs have existed or are on-going. Water quality 

programs developed by the parks include a comprehensive (i.e., park-wide) water quality 

monitoring program at PORE and stables and stormwater monitoring projects at GOGA. Other 

NPS monitoring programs include the Coastal Wetland Restoration at Lower Redwood Creek 

(GOGA), Giacomini Marsh (PORE/GOGA), and Crissy Marsh (PRES). The SFAN Preliminary 

Water Quality Status Report provides a more thorough review of the monitoring conducted by 

NPS staff (Cooprider, 2004). 

Several other agencies are monitoring aquatic resources (water quality, stream flow monitoring, 

and fish) within SFAN watersheds. The Tomales Bay Watershed Council (in and to which NPS 

staff participates and provides technical expertise) has developed a water quality monitoring plan 

for their watershed which includes PORE and GOGA lands. The I&M water quality monitoring 

protocol will be implemented, where possible, in conjunction with the Tomales Bay Watershed 
17

Council’s Water Quality Monitoring Plan. Other agencies associated with SFAN watersheds, 

either through water quality monitoring or land management activities include:

Alhambra Watershed Action Group (AWAG)

California Department of Fish and Game (CDFG) 

California Department of Health Services (CDHS)

California State Parks

(California) State Water Resources Control Board

Central Coast Regional Water Quality Control Board

City and County of San Francisco (CCSF)

Contra-Costa County

County of Marin

Friends of Alhambra Creek

Headlands Institute

Marin County Resource Conservation District (RCD)

Marin Municipal Water District (MMWD)

Muir Beach Community Services District (MBCSD)

San Francisco Bay RWQCB Surface Water Ambient Monitoring Program (SWAMP)

San Francisco State University (SFSU)

San Francisquito Creek Watershed Council

San Jose State University (SJSU)

Salmon Protection and Watershed Network (SPAWN)

Stinson Beach County Water District

Tomales Bay Agricultural Group (TBAG)

Tomales Bay Watershed Council (TBWC)

University of California-Berkeley (UCB)

University of California Cooperative Extension (UCCE)

University of San Francisco (USF)

Urban Watershed Project (UWP)

U.S. Geological Survey (USGS)

1.3 Measurable Results and Deliverables

Data will be summarized annually by the water quality specialist and every three to five years to 

evaluate trends and to conduct more intensive data analysis including comparison of data to 

relevant benchmarks (guidelines, criteria and objectives.) Reports will be provided to each park 

unit and the I&M coordinator. A completed NPSTORET database as well as a summary report 

will be provided to the NPS Water Resources Division (WRD) in Fort Collins annually. In the 

more detailed trend report, recommendations will be provided to parks regarding management 

actions to improve water quality including any additional monitoring that the individual parks 

could conduct (efforts outside the means or scope of the I&M monitoring program). See Table 

22 in section 24 for a complete summary of reporting and communication products.

The SFAN aquatics group, consisting of water resources professionals from all of the SFAN 

parks, as well as the Network Coordinator will meet quarterly to discuss progress and provide 

guidance for the freshwater quality monitoring program. More formal water quality planning 
18

meetings catering to park management staff will be held during the summer. These meetings 

will include a discussion of water quality monitoring results for each park and will provide a 

forum for discussing and recommending management practices related to water quality issues. 

These meetings will also provide an opportunity to receive suggestions on refining protocols. In 

addition, the meetings will help foster a relationship between I&M program staff and park staff 

to ensure that parks obtain needed data and feedback, and that the I&M program receives 

necessary information and support from parks. 
19

2.0 Sampling Design

2.1 Rationale For Selecting This Sampling Design Over Others

An appropriate sampling design ensures that specific monitoring questions will be answered with 

the data gathered and the subsequent statistical analysis. A sampling design needs to enable us 

to detect changes that are statistically significant and ecologically significant although these are 

not always identical (Irwin, 2004). The process of developing an overall sampling design 

requires knowledge of management objectives, associated monitoring objectives (Ch.1), and 

specific monitoring questions. A logical process for developing specific monitoring questions is: 

1) Develop monitoring questions for each objective, 2) Determine site locations based on 

monitoring questions, 3) Determine specific questions for each site location, and 4) Determine 

specific questions for each parameter. 

2.1.1 Sampling Design Types 

One approach to sampling design suggests three options for monitoring designs (EPA, 2002). 

These options include census (monitoring every water body), judgmental or targeted (specific 

water bodies and locations are targeted based on what is known), and statistical surveys 

(probability-based). EPA’s Environmental Monitoring and Assessment Program (EMAP) 

utilizes probability sampling. 

States will often utilize more than one sampling design to meet monitoring objectives but they 

do not typically use census monitoring. However, monitoring all waters of a particular type 

(e.g., recreational waters) is sometimes utilized. Although not commonly used, many states are 

adding some component of probability-based surveys to their monitoring programs. These 

designs ―ensure that sample units represent the target population and are statistically unbiased‖ 

((U.S. Environmental Protection Agency, 2002). Judgment is a major component of any water 

quality monitoring design and most states primarily utilize judgmental (non-random) designs that 

are focused on answering a specific management question. The USGS National Water Quality 

Assessment (NAWQA) program is an example of a judgmental (i.e. targeted) design (U.S. 

Environmental Protection Agency, 2002). 

Other sampling designs include a rotating basin component targets certain basins in a state for 

intensive and/or probability-based monitoring. The basins that are monitored change each year 

so that over a period of time (typically five years), the entire state is monitored (e.g., all lakes in 

the state). Fixed station networks monitor the same sites over a long period of time. These are 

often used to establish long-term trends in water quality at these sites. Intensive survey designs 

incorporate a large number of sites in an area (e.g., a watershed) for a specified period. This 

design may take the form of an intensive basin/watershed survey or a site-specific study. These 

designs may be used in conjunction with each other.

2.1.2 Sampling design for the SFAN 

Previously, parks within the SFAN have typically utilized judgmental designs for short-term 

projects (e.g., before and after a restoration project or implementation of a management practice) 

or source differentiation. Due to the proximity of water bodies to stables and dairies, monitoring 

has consisted largely of source differentiation rather than baseline or trend data. In addition, 
20

sampling has been opportunistic, rather than scheduled, in order to capture pollutant loads during 

storm events. However, more recent monitoring efforts have centered on scheduled sampling 

events with some flexibility built in for storm sampling.

In the SFAN protocol development process, it was determined that ideally, a hybrid sampling 

plan would be developed that includes both 1) targeted sites to answer site-specific pollutant or 

management issues or other limited inference questions and 2) probability-selected sites that 

allow for broader inferences to larger areas of the park or watershed as a whole. The monitoring 

objectives and questions in section 1 can be addressed by these different, but complementary 

sampling designs. Once specific monitoring objectives and monitoring questions were 

formulated, a process was begun to develop the network’s monitoring program. Table 10

provides examples by which particular questions, and appropriate sampling designs and data 

analyses that best address those questions. This table served as a point of reference for SFAN to 

select sites and the overall sampling design.

The key monitoring questions identified for SFAN (see section 1.2.2) fall into the lower tier 

questions (the last three monitoring questions). There are a number of factors, including: 

TMDL’s, land-use, or interaction with T&E species that provided the impetus for individual park 

units to be able to assess their compliance with beneficial use criteria, pollution monitoring and 

the effectiveness of specific management actions. The selection of the current list of sampling 

sites, and initial sampling plan were tailored to address those needs, relied heavily on 

consultation with park managers, and resulted in a judgmental or targeted sampling design.

Table 10. Choosing a sampling design based on monitoring questions.

Monitoring Question Site/Sampling 

Location

Overall Sampling Design & Analysis 

What are the natural 

chemical and biological 

ranges in water quality 

within the freshwater 

systems of SFAN? 

Random Analyze data from randomly chosen upstream and/or control sites 

or reference streams; analyze annual, seasonal, and daily data for 

each station and each group of stations in a stream or watershed. 

What are long-term trends 

in water quality in SFAN 

water bodies?

Random Analyze data from randomly chosen sites in the upper, middle, 

and lower reaches. Analyze annual and seasonal data for each 

station and for each group of stations in a stream or watershed.

Is the water quality of 

SFAN water bodies in 

compliance with beneficial 

uses?

Random and 

judgmental 

Focus on sites known to be impaired; analyze data for each site for 

each group of stations (collectively) in a stream. Compare 

reference reach range with impacted reach range.

What are the pollution 

sources within the 

watersheds?

Judgmental Compare data from individual sites from one sampling event to 

another; also compare data from multiple sites within a stream. 

Analyze annual and seasonal data for each station and for each 

group of stations in a stream or watershed. Compare variability in 

reference reaches with variability in impaired reaches.

Are specific management 

actions reducing pollution 

loads?

Judgmental Compare data from individual sites from one sampling event to 

another; also compare data from multiple sites within a stream. 

Analyze annual and seasonal data for each station and for each 

group of stations in a stream or watershed.
21

Judgmental sites will continue to be used in the long-term because 1) all of the SFAN parks have 

used this sampling design for the collection of legacy data, and many sites have been previously 

monitored, 2) sites can be co-located with monitoring sites for other vital signs, and 3) this 

design often provides more immediately useful data for park management, and 4) funding is 

limited and some portions of target streams are difficult to access due to their remote location, or 

the necessity to gain access through private property. 

Potential water quality monitoring sites for a judgmental design include: 1) where a stream 

leaves the park, 2) where a stream enters the park, 3) upstream reference sites near the stream 

source, 4) the mouth of a stream or tributary, and 5) upstream and downstream of known 

pollutant sources. 

Existing programs, such as the pathogen TMDL monitoring required by the RWQCB, have 

utilized similar site selection processes. The result is that sites in the upper, middle, and lower 

reaches are included. 

Drawbacks to a judgmental design are that assumptions are made regarding the stream locations 

and their relative levels of pollutants. For example, we generally assume that the most upstream 

site, the reference site near the stream sources, is probably the most natural site since there are 

fewer opportunities for contamination. We also assume (based on knowledge of past data) that 

we know where the most polluted sites or sources are. While a probabilistic design allows broad 

conclusions to be drawn about the percentage of water impacted by a particular parameter, it 

offers little information for management actions if a water body is already known to be impaired. 

However, a probabilistic design does not make assumptions and could potentially reveal 

previously unknown areas of compromised water quality. Such a design would also allow for a 

statistically-unbiased representation of the target population which allows for broad watershedlevel inferences about water quality.

However, the upper tier questions: (1) What are the natural chemical and biological ranges in 

water quality within the freshwater systems of SFAN? and (2) What are long-term trends in 

water quality in SFAN freshwater systems? are identified as important for addressing the 

objectives of I&M Vital Signs program, and require a statistically un-biased sampling design to 

support inferences from sampling site to whole watershed. Incorporating a sampling design 

element to address these monitoring questions in SFAN parks is crucial and will be considered in

the future. This could be accomplished through the development and integration of probabilitybased sampling sites that will assure geographic coverage which will complement the initial 

sampling design and selected sites.

Due to the judgmental or targeted nature of the current sampling design, we cannot currently

make statistically-supported inferences about the percentage of impaired miles in priority 

watersheds based on sampling at targeted locations. However, many of our streams are short 

compared with some other parks around the country. With long-term data from sites at various 

levels of the watershed including a reference or upper watershed site and a site at the bottom of a 

watershed, we can make educated guesses about some of the intervening sections, but no 

definitive statistical inferences can be made. Integration of probability-based sampling sites for 

priority freshwater streams in the San Francisco Bay Area Network (SFAN) would allow our 
22

network to address the first two monitoring questions from Table 10 without restricting 

conclusions and trends to the specific sites in priority freshwater streams.

Although the site selection presented in the current protocol narrative will primarily be 

judgmental, elements of randomness will be added at the levels of habitat and sampling point. 

For example, even though the selection of target streams and sites was not probabilistic, the 

particular pool or riffle that is sampled will be chosen randomly if more than one pool or riffle is 

present. The type of habitat sampled differs based on the type of stream (perennial or 

intermittent) and the monitoring questions (see Table 15(a,b) for a discussion of the targeted 

sampling habitat). In addition, the sampling spot within the habitat will also be chosen 

randomly. Temporal randomization (i.e., sampling at different times of the day) is another 

strategy for adding randomization to a sampling design. However, the SFAN water quality 

specialist will follow the same site order for each sampling event with the idea of sampling at 

approximately the same time every day for each site (within a two-hour window, where 

possible). Some parameters such as dissolved oxygen, temperature and pH can vary 

significantly within a 24 hour period. For example, dissolved oxygen can rise by several mg/L 

from early morning (lowest DO) to mid-afternoon (highest DO); and pH generally rises to its 

highest level in mid afternoon as photosynthesis removes carbon dioxide faster than it can be 

replaced by aeration in the riffles. Methods of cross-calibrating such measurements for temporal 

variation will be discussed further in SOP #5. 

A rotating basin scenario will be implemented in order to monitor the maximum number of water 

bodies of concern. The number of streams rotated and the rotation interval will depend on 

funding and staff constraints. This will enable monitoring of more water bodies on a fixed 

budget. It also allows sufficient time for comprehensive water quality data reporting. USGS 

NAWQA protocols recommend a minimum of two years of consecutive monthly monitoring 

(Gilliom et al., 2001) for rotating basin designs. A phasing-in approach (gradually adding more 

watersheds over time) will also be considered depending upon funding. This would allow 

longer-term data sets for trends, without two-year gaps. It also allows time to explore additional 

funding opportunities, partnerships, and ways of streamlining the monitoring program and 

enabling it to be more comprehensive.

2.2 Site Selection

2.2.1 Identification of Target Population, Study Boundaries, & Sample Units 

For the SFAN, the target population of measurements is from a select group of priority water 

bodies. The EPA’s Consolidated Assessment and Listing Methodology (CALM) provides 

examples of stratification for rivers/streams, lakes, wetlands, and estuaries (EPA, 2002). 

Rivers/streams are stratified into perennial/intermittent and wadeable/non-wadeable (deep river). 

Most streams within the SFAN fall into the categories of perennial or intermittent and wadeable 

with a few ephemeral streams. Ephemeral drainages are not typically monitored since they are 

only flowing during storm events and the SFAN hydrologic systems are very flashy. These types 

of drainages are also often hidden in deep brush (including poison oak) and/or located on steep 

or otherwise difficult to access terrain. The sampled population for the SFAN, at least for the 

first five years of protocol testing and refining, will primarily include perennial and intermittent,
23

wadeable streams within priority target watersheds. For the purposes of this monitoring plan, 

these are streams that are safely wadeable except in heavy storm or flood conditions. The target 

population is all water column parameter values and ranges from the selected areas of priority 

streams within the limited temporal collection index periods. 

Additional surface water strata (e.g., lagoons, lakes, marshes) may be added as protocols are 

updated and refined, and as funding permits. Although wetlands and marine/estuarine waters are 

significant resources within the SFAN, they are not included as target water bodies yet since 

these indicators were lower priority for the SFAN. However, protocols will be developed in the 

future as funding permits. All Areas of Special Biological Significance (ASBS) within the 

SFAN are in coastal waters and will be covered in a protocol for marine water quality. 

2.2.1.1 Data representativeness/sampling constraints: Assuring representativeness of the data will 

be accomplished by using methods used by the USGS (collector sites, cross-section checks, 

sampling from the centroid of flow, etc.). A combination of assuring representativeness, plus 

selecting sites upstream of bridges and culverts (as detailed in Standard Operating Procedure 

(SOP #12, Site Selection & Documentation)), and randomly selecting where to start sampling the 

midpoints and cross-sections upstream will assure both reasonable representativeness of the 

target population while still maintaining good data comparability with regional USGS data. To 

help ensure that inferences from a single site visit (sample population) to chemical and biological 

ranges at selected sites in priority streams (target population) are appropriate, continuous 

monitors will be deployed. Data from these instruments will help gain an understanding of 

seasonal and diurnal (daily) variability. This data, where available for a particular site, will also 

allow us to broaden the target population definition to include all water quality parameter values 

and ranges from the selected areas of priority streams, (without the caveat of the limited temporal 

collection periods). These types of variability occur in many water quality parameters and will be 

discussed in greater detail in the SOPs and in subsequent versions of this protocol.

Some constraints to sampling representatively include difficult or unsafe site access, particularly 

during storm events, lack of staff availability during the winter holidays when major storm 

events often occur, and laboratory constraints such as sample hold time, and hours of operation 

or holiday closures. Other constraints to sampling representatively are that sites will primarily be 

located within park boundaries and will not necessarily represent the larger watershed. This will 

not be a significant concern for the SFAN since parks encompass several watersheds in their 

entirety. However, watersheds with significant portions located outside park boundaries may not 

be sampled in some cases due to access issues, relative lack of management options, or other 

limitations. 
24

2.2.1.2 Selection of target streams: The SFAN watersheds are identified and described in the 

San Francisco Area Network Preliminary Water Quality Status Report (Cooprider, 2004). The 

target population was chosen based on: 1) Data trends from review of WRD Water Quality Data 

Inventory and Analysis Reports and a UC Berkeley report (Stafford and Horne, 2004) including 

recent data from PORE, GOGA, and PINN, 2) Results of water quality planning meetings in 

2002 and 2003, and 3) Criteria for Selection Table (Appendix C) for the SFAN Target Water 

Bodies. 

The selection criteria table in Appendix C provides the major information needed to prioritize 

target watersheds. This prioritization is essential to reducing the number of water bodies 

monitored due to staff, time, and funding constraints. The table takes into account Category 1 

and 2 water bodies as defined by the NPS Freshwater Work Group Subcommittee (Rosenlieb et 

al., 2002). Category 1 water bodies are listed as impaired by the Clean Water Act Section 303d. 

Category 2 water bodies have one or more of the following characteristics: lack baseline data, 

have an established threat, are subject to ecological impairment or are linked to another vital sign 

(e.g., stream T&E and fish assemblages). Other characteristics used to prioritize target water 

bodies include a high proportion of the watershed within park boundaries (higher priority) and 

whether other entities are monitoring a particular water body (lower priority).

There are three levels of prioritization: high, medium, and low priority. Category 1 (303d listed) 

water bodies are high priority for monitoring followed by water bodies having two or more of the 

Category 2 characteristics. Low priority water bodies have only one or none of the Category 2 

characteristics. Medium priority water bodies often had a combination of characteristics. Water 

bodies generally excluded from the priority list have one or more of the follow characteristics:

Only listed as impaired by diazinon (no other Category 1 or 2 characteristics): 

The San Francisco Bay Regional Water Quality Control Board listed all San Francisco Bay Area 

urban streams as impaired by diazinon. These creeks are not specifically listed by name and it 

has not been verified that all of these streams contain elevated levels of diazinon. However, all 

urban creeks are considered to be potentially impaired by diazinon and are automatically 

included. Many SFAN streams (Franklin, Lobos, Dragonfly, Tennessee Hollow, Milagra, 

Calera, Sanchez, and Coyote Creek) are included. 

Diazinon has now been phased out as a commercially available pesticide. Consequently, 

pyrethroid based pesticides have replaced diazinon as the Regional Board’s primary pesticide of 

concern. Pesticides are not currently monitored in park streams but planning is underway to 

address pesticide issues through the WRD Level 1 Inventory Project with the USGS. The SFAN 

is currently coordinating with the USGS to conduct baseline monitoring for pesticides in these 

urban creeks.

Lacking baseline data:

Water bodies that lack baseline data are not appropriate for Water Quality Vital Signs funding 

since there is separate funding through WRD for Level 1 Water Quality Inventory Program (R. 

Irwin, personal communication, 18 September 2004). Also, streams that lack baseline data are 

often lower priority for park management. This is illustrated by the fact that many of the streams 

lacking baseline data are not subject to ecological impairment. After baseline data is obtained 
25

for these water bodies, they will be added to the protocol if results indicate that there is an 

established threat. 

Streams primarily located off parklands:

Water bodies with only small portions on park property are often located in urban areas where 

local watershed groups are active. This greatly improves the potential for parks to work with 

volunteers who, in many cases, are already been conducting monitoring activities. This also 

includes water bodies that are located within the park legislative boundary but not managed by 

the park (and particularly areas where NPS staff access is restricted).

Adequate monitoring by other entities:

Water bodies consistently monitored by other entities (e.g., Stinson Beach County Water District 

monitors Easkoot Creek (GOGA)) need not be monitored. It is appropriate and fiscally 

responsible not to monitor these streams if the parks have access to the data and the data meets 

the needs of the monitoring program.

To provide an example of how the criteria for selection table and the above exceptions can be 

used to prioritize water bodies, consider Haggerty Gulch. It flows into Tomales Bay, a Section 

303d water body. However, it is primarily located off parklands. In addition, it lacks baseline 

data and may qualify for a separate monitoring program through WRD. 

Franklin Creek has some conflicting characteristics in the criteria for selection table. It has 

several low priority characteristics including: 1) only a small portion located on parklands, 2) 

only diazinon impaired, and 3) a local group conducting monitoring. However, it also has some 

high priority characteristics including 1) it has an established threat (high fecal coliform) and 2) 

is linked to the freshwater dynamics (stream hydrology) vital sign and 3) has the potential to 

support Federally threatened steelhead. It is also a highly visible resource for the park since it is 

located behind the John Muir historic house.

Strentzel Creek has a somewhat more complex set of decision-making factors. It is ephemeral, 

only half of the watershed is located on NPS property (JOMU), and it lacks baseline data. These 

are factors that would exclude it from the priority list. However, it is subject to ecological 

impairment and it is the only significant watershed within JOMU. Also, erosion and 

sedimentation in this watershed are highly significant management issues for that park. 

Therefore, it is included on the priority list. Strentzel Creek is actually a higher priority for 

JOMU than Franklin Creek since JOMU owns half of this small watershed and manages only a 

few hundred meters of Franklin Creek. However, because of the proximity of these two streams 

it makes sense to monitor both if possible. Strentzel Creek is ephemeral and there may be 

opportunities to coordinate local volunteers to monitor water quality (particularly sediment) 

during storm events.

West Union Creek is also a complex example of utilizing the table in appendix C. The stream is 

only partially located on parklands but in this case, that does not reduce its priority since the 

headwaters are located on parklands. Also, the San Francisquito Creek Watershed Council and 

other groups are monitoring the creek further downstream but data is very limited for the 

upstream portion of the creek on parklands. Reasons to include it as priority stream in this 
26

monitoring plan are that it has a vital signs link (supports salmonids and possibly California redlegged frogs) and is subject to ecological impairment from erosion, landslides and potentially 

high coliform levels from equestrian use. It is also located within the sediment-impaired San 

Francisquito Creek watershed. 

The examples above illustrate the point that the criteria for selection table provides a significant 

amount of information to guide decision making but it is not always straightforward. The 

purpose of the table is to guide decision making through a review of all issues that need to be 

considered and to document the decisions. Despite efforts to categorize water bodies and follow 

a logical process, professional judgment and park management also play a role and the decisionmaking process can be complex. The SFAN Preliminary Water Quality Status Report provides 

information about water quality priorities for each park (Cooprider, 2004). 

The proposed priority water bodies were primarily chosen because they have an established 

threat and link to another vital sign. Olema Creek and Lagunitas Creek are also heavily 

weighted because they are considered impaired and this has been verified by baseline data. 

Chalone Creek is included because nearly all of PINN is part of the Chalone Creek watershed. 

Additional (alternative) streams are those that have established threats (i.e., monitoring has 

shown high levels of pollutants) or are subject to ecological impairment (i.e., streams are 

suspected to be contaminated in the future) but are primarily priority for individual parks. 

Alternative streams could potentially be monitored if funding were available.

Table 11. High priority streams.

Stream Park

Lower Redwood Creek and tributaries

(Green Gulch, Kent, Banducci, Camino del Canyon)

GOGA

MUWO

Upper Redwood Creek and tributaries 

(Bootjack and Fern Creek)

GOGA

MUWO

Rodeo Creek and tributary 

(Gerbode Creek)

GOGA

Tennessee Valley Creek GOGA

Chalone Creek and tributaries

(Sandy Creek, McCabe Canyon, Bear Gulch)

PINN

Olema Creek and tributaries

(John West Fork, Davis Boucher Creek)

PORE/GOGA

(managed by PORE)

Lagunitas Creek tributaries 

(Bear Valley Creek, Devil’s Gulch, and Cheda 

Creek)

PORE/GOGA

(managed by PORE)

Pine Gulch Creek PORE

West Union Creek and upper tributaries GOGA
27

Table 12. Medium priority streams.

Stream Park

Strentzel Creek JOMU

Franklin Creek JOMU

Nyhan Creek GOGA

Oakwood Creek GOGA

Table 13. Low Priority Streams.

Stream Park

Additional Olema Creek tributaries 

(Quarry Gulch, Giacomini Gulch) 

PORE

Webb Creek GOGA

El Polin Spring (Creek) PRES

Tennessee Hollow Creek PRES

East Schooner Creek PORE

Home Ranch Creek PORE

Creamery Creek PORE

A Ranch Perennial Creek PORE

B Ranch Creek PORE

C Ranch Creek PORE

Kehoe Creek PORE

Abbotts Creek PORE

Muddy Hollow Creek PORE

2.2.2 Site selection criteria, stratification, and randomization

Examples of stratification in water quality sampling sites include broad stream type (perennial, 

intermittent, ephemeral), watershed size, stream pattern (straight, meandering, braided) or other 

channel characteristics. Sampling can also be stratified by time (e.g., by varying the order of 

sampling sites). For the SFAN, since the streams are mostly small coastal streams with similar 

substrate and channel type, watershed size, and hydrologic conditions, a stream classification 

scheme was not used to decide on monitoring locations. No stratification was used to determine 

current site locations. 

In consultation with park resource managers, sites were chosen based on the following criteria: 

1) evidence or suspicion of contamination at a particular site (e.g., faulty septic systems, 

agricultural use, pet waste, outfall pipe), 2) human or aquatic health issue (e.g., there is a 

swimming area in the receiving water of a stream, 3) presence of a stream gauge or other 

permanent hydrologic monitoring equipment (linkage to freshwater dynamics vital sign), and 4) 

linkage to other aquatic vital signs (e.g., stream fish assemblages). Co-locating water quality 

sites with past or current macroinvertebrate or fish monitoring sites helps ensure data that has 

been used for trend analysis and management decisions in the past, continue to be comparable 

with the current monitoring program. All sites within a given watershed will be sampled on the 

same day (or even around the same time) or during the same storm event. Sites should represent 

inputs from all areas of the watershed (i.e., all major tributaries), capture the most downstream 
28

site within NPS property, and be permanent long-term sites (considering access). When 

choosing the number of sites within a watershed, we wanted to be as comprehensive as possible 

in representing the watershed while choosing a number of sites that is practical (considering 

laboratory and staff costs and logistics). 

Where present, a particular tributary within a watershed may be suitable as a ―reference reach‖. 

This stream would be most similar to other streams in the watershed in geology and be the most 

natural (unaltered geomorphology and land use). These reference sites may be in wilderness 

areas with little disturbance, if available, or they may be located in the uppermost reaches of a 

particular priority stream, many of these sites are included in the site list as ―alternate‖ sites. 

These reference sites are included in the sampling design not only to ensure monitoring of the 

state of ―wilderness‖ or ―pristine‖ water on park lands, but also to provide data for a comparison 

with sites in a particular priority stream more significantly impacted by environmental stressors. 

In this way, water quality data from the selected sites in SFAN priority streams will serve to 

better inform management decisions of land-use issues or to support broader watershed-level 

inferences. 

After identifying specific monitoring questions that were to be addressed by sampling, efforts 

were made to determine if existing or previously-sampled sites could be used to answer these 

questions. If so, these sites were chosen for inclusion to enable data continuity and linkages. For 

example, there are six monitoring sites on Olema Creek that will be used. These are preestablished monitoring sites for the Regional Board’s pathogen TMDL project. The selection of 

water quality sites and site IDs was based to a large extent on existing or past water quality 

monitoring sites and park input. In some cases, the former site ID was initially used so that past 

and future data could be easily recognized as comparable. 

A more simplified, logical naming convention is used in this protocol. A site ID history table 

explains when former sites were chosen as long-term monitoring sites, and when their ID’s were 

changed. This table accompanies the site location and access table in Appendix E. Site locations 

are shown on maps in Appendix F.

2.3 Selection of parameters and protocols

The EPA Western Pilot Field Operations Manual for Wadeable Streams (Peck et al., 2001) and 

the National Field Manual (USGS, various dates) protocols will be followed for field methods. 

USGS protocol for stream discharge measurements will be followed (Rantz, 1982). The USDA 

Forest Service Redwood Sciences Laboratory protocol for turbidity and sediment sampling will 

be followed at the turbidity threshold sampling station on Olema Creek (U.S. Forest Service, 

2002). Table 13 includes a broad overview of field methods. Laboratory methods for fecal 

indicator bacteria (FIB), nutrients, and total suspended solids (TSS) will follow ―Standard 

Methods‖ (American Public Health Association, et al., 1998) or comparable EPA method. The 

SOPs will describe more protocol details not covered in this table. Summaries of the SOPs are 

provided in Section 3.0 of this protocol. The SOPs will rely heavily on local programs such as 

the State Water Resources Control Board’s Surface Water Ambient Monitoring Program 

(SWAMP) and the associated Quality Assurance Management Plan (Puckett, 2002). 
29

Water quality varies over space and time in still waters. Rivers and streams are generally well 

mixed. Therefore, depth integrated sampling may not be needed except in the dry season where 

only pools may be present. The USGS National Field Manual (NFM) discusses depth-integrated 

sampling further. The study objectives need to be considered when determining sample 

collection procedures. For example, if analyte discharge measurements are desired, the USGS 

National Field Manual recommends that depth and width integrating sampling be conducted 

(Wilde et al., 1998). 

Another reason that the USGS recommends depth-integrated sampling is that some forms of 

nutrients and bacteria are often associated with sediment particles. The San Francisco Bay 

Regional Water Quality Control Board does not use depth-integrated sampling for bacteria or 

nutrient TMDL monitoring. The Regional Board’s Surface Water Ambient Monitoring Program 

(SWAMP) does not collect depth-integrated samples for bacteria. Regardless, in many cases 

with the SFAN streams, there is not sufficient depth, except during storm events, to obtain a 

meaningful depth-integrated sample. In order to maintain consistency at all of the sites and 

throughout the sampling season, a ―grab‖ or ―hand-dipped’ sample will be obtained at a uniform 

depth (typically 4-8 inches) from the centroid of flow. During periods of low or no flow, where 

water is isolated in pools, a randomly-selected pool will be sampled, grab samples will be 

obtained as stated, but a profile of core parameters will be obtained that includes a surface-level 

sample (~ 4 inches) and a sample from near the bottom will be collected.

Nitrate, ammonia, and total nitrogen will be monitored regularly for long-term trend detection 

and for short-term, localized toxic or eutrophic events. Ammonia transforms to different nitrogen 

species very quickly. In the winter there may be high levels of total ammonia, but low levels of 

the toxic, unionized ammonia. Also, even though a sample may have no unionized ammonia in 

one section of a stream there may be a toxic event in another section. Therefore, it is important 

to target certain areas of the watershed; this is achieved through a judgmental design.

EPA’s recommended parameters for nutrient assessment are total phosphorous, total nitrogen, 

chlorophyll-a, and some measure of water clarity (e.g. turbidity for rivers and streams) (U.S. 

Environmental Protection Agency, 2000a). Nitrogen and phosphorous are the main causal 

agents of enrichment, while the two response variables, chlorophyll-a and water clarity are early 

indicators of system over-enrichment for most waters. However, it is generally agreed that Bay 

Area streams (i.e., freshwater systems) are nitrogen limiting, not phosphorus limiting. Therefore, 

any addition of nitrogen would impact aquatic growth and/or toxicity to organisms (Stafford and 

Horne, 2004).
30

Table 14. Target streams, parameters, and protocols to be monitored.

Stream Park Parameters Frequency Personnel Protocols

Olema Creek PORE Core 

parameters, 

flow, FIB, 

nutrients, 

sediment, 

water level

Monthly; 

weekly for 5 

weeks in 

summer and 

winter;

continuous at

one site; one 

storm event

SFAN Water 

Quality 

Specialist 

National Field Manual (USGS, 

various dates); Rantz , 1982 ; Peck 

et al., 2001; APHA et al., 1992; 

State Water Resources Control 

Board (Puckett 2002); U.S. Forest 

Service, 2002. 

Lagunitas 

Creek 

tributaries 

PORE

GOGA

Core 

parameters, 

flow, FIB, 

nutrients, 

sediment

Monthly, plus 

one storm event

continuous* at 

one site

SFAN Water 

Quality 

Specialist

National Field Manual (USGS, 

various dates); Rantz , 1982 ; Peck 

et al., 2001; APHA et al., 1992; 

State Water Resources Control 

Board (Puckett 2002); U.S. Forest 

Service, 2002.

Pine Gulch PORE Core 

parameters, 

flow, water 

level, FIB, 

nutrients

Monthly;

continuous* at 

one site

SFAN Water 

Quality 

Specialist

National Field Manual (USGS, 

various dates); Rantz, 1982 ; Peck et 

al., 2001; APHA et al., 1992; State 

Water Resources Control Board 

(Puckett 2002)

Lower

Redwood 

Creek 

GOGA

MUWO

Core 

parameters, 

flow, FIB, 

nutrients, 

sediment, 

water level

Monthly plus 

one storm 

event; one site 

continuous*

SFAN Water 

Quality 

Specialist 

National Field Manual (USGS, 

various dates); Rantz, 1982 ; Peck et 

al., 2001; APHA et al., 1992; State 

Water Resources Control Board 

(Puckett 2002)

Upper 

Redwood 

Creek 

GOGA

MUWO

Core 

parameters, 

flow, FIB, 

nutrients, 

sediment

Monthly plus 

one storm 

event; 

continuous* at 

one site

SFAN Water 

Quality 

Specialist

National Field Manual (USGS, 

various dates); Rantz, 1982 ; Peck et 

al, 2001; APHA et al., 1992; State 

Water Resources Control Board 

(Puckett, 2002)

Rodeo Creek GOGA Core 

parameters, 

flow, FIB, 

nutrients, 

sediment

Monthly plus 

one storm 

event;

continuous* at 

one site

SFAN Water 

Quality

Specialist

National Field Manual (USGS, 

various dates); Rantz, 1982 ; Peck et 

al., 2001; APHA et al., 1992; State 

Water Resources Control Board 

(Puckett 2002)

Tennessee 

Creek 

(GOGA)

GOGA Core 

parameters, 

flow, FIB, 

nutrients 

Monthly plus 

one storm 

event;

continuous* at 

one site

SFAN Water 

Quality 

Specialist

National Field Manual (USGS, 

various dates); Rantz, 1982 ; Peck et 

al., 2001; APHA et al., 1992; State 

Water Resources Control Board 

(Puckett 2002)

Nyhan Creek GOGA Core 

parameters, 

flow, FIB, 

nutrients

Monthly SFAN Water 

Quality 

Specialist

National Field Manual (USGS, 

various dates); Rantz , 1982 ; Peck 

et al, 2001, APHA et al., 1992; State 

Water Resources Control Board 

(Puckett, 2002)

Oakwood 

Creek 

GOGA Core 

parameters, 

flow, FIB, 

nutrients

Monthly SFAN Water 

Quality 

Specialist

National Field Manual (USGS, 

various dates); Rantz , 1982 ; Peck 

et al, 2001; APHA et al., 1992; State 

Water Resources Control Board 

(Puckett, 2002)
31

Stream Park Parameters Frequency Personnel Protocols

West Union 

Creek 

GOGA Core 

parameters, 

flow, FIB, 

nutrients, 

sediment

Monthly during 

winter and 

spring

SFAN Water 

Quality 

Specialist

National Field Manual (USGS, 

various dates); Rantz , 1982 ; Peck 

et al, 2001; APHA et al., 1992; State 

Water Resources Control Board 

(Puckett 2002); U.S. Forest Service, 

2002.

Franklin 

Creek 

JOMU Core 

parameters, 

flow, water 

level, FIB, 

nutrients

Monthly; 

continuous* at 

one site

SFAN Water 

Quality 

Specialist; 

assistance 

from local 

volunteers

National Field Manual (USGS, 

various dates); Rantz, 1982 ; Peck et 

al, 2001, APHA et al., 1992; State 

Water Resources Control Board 

(Puckett 2002)

Strentzel 

Creek 

JOMU Core 

parameters, 

flow, 

sediment 

Storm events SFAN Water 

Quality 

Specialist; 

assistance 

from local 

volunteers 

National Field Manual (USGS, 

various dates); Rantz, 1982 ; APHA 

et al., 1992; State Water Resources 

Control Board (Puckett 2002); U.S. 

Forest Service, 2002.

Chalone 

Creek 

PINN Core 

parameters, 

flow, FIB, 

nutrients, 

sediment

Monthly during 

winter and 

spring; 

continuous* at 

one site; one 

storm event

SFAN Water 

Quality 

Specialist 

with park 

staff 

assistance as 

available

National Field Manual (USGS, 

various dates); Rantz, 1982 ; Peck et 

al., 2001; APHA et al., 1992; State 

Water Resources Control Board 

(Puckett 2002)

*The continuous probe will be moved from watershed to watershed on a rotating basis 

(remaining in each watershed for at least two weeks, each season) for Olema, Pine Gulch, 

Redwood, Tennessee Valley, Rodeo, Franklin, and Chalone Creeks.

Notes on Table 14:

1. Ideally each priority stream would have a continuous monitoring data set that would represent

the diurnal and seasonal conditions in that stream. Logging multiparameter instruments 

(e.g., datasondes) collecting continuous data can be rotated between watersheds for two-week 

deployments.

2. Storm event sampling will be opportunistic. but will be consistent for each site from year to 

 year (i.e., an early/mid/late winter season storm will always be sampled).

3. In order to consider the potential of using field kits rather than laboratory analyses for nutrient 

 parameters, field kits can be used in conjunction with laboratory sampling and the results can 

 be compared.

4. (Ward et al., 1990) recommend reducing sampling frequency to once a quarter, unless looking 

for regulatory violations, to reduce serial correlation. However, there are often other variables 

of interest which change on a shorter time scale. If the same data is used for long-term trends 

and short-term exceedences measured values can be averaged over each quarter, 

so that there is just one value per quarter.

5. Maps of these water bodies are located in Appendix F.

6. Core parameters will be monitored continuously at sites on a rotating basis. Newly-revised 

USGS continuous monitoring protocols (Wagner et al, 2006) will be followed as appropriate. 

Water level is monitored continuously at sites where automatic recording stream gauges are 

located.
32

7. For streams that will be sampled during a storm event, the same general storm event will be 

 monitored every year (i.e., first flush, mid, or late-season storm; 3rd storm event, etc.)

Key to Table 14

 Core parameters*: dissolved oxygen (D.O.), specific conductance, pH, and temperature 

 Flow (quantitative) or Flow Severity Index* (estimated or qualitative)

 Water Level

 FIB (fecal indicator bacteria): Fecal/Total Coliforms, E. coli,

 Nutrients: Total nitrogen, ammonia, nitrate/nitrite, 

 Sediment: Turbidity and total suspended solids (TSS) or suspended sediment concentration 

* Minimum collection parameters for each station visit

2.3.1 Data Comparability 

Significant measures will be taken not only to ensure that our data is comparable with other 

agencies, but also to encourage universities, watershed councils and other volunteer groups 

conducting monitoring to document sufficient metadata to gauge the comparability of their data

with ours. The network water quality specialist coordinates with all entities involved in 

monitoring on parklands in order to optimize data sharing. Representatives from the 

agencies/entities listed in section 1.2.3 above will be contacted, data comparability issues will be 

discussed and a metadata checklist will be distributed (see Ch. 4, Data Handling, Analysis and 

Reporting). SOP 4 (QAPP) details the efforts to provide maximum data comparability with 

federal, state, and other monitoring agencies. This protocol provides the minimum standards and 

guidelines that SFAN should utilize, with strong encouragement to use more stringent criteria and 

to adopt methodologies that improve upon these minimum standards. The SFAN QAPP (SOP 4), 

and Field method SOP’s (SOPs #3-9) detail the procedures that will ensure that we have

representative, comparable, accurate and precise data that can be shared statewide and nationwide, 

to the extent possible. 

One of the central ways the SFAN freshwater quality monitoring protocol will insure the 

comparability of their data to outside groups is to follow some basic information quality 

guidelines by integrating a high degree of transparency about data and methods used to generate 

the data, including quantifying the limits of Measurement Quality Objectives (MQO’s - See 

Table 9 in the QAPP (SOP4)) specifications for precision, bias and sensitivity.
33

Table 15. Overview of SFAN Data Quality Assurance.

Data Comparability Issue SFAN Data Quality Assurance

Sufficiency of Metadata  Metadata requirements of NPSTORET are comprehensive, ensuring that 

methods, analyses and handling of both samples and data are documented in 

the same place as the data itself (including the attachment of the protocol 

and SOP documents themselves). 

 Systematic verification of data in the database, as well as periodic review of 

stated procedures and included documentation (SOP’s).

 The Protocol Narrative and SOP’s will thoroughly document all field and 

laboratory methods, including QA/ QC measures.

Field Methods  Standard USGS or SWQCB (SWAMP) protocols will be followed, as 

explained in the SOP’s.

 Documentation of equipment calibration frequency and acceptance criteria.

Lab Methods  All laboratories analyzing SFAN samples will be NELAP (or CA-ELAP) 

certified for the parameter and analysis being conducted.

 All methods used for laboratory samples will follow Standard Methods 

using APHA/AWWA/WEF methods or comparable EPA methods.

 Laboratory QC measures will include matrix spikes, method blanks, 

calibration standards, lab and field-duplicated samples.

Sensitivity  For lab parameters: Calculation of both Method Detection Limit (MDL) and 

Minimum Level of Quantitation (ML).

 For field or ―core‖ parameters: Quarterly collection of seven replicate 

samples or measurements in order to calculate the Alternative Measurement 

Sensitivity (AMS).

Precision  For Field Measurements: Duplicate at least one measurement, or 10% of a 

days’ samples (whichever is larger).

 For Lab Measurements: Duplicate analysis of 10% of samples. Report the 

Relative Percent Difference (RPD). 

Bias  Maintain consistent personnel and methodology where possible.

 Overlap* a minimum of seven (7) measurements when personnel changes, 

thirty (30) when a method or equipment changes, and fifty (50) when 

replacing surrogate estimators like FIB.

 Analyze such overlapping samples to determine the contribution of bias (if 

any) to any variance in the data.

 Control bias by: Use and analysis of ―blank‖ samples (Field, Trip or Lab 

Blanks) to determine contamination by methodology.

 For control of measurement bias, certified reference materials and/or spikes 

will be analyzed once every 20 samples and % difference shall not be more 

than the values listed in Table 10 of SOP#4 (QAPP).

―Accuracy‖  For the purposes of this protocol, the term ―accuracy‖ should be taken to be 

the ―uncertainty in accuracy‖ and is a combination of random error 

(precision) and systematic error (bias) components that are due to sampling 

and analytical operations. Measurement uncertainty will be controlled 

quantitatively through calculations of sensitivity, precision and bias.

*Overlap: old and new methods (i.e. old and new equipment, old and new personnel) will each 

be used to collect data from a site for a minimum number of times (a number of visits to different 

stations, or repeated measurements at a single site).
34

2.4 Sampling Frequency and Replication 

There are many points to consider when determining when to collect a water sample and take 

field measurements. Ideally, dissolved oxygen would be measured in the early morning (just 

before dawn) when D.O. is expected to be lowest. This would capture the worst-case scenario 

and help determine whether the D.O. range meets the established criteria. The same holds true 

for pH – if they occur, we want to capture the pH’s that are outside the criteria range of 6.5-8.5. 

However, we don’t yet know enough about the creeks to make decisions about when D.O. and 

pH levels would be most detrimental to aquatic life. These answers can be obtained over time. 

It is more realistic to answer these types of questions with continuous monitoring than with 

monthly monitoring. A continuous probe will be moved from watershed to watershed on a 

rotating basis for Olema, Pine Gulch, Redwood, Tennessee Valley, Rodeo, Franklin, and 

Chalone Creeks to facilitate the collection of this important data.

Sites will be monitored at approximately the same time for each monthly sample event (i.e., sites 

will be monitored roughly every thirty days, within a two hour window to the extent possible). 

The time of day that sampling takes place will be established during the first year of monitoring. 

The storm event (first, second third; early/mid/late season) will also be established during the 

first year of monitoring. Subsequent sampling years will mimic the initial monitoring year with 

regards to storm event and time of day. 

The specific monitoring questions determine how sites are selected and the type and number of 

habitat(s) (riffle, run or pool) sampled. Some reasons to sample pools include that they are often 

the most contaminated, they allow for sampling in intermittent streams where riffles/runs are 

absent part of the year, and they are important fish habitat. Reasons to sample riffles include 

transport, flow, and load–related concerns (e.g., sediment transport, fecal coliform load for 

TMDL monitoring). Information from riffles can also be used in conjunction with stream 

macroinvertebrate data. 

The primary sampling objective is to sample and take stream measurements in the centroid of 

flow wherever possible (see SOPs #5-8). At the establishment of each sampling site, a stream 

cross-section of core parameters will be measured to ensure and confirm that sampling at the 

centroid of flow is representative for other parameter sampling purposes. This measure will be 

repeated seasonally to ensure that the method continues to be representative. In an effort to 

impart some randomization to the exact sampling location within a target reach, a random 

number generation method will be used to select the point (upstream or downstream) within the 

centroid of flow (and within the desired habitat (riffle, run or pool)) for sample collection. For 

intermittent streams with isolated pools in the summer/fall it is also important to take samples 

and measurements in these pools since they are areas of fish refuge and to allow for comparison 

of annual and season variability in site water quality. Toxic ammonia, low D.O., and high 

temperatures are potential threats to aquatic life. In intermittent streams with isolated pools 

during the summer/fall, a randomly-selected pool will be sampled, grab samples will be obtained 

as stated for laboratory analysis, but a profile of core parameters will be obtained that includes 

measurements at the a surface (~ 4 inches) and at a point near the bottom. Tables 16a and 16b 

provide a summary of habitat sampling differences for perennial and intermittent streams. 
35

Following this sampling regime will allow SFAN to answer specific monitoring questions listed 

in Appendix D. SFAN will follow the rotating watershed schedule listed in Table 17.

Table 16. Habitat Sampling 

A. Perennial Streams.

Parameter Pool Season Riffle/Run Season

Core parameters X All

Bacteria X All

Nutrients X All

Sediment X Winter/spring

B. Habitat Sampling in Intermittent Streams*

Parameter Pool Season Riffle/Run Season**

Core parameters X All X Winter/spring

Bacteria X Summer/fall X Winter/spring

Nutrients X Summer/fall X Winter/spring

Sediment X Winter/spring

* Some site on intermittent streams may have perennial flow

**There may be years when there is flowing water well into summer; in this case sample based on flow not season. 

Table 17. General Water Quality Monitoring Schedule.

Stream Park Unit FY07 FY08 FY09 FY10

Olema Creek PORE M, S, W M, S, W M,S, W M,S,W

Lagunitas Creek PORE/GOGA M M

Pine Gulch PORE M M

Lower Redwood Creek GOGA/MUWO M ,S M, S

Upper Redwood Creek GOGA/MUWO M M

Rodeo Creek GOGA M, S M, S

Tennessee Creek GOGA M, S M, S

Nyhan Creek GOGA M, S M, S

Oakwood Creek GOGA M, S M, S

West Union Creek GOGA M M

Franklin Creek JOMU M M

Strentzel Creek JOMU S S

Chalone Creek PINN M, S M, S

M monthly monitoring (winter and spring only for Chalone Creek and West Union Creek)

S monitoring during at least one storm event

W weekly monitoring (of core parameters and FIB only) for five weeks in winter and summer

Opportunities for phasing-in additional water bodies (e.g., Presidio streams) or eliminating the 

rotating basin approach will continue to be considered. Due to the current pathogen TMDL 

program monitoring on Olema Creek, it will continue to be monitored annually for the 

foreseeable future. Ideally, Lagunitas Creek tributaries would also be monitored annually since 

this stream is an impaired water body. However, a sediment TMDL monitoring program is not 

yet in place for this creek (expected by 2008). Lower Redwood Creek is currently being 

monitored through 2006 as part of the Big Lagoon Restoration project. This is a short-term 

monitoring program designed by a consultant and modified by GOGA (Stillwater Sciences, 
36

2004) and will end before FY08; hence, it is recommended that I&M assume monitoring for the 

entire watershed (Upper and Lower Redwood Creek) at that time. USGS NAWQA protocols 

recommend a minimum of two years of consecutive monthly monitoring (Gilliom et al., 2001) 

for rotating basin designs. A phasing-in approach (gradually adding more watersheds over time) 

will also be considered depending upon funding. This would allow longer-term data sets for 

trends, without two-year gaps. Also, where annual monitoring is mandated by state TMDL 

project, then we will monitor every year and be able to analyze for long-term trends without twoyear gaps (an example would be Olema Creek) Other options are to conduct monthly monitoring 

of core parameters on all streams so that if there are any major problems, parks can be alerted. 

Monitoring for nutrient and bacteria parameters could then be conducted only quarterly, or 

monthly on a rotating schedule.

Sample size is a critical element of the power of statistical analysis. Sample size is determined 

largely by sampling design, and is one of three critical elements including confidence level and 

power that determine our ability to detect a change in water quality. Sample sizes will vary 

slightly depending on annual rainfall patterns and other conditions affecting how long a stream 

holds water, but a summary of anticipated sample sizes is shown in Table 18, below. 

Table 18. Sample Size Summary for SFAN Priority Streams.

Stream # of Sites* 

Proposed(Alt.)

# Samples 

/Site/Yr **

# Samples *** 

/Watershed/Yr

Park # Samples 

/Park/Yr

Olema 6(2) 13

18-20 FIB 

samples

72-96

(108-144 FIB 

samples)

PORE FY07-FY08

144-180

FY09-FY10

147-183

Pine Gulch 3 12 36 PORE 

Lagunitas 3 13 39 PORE / 

GOGA

Rodeo 2(1) 13 26-39 GOGA FY07-FY08

52-104

FY09-FY10

129-204

Tennessee 2(1) 7 14-21 GOGA

Nyhan/

Oakwood

0(2) 7-10 14-20 GOGA

Redwood 9(3) 7-13 117-156 GOGA/M

UWO

West Union 2(3) 7-12 24-48 GOGA

Franklin 1 12 12 JOMU 17-22

Strentzel 0(5) 2 10 JOMU

Chalone 5(3) 7-13 35-104 PINN 65-104

* The number of sites listed per stream is the proposed # with the alternate # of sites in 

parentheses (i.e. 6(2) means six proposed sites, with two alternate sites).

** The number of samples per site per year depends on the presence of water in intermittent 

streams during the dry season.

*** The number of samples per watershed per year depends on the availability of funding to 

sample alternate as well as proposed sites.

Based on data from a limited number of sites for the past two years, SFAN has been able to 

approximate the minimum detectible differences (MDD) in mean parameter values from one 

year to the next, which we will be able to distinguish given the sample sizes in the current 
37

protocol (Table 19). These approximations were based on available data for core parameters 

from long-term sites on Olema Creek. Those parameters for which we are unable to estimate the 

variation of the parameters of the population due to lack of baseline data, have estimated power 

and MDD goals that will be re-evaluated and updated as data is collected. 

Table 19. Minimum Detectable Differences for 1-year intervals of SFAN Sampling Design.

Confidence Level (1-α*100) Power (1-β *100) MDD (% change)

Core Parameters 95% 95% 15% (20% for SC)

Nutrients 95% 90% 30%

Sediment 95% 80% 40%

Bacteria 95% 80% 50%

 This power analysis was conducted using paired samples and the equations to estimate 

sample size using the form n=(s)2(Zα + Zβ)

2

/(MDC)2 where

o s= Standard deviation of the difference between paired samples

o Zα= Z coefficient for type I error rate

o Zβ= Z coefficient for type II error rate

 Analysis was checked using MS Excel macro from Gerow (In Press) at 

http://www.statsalive.com/

Because we do not have consistent or complete past data for either nutrient or sediment 

parameters for sites in SFAN priority streams, we have set some general goals based on initial 

estimates using the sample sizes in the current protocol. Because both bacteria and sediment 

parameters have high variation in SFAN streams, we have set more reasonable goal of being able 

to detect a larger change with slightly less power. Through evaluation of collected data, we 

should be able to refine our power and MDD calculations for these parameters, resulting in 

greater power to detect smaller change. 

The current sampling design should allow SFAN to detect the minimum difference in the mean 

for parameters shown in Table 19 on one-year intervals. Due to the rotating panel design, we 

will also be able to compare two-year periods every six years, with greater power to detect a 

smaller change. The same stations will be monitored during years one and two, and again during 

years five and year six. So, these two year periods can be compared to one another every six 

years. Because the sample size will be twice as large as for single-year comparisons, we should 

be able to detect a smaller change with greater power.

Due to the judgmental or targeted nature of the current sampling design, we cannot currently 

make statistically-supported inferences about the percentage of impaired miles in priority 

watersheds based on sampling at targeted locations. However, many of our streams are short 

compared to some other parks around the country. With long-term data from sites at various 

levels of the watershed including a reference or upper watershed site and a site at the bottom of a 

watershed, we can make educated guesses about some of the intervening sections, but no 

definitive statistical inferences can be made. With the integration of randomly-selected sites that 

will assure geographic coverage for SFAN watersheds, we will be able to integrate statisticallyunbiased inferences of the percentage of impaired stream miles, as well as the natural ranges of 

water-quality and long-term trends for water quality in freshwater systems of SFAN.
38
39

3.0 Field and Laboratory Methods

Standard operating procedures (SOPs) cover field season preparations and equipment, sequence 

of events in the field, details of taking measurements (including example field forms), postcollection processing of samples (e.g., lab analysis), end-of-season procedures, quality 

assurance/quality control (QA/QC), and all other details of water quality monitoring. The bulk 

of information related to field methods is included in SOP 3, SOP 5, and SOP 9. Most of the 

laboratory related details are included in SOP 6, SOP 7, and SOP 8. SOP 4 covers the majority 

of details related to QA/QC.

3.1 Standard Operating Procedures

All aspects related to field and laboratory methods are included in Standard Operating 

Procedures. Methods follow existing national programs (EPA and USGS). Quality assurance 

and quality control methods follow California Water Resources Control Board EPA-approved 

guidelines for Quality Assurance Project Plans. Details of field methods and implementation are 

outlined in the SOP documents including:

SOP 1: Revising the Protocol

SOP 2: Personnel Training and Safety

SOP 3: Equipment and Field Preparations 

SOP 4: QAPP (QA/QC SOP)

SOP 5: Field Methods For Measurement of Core Parameters 

SOP 6: Field and Laboratory Methods for Fecal Indicator Bacteria

SOP 7: Field Methods For Sampling Nutrients 

SOP 8: Field and Laboratory Methods For Sediment

SOP 9: Field Methods For Flow (Stream Discharge) 

SOP 10: Data Analysis 

SOP 11: Data Reporting

SOP 12: Site Selection and Documentation

SOP 1: Revising the Protocol

This SOP refers to revisions to be made after the monitoring plan has been implemented in 

October 2006. Data analysis after the first year or two of monitoring will help determine whether 

the monitoring data collected adequately answers the stated questions and meets objectives. 

Revising the protocol to thoroughly answer the monitoring questions will be a top priority. 

Practical issues to be considered include: sampling frequencies, site selection and location, 

logistics of transporting samples to laboratory, and effectiveness of the protocol during storm 

events. It is essential to make these critical changes earlier in the implementation of the 

monitoring plan to ensure long-term effectiveness of the protocol. Therefore, it is expected that 

the majority of major changes (i.e., those having the most effect on sampling design and 

statistical analysis) to the protocol would be made in the first few years. Any changes to the 

protocol or SOPs will be documented in a revision history log. In addition, the SOP emphasizes 

the importance of overlap in equipment, methods, and staff when changes occur in order to 

document bias in the data. 
40

SOP 2: Personnel Training and Safety

At least two network or park individuals will be trained initially. This will help ensure 

continuity should one person leave a position or otherwise not be available for a particular 

sampling event. In addition, it will be mandatory that two field staff be present for sampling 

during storm events (see safety SOP) and it is recommended at other times as well. Staff will be 

trained through review of written guidance plus a series of consecutive sampling events. The 

overall project purpose, protocols, equipment manuals, and field maps will be reviewed before 

commencing fieldwork. The first sampling event (or first group of sites in an event) will be used 

to demonstrate the sampling process including QA/QC. The second sampling events or group of 

sites will give the trainees an opportunity to sample with guidance. The trainer (water quality 

specialist, hydrologist, or hydrologic technician) will periodically accompany the recently trained 

individuals to ensure that the protocol continues to be followed and to address any questions. 

The safety SOP ensures that safety will be a priority in the short and long-term. The SOP will 

stress the importance of radio use, team communication (e.g., sign-out sheet or buddy system) 

and sound judgment. The SOP will also individually address potential safety hazards by 

focusing on the Job Hazard Analysis for this position. In addition, USGS standard safety 

protocols will be incorporated (Lane and Fay, 1997).

Sampling during storm events is of particular concern in Mediterranean climates. Most, if not 

all, of the streams in the SFAN have a rapid response time (hydrograph) with stage rising rapidly 

during a storm event. For example, individuals taking flow measurements in Chalone Creek 

(PINN) have had to end flow measurements since the stage rose to an unsafe level during the 

short time that the velocity measurements were being taken. 

Other potential hazards to be considered at all parks include flowing logs and other debris, 

quicksand (particularly at PINN), falling trees, drowning, falling, back injuries from 

lifting/bending/falling, poison oak and stinging nettle, and (though rare) large predators such as 

mountain lions. Though some of these hazards are rare, it is important to be aware of all of them. 

A thorough list of hazards is particularly useful for staff that may not be familiar with the local 

weather and climate, topography, flora, or fauna.

SOP 3: Equipment and Field Preparations 

This SOP will follow guidelines provided by the manufactures (e.g., Oakton, YSI, Inc., MarshMcBirney, Eureka Environmental, and Rickly Hydrologic) for equipment operation and 

maintenance including calibration methods and frequency, cleaning, changing pH electrodes, 

D.O. membranes, etc. In addition, recommendations from the WRD and USGS will be followed 

on pre-field mobilization and water quality instrument checks that include procedures for 

office/lab calibrations and error checks of each sensor to determine if acceptance criteria are met 

prior to conducting field work (P. Penoyer, NPS Hydrologist, Fort Collins, 2005, pers. comm).

A field equipment checklist is included in the protocol. This lists all required and optional 

equipment to be carried with the field crew (or in the field vehicle) and all times. The checklist is 

provided for review before leaving the base park/office for each sampling event. This SOP also 

includes procedures for preparing and maintaining continuous monitoring equipment following 

USGS protocols (Wagner et. al., 2006). End-of-season procedures and preparation of equipment 

for short and long-term storage are also covered here.
41

SOP 4: Overall Quality Assurance Project Plan (QAPP)

Following NPS guidance from (Irwin, 2004), the QAPP or QC SOP includes 1) QC objectives 

for measurement certainty (detection limits such as MDL (method detection limit) and PQL 

(practical quantitative limit), 2) QC objectives for measurement precision, 3) QC objectives for 

measurement systematic error (bias as percent recovery), 4) QC objectives for data completeness 

(including adequacy of planned sample sizes and statistical power), and 5) QC objectives for 

blank controls for lab measurements. Individual SOPs for parameters also includes discussion 

related to data comparability and selection of laboratories and protocols. SOPs are highly 

detailed (e.g., indicating how many duplicate samples will be collected for QC) so that other 

agencies can determine whether they can utilize SFAN data in conjunction with their own data). 

The California Department of Water Resources ―Guidelines for Preparing Quality Assurance 

Project Plans‖ (1998) was followed.

SOP 5: Field Methods for Measurement of Core Parameters

This SOP primarily focuses on the use of multiparameter probes for measuring basic water 

chemistry parameters. Specifically, the YSI 85 will be used for determining dissolved oxygen 

concentration and percent saturation, specific conductance, salinity, and temperature. Handheld, 

waterproof pH meters will be used in conjunction with the YSI 85. The SOP also discusses the 

use of continuous monitors for temperature, conductivity, pH, and dissolved oxygen. Details of 

this field SOP focus on the actual in-situ measurement (e.g., location of probe within sample site, 

location of probe in water column, proximity to streambank, differences in measurement 

techniques in pools versus riffles, etc.). Equipment use and preparations prior to fieldwork are 

discussed in the Equipment and Field Preparations SOP.

SOP 6 & 7: Field Methods for Sampling Bacteria and Nutrients

Details of these field SOPs focus on the actual sampling (e.g., sterile technique to avoid 

contaminating a sample, location of sample in the water column, proximity to streambank). 

Details of sample bottle labeling, storage, and transport to laboratories (including chain of 

custody protocols) are discussed. Laboratory methods are also discussed.

SOP 8: Field and Laboratory Methods for Sediment 

This SOP discusses all aspects of monitoring sediment (i.e., total suspended solids and turbidity). 

This includes preparation of sample bottles, how to collect a sample in the field, laboratory 

analysis using the oven-dry weight method for TSS, and use of a Hach 2100 turbidimeter. Depth 

integrated sampling and use of in-site turbidity sensors are also discussed as well as integration 

of sediment monitoring with other vital signs monitoring (e.g., freshwater dynamics/stream 

hydrology). Operation and maintenance of the network’s turbidity thresholds sampling unit is 

also introduced. 

SOP 9: Field Methods for Flow Measurements

Flow will be measured quantitatively at stream gauges (pressure transducer water level monitors 

such as Global or Druck, Inc.) using the USGS method for measurement of stream discharge 

(Rantz, 1982). Quantitative stream flow will also be assessed at sites related to TMDL projects 

in order to calculate loads to a 303d listed water. Where time or storm conditions do not permit 

safely measuring flows, then a quantitative estimate (float method) will be provided. In addition, 
42

regardless of whether a flow measurement can be taken, a qualitative description of flow will 

also be provided. This is often referred to as a flow severity value and has several categories. 

These categories include: no flow (pools present), dry, low, medium, high, flood. Other methods 

and instructions on when to use a particular method are discussed further in the SOP. The use of 

automatic dataloggers to monitor stream flow is also recommended and these procedures will be 

detailed in the SFAN freshwater dynamics protocol. 

SOP 10: Data Analysis

An overview of data analysis is covered in Ch. 4. However, more details are provided in this 

SOP including coverage of summary statistics, comparing data to water quality criteria, and 

QA/QC measures such as calculating duplicate precision. The data analysis SOP follows the 

Greater Yellowstone Network’s (GRYN) SOP #9 for Data Analysis (O’Ney, 2005). Also 

included in this SOP is a discussion of data analysis tools that have been integrated into 

NPSTORET.

SOP11: Data Reporting

This SOP provides details on reporting intervals, content, and format. It closely follows other 

networks data reporting SOPs as well as the SFAN Data Management Plan. 

SOP 12: Site Selection and Documentation

This SOP discusses various permits or contacts required before commencing fieldwork. Access 

issues are covered such as obtaining keys or combinations for locks and being sensitive towards 

landowner concerns. Other topics to be discussed include randomization to determine a 

sampling location within a sampling site. Site documentation is also covered including 

photographic documentation (periphyton, gravel bars, riparian cover) and site naming 

conventions.

Data Collection and Management

There is no established data collection SOP for Freshwater Quality. However, the Network’s 

overall Data Management Plan (Press, 2005) should be consulted. Some of the suggested 

methods for data collection include: 1) using an established field data sheet instead of a field 

notebook, 2) using a handheld computer to enter data, 3) using a handheld tape recorder and later 

transcribing the data, 4) keeping a log of any decisions made, 5) ensure proper training for field 

crews. The third suggestion can be useful if there is only one person collecting field 

measurements, particularly flow measurements. 

3.2 Field and Laboratory Methods Overview 

Field and laboratory methods are covered in detail in the QAPP and SOPs. Field and lab 

documentation, sample handling, logistics, and measurement quality objectives for field and 

laboratory parameters are covered in the QAPP. Only labs approved for the parameters of 

interest by the State and the National Environmental Laboratory Accreditation Program will be 

utilized. 

Additional research was conducted to obtain information and comparative results from several 

labs prior to the establishment of a laboratory contract for the SFAN freshwater quality 
43

monitoring project. Laboratory detection limits must meet the specific guidelines outlined in the 

QAPP. Any change of labs should be thoroughly documented. Any change in methods or 

personnel should also be documented and overlap should be provided/conducted whenever 

possible. 
44
45

4.0 Data Handling, Analysis and Reporting

Roles and responsibilities for data managers, project managers, and the Network Coordinator in 

relation to data management are outlined in the SFAN Data Management Plan (Press, 2005). 

The Data Management Plan also provides guidance on dealing with legacy data and nonprogrammatic data from internal (NPS) and external sources. The SFAN Water Quality 

Specialist will coordinate with internal and external monitoring programs regarding acquisition 

of legacy data and metadata.

4.1 Metadata Procedures 

Metadata reporting is accomplished through the metadata template located on the main 

switchboard of the NPSTORET database. The metadata template consists of nine categories 

including:

1) Collection Procedures 

2) Gear Configurations 

3) Preserve/Transport 

4) Analytical Procedures 

5) Lab Sample Preparation 

6) Characteristics

7) Laboratory Information

8) Staff and Roles

9) Citations

A metadata checklist (D. Tucker, personal communication, 5 December 2004) will be used and 

presented to all individuals conducting water quality data collection. The checklist is included in 

Appendix G of this document. Field data sheets will contain much of the metadata and the 

checklist will help ensure that additional metadata is documented and tracked by field and office 

personnel. Metadata will be checked at least twice by the SFAN Water Quality Specialist before 

submission of the yearly NPSTORET Database to WRD.

4.2 Overview of Database Design

The SFAN will be utilizing the NPSTORET database produced by WRD. This database is a 

modification of EPA’s STORET (Storage and Retrieval) database. It is a relational Microsoft 

Access database with built-in tools for transferring data to WRD and ultimately to STORET. 

The long-term location of the master database is on the PORE network 

(U:\Natural\_Water\NPS_STORET\NPSTORET). The SFAN Water Quality Specialist will be 

responsible for managing the master database. Satellite copies of the SFAN NPSTORET 

database will be located on servers at PINN and GOGA. 

A description of database structure, goals, and a link to download a copy can be found at the 

WRD Website: http://www.nature.nps.gov/water/infoanddata/index.cfm A brief summary is 

included here, but a hard copy of this document as it appeared at the time of this protocol version 

is included in Appendix G.
46

Table 20. Overview of NPSTORET Database Structure.

Elements Description SFAN Implementation

Organization Defines the owner of related data sets in NPSTORET SFAN is defined as the overarching 

owner of all Network and Park project 

data.

Projects Defines a project name, start date, duration, purpose, study 

area and contact info. Allows for defining relationships to 

particular stations, characteristics, personnel and 

supporting documentation.

Projects are defined to maintain data 

sets for network pilot data, SFAN 

long-term monitoring data, as well as 

various state, county or park-level 

monitoring of park water resources.

Stations Defines the location of water quality data collection 

points. Allows the definition of lat./long., elevation, 

county, state, and depth of sampling point, as well as a 

narrative station description and travel direcitons. Allows 

for the association of picture files for documenting site 

location or variation of conditions at the station.

SFAN defines stations for all current 

and legacy sampling sites, including 

seasonal photos and site naming 

history if applicable.

Metadata Defines the background information about the following 

elements: Field Sample Collection Procedures, Gear 

Configurations, Sample Preservation, Transport, and 

Storage Procedures, Field/Lab Analytical Procedures, Lab 

Sample Preparation Procedures, Characteristics(water 

quality parameters), Groups of characteristics, Laboratory 

information, Staff and roles, and Citations. Collection 

method, equipment, laboratory methods, preservation and 

transport. Uses the EPA’s ―official‖ STORET 

Characteristic list, and requires the definition of various 

details depending on the chosen element.

SFAN has defined characteristics by 

EPA STORET name and the method 

or equipment used to collect (e.g. 

―DO_YSI85‖ for Dissolved Oxygen 

as measured by the YSI 85 

multiparameter probe). Different 

methods to collect the same general 

characteristic are defined 

independently to ensure appropriate 

statistical treatment.
47

Elements Description SFAN Implementation

Results Contains the narrative and numerical data collected during 

site visits or other monitoring activities. In order to enter 

the results of monitoring activities: 

1) A Project must have been created,

2) One or more Stations must have been established, and 

3) Minimally defined Characteristics must have been 

created.

SFAN has defined Activities as the 

various characteristic groups 1) Field 

Parameters 2) Bacteriological Lab 

Analysis; 3) Sediment Field and Lab 

Analysis and 4) Nutrient Lab 

Analysis; QA replicate data is 

associated with a particular station 

visit, and is flagged as Quality 

Assurance sampling, as are the 

replicate samples for calculation of 

PQL

Reports, 

Statistics, 

Graphs and 

Exports

NPSTORET has the capability to generate a variety of 

reports, statistical analyses, graphics and data export 

options. List or detailed reports can be generated to 

document each database template. Any subset of data can 

be analyzed using built-in statistical tools that include 

options for dealing with censored (detection 

limit/quantification limit) data. Any subset of data can be 

graphed using a variety of formats including Time Series 

and Box-and-Whiskers. Graphs are generated in 

Microsoft Excel to they can be saved or customized. 

Exports of any database element or any subset of Results 

data can be made to Access, Excel and text formats.

SFAN will be generating graphs and 

statistical analyses using imbedded 

tools. As we gather data and begin to 

perform analyses, we will work 

closely with WRD to tailor reporting, 

analyses and graphic capabilities to 

match SFAN needs. Subsequent 

revisions of NPSTORET will reflect 

improvements in reporting and 

analytical tools. 

Because this database is still in development, and a full version release is not expected until later 

this year, some details of actual fields, requirements and capabilities are still changing. For a 

draft version of a data dictionary for NPSTORET, including a list of fields, their description and 

lists of acceptable values for each field can be found in the draft guidance document from the

WRD (Tucker, 2004). This document is titled: ―Draft Guidance on Data Reporting and 

Archiving in STORET‖ and can be found online at: 

http://www.nature.nps.gov/water/infoanddata/wqpartetest.pdf

A report from NPSTORET containing the field definitions for the SFAN I&M Freshwater 

Quality Monitoring Program is included in Appendix G for reference only. The most current 

version is accessible only through the active copy of NPSTORET on the PORE server.

Satellite databases will be created at the beginning of each water year. The water year is 

generally from October to September. Individuals entering data into satellite copies are 

responsible for verifying data. They should also create back-up copies of the database on a CD 

or zip drive or on a different server or computer. The satellite databases will be brought into the 

master database at the end of each water year. 

Data storage templates for NPSTORET include projects, stations, metadata, and results. All data 

for this program will be entered under the project name: SFAN_I&M: SFAN Long-Term Water 

Quality Monitoring Program. NPSTORET will run under Microsoft Access 2002 or higher. 
48

Notes to include in the SFAN version of NPSTORET include: 1) upstream and surrounding land 

usage 2) site observations even if normal, 3) indicated whether the station is a reference site or 

not, 4) indicate whether the stream is ephemeral, intermittent, or perennial, and 5) indicate the 

type of water body, e.g., stream mainstem, tributary, pond, lagoon, lake.

There is a SIM Export button in the NPSTORET that creates a data file that is easily transferable 

to WRD for inclusion in the overall version of NPSTORET and ultimately to EPA’s STORET in 

Washington, D.C. Also, NPSTORET will export data in Microsoft Access, Microsoft Excel, or 

comma or space delimited Text format for further data analyses. 

In addition, a copy of NPSTORET will be made available to the Tomales Bay Watershed 

Council (TBWC) for use as a database to store their water quality data. Advice and support will 

be provided to ensure that legacy data from the old TBWC database will be moved into 

NPSTORET. A unique feature of this previous TBWC database is that is has a hierarchical 

structure that denotes the location of every water body in relation to every other water body. The 

SFAN and PORE staffs have been coordinating with the TBWC over the past few years 

(including providing feedback on their database) and this is expected to continue in the future. 

4.3 Data entry, verification and editing

4.3.1 Data Entry

Data will be reviewed upon receipt from a laboratory and during and immediately after field 

measurements (this is also true of data from data loggers such as turbidity sensor or pressure 

transducer data). This helps identify potential equipment problems and/or presence of pollutants. 

Full data analysis is not necessary until a complete set of data is gathered (annual), but it is 

essential to preview data as it is gathered. This includes comparing site data to expected results. 

For example, a pH of 12 is outside the established range for the SFAN sites and the data 

reviewer would need to determine the source of error. Similarly, the NPSTORET database has

functions that can detect errant values that are entered. For example, a pH of 15 is not possible 

since it is on a scale of 1-14, so the program would not allow ―15‖ to be entered as a pH 

measurement. The individual reviewing the data should have a working knowledge of what 

would be expected for that stream or watershed in different seasons, etc. 

Data will be reviewed within a week after each sampling event for inconsistencies related to field 

personnel, how well SOPs are followed and how timing and logistics of sample collection and 

transport to laboratories may be affecting sample data. Also, at this time, any field notes 

regarding broken equipment or other needs (calibration, batteries, or replacement) can be 

addressed in time for the next sampling event. The SFAN data managers will work with the 

SFAN water quality specialist to ensure that data is well-understood and entered into the proper 

fields in NPSTORET. This coordination will also help ensure that metadata is complete and 

accurate. Data will be entered into the SFAN NPSTORET database no less than once a month to 

ensure adequate interpretation of field notes and receipt of proper laboratory QA/QC 

information. Entering data soon after collection and receipt of data from the laboratory ensures 

that labs are providing the needed data (including MDL, PQL) and handling samples properly. 
49

4.3.2 Data Verification

The accuracy of digitized records should be verified with field and laboratory data sheets. Once 

data is entered into the database, a different individual verifies the datasheet information against 

the database. Field staff will verify each of the field sheets that are entered into the database. As 

a QA/QC measure, the project manager will verify approximately 10% of the data entered. See 

the QAPP for additional details. 

4.3.4 Data Validation 

Data validation is the final step in assuring the accuracy of data transfer from raw to digital form. 

Questionable data are identified, reviewed, and corrected if necessary. Automatic validation that 

checks the data as it is entered is built into NPSTORET and will be modified, if necessary, for 

the SFAN version of NPSTORET. These automatic validations are programming elements that 

―censor‖ the data based on known ranges. Therefore the data manager would not be allowed to 

enter data that is invalid such as 16 for pH or a date in the future. Through this process, outliers 

are identified. Examples of common errors are missed decimal places, numerical data placed in 

the wrong field (for example, the database shows a pH of 12 when 12 is actually the water 

temperature). Outliers can be identified through simply graphing all observations for a given 

station and parameter or graphing all station data together if there is only low to medium 

variability. 

4.4 Routine data summaries and statistical analyses to detect change 

This section is intended to provide an overview of statistical analyses appropriate for water 

quality data. It addresses particular features of water quality data sets that are unique and 

discusses methods of dealing with these features. More detailed and specific data analysis 

techniques are included in SOP#10 – Data Analysis. This SOP also covers details of data 

representation including tabular and graphical data.

4.4.1 Characteristics of Water Quality Data

Most traditional statistical methods are based on the assumption that the data being analyzed 

have originated from a population (of measurements) with a normal (symmetric) distribution. 

Classical statistics makes other assumptions including uncorrelated data and constant variance 

for populations being compared (Gilbert, 1987). However, water quality data typically has a 

non-normal distribution (due to a lower bound of zero, the presence of outliers, and positive 

skewness). Seasonality and autocorrelation are also common as well as covariance with other 

variables such as discharge (Helsel and Hirsch, 2002). All these factors are important in 

deciding types of analysis to use since the ability to detect trends is dependent upon the 

variability of the data, as well as the responsiveness of the indicators (parameters), and sample 

size (Irwin, 2004).

Water quality data is usually highly variable, both temporally and spatially. Temporal variability 

is caused by autocorrelation (serial correlation) and by seasonality. Ward et al. (1990), 

recommend reducing sampling frequency to once a quarter, unless looking for regulatory 

violations, to reduce serial correlation. However, there are often other variables of interest which 

change on a shorter time scale than three months. For example, if the same data is used for longterm trends and short-term exceedences, measured values can be averaged over each quarter, to 
50

provide just one value per quarter. This method could also be useful in analyzing large data sets 

with varying sampling frequencies (common with past water quality data). Seasonal variation 

can often be explained by variation in discharge. However, seasonality sometimes remains in the 

data set even after accounting for flow effects. In these cases, seasonal variation can be reduced 

by analyzing data grouped by season (Hirsch et al., 1982). See section 4.6 for more on 

seasonality and data analysis.

4.4.2 Preparing the Raw Data Set for Analysis 

4.4.2.1 Censored and missing data: In addition to the above characteristics, water quality data is 

commonly ―censored‖ or reported as less than or greater than the detection limit (this has been 

common for ammonia and nitrate data within the SFAN as well as fecal coliform data). This data 

is considered outside the range of quantitation. In other words, it cannot be accurately quantified 

and represented as a numerical value). Data outside the range of quantitation will not be 

statistically analyzed. More information on dealing with censored data is included in the 

SOP#10 – Data Analysis. For more information on the range of quantitation, detection limits, 

etc. refer to SOP#4 – Quality Assurance Project Plan. 

Uncensored data is particularly an issue with FIB data. Knowledge of the water quality patterns, 

with relation to location and storm event, is required in order to determine if a bacteria sample 

should be diluted and to what magnitude. Having an educated guess of what the dilution should 

be for a given sample is essential to limiting the number of results that are censored. 

4.4.2.2 Replicates: Replicates from the raw data record should be averaged together and the 

single mean value used in their place for analysis, or else the median value should be used. The 

standard deviation or range of the replicates provides an estimate of the variability in the 

measurement technique (Stafford and Horne, 2004).

4.4.2.3 Data transformations: Data transformations can be utilized including logarithmic 

transformations and adjusting data for flow. Logarithmic transformations will be used 

particularly with FIB data since transforming allows for a more simple data analysis and 

graphical display of data with a range that often spans over several orders of magnitude. In 

addition geometric means, required for regulatory monitoring of FIB, are calculated after log 

transformations (see SOP #10). 

Logarithmic and flow transformations can make the data more ―normal‖ in distribution and 

increase the possibility of using parametric statistics which are slightly more powerful for 

determining statistical differences. An advantage of using the medians and interquartile ranges 

to describe central tendencies is that they remain the same even when the data is transformed 

whereas the mean and standard deviation change (Helsel and Hirsch, 2002). Data that is 

transformed for analysis will be back-transformed prior to reporting.

4.4.3 Data Analysis: Techniques & Issues 

Non-parametric statistical tests are more appropriate for non-normal data and are used to 

describe distributions in water quality data. The median and interquartile range (IQR) (middle 

50% of data points) will used in addition to the mean and standard deviation typically used for 
51

normally distributed data (Hirsch et al., 1991). The median is particularly useful for water 

quality data since it is less sensitive to outliers than the mean (Zar, 1999). 

Confidence intervals (95%) will be used to bound uncertainties in means and medians (Irwin, 

2004). Summary statistics and correlation techniques will be used to quantify relationships 

between water quality parameters. To limit seasonal variability, statistical tests will be 

conducted for each of the different seasons.

Trend analyses will also be conducted following techniques discussed in ―Statistical Methods in 

Water Resources‖ (Helsel and Hirsch, 2002). As WRD suggests (Irwin, 2004), traditional 

hypothesis tests will not be used. Modified hypothesis testing may be used for trend detection. 

Methods for long-term trend analysis (e.g., every 5 or 10 years) are discussed further in SOP#10. 

Table 21 describes the broad types of data analysis for each monitoring question. For each 

monitoring question, individual station data will be summarized seasonally and annually. Data 

from all stations within each watershed will also be summarized seasonally and annually. 

Discrete and continuous data will be analyzed separately. However, data from the same days 

will be compared for quality control and to obtain a relationship between the datalogger readings 

and instantaneous monthly/weekly data. All data will be compared with water quality standards 

by graphing the data along with a ―criteria line‖ on the graph that clearly shows which 

measurements fall above or below the standards. Within each watershed, data from stations 

upstream and downstream of a suspected pollution source or tributary will be compared. 

Summary tables, histograms, and box and whisker plots will be used to show median and 

interquartile ranges (non-parametric), mean and standard deviation (parametric), and 95% 

confidence intervals for means and medians. 

Table 21. Sampling Designs and Data Analysis Based on Monitoring Questions.

Monitoring Question Overall Sampling Design & Analysis 

What are the existing chemical and 

biological ranges in water quality at 

particular sites† within SFAN priority

freshwater streams? 

Analyze annual, seasonal, and daily data for each station and each group of 

stations in a stream or watershed. 

What are long-term trends in water 

quality at particular sites† in the SFAN 

priority streams?

Analyze data from sites in the upper, middle, and lower reaches if possible, 

or at the stream source and mouth. Analyze annual and seasonal data for 

each station and for each group of stations in a stream or watershed.

Is the water quality of the SFAN at 

particular sites in priority streams in 

compliance with beneficial uses?

Focus on sites known or suspected to be impaired; analyze data for each site 

for each group of stations (collectively) in a stream. Compare reference 

reach range with impacted reach range.

What are the pollution sources within 

the watersheds?

Compare data from individual sites from one sampling event to another; 

also compare data from multiple sites within a stream. Analyze annual and 

seasonal data for each station and for each group of stations in a stream or 

watershed. Compare variability in reference reaches with variability in 

impaired reaches.

*Are specific management actions 

reducing pollution loads?

Compare data from individual sites from one sampling event to another; 

also compare data from multiple sites within a stream. Analyze annual and 

seasonal data for each station and for each group of stations in a stream or 

watershed.
52

† The caveat of limiting range and trend analyses to data from particular sites in priority streams 

will be eliminated with the integration of a probablistic monitoring element.

*Documenting effectiveness generally requires higher frequency sampling over more than two 

years (Dave Lewis, personal communication, 28 July 2005). Therefore, this may be a situation 

where the I&M program notifies parks of pollution sources so that parks can implement 

management practices and potentially augment existing I&M monitoring. 

4.5 Reporting schedule and format 

Reporting results is a critical component of long-term vital signs monitoring in order to ensure 

that information generated through the program is available to all levels of park management 

including planning, interpretation, maintenance, and law enforcement. An overall 

communication strategy is being developed and will be updated in the document: SFAN 

Communication and Outreach Strategy.

The overall strategy provides detailed information about required reports including 1) annual 

reports and 2) Analysis AND synthesis reports. Suggested formats are documented in the SFAN 

Data Management Plan – Appendix C (Press, 2005)

In order to complete the annual report, the SFAN Data Management Team will work with the 

water quality specialist to ensure that data from the network’s version of NPSTORET is provided 

to WRD on an annual basis. An additional requirement for WRD is to provide a report that 

includes a paragraph summary for each parameter plus summary graphs of each site. In addition, 

summary paragraphs will be provided for each watershed including any proposed management 

activities related to water quality improvements. Recommendations for revising the protocol 

(changing monitoring intervals and timing, moving/adding sites, etc.) will also be proposed. 

These annual reports will also be provided to the SFAN parks, and can be used to report to 

GPRA and can be included in the AAWRP annual report to Congress. 

A comprehensive data analysis and synthesis will be written every few years in addition to more 

simplified, general annual summaries. Having this extra time allows for more thorough data 

analysis and review of protocols and may give greater opportunity for adaptive management. 

More details on data reporting are included in the Data Reporting SOP (#11). 

In addition, the Water Quality Specialist will be responsible for contributing to the Annual 

Administrative Report and Workplan required by each network along with additional outreach 

products summarized in Table 22.
53

Table 22. Summary of reporting and communication products.

Communcaction 

Product

Lead Audience Schedule Summary

Annual Report: Water Quality 

Specialist

Park Resource 

Managers

Annually Formatted as described in Data 

Management Plan – Appendix C. 

- Archive old data and document 

monitoring activities

-Describe current condition of the 

resources

-Document changes in the monitoring 

protocol

-Increase communication within the park 

and network

Analysis and 

Synthesis Report 

PORE 

Hydrologist

Park Resource 

Managers

3-5 years Formatted as described in Data 

Management Plan – Appendix C. 

- Determine patterns and trends

-Discover correlations among resources 

being monitored

-Analyze data to determine the level of 

change that can be detected using the 

existing sampling 

 scheme

-Provide context, interpret data for the 

park within a multi-park, regional, or 

national context

-Recommend changes to management 

practices

Program and 

Protocol Reviews

Network 

Coordinator

Program Lead, 

Water Quality 

Steering Committee, 

I&M Technical 

Steering Committee, 

Water Resource 

Division 

5 years -Periodic formal reviews of operations 

and results

-Review of protocol design and product 

to determine if changes are needed

-Part of the quality assurance – peer 

review process

Executive Briefing Water Quality 

Specialist

Program Managers, 

Superintendents, 

Front line 

interpretation staff

Annually 

(upon 

completion of 

annual report)

Two-page summary that lists monitoring 

objectives and questions, discusses 

annual results, and provides a regional 

context. 

Vital Sign Report 

Card

Network 

Coordinator

Program Managers, 

Superintendents, 

Front line 

interpretation staff

3-5 years 

(upon 

completion of 

Analysis and 

Synthesis 

Report

Two-page summary that aggregates 

trend data into an index. Provides 

Web Site Intranet Water Quality 

Specialist

Park Staff Annually or as 

needed

Post all completed reports

Web Site Internet Water Quality 

Specialist

Park Staff, General 

Public

Annually or as 

needed

Post all Executive Briefings, Report 

Cards, 

Park Presentations Water Quality 

Specialist

Park Staff Annually Provide a presentation to park staff 

during senior staff, all employee, or 

division meetings at each park upon 

request. Gives staff an opportunity to 

ask questions about the program.
54

Communcaction 

Product

Lead Audience Schedule Summary

IM Update Water Quality 

Specialist

Park Staff Quarterly This one-page monthly e-mail provides 

park staff with a short update on vital 

signs projects. Text should be no more 

than one paragraph. 

Photos Water Quality 

Specialist

For all reports and 

publication

Continuous High quality publication quality photo 

are needed to support all communication 

products. For digital photos that means 

300 pixels per inch resolution in a plain 

or compressed TIF format. Specialist 

should make every effort to document 

ongoing work, special incidents, site 

visits for communication purposes. 

4.6 Data archiving procedures

Electronic data archiving includes long-term storage and access through the network server. The 

NPSTORET database and all reports will be available electronically through the GOGA main

server where all I&M files are stored. In addition original data sheets and copies of reports will 

be stored in GOGA archives with hard copies potentially available in the GOGA Resource 

Management building where many I&M program staff are located. Once data have been 

validated/verified and the appropriate QA/QC procedures conducted (see the QAPP), the SFAN 

Water Quality Specialist will notify the Network Data Manager that the dataset is ready to be 

archived. All archived data will be stored in the secure Archive folder on the network server. 

The suggested directory structure for archived project folders is in the SFAN Data Management 

Plan.
55

5.0 Personnel Requirements and Training

5.1 Roles and responsibilities

The GS-6/7 Water Quality Specialist will be responsible for implementing the SFAN Freshwater 

Quality Protocol. The position will be term subject-to-furlough for the immediate future. A 

permanent position may be considered in the future dependent on funding. The Network Water 

Quality Specialist will have a flexible schedule (―maxi-flex‖) due to the need for travel time and 

long hours in the field.

The Network Water Quality Specialist will be directly supervised by the PORE Hydrologist. 

Duty station will be at the PORE headquarters. There is currently a dedicated office space for 

the individual at the PORE. Office space will also be provided at GOGA (Fort Cronkhite) in the 

same location as the Network Coordinator, Lead Data Manager, and Vegetation Ecologist. 

The Network Water Quality Specialist will be responsible for conducting fieldwork and all 

QA/QC measures, data management, data analysis, and reporting. The Network Coordinator 

will provide programmatic oversight for data management, analysis, and reporting. In addition, 

the Network Aquatic Professionals Group will meet quarterly in order to maintain 

communication and coordination among the parks and between the parks and I&M staff. 

Additional individuals will assist with field work and data validation/verification tasks. These 

may be network technicians or park staff. 

The PORE Hydrologist, with assistance from the Network Water Quality Specialist, will 

coordinate all contract management activities related to the water quality monitoring program. 

These individuals will coordinate with resource management staff at the parks to ensure 

monitoring goals are being met, to keep parks informed of monitoring activities, and to pursue 

funding opportunities. Partnerships and coordination with other agencies/individuals will 

include the Tomales Bay Watershed Council, Marin County Environmental Health Services, and 

the Regional Water Quality Control Board.

The Network Water Quality Specialist will work closely with other SFAN staff to integrate 

weather and stream hydrology (freshwater dynamics) monitoring components with water quality 

monitoring thereby limiting travel, improving efficiency, and optimizing safety. Park and 

network staff will work together when possible, particularly during storm events. This is a safety 

measure as well as a QA/QC measure.

The SFAN Aquatic Professionals Group will consist of:

Network Water Quality Specialist (Group lead)

*Network Hydrologic/Weather Technician or Intern

GOGA Hydrologist 

GOGA Aquatic Ecologist 

Network I&M Coordinator (will represent JOMU and EUON as well as overall network)

Network Data manager 

PINN Resource Manager 

PORE Hydrologist 
56

PWR Aquatic Ecologist (pending Technical Assistance request through WRD)

*These individuals may not participate in all meetings, particularly those related to management 

issues such as budget and personnel 

Tasks for the SFAN Aquatic Professionals Group

 Conduct quarterly meetings to accomplish the following tasks:

 Provide input for the Stream T&E and Fish Assemblages, Freshwater Quality, Freshwater 

Dynamics, and Weather Monitoring programs

 Communicate network and park needs and work together to prioritize and resolve issues

 Make decisions regarding personnel hiring and program implementation

 Provide a forum to discuss monitoring results 

 Review and approve workplans for network staff including the Water Quality Specialist and 

Hydrologic Technician

 Review technical reports (e.g., annual reports to WRD) and provide technical and 

programmatic oversight

 Assist Network Water Quality Specialist in recruiting field assistance among park and network 

staff

 Assist with coordination of aquatics group meetings

 Establish a MOU with state agencies conducting monitoring programs

 Participate in I&M Technical Steering Committee Meetings as a water resources 

representative (as needed)

Tasks for the SFAN Water Quality Specialist:

 Be well-versed in all aspects of the SFAN Freshwater Quality Protocol and conduct protocol 

revisions

 Coordinate logistics for field work and laboratory sample drop-off

 Coordinate field assistance for protocol implementation and provide training to field assistants

 Calibrate and maintain equipment in good working order and keep maintenance records

 Collect field data and implement field QA/QC measures

 Coordinate with laboratories regarding field sampling schedules and measurement quality 

objectives (QA/QC)

 Coordinate data entry, verification, and validation and consult with network data managers

 Perform statistical analyses on data; present and interpret results in technical reports

 Coordinate with PORE Hydrologist regarding staff and training needs, data analysis and data 

interpretation

 Coordinate with PORE Hydrologist regarding budget, vehicle, and equipment needs

 Assist with coordination of Aquatics Group Meetings

 Coordinate with USGS and WRD on Level 1 Water Quality Inventory

 Complete annual report and other communication products

 Provide regular updates to the aquatics group including a summary of data and related 

activities

Broad tasks for PORE Hydrologist 

 Provide technical assistance and supervision for the SFAN Water Quality Specialist
57

 Develop and conduct performance review (to be reviewed by aquatic professionals group)

 Manage WRD Water Quality Monitoring Program budget

 Manage laboratory contracts for the SFAN Freshwater Quality Monitoring program

 Assist in coordination of Aquatic Professionals Group Meetings

 Provide or coordinate training for the SFAN Water Quality Specialist

 Conduct annual QA/QC field checks

 Participate in I&M Technical Steering Committee Meetings as a water resources 

 representative

Broad tasks for Network Coordinator

 Participate in Aquatic Professionals Group meetings

 Coordinate guidance on data management, data analysis and reporting

 Provide information related to I&M program requirements including reporting requirements 

and deadlines

 Review technical reports and provide programmatic oversight

Tasks for Network Data Manager 

 Provide assistance to the Network Water Quality Specialist regarding data management, 

archiving, reporting

 Assist with GIS needs

 Assist in coordinating with WRD regarding the NPSTORET database 

 Assist with compilation of metadata for past and current monitoring programs; develop a 

scope of work for dealing with legacy water quality data throughout the network

5.2 Qualifications and training 

See Section A8 of the QAAP for staff training/qualifications. Also, SOP 2 (training) and SOP 3 

(safety) will include other details regarding staff requirements.
58
59

6.0 Operational Requirements

6.1 Annual workload and field schedule

A general monitoring schedule for the SFAN water bodies was presented previously in Table 12. 

Time commitments for the water quality specialist will be approximately 50% for field work and 

50% for data management, analysis, and reporting. The field work load will be heavier in the 

winter. Since some parks or streams will not be monitored in the dry season (summer/fall), this 

is when the majority of the data analysis and reporting will occur. It is anticipated that data 

entry/management will be on-going in conjunction with the field work. Where possible, efforts 

will be made to obtain additional help for data entry. The project lead (water quality specialist) 

would then be more available for data validation and QA/QC measures. Also, where possible, 

the other park and network staff will assist with water quality monitoring in order to improve 

efficiency and safety. 

6. 2 Key Partnerships and Access Requirements

A list of other regional water quality monitoring programs was offered in section 1.2.3 of this 

protocol. The SFAN Water Quality Specialist will maintain records of these and other groups or 

organizations monitoring water quality in or near SFAN parks. The person will also maintain 

contact information for project leaders of such programs. In addition, a data inventory for 

historic and current water quality data in SFAN parks will also be maintained with contact 

information, duration of monitoring and parameters monitored in order to facilitate data 

integration. As key partnerships are established with other monitoring agencies, the details of 

these partnerships will be included here. Refer to appendix C to determine what group, if any, is 

currently monitoring SFAN streams.

For some SFAN monitoring sites, access is restricted or controlled due to ownership or 

management of the site by private, or outside public entities. Please refer to the Site Location 

and Access Table in Appendix E for information and access recommendations for specific sites.

 

6.3 Facility and equipment needs

An inventory of all park and network equipment is included in SOP#3 – Equipment and Field 

Preparations. The SFAN Water Quality Monitoring Program has a dedicated YSI 85, pH meters,

and a flow meter. Primary equipment costs will be related to purchase of continuous dataloggers 

for determining daily variability on water quality parameters. Another significant cost would be 

calibration of flow meters. Other anticipated costs include repair or replacement of old meters 

and purchasing supplies such as calibration kits, buffer solutions, batteries, gloves, etc. 

Equipment lists specific to each monitoring parameter are included in the SOPs. 

Total suspended solids (TSS) analysis can be conducted ―in-house‖ in the wet lab located at 

GOGA (Marin Headlands). The lab contains a balance, sink, vacuum, and drying oven used in 

TSS analyses. See SOP#8 – Field and Laboratory Methods for Sediment. 
60

6.4 Startup costs and budget considerations

Table 23. Cost of laboratory analysis by parameter 

Analyte Method Code Method Name *Cost per sample

Fecal/Total coliform SM 9221B /Multiple Tube Technique (MPN) $30.00

E. coli/Total coliform SM 9223B Quantitray† (MPN) $20.00 @ offsite lab

$6.35 @ NPS lab

Total Kjeldahl Nitrogen SM 4500 Persulfate Method (oxidation to nitrate) $50.00

Ammonia SM 4500F Phenate Method (spectrophotometric) $25.00

Nitrate or Nitrite SM 4500 Colorimetric or cadmium reduction $20.00

Total suspended solids SM 2540D gravimetric in-house lab

Suspended Sediment SM 2540D gravimetric $35.00

*Approximate cost; prices will vary by laboratory

† SFAN has purchased an IDEXX Quantitray system for E. coli. The SFAN WQ lab will be set up in the 

Pacific Coast Science and Learning Center at PORE.

Table 24. Cost of laboratory analysis by stream for FY07-08 (update)

Creek All Sites Proposed Sites Only

Chalone* $7,523 $4,975

Olema* $15,932 $12,423

Pine Gulch $4,280 $4,280

Rodeo* $5,855 $4,100

Tennessee* $2,647 $1,701

Nyhan (A) $1170

Oakwood (A) $851

Franklin $1,383 $1,383

Strentzel (A) $385

$40,026 $28,861

*These are proposed creeks with at least one alternate site

A – These are alternate creeks

Table 25. Cost of laboratory analysis by stream for FY09-10

Creek All Sites Proposed Sites Only

Lagunitas $5,805 $5,805

Olema $15,932 $12,423

Upper Redwood $7,290 $5,940

Lower Redwood $13,635 $10,125

West Union $6,750 $3,915

$49,412 $38,208
61

Table 26. Estimated Budget

Source of Funding or Expense Budget Expenses

WRD $69,000

I&M (Freshwater Quality) $20,000

Personnel GS-7/4 $45,000

Vehicle $4,500

Equipment and Supplies $4,500

Travel $1,000

Lab Contracts $34,000

TOTAL $89,000

Personnel costs cover a GS-6/7 full time, term subject-to-furlough position. Travel covers local 

network travel, bridge tolls, and overnight stays for PINN. Equipment and supplies costs include 

the purchase of continuous loggers, replacement/repair of YSI 85 multiparameter probes and 

Oakton pH meters, and repair and calibration of existing flow meters. YSI 85 multiparameter 

probes generally last about 3 years and cost $1,200. Minisondes or datasondes that are deployed 

to determine diurnal variability are $3,000-$8,000 depending on the sensors that are attached.

Sensors for basic core parameters are standard. Additional sensors for nitrate, ammonia, and 

turbidity add additional costs. These start-up equipment costs are significant for FY06. 

Laboratory contracts will cover the cost of analyses for nutrients, fecal indicator bacteria, and 

potentially total suspended solids. Approximate costs for laboratory analyses are outlined in 

Table 23 for each parameter method. Further research into additional labs will determine if these 

costs are realistic for the desired detection limits (see SOP #4). 
62
63

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20 July 2005.

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67

Appendix A. Beneficial Uses of the SFAN Water Bodies 
68

Beneficial Uses of individual the SFAN water bodies as determined by the San Francisco Bay 

RWQCB (with modifications/additions by the SFAN staff in an April 2003 Memo to the 

RWQCB) are listed in the table below. Sets of water bodies grouped together with similar 

shading are located within the same greater watershed. Chalone Creek is located within the 

jurisdiction of the Central Coast Regional Water Quality Control Board; however, it is not 

included in there list of streams. Potential beneficial uses are indicated by “P”, existing beneficial 

uses are indicated by “E”. 

Park

AGRCOLDCOMMESTFRSHGWRINDMARMIGRMUNNAVPROCRAREREC1REC2SHELSPWNWARMWILD

Tomales Bay PORE

GOGA

E E E E E E E E E E E E E E

Lagunitas Creek GOGA E E E E E E E E E E E

Bear Valley Creek PORE E E E P E E E

Haggerty Gulch PORE E E E E E E

Olema Creek PORE E E E E E E E E E

Pacific Ocean PORE

GOGA

E E E E E E E E E E E

Santa Maria Creek PORE E E E P E E E E

Coast Creek PORE E P P E E E E

Alamere Creek PORE P E E E

Crystal Lake PORE P E E E E

Arroyo Hondo PORE E P E P E E E

Limantour Estero PORE E E E E E E P E E E E

Glenbrook Creek PORE E E E E E E P E E E

Muddy Hollow PORE E E E E E E P E E E

Kehoe Lagoon PORE E E E E

Abbott’s Lagoon PORE E E E E E

Drakes Estero PORE P E E E E E E E E E

East Schooner Ck. PORE P P P P E

Home Ranch Creek PORE E E E E E E

Bolinas Lagoon GOGA E E E E E E E E E E

Pine Gulch PORE E E E E E E

McKinnan Gulch GOGA E E E E E E

Morses Gulch GOGA E E E E E E

Pike County Gulch GOGA E E E E E E

Stinson Gulch GOGA E E E E E E E E

Easkoot Creek GOGA E E E E E E E

Webb Creek GOGA E E E E

Lone Tree Creek GOGA E

Redwood Creek GOGA E E E E E E E E E E

Tennessee Valley GOGA E E E E E E

Rodeo Lagoon GOGA E E E E E E

Rodeo Creek GOGA E E E E E

Nyhan Creek GOGA E E E

San Francisco Bay GOGA E E E E E E E E E E E E E

West Union Creek GOGA E E E E E E E

Lobos Creek PRES P P E E E E E

Mountain Lake PRES P E E E

San Pedro Creek GOGA E E E E E E

Alhambra Creek JOMU P P E P P E E E E
69

Definitions of Beneficial Uses are included below. These are defined by the 

San Francisco Bay Regional Water Quality Control Board at

http://www.waterboards.ca.gov/sanfranciscobay/basinplan/web/BP_CH2.html

Accessed July 20, 2005

AGRICULTURAL SUPPLY (AGR)

Uses of water for farming, horticulture, or ranching, including, but not limited to, irrigation, 

stock watering, or support of vegetation for range grazing.

The criteria discussed under municipal and domestic water supply (MUN) also effectively 

protect farmstead uses. To establish water quality criteria for livestock water supply, the 

Regional Board must consider the relationship of water to the total diet, including water freely 

drunk, moisture content of feed, and interactions between irrigation water quality and feed 

quality. The University of California Cooperative Extension has developed threshold and 

limiting concentrations for livestock and irrigation water. Continued irrigation often leads to one 

or more of four types of hazards related to water quality and the nature of soils and crops. These 

hazards are (1) soluble salt accumulations, (2) chemical changes in the soil, (3) toxicity to crops, 

and (4) potential disease transmission to humans through reclaimed water use. Irrigation water 

classification systems, arable soil classification systems, and public health criteria related to 

reuse of wastewater have been developed with consideration given to these hazards.

AREAS OF SPECIAL BIOLOGICAL SIGNIFICANCE (ASBS)

Areas designated by the State Water Resources Control Board.

These include marine life refuges, ecological reserves, and designated areas where the 

preservation and enhancement of natural resources requires special protection. In these areas, 

alteration of natural water quality is undesirable. The areas that have been designated as ASBS in 

this region are depicted in Figure 2-1. The state Ocean Plan (see Chapter 5) requires wastes to be 

discharged at a sufficient distance from these areas to assure maintenance of natural water 

quality conditions.

COLD FRESHWATER HABITAT (COLD)

Uses of water that support cold water ecosystems, including, but not limited to, preservation or 

enhancement of aquatic habitats, vegetation, fish, or wildlife, including invertebrates.

Cold freshwater habitats generally support trout and may support the anadromous salmon and 

steelhead fisheries as well. Cold water habitats are commonly well-oxygenated. Life within these 

waters is relatively intolerant to environmental stresses. Often, soft waters feed cold water 

habitats. These waters render fish more susceptible to toxic metals, such as copper, because of 

their lower buffering capacity.

OCEAN, COMMERCIAL, AND SPORT FISHING (COMM)

Uses of water for commercial or recreational collection of fish, shellfish, or other organisms in 

oceans, bays, and estuaries, including, but not limited to, uses involving organisms intended for 

human consumption or bait purposes.

To maintain ocean fishing, the aquatic life habitats where fish reproduce and seek their food 

must be protected. Habitat protection is under descriptions of other beneficial uses.

ESTUARINE HABITAT (EST)

Uses of water that support estuarine ecosystems, including, but not limited to, preservation or 

enhancement of estuarine habitats, vegetation, fish, shellfish, or wildlife (e.g., estuarine 
70

mammals, waterfowl, shorebirds), and the propagation, sustenance, and migration of estuarine 

organisms.

Estuarine habitat provides an essential and unique habitat that serves to acclimate anadromous 

fishes (salmon, striped bass) migrating into fresh or marine water conditions. The protection of 

estuarine habitat is contingent upon (1) the maintenance of adequate Delta outflow to provide 

mixing and salinity control; and (2) provisions to protect wildlife habitat associated with 

marshlands and the Bay periphery (i.e., prevention of fill activities). Estuarine habitat is 

generally associated with moderate seasonal fluctuations in dissolved oxygen, pH, and 

temperature and with a wide range in turbidity.

FRESHWATER REPLENISHMENT (FRSH)

Uses of water for natural or artificial maintenance of surface water quantity or quality.

GROUNDWATER RECHARGE (GWR)

Uses of water for natural or artificial recharge of groundwater for purposes of future extraction, 

maintenance of water quality, or halting saltwater intrusion into freshwater aquifers.

The requirements for groundwater recharge operations generally reflect the future use to be made 

of the water stored underground. In some cases, recharge operations may be conducted to 

prevent seawater intrusion. In these cases, the quality of recharged waters may not directly affect 

quality at the well field being protected. Recharge operations are often limited by excessive 

suspended sediment or turbidity that can clog the surface of recharge pits, basins, or wells.

Under the state Antidegradation Policy, the quality of some of the waters of the state is higher 

than established by adopted policies. It is the intent of this policy to maintain that existing higher 

quality to the maximum extent possible.

Requirements for groundwater recharge, therefore, shall impose the Best Available Technology 

(BAT) or Best Management Practices (BMPs) for control of the discharge as necessary to assure 

the highest quality consistent with maximum benefit to the people of the state. Additionally, it 

must be recognized that groundwater recharge occurs naturally in many areas from streams and 

reservoirs. This recharge may have little impact on the quality of groundwater under normal 

circumstances, but it may act to transport pollutants from the recharging water body to the 

groundwater. Therefore, groundwater recharge must be considered when requirements are 

established.

INDUSTRIAL SERVICE SUPPLY (IND)

Uses of water for industrial activities that do not depend primarily on water quality, including, 

but not limited to, mining, cooling water supply, hydraulic conveyance, gravel washing, fire 

protection, and oil well repressurization.

Most industrial service supplies have essentially no water quality limitations except for gross 

constraints, such as freedom from unusual debris.

MARINE HABITAT (MAR)

Uses of water that support marine ecosystems, including, but not limited to, preservation or 

enhancement of marine habitats, vegetation such as kelp, fish, shellfish, or wildlife (e.g., marine 

mammals, shorebirds).

In many cases, the protection of marine habitat will be accomplished by measures that protect 

wildlife habitat generally, but more stringent criteria may be necessary for waterfowl marshes 

and other habitats, such as those for shellfish and marine fishes. Some marine habitats, such as 

important intertidal zones and kelp beds, may require special protection.
71

FISH MIGRATION (MIGR)

Uses of water that support habitats necessary for migration, acclimatization between fresh water 

and salt water, and protection of aquatic organisms that are temporary inhabitants of waters 

within the region.

The water quality provisions acceptable to cold water fish generally protect anadromous fish as 

well. However, particular attention must be paid to maintaining zones of passage. Any barrier to 

migration or free movement of migratory fish is harmful. Natural tidal movement in estuaries 

and unimpeded river flows are necessary to sustain migratory fish and their offspring. A water 

quality barrier, whether thermal, physical, or chemical, can destroy the integrity of the migration 

route and lead to the rapid decline of dependent fisheries.

Water quality may vary through a zone of passage as a result of natural or human- induced 

activities. Fresh water entering estuaries may float on the surface of the denser salt water or hug 

one shore as a result of density differences related to water temperature, salinity, or suspended 

matter.

MUNICIPAL AND DOMESTIC SUPPLY (MUN)

Uses of water for community, military, or individual water supply systems, including, but not 

limited to, drinking water supply.

The principal issues involving municipal water supply quality are (1) protection of public health; 

(2) aesthetic acceptability of the water; and (3) the economic impacts associated with treatmentor quality-related damages.

The health aspects broadly relate to: direct disease transmission, such as the possibility of 

contracting typhoid fever or cholera from contaminated water; toxic effects, such as links 

between nitrate and methemoglobinemia (blue babies); and increased susceptibility to disease, 

such as links between halogenated organic compounds and cancer.

Aesthetic acceptance varies widely depending on the nature of the supply source to which people 

have become accustomed. However, the parameters of general concern are excessive hardness, 

unpleasant odor or taste, turbidity, and color. In each case, treatment can improve acceptability 

although its cost may not be economically justified when alternative water supply sources of 

suitable quality are available.

Published water quality objectives give limits for known health-related constituents and most 

properties affecting public acceptance. These objectives for drinking water include the U.S. 

Environmental Protection Agency Drinking Water Standards and the California State 

Department of Health Services criteria.

NAVIGATION (NAV)

Uses of water for shipping, travel, or other transportation by private, military, or commercial 

vessels.

INDUSTRIAL PROCESS SUPPLY (PROC)

Uses of water for industrial activities that depend primarily on water quality.

Water quality requirements differ widely for the many industrial processes in use today. So many 

specific industrial processes exist with differing water quality requirements that no meaningful 

criteria can be established generally for quality of raw water supplies. Fortunately, this is not a 

serious shortcoming, since current water treatment technology can create desired product waters 

tailored for specific uses.
72

PRESERVATION OF RARE AND ENDANGERED SPECIES (RARE)

Uses of waters that support habitats necessary for the survival and successful maintenance of 

plant or animal species established under state and/or federal law as rare, threatened, or 

endangered.

The water quality criteria to be achieved that would encourage development and protection of 

rare and endangered species should be the same as those for protection of fish and wildlife 

habitats generally. However, where rare or endangered species exist, special control 

requirements may be necessary to assure attainment and maintenance of particular quality 

criteria, which may vary slightly with the environmental needs of each particular species. 

Criteria for species using areas of special biological significance should likewise be derived from 

the general criteria for the habitat types involved, with special management diligence given 

where required.

WATER CONTACT RECREATION (REC1)

Uses of water for recreational activities involving body contact with water where ingestion of 

water is reasonably possible. These uses include, but are not limited to, swimming, wading, 

water-skiing, skin and scuba diving, surfing, whitewater activities, fishing, and uses of natural 

hot springs.

Water contact implies a risk of waterborne disease transmission and involves human health; 

accordingly, criteria required to protect this use are more stringent than those for more casual 

water-oriented recreation.

Excessive algal growth has reduced the value of shoreline recreation areas in some cases, 

particularly for swimming. Where algal growths exist in nuisance proportions, particularly blue 

green algae, all recreational water uses, including fishing, tend to suffer.

One criterion to protect the aesthetic quality of waters used for recreation from excessive algal 

growth is based on chlorophyll a.

NONCONTACT WATER RECREATION (REC2)

Uses of water for recreational activities involving proximity to water, but not normally involving 

contact with water where water ingestion is reasonably possible. These uses include, but are not 

limited to, picnicking, sunbathing, hiking, beachcombing, camping, boating, tide pool and 

marine life study, hunting, sightseeing, or aesthetic enjoyment in conjunction with the above 

activities.

Water quality considerations relevant to noncontact water recreation, such as hiking, camping, or 

boating, and those activities related to tide pool or other nature studies require protection of 

habitats and aesthetic features. In some cases, preservation of a natural wilderness condition is 

justified, particularly when nature study is a major dedicated use.

One criterion to protect the aesthetic quality of waters used for recreation from excessive algal 

growth is based on chlorophyll a.

SHELLFISH HARVESTING (SHELL)

Uses of water that support habitats suitable for the collection of crustaceans and filter-feeding 

shellfish (e.g., clams, oysters, and mussels) for human consumption, commercial, or sport 

purposes.

Shellfish harvesting areas require protection and management to preserve the resource and 

protect public health. The potential for disease transmission and direct poisoning of humans is of 

considerable concern in shellfish regulation. The bacteriological criteria for the open ocean, 
73

bays, and estuarine waters where shellfish cultivation and harvesting occur should conform to the 

standards described in the National Shellfish Sanitation Program, Manual of Operation.

Toxic metals can accumulate in shellfish. Mercury and cadmium are two metals known to have 

caused extremely disabling effects in humans who consumed shellfish that concentrated these 

elements from industrial waste discharges. Other elements, radioactive isotopes, and certain 

toxins produced by particular plankton species also concentrate in shellfish tissue. Documented 

cases of paralytic shellfish poisoning are not uncommon in California.

FISH SPAWNING (SPWN)

Uses of water that support high quality aquatic habitats suitable for reproduction and early 

development of fish.

Dissolved oxygen levels in spawning areas should ideally approach saturation levels. Free 

movement of water is essential to maintain well-oxygenated conditions around eggs deposited in 

sediments. Water temperature, size distribution and organic content of sediments, water depth, 

and current velocity are also important determinants of spawning area adequacy.

WARM FRESHWATER HABITAT (WARM)

Uses of water that support warm water ecosystems including, but not limited to, preservation or 

enhancement of aquatic habitats, vegetation, fish, or wildlife, including invertebrates.

The warm freshwater habitats supporting bass, bluegill, perch, and other panfish are generally 

lakes and reservoirs, although some minor streams will serve this purpose where stream flow is 

sufficient to sustain the fishery. The habitat is also important to a variety of non-fish species, 

such as frogs, crayfish, and insects, which provide food for fish and small mammals. This habitat 

is less sensitive to environmental changes, but more diverse than the cold freshwater habitat, and 

natural fluctuations in temperature, dissolved oxygen, pH, and turbidity are usually greater.

WILDLIFE HABITAT (WILD)

Uses of waters that support wildlife habitats, including, but not limited to, the preservation and 

enhancement of vegetation and prey species used by wildlife, such as waterfowl.

The two most important types of wildlife habitat are riparian and wetland habitats. These habitats 

can be threatened by development, erosion, and sedimentation, as well as by poor water quality.

The water quality requirements of wildlife pertain to the water directly ingested, the aquatic 

habitat itself, and the effect of water quality on the production of food materials. Waterfowl 

habitat is particularly sensitive to changes in water quality. Dissolved oxygen, pH, alkalinity, 

salinity, turbidity, settleable matter, oil, toxicants, and specific disease organisms are water 

quality characteristics particularly important to waterfowl habitat. Dissolved oxygen is needed in 

waterfowl habitats to suppress development of botulism organisms; botulism has killed millions 

of waterfowl. It is particularly important to maintain adequate circulation and aerobic conditions 

in shallow fringe areas of ponds or reservoirs where botulism has caused problems.

PRESENT AND POTENTIAL BENEFICIAL USES

SURFACE WATERS

Surface waters in the region consist of freshwater rivers, streams, and lakes (collectively 

described as inland surface waters), estuarine waters, and coastal waters. Estuarine waters are 

comprised of the Bay system from the Golden Gate to the regional boundary near Pittsburg and 

the lower portions of streams flowing into the Bay, such as the Napa and Petaluma rivers in the 

north and Coyote and San Francisquito creeks in the south.
74

Inland surface waters support or could support most of the beneficial uses described above. The 

specific beneficial uses for inland streams include municipal and domestic supply, agricultural 

supply, industrial process supply, groundwater recharge, water contact recreation, non-contact 

water recreation, wildlife habitat, cold freshwater habitat, warm freshwater habitat, fish 

migration, and fish spawning. The San Francisco Bay Estuary supports estuarine habitat, 

industrial service supply, and navigation in addition to all of the uses supported by streams.

Coastal waters' beneficial uses include water contact recreation; non-contact water recreation; 

industrial service supply; navigation; marine habitat; shellfish harvesting; ocean, commercial and 

sport fishing; and preservation of rare and endangered species. In addition, the California 

coastline within the San Francisco Bay Basin is endowed with exceptional scenic beauty.

Beneficial uses of each significant water body have been identified and are organized according 

to the seven major watersheds within the region (Figure 2-2). The maps locating each water body 

(Figures 2-3 through 2-9) and tables keyed to each map (Tables 2-1 through 2-7) describing 

associated present and potential beneficial uses were produced using a geographical information 

system (GIS) at the Regional Board. More detailed representations of each location can be 

created using this computerized version.

The beneficial uses of any specifically identified water body generally apply to all its tributaries. 

In some cases a beneficial use may not be applicable to the entire body of water, such as 

navigation in Calabazas Creek or shellfish harvesting in the Pacific Ocean. In these cases, the 

Regional Board's judgment regarding water quality control measures necessary to protect 

beneficial uses will be applied.
75

Appendix B. Water Quality Monitoring Stages 
76

Monitoring Stages of All Water Bodies Within Legislative Boundaries

Immediate

Watershed

Limited 

Monitoring

Baseline 

Monitoring

Adaptive 

Monitoring

Management 

Action

Restoration 

White Gulch Tomales Bay

Bear Valley Creek Lagunitas 

Creek

NPS

Haggerty Gulch Tomales Bay NPS

Olema Creek Lagunitas 

Creek

NPS NPS NPS NPS/Other

Cheda Creek Lagunitas 

Creek

NPS

Devil’s Gulch Lagunitas 

Creek

NPS

Lagunitas Tomales Bay SFBRWQCB USGS

Tomales Bay* Tomales Bay NPS Other/NPS Other

Bass Lake Pacific Ocean NPS

Hagmaier Pond Olema Creek NPS

Vision Pond Drakes Bay NPS

Pelican Lake Pacific Ocean

Wildcat Lake Pacific Ocean

Pacific Ocean* NOAA

Santa Maria 

Creek

Drakes Bay

Coast Creek Drakes Bay

Alamere Creek Pacific Ocean

Arroyo Hondo Pacific Ocean

Crystal Lake Alamere 

Creek

Glenbrook Creek Limantour 

Estero

NPS NPS

Muddy Hollow Limantour 

Estero

NPS NPS

Laguna Creek Drakes Bay NPS

Limantour 

Estero*

Drakes Bay

McClure’s Creek Pacific Ocean

Kehoe Creek Pacific Ocean NPS

Abbott’s Creek Pacific Ocean NPS

East Schooner Ck. Drakes Estero NPS NPS

Home Ranch 

Creek

Drakes Estero NPS NPS

Creamery Creek Drakes Estero NPS

Drakes Estero* Drakes Bay NPS DHS

Drakes Bay* Pacific Ocean NPS DHS, others

A Ranch 

Perennial

Drakes Bay NPS

B Ranch Drakes Bay NPS

C Ranch Drakes Bay NPS

Pine Gulch Bolinas 

Lagoon

NPS Others, 

SFBRWQCB

McKinnan Gulch Bolinas 

Lagoon

NPS SFBRWQCB

Pike County 

Gulch

Bolinas 

Lagoon
77

Immediate

Watershed

Limited 

Monitoring

Baseline 

Monitoring

Adaptive 

Monitoring

Management 

Action

Restoration 

Audubon Canyon Bolinas 

Lagoon

SFBRWQCB

Morses Gulch Bolinas 

Lagoon

NPS

Stinson Gulch Bolinas 

Lagoon

Laurel Creek Bolinas 

Lagoon

Black Rock Creek Bolinas 

Lagoon

SBWD

Fitzhenry Creek Bolinas 

Lagoon

SBWD

Easkoot (Table 

Rock) Creek

Bolinas 

Lagoon

NPS/Other SBWD NPS

Webb Creek Pacific Ocean UCB SFBRWQCB

Lone Tree Creek Pacific Ocean UCB

Cold Stream Pacific Ocean UCB

Redwood Creek Pacific Ocean NPS, UCB, 

USGS, 

SFBRWQCB

NPS NPS NPS/Other

Green Gulch Redwood 

Creek

NPS, 

SFBRWQCB

NPS

Kent Creek Redwood 

Creek

Fern Creek Redwood 

Creek

USF

Bootjack Creek Redwood 

Creek

USF

Tennessee Valley Pacific Ocean NPS, 

SFBRWQCB

NPS NPS

Rodeo Lagoon* Pacific Ocean NPS, UCB HI, 

SFBRWQCB

Rodeo Creek Rodeo 

Lagoon

NPS, UCB SFBRWQCB NPS NPS

Gerbode Creek Rodeo Creek UCB

Nyhan Creek Coyote Creek NPS

Oakwood Valley Nyhan Creek NPS

Coyote Creek Richardson 

Bay

San Francisco 

Bay*

SFEI, many 

others

SFEI, others

Franklin Creek Alhambra 

Creek

NPS/Other

Strentzel Creek Alhambra 

Creek

NPS NPS

Crissy Marsh San Francisco 

Bay

NPS NPS NPS

Lobos Creek Pacific Ocean NPS, UWP, 

Presidio 

Trust, 

SFBRWQCB

El Polin Spring Sam 

Francisco 

Bay

NPS
78

Immediate

Watershed

Limited 

Monitoring

Baseline 

Monitoring

Adaptive 

Monitoring

Management 

Action

Restoration 

Dragonfly Creek San Francisco 

Bay

NPS NPS/Presidi

o Trust

Tennessee Hollow San Francisco 

Bay

NPS Presidio Trust

Mountain Lake Pacific Ocean NPS/Other NPS/Presidi

o Trust

Milagra Creek Pacific Ocean NPS/Other

Calera Creek Pacific Ocean NPS, other

Sanchez Creek Pacific Ocean NPS

Laguna Salada Pacific Ocean

San Pedro Creek Pacific Ocean Other

San Mateo Creek San Francisco 

Bay

SFBRWQCB

Pilacartos Creek San Francisco 

Bay

SFBRWQCB

Pilacartos Lake San Francisco 

Bay

SFBRWQCB

Stone Dam 

Reservoir

San Francisco

Bay

SFBRWQCB

San Andreas Lake San Francisco 

Bay

SFBRWQCB

Lower Crystal 

Springs Reservoir

San Francisco 

Bay

SFBRWQCB

Upper Crystal 

Springs Reservoir

San Francisco 

Bay

SFBRWQCB

West Union Creek San 

Francisquito 

Creek

NPS others

McGarvey Gulch San 

Francisquito 

Creek

NPS

Sandy Creek Chalone 

Creek

NPS

Bear Gulch 

Reservoir

Bear Gulch NPS

Bear Gulch Chalone 

Creek

NPS

Chalone Creek Salinas River NPS NPS

DHS-California Dept. of Health Services

HI – Headlands Institute

NOAA – National Oceanic and Atmospheric Association

NPS – National Park Service 

SBWD – Stinson Beach Water District

SFBRWQCB – San Francisco Bay Regional Water Quality Control Board

SFEI – San Francisco Estuary Institute

SWRCB – State Water Resources Control Board

UCB – University of California, Berkeley

USF – University of San Francisco

USGS – U.S. Geological Survey

UWP – Urban Watershed Project

Definitions of Monitoring Stages:

No monitoring – all columns are blank; no monitoring has been conducted or information is not available
79

Limited Monitoring – annual monitoring only; past or current sporadic monitoring, few data points 

Baseline Monitoring – seasonal/quarterly or monthly monitoring for at least one year 

Adaptive Monitoring – past data has shown elevated levels; source area monitoring was initiated 

Management Action - BMPs such as buffer strips and fencing have been implemented 

Restoration – past or on-going restoration (e.g., channel or habitat improvement) has occurred or the planning process is 

underway.
80
81

Appendix C. Selection Criteria of the SFAN “Target” Water 

Bodies

83

Selection criteria of the SFAN target water bodies within NPS legislative boundaries based on WRD Category 1 and Category 2 water 

bodies and other criteria. Only wadeable streams are included as target water bodies. 

CATEGORY 1 CATEGORY 2 OTHER 

Park Unit On section 303d 

list?

Lacking 

Baseline 

Data?

Established 

Threat?

Subject to 

ecological 

impairment?

Vital 

Signs 

Link?

Managed by 

NPS?

Other agencies/entities 

currently monitoring?

White Gulch PORE X* X Yes

Bear Valley Creek PORE X* X Yes

Haggerty Gulch PORE X* X Partial

Olema Creek PORE X* X X X Yes

Cheda Creek GOGA X* X X Yes

Devil’s Gulch GOGA X* X X Yes

Lagunitas Creek PORE

GOGA

 X X X Partial USGS, SPAWN, and others

Santa Maria Creek PORE X Yes

Coast Creek PORE X Yes

Alamere Creek PORE X Yes

Arroyo Hondo PORE X Yes

Glenbrook Creek PORE X Yes

Muddy Hollow PORE Yes

Laguna Creek PORE Yes

McClure’s Creek PORE X Yes

Kehoe Creek PORE X Yes

Abbott’s Creek PORE X Yes

Home Ranch Creek PORE X Yes

Creamery Creek PORE X Yes

A Ranch Perennial PORE X Yes

B Ranch Creek PORE X Yes

C Ranch Creek PORE X Yes

Pine Gulch PORE X X Yes

McKinnan Gulch GOGA X Yes

Pike County Gulch GOGA X Yes

Audubon Canyon GOGA X No

Morses Gulch GOGA X Yes

McKinnan Gulch GOGA X Yes

Stinson Gulch GOGA X Yes

Laurel Creek GOGA Partial

Black Rock Creek GOGA Partial

Fitzhenry Creek GOGA Partial

Easkoot Creek GOGA X Partial Stinson Beach Water 

Agency

Lone Tree Creek GOGA X Yes

Cold Stream GOGA X Yes
84

CATEGORY 1 CATEGORY 2 OTHER 

Park Unit On section 303d 

list?

Lacking 

Baseline 

Data?

Established 

Threat?

Subject to 

ecological 

impairment?

Vital 

Signs 

Link?

Managed by 

NPS?

Other agencies/entities 

currently monitoring?

Webb Creek GOGA Minimal

Redwood Creek GOGA X X Yes

Green Gulch GOGA X X Partial

Kent Creek GOGA X X Partial

Fern Creek GOGA X X Partial

Bootjack Creek GOGA X Partial

Tennessee Valley GOGA X X Yes

Rodeo Creek GOGA X X Yes

Gerbode Creek GOGA X X Yes

Nyhan Creek GOGA X* X Partial

Oakwood Valley GOGA X* Yes

Coyote Creek GOGA X X Minimal

Franklin Creek JOMU X** X X Minimal Friends of Alhambra 

Creek

Strentzel Creek JOMU X X Partial

Lobos Creek PRES X** X Yes City/County of San 

Francisco

El Polin Spring PRES Yes‡

Dragonfly Creek PRES X** Yes‡

Tennessee Hollow PRES X** X Yes‡

Milagra Creek GOGA X** X X Minimal

Calera Creek GOGA X** X X Minimal

Sanchez Creek GOGA X** X X Minimal

San Pedro Creek GOGA X X X No San Pedro Creek Watershed 

Coalition

San Mateo Creek GOGA No CA Water Resources 

Control Board

Pilacartos Creek GOGA No CA Water Resources 

Control Board

West Union Creek GOGA X* X X X Partial San Francisquito Creek 

Watershed Council

Chalone Creek PINN X* X X Yes

Sandy Creek PINN X Yes

Bear Gulch PINN X Yes

** All urban creeks are impaired by diazinon according to the San Francisco Bay Regional Water Quality Control Board

* These water bodies are tributaries of or adjacent to impaired waters but are not themselves listed as impaired

‡ These Presidio water bodies are owned by the Presidio Trust but jointly managed by the Presidio Trust and NPS
85

Category 1 and Category 2 Definitions

Section 303d List – on the Clean Water Act’s Section 303d list of impaired water bodies (impaired due to one or more pollutants)

Lacking Baseline Data – no data has been collected for the stream or data is very limited and does not provide enough information to 

know the baseline condition

Established Threat – monitoring has shown that water quality is compromised due to one or more pollutants

Subject to Ecological Impairment – monitoring has not been conducted or has not shown poor water quality due to pollutants; however, there is potential for 

impairment 

Vital Signs Link- the creek provides habitat for one or more threatened or endangered species (salmonids, CA red-legged frog, San 

Francisco Garter Snake, CA freshwater shrimp)

Managed by NPS (Category Definitions):

Yes – watershed is located entirely or mostly within park boundaries and is managed by NPS

No – watershed is located within legislative boundary but is managed by other entities

Partial – watershed is partially located within parklands and/or is managed by multiple agencies (e.g., Lagunitas Creek Watershed is 

managed by NPS, CA State Parks and the Marin Municipal Water District)

Minimal – watershed is primarily located outside parklands
86
87

Appendix D. Specific Monitoring Questions and Related 

Sample Location and Monitoring Questions for Each Stream 
88

Specific Monitoring Questions and Related Sample Location

Monitoring question Habitat Frequency/Timing*

1 How long does turbidity remain in a stream after a peak storm event? Riffle/Run S

2 What percentage of pH observations for each station fall within the numerical objective range of 

6.5 – 8.5?

Pool and Riffle/Run M, C

3 What percentage of all samples exceeds the recommended criteria of 0.025 mg/L for ammonia? Pool and Riffle/Run M

4 Do the seasonal median concentrations of dissolved oxygen at each station fall below the 

recommended criteria of 7.0 mg/L (San Francisco Bay Region) or 5.0 mg/L (Central Coast 

Regional)?

Pool and Riffle/Run M, C

5 Based on the median of seasonal values, what percentage of stations meets the fecal coliform 

criteria for non-contact recreation (2000 MPN/100mL)?

Pool and Riffle/Run M

6 What is the seasonal and annual variability in pH, D.O., conductivity, and temperature based on 

monthly samples over a year?

Pool and Riffle/Run M

7 What is the diel, seasonal, and annual variability in pH, D.O., conductivity, and temperature based 

on continuous 15-minute readings over a year?

Pool C

8 Is there a significant relationship between turbidity and Total Suspended Solids or Suspended 

Sediment Concentration during a storm event?

Pool and Riffle/Run M, S

9 Is there a significant relationship between conductivity and fecal coliforms annually and during 

each season?

Pool and Riffle/Run M

10 What is 30-day average flow-weighted fecal coliform load to Tomales Bay during the winter? Riffle/Run M, W

11 Does the 30-day average log mean fecal coliform concentration exceed 200MPN/100mL (criteria 

for contact recreation) based on five consecutive weeks of sampling in the summer or winter?

Pool and Riffle/Run M, W

12 What percentage of samples exceeds the log mean total coliform concentration of 

1000MPN/100mL (criteria for contact recreation) seasonally and annually?

Pool and Riffle/Run M

13 What is the average annual and seasonal fecal coliform load contribution from each tributary? Riffle/Run M

14 What is the maximum fecal coliform concentration at each monitoring station? Pool and Riffle/Run M

15 What are the existing nutrient levels and how do they compare to recommended criteria for nitrate, 

ammonia, and Total nitrogen?

Pool and Riffle/Run

M=monthly, W=weekly, C=continuous, S= storm event

*The storm event (first, second third; early/mid/late season) will be established during the first year of monitoring. The time

of day that sampling takes place will also be established during the first year of monitoring. Subsequent sampling years will

mimic the initial monitoring year with regards to storm event and time of day.
89

Monitoring Questions for Each Stream

This table includes priority and alternative streams as well as proposed and alternate sites. For all 

streams, question #’s 1-5, 12, and 14-15 from the “Specific Monitoring Questions and Related 

Sample Location” will be addressed. The table denotes additional questions to be addressed at 

each stream. 

Stream/Watershed Monitoring question # Proposed Sites # Alternate 

Sites*

Olema mainstem 6,7,8,9,10, 11 4

John West Fork 11, 13 1

Davis Boucher 11, 13 1

Quarry Gulch 11, 13 1

Giacomini Gulch 11, 13 1

Home Ranch Creek 9,11 1

East Schooner Creek 9,11 1

Pine Gulch 6, 7 3

Bear Valley Creek 10,11, 13 1

Cheda Creek 13 1

Devils Gulch 13 1

Green Gulch 13 1 1

Golden Gate Dairy Trib 13 1

Redwood Mainstem 6,7,8,9 3

Banducci Creek 13 1

Kent Creek 13 1

Camino del Canyon 13 1

Fern Creek 6, 13 1 1

Bootjack Creek 6, 13 1

Gerbode Creek 13 1

Rodeo Creek 6, 7, 9 1 1

Tennessee Creek 6, 7, 9 2 1

Nyhan Creek 1

Oakwood Creek 1

Sandy Creek 13 2 2

Bear Gulch 13 1

Chalone mainstem 7 2 1

Franklin Creek 6, 7 1

Strentzel Creek 8 5

West Union Creek 6, 8 2 3

Total # of sites 33 22

*Proposed sites will be monitored; alternate sites are important but may not be a part of the long 

term plan (i.e., they may be monitored for a short period and then discontinued). Identification 

of proposed and alternate sites may change as data are analyzed and/or as the water quality 

program evolves. For some alternate sites, short term monitoring is planned or being conducted 

by other entities
90
91

Appendix E. Water Quality Monitoring Site Location and 

Access and Site History and Site ID Selection 

93

Site Location and Access Table 

Park/

Owner Stream Site ID UTM N UTM E Elevation Access/Directions

Topo Quad

(7.5-

minute)

Stream 

Type Site Type

Permission & 

Access Notes

PORE Olema 

creek

OLM 18 4203441 523220 320 ft Hwy. 1 MP 21.06; mainstem Olema above Randall 

Gulch, park in pull-out east of Hwy. 1 near white house 

Bolinas intermittent 

(perennial 

pools)

Proposed

PORE Olema 

creek

OLM 14 4205596 521507 200 ft Northernmost Five Brooks bridge across from park 

residence; park in large pull-out west of Hwy. 1 adjacent 

to bridge

Double 

Point

perennial 

flow

Proposed

PORE Olema 

creek

OLM 11 4210501 518436 40ft Upstream of Bear Valley Rd. Bridge; park in pull-out on 

north side of Bear Valley Rd. (west of creek)

Inverness perennial 

flow

Proposed

PORE Olema 

creek

OLM 

10B

4212695 516882 20 ft Below residence #530 (Olema Marsh); park at residence, 

walk downhill east towards creek (look for path through 

vegetation towards the left (north); avoid trees and 

shrubs) 

Inverness perennial 

flow

Proposed

PORE John West 

Fork

OLM 1 4205293 521706 200 ft Upstream of Hwy. 1 culvert at MP 22.67; park at pull-out 

on west side of Hwy. 1 (south of Five Brooks and Ralph 

Giacomini Ranch), sample at staff gauge

Double 

Point

perennial 

flow

Proposed

PORE Davis 

Boucher

Creek

OLM 

6A

4206897 520260 160 ft Park at Stewart’s Ranch behind barns (northwest side of 

ranch); follow horse trail and cross Olema; continue 

along trail (don’t cross the footbridge) and cross Davis 

Boucher; sample above horse trail (50 m upstream of trail 

bridge)

Inverness perennial 

flow

Proposed Coordinate 

with park re: 

private 

property

PORE Quarry 

Gulch

OLM 4 4209737 519021 40 ft just above confluence with Olema; park at pull-out on 

west side of Hwy. 1 after cemetery

Inverness intermittent Alternate 

PORE Giacomini 

Gulch

OLM 2 4205548 521513 200 ft Hwy. 1 MP 22.78; park at pull-out west of Hwy.1 near 

John West Fork; sample upstream of culvert 

Double 

Point

intermittent Alternate 

Private Pine Gulch PNG 1 4196963 527051 0 ft Hwy. 1 to Bolinas Rd., turn left into driveway to sample 

downstream of road bridge; cross footbridge and access 

site near stream gauge

Bolinas perennial 

flow

Proposed Coordinate 

with park re: 

private 

property

PORE Pine Gulch PNG 2 4199638 524985 120 ft Park at Olema Valley Trail pull-out on west side of 

Hwy.1 just north of Dogtown; follow trail then veer off 

to the west on undesignated trail around north end of 

wetland, cross the creek, then follow the creek a short 

distance; sample near stream bend before entrance to the 

gorge (sample near fish index reach).

Bolinas perennial 

flow

Proposed Contact park 

hydrologist or 

fishery 

biologist for 

assistance in 

locating site

PORE Pine Gulch PNG 3 4200800 524775 200 ft Hwy. 1 to Texiera Ranch; enter gate and follow road to 

the end (past the residence); walk west to the Olema 

Valley Trail, follow trail, cross the creek twice; sample 

upstream of horse trail crossing (2nd crossing)

Bolinas perennial 

flow

Proposed Gate key 

required
94

Park/

Owner Stream Site ID UTM N UTM E Elevation Access/Directions

Topo Quad

(7.5-

minute)

Stream 

Type Site Type

Permission & 

Access Notes

PORE Bear 

Valley 

Creek

LAG 1 4210696 517655 40 ft Behind PORE Bear Valley headquarters; adjacent to 

Roads & Trails yard (downstream of bridge); obtain flow 

measurement above bridge

Inverness perennial 

flow

Proposed

GOGA Cheda 

Creek

LAG 2 4210036 522385 120 ft upstream of Sir Francis Drake Blvd. MP 19.17 San 

Geronimo

perennial 

flow

Proposed

SPTSP Devil's 

Gulch

LAG 3 4209214 523361 120 ft upstream of Sir Francis Drake Blvd., below Devils Gulch 

trail (Samuel P. Taylor State Park); access creek past dog 

walking sign

San 

Geronimo

perennial 

flow

Proposed

Private Green 

Gulch

GG 1 4190636 537523 < 40 ft Hwy 1 to Pacific Way; Lower Green Gulch (north), next 

to horse pasture

Point Bonita intermittent Proposed Coordinate 

with park re: 

private 

property

Private Green 

Gulch

GG 2 4191394 538455 160 ft Hwy.1 to Green Gulch Zen Center; Upper Green Gulch 

(above Zen Center); near parking lot

Point Bonita intermittent Alternate Coordinate 

with park re: 

private 

property

GOGA Golden 

Gate Dairy

GGD 4190940 537395 40 ft Hwy. 1 across from Muir Beach entrance road (Pacific 

Way); 5-10 m upstream of Hwy.1 culvert

Point Bonita intermittent Proposed Coordinate 

with park re: 

private 

property

MTSP Banducci BAND 1 4191563 536541 < 40 ft Hwy. 1 to Redwood Creek bridge; take road along 

Redwood Creek to sample upstream of Banducci culvert 

(above Redwood Confluence)

Point Bonita intermittent Alternate 

MUWO Redwood 

Creek

RDW 1 4193545 538056 120 ft Hwy. 1 to Frank Valley Rd.; Muir Woods concrete 

bridge above CDC 2, below Muir Woods

San Rafael perennial Proposed

GOGA Redwood 

Creek

RDW 2 4191053 537084 40 ft Above Hwy. 1 bridge (below Banducci) Point Bonita perennial; 

pools in 

summer

Proposed

GOGA Redwood 

Creek

RDW 3 4190393 537396 < 40 ft Hwy.1 to Pacific Way; just upstream of Muir Beach 

Pedestrian Bridge

Point Bonita perennial; 

pools in 

summer

Proposed

MTSP Kent Creek KC 1 4192716 537205 120 ft Frank Valley Rd. to approximately 50 ft above Redwood 

Creek confluence (above Kent Creek culvert)

San Rafael intermittent Proposed

MUWO Camino del 

Canyon

CDC 2 4193508 538100 120 ft Frank Valley Rd. to Camino del Canyon/Redwood 

confluence (CDC 1 is above slide)

San Rafael intermittent Proposed

MUWO Fern Creek FC 1 4194958 537077 200 ft Frank Valley Rd. to Muir Woods parking lot; take main 

trail past Cathedral Grove; follow Fern Creek Trail; 

sample above the Fern Creek/Redwood Creek confluence 

near MUWO/MTSP boundary

San Rafael intermittent Proposed
95

Park/

Owner Stream Site ID UTM N UTM E Elevation Access/Directions

Topo Quad

(7.5-

minute)

Stream 

Type Site Type

Permission & 

Access Notes

MTSP Fern Creek FC 2 4196588 536615 1000 ft Panoramic Hwy. MP 3.22; Fern Creek above Panoramic 

Hwy. culvert in Mt. Tamalpais State Park

San Rafael intermittent Alternate Notify State 

park, obtain 

permit

MTSP Bootjack 

Creek

BJC 1 4195822 534960 1440 ft Bootjack Camp above Panoramic Highway in Mt. 

Tamalpais State Park

San Rafael intermittent Proposed Notify State 

park, obtain 

permit

GOGA Gerbode 

Creek

GERB1 4187657 542339 < 40 ft Hwy. 101 to 1st exit north of Golden Gate Bridge 

(Sausalito/Alexander Ave.); follow Bunker Rd. west 

towards Fort Cronkhite; access from Bobcat Trail after 

road bridge; sample above confluence with Rodeo Creek

Point Bonita perennial Proposed

GOGA Rodeo 

Creek

RC 1 4187316 542493 < 40 ft Bunker Rd. to unmaintained road across from Presidio 

stables; access site through willows; site is upstream of 

Miwok trail bridge and downstream of stables (stable 

tributary convergence), approximately 420 m upstream of 

Gerbode/Rodeo Creek confluence)

Point Bonita perennial Proposed

GOGA Rodeo 

Creek

RC 2 4188095 544009 200 ft Follow Bunker Rd. to park housing just southwest of 

tunnel; site is approximately 30m upstream of Capehart 

housing 

San 

Francisco 

North

perennial Alternate 

GOGA Tennessee 

Creek

TV 1 4190335 541262 260 ft Hwy. 1 to Tennessee Valley Rd. to end (trailhead 

parking); 100 m upstream of Old Springs Trails crossing; 

above Gabino's house, above Miwok stables

Point Bonita intermittent Alternate Coordinate 

with park re: 

private 

property

GOGA Tennessee 

Creek

TV 2 4190212 540670 160 ft Below Miwok stables, 330 meters upstream of 

Tennessee Valley/Haypress tributary confluence

Point Bonita intermittent Proposed Gate 

combination 

required

GOGA Tennessee 

Creek

TV 3 4189337 540597 80 ft 2 meters downstream of Backdoor (tributary to Tenn. 

Valley); access from Tenn. Valley trail

Point Bonita intermittent Proposed Gate 

combination 

required

GOGA Nyhan 

Creek

NYH 1 4191465 541504 40 ft Tennessee Valley Rd.; park at pull-out across from 

Oakwood Valley sign. Sample above Oakwood 

confluence, below footbridge. 

Point Bonita perennial Alternate 

GOGA Oakwood 

Creek

OAK 1 4191470 541561 40 ft Above culvert near confluence with Nyhan Point Bonita intermittent Alternate 

GOGA West 

Union 

Creek

WU 1 4144676 562565 640 ft Hwy. 280 South towards Redwood City; Woodside Rd. 

exit; Woodside west then veer right onto Kings Mountain 

Rd. to Huddart County park; park at Zwierlein Picnic 

area, Crystal Springs Trail, cross McGarvey Gulch, right 

onto Miramontes Trail. Site is on the mainstem in 

Phleger Estate 1/4mi down the trail from Huddart Co. 

Park boundary

Woodside ponded in 

summer

Proposed Notify ranger 

at entrance 

station
96

Park/

Owner Stream Site ID UTM N UTM E Elevation Access/Directions

Topo Quad

(7.5-

minute)

Stream 

Type Site Type

Permission & 

Access Notes

GOGA West 

Union 

Trib. #1

WU 2 4144954 562339 640 ft Tributary #1 (first tributary upstream of McGarvey 

Gulch), above Miramontes trail crossing

Woodside dry in 

summer

Alternate Notify ranger 

at entrance 

station

GOGA West 

Union 

Trib. #2

WU 3 4145237 561550 640 ft Tributary#2, (second tributary upstream of McGarvey 

Gulch); upstream of Raymundo trail bridge

Woodside dry in 

summer

Alternate Notify ranger 

at entrance 

station

GOGA West 

Union 

Creek

WU 4 4145512 561055 720 ft Mainstem; upstream of Trib. #2 Woodside dry in 

summer

Alternate Notify ranger 

at entrance 

station

Huddart 

County 

Park

McGarvey 

Gulch

MGG 1 4144415 562513 640 ft Between trail crossing and confluence with West Union 

creek (accessible area above large boulders)

Woodside ponded in 

summer

Proposed Notify ranger 

at entrance 

station

JOMU Franklin 

Creek

FRA 1 4205172 576184 120 ft I-80 to Hwy. 4 to Martinez; Alhambra Ave (left), to 

JOMU visitor center; site is upstream of bridge near 

automatic stream gauge

Briones 

Valley

intermittent; 

pools in 

summer

Proposed Gate key 

required for 

vehicle entry; 

separate gate 

combo for foot 

entry

JOMU Strentzel 

Creek

STR 1 4203860 575809 260 ft Alhambra Ave. south past Mt. Wanda, veer right, enter at 

Strain Ranch; site is just above confluence with 4th N. 

tributary (counting from east to west

Briones 

Valley

Ephemeral; 

small 

spring-fed 

tributary

Alternate Key to Strain 

Ranch gate, 

coordinate 

with park 

contact re: 

private 

property

JOMU Strentzel 

Creek

STR 2 4203819 575797 260 ft 4th north tributary (from east to west) Briones 

Valley

ephemeral Alternate 

JOMU Strentzel 

Creek

STR 3 4203805 575781 260 ft 3rd south tributary (from east to west) Briones 

Valley

ephemeral Alternate 

JOMU Strentzel 

Creek

STR 4 4203594 576341 260 ft mainstem Strentzel Creek at fire road crossing near Strain 

Ranch

Briones 

Valley

ephemeral Alternate 

JOMU Strentzel 

Creek

STR 5 4203759 576711 220 ft mainstem Strentzel Creek above Alhambra Ave. culvert Briones 

Valley

ephemeral Alternate 

PINN Sandy 

Creek

SC 1 4039107 665268 920 ft I-280 south to San Jose; 101 south to Hwy. 25 to 

Hollister; Hwy. 25 to PINN (Hwy. 146). Park at Hwy. 

146 pull-out near air quality site; site is in creek opposite 

of air quality site

North 

Chalone 

Peak

intermittent Proposed

PINN Sandy 

Creek

SC 2 4039516 665483 1000 ft In Pinnacles Campground; near park boundary; far 

southwest side of campground, near restroom leachfield; 

sample upstream of culvert 

North 

Chalone 

Peak

intermittent Alternate 
97

Park/

Owner Stream Site ID UTM N UTM E Elevation Access/Directions

Topo Quad

(7.5-

minute)

Stream 

Type Site Type

Permission & 

Access Notes

PINN Sandy 

Creek

SC3 4040202 666068 1000 ft In Pinnacles campground near pump-out station and 

downstream of restroom (adjacent to leachfield); 

opposite side of campground as SC 2 (i.e., far north east 

end); upstream of tributary confluence

North 

Chalone 

Peak

intermittent Alternate 

Private McCabe 

Creek

MC1 4040066 665749 1000 ft McCabe Canyon above Hwy. 146 culvert; across from 

Pinnacles campground

North 

Chalone 

Peak

intermittent Proposed Notify 

landowner 

(contact park), 

gate key 

required

PINN Bear Gulch BG 2 4038964 663073 1240 ft Park at visitor center parking lot; walk to Resource 

Management bldg.; sample behind the building near 

footbridge

North 

Chalone 

Peak

intermittent Proposed

PINN Chalone 

mainstem

CHA 1 4038045 665325 920 ft Hwy. 146 before (east of) East Entrance station; follow 

fire road to parking area on the right before road crosses 

creek. Follow pink flagging to site. 

North 

Chalone 

Peak

intermittent Proposed Gate key 

required; 4x4 

may be needed 

in wet 

conditions

PINN Chalone 

mainstem

CHA 2 4039344 664153 1000 ft Hwy. 146 Road Bridge to visitor’s center; site is 

downstream of bridge across from fire wayside exhibit 

and portable toilet

North 

Chalone 

Peak

dry summer 

to fall

Proposed

PINN North Fork 

Chalone

CHA 3 4041178 662881 1080 ft Hwy. 146 Chalone Picnic Area; pass picnic area for 

access to North Wilderness trail; site is just upstream of 

West Fork

North 

Chalone 

Peak

dry summer 

to fall

Alternate Note: Road 

along Chalone 

Creek has been 

removed in 

this area
98

Site History and Site ID Selection

RC2 GGNRA pre-1999 database, stables studies no ROD 20, RC-1-2500 in stables study and (draft protocol v. 2.01), RC Control

TV1 GGNRA pre-1999 database, stables studies no TV 1-2615 stables study and (draft protocol v. 2.01) (site access restricted since 

near private residence?)

Site ID Source of site location Site ID the same? Notes

OLM 18 PORE on-going database yes

OLM 14 PORE on-going database yes

OLM 11 PORE on-going database yes

OLM 10B PORE on-going database yes

OLM 1 PORE on-going database yes

OLM 6A PORE on-going database yes

OLM 4 PORE on-going database yes

OLM 2 PORE on-going database no This site is entered as OLM 2A in PORE WQ database (OLM 2 was downstream or 

culvert)

PNG 1 PORE on-going database yes near PGL 1 from GGNRA pre-1999 database

PNG 2 SFAN 2004 Macroinvert Sampling yes same as macroinvert site

PNG 3 SFAN 2004 Macroinvert Sampling yes same as macroinvert site

LAG 1 PORE on-going database yes

LAG 2 PORE on-going database yes

LAG 3 PORE on-going database yes

GG1 stables and Big Lagoon studies no GG north (draft protocol v. 2.01); check access since private property (Green Gulch 

Farm and Zen Center)

GG2 stables and Big Lagoon studies no GG Control (draft protocol v. 2.01); check access since private property (Green Gulch 

Farm and Zen Center)

GGD GGNRA pre-1999 database, stables studies no GGD Culvert (draft protocol v. 2.01); similar to GGD 3 (RDW-4-1), but away from 

culvert affects

BAND 1 GGNRA pre-1999 database yes near "Banducci" site in 2004 USF (J.Lendvay) study; near Station 9 in 1994 USF 

(Leach, Podlech,Brown) study "Redwood Creek: Banducchi Bridge"

RDW 1 GGNRA pre-1999 database, USF studies yes (pre-99 database) close to Station 2 in USF Podlech, Brown, & Karentz study (1994) and Station 10 in 

USF Leach, Podlech, & Brown (1997)

RDW 2 GGNRA pre-1999 database no RDW3 (draft protocol v. 2.01)

RDW3 GGNRA pre-1999 database, stables and 

Big Lagoon studies, USF studies

no RDW MuBe (draft protocol v. 2.01)RDW 22, Ped Bridge @ Muir Beach, Redwood 

Creek at Muir Beach Parking Lot, "Muir Beach" in J. Lendvay, 2004 (USF)

KC 1 GGNRA pre-1999 database yes

CDC 2 GGNRA pre-1999 database yes

FC 1 University of San Francisco (USF) studies no (USF - M. Podlech, 1994);Station 11 ("Fern Creek at the mouth, in Muir Woods"

FC 2 University of San Francisco (USF) studies no USF - Jack Lendvay, 2004; "Fern Creek" site name

BJC1 GGNRA pre-99 database; University of 

San Francisco (USF) studies; 

yes, pre-99 database RDW, pre-99 database and (draft protocol v. 2.01); USF - Jack Lendvay, 2004; 

"Bootjack Creek" site name and USF - Podlech, Brown, & Karentz, 1994; Station 3 

("Redwood Creek headwaters at Bootjack Camp")

GERB1 GGNRA pre-1999 database no ROD 6 (draft protocol v. 2.01)

RC1 GGNRA stables studies, SFAN 2004 

monitoring; USF 

no RC 1-750 in stables study and (draft protocol v. 2.01); Station 3 in (Leach, Podlech, and 

Brown, 1997)
99

TV2 GGNRA pre-1999 database, stables studies, 

USF, SFAN 2004 Monitoring

no also TV 1-2095 in stables study, pre-99 db and (draft protocol v. 2.01); Station 6 

in USF (Leach, Podlech, and Brown, 1997)

TV3 GGNRA pre-1999 database, stables studies no TV1-1120 stables study and (draft protocol v. 2.01)also TV 8 in pre-1999 

database, ; site ID same as SFAN 2004 monitoring

NYH 1 GGNRA pre-1999 database, SFAN 2004 

monitoring

No, TV 9 changed name since it is not in the Tennessee Valley watershed

OAK 1 GGNRA pre-1999 database, SFAN 2004 

monitoring

No, TV 3 changed name since it is not in the Tennessee Valley watershed

WU 1 SFAN 2004 monitoring yes

WU 2 SFAN 2004 monitoring yes

WU 3 SFAN 2004 monitoring yes

WU 4 new site, (SFAN 2003 recon)

MGG 1 SFAN 2004 monitoring yes

FRA 1 SFAN 2004 monitoring yes

STR 1 SFAN 2004 monitoring yes

STR 2 SFAN 2004 monitoring yes

STR 3 SFAN 2004 monitoring yes

STR 4 SFAN 2004 monitoring yes

STR 5 SFAN 2004 monitoring yes

SC 1 PINN 1997-2002 monitoring, SFAN 2004 

monitoring

yes Same as SFAN 2004 monitoring

SC 2 new PINN site 2005 (assistance from SFAN) Yes Same as 2005 site

SC3 new PINN site 2005 Yes Same as 2005 site

MC1 new PINN site 2005 Yes Same as 2005 site

BG 2 PINN 1997-2002 monitoring, SFAN 2004 

monitoring

Yes Same as SFAN 2004 monitoring

CHA 1 PINN 1997-2002 monitoring, SFAN 2004 

monitoring

Yes Same as SFAN 2004 monitoring

CHA 2 PINN 1997-2002 monitoring, SFAN 2004 

monitoring

Yes Same as SFAN 2004 monitoring

CHA 3 PINN 1997-2002 monitoring No "North Fork - approximately 30-40 m upstream of confluence"
100
101

Appendix F. Maps of Watersheds and Sampling Locations 
102

San Francisco Area Network Nat1ona1 Park serv1ce ",·;;;:; ...,... Proposed Fresh Water Qual1ty Man 1tonng S1tes us Department of the Intenor .. 

Golden Gate, Pomt Reyes, John MUir 

D Watersheds 

- Point Reyes Administrative Boundary 

D Golden Gate Legislative Boundary 

- John Muir Administrative Boundary 

2.5 10 15 20 

Miles 
103

San Francisco Area Network Nat1ona1 Park serv1ce ·.::·:: 

......,_ Lagun1tas & Olema Creek, Proposed Freshwater Quality S1tes us Department of the Intenor .,. 

518000 

Fresh Water Quality Site Type 

• Alternate j, 

e Proposed ~ 

r::::::J Point Reyes Legislative Boundary 

r::::::J GOGA Legislative Boundary 

[QILagunitas Watershed 

0 0.5 

S20000 522000 524000 526000 
104

San Francisco Area Network Nat1ona1 Park serv1ce ·.::·:: 

P1ne Gulch Watershed, Proposed Freshwater Qual1ty S1tes u s Department of the Intenor ......,_ 

522000 

Fresh Water Quality Site Type 

• Proposed N 

Pine Gulch Watershed f 

GOGA Legislative Boundary · .. 

Point Reyes Legislative Boundary 

0.5 

Miles 

522000 

.. 524000 526000 528000 

524000 
105

San Francisco Area Network Nat1ona1 Park serv1ce ·,::·:: 

Upper Redwood Creek, Proposed Freshwater Quality S1tes u s Department of the Intenor ......,_ 

.. 534000 536000 538000 540000 
106

San Francisco Area Network Nat1ona1 Park serv1ce ·.::·:: 

Lower Redwood Creek, Proposed Freshwater Quality S1tes u s Department of the Intenor ......,_ 

.. 536000 538000 540000 

Alternate N 

Proposed ~ 

Redwood Creek Watershed 

0 0.25 0.5 

Miles 

536000 538000 
107

~ illlli!!~~:;,s~~~ffi i: 

-

"' ... 

gH~~~ ~~~~~ ~~~~ 

"' 

~ 

0 

~~~~~ ~~ ~~ ~~ ~~~~~~~~~~g 

"' 

~ 

0 

0 

0 

.... 

co 

~ 

N e Proposed Sites ! 

+ Alternate Sites ~ 

CJ Tennessee Valley Watershed 

c::::J GOGA Legislative Boundary 

0.2 0.4 0.8 

Miles 

FILE: IIINPPORE07/GIS/GISiprojocts11Wator quality/SFAN WQ maps!SFAN_WQ_TENN.mxd 
108

0 

0 

0 

"' "' 

~ 

Fresh Water Quality Site Types N 

• • 

Proposed Sites 

Alternate Sites i c::J Watershed Boundary 

c::J GOGA Legislative Boundary 

0.6 0.9 

Miles 

540000 541000 542000 543000 FILE: IIINPPORE07/GISIGIS/projocts1AYater quality/SFAN WQ maps/SFAN_WQ_ROOEO.mxd 
109

San Francisco Area Network Nat1ona1 Park serv1ce ·.::·:: 

Franklin Creek and Strentzel Creek, Proposed Freshwater Qual1ty S1tes us Department of the Intenor ......,_ 

.. 576000 

0.125 0.25 

Miles 

576000 
110

San Francisco Area Network Nat1ona1 Park serv1ce ·,::·:: 

......,_ West Un1on Creek, Proposed Freshwater Quality S1tes u s Department of the Intenor .,. 

560000 562000 564000 
111

San Francisco Area Network Nat1ona1 Park serv1ce ",·;;;:; ...,... P1nnacles Nat1onal Monument Fresh Water Quality Momtormg us Department of the Intenor .. 
112

San Francisco Area Network Nat1ona1 Park serv1ce ·,·:.··.:: 

Chalone Creek, Proposed Freshwater Qual1ty S1tes us Department of the Intenor ,..,..,_ 

'l'// Chalone Creek 

Sandy Creek 

0.25 0.5 

Miles 

.. 664000 666000 
113

Appendix G. Metadata Checklist and SFAN NPSTORET 

Characteristics Definitions Report

Metadata Checklist (Tucker, D. personal communication, 14 November 2004.)

Projects:

1) Project ID (8 characters or less)

2) Project Name (60 characters or less)

3) Start Date

4) Project Duration (15 characters or less) - typically this would be something like "Ongoing", "2 

Years", 

 etc.

5) Project Purpose (4000 characters or less)

Stations:

1) Location ID (15 characters or less)

2) Name (60 characters or less)

3) Station Primary Type (Stream/River; Wetland, etc. from STORET Pick List)

4) Station Secondary Type (Only for certain Primary Types: e.g. Canal, CERCLA Superfund 

Site, Facility, 

 Mine/Mine Discharge, and Wetland)

5) Decimal degrees latitude/longitude

6) Lat/Lon Method (STORET Pick List)

7) Lat/Lon Datum (STORET Pick List)

8) County

9) State

Metadata:

For every characteristic measured, provide, as appropriate:

1) Official EPA STORET Characteristic Name (STORET Pick List)

2) Your Name for the Parameter/Characteristic

3) Sample Fraction (STORET Pick List)

4) Units

5) Value Type (Actual, Calculated, Estimated)

6) Field/Lab

7) Medium

8) Statistic Type (STORET Pick List)

9) Duration Basis (STORET Pick List)

10) Weight Basis (STORET Pick List)

11) Temperature Basis (STORET Pick List)

12) Particle Size Basis

13) Analytical Procedure - (e.g. Metals in Marine Waters by ICP/MS - EPA/ORD 200.1; 

Ammonia Nitrogen in Water, Hach 8038)
114

14) Gear Configuration (name or type of instrument and how it was configured)

15) Sample Collection Procedure/Description (for samples taken to a lab)

16) Sample Handling Procedure (e.g. Cool to 4°C, adjust pH <2 with H2SO4)

17) Lab Sample Preparation Procedure (e.g. filtration of water samples, 0.45 microns)

18) Lab Identification and Certification for Characteristic (what lab and was it certified for that 

 characteristic)

19) Detection Limit

20) Lower Quantification Limit

21) Upper Quantification Limit

22) Description/Interpretation of the Limit

23) Lower Range Value (used for warning messages about possible out of range values during 

data entry)

24) Upper Range Value (used for warning messages about possible out of range values during 

data entry)

25) Free Text Characteristic/Parameter Description

Metadata Checklist (cont.)

Results:

1) Station ID - one of the previously entered

2) Date

3) Time (optional)

4) Time Zone (required if Time given)

5) Activity/Sample ID

6) Replicate Number (optional)

7) Depth (optional)

8) Depth Units (required if Depth given)

9) Your Name for Parameter/Characteristic

10) Detection Condition (STORET Pick List)

11) Result Value/Text

12) Value Type (Actual, Calculated, Estimated)

13) Value Status (Final, Preliminary)

14) Lab Remarks (STORET Pick List)

15) Detection Limit (if not given in metadata and/or varies with results)

16) Lower Quantification Limit (if not given in metadata and/or varies with results)

17) Upper Quantification Limit (if not given in metadata and/or varies with results)

18) Description/Interpretation of the Limit (if not given in metadata and/or varies with results)
115

SFAN NPSTORET Characteristics Definitions Report

Printed 9/28/06 (contact SFAN for most current version)

NPSTORET Characteristics 

San Francisco Bay Area Network Sorted by Sequence Number

STORET Name: Temperature, air Local AirTemp_YSI85

Comp? 

Sequence 100 Sample Value Act Unit of deg C Field/Lab: Field

MediumAir Statistic Type: Duration:

Weight Basis: Part. Size Basis: Temp. Basis:

Detection Limit: Lower Quant Upper Quant 

Detection/Quantification Limit 

QA/QC Lower Range 10 QA/QC Upper Range 38

Characteristic 

Defined Procedures, Configuration, &&

Analytical: SFAN_SOP 5: Field Methods for Measurement of Core Parameters

Collection: WQ_PROBE: Field Methods for Measurement of Core Parameters

Gear Config: YSI 85: Multiparameter probe

Projects: SFAN_I&M: SFAN Long-Term Water Quality Monitoring Program

SFAN_WQ: SFAN pilot monitoring for Freshwater Quality Protocol

Groups: Field: Field Parameters (F)

STORET Name: Temperature, air Local AirTemp_Glass

Comp? 

Sequence 101 Sample Value Unit of deg C Field/Lab: Field

MediumAir Statistic Type: Duration:

Weight Basis: Part. Size Basis: Temp. Basis:

Detection Limit: Lower Quant Upper Quant 

Detection/Quantification Limit 

QA/QC Lower Range QA/QC Upper Range 

Characteristic 
116

Defined Procedures, Configuration, &&

Projects: SFAN_I&M: SFAN Long-Term Water Quality Monitoring Program

Groups: Field: Field Parameters (F)

STORET Name: Temperature, air Local AirTemp_Oakton

Comp? 

Sequence 101.5 Sample Value Unit of deg C Field/Lab: Field

MediumAir Statistic Type: Duration:

Weight Basis: Part. Size Basis: Temp. Basis:

Detection Limit: Lower Quant Upper Quant 

Detection/Quantification Limit 

QA/QC Lower Range QA/QC Upper Range 

Characteristic Air temperature taken with the Oakton pHTestr 30

Defined Procedures, Configuration, &&

Projects:

Groups: Field: Field Parameters (F)

Thursday, September 28, 2006 Page 12 of 35
117

NPSTORET Characteristics 

San Francisco Bay Area Network Sorted by Sequence Number

STORET Name: Temperature, water Local H2OTemp_YSI85

Comp? 

Sequence 102 Sample Value Act Unit of deg C Field/Lab: Field

MediumWater Statistic Type: Duration:

Weight Basis: Part. Size Basis: Temp. Basis:

Detection Limit: Lower Quant Upper Quant 

Detection/Quantification Limit 

QA/QC Lower Range 10 QA/QC Upper Range 17

Characteristic 

Defined Procedures, Configuration, &&

Analytical: SFAN_SOP 5: Field Methods for Measurement of Core Parameters

Collection: WQ_PROBE: Field Methods for Measurement of Core Parameters

Gear Config: YSI 85: Multiparameter probe

Projects: SFAN_I&M: SFAN Long-Term Water Quality Monitoring Program

SFAN_WQ: SFAN pilot monitoring for Freshwater Quality Protocol

Groups: Field: Field Parameters (F)

STORET Name: Temperature, water Local H2OTemp_Oakton

Comp? 

Sequence 103 Sample Value Unit of deg C Field/Lab: Field

MediumWater Statistic Type: Duration:

Weight Basis: Part. Size Basis: Temp. Basis:

Detection Limit: Lower Quant Upper Quant 

Detection/Quantification Limit 

QA/QC Lower Range QA/QC Upper Range 

Characteristic 

Defined Procedures, Configuration, &&

Projects: SFAN_I&M: SFAN Long-Term Water Quality Monitoring Program

Groups: Field: Field Parameters (F)
118

STORET Name: Temperature, water Local H2OTemp_Glass

Comp? 

Sequence 104 Sample Value Unit of deg C Field/Lab: Field

MediumWater Statistic Type: Duration:

Weight Basis: Part. Size Basis: Temp. Basis:

Detection Limit: Lower Quant Upper Quant 

Detection/Quantification Limit 

QA/QC Lower Range QA/QC Upper Range 

Characteristic 

Defined Procedures, Configuration, &&

Projects: SFAN_I&M: SFAN Long-Term Water Quality Monitoring Program

Groups: Field: Field Parameters (F)

STORET Name: Specific conductance Local Cond_YSI85

Comp? 

Sequence 105 Sample Value Act Unit of uS/cm Field/Lab: Field

MediumWater Statistic Type: Duration:

Weight Basis: Part. Size Basis: Temp. Basis:

Thursday, September 28, 2006 Page 13 of 35
119

NPSTORET Characteristics 

San Francisco Bay Area Network Sorted by Sequence Number

Detection Limit: Lower Quant Upper Quant 

Detection/Quantification Limit 

QA/QC Lower Range WQ_PROBE: Field Methods for Measurement of Core Parameters QA/QC Upper 

Range 

Characteristic YSI 85: Multiparameter probe

Defined Procedures, Configuration, && SFAN_I&M: SFAN Long-Term Water Quality Monitoring Program

SFAN_WQ: SFAN pilot monitoring for Freshwater Quality Protocol

Collection: Field: Field Parameters (F)

STORET Name: Specific conductance Local SC_YSI85 Comp?



Sequence 106 Sample Value Cal Unit of uS/cm Field/Lab: Field

MediumWater Statistic Type: Duration:

Weight Basis: Part. Size Basis: Temp. Basis: 25 Deg C

Detection Limit: Lower Quant Upper Quant 

Detection/Quantification Limit 

QA/QC Lower Range QA/QC Upper Range 

Characteristic 

Defined Procedures, Configuration, &&

Analytical: SFAN_SOP 5: Field Methods for Measurement of Core Parameters

Collection: WQ_PROBE: Field Methods for Measurement of Core Parameters

Gear Config: YSI 85: Multiparameter probe

Projects: SFAN_I&M: SFAN Long-Term Water Quality Monitoring Program

SFAN_WQ: SFAN pilot monitoring for Freshwater Quality Protocol

Groups: Field: Field Parameters (F)

STORET Name: Salinity Local Salinity_YSI85 Comp?



Sequence 107 Sample Dissolved Value Unit of ppth Field/Lab: Field

MediumWater Statistic Type: Duration:

Weight Basis: Part. Size Basis: Temp. Basis:
120

Detection Limit: Lower Quant Upper Quant 

Detection/Quantification Limit 

QA/QC Lower Range QA/QC Upper Range 

Characteristic Value determined by YSI85 using specific conductance and algorithms found in SMEWW. While 

technically unitless, values are close to those using mass of dissolved salts in given mass of water 

(parts per thousand).

Defined Procedures, Configuration, &&

Analytical: SFAN_SOP 5: Field Methods for Measurement of Core Parameters

Collection: WQ_PROBE: Field Methods for Measurement of Core Parameters

Gear Config: YSI 85: Multiparameter probe

Projects: SFAN_I&M: SFAN Long-Term Water Quality Monitoring Program

SFAN_WQ: SFAN pilot monitoring for Freshwater Quality Protocol

Groups: Field: Field Parameters (F)

Thursday, September 28, 2006 Page 14 of 35
121

NPSTORET Characteristics 

San Francisco Bay Area Network Sorted by Sequence Number

STORET Name: Dissolved oxygen saturation Local DO%_YSI85

Comp? 

Sequence 108 Sample Value Act Unit of % Field/Lab: Field

MediumWater Statistic Type: Duration:

Weight Basis: Part. Size Basis: Temp. Basis:

Detection Limit: Lower Quant Upper Quant 

Detection/Quantification Limit 

QA/QC Lower Range QA/QC Upper Range 

Characteristic 

Defined Procedures, Configuration, &&

Analytical: SFAN_SOP 5: Field Methods for Measurement of Core Parameters

Collection: WQ_PROBE: Field Methods for Measurement of Core Parameters

Gear Config: YSI 85: Multiparameter probe

Projects: SFAN_I&M: SFAN Long-Term Water Quality Monitoring Program

SFAN_WQ: SFAN pilot monitoring for Freshwater Quality Protocol

Groups: Field: Field Parameters (F)

STORET Name: Dissolved oxygen (DO) Local DO_YSI85

Comp? 

Sequence 109 Sample Value Act Unit of mg/l Field/Lab: Field

MediumWater Statistic Type: Duration:

Weight Basis: Part. Size Basis: Temp. Basis:

Detection Limit: Lower Quant Upper Quant 

Detection/Quantification Limit 

QA/QC Lower Range QA/QC Upper Range 

Characteristic 

Defined Procedures, Configuration, &&

Analytical: SFAN_SOP 5: Field Methods for Measurement of Core Parameters

Collection: WQ_PROBE: Field Methods for Measurement of Core Parameters
122

Gear Config: YSI 85: Multiparameter probe

Projects: SFAN_I&M: SFAN Long-Term Water Quality Monitoring Program

SFAN_WQ: SFAN pilot monitoring for Freshwater Quality Protocol

Groups: Field: Field Parameters (F)

STORET Name: pH Local pH_Oakton Comp?



Sequence 110 Sample Value Act Unit of None Field/Lab: Field

MediumWater Statistic Type: Duration:

Weight Basis: Part. Size Basis: Temp. Basis:

Detection Limit: 0.01 Lower Quant 0.0318 Upper Quant 15

Detection/Quantification Limit 

QA/QC Lower Range 6.5 QA/QC Upper Range 8.5

Characteristic 

Defined Procedures, Configuration, &&

Analytical: SFAN_SOP 5: Field Methods for Measurement of Core Parameters

Collection: WQ_PROBE: Field Methods for Measurement of Core Parameters

Gear Config: OAKTON_PH: Oakton pH Testr 30

Projects: SFAN_I&M: SFAN Long-Term Water Quality Monitoring Program

SFAN_WQ: SFAN pilot monitoring for Freshwater Quality Protocol

Groups: Field: Field Parameters (F)

Thursday, September 28, 2006 Page 15 of 35
123

NPSTORET Characteristics 

San Francisco Bay Area Network Sorted by Sequence Number

STORET Name: pH Local pH_paper Comp? 

Sequence 111 Sample Value Unit of None Field/Lab: Field

MediumWater Statistic Type: Duration:

Weight Basis: Part. Size Basis: Temp. Basis:

Detection Limit: Lower Quant Upper Quant 

Detection/Quantification Limit 

QA/QC Lower Range QA/QC Upper Range 

Characteristic 

Defined Procedures, Configuration, &&

Analytical: SFAN_SOP 5: Field Methods for Measurement of Core Parameters

Projects: SFAN_I&M: SFAN Long-Term Water Quality Monitoring Program

Groups: Field: Field Parameters (F)

STORET Name: Flow, severity (choice list) Local Flow_Severity

Comp? 

Sequence 112 Sample Value Est Unit of None Field/Lab: Field

MediumWater Statistic Type: Duration:

Weight Basis: Part. Size Basis: Temp. Basis:

Detection Limit: Lower Quant Upper Quant 

Detection/Quantification Limit 

QA/QC Lower Range 1 QA/QC Upper Range 6

Characteristic 1=No Flow; 2=Low Flow; 3=Normal Flow; 4=Flood Flow; 5=High Flow; 6=Dry. Subjective, nonsequencial values that will be relative measures for each stream. Used by SWQCB Surface Water

Ambient Monitoring Program (SWAMP)

Defined Procedures, Configuration, &&

Collection: FLOW: Field Methods for Flow Measurements

Projects: OLM_TMDL: Olema Creek Pathogen TMDL Monitoring Program

SFAN_I&M: SFAN Long-Term Water Quality Monitoring Program

SFAN_WQ: SFAN pilot monitoring for Freshwater Quality Protocol
124

Groups: Field: Field Parameters (F)

STORET Name: Flow Local discharge Comp? 

Sequence 113 Sample Value Cal Unit of cfs Field/Lab: Field

MediumWater Statistic Type: Duration:

Weight Basis: Part. Size Basis: Temp. Basis:

Detection Limit: 0.01 Lower Quant Upper Quant 

Detection/Quantification Limit 

QA/QC Lower Range QA/QC Upper Range 

Characteristic 

Defined Procedures, Configuration, &&

Analytical: SFAN_SOP 9: Field Methods for Flow Measurements

Collection: FLOW: Field Methods for Flow Measurements

Gear Config: FLO-MATE: Marsh-McBirney Flo-Mate

Projects: SFAN_I&M: SFAN Long-Term Water Quality Monitoring Program

SFAN_WQ: SFAN pilot monitoring for Freshwater Quality Protocol

Groups: Field: Field Parameters (F)

Thursday, September 28, 2006 Page 16 of 35
125

NPSTORET Characteristics 

San Francisco Bay Area Network Sorted by Sequence Number

STORET Name: Flow Local Estimated velocity

Comp? 

Sequence 114 Sample Value Est Unit of ft/sec Field/Lab: Field

MediumWater Statistic Type: Duration:

Weight Basis: Part. Size Basis: Temp. Basis:

Detection Limit: Lower Quant Upper Quant 

Detection/Quantification Limit 

QA/QC Lower Range QA/QC Upper Range 

Characteristic Estimation of stream flow velocity based on the "orange peel" method. Reported value is the 

average of a minimum of three replicates

Defined Procedures, Configuration, &&

Analytical: SFAN_SOP 9: Field Methods for Flow Measurements

Projects: OLM_TMDL: Olema Creek Pathogen TMDL Monitoring Program

PORE_BO: NOAA Fisheries Biological Opinion on Grazing

PORE_HSP: PORE Horseshoe Pond Restoration Project

PORE_WQ: PORE Water Quality Monitoring Program

SFAN_I&M: SFAN Long-Term Water Quality Monitoring Program

SFAN_WQ: SFAN pilot monitoring for Freshwater Quality Protocol

Groups: Field: Field Parameters (F)

STORET Name: Flow Local Estimated Flow Comp?



Sequence 115 Sample Value Unit of cfs Field/Lab: Field

MediumWater Statistic Type: Duration:

Weight Basis: Part. Size Basis: Temp. Basis:

Detection Limit: Lower Quant Upper Quant 

Detection/Quantification Limit 

QA/QC Lower Range QA/QC Upper Range 

Characteristic Estimated flow uses "orange peel" or "float" method to determine average velocity in the centroid of

flow and several depths in the cross-section, along with stream width to determine an estimate of 

flow. Most likely to overestimate cfs due to avg. velocity being taken from the centroid of flow.
126

Defined Procedures, Configuration, &&

Analytical: SFAN_SOP 9: Field Methods for Flow Measurements

Projects: SFAN_I&M: SFAN Long-Term Water Quality Monitoring Program

Groups: Field: Field Parameters (F)

STORET Name: Gage heightLocal Gage Height Comp?



Sequence 116 Sample Value Act Unit of ft Field/Lab: Field

MediumWater Statistic Type: Duration:

Weight Basis: Part. Size Basis: Temp. Basis:

Detection Limit: 0.2 Lower Quant Upper Quant 

Detection/Quantification Limit 

QA/QC Lower Range QA/QC Upper Range 

Characteristic 

Defined Procedures, Configuration, &&

Analytical: SFAN_SOP 9: Field Methods for Flow Measurements

Collection: FLOW: Field Methods for Flow Measurements

Thursday, September 28, 2006 Page 17 of 35

OLM_TMDL: Olema Creek Pathogen TMDL Monitoring Program

PORE_BO: NOAA Fisheries Biological Opinion on Grazing

PORE_HSP: PORE Horseshoe Pond Restoration Project

PORE_WQ: PORE Water Quality Monitoring Program

SFAN_I&M: SFAN Long-Term Water Quality Monitoring Program

SFAN_WQ: SFAN pilot monitoring for Freshwater Quality Protocol

Field: Field Parameters (F)
127

NPSTORET Characteristics 

San Francisco Bay Area Network Sorted by Sequence Number

STORET Name: Stream width measure Local Stream Width

Comp? 

Sequence 117 Sample Value Act Unit of ft Field/Lab: Field

MediumWater Statistic Type: Duration:

Weight Basis: Part. Size Basis: Temp. Basis:

Detection Limit: 0.1 Lower Quant 0.1 Upper Quant 

Detection/Quantification Limit 

QA/QC Lower Range QA/QC Upper Range 

Characteristic 

Defined Procedures, Configuration, &&

Analytical: SFAN_SOP 9: Field Methods for Flow Measurements

Collection: FLOW: Field Methods for Flow Measurements

Projects: OLM_TMDL: Olema Creek Pathogen TMDL Monitoring Program

PORE_BO: NOAA Fisheries Biological Opinion on Grazing

PORE_HSP: PORE Horseshoe Pond Restoration Project

PORE_WQ: PORE Water Quality Monitoring Program

SFAN_I&M: SFAN Long-Term Water Quality Monitoring Program

SFAN_WQ: SFAN pilot monitoring for Freshwater Quality Protocol

Groups: Field: Field Parameters (F)

STORET Name: Weather Comments (text) Local weather Comp?



Sequence 118 Sample Value Unit of Field/Lab:

Medium Statistic Type: Duration:

Weight Basis: Part. Size Basis: Temp. Basis:

Detection Limit: Lower Quant Upper Quant 

Detection/Quantification Limit 

QA/QC Lower Range QA/QC Upper Range 

Characteristic 
128

Defined Procedures, Configuration, &&

Projects: BEACH_WQ: Beach Recreational Water Quality Monitoring Program

OLM_TMDL: Olema Creek Pathogen TMDL Monitoring Program

PORE_BO: NOAA Fisheries Biological Opinion on Grazing

PORE_HSP: PORE Horseshoe Pond Restoration Project

PORE_WQ: PORE Water Quality Monitoring Program

SFAN_I&M: SFAN Long-Term Water Quality Monitoring Program

SFAN_WQ: SFAN pilot monitoring for Freshwater Quality Protocol

Groups: Field: Field Parameters (F)

GENERAL: General Observations

Thursday, September 28, 2006 Page 18 of 35
129

NPSTORET Characteristics 

San Francisco Bay Area Network Sorted by Sequence Number

STORET Name: Precipitation Time Since Event Local Last Precipitation

Comp? 

Sequence 119 Sample Value Est Unit of days Field/Lab: Field

MediumOther Statistic Type: Duration:

Weight Basis: Part. Size Basis: Temp. Basis:

Detection Limit: Lower Quant Upper Quant 

Detection/Quantification Limit 

QA/QC Lower Range QA/QC Upper Range 

Characteristic 

Defined Procedures, Configuration, &&

Projects: BEACH_WQ: Beach Recreational Water Quality Monitoring Program

OLM_TMDL: Olema Creek Pathogen TMDL Monitoring Program

PORE_WQ: PORE Water Quality Monitoring Program

SFAN_I&M: SFAN Long-Term Water Quality Monitoring Program

SFAN_WQ: SFAN pilot monitoring for Freshwater Quality Protocol

Groups: Field: Field Parameters (F)

GENERAL: General Observations

STORET Name: Water appearance (text) Local Water Appearance

Comp? 

Sequence 120 Sample Value Unit of Field/Lab: Lab

MediumWater Statistic Type: Duration:

Weight Basis: Part. Size Basis: Temp. Basis:

Detection Limit: Lower Quant Upper Quant 

Detection/Quantification Limit 

QA/QC Lower Range QA/QC Upper Range 

Characteristic 
130

Defined Procedures, Configuration, &&

Collection: WQ_SAMPLE: General Water Quality Procedures

Projects: BEACH_WQ: Beach Recreational Water Quality Monitoring Program

PORE_WQ: PORE Water Quality Monitoring Program

SFAN_I&M: SFAN Long-Term Water Quality Monitoring Program

SFAN_WQ: SFAN pilot monitoring for Freshwater Quality Protocol

Groups: Field: Field Parameters (F)

GENERAL: General Observations

STORET Name: General Observation (text) Local General Notes

Comp? 

Sequence 121 Sample Value Unit of Field/Lab: Field

Medium Statistic Type: Duration:

Weight Basis: Part. Size Basis: Temp. Basis:

Detection Limit: Lower Quant Upper Quant 

Detection/Quantification Limit 

QA/QC Lower Range QA/QC Upper Range 

Characteristic 

Defined Procedures, Configuration, &&

Thursday, September 28, 2006 Page 19 of 35

BEACH_WQ: Beach Recreational Water Quality Monitoring Program

OLM_TMDL: Olema Creek Pathogen TMDL Monitoring Program

PORE_WQ: PORE Water Quality Monitoring Program

SFAN_I&M: SFAN Long-Term Water Quality Monitoring Program

SFAN_WQ: SFAN pilot monitoring for Freshwater Quality Protocol

Field: Field Parameters (F)

GENERAL: General Observations
131

NPSTORET Characteristics 

San Francisco Bay Area Network Sorted by Sequence Number

STORET Name: Turbidity Local turbidity_Hach2100

Comp? 

Sequence 122 Sample Value Act Unit of NTU Field/Lab: Field

MediumWater Statistic Type: Duration:

Weight Basis: Part. Size Basis: Temp. Basis:

Detection Limit: 0.01 Lower Quant 0.0318 Upper Quant 1000

Detection/Quantification Limit 

QA/QC Lower Range QA/QC Upper Range 

Characteristic 

Defined Procedures, Configuration, &&

Analytical: 8195: Determination of Turbidity

Collection: DI_SAMPLE: Field and Laboratory Methods for Sediment

Projects: SFAN_I&M: SFAN Long-Term Water Quality Monitoring Program

SFAN_WQ: SFAN pilot monitoring for Freshwater Quality Protocol

Groups: Field: Field Parameters (F)

Sediment: Sediment Analysis (S)

STORET Name: Turbidity severity (choice list) Local turbidity severity

Comp? 

Sequence 123 Sample Value Unit of Field/Lab:

Medium Statistic Type: Duration:

Weight Basis: Part. Size Basis: Temp. Basis:

Detection Limit: Lower Quant Upper Quant 

Detection/Quantification Limit 

QA/QC Lower Range QA/QC Upper Range 

Characteristic 

Defined Procedures, Configuration, &&

Projects: SFAN_I&M: SFAN Long-Term Water Quality Monitoring Program
132

SFAN_WQ: SFAN pilot monitoring for Freshwater Quality Protocol

Groups: Field: Field Parameters (F)

Sediment: Sediment Analysis (S)

STORET Name: Total Coliform Local total coliform

Comp? 

Sequence 124 Sample Value Est Unit of MPN/100ml Field/Lab: Lab

MediumWater Statistic Type: Duration:

Weight Basis: Part. Size Basis: Temp. Basis:

Detection Limit: 2 Lower Quant 2 Upper Quant 1600

Detection/Quantification Limit Limits refer to Most Probable Number (MPN)/100mL of sample volume; Dilutions 

of 10x: 20-16,000; 100x: 200-160,000; 1000x: 2000-1,600,000

QA/QC Lower Range QA/QC Upper Range 

Thursday, September 28, 2006 Page 20 of 35

SM 9221 B: Fecal and total coliform enumeration by Most Probable Number (multiple tube technique)

GRABSAMPLE: Field Methods for Sampling Fecal Indicator Bacteria

 

 

 

 

 

 

 

 

 

 

 
133

NPSTORET Characteristics 

SFAN_I&M: SFAN Long-Term Water Quality Monitoring Program

SFAN_WQ: SFAN pilot monitoring for Freshwater Quality Protocol

San Francisco Bay Area Network Bacteria: Bacteriologic Analysis (B) Sorted by Sequence 

Number

STORET Name: Fecal Coliform Local fecal coliforms

Comp? 

Sequence 125 Sample Value Est Unit of MPN/100ml Field/Lab: Lab

MediumWater Statistic Type: Duration:

Weight Basis: Part. Size Basis: Temp. Basis:

Detection Limit: 2 Lower Quant 2 Upper Quant 1600

Detection/Quantification Limit detection limits and quantification limits can be changed if a sample is diluted; e.g., 

dilute 10x gives a lower detection limit of 20 and upper quantification limit of 16,000, 

etc.

QA/QC Lower Range QA/QC Upper Range 

Characteristic 

Defined Procedures, Configuration, &&

Analytical: SM 9221 B: Fecal and total coliform enumeration by Most Probable Number (multiple tube technique)

Collection: GRABSAMPLE: Field Methods for Sampling Fecal Indicator Bacteria

Projects: SFAN_I&M: SFAN Long-Term Water Quality Monitoring Program

SFAN_WQ: SFAN pilot monitoring for Freshwater Quality Protocol

Groups: Bacteria: Bacteriologic Analysis (B)

STORET Name: Escherichia coli Local E.coli Comp?



Sequence 126 Sample Value Unit of MPN/100ml Field/Lab: Lab

MediumWater Statistic Type: Duration:

Weight Basis: Part. Size Basis: Temp. Basis:

Detection Limit: Lower Quant Upper Quant 

Detection/Quantification Limit 

QA/QC Lower Range QA/QC Upper Range 
134

Characteristic 

Defined Procedures, Configuration, &&

Analytical: 9223-B: Enzyme Substrate Test, E. coli, Coliform Group

Collection: GRABSAMPLE: Field Methods for Sampling Fecal Indicator Bacteria

Projects: SFAN_I&M: SFAN Long-Term Water Quality Monitoring Program

SFAN_WQ: SFAN pilot monitoring for Freshwater Quality Protocol

Groups: Bacteria: Bacteriologic Analysis (B)

STORET Name: Enterococcus Group Bacteria Local Enterococcus

Comp? 

Sequence 127 Sample Value Unit of MPN/100ml Field/Lab: Lab

MediumWater Statistic Type: Duration:

Weight Basis: Part. Size Basis: Temp. Basis:

Thursday, September 28, 2006 Page 21 of 35
135

NPSTORET Characteristics 

San Francisco Bay Area Network Sorted by Sequence Number

Detection Limit: Lower Quant Upper Quant 

Detection/Quantification Limit ENTEROLERT2000: Enterolert Quanti-Tray/2000; Multi Tube, Multi Well, for Enterococcii

QA/QC Lower Range GRABSAMPLE: Field Methods for Sampling Fecal Indicator Bacteria QA/QC Upper 

Range 

Characteristic SFAN_I&M: SFAN Long-Term Water Quality Monitoring Program

Defined Procedures, Configuration, && SFAN_WQ: SFAN pilot monitoring for Freshwater Quality Protocol

Analytical: Bacteria: Bacteriologic Analysis (B)

STORET Name: Suspended Sediment Concentration (SSC)Local SSC

Comp? 

Sequence 128 Sample Total Value Unit of mg/l Field/Lab: Lab

MediumWater Statistic Type: Duration:

Weight Basis: Part. Size Basis: Temp. Basis:

Detection Limit: Lower Quant Upper Quant 

Detection/Quantification Limit 

QA/QC Lower Range QA/QC Upper Range 

Characteristic 

Defined Procedures, Configuration, &&

Analytical: 2540-D: Total Suspended Solids in Water

Collection: DI_SAMPLE: Field and Laboratory Methods for Sediment

Laboratory: SEQ: Sequoia Analytical Laboratory

Projects: SFAN_I&M: SFAN Long-Term Water Quality Monitoring Program

SFAN_WQ: SFAN pilot monitoring for Freshwater Quality Protocol

Groups: Sediment: Sediment Analysis (S)

STORET Name: Total Suspended Solids (TSS) Local TSS Comp?



Sequence 129 Sample Suspended Value Est Unit of mg/l Field/Lab: Lab

MediumWater Statistic Type: Duration:

Weight Basis: Part. Size Basis: Temp. Basis:
136

Detection Limit: 0.5 Lower Quant 1.59 Upper Quant 

Detection/Quantification Limit 

QA/QC Lower Range QA/QC Upper Range 

Characteristic 

Defined Procedures, Configuration, &&

Analytical: 2540-D: Total Suspended Solids in Water

Collection: DI_SAMPLE: Field and Laboratory Methods for Sediment

Projects: SFAN_I&M: SFAN Long-Term Water Quality Monitoring Program

SFAN_WQ: SFAN pilot monitoring for Freshwater Quality Protocol

Groups: Sediment: Sediment Analysis (S)

STORET Name: Nitrogen, ammonia (NH3) as NH3 Local Ammonia as 

NH3 Comp? 

Sequence 130 Sample Total Value Unit of mg/l Field/Lab: Lab

MediumWater Statistic Type: Duration:

Weight Basis: Part. Size Basis: Temp. Basis:

Thursday, September 28, 2006 Page 22 of 35
137

NPSTORET Characteristics 

San Francisco Bay Area Network Sorted by Sequence Number

Detection Limit: 0.1 Lower Quant 0.318 Upper Quant 

Detection/Quantification Limit 350.3: Ammonia Nitrogen Using an ISE

QA/QC Lower Range SFAN_SOP 7: Field Methods for Sampling Nutrients QA/QC Upper Range 

Characteristic SFAN_I&M: SFAN Long-Term Water Quality Monitoring Program

Defined Procedures, Configuration, && SFAN_WQ: SFAN pilot monitoring for Freshwater Quality Protocol

Analytical: Nutrient: Nutrient Analysis (N)

STORET Name: Nitrogen, ammonia as N Local Ammonia as N

Comp? 

Sequence 131 Sample Total Value Unit of mg/l Field/Lab: Lab

MediumWater Statistic Type: Duration:

Weight Basis: Part. Size Basis: Temp. Basis:

Detection Limit: 0.1 Lower Quant 0.318 Upper Quant 

Detection/Quantification Limit 

QA/QC Lower Range QA/QC Upper Range 

Characteristic 

Defined Procedures, Configuration, &&

Analytical: 350.3: Ammonia Nitrogen Using an ISE

Collection: SFAN_SOP 7: Field Methods for Sampling Nutrients

Projects: SFAN_I&M: SFAN Long-Term Water Quality Monitoring Program

SFAN_WQ: SFAN pilot monitoring for Freshwater Quality Protocol

Groups: Nutrient: Nutrient Analysis (N)

STORET Name: Ammonia, unionized Local UIA Comp?



Sequence 132 Sample Value Cal Unit of mg/l Field/Lab: Lab

MediumWater Statistic Type: Duration:

Weight Basis: Part. Size Basis: Temp. Basis:

Detection Limit: Lower Quant Upper Quant 

Detection/Quantification Limit 
138

QA/QC Lower Range QA/QC Upper Range 

Characteristic Calculated from Total Ammonia (TAN) x a conversion factor (given by pH and Temp).

Defined Procedures, Configuration, &&

Collection: SFAN_SOP 7: Field Methods for Sampling Nutrients

Projects: SFAN_I&M: SFAN Long-Term Water Quality Monitoring Program

SFAN_WQ: SFAN pilot monitoring for Freshwater Quality Protocol

Groups: Nutrient: Nutrient Analysis (N)

STORET Name: Nitrogen, Nitrate (NO3) as NO3 Local Nitrate as NO3

Comp? 

Sequence 133 Sample Total Value Unit of mg/l Field/Lab: Lab

MediumWater Statistic Type: Duration:

Weight Basis: Part. Size Basis: Temp. Basis:

Thursday, September 28, 2006 Page 23 of 35
139

NPSTORET Characteristics 

San Francisco Bay Area Network Sorted by Sequence Number

Detection Limit: 0.01 Lower Quant 0.0318 Upper Quant 

Detection/Quantification Limit 300(B): Inorganic Anions by Ion Chromatography

QA/QC Lower Range SFAN_SOP 7: Field Methods for Sampling Nutrients QA/QC Upper Range 

Characteristic SFAN_I&M: SFAN Long-Term Water Quality Monitoring Program

Defined Procedures, Configuration, && SFAN_WQ: SFAN pilot monitoring for Freshwater Quality Protocol

Analytical: Nutrient: Nutrient Analysis (N)

STORET Name: Nitrogen, Nitrate (NO3) as N Local Nitrate as N

Comp? 

Sequence 134 Sample Total Value Unit of mg/l Field/Lab: Lab

MediumWater Statistic Type: Duration:

Weight Basis: Part. Size Basis: Temp. Basis:

Detection Limit: 0.01 Lower Quant 0.0318 Upper Quant 

Detection/Quantification Limit 

QA/QC Lower Range QA/QC Upper Range 

Characteristic 

Defined Procedures, Configuration, &&

Analytical: 300(B): Inorganic Anions by Ion Chromatography

Collection: SFAN_SOP 7: Field Methods for Sampling Nutrients

Projects: SFAN_I&M: SFAN Long-Term Water Quality Monitoring Program

SFAN_WQ: SFAN pilot monitoring for Freshwater Quality Protocol

Groups: Nutrient: Nutrient Analysis (N)

STORET Name: Nitrogen, Nitrite (NO2) as NO2 Local Nitrite as NO2

Comp? 

Sequence 135 Sample Value Unit of mg/l Field/Lab: Lab

MediumWater Statistic Type: Duration:

Weight Basis: Part. Size Basis: Temp. Basis:

Detection Limit: 0.01 Lower Quant 0.0318 Upper Quant 
140

Detection/Quantification Limit 

QA/QC Lower Range QA/QC Upper Range 

Characteristic 

Defined Procedures, Configuration, &&

Analytical: 4500-NO2(B): Nitrite in Water by Colorimetry

Collection: SFAN_SOP 7: Field Methods for Sampling Nutrients

Projects: SFAN_I&M: SFAN Long-Term Water Quality Monitoring Program

SFAN_WQ: SFAN pilot monitoring for Freshwater Quality Protocol

Groups: Nutrient: Nutrient Analysis (N)

STORET Name: Nitrogen, Nitrite (NO2) as N Local Nitrite as N

Comp? 

Sequence 136 Sample Total Value Unit of mg/l Field/Lab: Lab

MediumWater Statistic Type: Duration:

Weight Basis: Part. Size Basis: Temp. Basis:

Thursday, September 28, 2006 Page 24 of 35
141

NPSTORET Characteristics 

San Francisco Bay Area Network Sorted by Sequence Number

Detection Limit: 0.01 Lower Quant 0.0318 Upper Quant 

Detection/Quantification Limit 4500-NO2(B): Nitrite in Water by Colorimetry

QA/QC Lower Range SFAN_SOP 7: Field Methods for Sampling Nutrients QA/QC Upper Range 

Characteristic SFAN_I&M: SFAN Long-Term Water Quality Monitoring Program

Defined Procedures, Configuration, && SFAN_WQ: SFAN pilot monitoring for Freshwater Quality Protocol

Analytical: Nutrient: Nutrient Analysis (N)

STORET Name: Nitrogen, Kjeldahl Local TKN Comp?



Sequence 137 Sample Value Unit of mg/l Field/Lab: Lab

MediumWater Statistic Type: Duration:

Weight Basis: Part. Size Basis: Temp. Basis:

Detection Limit: 0.5 Lower Quant 1.59 Upper Quant 

Detection/Quantification Limit 

QA/QC Lower Range QA/QC Upper Range 

Characteristic 

Defined Procedures, Configuration, &&

Analytical: 4500-NOR(B): Total Kjeldahl Nitrogen in Water

Collection: SFAN_SOP 7: Field Methods for Sampling Nutrients

Projects: SFAN_I&M: SFAN Long-Term Water Quality Monitoring Program

SFAN_WQ: SFAN pilot monitoring for Freshwater Quality Protocol

Groups: Nutrient: Nutrient Analysis (N)

STORET Name: Phosphorus, orthophosphate as P Local Orthophosphate as P

Comp? 

Sequence 138 Sample Value Unit of mg/l Field/Lab: Lab

MediumWater Statistic Type: Duration:

Weight Basis: Part. Size Basis: Temp. Basis:

Detection Limit: Lower Quant Upper Quant 

Detection/Quantification Limit 
142

QA/QC Lower Range QA/QC Upper Range 

Characteristic 

Defined Procedures, Configuration, &&

Collection: SFAN_SOP 7: Field Methods for Sampling Nutrients

Projects: SFAN_WQ: SFAN pilot monitoring for Freshwater Quality Protocol

Groups: Nutrient: Nutrient Analysis (N)

STORET Name: Phosphorus, phosphate (PO4) as PO4 Local Phosphate as 

PO4 Comp? 

Sequence 139 Sample Value Unit of mg/l Field/Lab: Lab

MediumWater Statistic Type: Duration:

Weight Basis: Part. Size Basis: Temp. Basis:

Thursday, September 28, 2006 Page 25 of 35
143

NPSTORET Characteristics 

San Francisco Bay Area Network Sorted by Sequence Number

Detection Limit: Lower Quant Upper Quant 

Detection/Quantification Limit 

QA/QC Lower Range SFAN_SOP 7: Field Methods for Sampling Nutrients QA/QC Upper Range 

Characteristic SFAN_WQ: SFAN pilot monitoring for Freshwater Quality Protocol

Defined Procedures, Configuration, && Nutrient: Nutrient Analysis (N)

STORET Name: Phosphorus Local Total PhosphorusComp?



Sequence 140 Sample Value Unit of mg/l Field/Lab: Lab

MediumWater Statistic Type: Duration:

Weight Basis: Part. Size Basis: Temp. Basis:

Detection Limit: Lower Quant Upper Quant 

Detection/Quantification Limit 

QA/QC Lower Range QA/QC Upper Range 

Characteristic 

Defined Procedures, Configuration, &&

Analytical: 365.2: Phosphorus by Single Reagent Colorimetry

Collection: SFAN_SOP 7: Field Methods for Sampling Nutrients

Projects: SFAN_WQ: SFAN pilot monitoring for Freshwater Quality Protocol

Groups: Nutrient: Nutrient Analysis (N)

STORET Name: pH Local Lab pHComp? 

Sequence 141 Sample Value Unit of None Field/Lab: Lab

MediumWater Statistic Type: Duration:

Weight Basis: Part. Size Basis: Temp. Basis:

Detection Limit: Lower Quant Upper Quant 

Detection/Quantification Limit 

QA/QC Lower Range QA/QC Upper Range 

Characteristic 

Defined Procedures, Configuration, &&
144

Analytical: 150.1: pH

Collection: SFAN_SOP 7: Field Methods for Sampling Nutrients

Projects: SFAN_WQ: SFAN pilot monitoring for Freshwater Quality Protocol

Groups:

STORET Name: MBAS (detergents, surfactants) Local MBAS Comp?



Sequence 142 Sample Total Value Unit of mg/l Field/Lab: Lab

MediumWater Statistic Type: Duration:

Weight Basis: Part. Size Basis: Temp. Basis:

Thursday, September 28, 2006 Page 26 of 35
145

NPSTORET Characteristics 

San Francisco Bay Area Network Sorted by Sequence Number

Detection Limit: Lower Quant Upper Quant 

Detection/Quantification Limit 425.1: Methylene Blue Active Substances

QA/QC Lower Range SFAN_SOP 7: Field Methods for Sampling Nutrients QA/QC Upper Range 

Characteristic SFAN_WQ: SFAN pilot monitoring for Freshwater Quality Protocol

Defined Procedures, Configuration, &&

STORET Name: Gage heightLocal Datalogger Gage Ht

Comp? 

Sequence 143 Sample Value Unit of ft Field/Lab: Field

MediumWater Statistic Type: Duration:

Weight Basis: Part. Size Basis: Temp. Basis:

Detection Limit: Lower Quant Upper Quant 

Detection/Quantification Limit 

QA/QC Lower Range QA/QC Upper Range 

Characteristic Recorded gage height from in-stream permanent pressure transducer.

Defined Procedures, Configuration, &&

Projects: SFAN_WQ: SFAN pilot monitoring for Freshwater Quality Protocol

Groups:

STORET Name: Flow Local Datalogger Discharge

Comp? 

Sequence 144 Sample Value Unit of cfs Field/Lab: Field

MediumWater Statistic Type: Duration:

Weight Basis: Part. Size Basis: Temp. Basis:

Detection Limit: Lower Quant Upper Quant 

Detection/Quantification Limit 

QA/QC Lower Range QA/QC Upper Range 

Characteristic Calculated discharge from datalogger gage height and stream's rating curve.
146

Defined Procedures, Configuration, &&

Analytical: FLOW FROM GAGE: Discharge from automatic gage and rating curve

Projects: SFAN_WQ: SFAN pilot monitoring for Freshwater Quality Protocol

Groups:

STORET Name: Copper Local Total Copper Comp?



Sequence 145 Sample Total Value Unit of ug/l Field/Lab: Lab

MediumWater Statistic Type: Duration:

Weight Basis: Part. Size Basis: Temp. Basis:

Thursday, September 28, 2006 Page 27 of 35
147

NPSTORET Characteristics 

San Francisco Bay Area Network Sorted by Sequence Number

Detection Limit: Lower Quant Upper Quant 

Detection/Quantification Limit 200.8(W): Metals in Waters by ICP/MS

QA/QC Lower Range SFAN_SOP 7: Field Methods for Sampling Nutrients QA/QC Upper Range 

Characteristic SFAN_WQ: SFAN pilot monitoring for Freshwater Quality Protocol

Defined Procedures, Configuration, && Metals: Metals

STORET Name: Chlorophyll a, uncorrected for pheophytinLocal Chlorophyll a

Comp? 

Sequence 146 Sample Value Unit of ug/l Field/Lab: Lab

MediumWater Statistic Type: Duration:

Weight Basis: Part. Size Basis: Temp. Basis:

Detection Limit: Lower Quant Upper Quant 

Detection/Quantification Limit 

QA/QC Lower Range QA/QC Upper Range 

Characteristic 

Defined Procedures, Configuration, &&

Analytical: 10200-H: Chlorophyll a-b-c Determination

Collection: SFAN_SOP 7: Field Methods for Sampling Nutrients

Projects: SFAN_WQ: SFAN pilot monitoring for Freshwater Quality Protocol

Groups: Nutrient: Nutrient Analysis (N)

STORET Name: Alkalinity, Carbonate as CaCO3 Local Carbonate alkalinity

Comp? 

Sequence 147 Sample Value Unit of ug/l Field/Lab: Lab

MediumWater Statistic Type: Duration:

Weight Basis: Part. Size Basis: Temp. Basis:

Detection Limit: Lower Quant Upper Quant 

Detection/Quantification Limit 

QA/QC Lower Range QA/QC Upper Range 
148

Characteristic 

Defined Procedures, Configuration, &&

Analytical: 310.1: Alkalinity by Titration

Collection: SFAN_SOP 7: Field Methods for Sampling Nutrients

Projects: SFAN_WQ: SFAN pilot monitoring for Freshwater Quality Protocol

Groups:

STORET Name: Alkalinity, Bicarbonate as CaCO3 Local Bicarbonate

Comp? 

Sequence 148 Sample Value Unit of mg/l Field/Lab: Lab

MediumWater Statistic Type: Duration:

Weight Basis: Part. Size Basis: Temp. Basis:

Thursday, September 28, 2006 Page 28 of 35
149

NPSTORET Characteristics 

San Francisco Bay Area Network Sorted by Sequence Number

Detection Limit: Lower Quant Upper Quant 

Detection/Quantification Limit 310.1: Alkalinity by Titration

QA/QC Lower Range SFAN_SOP 7: Field Methods for Sampling Nutrients QA/QC Upper Range 

Characteristic SFAN_WQ: SFAN pilot monitoring for Freshwater Quality Protocol

Defined Procedures, Configuration, &&

STORET Name: Alkalinity, Total (total hydroxide+carbonate+bicarbonate) Local 

Total Alkalinity Comp? 

Sequence 149 Sample Value Unit of mg/l Field/Lab: Lab

MediumWater Statistic Type: Duration:

Weight Basis: Part. Size Basis: Temp. Basis:

Detection Limit: Lower Quant Upper Quant 

Detection/Quantification Limit 

QA/QC Lower Range QA/QC Upper Range 

Characteristic 

Defined Procedures, Configuration, &&

Analytical: 310.1: Alkalinity by Titration

Collection: SFAN_SOP 7: Field Methods for Sampling Nutrients

Projects: SFAN_WQ: SFAN pilot monitoring for Freshwater Quality Protocol

Groups:

STORET Name: Hardness, carbonate Local Hardness Comp?



Sequence 150 Sample Value Unit of mg/l Field/Lab: Lab

MediumWater Statistic Type: Duration:

Weight Basis: Part. Size Basis: Temp. Basis:

Detection Limit: Lower Quant Upper Quant 

Detection/Quantification Limit 

QA/QC Lower Range QA/QC Upper Range 
150

Characteristic 

Defined Procedures, Configuration, &&

Analytical: 2340: Hardness in Water by EDTA Titration

Collection: SFAN_SOP 7: Field Methods for Sampling Nutrients

Projects: SFAN_WQ: SFAN pilot monitoring for Freshwater Quality Protocol

Groups:

STORET Name: Solids, Dissolved Local TDS Comp?



Sequence 151 Sample Value Unit of mg/l Field/Lab: Lab

MediumWater Statistic Type: Duration:

Weight Basis: Part. Size Basis: Temp. Basis:

Thursday, September 28, 2006 Page 29 of 35
151

NPSTORET Characteristics 

San Francisco Bay Area Network Sorted by Sequence Number

Detection Limit: Lower Quant Upper Quant 

Detection/Quantification Limit 160.1: Filterable Residue - TDS

QA/QC Lower Range SFAN_SOP 7: Field Methods for Sampling Nutrients QA/QC Upper Range 

Characteristic SFAN_WQ: SFAN pilot monitoring for Freshwater Quality Protocol

Defined Procedures, Configuration, &&

STORET Name: Chloride Local Chloride Comp? 

Sequence 152 Sample Total Value Unit of mg/l Field/Lab: Lab

MediumWater Statistic Type: Duration:

Weight Basis: Part. Size Basis: Temp. Basis:

Detection Limit: Lower Quant Upper Quant 

Detection/Quantification Limit 

QA/QC Lower Range QA/QC Upper Range 

Characteristic 

Defined Procedures, Configuration, &&

Collection: SFAN_SOP 7: Field Methods for Sampling Nutrients

Projects: SFAN_WQ: SFAN pilot monitoring for Freshwater Quality Protocol

Groups:

STORET Name: Sulfur, sulfate (SO4) as SO4 Local Sulfate as SO4

Comp? 

Sequence 153 Sample Total Value Unit of mg/l Field/Lab: Lab

MediumWater Statistic Type: Duration:

Weight Basis: Part. Size Basis: Temp. Basis:

Detection Limit: Lower Quant Upper Quant 

Detection/Quantification Limit 

QA/QC Lower Range QA/QC Upper Range 

Characteristic 
152

Defined Procedures, Configuration, &&

Analytical: 300(B): Inorganic Anions by Ion Chromatography

Collection: SFAN_SOP 7: Field Methods for Sampling Nutrients

Projects: SFAN_WQ: SFAN pilot monitoring for Freshwater Quality Protocol

Groups: Nutrient: Nutrient Analysis (N)

STORET Name: Fluorides Local Fluoride as F Comp?



Sequence 154 Sample Total Value Unit of mg/l Field/Lab: Lab

MediumWater Statistic Type: Duration:

Weight Basis: Part. Size Basis: Temp. Basis:

Thursday, September 28, 2006 Page 30 of 35
153

NPSTORET Characteristics 

San Francisco Bay Area Network Sorted by Sequence Number

Detection Limit: Lower Quant Upper Quant 

Detection/Quantification Limit 300(B): Inorganic Anions by Ion Chromatography

QA/QC Lower Range SFAN_SOP 7: Field Methods for Sampling Nutrients QA/QC Upper Range 

Characteristic SFAN_WQ: SFAN pilot monitoring for Freshwater Quality Protocol

Defined Procedures, Configuration, && Nutrient: Nutrient Analysis (N)

STORET Name: Calcium Local Calcium Comp? 

Sequence 155 Sample Total Value Unit of mg/l Field/Lab: Lab

MediumWater Statistic Type: Duration:

Weight Basis: Part. Size Basis: Temp. Basis:

Detection Limit: Lower Quant Upper Quant 

Detection/Quantification Limit 

QA/QC Lower Range QA/QC Upper Range 

Characteristic 

Defined Procedures, Configuration, &&

Analytical: 200.7_M: ICP-AES For Trace Element Analysis

Collection: SFAN_SOP 7: Field Methods for Sampling Nutrients

Projects: SFAN_WQ: SFAN pilot monitoring for Freshwater Quality Protocol

Groups: Nutrient: Nutrient Analysis (N)

STORET Name: Magnesium Local Magnesium Comp?



Sequence 156 Sample Total Value Unit of mg/l Field/Lab: Lab

MediumWater Statistic Type: Duration:

Weight Basis: Part. Size Basis: Temp. Basis:

Detection Limit: Lower Quant Upper Quant 

Detection/Quantification Limit 

QA/QC Lower Range QA/QC Upper Range 

Characteristic 

Defined Procedures, Configuration, &&
154

Analytical: 200.7_M: ICP-AES For Trace Element Analysis

Collection: SFAN_SOP 7: Field Methods for Sampling Nutrients

Projects: SFAN_WQ: SFAN pilot monitoring for Freshwater Quality Protocol

Groups: Nutrient: Nutrient Analysis (N)

STORET Name: Potassium Local PotassiumComp? 

Sequence 157 Sample Value Unit of mg/l Field/Lab: Lab

MediumWater Statistic Type: Duration:

Weight Basis: Part. Size Basis: Temp. Basis:

Thursday, September 28, 2006 Page 31 of 35
155

NPSTORET Characteristics 

San Francisco Bay Area Network Sorted by Sequence Number

Detection Limit: Lower Quant Upper Quant 

Detection/Quantification Limit 200.7_M: ICP-AES For Trace Element Analysis

QA/QC Lower Range SFAN_SOP 7: Field Methods for Sampling Nutrients QA/QC Upper Range 

Characteristic SFAN_WQ: SFAN pilot monitoring for Freshwater Quality Protocol

Defined Procedures, Configuration, && Nutrient: Nutrient Analysis (N)

STORET Name: Sodium Local SodiumComp? 

Sequence 158 Sample Total Value Unit of mg/l Field/Lab: Lab

MediumWater Statistic Type: Duration:

Weight Basis: Part. Size Basis: Temp. Basis:

Detection Limit: Lower Quant Upper Quant 

Detection/Quantification Limit 

QA/QC Lower Range QA/QC Upper Range 

Characteristic 

Defined Procedures, Configuration, &&

Analytical: 200.7_M: ICP-AES For Trace Element Analysis

Collection: SFAN_SOP 7: Field Methods for Sampling Nutrients

Projects: SFAN_WQ: SFAN pilot monitoring for Freshwater Quality Protocol

Groups:

STORET Name: Iron Local Iron Comp? 

Sequence 159 Sample Total Value Unit of mg/l Field/Lab: Lab

MediumWater Statistic Type: Duration:

Weight Basis: Part. Size Basis: Temp. Basis:

Detection Limit: Lower Quant Upper Quant 

Detection/Quantification Limit 

QA/QC Lower Range QA/QC Upper Range 

Characteristic 

Defined Procedures, Configuration, &&
156

Analytical: 200.7_M: ICP-AES For Trace Element Analysis

Collection: SFAN_SOP 7: Field Methods for Sampling Nutrients

Projects: SFAN_WQ: SFAN pilot monitoring for Freshwater Quality Protocol

Groups: Metals: Metals

STORET Name: Manganese Local Manganese Comp?



Sequence 160 Sample Total Value Unit of mg/l Field/Lab: Lab

MediumWater Statistic Type: Duration:

Weight Basis: Part. Size Basis: Temp. Basis:

Thursday, September 28, 2006 Page 32 of 35
157

NPSTORET Characteristics 

San Francisco Bay Area Network Sorted by Sequence Number

Detection Limit: Lower Quant Upper Quant 

Detection/Quantification Limit 200.7_M: ICP-AES For Trace Element Analysis

QA/QC Lower Range SFAN_SOP 7: Field Methods for Sampling Nutrients QA/QC Upper Range 

Characteristic SFAN_WQ: SFAN pilot monitoring for Freshwater Quality Protocol

Defined Procedures, Configuration, &&

STORET Name: Gold Local GoldComp? 

Sequence 161 Sample Total Value Unit of ug/l Field/Lab: Lab

MediumWater Statistic Type: Duration:

Weight Basis: Part. Size Basis: Temp. Basis:

Detection Limit: Lower Quant Upper Quant 

Detection/Quantification Limit 

QA/QC Lower Range QA/QC Upper Range 

Characteristic 

Defined Procedures, Configuration, &&

Analytical: 200.7(W): Metals in Water by ICP-AES

Collection: SFAN_SOP 7: Field Methods for Sampling Nutrients

Projects: SFAN_WQ: SFAN pilot monitoring for Freshwater Quality Protocol

Groups: Metals: Metals

STORET Name: Lead Local LeadComp? 

Sequence 162 Sample Total Value Unit of ug/l Field/Lab: Lab

MediumWater Statistic Type: Duration:

Weight Basis: Part. Size Basis: Temp. Basis:

Detection Limit: Lower Quant Upper Quant 

Detection/Quantification Limit 

QA/QC Lower Range QA/QC Upper Range 

Characteristic 

Defined Procedures, Configuration, &&
158

Analytical: 200.8(W): Metals in Waters by ICP/MS

Collection: SFAN_SOP 7: Field Methods for Sampling Nutrients

Projects: SFAN_WQ: SFAN pilot monitoring for Freshwater Quality Protocol

Groups: Metals: Metals

STORET Name: Zinc Local ZincComp? 

Sequence 163 Sample Value Unit of ug/l Field/Lab: Lab

MediumWater Statistic Type: Duration:

Weight Basis: Part. Size Basis: Temp. Basis:

Thursday, September 28, 2006 Page 33 of 35
159

NPSTORET Characteristics 

San Francisco Bay Area Network Sorted by Sequence Number

Detection Limit: Lower Quant Upper Quant 

Detection/Quantification Limit 200.7(W): Metals in Water by ICP-AES

QA/QC Lower Range SFAN_SOP 7: Field Methods for Sampling Nutrients QA/QC Upper Range 

Characteristic SFAN_WQ: SFAN pilot monitoring for Freshwater Quality Protocol

Defined Procedures, Configuration, && Metals: Metals

STORET Name: Antimony Local AntimonyComp? 

Sequence 164 Sample Total Value Unit of ug/l Field/Lab: Lab

MediumWater Statistic Type: Duration:

Weight Basis: Part. Size Basis: Temp. Basis:

Detection Limit: Lower Quant Upper Quant 

Detection/Quantification Limit 

QA/QC Lower Range QA/QC Upper Range 

Characteristic 

Defined Procedures, Configuration, &&

Analytical: 200.8(W): Metals in Waters by ICP/MS

Collection: SFAN_SOP 7: Field Methods for Sampling Nutrients

Projects: SFAN_WQ: SFAN pilot monitoring for Freshwater Quality Protocol

Groups: Metals: Metals

STORET Name: Nickel Local NickelComp? 

Sequence 165 Sample Total Value Unit of ug/l Field/Lab: Lab

MediumWater Statistic Type: Duration:

Weight Basis: Part. Size Basis: Temp. Basis:

Detection Limit: Lower Quant Upper Quant 

Detection/Quantification Limit 

QA/QC Lower Range QA/QC Upper Range 

Characteristic 

Defined Procedures, Configuration, &&
160

Analytical: 200.7(W): Metals in Water by ICP-AES

Collection: SFAN_SOP 7: Field Methods for Sampling Nutrients

Projects: SFAN_WQ: SFAN pilot monitoring for Freshwater Quality Protocol

Groups: Metals: Metals

STORET Name: Barium Local BariumComp? 

Sequence 166 Sample Total Value Unit of ug/l Field/Lab: Lab

MediumWater Statistic Type: Duration:

Weight Basis: Part. Size Basis: Temp. Basis:

Thursday, September 28, 2006 Page 34 of 35
161

NPSTORET Characteristics 

San Francisco Bay Area Network Sorted by Sequence Number

Detection Limit: Lower Quant Upper Quant 

Detection/Quantification Limit 200.8(W): Metals in Waters by ICP/MS

QA/QC Lower Range SFAN_SOP 7: Field Methods for Sampling Nutrients QA/QC Upper Range 

Characteristic SFAN_WQ: SFAN pilot monitoring for Freshwater Quality Protocol

Defined Procedures, Configuration, && Metals: Metals

Number of Complete Characteristics: 98

Number of Incomplete Characteristics: 0

Thursday, September 28, 2006 Page 35 of 35
Appendix H Standard Operating Procedures

162

Appendix H Standard Operating Procedures

Contents

Page

SOP #1 Protocol Revision and Review ...................................................................................... 176

1.1 Revision History Log...................................................................................................... 176

1.2 Scope and Application .................................................................................................... 176

1.3 Protocol Revision Procedures......................................................................................... 177

1.4 Protocol Review.............................................................................................................. 178

1.4.1 Reviewer Comments.............................................................................................. 178

1.5 References....................................................................................................................... 178

SOP #2 Personnel Training and Safety....................................................................................... 180

2.1 Revision History Log...................................................................................................... 180

2.2 Acknowledgements......................................................................................................... 180

2.3 Scope and Application .................................................................................................... 180

2.4 Training........................................................................................................................... 180

2.4.1 Introduction............................................................................................................ 180

2.4.2 Procedures.............................................................................................................. 181

2.5 Safety .............................................................................................................................. 182

2.5.1 Introduction............................................................................................................ 182

2.5.2 Procedures for Safety Preparation ......................................................................... 184

2.5.3 Forms ..................................................................................................................... 185

2.5.4 Checklists for Standard Safety Equipment ............................................................ 188

2.6 References....................................................................................................................... 189

SOP #2 Appendix A. Job Hazard Analysis for Aquatic Surveys and Projects..................... 190

SOP #2 Appendix B. Working in Poison Oak – Safety Briefing ......................................... 199
Appendix H Standard Operating Procedures

163

SOP #3 Equipment and Field Preparations................................................................................. 200

3.1 Revision History Log...................................................................................................... 200

3.2 Acknowledgements......................................................................................................... 200

3.3 Scope and Application .................................................................................................... 200

3.3.1 Introduction............................................................................................................ 200

3.4 Equipment Calibration, Inspection, and Maintenance.................................................... 201

3.4.1 Multiparameter instrument (dissolved oxygen and conductivity) ......................... 202

3.4.2 Thermometer/Thermistor....................................................................................... 203

3.4.3 pH Meter................................................................................................................ 206

3.4.4 Post-Calibration Checks......................................................................................... 208

3.4.5 Continuous Water-Quality Monitoring Equipment ............................................... 209

3.4.6 Equipment and Supplies: Maintenance and Storage.............................................. 209

3.5 Field Preparations ........................................................................................................... 210

3.6 QA/QC Procedures for Equipment ................................................................................. 212

3.7 References....................................................................................................................... 213

SOP #3 Appendix A. YSI Multiparameter Probe Manual.................................................... 214

SOP #3 Appendix B. Oakton pH Meter Manual .................................................................. 216

SOP #3 Appendix C. Eureka Environmental Engineering – Manta multiprobe User’s Manual

............................................................................................................................................... 218

SOP #3 Appendix D. Equipment Log Sheets....................................................................... 226

SOP #3 Appendix E. Technical Support Information .......................................................... 227

SOP #4 Quality Assurance Project Plan (QAPP) ....................................................................... 228

4.1 Revision History Log...................................................................................................... 228

4.2 Acknowledgements......................................................................................................... 228

4.3 List of Acronyms for SOP #4 ......................................................................................... 229

4.4 Project Management ....................................................................................................... 230
Appendix H Standard Operating Procedures

164

4.4.1 Distribution List..................................................................................................... 230

4.4.2 Project/Task Organization ..................................................................................... 230

4.4.3 Problem Definition/Background............................................................................ 231

4.4.4 Project/Task Description........................................................................................ 232

4.4.5 Data Quality Objectives (DQOs) and Criteria for Measurement Data .................. 234

4.4.6 Special Training/Certification................................................................................ 239

4.4.7 Documentation and Records.................................................................................. 240

4.5 Data Generation and Acquisition.................................................................................... 241

4.5.1 Sampling Process Design (Experimental Design)................................................. 241

4.5.2 Sampling Methods................................................................................................. 242

4.5.3 Sample Handling and Custody Requirements ....................................................... 242

4.5.4 Analytical Methods Requirements......................................................................... 244

4.5.5 Quality Control Requirements............................................................................... 247

4.5.6 Instrument/Equipment Testing, Inspection, and Maintenance Requirements....... 250

4.5.7 Instrument Calibration and Frequency................................................................... 250

4.5.8 Inspection/Acceptance Requirements For Supplies And Consumables................ 251

4.5.9. Data Acquisition Requirements (Non-direct Measurements)............................... 251

4.5.10 Data Management ................................................................................................ 252

4.6 Assessment and Oversight .............................................................................................. 252

4.6.1 Assessments and Response Actions....................................................................... 252

4.6.2 Reports to Management ......................................................................................... 252

4.7 Data Validation and Usability......................................................................................... 253

4.7.1 Data Review, Verification, and Validation Requirements..................................... 253

4.7.2 Validation and Verification Methods..................................................................... 253

4.7.3 Reconciliation with Data Quality Objectives ........................................................ 254
Appendix H Standard Operating Procedures

165

4.8 References....................................................................................................................... 254

SOP #4 Appendix A. Field Data Sheet – Stream Site .......................................................... 256

SOP #5 Field Methods for Measurements of Core Parameters.................................................. 261

5.1 Revision History Log...................................................................................................... 261

5.2 Acknowledgements......................................................................................................... 261

5.3 Scope and Application .................................................................................................... 262

5.3.1 Core/Required Parameters..................................................................................... 262

5.4 Measurement Procedures................................................................................................ 263

5.4.1 Monthly/Weekly Monitoring................................................................................. 263

5.4.2 Continuous Monitoring.......................................................................................... 270

5.5 Data Management ........................................................................................................... 272

5.6 Quality Assurance/Quality Control................................................................................. 272

5.7 References....................................................................................................................... 274

SOP #5 Appendix A. Field Data Sheet for Core Parameters................................................ 276

SOP #5 Appendix B. Winkler Titration Method for Dissolved Oxygen Measurement ....... 278

SOP #6 Field and Laboratory Methods for Monitoring Fecal Indicator Bacteria ...................... 281

6.1 Revision History Log...................................................................................................... 281

6.2 Acknowledgements......................................................................................................... 281

6.3 List of Acronyms Used ................................................................................................... 282

6.4 Scope and Application .................................................................................................... 283

6.4.1 Fecal Indicator Bacteria and Their Relation to Water Quality .............................. 283

6.4.2 Water Quality Standards for Fecal Indicator Bacteria........................................... 283

6.4.3 Fecal Indicator Bacteria Levels in SFAN Waters.................................................. 284

6.4.4 Tomales Bay Pathogen Total Maximum Daily Load (TMDL) Project................. 285

6.4.5 FIB Sampling and Analysis Methods Overview ................................................... 285
Appendix H Standard Operating Procedures

166

6.5 Techniques...................................................................................................................... 287

6.5.1 Tips for collection of bacteria samples:................................................................. 287

6.5.2 Aseptic Technique (from O’Ney, 2004)................................................................ 287

6.5.3 Sample Bottles....................................................................................................... 287

6.5.4 Collecting the Samples .......................................................................................... 288

Prepare for sampling....................................................................................................... 288

Collect the sample........................................................................................................... 289

6.5.5 Preparing the Samples and Laboratory Analysis................................................... 289

6.6 Field Preparations and Laboratory Coordination............................................................ 290

6.6.1 Equipment Checklist.............................................................................................. 291

6.7 Quality Assurance/Quality Control (Check with QAPP) ............................................... 291

6.8 References....................................................................................................................... 291

SOP #6 Appendix A.............................................................................................................. 293

SOP #7 Field Methods for Sampling Nutrients.......................................................................... 294

7.1 Revision History Log...................................................................................................... 294

7.2 Acknowledgements......................................................................................................... 294

7.3 Scope and Application .................................................................................................... 295

7.3.1 Nutrients and Their Relation to Water Quality...................................................... 295

7.3.2 Nutrient Levels in SFAN Waters........................................................................... 296

7.3.3 Nutrient Sampling and Analysis Methods Overview ............................................ 296

7.4 Techniques...................................................................................................................... 297

7.4.1 Tips for collection of nutrient samples: ................................................................. 297

7.4.2 Aseptic Technique (from O’Ney, 2004)................................................................ 297

7.4.3 Sample Bottles....................................................................................................... 298

7.4.4 Collecting the Samples .......................................................................................... 298
Appendix H Standard Operating Procedures

167

7.5 Field Preparation and Laboratory Coordination ............................................................. 299

7.6 Quality Assurance/Quality Control................................................................................. 300

7.7 Data Reporting................................................................................................................ 301

7.7.1 Calculating Unionized Ammonia .......................................................................... 301

7.8 References....................................................................................................................... 302

7.8 References....................................................................................................................... 303

SOP #8 Field and Laboratory Methods for Sediment................................................................. 304

8.1 Revision History Log...................................................................................................... 304

8.2 List of Acronyms Used for SOP #8 ................................................................................ 304

8.3 Scope and Application .................................................................................................... 305

8.3.1 Introduction............................................................................................................ 305

8.3.2 Sediment Impaired Waters within SFAN .............................................................. 305

8.3.3 Water Quality Criteria Recommendations for Sediment....................................... 307

8.3.4 Sediment Levels in SFAN Waters......................................................................... 308

8.3.5 Sediment Monitoring Rationale & Objectives....................................................... 308

8.4 Field Techniques............................................................................................................. 310

8.4.1 Introduction............................................................................................................ 310

8.4.2 Preparations and Field Rinsing of Equipment ....................................................... 310

8.4.3 Isokinetic, Depth-Integrated Sampling .................................................................. 311

8.4.4 Non-isokinetic Sampling ....................................................................................... 314

8.4.5 Turbidity Threshold Sampling............................................................................... 314

8.5 Sample Preservation, Storage, and Analysis................................................................... 321

8.5.1 Suspended Sediment Concentration (SSC) and Total Suspended Solids (TSS).... 321

8.5.2 Turbidity ................................................................................................................ 321

8.6 Quality Assurance/Quality Control................................................................................. 324
Appendix H Standard Operating Procedures

168

8.7 References....................................................................................................................... 324

SOP #8 Appendix A Sampling with the US DH-48 Depth-Integrating Suspended-Sediment 

Sampler ................................................................................................................................. 327

SOP #8 Appendix B Depth Integrated Sampling Form Stream Flow Measurement Field Form

............................................................................................................................................... 328

SOP #8 Appendix C Turbidity Threshold Sampling Field Manual...................................... 332

SOP #8 Appendix D Laboratory Procedures For Determining Suspended Sediment 

Concentration........................................................................................................................ 333

SOP #8 Appendix E Turbidimeter Instrument Log .............................................................. 334

SOP #9 Field Measurements for Flow Measurements ............................................................... 335

9.1 Revision History Log...................................................................................................... 335

9.2 Acknowledgements......................................................................................................... 335

9.3 Introduction..................................................................................................................... 335

9.4 Calibration....................................................................................................................... 336

9.4.1 Calibration of Current Velocity Meters (Flow meters) (from O’Ney, 2005) ........ 336

9.4.2 General Performance Checks................................................................................. 336

9.5 Measurements Techniques.............................................................................................. 337

9.5.1 Quantitative Methods (from O’Ney, 2005; Adapted from Texas Commission on 

Environmental Quality, 2003) ........................................................................................ 337

9.5.2 Alternative Methods............................................................................................... 344

9.5.3 Qualitative Methods............................................................................................... 344

9.6 Data Analysis & Reporting............................................................................................. 345

9.7 References....................................................................................................................... 346

SOP #9 Appendix A Field Form for Recording Flow Measurements.................................. 348

SOP #10 Data Analysis............................................................................................................... 352

10.1 Revision History Log.................................................................................................... 352

10.2 Introduction and Acknowledgements........................................................................... 352
Appendix H Standard Operating Procedures

169

10.3 Preparing the Raw Data Set for Analysis ..................................................................... 353

10.3.1 Sample Sizes and Minimum Detectable Differences and Quantifying Data Quality

......................................................................................................................................... 353

10.3.2 Censored Data and Outliers................................................................................. 355

10.3.3 Replicates and Data Transformations.................................................................. 356

10.4 Data Analysis................................................................................................................ 357

10.4.1 Summary Statistics and Tabular Data Presentation............................................. 357

10.4.2 Graphical Data Presentation ................................................................................ 361

10.4.3 Long-term trend analysis ..................................................................................... 364

10.5 References..................................................................................................................... 368

SOP #11 Data Reporting............................................................................................................. 370

11.1 Revision History Log.................................................................................................... 370

11.2 Introduction................................................................................................................... 370

11.3 Report Format ............................................................................................................... 372

11.4 Review Procedure ......................................................................................................... 373

11.4.1 Internal Review.................................................................................................... 373

11.4.2 Park Review......................................................................................................... 373

11.4.3 External Review................................................................................................... 373

11.5 Distribution Procedure .................................................................................................. 374

11.5.1 Identifying Stakeholders...................................................................................... 374

11.5.2 Distributing the Report ........................................................................................ 374

11.6 References..................................................................................................................... 374

SOP #12 Site Selection and Documentation............................................................................... 376

12.1 Revision History Log.................................................................................................... 376

12.2 Acknowledgements....................................................................................................... 376

12.3 Field Preparation and Site Selection............................................................................. 376
Appendix H Standard Operating Procedures

170

12.3.1 Permission and Access......................................................................................... 376

12.3.2 Site Selection ....................................................................................................... 376

12.4 Site Documentation....................................................................................................... 378

12.4.2 Obtaining Station Coordinates............................................................................. 379

12.4.3 Photographic Documentation............................................................................... 379

12.4.4 Establishing NPS-STORET project files............................................................ 380

12.4.5 Entering Station Information in NPSTORET...................................................... 380

12.4.6 Entering Additional Information Into NPSTORET............................................. 381

12.4.7 Creating Field Folders.......................................................................................... 381

12.5 Equipment Installation.................................................................................................. 382

12.5.2 Installation of an Automatic Stage Recorder and Establishing a Rating Curve .. 383

12.6 References..................................................................................................................... 384
Appendix H Standard Operating Procedures

171

Figures

Page

Figure 8.1 From USGS National Field Manual (Webb and Radke, 1998)................................. 314

Figure 9.1. Top setting wading rod............................................................................................ 341

Figure 9.2. Flow calculations..................................................................................................... 343

Figure 10.1 Example data summary chart. ................................................................................. 362

Figure 10.2 Example box and whiskers plot, quantiles, and mean and standard deviation 

summaries by month. .............................................................................................. 363

Figure 10.3 Histograms displaying data from multiple years, such as these from Rugg 2000. . 364
Appendix H Standard Operating Procedures

172

Tables

Page

Table 1.1 Current SFAN Freshwater Quality Protocol Documents. .......................................... 177

Table 3.1 Calibration schedule (modified from O’Ney, 2005)................................................... 202

Table 3.2. Post-Calibration Check Error Limits for water-quality equipment. ......................... 208

Table 3.3 Storage time for calibration standards. ....................................................................... 210

Table 3.4 Field Equipment Checklist.......................................................................................... 211

Table 3.5 QA Protocols............................................................................................................... 212

Table 4.1 QAPP Distribution List............................................................................................... 230

Table 4.2 Project Tasks and Responsibilities. ............................................................................ 230

Table 4.3 Impaired water bodies in the SFAN. .......................................................................... 232

Table 4.4 Project Task Extended Timetable. .............................................................................. 233

Table 4.5 Overall Water Quality Monitoring Schedule.............................................................. 233

Table 4.6 Data utilization and Related Management Decisions. ............................................... 234

Table 4.7 Overview of SFAN Data Quality Assurance.............................................................. 237

Table 4.8 Target streams, parameters, and protocols to be monitored. ...................................... 241

Table 4.9 Summary of Sample Handling Requirements. ........................................................... 243

Table 4.10 Measurement Quality Objectives.............................................................................. 245

Table 4.11 QA protocols............................................................................................................. 249

Table 4.12 Routine Instrument Inspections and Calibrations..................................................... 250

Table 5.1 Measurement Stabilization Criteria (core parameters) (from USGS National Field 

Manual) and WRD recommended instrument stabilization criteria for recording field 

measurements. Note the units to be used and recommended calibration frequencies.

.................................................................................................................................... 266

Table 5.2 Recommended Depths for Conducting Field Data Measurements (from Puckett, 2002).

.................................................................................................................................... 267

Table 5.3 Data Quality Objectives for Field Measurements....................................................... 273
Appendix H Standard Operating Procedures

173

Table 6.1 Ranges of fecal indicator bacteria typically found in uncontaminated surface water and 

contaminated surface water (from Table 7.1-1 in the USGS National Field Manual).

.................................................................................................................................... 283

Table 6.2 General numeric objectives for select beneficial uses in surface waters in the San 

Francisco Bay Area. ................................................................................................... 284

Table 6.3 Range in Fecal Indicator Bacteria* in SFAN parks (MPN/100mL) based on land use.

.................................................................................................................................... 285

Table 7.1 Summary of methods for laboratory parameters (modified from Puckett, 2002). ..... 297

Table 7.2 Fraction of unionized ammonia in aqueous solution at different pH values and 

temperatures. Calculated from data in Emmerson et al. (1975)................................. 302

Table 8.1 San Francisco Bay Regional Water Quality Control Board TMDL Project Timeline as 

of 6-29-05................................................................................................................... 306

Table 8.2 Recommended criteria for sediment. .......................................................................... 307

Table 8.3 Total Suspended Solids in mg/L................................................................................. 308

Table 8.4 Turbidity in Nephelometric Turbidity Units (NTU)................................................... 308

Table 8.5 Sediment monitoring questions, location, sampling frequency and analysis. ........... 310

Table 8.6 Pre-field check list for D-48 hand-held samplers (adapted from the Federal Interagency 

Sedimentation Project (FISP, 1958) and Webb and Radtke, 1998, Selection of 

Equipment for Collection of Water Samples. ............................................................ 312

Table 8.7 TTS Weekly Field Visits (complete these tasks in the order listed)........................... 319

Table 8.8 Hach 2100P Turbidimeter Specifications. .................................................................. 323

Table 8.9 From USGS National Field Manual, Section 6.7 (Anderson, 2004). ......................... 323

Table 9.1 Flow Severity Values.................................................................................................. 345

Table 9.2 NPSTORET Flow Monitoring Codes and Definitions............................................... 346

Table 10.1 Sample Size Summary for SFAN Priority Streams. ................................................. 353

Table 10.2 Minimum Detectable Differences for SFAN Sampling Design. .............................. 354

Table 10.3 SFAN Data Quality Assurances. .............................................................................. 355

Table 10.4 Options for testing monotonic trends in uncensored water quality data................... 366
Appendix H Standard Operating Procedures

174

Table 10.5 Options for testing step trends in uncensored water quality data. ............................ 366

Table 10.6 Options for testing for monotonic trends in censored water quality data................. 367

Table 10.7 Options for testing for step trends in censored water quality data............................ 367

Table 11.1 Summary of reporting and communication products.. ............................................. 371

Table 12.1. Station IDs for water quality sampling locations.................................................... 380
Appendix H Standard Operating Procedures 

175
176

SOP #1 Protocol Revision and Review

1.1 Revision History Log

Prev. Version # Revision Date Author Changes Made Reason for 

Change

New 

Version #

Jan. 2005 Mary 

Cooprider

Created SOP to 

document protocol 

revision procedures

Addressing 

comments by 

WRD

1.0

1.0 8-24-2006 Rob Carson Added revision 

history table, and 

section containing 

protocol review 

comments, responses 

and approvals

Suggested by peer 

review

1.1

1. ―Version numbers increase incrementally by hundredths (e.g. version 1.01, version 1.02 

...etc) for minor changes. Major revisions should be designated with the next whole number 

(e.g., version 2.0, 3.0, 4.0 ...). Record the previous version number, date of revision, author 

of the revision, identify paragraphs and pages where changes are made, and the reason for 

making the changes along with the new version number‖ (Peitz et al., 2002).

2. Notify the SFAN Lead Data Manager of any changes to the Protocol Narrative or SOP so 

that the new version number can be incorporated in the Metadata of the NPSTORET 

database. The Data Manager will then edit the database per any changes to the Protocol 

Narrative and SOPs.

3. Post new versions on the internet and forward copies to all individuals with a previous 

version of the Protocol Narrative or SOP.

1.2 Scope and Application

This Standard Operating Procedure explains how to make changes to the Freshwater Quality 

Protocol Narrative and accompanying SOPs, and explains procedures for tracking these changes. 

SFAN or park staffs editing the Protocol Narrative or any SOP need to follow this procedure to 

eliminate confusion in data collection and analysis methods. All SFAN aquatic resources staff 

should be familiar with this SOP in order to identify and use the most current methodologies. 

This SOP is adapted from the Bird Monitoring Protocol SOP #11 for Agate Fossil Beds National 

Monument, Nebraska and Tallgrass Prairie National Preserve, Kansas (Peitz et al., 2002). Their 

protocol can be accessed at http://science.nature.nps.gov/im/monitor/protocols/birds.htm

This SOP also contains a Table 1.1 listing the most current version of the protocol narrative and 

each of the SOP’s. This will provide a single reference for ensuring that the most current 

documents are being used. Also included is a section containing comments from protocol review, 

responses to those comments and approvals.
177

Table 1.1 Current SFAN Freshwater Quality Protocol Documents.

Document Name Current 

Version

Version 

Date

Author

San Francisco Bay Area Network Freshwater 

Quality Monitoring Protocol, Protocol Narrative

2.11 10/12/06 Cooprider, M. and 

Carson, R.

SOP#1: Protocol Revision and Review 1.1 8/25/06 Cooprider, M. and 

Carson, R.

SOP#2: Personnel Training and Safety 1.02 6/22/06 Cooprider, M. and 

Carson, R.

SOP#3: Equipment and Field Preparations 1.03 8/1/06 Cooprider, M. and 

Carson, R.

SOP#4: Quality Assurance Project Plan (QAPP) 2.04 10/13/06 Cooprider, M. and 

Carson, R.

SOP#5: Field Methods for Measurement of Core 

Parameters

1.03 8/1/06 Cooprider, M. and 

Carson, R.

SOP#6: Field and Laboratory Methods for Fecal 

Indicator Bacteria

1.1 8/11/06 Cooprider, M. and 

Carson, R.

SOP#7: Field Methods for Sampling Nutrients 1.02 3/16/06 Cooprider, M. and 

Carson, R.

SOP#8: Field and Laboratory Methods for 

Sediment

1.02 3/23/06 Cooprider, M. and 

Carson, R.

SOP#9: Field Methods for Measuring Stream 

Discharge

1.02 3/9/06 Cooprider, M. and 

Carson, R.

SOP#10: Data Analysis 1.03 9/28/06 Cooprider, M. and 

Carson, R.

SOP#11: Data Reporting 1.02 3/23/06 Cooprider, M. and 

Carson, R.

SOP#12: Site Selection and Documentation 1.01 3/9/06 Cooprider, M. and 

Carson, R.

1.3 Protocol Revision Procedures

1. The Freshwater Quality Monitoring Protocol Narrative and accompanying SOPs has made 

every effort to incorporate the most sound methodologies for collecting and analyzing water 

quality data. However, all protocols require editing as new and different sample collection, 

analysis, and data management information becomes available. Required edits should be 

made as soon as they are deemed necessary and appropriate reviews conducted. 

2. All edits will be reviewed for grammatical and technical accuracy and overall clarity. Minor 

changes or additions to existing methods will be reviewed ―in-house‖ by the SFAN aquatic 

professionals’ team and other appropriate network staff. However, if a complete change in 

methods is anticipated, then an outside review is required. Regional (Pacific West Region) 

and National staff (Water Resources Division) of the National Park Service familiar with 

water quality monitoring and data analysis will be utilized as reviewers. Also, local and state 

experts in water quality monitoring and statistical methodologies outside of the Park Service 

will be utilized in the review process. A group of technical experts was utilized for the 

external peer review of the initial Freshwater Quality Protocol; these individuals would be 

called upon again to provide input related to any significant revisions in methodology.
178

3. Edits and protocol revisions will be documented in the Revision History Log that 

accompanies the Protocol Narrative and each SOP. Only changes in the Protocol Narrative 

or specific SOP that has been edited will be logged. ―Version numbers increase 

incrementally by hundredths (e.g. version 1.01, version 1.02 ...etc) for minor changes. 

Major revisions should be designated with the next whole number (e.g., version 2.0, 3.0, 4.0 

...). Record the previous version number, date of revision, author of the revision, identify 

paragraphs and pages where changes are made, and the reason for making the changes along 

with the new version number‖ (Peitz et al, 2002).

4. Notify the SFAN Lead Data Manager of any changes to the Protocol Narrative or SOP so 

that the new version number can be incorporated in the Metadata of the NPSTORET 

database. The Data Manager will then edit the database per any changes to the Protocol 

Narrative and SOPs.

5. Post new versions on the internet and forward copies to all individuals with a previous 

version of the Protocol Narrative or SOP.

6. When any significant changes in the sampling protocol occur such as changes in sample 

collection techniques or equipment, a change in analytical laboratory, or changes in staff, 

there should be an ―overlap‖ of methods and personnel (Oakley et al., 2003). This requires 

using both the old and new techniques on a given sample as well as having both the outgoing 

and new staff sample concurrently. The National Park Service Water Resources Division 

(NPS-WRD) recommends an overlap of at least seven sampling events (Irwin, 2005).

1.4 Protocol Review

1.4.1 Reviewer Comments

Appendix A contains the PWR Protocol Review Checklist generated by the formal peer review 

process. Also included in this appendix are the consolidated comments and responses from 

formal peer review.

1.5 References 

Irwin, R. 2005. Personal Communication. National Park Service, Water Resources Division, Fort 

Collins, Colorado.

Peitz, D.G., S. G. Fancy, L. P. Thomas, and B. Witcher. 2002. Bird monitoring protocol for 

Agate Fossil Beds National Monument, Nebraska and Tallgrass Prairie National Preserve, 

Kansas. Prairie Cluster prototype monitoring program. Version 1.00, September 6, 2002.

Oakley, K.L, L.P. Thomas, and S.G. Fancy. 2003. Monitoring Protocol Guidelines. Wildlife 

Society Bulletin 31(4): 1000-1003. 
179
180

SOP #2 Personnel Training and Safety

2.1 Revision History Log

Prev. Version # Revision Date Author Changes Made Reason for 

Change

New Version 

#

1.0 8/05/05 M. Cooprider Minor edits Preparation for 

formal peer review

1.01

1.01 6/22/06 R. Carson Revised JHA Prev. version had 

GOGA Aquatic 

Ecol. JHA

1.02

Only changes in this specific SOP will be logged here. ―Version numbers increase incrementally 

by hundredths (e.g. version 1.01, version 1.02 ...etc) for minor changes. Major revisions should 

be designated with the next whole number (e.g., version 2.0, 3.0, 4.0 ...). Record the previous 

version number, date of revision, author of the revision, identify paragraphs and pages where 

changes are made, and the reason for making the changes along with the new version number‖ 

(Peitz et al, 2002).

2.2 Acknowledgements

The USGS National Field Manual Chapter 9 (Safety) was used extensively (Lane and Fay 1997) 

during the writing of this protocol. In addition, the Job Hazard Analysis (JHA) from Golden 

Gate National Recreation Area (Fong et al., 2003) was followed for safety hazards specific to 

aquatic projects in the Coastal California Mediterranean climate. The Greater Yellowstone 

Network’s Safety and Health SOP (O’Ney 2005) for their long-term water quality monitoring 

plan was also reviewed for ideas on format and content. The SFAN Water Quality Monitoring 

Program acknowledges the individuals involved in writing and researching these documents.

2.3 Scope and Application

Safety and training are included together in a single SOP because they are closely linked. 

Training for water quality sampling is much more than learning proper equipment use and 

sampling techniques. Safety and QA/QC are significant components of a long-term water quality 

monitoring plan. Many safety issues are associated with implementing a long-term water quality 

monitoring plan that includes extensive field work across multiple parks, with multiple staff in 

varying environmental conditions. Thorough planning is required to ensure that training and 

safety requirements are met and that the safety of field personnel is not compromised. 

2.4 Training

2.4.1 Introduction

NPS staff collecting all water quality data and downloading continuous loggers and have either 

already been trained by other NPS staff or will be trained before plan implementation. Scientists 
181

at PORE and GOGA have been conducting water quality related activities for several years and 

can provide training if necessary to network staff. Current network staff are trained in water 

quality procedures and can learn additional methods (e.g., use of Hydrolab mini-sondes for 

continuous measurement) from GOGA and PORE staff.

All technical staff involved in data collection will have education background in biological or 

physical sciences. The Network Water Quality Specialist (Program Lead) will have specialized 

experience in water quality or closely related aquatic resource. Where necessary (e.g., with staff 

turnover, adoption of new methods, etc.) local technical experts (universities/agencies) will be 

called upon for training assistance. Familiarity with GPS navigation will also be a qualification 

(or training will be provided). First Aid and CPR training are highly recommended. Boater 

certification will not be needed at this time. Field personnel (network hydrologic technician) 

will receive training in a variety of discharge (flow) measurement methods (e.g., low flow, high 

flow bridge-deployed). 

Field personnel (Network Hydrologic Technician and other SFAN staff (biological 

technician/park Americorps crews)) will be evaluated on their field performance during field QA 

audits conducted by the SFAN Water Quality Specialist, other park aquatic professionals. Field 

performance audits are recommended every two years, or more often if necessary. If any 

deficiencies within a crew are noted during this QA audit, they will be documented and remedied 

prior to continued field sampling. This can be accomplished by additional training or by 

changing personnel, but verification of correction of any deficiencies must be documented in 

writing prior to the resumption of further sample collection activities. 

2.4.2 Procedures

1. At least two network or park individuals will be trained in equipment use and sampling 

techniques, and QA/QC measures. This will help ensure continuity should one person leave 

a position or otherwise not be available for a particular sampling event. In addition, it will be 

mandatory that two field staff be present for sampling during storm events and it is 

recommended at other times as well. 

2. Staff will be trained through review of written guidance plus a series of sampling events. 

The overall project purpose, protocols, equipment manuals, and field maps will be reviewed 

before commencing fieldwork. The first sampling event (or first group of sites in an event) 

will be used to demonstrate the sampling process including QA/QC (see SOP #4 – QA/QC 

SOP). The second sampling events or group of sites will give the trainees an opportunity to 

sample with guidance. The trainer (Network Physical Scientist) will periodically accompany 

the recently trained individuals to ensure that the protocol continues to be followed and to 

address any questions.

3. Ensure that all field personnel obtain First Aid and CPR training. This is also highly 

recommended for office personnel. 
182

4. Supervisory staff should ensure that all field staff are well trained in the safety guidelines and 

policies outlined below.

2.5 Safety

2.5.1 Introduction

Safety is ―the condition of averting or not causing injury, danger, or loss‖ (Lane and Fay, 1997). 

As a Federal employee, you are required to know and follow safety policies and requirements. 

The USGS National Field Manual (NFM) provides background information on safety policies 

from the Department of Interior (DOI), the Occupational Safety and Hazard Act (OSHA), the 

Environmental Protection Agency (EPA), and the Department of Transportation (DOT). The 

USGS National Field Manual extensively covers all of the topics below:

Safety Policies, Regulations, and Requirements

Field trip preparations and emergency contacts*

Transportation*

Surface water activities*

Groundwater activities

Chemicals*

Contaminated Water*

Environmental Conditions*

Animals*

Plants *

Checklist of Safety Equipment*

The asterisk (*) denote topics that are covered here since they are most pertinent to the current 

SFAN water quality monitoring protocol. This SOP will also individually address potential 

safety hazards by focusing on an existing Job Hazard Analysis created for the aquatics program 

at GOGA. Consult the NFM at http://water.usgs.gov/owq/FieldManual/Chap9/content.html for 

complete recommended safety procedures. This document is included in the appendices and 

should be readily available as a reference in the field. 

Plants

The USGS National Field Manual, Chapter 9 provides a thorough summary of field hazards. 

Some of the most common health hazards within SFAN include poison oak and stinging nettle. 

The safety briefing ―Working in Poison Oak‖ (Brands-Maloney, 2001) provides an extensive 

review of poison oak identification, location, prevention, and treatment of contact dermatitis and 

is included in the appendix. Field personnel should review this BEFORE entering the field. Be 

familiar with the shape, color, and size of poison oak leaves twigs, vines, and, yes, shrubs. 

Stinging nettle is not a health threat but causes skin irritation which can be severe (though 

temporary) if in large amounts.
183

Animals and disease vectors

Although rare, large predators such as mountain lions inhabit some of the areas within the parks. 

Though some of these hazards are rare, it is important to be aware of all of them. Rattlesnakes 

may also occur but rarely near riparian areas where sampling will occur. Local information 

about ticks and Lyme disease is also included in the appendix. West Nile Virus, a more recent 

concern, is transmitted by mosquitoes. Though not a major threat, it is important to be aware of 

this virus. Only a few species of mosquitoes carry the virus and fewer are infected. Another 

issue to be aware of is Hantavirus which is spread through rodent feces and normally a concern 

indoors, or garages, or other areas where equipment may be stored. As with all hazards, consult 

the USGS National Field Manual for details. 

Inclement Weather and Surface Water Activities

Sampling during storm events is of particular concern in Mediterranean climates. Most, if not 

all, of the streams in the SFAN are ―flashy‖, meaning that water level rises rapidly during a 

storm event. For example, individuals taking flow measurements in Chalone Creek (PINN) have 

had to end flow measurements since the stage rose to an unsafe level during the short time that 

the velocity measurements were being taken. Do not attempt to wade in a stream for which 

values of depth multiplied by velocity are greater than or equal to 10 ft2/s. During high flows 

use of a wading belt is recommended to avoid the waders filling with water. Any time chest 

waders are worn, a life jacket is required. 

Other potential hazards to be considered at all parks include flowing logs and other debris, 

quicksand (particularly at PINN), falling trees, drowning, falling, back injuries from 

lifting/bending/falling. A thorough list of hazards is particularly useful for staff that may not be 

familiar with the local weather and climate, topography, flora, or fauna. A good summary of 

these hazards is provided in the Job Hazard Analysis (JHA) for Aquatic Projects (Fong et al, 

2003) in the Appendix.

Contaminated Water

Waterborne pathogens include typhoid, tetanus, hepatitis, polio, and rabies. Excess quantities of 

E. coli can cause gastrointestinal problems but are usually less severe than the previously 

mentioned pathogens. Never drink water straight from a creek. Water being sampled may be 

contaminated with pathogens or harmful chemicals. Use extra precautions when working with 

water that is known to be contaminated. Some precautions include not eating or drinking while 

sampling and not putting objects such as pencils in your mouth. In particular, keep hands away 

from nose, ears and mouth (this also helps reduce spreading of poison oak). Wash hands 

thoroughly before eating. If no soap and water are available, use of an antibacterial hand 

cleanser is highly recommended. 

Chemicals

Some potentially hazardous chemicals are required for cleaning of water quality instruments. 

Chemicals become hazardous when they are used improperly or care is not taken. Know the 

location of Materials Safety Data Sheets (MSDS) and consult these BEFORE using any 

chemical. Also, know the storage requirements and proper location for the chemical. 
184

Transportation 

Safety considerations for vehicles used to reach sampling sites are covered in the attached JHA. 

Most of us drive a vehicle regularly and may not always think about the hazards associated with 

it. It is very important to inspect the vehicle before leaving. Ensure that safety equipment is in 

the vehicle. During driving to and from sampling areas it is particularly important to consider 

issues such as nighttime driving and fatigue, storms, road flooding, driving in (initially) 

unfamiliar areas and remote areas where large animals may be crossing the road. Additional 

details regarding transportation safety procedures and policies are listed in the USGS National 

Field Manual. 

Environmental Hazards and General Emergency Information

Individual parks have occupant emergency plans which cover safety procedures for medical 

emergencies, earthquakes, floods, fires, bomb threats. Be familiar with the procedures and 

emergency contact numbers of your duty station park as well as other parks you may visit during 

field sampling activities. Overall, be aware of your environment, use common sense, do not 

exceed your limits (for example, operation of equipment; lifting heavy objects and equipment; 

physical tolerance to exertion, heat, and cold), and trust your instincts (Lane and Fay, 1997).

2.5.2 Procedures for Safety Preparation

Adapted from the California Water Resources Control Board Surface Water Ambient Monitoring 

Program (SWAMP) Appendix H of the Quality Assurance Management Plan (Puckett, 2002).

Basic planning is required before each field sampling event. A large component of the planning 

effort involves gathering safety information and documenting all aspects of field sampling trip 

plans. A trip plan should be completed. One copy should be left at the office and additional 

copies should be given to field personnel involved in the trip. The trip plan should contain the 

following information:

Destination information (parks, streams/sites)

Field trip participants including guests and observers along with emergency contact 

 information for each

Estimated departure and return times and dates 

Lodging information and contact phone numbers when traveling overnight

Vehicle information (make and model of vehicle to be used)

Phone numbers for mobile phones or park radio frequencies

Contact number of staff at destination park (if applicable)

Dispatch phone numbers for each park

The trip plan is a valuable tool in the overall trip planning process. In addition, the plan provides 

valuable information for other staff not participating in the trip (who may assist you should an 

emergency occur). Other safety preparations include:

Check the weather and be aware of changing weather conditions and potential for storms, 

floods and landslides. 
185

Carry basic safety equipment (first aid kit, flashlight, boots, rain gear, and antibacterial hand 

 cleanser)

Carry the USGS NFM Ch.A9, basic first aid protocols, emergency phone numbers and 

Material Safety Data Sheets (if applicable)

Collect and update emergency contact information prior to the field season

Consult the safety checklist in this SOP as well as the equipment checklist in SOP #3 before 

 each sampling event

Note and discuss potential hazards at each site with field staff

Requirements for All Field Personnel:

1. At least two network or park individuals will be trained and introduced to all potential safety 

hazards. This will help ensure continuity should one person leave a position or otherwise not 

be available for a particular sampling event. 

2. It will be mandatory that two field staff be present for sampling during the winter (high 

flows) and it is highly recommended at other times as well. 

3. Staff will review the attached Job Hazard Analysis (JHA) adapted from the GOGA JHA for 

Aquatic surveys and projects. The USGS National Field Manual will be available for, and 

reviewed by, all staff.

4. A tetanus shot is required for field personnel.

5. As indicated in the training section, all field personnel should be certified in CPR and First 

Aid.

2.5.3 Forms

Complete for each park:

2.5.3.1 Emergency Contact Form (from USGS National Field Manual, Ch. A 9)

Personal contacts

Name: Phone: (home) (work) ___________________________________________________

Name: Phone: (home) (work) ___________________________________________________

SFAN contacts

Golden Gate National Recreation Area ____________________________________________

John Muir National Historic Site _________________________________________________

Pinnacles National Monument ___________________________________________________

Point Reyes National Seashore ________________________________________
186

Local emergency contacts (or call 911)

Hospital Phone: ______________________________________________________________

Address: ____________________________________________________________________

Other medical facility (24-hour care) Phone: _______________________________________

Address: ____________________________________________________________________

Police______________________________________________________________________

Fire________________________________________________________________________

Utility______________________________________________________________________

Health Information Centers

Center for Disease Control______________________________________________________

Information Hotline: __________________________________________________________

Fax: Disease Directory: _________________________________________________________

Other_______________________________________________________________________

____________________________________________________________________________
187

2.5.3.2 Medical Information form for Office Personnel (USGS National Field 

Manual, Ch. A9) 

Medical Information for Office Personnel 

Employee name: Home phone: 

Tr eatment preference: medical other (specify) 

Doctor. Phone: 

Other emergency contaCl:: Phone: 

Allergies and other Medications bcing taken Medications to avoid medical conditions 

Relevant medical history: 

Allergies and other medical conditions: 

Special instructions: 

Figure 9-2. Example of medical infOIIIlBtion fOfiil to be completed 

and tBken on field tii p;o. 
188

2.5.4 Checklists for Standard Safety Equipment

Checklists are helpful for ensuring that personnel have the appropriate safety equipment 

available during field trips. Each study team needs to consider the specific needs for their work 

and should customize these checklists as necessary.

2.5.4.1 Safety Equipment Checklists

Check Item

 Climatic and UV protection, etc.

Boots

Fluids (for example, water and sports drinks)

Hat, wide-brimmed

Insect repellent (unscented)

Rain gear

Sunglasses

Sunscreen

Antibacterial soap or hand lotion

Temperature-modifying clothing

2.5.4.2 Items for Vehicles

Check Item

 Flotation and reflective protection

Orange flotation vests and jackets

Safety harness

 Chemical protection and storage

Chemical spill kit

Eye wash kit (replace old or expired wash solution)

Material Safety Data Sheets (MSDS)

Chemical reagents (stored in appropriate area)

Flammable solvents (stored in appropriate dedicated area)

Pressurized gases (stored in appropriate area)

 Communications and instructions

Field folder (including maps, emergency phone numbers for medical facilities, office contacts, family contacts)

Cellular phone/communication equipment (check that the service is operational for the area to be traveled)

 First aid and protective equipment

Complete change of clothes (stored in dry area)

Fire extinguisher (safely secured)

First aid kit and manual (check for missing or old, expired items and replace if necessary)

Orange reflective vest

 Miscellaneous equipment

Bungee cords (to secure loose articles)

District flood plan (most current version)

Flagging

Flares

Flashlight (including fresh batteries)

Flexible hose (to vent exhaust away from vehicle)

Safety cones

Tool kit

U.S. Geological Survey TWRI Book 9 Chapter A9.
189

2.6 References

Brands-Maloney, C. 2001. Working in Poison Oak. Point Reyes National Seashore Safety 

Briefing. U.S. Department of Interior, National Park Service. 

Fong, D., B. Holden, D. Anderson. 2003. Golden Gate National Recreation Area Job Hazard 

Analysis for Aquatic Surveys and Projects. Golden Gate National Recreation Area and 

Redwood National Park. U.S. Department of Interior, National Park Service. 

Lane, S.L., and Fay, R.G., October 1997, Safety in field activities: U.S. Geological Survey 

Techniques of Water-Resources Investigations, book 9, chap. A9, accessed __date__ at 

http://pubs.water.usgs.gov/twri9A9/ 

O’Ney SE. 2005. Safety and Health, Version 1.0, Standard Operating Procedure #3. In 

Regulatory Water Quality Monitoring Protocol, Version 1.0, Appendix E – SOPs, National 

Park Service, Greater Yellowstone Network. Bozeman, MT. 37 pp. plus appendices.

Peitz, D.G., S. G. Fancy, L. P. Thomas, and B. Witcher. 2002. Bird monitoring protocol for 

Agate Fossil Beds National Monument, Nebraska and Tallgrass Prairie National Preserve, 

Kansas. Prairie Cluster prototype monitoring program. Version 1.00, September 6, 2002.

Puckett, M. 2002. Quality Assurance Management Plan for the State of California's Surface 

Water Ambient Monitoring Program ("SWAMP"). California Department of Fish and 

Game, Monterey, CA. Prepared for the State Water Resources Control Board, Sacramento, 

CA. 145 pages plus Appendices.
190

SOP #2 Appendix A Job Hazard Analysis for Aquatic Surveys 

and Projects 

Note: not all hazards apply to water quality monitoring
191

Job Hazard Analysis

I&M/PORE – Water Quality

U.S. Department of Interior WORK PROJECT/ACTIVITY LOCATION UNIT

National Park Service

Water Quality Sampling and 

Projects

San Francisco Bay Area 

Network (SFAN)

Point Reyes NS (PORE)

Nat'l Resource Mngt 

and Science

JOB HAZARD ANALYSIS (JHA) DEVELOPED BY JOB TITLE DATE PREPARED

Adapted from Aquatic surveys and projects 

JHA developed by Darren Fong (GOGA) and 

Baker Holden III and David Anderson (REDW) Rob Carson (SFAN – PORE)

Water Quality Specialist Revised 14 July 2006

APPROVED BY: DATE:

Required and/or Recommended Personal Protective Equipment:

Sturdy work boots Life Preserver

Warm clothing / hat Felt sole waders (chest, hip, neoprene)

Sun hat Felt sole wading boots

Sun glasses Cotton gloves / wool gloves

Sunscreen 

Personal water bottles Latex gloves

First Aid Kit Survivor kit

Park radio Polarized sunglasses

Technu (poison oak cleanser) Maps

Forceps / vial 

Safety glasses 

TASKS/PROCEDURES HAZARDS ABATEMENT ACTIONS

Engineering Controls*Substitution*Administrative Controls* 

Personal Protection Equipment

All Tasks and Procedures Unfamiliarity All people (permanent, seasonal, VIPs) involved in any project should 

receive a general orientation and tailgate safety session specific to the task 

prior to beginning of work. 
192

1. Driving to and from remote field sites. 1a. Narrow, single-lane 

roads with bumpy or 

―washboard‖ surfaces;

1b. Driving with limited 

visibility;

1c. Sharp rocks on edge or 

in middle of road;

1d. Large animals crossing 

or standing in roads 

(including park bypass);

1f. Fatigue at night and 

after a long shift in the 

field;

1g. Storm conditions –

wind, lightning, muddy/ 

slippery roads; 

1h. Fallen trees on road;

1i. Others driving on the 

road;

WEAR SEATBELTS AT ALL TIMES WHEN VEHICLE IS MOVING

1a. Maintain a safe speed (this if often below the legal speed limit) for the road 

conditions;

stay clear to the right, especially on curves, drive with headlights on at all times;

when turning around on mountain roads always ―face the danger‖ (versus 

backing toward the cliff edge, e.g.); the passenger should get out and spot for 

driver when backing up;

1b. Maintain windshield cleaner fluid level and clean both sides of windows 

regularly (remember back window); 

slow down; 

if blinded by sun or dust, proceed slowly or pullover and wait for hazard to pass; 

keep to the right hand side of the road and drive with your lights on;

1c. Get out and move sharp rocks out of the way, reduce speed substantially in 

places with large amounts of rock fall;

make sure tires are properly inflated and check tread and walls regularly for 

damage;

make sure tire jack fits the vehicle and all parts are in the vehicle;

1d. Slow down where animals might be present to allow for reaction time; do 

not swerve abruptly to avoid hitting an animal, if necessary it’s better to ride out 

the impact;

1f. Be aware of signs of fatigue- pull over and rest! Take a short catnap or eat a 

snack or have a partner drive; do not take chances by continuing to drive; 

communicate with your field partner;

1g. Keep informed on the current weather- check www.weather.com or 

www.wrh.noaa.gov;

if winds exceed 15 mph, or the excessive wind category on Beaufort scale (tree 

tops swaying, twigs and leaves falling, etc.), do not travel into the field; 

avoid going to the field if lightning is present and avoid using radios;

drive slowly when roads are muddy and slippery or snow covered, check with 

geologists if you are uncertain of back road conditions;

avoid wet clay roads as much as possible, these roads can fail after storms, 

especially in spring, maintain a slow speed when driving on these roads!;

if you damage waterbars make sure you repair them immediately;

1h. For small trees, try and remove tree or cut with a handsaw and remove 

portion of tree; for large trees, notify support crew to remove tree; 

1i. Do not assume you are the only one on the road behind locked gates (day or 

night), people from other agencies use these roads;

be alert to the idea that others may be coming in from the field in the early a.m. -

drive slow and keep right!; 

if you encounter an unusual situation, contact your partner to inform and 

notify the supervisor or park ranger- avoid confrontational situations with 
193

2. Communication 2a. Unable to reach a 

radio repeater in a 

remote location.

2a. Make sure radio is charged- try to raise someone on the radio to inform them 

of your predicament;

if you are unable to reach a repeater from your location climb up slope toward a 

ridge top or knoll and try again;

try at regular intervals, just meandering around may help in getting a signal;

use cell phone in vehicle (if available), as this may be more reliable for 

communication in remote locations.

3. Hiking 3a. Steep, rugged, and 

slippery terrain

3b. Undergrowth

3a. Assess terrain conditions to find safe route and modify sampling plans to 

avoid unsafe areas; Proper footwear is VERY important- wear boots with 

Vibram or other slip-resistant soles with tops well above the ankle, broken in 

before the field season, plus 2-3 pairs of cotton or wool socks, NO TENNIS 

SHOES; if wearing wading boots be cognizant that they are slippery on grass 

and mud, carry supplies in backpack, make sure pack is comfortable and secure, 

waist belt recommended;

take care when walking on hardwood leaf litter and on wet ground;

maintain an erect posture when contouring steep slopes;

avoid walking below another person due to the potential for rocks to dislodge 

from above; use caution when crossing large and/or wet logs.

3b. Wear safety glasses (or other glasses) when hiking in brushy areas to 

protect eyes from protruding objects.
194

4. Encountering noxious plants, animals, disease, and people 4a. Poison oak

4b. Bees/Wasps/Hornets

4c. Ticks

4a. Make sure you can identify poison oak in all its growth forms, foliage, bare 

twigs, and berries (the plant is toxic in winter when foliage is absent!);

apply barrier cream to prevent exposure;

wear long sleeves or Tyvex suit (or comparable);

avoid sitting with arms resting on knees;

use Technu (or something similar) lotion to prevent exposure;

wash with Technu soap immediately after returning from the field;

bring an extra set of clothes and shoes to change into after coming out of field;

wash field clothes separately from other laundry.

4b. Determine if any field crew are allergic to bee stings. Notify other crew 

members and the supervisor if you know you are allergic to bee stings. Ensure 

that individual carries prescribed medication to prevent anaphylactic shock;

Carry a bee sting kit or Benadryl or other antihistamine;

Be aware of the ground where you step- some hornets build nests in the ground 

at the base of trees or shrubs, or in rotten logs- watch for bees buzzing in and out 

of holes or around ground level;

if possible, flag a nest so future surveyors won’t run into it; 

4c. Know how to identify and distinguish the ―deer tick‖ that carries Lyme 

disease, from the ―wood tick‖ that does not;

if bitten by a tick, remove it (grasp tick with tweezers at head and pull straight 

out), and follow instructions for preserving it and turn it in to the county health 

department so they can determine if it was carrying Lyme;

fill out a CA-1 (accident report) in the event that symptoms of Lyme disease 

appear eventually;

4d. Inspect items left lying on the ground, e.g., clothing, for scorpions prior to 

putting them on;

4e. Avoid rattlesnakes by inspecting the ground near logs before stepping over 

them; avoid placing hands on rock ledges or other natural hoists without visually 

inspecting them first; in the unlikely event you’re bitten by a rattlesnake, stay 

calm, sit still, and call and wait for help;

4g. Avoid mountain lions; if you encounter a lion that doesn’t run from youleave the area; if attacked- fight back!

4h. Stay away from dead rodents and rodent feces, especially in closed 

buildings. 

4i. Report uncomfortable encounters with strangers in the park to a supervisor 

as soon as possible; report apparent illegal activity to a park ranger, do not get 
195

5. Exposure to environmental variables 5a. Treatment of 

general injuries

5b. Hypothermia

5c. Hyperthermia

5d. Giardia

5e. Sunburn

5a. All NPS field staff and contractors will be required to have current First Aid 

certification. 

5b. Always anticipate bad weather and dress accordingly, or carry warm clothes 

with you. Always travel in pairs as a minimum. Keep clothing as dry as 

possible. Eat high energy nutritional supplements between meals. Cover the 

head and neck to prevent heat loss. Keep active to maintain the body’s 

metabolism. Drink plenty of liquids to prevent dehydration, although an 

individual does not ―feel‖ thirsty. Drink warm liquids not cold. Understand the 

effects of cold and wind: most hypothermia cases develop between 30F and 

50F. 

5c. Hyperthermia may occur during high temperatures, monitor for dehydration, 

heat exhaustion, heat cramps, and heat stroke;

symptoms include nausea, headache, and flushed, red skin;

drink plenty of water (even when you are not thirsty); 

as heat increases, take frequent breaks in cool locations; wear a light shirt.

5d. Giardia is caused by drinking contaminated water- carry plenty of water on 

outings. Consider all streams contaminated. 

5e. Much of the work takes place in full sunlight (estuary seining, snorkeling, 

etc.) so prevent sunburn, use 15+ or greater SFP sunscreen and lip balm; and 

wear a hat, sunglasses, and shirt. 

6. General work in or near streams 6a. Working near 

unstable, steep, deep 

channels, swift flows. 

6b. Giardia

6c. Sunburn

6d. Undergrowth

6a. Reconnoiter to familiarize yourself with stream and reach adjacent to 

project. Know the current and projected flow conditions from weather 

forecasts and stream gauge info. Familiarize yourself with work area prior to 

fieldwork. Review maps and aerial photos to determine access points, 

reference points, and potential evacuation points. Develop evacuation plans for 

remote stream sites and make sure you sign out (including location) on the 

checkout board prior to leaving for the field.

6b. Refer to 5d.

6c. Refer to 5e.

6d. Refer to 3b. 
196

7. Aquatic surveys, Water Quality/Flow Sampling, Culvert 

Surveys, Spawning/Carcass Counts, Habitat Monitoring, 

Frog Surveys, Fish Distribution Study, Habitat 

Improvement Design and Layout, and Project Monitoring

7a. Wading/walking in 

and across streams

7b. Wading/walking in 

and across aquatic 

sites

7c. Crossing Debris 

Jams

7b. Hypothermia

7c. Giardia

7d. Sunburn

7a. Wear proper waders, felt-soled, chest or hip boots for conditions. When 

using waders, wear wading belt or similar. Purchase and use waders with felt 

soles or retrofitted with anti-slip devices. In cold weather, wear neoprene 

waders or wear warm, preferably polyester garments with standard waders. 

Use walking stick to improve stability in current. Walk slowly and carefully. 

Work in teams of two or more and within sight of one another. Cross-stream at 

shallow riffles, and avoid deep, swift areas. Consult weather forecast each 

morning or call local observer to determine stream and flow conditions. Avoid 

wet logs and slippery rocks. Sign out/in at board in front office each day. All 

people must be CPR and First Aid Certified. Carry a means of communication 

(e.g., cell phone or radio).

7b. Refer to 7a. When wading in aquatic sites with deep, fine sediments, test 

fine sediment depths with wading rod before entering. Do not enter when fine 

sediment depths extend above knee.

7c. Determine the safest route along the creek; either climbing around on 

either side of the banks, or by going under and/or on top of the jam. 

When crossing you should be in sight of your coworkers in case anything 

should occur. Free both hands to assist with climbing jams. If crossing 

under and/or on top of the jam, be cognizant of its structural integrity. 

Walk or crawl on the larger key pieces/logs in the jam as smaller woody 

pieces are more prone to shift, break, or completely give way. Usually, 

the larger pieces are the most stable and structurally sound. The same is 

true for any handholds you may use when climbing the jam. If unsure, do 

not put all your weight on a piece at once, be slow and maintain your 

handholds if possible. Avoid slick wet logs without bark and if cold, be 

aware of ice that may be on their surfaces. DO NOT JUMP onto log 

pieces.

7b. Refer to 5b.

7c. Refer to 5d.

7d. Refer to 5e.
197

8. Boats (non-motorized) 9a. Drowning

9b. Capsizing

9c. Hypothermia

9a. Wear proper boating protective/floatation gear (life vests, water-repellent 

clothing) at all times. Use boats ONLY if trained and knowledgeable in boat 

use. Work in pairs or teams. Consult flow gauge to determine stream safety 

level. 

9b. Watch out for large organic debris (sweepers) in the channel. Scout 

unfamiliar obstacles before paddling through. Balance the weight in the boat. 

Be cognizant that a boat can be easily tipped by shifting your weight.

9c. See 5a.

JHA Instructions 

The JHA shall identify the location of the work project or activity, the name of

employee(s) involved in the process, the date(s) of acknowledgment, and the name of 

the appropriate supervisor approving the JHA. The supervisor acknowledges that 

employees have read and understand the contents, have received the required 

training, and are qualified to perform the work project or activity. 

Identify all tasks and procedures associated with the work project or activity that 

have potential to cause injury or illness to personnel and damage to property or 

material. Include emergency evacuation procedures (EEP).

Identify all known or suspect hazards associated with each respective 

task/procedure listed. For example:

a. Research past accidents/incidents.

b. Research the Health and Safety Code, or other appropriate literature.

c. Discuss the work project/activity with participants.

d. Observe the work project/activity.

e. A combination of the above.

Emergency Evacuation Instructions 

Work supervisors and crewmembers are responsible for developing and discussing 

field emergency evacuation procedures (EEP) and alternatives in the event a 

person(s) becomes seriously ill or injured at the worksite.

Be prepared to provide the following information:

a. Nature of the accident or injury (avoid using victim's name).

b. Type of assistance needed, if any (ground, air, or water evacuation).

c. Location of accident or injury, best access route into the worksite (road 

name/number),

 Identifiable ground/air landmarks. 

d. Radio frequencies.

e. Contact person. 

f. Local hazards to ground vehicles or aviation.

g. Weather conditions (wind speed & direction, visibility, temperature).

h. Topography. 

i. Number of individuals to be transported.

j. Estimated weight of individuals for air/water evacuation. 

The items listed above serve only as guidelines for the development of emergency 

evacuation procedures. 

JHA and Emergency Evacuation Procedures Acknowledgment

 Identify appropriate actions to reduce or eliminate the hazards identified. 

Abatement measures listed below are in the order of the preferred 

abatement method:

We, the undersigned work leader and crewmembers, acknowledge participation in the 

development of this JHA (as applicable) and accompanying emergency evacuation 

procedures. We have thoroughly discussed and understand the provisions of each of 

these documents:

a. Engineering Controls (the most desirable method of abatement). 

For example, ergonomically designed tools, equipment, and SIGNATURE DATE SIGNATURE DATE

Furniture.
198

b. Substitution. For example, switching to high flash point, non-toxic 

solvents.

Work Leader

c. Administrative Controls. For example, limiting exposure by reducing 

the work schedule; establishing appropriate procedures and practices.

d. PPE (least desirable method of abatement). For example, using hearing 

 protection when working with or close to portable machines 

(chain saws, rock drills, and portable water pumps).

e. A combination of the above.

Copy of the JHA as justification for purchase orders when procuring PPE.
 199

SOP #2 Appendix B. Working in Poison Oak – Safety Briefing 

(hardcopy only) 
 200

SOP #3 Equipment and Field Preparations 

3.1 Revision History Log

Prev. 

Version #

Revision 

Date

Author Changes Made Reason for Change New 

Version #

1.0 8/5/05 M. Cooprider Minor edits Preparation for formal 

peer review

1.01

1.01 3/8/06 R. Carson Minor edits, updates to text 

and tables

Addressing peer 

reviewer comments

1.02

1.02 8/1/06 R. Carson Minor edits, updates to 

reference documents, 

inclusion of USGS 

continuous monitoring 

equipment guidelines

Availability of USGS 

reports and WRD 

guidance

1.03

Only changes in this SOP will be logged. ―Version numbers increase incrementally by 

hundredths (e.g. version 1.01, version 1.02 ...etc) for minor changes. Major revisions should be 

designated with the next whole number (e.g., version 2.0, 3.0, 4.0 ...). Record the previous 

version number, date of revision, author of the revision, identify paragraphs and pages where 

changes are made, and the reason for making the changes along with the new version number‖ 

(Peitz et al, 2002).

3.2 Acknowledgements

Several other Standard Operating Procedures and technical guidance were consulting while 

writing this SOP. The overarching guidance is from the USGS National Field Manual. In 

addition, Procedures for Collection of Required Field Parameters, Version 1.0, Standard 

Operating Procedure #5 (O’Ney, 2005), the Crissy Field Restoration Monitoring Program 

Quality Assurance Project Plan (Ward, 2004), the Quality Assurance Management Plan for the 

State of California's Surface Water Ambient Monitoring Program ("SWAMP") (Puckett, 2002), 

and the Guidelines and Standard Procedures for Continuous Water-Quality Monitors: Station 

Operation, Record Computation, and Data Reporting.(Wagner et. al., 2006)were also consulted 

for guidance on specific parameters, instruments, or methods. Finally, equipment log sheets and 

the equipment technical support guide were compiled by Amelia Ryan. Much appreciation is 

extended to the individuals involved in the production of these documents. 

3.3 Scope and Application 

3.3.1 Introduction

Field measurements should represent the natural condition of the surface water at the time of 

sampling. Equipment calibration and maintenance will help ensure that field measurements 

reflect the actual site conditions as closely as possible. Keeping routine records of equipment 

calibrations, maintenance, and repair is an integral part of QA/QC efforts in the water quality 
 201

monitoring program. In addition knowledge of expected stream conditions is necessary in order 

to determine whether field measurements are accurate or equipment is out of calibration.

This SOP will follow guidelines provided by equipment manufactures (e.g., Oakton, YSI, Inc., 

Marsh-McBirney) for equipment operation and maintenance as well as calibration guidelines 

outlined in the USGS National Field Manual. This includes calibration methods and frequency, 

equipment cleaning, changing pH electrodes, D.O. membranes, etc. Procedures for dealing with 

deficient equipment are also discussed and include preventative maintenance procedures and 

schedules to minimize downtime of sampling and measurement equipment. Information on spare 

parts, batteries and contingency plans for equipment back-up is also provided. 

To minimize or avoid downtime of measurement instruments, all field sampling and laboratory 

equipment will be maintained in good working order. Also, spare equipment or common spare 

parts (e.g., batteries, D.O. membranes, and pH electrodes) will be available so that repairs or 

replacement can be made as quickly as possible and measurements will not be lost. All field 

equipment having manufacturer-recommended schedules of maintenance will receive preventive 

maintenance according to that schedule (see Table 3.1). Other equipment used only occasionally 

will be inspected at least monthly. After use in the field, all equipment will be re-checked for 

needed maintenance.

An instrument or device used in obtaining an environmental measurement must be calibrated by 

the measurement of a standard. Every instrument or device has a specialized procedure for 

calibration and a special type of standard used to verify calibration. See instrument manuals for 

further details. A log book will be kept to record dates of calibration and any equipment errors 

or failures, battery changes, changes of calibration solutions, and repair notes. The log book will 

also contain calibration methods, this schedule of inspections and calibrations, and a list of 

needed supplies and equipment.

3.4 Equipment Calibration, Inspection, and Maintenance 

Overview of Calibration Tasks:

 Field instruments calibration and maintenance should be logged in the equipment binder. 

Include: the date of calibration, any change of calibration solutions, changed batteries, D.O. 

membranes, pH electrodes, date and description of repairs conducted by the manufacturer.

 The log book should be reviewed before leaving for the field.

 Each instrument (meters and sensors) should be calibrated if appropriate, then error-checked 

against calibration acceptance criteria before leaving for the field. 

 Measurement technique should be practiced if the instrument is new to the operator.

 Backup instruments should be readily available and in good working condition.
 202

Table 0.1 Calibration schedule (modified from O’Ney, 2005).

Parameter Calibration Frequency Acceptance 

Criteria

Corrective Actions

Temperature 

Liquid-in-glass 

thermometer:

Calibration-check every 3 to 6 

months, using a 2-point 

calibration-check, and annually, 

using a 3-point calibration-check

10% of the readings taken each day 

must be duplicated, or a minimum 

of 1 reading if fewer than 10 

samples are read.

±1.0 oC Re-test with a different thermometer; 

repeat measurement

Temperature 

Thermistor 

thermometer:

Every 3 to 4 months, check 

calibration, annually, using a 5-

point calibration check

Same as 

above

Re-test with a different thermometer; 

repeat measurement

Specific 

Conductance

Prior to field mobilization, at the 

field site, and calibration check at 

day’s end;

10% of the readings taken each day 

must be duplicated or a minimum 

of 1 reading if fewer than 10 

samples are read.

±5% Re-test; check low battery indicator; 

use a different meter; use different 

standards; repeat measurement

Dissolved 

oxygen

Prior to field mobilization, at the 

field site, and calibration check at 

day’s end

±10% Re-enter altitude; re-test; check low 

battery indicator; check membrane 

for wrinkles, tears or air bubbles; 

replace membrane; use a different 

meter; repeat measurement

Eureka Manta 

® multiprobe 

datalogger

Beginning and end of each 

deployment

See manual Follow manual suggestions for 

calibrating or calibration-checks of 

each parameter probe. 

pH meter Prior to field mobilization (three 

point calibration using buffer 

solutions (pH 4,7, and 10)) 

At the field site, and calibration 

check at day’s end (one point 

calibration) 

10% of all reading taken each day 

must be duplicated or a minimum 

of 1 reading if fewer than 10 

samples are read. 

±0.2 pH 

unit;

±0.2 pH unit

RPD ±0.1 

pH unit

Re-test; check low battery indicator; 

use different standards; repeat 

measurement

Notes on Table 3.1

-All instruments should be visually inspected before use

-Check batteries before use

-Rinse all equipment after use

-Insure that pH electrodes and D.O. membrane remain moist.

3.4.1 Multiparameter instrument (dissolved oxygen and conductivity)

Network staff should consult the manufacturers' instruction manual for detailed calibration 

procedures for multiprobe instruments (Appendix A). All calibration and maintenance activities 

must be recorded in a Calibration Logbook (see Appendix D). The minimum calibration 

schedule and calibration acceptance criteria are in Table 3.1 above. General guidelines for 

conductivity and dissolved oxygen are provided below. 
 203

D.O. (and conductivity) should be calibrated before each site; 

Clean sensors thoroughly with deionized water (DIW) before and after making a measurement 

(this is sufficient cleaning in most cases)

Rinse and clean (use tiny brush) YSI 85 with tap water. 

Remove oils or other chemical residues (salts) with detergent (soak in solution of water and 

detergent)

If these residues persist, then, a chemical (acid) recommended by YSI may be used 

Always calibrate from low to high specific conductance

Calibrate at the field site – bring conductivity standards to water sample temperature

Record the sources of calibration standards; standards should be traceable to a source such as 

NIST (National Institute of Standards and Technology or EPA certified vendors.

Never re-use standards or use expired standards

For short-term storage (days to a couple weeks): ensure that sponge in probe chamber remains 

saturated; have extra (unused) sponges available

For longer term storage (2 weeks or more): remove all sensors from the multiprobe and store 

per manufacturers instructions; store clean and dry

 Ensure that conductivity standards are clearly labeled with the expiration date. Never used an 

expired solution to calibrate

 All instruments must meet the calibration error limits stated in Table 3.1

Record all calibration and maintenance activities in the log book

The Winkler titration method is used as a back-up if the oxygen sensor fails in the field. It can 

also be used to calibrate D.O. in the laboratory. It is a good idea to practice this method in the 

laboratory before the possibility of needing to use it in the field. See SOP#5 for details about 

the technique.

On an annual basis, place all the probes in the same bucket or appropriate deep lab sink, leave 

them a few minutes to equilibrate, and then compare the readings. Usually, they will not give 

identical readings but should agree within acceptance criteria. If they do not, note the 

differences, perform troubleshooting on the sensors that do not read correctly after recalibration 

and again check against the appropriate standard(s) using error check procedures

Consult the YSI manual for details on how to calibrate conductivity and dissolved oxygen and 

how to clean the conductivity cell and dissolved oxygen sensor. If chemicals are necessary for 

D.O. probe/conductivity cell cleaning, review the chemicals’ MSDS for required handling and 

disposal. Also consult the MSDSs for conductivity standards. 

3.4.2 Thermometer/Thermistor

(From USGS National Field Manual Ch. 6.1)

Accurate determination of other field measurements depends on accurate temperature 

measurements. This is particularly important for thermistors incorporated in specific electrical 

conductance and dissolved-oxygen instruments, such as the hand-held YSI 85. These 

thermistors are used for automatic temperature compensation of the measurements being made. 
 204

Thermistors included in other field-measurement instruments must be calibration-checked 

routinely.

The thermistor in the YSI 85 multiprobe should be checked for accuracy against a NISTtraceable rated, liquid-filled thermometer by Network staff upon receipt from the manufacturer 

and at a minimum quarterly thereafter (see procedure below). The thermistors should be 

checked against a broad range of temperatures (e.g. from an ice water bath to beyond the range 

water body temperatures are expected to be encountered in the field; e.g. 45C). Conduct an 

annual 5-point calibration check.

If a temperature probe is found to not meet the temperature calibration requirements set forth in 

the Table 3.1, the entire multiprobe should be returned to the manufacturer for replacement. 

Once calibrated by the manufacturer, thermistor thermometers are one of the more accurate and 

stable sensors requiring the least maintenance. Multiparameter instruments are generally 

equipped with a thin-walled, titanium-sleeved thermistor that offers fast response and resists 

corrosion. The device is of high precision (e.g. 2252 ohms @ 25 C w/precision of 1%) and 

uses an imbedded algorithm to convert resistance to temperature. When handled according to 

manufactures specifications, and checked on a regular basis, the sensor should provide a long 

period of useful operation. Radtke et al. (1998) detail the proper calibration and documentation 

for thermometers and thermistor thermometers.

All temperature measurements should be made and reported in units of degrees Celsius (C). 

Each Network lab should be equipped with a NIST-Traceable rated liquid-filled or digital 

calibration thermometer (preferred) or a liquid-in-glass thermometer graduated at 0.1 C with a 

minimum range of –5 to + 45 C. Prior to conducting fieldwork, temperature sensors used 

should be tested against thermometers rated by the National Institute of Standards and 

Technology (NIST) as traceable for lab testing of temperature equipment. A second NISTTraceable rated liquid-filled or digital thermometer may also be appropriate for field use and 

may best serve to field check the thermistor-based measurements of the multiprobes and measure 

ambient air temperatures when at the monitoring station.

CALIBRATION EQUIPMENT

 Calibration thermometer, liquid-in-glass sensor, rated as Traceable by NIST

o Temperature range at least –5 to +45°C

o 0.1°C graduated

 Thermometer, liquid-in-glass sensor

o Temperature range –5 to +45°C

o Minimum 0.5°C graduated

o Calibrated accuracy within 1 percent of full scale or 0.5°C, whichever is less

o Calibration-checked and certified against calibration (NIST) thermometer

 Thermistor thermometer

o Calibration checked accuracy within 0.1°C to 0.2°C

o Digital readout to at least 0.1°C

o Calibration-checked and SFAN certified against calibration (NIST) thermometer

 Soap solution (1 L), nonphosphate laboratory detergent

 Deionized water (1 L), maximum conductivity of 1 mS/cm
 205

 Paper tissues, disposable, soft, and lint free (e.g., ChemWipes)

 Log book, for recording all calibrations, maintenance, and repairs

CALIBRATION PROCEDURE

The standard thermometer against which all other thermometers are calibration checked must be 

NIST-traceable rated. It must be accurate to 0.1°C. Confirm the traceability of the a NIST 

thermometer before checking field thermometers. NIST-traceable rated thermometers are not for 

field use.

Thermometers being calibration checked must meet NIST specifications to a minimum of three 

temperatures at approximately 0°, 25°, and 40°C. Thermistors must be calibration checked at 5 

points within this range. If environmental water or air temperatures will fall below 0°C or rise 

above 40°C, add additional calibration points to bracket the temperatures to be measured. Field 

checking thermometer calibration by comparing readings with another field thermometer does 

not substitute for required laboratory calibration check procedures. When measuring water 

temperature in the laboratory:

1. Submerge the bulb and liquid column of the total-immersion thermometer.

2. Keep the NIST-traceable rated thermometer and the thermistor sensor submerged in the 

container throughout calibration.

3. Read the NIST-traceable rated thermometer and record the thermistor readings 

throughout warming and cooling periods.

4. Check the meter batteries periodically for proper voltage.

5. Record the calibration data in the instrument log book for each thermistor thermometer, 

noting if a sensor has been replaced.

6. Tag acceptable thermometers as ―SFAN certified‖ with calibration check date and 

certifier’s initials.

The following procedure will be used to check the calibration at 0°C:

1. Freeze several ice cube trays filled with deionized water.

2. Fill a 1,000-mL plastic beaker or Dewar flask three-fourths full of crushed, deionized ice. 

Add chilled, deionized water to the beaker. Place the beaker of ice/water mixture in a 

larger, insulated container or Dewar flask. Place the NIST-traceable thermometer into the 

ice/water mixture and make sure that the temperature is uniform at 0°C by stirring and 

checking at several locations.

3. Pre-cool the test thermometer sensor to 0°C by immersing it in a separate ice/water bath.

4. Add the test thermometer sensor(s) to the ice/water mixture. Position the sensor(s) so that 

they are properly immersed and so that the scales can be read. Periodically stir the 

ice/water mixture and allow at least 2 minutes for the thermometer readings to stabilize.

5. When the readings stabilize, compare the temperature of one test thermometer at a time 

with that of the NIST-traceable thermometer. Without removing the temperature 

sensor(s) from the test bath, read the test thermometer(s) to the nearest graduation (0.1 to 

0.5°C) and the NIST-traceable thermometer to the nearest 0.1°C.

 Take three readings for each thermometer within a 5-minute span.

 Calculate the mean of the three temperature readings for each thermometer and 

compare its mean value with the NIST thermometer.
 206

 If the test liquid-filled thermometer is found to be within ±1 percent of full scale 

or ±0.5°C of the NIST-traceable thermometer, whichever is less, set it aside for 

calibration checks at higher temperatures.

 If the test thermistor is found to be within ±0.2°C of the NIST thermometer, set it 

aside for calibration checks at higher temperatures.

6. For ―room temperature‖ calibration (about 25°C), place a Dewar flask or container filled 

with about 1 gallon of water in a box filled with packing insulation. (A partially filled 

insulated ice chest can be used for multiparameter instruments.) Place the calibration 

container in an area of the room where the temperature is fairly constant (areas away 

from drafts, vents, windows, and harsh lights).

7. Properly immerse the NIST-traceable rated and test thermometer sensor(s) in the water. 

Cover the container and allow the water bath and thermometers to equilibrate. Stir the 

water and check every couple of hours for temperature uniformity using the NIST 

thermometer—it may be necessary to let the bath equilibrate overnight.

8. Compare one test thermometer at a time with the NIST- thermometer. Calibrate as 

described in step 5 above.

 For greater than 25°C temperature calibration, place a beaker (1,000 mL or more) of 

warm water (about 40°C) on a magnetic stirrer plate and repeat procedure as 

described in step 5 above.

 Tag acceptable thermometers as ―Certified‖ with calibration check date and certifier’s 

initials.

 Record procedure in calibration logbook.

Corrections can be applied to measurements made with a thermistor instrument system if 

necessary, using a calibration curve or table plotted in the log book. Thermometers found to be 

out of calibration by more than 0.2°C must be recalibrated per manufacturer’s instructions or 

returned to the manufacturer for proper calibration and (or) repairs. 

Thermometers can easily become damaged or out of calibration. Take care to:

 Keep thermometers clean (follow manufacturer’s recommendations).

 Carry thermometers in protective cases; thermometers and cases must be free of sand and 

debris.

 Store liquid-filled thermometers in a bulb-down position and in a cool place away from 

direct sunlight.

 As an additional precaution on field trips, carry extra calibrated thermometers as spares, 

and a supply of batteries for instrument systems.

 Never carry a mercury-filled thermometer in the field.

3.4.3 pH Meter

(Adapted from the Surface Water Ambient Monitoring Program Quality Assurance Management 

Plan (Puckett, 2002) and USGS National Field Manual Ch. 6.4)

Because a large variety of pH meters and electrodes are available on the market, it is very 

important to be thoroughly familiar with the instruction manual provided by the manufacturer. 
 207

Electrodes must be clean and properly operating to produce accurate results. The liquid junction 

also must be free flowing, and the electrolyte solution in the electrode must be at the proper 

level. Because of the variety of electrodes available, follow the cleaning and storing instructions 

provided by the manufacturer. In this case, SFAN will be using the Oakton pH Testr 30. It is a 

waterproof meter requiring four A76 batteries. See the appendix for manufacturer recommended 

calibration and maintenance. 

When single function pH meters are used, pH is calibrated for each day of use, and at each 

sampling site. Additional calibrations may be necessary if questions arise regarding a 

particularly measurement. The pH meter should be calibrated with a buffer of pH 7.0 and either 

4.0 for naturally acidic waters or pH 10.0 for alkaline waters. The pH of SFAN waters is 

generally between 6.5 and 8.5. The pH buffers contain high concentrations of phosphate. Care 

must be taken during calibration to avoid leaving traces of buffer on equipment or at the work 

place that could contaminate water samples. Buffer solutions prepared in the field offices from 

reagent powder or concentrate are labeled with date of preparation and replaced after one month 

(Puckett, 2002). 

 Ensure that the pH electrode remains moist at all times. 

 Rinse and clean (use tiny brush) pH meter with tap water

 Never wipe the pH electrode membrane with anything or store it dry (check manufacturer's 

instructions)

 Record any operation difficulties, batteries changed, or pH electrodes changed in the 

equipment log book

 Check MSDS for pH buffer solutions

 Always cap the buffer solutions to prevent evaporation and contamination from atmospheric 

carbon dioxide

 Take care not to dilute a buffer (e.g., with water dripping from a sensor) or contaminate with 

another buffer

 Never pour used buffer into a stock solution bottle or allow anything else to enter the stock 

bottle

 Discard buffers on their expiration date; copy the expiration data onto any container into which 

the buffer is 

transferred

 Calibrate before heading to the field.

 Calibrate as close to the temperature of the water body as possible*

* This is important for older pH tester technology. The Oakton pH Testr 30 that is being used by 

SFAN water quality personnel is equipped with a microprocessor that performs autocalibration 

operations that automatically compensate for buffer temperatures by deriving the Nernst slope

Buffer solutions in the calibration kit that are taken from the stock bottle should be replaces by 

new solution from the stock bottle at least weekly. Be sure to note in the equipment maintenance 

log that the calibration solutions were changed.
 208

The table in the Appendix B demonstrates how pH calibration standards differ based on 

temperature. A bucket can be used to place the calibration standards (capped) in while they 

equilibrate with the sample water temperature (approximately 15 minutes).

3.4.4 Post-Calibration Checks

From Procedures for Collection of Required Parameters, SOP#5 by O’Ney (2005)

Post-calibration checks must be performed after each use of the instrument and before any 

instrument maintenance. The sooner this procedure is performed, the more representative the 

results will be for assessing performance during the preceding field measurements. Calibration 

and post-calibration should be no more than 24 hours apart. Take the same care used in 

performing the initial calibration by rinsing the sensors and waiting for functions to stabilize. 

After making measurements at the last station, fill the sampling cup with ambient water (not 

deionized or tap water). Repeat the initial calibration procedures performed before the sampling 

trip. Record post-calibration values in a Calibration Logbook (generally on the same page with 

the initial calibration for that sampling trip).

Do not adjust the instrument (using calibration controls) during the post-calibration check. 

The purpose of the post-calibration is to determine if the instrument has held calibration during 

the day of sampling. Compare the post-calibration values to the expected values for the 

standards, so the field measurements for the day can be reported with confidence. The difference 

between the post-calibration value and expected standard value can be used to indicate both 

calibration precision and instrument performance.

Post-Calibration Check Error Limits

Calibrations made prior to field mobililzation, or at the site, and post-calibration should take 

place no more than 24-hours apart. If post-calibration values (Table 3.2) fall outside the error 

limits for DO, pH, and specific conductance, data collected does not meet quality assurance 

(QA) and should not be reported. If post calibration measurements do not consistently fall within 

the error limits after in-house trouble shooting, the instrument should be returned to the 

manufacturer for maintenance. 

Table 0.2. Post-Calibration Check Error Limits for water-quality equipment.

The more stringent acceptance criteria from the USGS in the third column above, and is 

presented as a goal for NPS networks. The less stringent criteria presented in the second column 

is minimum recommendations by WRD and may be adjusted in the future. See WRD online 

PARAMETER Error Limits Acceptance Criteria USGS Error-Check Acceptance 

Criteria (multiparameter monitoring 

equip.) (Wagner, et al. 2006)

Temperature ± 1 °C, annual calibration check ± 0.2 °C

Specific Conductance ± 5% The larger of ± 5uS/cm or ± 3%

pH ± 0.5 standard units ± 0.2 standard units

Dissolved Oxygen ± 0.5 mg/L, ± 6% saturation ± 0.3 mg/L, ± 3% saturation
 209

guidance for the latest recommendations. SFAN will strive to achieve the USGS recommended 

values, but will at least attain WRD suggested values, and note when USGS values were not 

attained.

3.4.5 Continuous Water-Quality Monitoring Equipment

(e.g. Eureka Manta® multiprobe datalogger)

The USGS publication ―Guidelines and standard procedures for continuous water-quality 

monitors‖ by Wagner et al (2006) should be used as a guide for the operation, calibration, data 

processing and reporting of continuous water-quality monitoring equipment. 

Procedures for the operation, calibration, data correction and reporting

Procedures for calibration and cleaning of the Eureka Manta® multiprobe are outlined in 

Appendix C. Calibration steps are divided in four parts: pre-field calibration, post field 

calibration, cleaning, and downloading. The manual can be found at: 

http://www.eurekaenvironmental.commanta/documents/Manta.pdf

For instruments used in continuous monitoring mode, post-calibrations should follow the USGS 

protocols separating corrections due to biofouling from instrument drift. The USGS postcalibration error check acceptance criteria for multiparameter instruments can be seen in the third 

column of Table 3.2 (above).

Some of the QA/QC measures for conductivity and dissolved oxygen, temperature, and pH are 

embedded in the sections above. The following are QA/QC measures are from the Crissy Field 

Restoration Monitoring Program Quality Assurance Project Plan (Ward, 2004):

Never accept any calibration for which you have received a warning message. Determine and 

correct the cause of the problem and re-calibrate.

 Don’t use expired standards and use fresh solutions for calibration. Probes may be rinsed with 

expired solutions, but NOT calibrated.

 Replace the D.O. membrane before each deployment, allowing the probe to sit at least 6 hours 

after replacement before pre-field calibration error checking and deployment. Note that new 

technology present in digital luminescent DO sensors do not use a Clark cell membrane and 

largely make these steps unnecessary. 

3.4.6 Equipment and Supplies: Maintenance and Storage

The following is a guide for maintaining calibration standards and other solutions and supplies

(Table 3.3). Although some samples have an extended shelf life, they should be replaced when 

they exceed the manufacturers’ expiration date.
 210

Table 0.3 Storage time for calibration standards.

Item Shelf Life

Conductivity standards 1.5 years

pH buffer solution in small bottle 1 month in small container

pH buffer solution in stock container Expiration data stamped on bottle

pH buffer powder Indefinite

D.O. electrolyte crystals or solution indefinite

The following information applies to all water quality equipment and instruments. 

Long Term Storage

Field instruments are often stored for indefinite periods. For example, back-up instruments are 

used during repair of the primary instrument. The instrument cannot be kept in a perpetual state 

of readiness without regular maintenance.

Whenever equipment is to be stored for extended periods of time:

- Thoroughly clean the sensors.

- Remove installed batteries (AA batteries, C batteries, polarizing batteries).

- Fill the storage cap about 1/3 full of tap water (if the multiprobe may be exposed to freezing 

temperatures a solution of 1⁄2 tap water and 1⁄2 methanol should be used).

- Store away from direct sunlight. ----The instrument can be reliably reactivated for field use

 with minimum of effort the day before field use.

(From the State Water Resources Control Board Surface Water Ambient Monitoring Program (SWAMP) Part of Appendix E Quality Assurance 

Management Plan)

3.5 Field Preparations

The network Water Quality Specialist (Hydrologist/Physical Scientist) will determine which lab 

will be used for the sampling event based on executed purchase orders or Blanket Purchase 

Authority (BPA). Analytical laboratories often have different constraints on the number of 

samples they can process and the days and times that they can accept samples. The laboratory 

should be notified of the sampling event as soon as possible. Information to be provided 

includes the number of sites and times/days that samples will be collected, what parameters will 

be analyzed, and any courier services needed. This gives ample time for the laboratory to 

provide sample bottles and other supplies (coolers, blue ice, labels, and COC forms). Chain of 

Custody (COC) forms should be completed and faxed to the chosen laboratory at least one day 

prior to sampling or as required by the laboratory. Call the lab in advance (1-2 weeks or more) to 

schedule a sample pick-up or drop-off and notify the lab of the # of samples and analyses 

required. In addition, call the lab the morning of the sampling to verify.

A number of steps should be taken at the office to insure that all of the equipment is in the 

vehicle. Be sure to use the following checklist for equipment inventory (Table 3.4).
 211

Table 0.4 Field Equipment Checklist.

Check Item

 Equipment for Collecting Required Field Parameters

Calculator (for calculating centroid of flow)

Bacteria bottles: Sterile 100 mL bottles (provided by lab)

Nutrient bottles: Sterile sample bottles, (provided by lab)

Sediment bottles: 500mL or 1-liter sample bottles (CLEAN!)

Sharpie, pen, pencil

Clipboard

Field collection data sheets (on Rite in Rain paper if necessary)

Labels from laboratory

Labels for sediment bottles (and nutrient bottles if necessary)

Chain of Custody

Disposable rubber gloves

Paper towels or rag for drying bottles before labeling

YSI 85 or (YSI 30 and YSI 55) multiparameter probes

Extra AA batteries (6) for YSI meter

pH meter*

Extra pH meter or pH tape at the very least

pH meter batteries (four A76 watch batteries)

1-3 Large coolers

1 small cooler

Blue ice

Flow meter and extra D batteries

Top-setting wading rod

50m measuring tape

Chaining pins (or similar)

Waders/rubber boots

Radio or cell phone (depending on location)

Keys and/or combinations for gate locks, dataloggers

Water jugs with tap water for rinsing boots

Water jug with distilled water for rinsing pH electrodes and YSI probe

All maintenance log books and calibration standards for all field equipment

Digital camera with optional waterproof case

GPS unit

Hand sanitizer and/or antibacterial soap

All maintenance parts and calibration standards for field equipment

NIST calibrated Centigrade thermometer for air temp

NIST calibrated Centigrade thermometer for back-up

Winkler titration kit for D.O. back-up

Stopwatch and headset for discharge measurements (for pygmy or price AA- flow meters)

Personal flotation device

Traffic safety vest, cones, signs, warning lights

First aid kit

Highway emergency kit

Tool kit

Tape (electrical, fiber, other)

Fire extinguisher

Flashlight with extra batteries

Weather report

Field trip itinerary

Work gloves

Drinking water

Copy of safety SOP

Maps

Deionized water 
 212

3.6 QA/QC Procedures for Equipment 

Table 0.5 QA Protocols.

Measurement Parameter QA Protocol

*Total Kjeldahl Nitrogen Duplicates 10% of samples, lab matrix spike

*Nitrate as N Duplicates 10% of samples, lab matrix spike, Field Blank, Trip Blank

*Nitrite as N Duplicates 10% of samples, lab matrix spike, Field Blank, Trip Blank

*Nitrate + Nitrite Duplicates 10% of samples, lab matrix spike, Field Blank, Trip Blank

*Ammonia Duplicates 10% of samples, lab matrix spike, Field Blank, Trip Blank

*Fecal coliforms Lab and field duplicates, Field Blank, Trip Blank

*Total coliforms Lab and field duplicates , Field Blank, Trip Blank

*Total Suspended Solids Lab and field duplicates, Field Blank, Trip Blank

Turbidity Equipment blanks; duplicates 10% of samples

*Also refer to laboratory QA manuals for lab parameters

The primary QA/QC measure conducted in the lab before commencing field work are the 

―equipment blanks‖. These tests are used to ensure that equipment used during sampling does 

not contaminate samples. Equipment blanks are run when new equipment , equipment that has 

been cleaned after use at a contaminated site, or equipment that is not dedicated for surfact water 

sampling, is used. Consult the Quality Assurance Project Plan (SOP #4) for additional details.

Check precision in the field every tenth sample by repeating an in situ measurement three 

separate times or by repeating the measurements on three separate aliquots from the same 

composited sample volume (e.g. from a churn splitter). Note that these should all be recorded as 

the same sample and only one value included in the data analysis.

Document ability to make accurate measurements by measuring known reference solutions (e.g. 

zero DO solution).
 213

3.7 References 

Eureka Environmental Engineering. 2006. Manta Water Quality Multiprobe Startup Guide. 

June 8, 2006 revision. Austin, Texas, USA.

Hydrolab Corporation. 1998. DataSonde 4 and Minisonde Water Quality Multiprobes User’s 

Manual. Revision E. Austin, Texas, USA.

National Park Service. 2002. Recommendations for Core Water Quality Monitoring Parameters 

and Other Key Elements of the NPS Vital Signs Program Water Quality Monitoring 

Component. Freshwater Workgroup Subcommittee. Fort Collins, CO. 

O’Ney, SE. 2005. Procedures for Collection of Required Field Parameters, Version 1.0, Standard 

Operating Procedure #5. In Regulatory Water Quality Monitoring Protocol, Version 1.0, 

Appendix E-SOPs, National Park Service, Greater Yellowstone Network. Bozeman, MT. 

37 pp. plus appendices. 

Peck, D.V., J.M. Lazorchak, and D.J. Klemm. 2001. Environmental monitoring and assessment 

program-surface waters: Western pilot study field operations manual for wadeable 

streams. U.S. Environmental Protection Agency, Washington, D.C. 

Peitz, D.G., S. G. Fancy, L. P. Thomas, and B. Witcher. 2002. Bird monitoring protocol for 

Agate Fossil Beds National Monument, Nebraska and Tallgrass Prairie National 

Preserve, Kansas. Prairie Cluster prototype monitoring program. Version 1.00, 

September 6, 2002.

Penoyer, P. 2003. Vital Signs Long-Term Aquatic Monitoring Projects. Part C – Draft Guidance 

on WRD Required Parameter Measurements, General Monitoring Methods, and Some 

Design Considerations in Preparation of a Detailed Study Plan. U.S. Department of 

Interior. National Park Service, Water Resources Division. 

Puckett, M. 2002. Quality Assurance Management Plan for the State of California's Surface 

Water Ambient Monitoring Program ("SWAMP"). California Department of Fish and 

Game, Monterey, CA. Prepared for the State Water Resources Control Board, 

Sacramento, CA. 145 pages plus Appendices.

Radtke, D. M., J. K. Kurlin, and F. D. Wilde. 1998. Field measurements: U.S.Geological Survey 

Techniques of Water-Resources Investigations, book 9, Chap. A6, accessed 5 November 

2004 at http://pubs.water.usgs.gov/twri9A6/

Wagner, R.J., Boulger, R.W., Jr., Oblinger, C.J., and Smith, B.A., 2006, Guidelines and standard 

procedures for continuous water-quality monitors—Station operation, record 

computation, and data reporting: U.S. Geological Survey Techniques and Methods 1-D3, 

51p. + 8 attachments; accessed April 10, 2006, at http://pubs.water.usgs.gov/tm1d3

Ward, K. 2004. Water Quality Standard Operating Procedures. In Draft Crissy Field Restoration 

Monitoring Program Quality Assurance Project Plan, Appendix 1. Golden Gate National 

Recreation Area, U.S. Department of Interior, National Park Service. San Francisco, CA. 

YSI Incorporated. 1998. YSI Model 85 Handheld Oxygen, Conductivity, Salinity and 

Temperature System Operations Manual. Revision D. Yellow Springs, Ohio, USA. 
214

SOP #3 Appendix A. YSI Multiparameter Probe Manual 

(hard copy only)
215
216

SOP #3 Appendix B. Oakton pH Meter Manual 

(hard copy only) 
 217
218

SOP #3 Appendix C. Eureka Environmental Engineering –

Manta multiprobe User’s Manual

(hard copy only)

USGS Continuous WQ Monitor Field Form

USGS Calibration Log Sheet

Eureka Manta Calibration Instructions

From Wagner et al. 2006
 219

February 2006 Station No. _____ _ 

Station No. 

Monitor n~ted By 

U.S. GEOLOGICAL SURVEY 

CONTINUOUS WATER-QUALITY MONITOR FIELD FORM 

Station Name 

Date Walch Time Time Datum 

Gage HI (Ris!ng, FaDing, Steady, Peak) Channel Conditions 

Monitor Make/Model Monnor Serial No. 

Field Meter Make/Model Field Meter Serial No. 

Weather CokJ COOl warm 110~ !Ufn Mill S.:.~ Sno• HI.ZI'IIO Dty CIOUI!y ~ CIOU<I'y OWrt.UI Cit¥ 'Mrttly Gu~y ert-.zt em 

Con111ents: 

MONITOR FOULING CHECKS 

Before Cleaning After Cleaning 

Tme Time 

---

Recorded/ FJeld Recorded/ Field 

Parameter Uve Value W..eter Uve Value Meter 

Temp (•C) 

pH (units) 

DO(mg/L) 

SC (qSian) 

Turbidity ( FNU FNMU F8U ) 

Method code ---

Other 

CALIBRATION DRIFT CHECKS 

TEMPERATURE C;alibr;ation 0\eclc: Rewi~t on 

Calibration Cnteria: ± 1 percent or t 0.5 •c for Time --- Time 

liquid-f lied thermometers; ± 0-2 •c for thermisters ---

Coll'W'n!ms: 

~PSQFI~ Q!!Q!.l !A~Ii Calibration Check Recalibration 

C31ibration Ctrt«i.a: ;tw gre:3:.er of 5 \I.Sfcm 01 ~of r.,. --- Time --- meas....-ed v.1.'ue 

STDVALUE STD STD EXP. STD sc Err« STD sc Error LOT NO. TYPE DATE TEMP READING % TEMP READING .~o 

KCI; NaCI 

Cell Reading in air= 

range = (should be zero) 

Collll"'lents: 
 220

Slabon No.-----------

ISSOLVEO OXYGEN calibration Check Recalibration 

C-l bt~tion Criteri:.: 10 3M~ Time nme 

DO DO 

BARD TABLE SALINITY Reading BARD TABLE SAUNITV Reading 

TEMP PRES R=G CORR. DO ERROR in zero De TEMP PRES READING CORR. DO ERROR in zero 

'C mmHa FACTOR READING 'Mo sol'n 'C mmHa mall FACTOR READING % DOsol'n 

ALI'I!TY: SALINITY 

CORRECTION 

pO CHARGE: p OGAIN: U.l!l! B~!!r Calibr~ld: 

APPLIED? YN 

COI.'MENTS: 

.llli calibration Check Recalibration 

= ration cm.rio: t 0.2 pH urils Time - -- Time --- pH THE(). BUFFER LOT NO. BUFFER TEMP pH ERROR TEMP pH ERROR SLOPE MILU· 

BUFFER RETlCAL EXP DATE READ· % READ- ~ VOLTS 

pH lNG lNG 

FROM 

TABLE 

pH7 

pH_ 

pH_ 

Corrmo<lto: 

URBIDITY Calibration Check Recalibration 

Calibrat1on Critena: ± 0.5 Tur1:>icl1y Urrls or! 5% Time Time 

Lot no. or CONC TEMP ERROR TEMP ERROR 

Date ProDarod 'C READING % 'C READING 'II. 

5tock Turbidity 

Standard 

o 

Standard {DIW) 

Standard 1 

Standard 2 

Standard 3 

ufbidity Sensor Limit : Commonts: 

FINAL READINGS Time 

Parameter Reoordedl Field Meter Parameter Recorded! Field Met.,. 

Uve Value Uve Value 

Temp ('C) Turbid ity ( FNU ~o U FSU ) 

1>H (units) 

METHODCOOE ---

OO(mgll) Other 

SC ('IS/em) 

Monitor fonn wr. 3.0 

1-2 
 221

Station No. _________ _ 

MAINTENANCE RECORD FOR CONTINUOUS MONITOR 

Coi'MCSon factors applied to fie'd IT'I!' ~r readings? YES NO 

S..rte<y c:honge<l? YES NO Vo7tige 11Cli1s 

SEnsors cleaned'? YES NO Type of fouling 

Calibration check: WT SCJ*i 00 TURB Reeal bta d: wr SC pH DO TIJRB 

s.m<>rc:honge<l? sc YES NO Senoo< IO 

pH YES NO Senoo< IO 

DO YES NO 5!1150< 10 

TU'bicfty YES NO Senoo< IO 

Sondeetla"'lecl? YES NO NE'Yo' Sonde No. Old Sonde No. 

DO ~-rant cllongocl? YES NO Oaio Ctlangod: M~miW arlcrlf"id tO relax ---hrs 

Comi'T'Ie'ms 

Reference (field) 

Meter(s) Make/Model Serial No. Corr. Factor Applied? 

Multi.Meter None Yes No 

Temperature None Yes No 

Conductivity None Yes No 

pH None Yes No 

Dissolved Oxygen None Yes No 

Turl>iditv (1) None Yes No 

Turbidity (2) None Yes No 

[other None Yes No 

COMMENTSIOBSERVATIONS: 

Turbidity method codes are available at: http:llwater.usgs.govlowqffieldManuaiiCtwpter6/6.7 _contents.htlnl 

Pt.4onitot form ver. 3.0 

1-4 
222

Modified from Wagner et al (2006)

Standard protocol for the operation and maintenance of a continuous water-quality 

monitor

1. Conduct site inspection

 Record monitor readings, time and monitor conditions

 With an independent field meter, observe and record readings and time near 

the continuous sensor(s)

2. Remove sonde from the monitoring location

3. Clean Sensors

4. Return sonde to the monitoring location

 Record monitor readings and time

 Using an independent field meter, observe and record readings near the 

sensor(s)

5. Remove sonde, rinse thoroughly, and check calibration

 Record calibration-check values

 Recalibrate if necessary (i.e. values are outside the calibration criteria)

6. Return sonde to monitoring location

 Record monitor readings and time

 Using an independent field meter, observe and record readings near the sensor

From Eureka Environmental Engineering Manta Water Quality Multiprobe Startup Guide

Eureka Manta instructions for cleaning, calibration and deployment

Cleaning: (see table on page 12 and 13 of Manta startup guide for specific instructions by 

probe type)

In general, wash housing and probe sensors with warm soapy water and a soft brush, use a soft 

lint-free cloth to wipe membranes dry.

General Calibration Procedures

1) Clean and perform routine maintenance if necessary.

2) Rinse sensors thoroughly (more than once may be required) with DI (deionized) water 

between calibrations. Shake the transmitter vigorously to remove traces of old 

calibration solutions – repeat if necessary.

3) Select a calibration standard whose value is near to your representative field sample. For 

example, if your pH is generally alkaline, choose pH 7 and pH 10. 

4) Rinse the sensors twice with a small quantity of your calibration standard. Discard and 

do not reuse calibration standard.

5) Secure your Manta with the sensors pointing up, and fill the calibration cup as required to 

perform the calibration.

6) For best results, use fresh calibration solutions, and discard once they have been used.
223

Temperature

This sensor is factory calibrated and does not require calibration

Clark Cell Dissolved Oxygen (% Saturation Method)

If you have replaced the membrane, it is best to wait 24 hours before calibration.

1) Fill your calibration cup up to the level of the DO membrane with a tap water, DI water, 

your conductivity standard, or a pH standard. Contrary to other manufacturers, Eureka 

allows you to use high salinity standards during an air calibration. 

2) With a paper towel, make certain the membrane is dry and free of water droplets.

3) Place the black rubber cal cup cover upside down over the calibration cup.

4) Wait approximately two minutes for the air to become fully saturated and the temperature 

to equilibrate. Make sure your circulator is turned off. Follow the calibration procedures 

on your Amphibian or on the desktop software.

5) DO % saturation also calibrates DO mg/L.

6) If you used pH buffer or Conductivity standard, add more to your cal cup and proceed to 

that calibration.

pH Calibration

pH is a two or three point calibration. Choose your calibration buffers to bracket the likely pH of 

your sample waters.

1) Rinse with a pH buffer, and then fill the calibration cup with enough buffer to cover both 

the pH glass bulb and reference.

2) Follow the instructions on your Amphibian or PC to perform the calibration.

3) Discard the buffer, rinse with second buffer. Add second buffer to cover pH glass and 

reference. Calibrate with second buffer. 

4) Repeat steps 2 & 3 if you are performing a three point calibration.

Note – the order of pH buffers is not important, and using pH 7 buffer is not required.

Conductivity Calibration

This procedure calibrates specific conductance and salinity.

1) Fill the calibration cup to cover the conductivity sensor. Tap gently on the cup to make 

sure there aren’t bubbles trapped in the conductivity sensor.

2) Follow the instructions on the Amphibian or Manta PC software to calibrate the sensors.
224

Depth Calibration

Depth is a one point calibration, which should be done in air to set the zero point.

1) Make sure there is no water in contact with the depth sensor. Shake it a bit if necessary.

2) Follow the instructions on the Amphibian or Manta PC software to calibrate the sensors.

The Manta Internal Battery Pack

The Manta with Internal Battery Pack includes 8 C-cell batteries inside a Manta 3 inch housing. 

Since every Manta has onboard memory, the batteries supply the power need for turning a Manta 

into a datalogger. There are basically four parts to Manta logging:

 Turning it on or off

 Changing the batteries

 Downloading data

 Changing the logging interval

Turning the Manta Logger ON or OFF

Loosen the stainless steel thumb screw on the 

top of the Manta. Rotate the on-off switch, 

and insert the thumb screw in the hole on the 

left of the picture.

You will notice that the lights will begin 

flashing on the Manta. It is waking up, 

looking at the time, and determining when to 

log a reading. 

The Manta ships with a default interval of two 

minute warm-up and 30 minute interval. 

Therefore, if you turn it on at 17 minutes past 

the hour, it will wake up, and determine that it 

needs to go to sleep until 28 after the hour. It 

will then wakeup at 28 past, warm-up for two 

minutes, and log a reading. It will then enter 

sleep mode for 28 minutes.

Changing the Batteries

Turn the large knob on top of the Manta counter-clockwise until the entire 

top has worked its way off.
225

Top Cap

Remove the batteries. They will slide out. 

Replace batteries as indicated by the + / -

indication stickers. It is recommended to use 

the same brand of batteries. Make sure each 

column is pointed in the right direction!

Downloading Data

1) Clean all contaminants from the Manta before downloading data – this helps protect the 

seals and connectors.

2) Remove the data-port knob on top by turning counter-clockwise until the lid is removed.

3) Plug the download cable into the download jack on the Manta and to your USB port on 

the computer

4) Launch the Manta Manager Software. Data will begin transfer automatically.

5) When complete, you can unplug the Manta.

Calibration

Calibrating is just the same as with any Manta. However, you will want to remove the batteries 

first – otherwise they will fall out! Use the Download cable and connect it to your PC’s USB 

port. Launch the Manta Manager Software.

Changing the Logging Interval

See the Manta Manager software for a description of changing the logging interval or file-name.

attached with some moisture present (e.g., put wet sponge in calibrator cup or 

place a small amount of DI water in cup).
226

SOP #3 Appendix D. Equipment Log Sheets

Water Resources Instrument Log

Date Instrument Operator

Instrument Spot Check () Calibration (note what 

parameter calibrated 

if more than one 

possible)

In Range Out Of Comments

Range 

(Calibrate)

 pHTestr Instrument Log (indicate pH Testr2 or Testr3 and ID #)

Name Date

Buffer Changed

(specify which 

buffer/s 4,7,or10)

Batteries Changed 

(specify which 

Testr)

Electrode 

Soaked in 

Buffer ()

Electrode Changed

(specify which Testr)

YSI 85 Instrument Log

Name Date Membrane 

Change ()

Battery 

Change 

()

DO 

Calibration

Conductivity 

cell cleaning

Conductivity 

cell spot 

check 

reading

Conductivity 

calibration
227

SOP #3 Appendix E. Technical Support Information

Instrument Supplier Technical Support

Turbidimeter HACH Steps to help:

1. Call the Hach Service line : (800) 227-4224

2. Choose the technical support and service menu option.

When you speak to the service department on the phone, they will try to 

determine if you need to send the instrument in for servicing. If so, make 

sure to get a JOB NUMBER from them. Without this you will not be 

able to send the product in for service. They will also give you the name 

and contact info of a service technician who can help you.

YSI 30,55,85 YSI EquipCo (Authorized Repair Center)

1 (800) 550-5875

2100 Meridian Park Blvd

Concord, CA 94520

Or

YSI

800-897-4151

937-767-7241

Fax:937-767-1058

E-mail: environmental@ysi.com

Flo-mate 2000 

flowmeter

MarshMcBirney

Service Department:

Tel: 1 (800) 368-2723

Fax: (301) 874-2172

Email: service@marsh-mcbirney.com

pH, TDS 

Testrs

OAKTON OAKTON Instruments

P.O. Box 5136, Vernon Hills, IL 60061, USA

Tel: toll free 1-888-4OAKTON (1-888-462-5866)

Fax: (1) 847-247-2984

E-mail:info@4oakton.com

http://www.4oakton.com

(Call before 3 pm)

New Electrode Sensors: Item # WD-35624-38 $58.25

pH Solution OSH (Orchard 

Supply and 

Hardware), 

Bens, etc.

N/A

Eureka Manta Eureka 

Environmental 

Engineering

Eureka Environmental Engineering

2113 Wells Branch Parkway, Suite 4400

Austin, TX 78728

Tel: 512-302-4333

Fax: 512-251-6842

E-mail: support@eurekaenvironmental.com
228

SOP #4 Quality Assurance Project Plan (QAPP)

4.1 Revision History Log

Prev. 

Version #

Revision Date Author Changes Made Reason for 

Change

New Version 

#

1.0 February 16, 2005 Mary 

Cooprider

Table 4.10, few 

minor edits

Clarification of 

QA/QC measures

1.01

1.01 May 12, 2005 Mary 

Cooprider

Update tables and 

schedule

Preparation for 

technical peer 

review

2.0

2.0 August 3, 2005 Mary 

Cooprider

Minor edits and 

updates

Preparation for 

formal peer review

2.01

2.01 March, 2006 Rob Carson Minor edits, 

updates to text and 

tables

Addressing peer 

reviewer comments

2.02

2.02 September, 2006 Rob Carson Minor edits, 

inclusion of 

updated field forms

Availability of new 

USGS and WRD 

guidance; and 

changes to field 

forms

2.03

2.03 October 2006 Rob Carson Minor Edits to 

MQO table and 

discussion of bias 

and % difference 

(PD)

Availability of 

updated WRD 

advise based on 

EDSC guidance

2.04

4.2 Acknowledgements

The preparation of this Quality Assurance Project Plan (QAPP) was funded by the National Park 

Service Water Resources Division. This QAPP is adapted from the Quality Assurance 

Management Plan (QAMP) for the San Francisco Bay Regional Water Quality Control Boards’ 

Surface Water Ambient Monitoring Program (SWAMP) (Puckett, 2002). The content of the 

SWAMP QAMP is used frequently here. This QAPP follows the formatting and guidelines set 

forth by the California Department of Water Resources’ Guidelines for Preparing Quality 

Assurance Project Plans (California Department of Water Resources, 1998). In addition, 

Golden Gate National Recreation Area’s Crissy Field Restoration Program QAPP (Ward, 2004) 

was closely followed. Quality assurance guidelines and procedures for continuous water-quality 

monitoring equipment were taken from the most recent USGS techniques and methods paper 

(Wager,et al, 2006). In order to insure the highest level of data comparability within NPS park 

units, this QAPP mirrors the Crissy Field QAPP where applicable. 
229

4.3 List of Acronyms for SOP #4

CMS Client Matrix Spike

COC Chain of Custody

CWA Clean Water Act

DFG Department of Fish and Game

DHS Department of Health Services

DQO Data Quality Objective

DWR Department of Water Resources

ELAP Environmental Laboratory Accreditation Program

EMAP Environmental Monitoring and Assessment Program (EPA’s)

LCS Laboratory Control Spike

MDL Method Detection Limit

PQL Practical Quantitation Limit

QAMP Quality Assurance Management Plan

QAPP Quality Assurance Project

QA/QC Quality Assurance/Quality Control

RDL Reporting Detection Limit

RPD Relative Percent Difference

RSD Relative Standard Deviation

RWQCB Regional Water Quality Control Board

SFEI San Francisco Estuary Institute

SOP Standard Operating Procedure

SWAMP Surface Water Ambient Monitoring Program

SWRCB State Water Resources Control Board

TMDL Total Maximum Daily Load

UC University of California

USEPA U.S. Environmental Protection Agency

USGS U.S. Geological Survey
230

4.4 Project Management

4.4.1 Distribution List

Table 0.1 QAPP Distribution List.

Name Agency/Affiliation

Rob Carson, Water Quality Specialist San Francisco Area Network

Brannon Ketcham, Hydrologist Point Reyes National Seashore

Tamara Williams, Hydrologist Golden Gate National Recreation Area

Darren Fong, Aquatic Ecologist Golden Gate National Recreation Area

Marcus Koenen, I&M Coordinator San Francisco Area Network

Denise Louie, Chief Natural Resources Pinnacles National Monument 

4.4.2 Project/Task Organization

This plan is intended to be a long-term monitoring plan. However, tasks and budget will be 

organized in five year increments. The plan will be managed and largely implemented by 

network (SFAN) personnel with assistance from park staff and technical expertise from the NPS 

Water Resources Division (WRD) and local experts where necessary (Table 4.2). Decisions 

regarding the I&M Water Quality Program development and long-term monitoring plan have 

been and will continue to be informally made by consensus of the SFAN Aquatic Professionals 

group. The I&M Water Quality Program will remain adaptive to changing park and network 

needs. This group consists of key network staff including the water quality specialist, network 

coordinator, park hydrologists and an aquatic ecologist. Broader-based, long-term decisions are 

approved by the NPS-WRD. These include approval of WRD-funded staff workplans and 

approval of the overall monitoring plan.

Table 0.2 Project Tasks and Responsibilities.

Name Title/Responsibility

Rob Carson, Water Quality Specialist 

(SFAN)

Technical Lead, oversee collection of monitoring data 

and data management, coordinate report writing and 

protocol staff revision

Marie Denn, Aquatic Ecologist (PWR)

Darren Fong, Aquatic Ecologist (GOGA)

Brannon Ketcham, Hydrologist PORE)

Tamara Williams, Hydrologist GOGA)

Aquatic Professionals Team, technical 

Marcus Koenen, SFAN I&M 

Coordinator

Coordinate with water quality specialist reporting 

requirements, assist with peer review process

Dave Press, SFAN Data Management Lead Assist with water quality data collection and validation; 

database uploading to WRD
231

4.4.3 Problem Definition/Background

―National Park managers are directed by federal law and NPS policies and guidance to know the 

status and trends in the condition of natural resources under their stewardship to fulfill the NPS 

mission of conserving parks unimpaired‖ (Welch, 2003). The mission of the National Park 

Service is:

"...to promote and regulate the use of the Federal areas known as national parks, 

monuments, and reservations hereinafter specified by such means and measures as 

conform to the fundamental purposes of the said parks, monuments, and reservations, 

which purpose is to conserve the scenery and the natural and historic objects and the 

wild life therein and to provide for the enjoyment of the same in such manner and by such 

means as will leave them unimpaired for the enjoyment of future generations (National 

Park Service Organic Act 1916)."

―Recognizing the need to understand the condition of natural resources within the park system, a 

servicewide inventory and monitoring (I&M) program was established (NPS-75 1995; 

http://science.nature.nps.gov/im/monitor/nps75.pdf). The I&M program was given the 

responsibility to determine the nature and status of natural resources under NPS stewardship and 

to monitor changes in the condition of these resources over time. Information from inventory 

and monitoring efforts can then be incorporated into NPS planning, management, and decision 

making‖ (Welch, 2003).

In addition to the overarching NPS goal of resource stewardship, other policies and guidance are 

aimed specifically at maintaining or improving water quality. California’s Porter-Cologne Water 

Quality Control Act and the federal Clean Water Act (CWA) direct water quality programs to 

implement protection and restoration of the integrity of State waters. Section 303d of the Clean 

Water Act lists all impaired waters. These are waters with compromised quality and/or limited 

use due to an excess of one or more pollutants. Related to this, the overarching Government 

Performance and Results Act (GPRA) goal for water quality is that ―...99.3% of streams and 

rivers managed by NPS will meet State and Federal water quality standards‖. Impaired water 

bodies in SFAN are listed in Table 4.3. Primary SFAN water quality issues include agricultural 

operations (dairy and beef cattle ranching, vegetable farming, viticulture, mariculture), 

recreational use (beaches, stable operations, dog walks), erosion and sedimentation, and water 

supply (flooding, overwithdrawal). 
232

Table 0.3 Impaired water bodies in the SFAN.

Water body Park Unit Pollutant 

Coyote Creek GOGA Diazinon

Lagunitas Creek PORE, GOGA Pathogens, Sediment, Nutrients

Richardson Bay GOGA High Coliform, Mercury, PCBs, Pesticides, 

Exotic Species

San Francisco Bay GOGA, PRES Mercury, PCBs, Nickel, Pesticides, Exotic 

Species, Dioxin, Selenium

San Francisco Bay Urban Creeks GOGA, PRES, JOMU Diazinon

San Francisquito Creek GOGA Diazinon, Sediment

San Pedro Creek GOGA High Coliform

Tomales Bay PORE, GOGA Pathogens, Sediment, Nutrients, Mercury

The primary objectives of this monitoring program are to 1) Maintain waters that vary within 

their natural chemical and biological ranges and meet applicable federal and state water quality 

criteria, 2) Improve the water quality of impaired waters, and 3) Maintain high water quality 

where it exists.

Based on these objectives, monitoring data from this program will be used to answer the 

following questions:

 What are the existing chemical and biological ranges in water quality at selected sites within 

priority SFAN streams? 

 What are the long-term trends in water quality at selected sites in priority SFAN streams?

 Is the water quality of priority SFAN streams in compliance with designated beneficial uses?

 What are the point and non-point pollution sources within the watersheds?

 Are specific management actions reducing pollution loads? 

4.4.4 Project/Task Description

4.4.4.1 Quality Assurance

The SFAN Water Quality Monitoring Program has been developed and will be implemented 

with the objective of collecting high quality monitoring data that could be of the most use to the 

National Park Service, U.S. Geological Survey, and California and San Francisco Bay Area 

monitoring programs. A technical panel of aquatic resource specialists will be consulted 

regarding QA/QC measures and plan implementation. 

4.4.4.2 Data Management, Data Evaluation, and Reporting

Data management, evaluation, and reporting will be high priorities of SFAN. The NPSTORET 

database will be the central depository of all data collected by SFAN. The SFAN version of 

NPSTORET will be sent annually to the WRD. NPSTORET Templates are designed to capture 

all critical field information for uploading data and required meta-data into STORET. These 

templates should be used whenever feasible to do so as that should streamline the data 

management process significantly. The discussion of this data management system and links to 
233

example NPSTORET templates may be found at www.nature.nps.gov/water/infoanddata. 

Alternatively, and electronic data deliverable file (EDD) may be generated but it should capture 

all the ancillary information and meta-data that the NPSTORET templates would.

It is the goal of the SFAN data management program to ultimately provide standardized data 

management, evaluation, and reporting. It is also a goal of SFAN to be as "paperless" as 

possible, and to develop a database that will allow internet web access to all parties interested in 

the data and technical reports produced through SFAN studies. SFAN will include the use of 

existing data to the extent that it can be verified and placed or linked into centralized locations, 

but such "outside data" shall not be a part of the official SFAN database at this time. A summary 

of the NPSTORET data base is included in the protocol narrative of the overall water quality 

monitoring plan.

Table 0.4 Project Task Extended Timetable.

Deliverables FY06 FY07 FY08 FY09 FY10

Develop QAPP X

Meet with local technical experts to review 

monitoring protocol 

X

Finalize protocol and have peer reviewed X

Conduct equipment inventory and calibration, 

purchase any needed equipment

X X

Collect monitoring data X X X X

Produce annual summary report X X X X

Share results with parks and scientific community at 

annual ―Water Quality Forum‖

X X X X

Produce comprehensive data analysis and synthesis 

(trends) report

X

Table 0.5 Overall Water Quality Monitoring Schedule.

Stream Park Unit FY07 FY08 FY09 FY10

Olema Creek PORE M, S, W M, S, W M,S, W M,S,W

Lagunitas Creek PORE/GOGA M M

Pine Gulch PORE M M

Lower Redwood Creek GOGA/MUWO M, S M, S

Upper Redwood Creek GOGA/MUWO M M

Rodeo Creek GOGA M, S M, S

Tennessee Creek GOGA M, S M, S

Nyhan Creek GOGA M, S M, S

Oakwood Creek GOGA M, S M, S

West Union Creek GOGA M M

Franklin Creek JOMU M M

Strentzel Creek JOMU S S

Chalone Creek PINN M, S M, S

M monthly monitoring (winter and spring only for Chalone Creek and West Union Creek)

S monitoring during at least one storm event

W weekly monitoring for five consecutive weeks in winter and summer
234

4.4.5 Data Quality Objectives (DQOs) and Criteria for Measurement Data

DQO’s are qualitative and quantitative statements of the quality of data needed to support 

specific decisions or actions. Data acceptability criteria are included in DQOs. The purpose of 

DQOs is to document 1) the intended use of the data in order or importance, 2) decision to be 

made when data are obtained, and 3) decision makers who will use the data (California 

Department of Water Resources, 1998). Decision makers for SFAN will generally be the same 

for each parameter. Recommendations will be developed by network staff and park aquatic 

professionals. These recommendations in the form of annual reports or summaries will be made 

to managers such as Resource Management Chief’s and Park Superintendents. Other decision 

makers may include local agencies and landowners. All data including core parameters, bacteria, 

nutrients, and sediment have the same intended uses since they all help identify pollution sources 

and areas of concern with respect to aquatic health and other beneficial uses.

Table 0.6 Data utilization and Related Management Decisions.

Parameter Intended use of data Relevant Management Decision

Core 

parameters

Determine the natural variation and range in water quality 

parameters. Analyze data from control sites or reference 

streams; analyze annual, seasonal, and daily data for each 

station and each group of stations in a stream or 

watershed

If results are unexpected (i.e., out of 

normal range), choose different 

reference, or ―control‖ sites or pursue 

geological and other studies that 

would help explain the variability 

Core 

parameters

Determine the long-term trends in water quality 

parameters. Analyze data from all sites. Analyze annual 

and seasonal data for each station and for each group of 

stations in a stream or watershed.

If data trends point to problems (e.g., 

consistent decline in D.O., or 

consistent increase or decline in pH 

or temperature) check data with 

surrounding areas, compare with 

local and regional climate data, 

compare data with other indicators 

(e.g., air quality)

Core 

parameters, 

nutrients, 

bacteria, 

sediment

Determine if water bodies are meeting water quality 

criteria. Determine the level of compliance with beneficial 

uses. Focus on sites known to be impaired; analyze data 

for each site for each group of stations (collectively) in a 

stream.

Determine what level of compliance 

is acceptable (e.g., 100% of stations 

meeting the criteria 90% of the time); 

adapt monitoring strategy if 

necessary to focus on stations that do 

not meet criteria

Core 

parameters, 

nutrients, 

bacteria, 

sediment

Determine the sources of water quality degradation within 

park watersheds. Compare data from individual sites from 

one sampling event to another; also compare data from 

multiple sites within a stream. Provide data to local 

agencies (where appropriate and not for regulatory 

purposes) and landowners

Make decision on how to present 

data and work internally with other 

park divisions where applicable, with 

local landowners, and with agencies 

to alleviate problems; work with 

local groups on implementation 

strategies related to the BMPs

Core 

parameters, 

nutrients, 

bacteria, 

sediment

Determine if management actions are improving water 

quality. Compare data from individual sites from one 

sampling event to another; also compare data from 

multiple sites within a stream. Provide data to local 

agencies (where appropriate)

Continue management action if

effective and use to encourage 

additional use of BMP; improve or 

change BMP,

Goals For Achieving Data Quality Objectives (DQO's)
235

Data quality objectives will be achieved in a number of ways including: 

 Developing standard operating procedures (SOP) with standardized field and 

laboratory methods,

 Forming and convening a SFAN External Scientific Planning and Review 

Committee which will serve to bring together scientists that are "external" to the 

NPS as well as internal to provide on-going peer review of all SFAN water 

quality monitoring activities, with QA oversight being one of the primary focuses; 

and 

 Documenting the comparability of laboratory and field methods that are 

consistent with the DQO's.

The intent is to provide the minimum standards and guidelines that SFAN should utilize, with 

strong encouragement to use more stringent criteria and to adopt methodologies that improve upon 

these minimum standards. The major goal that this SFAN QAPP (SOP 4) can accomplish, is to 

have representative, comparable, accurate and precise data that can be shared statewide and 

nationwide, to the extent possible. Refer to Table 4.7 below to see a summary of SFAN data 

quality assurances.

The following SOPs were completed as part of the DQO process:

SOP 1: Revising the Protocol

SOP 2: Personnel Training and Safety

SOP 3: Equipment and Field Preparations 

SOP 4: Quality Assurance Project Plan (QAPP)

SOP 5: Field Methods for Measurement of Core Parameters 

SOP 6: Field Methods for Sampling Nutrients 

SOP 7: Field and Laboratory Methods for Sampling Bacteria

SOP 8: Field and Laboratory Methods for Sediment 

SOP 9: Field Methods for Measuring Flow 

SOP 10: Data Analysis 

SOP 11: Data Reporting

SOP 12: Site Selection and Documentation

These SOPS are in Appendix H of the Freshwater Quality Protocol Narrative (―protocol 

narrative‖). The generally accepted goal at least for the first several years of the "start-up" of the 

SFAN Water Quality Monitoring Program is to "standardize where possible; document 

otherwise". The need for flexibility to accommodate park-specific sample collection needs was 

acknowledged, along with the need to standardize methods to the extent possible. Data quality 

will be attained by maximizing and documenting the accuracy and precision of the methods 

used. Any changes in procedures due to equipment changes or to improved precision and 

accuracy will be documented. Wherever possible, there should be overlap in sampling methods 

as well as overlap of staff when turnover occurs. Data quality objectives include 
236

representativeness, comparability, completeness, and precision. These are discussed further 

below (from Puckett, 2002):

Representativeness

The representativeness of the data is mainly dependent on the sampling locations and the 

sampling procedures adequately representing the true condition of the named target 

population at the sample site(s). Requirements for selecting sample sites are discussed in 

more detail in the protocol narrative. Selection of appropriate sample sites and the use of 

only approved/documented analytical methods will ensure that the measurement data does 

represent the conditions at the investigation site, to the extent possible. Assuring 

representiveness of the data for the site and times sampled will be accomplished by using 

methods used by the USGS (collector sites, cross-section checks, sampling from the centroid 

of flow, etc.) A combination of assuring representativeness, plus selecting sites upstream of 

bridges and culverts (as detailed in Standard Operating Procedure (SOP #12, Site Selection & 

Documentation)), and randomly selecting where to start sampling the midpoints and crosssections upstream will assure reasonable representativeness of the target population while 

still maintaining good data comparability with regional USGS data To help ensure that 

inferences from a single site visit (sample population) to chemical and biological ranges at 

selected sites in priority streams (target population) are appropriate, continuous monitors will 

be deployed. Data from these instruments will help gain an understanding of seasonal and 

diurnal (daily) variability. This data, where available for a particular site, will also allow us 

to eventually broaden the target population definition to include all water quality parameter 

values and ranges from the selected areas of priority streams, (without the caveat of the 

limited temporal collection periods.) These types of variability occur in many water quality 

parameters and will be discussed in greater detail in the SOPs and in subsequent versions of 

this protocol.

Some constraints to sampling representatively include difficult or unsafe site access, 

particularly during storm events, lack of staff availability during the winter holidays when 

major storm events often occur, and laboratory constraints such as sample hold time, and 

hours of operation or holiday closures. Other constraints to sampling representatively are that 

sites will primarily be located within park boundaries and will not necessarily represent the 

larger watershed. This will not be a significant concern for the SFAN since parks encompass 

several watersheds in their entirety. However, watersheds with significant portions located 

outside park boundaries may not be sampled in some cases due to access issues, relative lack 

of management options, or other limitations.

Comparability

The comparability of data produced by SFAN is predetermined by the commitment of its 

staff and contracted laboratories to use standardized methods, where possible, including 

USGS field methods and U.S. Environmental Protection Agency (EPA) approved analytical 

methods, or documented modifications that provide equal or better results. These methods 

have specified units in which the results are to be reported. For internal data comparability, 
237

the SOP’s of the SFAN Freshwater Quality Monitoring Protocol carefully describe the 

methods to be followed during water quality sampling. If followed carefully, these should 

provide the methodological and temporal consistency that will ensure internal data 

comparability. This includes such discussions as training, overlap of sampling methods 

when equipment, personnel or methods change, and documentation of bias between old and 

new methods. The comparability of SFAN data to the data collected by outside entities from 

the state to consultants and volunteers will depend on the documentation of methodologies 

and QA/QC practices of these groups. The project manager will meet with outside project 

leaders to determine and document methodologies of outside projects. One of the central 

ways the SFAN freshwater quality monitoring protocol will insure the comparability of their 

data to outside groups is to follow some basic information quality guidelines by integrating a 

high degree of transparency about data and methods used to generate the data, including 

quantifying the limits of Measurement Quality Objectives specifications for precision, bias 

and sensitivity.

Because the state was involved in discussions through guidance and review of this protocol, 

data collected as part of SFAN water quality monitoring activities should be directly 

comparable to the state-collected data. Regular consultation with outside monitoring groups 

will establish and/or maintain a high level of comparability wherever possible. All 

contracted labs will use standardized methods and will be NELAP or CA ELAP-certified.

Table 0.7 Overview of SFAN Data Quality Assurance.

Data Comparability Issue SFAN Data Quality Assurance

Sufficiency of Metadata  Metadata requirements of NPSTORET are comprehensive, 

ensuring that methods, analyses and handling of both samples 

and data are documented in the same place as the data itself 

(including the attachment of the protocol and SOP documents 

themselves). 

 Systematic verification of data in the database, as well as periodic 

review of stated procedures and included documentation (SOP’s).

 The Protocol Narrative and SOP’s will thoroughly document all 

field and laboratory methods, including QA/ QC measures.

Field Methods  Standard USGS or SWQCB (SWAMP) protocols will be 

followed, as explained in the SOP’s.

 Documentation of equipment calibration frequency and 

acceptance criteria.

Lab Methods  All laboratories analyzing SFAN samples will be NELAP (or 

CA-ELAP) certified for the parameter and analysis being 

conducted.

 All methods used for laboratory samples will follow Standard 

Methods using APHA/AWWA/WEF methods or comparable 

EPA methods.

 Laboratory QC measures will include matrix spikes, method 

blanks, calibration standards, lab and field-duplicated samples.
238

Data Comparability Issue SFAN Data Quality Assurance

Sensitivity  For lab parameters: Calculation of both Method Detection Limit 

(MDL) and Minimum Level of Quantitation (ML).

 For field or ―core‖ parameters: Quarterly collection of seven 

replicate samples or measurements in order to calculate the 

Alternative Measurement Sensitivity (AMS).

Precision  For Field Measurements: Duplicate at least one measurement, or 

10% of a days’ samples (whichever is larger).

 For Lab Measurements: Duplicate analysis of 10% of samples. 

Report the Relative Percent Difference (RPD). 

Bias  Maintain consistent personnel and methodology where possible.

 Overlap a minimum of seven (7) measurements when personnel 

changes, thirty (30) when a method or equipment changes, and 

fifty (50) when replacing surrogate estimators like FIB.

 Analyze such overlapping samples to determine the contribution 

of bias (if any) to any variance in the data.

 Control bias by: Use and analysis of ―blank‖ samples (Field, 

Trip or Lab Blanks) to determine contamination by methodology.

 For control of measurement bias, certified reference materials 

and/or spikes will be analyzed once every 20 samples and % 

difference shall not be more than the values listed in Table 4.10.

―Accuracy‖  For the purposes of this protocol, the term ―accuracy‖ should be 

taken to be the ―uncertainty in accuracy‖ and is a combination of 

random error (precision) and systematic error (bias) components 

that are due to sampling and analytical operations. Measurement 

uncertainty will be controlled quantitatively through calculations 

of sensitivity, precision and bias.

Completeness

The completeness of data is basically a relationship of how much of the data is available for 

use compared to the total potential data before any conclusion is reached. Ideally, 100% of 

the data should be available. However, the possibility of data becoming unavailable due to 

laboratory error, insufficient sample volume, or samples broken in shipping must be 

expected. Also, unexpected situations may arise where field conditions do not allow for 

100% data completeness. 

 Therefore, 90% data completeness is required for data usage in most cases.

Precision and Accuracy

The precision and accuracy of data are determined by particular actions of the analytical 

laboratory and field staff. The precision of data is a measure of the reproducibility of the 

measurement when an analysis is repeated. It is reported in Relative Percent Difference 

(RPD) or Relative Standard Deviation (RSD). The accuracy of an analysis is a measure of 

how much of the constituent actually present is determined. It is measured, where 

applicable, by adding a known amount of the constituent to a portion of the sample and 

determining how much of this spike is then measured. It is reported as Percent Difference. 

The acceptable percent deviations and the acceptable percent recoveries are dependent on 
239

many factors including: analytical method used, laboratory used, media of sample, and 

constituent being measured.

It is the responsibility of the program manager (water quality specialist) to control the 

precision and accuracy of the field data, while verifying that the data are representative. For 

samples that undergo laboratory analysis, the analytical data's precision, accuracy, and 

comparability are mainly the responsibility of the laboratory. The program manager also has 

prime responsibility for determining that the 90% data completeness criteria are met or for 

justifying acceptance of a lesser percentage.

Laboratories performing the analysis of samples for this project have developed precision 

and accuracy limits for acceptability of data. For parameters and matrices which have EPA 

established criteria, the limits are either equal to, or more stringent than, the established limit. 

In no case will measurement quality objectives for precision and bias be less stringent than 

marine EMAP recommendations.

4.4.6 Special Training/Certification

Field

Proper training of field personnel represents a critical aspect of quality control. Details of staff 

training are presented in SOP 2. Safety issues related to water quality work are presented in SOP 

2; all field staff will be well-versed in this SOP. . The USGS offers a comprehensive two-week 

training course in field methods entitled ―Field Water-Quality Methods for Ground Water and 

Surface Water‖ for hydrologic field technicians. This training is available for NPS staff when 

slots are available. The WRD may be a resource for locating and scheduling such training for 

staff.

NPS staff downloading continuous loggers and collecting all other water quality data have either 

already been trained by other NPS staff or will be trained before plan implementation. Scientists 

at PORE and GOGA have been conducting water quality related activities for several years and 

can provide training if necessary to network staff. However, the water quality specialist is 

expected to be independent and knowledgeable in chemistry and water sampling techniques. 

All technical staff involved in data collection will have educational background in biological or 

physical sciences. The network water quality specialist will have specialized experience in water 

quality or closely related aquatic resource. Where necessary (e.g., with staff turnover, adoption 

of new methods, etc.) local technical experts (universities/agencies) will be called upon for 

training assistance. Familiarity with GPS navigation will also be a qualification (or training will 

be provided). First Aid and CPR training are highly recommended. Boater certification will not 

be needed at this time. Field personnel will receive training in a variety of discharge (flow) 

measurement methods (e.g., low flow, high flow bridge-deployed). 

Field personnel will be evaluated on their field performance during field QA audits conducted by 

the SFAN water quality specialist and other park aquatic professionals. Field performance audits 
240

are recommended every two years, or more often if necessary. If any deficiencies within a crew 

are noted during this QA audit, they will be documented and remedied prior to continued field 

sampling. This can be accomplished by additional training or by changing personnel, but 

verification of correction of any deficiencies must be documented in writing prior to the 

resumption of further sample collection activities. 

Laboratory 

Meetings, whether by phone or in person, will be held with the laboratory (-ies) at regular 

intervals to review QA/QC procedures and make recommendations for future revisions to the 

SFAN QAPP. The more frequent the interactions with laboratory staff the better the 

understanding of any key issues or correction of problems will be. Issues such as timing of 

sample transport and analysis and lab capability and capacity for samples are important to 

QA/QC data completeness objectives. 

4.4.7 Documentation and Records

 All field data gathered will be recorded on standardized field data entry forms that include 

metadata to be entered into the NPSTORET database. 

 Data will be scanned upon receipt from laboratory and during and immediately after field 

measurements (this is also true of data from data loggers such as turbidity sensor, pressure 

transducer, or multiparameter mini-sonde data). 

 Data will be more thoroughly reviewed within a week after each sampling event for 

inconsistencies related to field personnel, how well SOPs are followed, and how timing and 

logistics of sample collection and transport to laboratories may be affecting sample data. 

 Field data will not be entered into the database until laboratory results have arrived.

 Field and laboratory data sheets will be copied and stored in a ―data to be entered‖ folder. 

 Original copies of datasheets and laboratory chain of custody forms will be stored in the 

SFAN Water Quality Monitoring Program Office in the Marin Headlands (GOGA). 

 SFAN data managers will work with the SFAN hydrologic technician to ensure that data is 

well-understood and entered into the proper fields in NPSTORET. 

 Data will be entered into the SFAN NPSTORET database no less than once a month to 

ensure adequate interpretation of field notes and receipt of proper laboratory QA/QC 

information. Each datasheet will be initialed and dated by the person entering the data.

 A different individual than the one that entered the data will verify the datasheet information 

against the database.

 Data will also be validated; during this process questionable data are identified, reviewed, 

and corrected if necessary. 

 After data entry, verification, and validation, copies will be retained by the person entering 

the data for one year. After that time or another appropriate time, data will be archived.

Sample datasheets are included in the Appendix A of this document. Chain of custody forms 

vary depending upon the laboratory. Reporting of results including summary charts and reports 

are explained in more detail in the Water Quality Protocol Narrative. 
241

4.5 Data Generation and Acquisition

4.5.1 Sampling Process Design (Experimental Design) 

Table 0.8 Target streams, parameters, and protocols to be monitored.

Stream Park Parameters Frequency Personnel Protocols

Olema Creek PORE Core 

parameters, 

flow, FIB, 

nutrients, 

sediment, 

water level

Monthly; 

weekly for 5 

weeks in 

summer and 

winter, 

continuous at 

one site*; one 

storm event

SFAN Water 

Quality 

Specialist 

National Field Manual (USGS, 

various dates); Rantz , 1982 ; 

Peck et al., 2001; APHA et al., 

1992; State Water Resources 

Control Board (Puckett 2002); 

U.S. Forest Service, 2002. 

Lagunitas 

Creek 

tributaries 

PORE

GOGA

Core 

parameters, 

flow, FIB, 

nutrients, 

sediment

Monthly, plus 

one storm 

event

SFAN Water 

Quality 

Specialist

National Field Manual (USGS, 

various dates); Rantz , 1982 ; 

Peck et al., 2001; APHA et al., 

1992; State Water Resources 

Control Board (Puckett 2002); 

U.S. Forest Service, 2002.

Pine Gulch PORE Core 

parameters, 

flow, water 

level, FIB, 

nutrients

Monthly SFAN Water 

Quality 

Specialist

National Field Manual (USGS, 

various dates); Rantz, 1982 ; Peck 

et al., 2001; APHA et al., 1992; 

State Water Resources Control 

Board (Puckett 2002)

Lower 

Redwood 

Creek 

GOGA

MUWO

Core 

parameters, 

flow, FIB, 

nutrients, 

sediment, 

water level

Monthly plus 

one storm 

event; one site 

continuous*

SFAN Water 

Quality 

Specialist 

National Field Manual (USGS, 

various dates); Rantz, 1982 ; Peck 

et al., 2001; APHA et al., 1992; 

State Water Resources Control 

Board (Puckett 2002)

Upper 

Redwood 

Creek 

GOGA

MUWO

Core 

parameters, 

flow, FIB, 

nutrients, 

sediment

Monthly plus 

one storm 

event

SFAN Water 

Quality 

Specialist

National Field Manual (USGS, 

various dates); Rantz, 1982 ; Peck 

et al, 2001; APHA et al., 1992; 

State Water Resources Control 

Board (Puckett, 2002)

Rodeo Creek GOGA Core 

parameters, 

flow, FIB, 

nutrients, 

sediment

Monthly plus 

one storm 

event 

SFAN Water 

Quality 

Specialist

National Field Manual (USGS, 

various dates); Rantz, 1982 ; Peck 

et al., 2001; APHA et al., 1992; 

State Water Resources Control 

Board (Puckett 2002)

Tennessee 

Creek 

(GOGA)

GOGA Core 

parameters, 

flow, FIB, 

nutrients 

Monthly plus 

one storm 

event

SFAN Water 

Quality 

Specialist

National Field Manual (USGS, 

various dates); Rantz, 1982 ; Peck 

et al., 2001; APHA et al., 1992; 

State Water Resources Control 

Board (Puckett 2002)

Nyhan Creek GOGA Core 

parameters, 

flow, FIB, 

nutrients

Monthly SFAN Water 

Quality 

Specialist

National Field Manual (USGS, 

various dates); Rantz , 1982 ; 

Peck et al, 2001, APHA et al., 

1992; State Water Resources 

Control Board (Puckett, 2002)
242

Stream Park Parameters Frequency Personnel Protocols

Oakwood 

Creek 

GOGA Core 

parameters, 

flow, FIB, 

nutrients

Monthly SFAN Water 

Quality 

Specialist

National Field Manual (USGS, 

various dates); Rantz , 1982 ; 

Peck et al, 2001; APHA et al., 

1992; State Water Resources 

Control Board (Puckett, 2002)

West Union 

Creek 

GOGA Core 

parameters, 

flow, FIB, 

nutrients, 

sediment

Monthly 

during winter 

and spring

SFAN Water 

Quality 

Specialist

National Field Manual (USGS, 

various dates); Rantz , 1982 ; 

Peck et al, 2001; APHA et al., 

1992; State Water Resources 

Control Board (Puckett 2002); 

U.S. Forest Service, 2002.

Franklin 

Creek 

JOMU Core 

parameters, 

flow, water 

level, FIB, 

nutrients

Monthly SFAN Water 

Quality 

Specialist; 

assistance 

from local 

volunteers

National Field Manual (USGS, 

various dates); Rantz, 1982 ; Peck 

et al, 2001, APHA et al., 1992; 

State Water Resources Control 

Board (Puckett 2002)

Strentzel 

Creek 

JOMU Core 

parameters, 

flow, 

sediment 

Storm events SFAN Water 

Quality 

Specialist; 

assistance 

from local 

volunteers 

National Field Manual (USGS, 

various dates); Rantz, 1982 ; 

APHA et al., 1992; State Water 

Resources Control Board (Puckett 

2002); U.S. Forest Service, 2002.

Chalone 

Creek 

PINN Core 

parameters, 

flow, FIB, 

nutrients, 

sediment

Monthly 

during winter 

and spring; 

one storm 

event

SFAN Water 

Quality 

Specialist with 

park staff 

assistance as 

available

National Field Manual (USGS, 

various dates); Rantz, 1982 ; Peck 

et al., 2001; APHA et al., 1992; 

State Water Resources Control 

Board (Puckett 2002)

*The continuous probe will be moved from watershed to watershed on a rotating basis for 

Olema, Pine Gulch, Redwood, Tennessee Valley, Rodeo, Franklin, and Chalone Creeks

4.5.2 Sampling Methods

All measurements and sampling associated with monitoring activities will be conducted 

according to the SOPs outlined in the protocol narrative. If there is a change in the protocol such 

as a change in sampling method, equipment, or staff, then there will be overlap of methods and 

personnel where possible (see SOP 1: Methods for Protocol Revision). 

4.5.3 Sample Handling and Custody Requirements

Proper sample handling procedures for water, sediment, and biological samples are provided in 

Table 4.8. This table provides a summary of recommended sample containers, sample volumes, 

initial preservation, and maximum storage times for water samples. In the field, all samples will 

be packed in frozen ice packs during shipment, so that they will be kept at approximately 4 ̊C. 

Samples will be shipped in insulated containers. All caps and lids will be checked for tightness 

prior to shipping. All samples will be handled, prepared, transported and stored in a manner so 

as to minimize bulk loss, analyte loss, contamination or biological degradation. Sample 
243

containers will be clearly labeled with an indelible marker. Where appropriate, samples may be 

frozen to prevent biological degradation. Water samples will be kept in glass or plastic bottles 

and kept cool at a temperature of 4 ̊C until analyzed. 

Table 0.9 Summary of Sample Handling Requirements.

Analyte Sample Container Minimum Sample 

Volume/Typical 

Sample Volume

Holding Time Preservation

Total Kjeldahl 

Nitrogen (TKN)

Plastic bottle 600 mL Recommend: 7 days; 

Maximum: 28 days

Cool to 4°C

Nitrate and Nitrite Plastic bottle 125 mL/150 mL 48 hours Cool to 4°C

Ammonia Plastic bottle 125 mL/500 mL 48 hours

28 days with 

preservative

Sulfuric acid 

preservative, Cool to 

4°C

Fecal & Total 

Coliform

125 ml sterile plastic 

(high density 

polyethylene or 

polypropylene) 

container

100 ml volume 

sufficient for both 

fecal and total 

coliform analyses

6 hours at 4°C, dark 

for regulatory data 

use; lab must be 

notified well in 

advance. Possibly

24hr hold time at 4C 

dark, if nonregulatory data use.

Sodium thiosulfate 

is pre-added to the 

containers in the 

laboratory (chlorine 

elimination). Cool 

to 4°C; dark.

Suspended Sediment 

Concentration (SSC) 

or Total Suspended 

Solids (TSS)

500 ml clean plastic 

bottle

500 ml (one bottle) 7 days Cool to 4°C

Turbidity glass vial 15 mL NA NA

4.5.3.1 Laboratory Custody Log

Laboratories chosen will be National Environmental Laboratory Accreditation Program 

(NELAP) certified (or CA ELAP-certified) and this is discussed further in the protocol narrative. 

Therefore, they are expected to follow standard procedures. Laboratories will maintain custody 

logs sufficient to track each sample submitted and to analyze or preserve each sample within 

specified holding times. 

4.5.3.2 Field Log

The following items will be recorded on data sheets for each sampling station:

• Time of sample collection;

• Sample ID numbers, 

• The results of any field measurements (temperature, D.O., pH, conductivity, turbidity) 

and the time that measurements were made;

• Qualitative descriptions of relevant water conditions (e.g. color, flow level, clarity) or 

weather (e.g. wind, rain) at the time of sample collection;
244

• A description of any unusual occurrences associated with the sampling event, particularly 

those that may affect sample or data quality.

Field personnel will have custody of samples during field sampling. Chain of custody forms will 

accompany all samples during transport/shipment to the contract laboratories. Field personnel 

will enter sampling time and other relevant data on the chain of custody forms. All water quality 

samples will be transported to the analytical laboratory directly by the field crew or by overnight 

courier. See Appendix A for field data sheets. Chain of custody forms vary depending on the 

laboratory.

4.5.4 Analytical Methods Requirements

Detection limits may be affected by instrument sensitivity or by bias due to contamination or 

matrix interferences. Common laboratory practice is to adjust detection limits upward in cases 

where high instrument precision (i.e., low variability) results in calculated detection limits that 

are lower than the absolute sensitivity of the analytical instrument. In these cases, best 

professional judgment is used to adjust detection limits upward to reduce false positives and 

values below the detection limit are not reported. In all cases, results cannot be reported for 

values less than the Method Detection Limit (MDL). Most MDLs are considerably lower than 

water quality objectives and provide the foundation for having a high level of certainty in the 

data (Puckett, 2002). 

Data below or beyond an MDL will not be presented numerically. Data falling between the 

MDL and minimum level of quantitation (ML) are considered detected but not quantifiable and 

can be given a result of Present, below quantification level. The ML is equal to the MDL 

multiplied by 3.18 (or some number between 2 and 10 that may be determined by the analytical 

laboratory). (Irwin, 2006). See the section ―Preparing the Raw Data Set for Analysis‖ in SOP 

#10 (data analysis)

The SFAN Water Quality Monitoring Program will follow recommendations in the recent Helsel 

(2005) book for recommended use of detection and quantification limits:

We will not report into a database any value higher than the MDL but lower than the ML. 

Instead, the detection condition field is set to "Present, below Quantification Limit". With that 

detection condition, STORET automatically enters "*Present <QL" in the result field. (A major 

advantage of this approach is that no "estimates" are treated as quantitative when in fact they are 

not quantitative.) In (eventual) statistical analyses, values between the MDL and ML are best 

interpreted using either an interval-censored method (parametric), or a rank-based method 

(nonparametric) where all in-between values are represented as the same tied rank. The older 

recommendation of censoring to half the MDL is clearly no longer recommended. Helsel (2005) 

also gives recommendations for how not to report into data bases (for example, never report 

single values below the MDL or even the ML, and do not report nondetects as half the detection 

limit. One should also not report nondetects as a negative (―-―) sign followed by the actual MDL 

value, because someone invariably decides it really is a negative number
245

In Summary:

 Values below the Method Detection Limit (MDL) are to be reported as a (<) sign followed 

by the actual MDL value, and flagged with an ND = not detected.

 Values between the MDL and the ML (or quantification limit) should be reported as ―*Present, 

below Quantification Limit‖.

 Values above the ML (or quantification limit) are deemed as acceptable values without 

reservation, and are shown as the actual measured value, and assigned a QA code of A 

(acceptable without reservation).

In general, laboratories should strive to meet target reporting limit recommendations for undetected 

analytes. In those cases where high concentrations of some analytes require analysis of a diluted 

sample and the dilution results in non-detects for other analytes, analysis of the sample at several 

different dilutions may be required to meet program detection limits as fully as practical. Table 4.9 

lists analytical methods and measurement quality objectives (MQOs) for all water quality 

parameters except flow. In addition to the MDL, these include precision, and systematic 

error/bias/percent recovery. Details of QA/QC for flow measurements will be outlined in a 

separate protocol. 

Table 0.10 Measurement Quality Objectives.

Parameter Instrument 

or Method

Precision 

(RPD of 

duplicates)

1 Measurement 

Systematic Error 

(% recovery)

2Alternative 

Measurement 

Sensitivity 

(AMS)

Method 

Detection 

Limit

3

 Minimum 

Level of 

Quantitation 

(ML)

pH Oakton pH 

testr 30

+ 0.1 units 95-105% 

(5% PD)

*** 0.01 pH 0.0318 pH

Dissolved 

oxygen

YSI 85 + 0.3 mg/L 95-105%

(5% PD)

*** 0.01mg/L 0.0318 mg/L

Salinity YSI 85 + 2% or 

+0.1 ppt

5% PD% *** 0.1 ppt 0.318 ppt

Temperature YSI 85 + 0.2 0C 95-105% (5% PD) *** 0.10C 0.318 0C

Specific 

Conductance 

or 

Conductivity

YSI 85 + 5 uS/cm 

or + 3% of 

the 

measured 

value, 

whichever 

is greater

95-105% 

(5% PD)

2.5 μS/cm 0.1 μS/cm 0.318 μS/cm

Total 

Kjeldahl 

Nitrogen

SM 4500

EPA 300

+30% 90-110% 

(5% PD) 

0.5 mg/L 

(Puckett, 

2002)

0.1 mg/L 3.18 x MDL 

Nitrate as N SM 4500

EPA 300

+30% 90-110% (10% 

PD)

0.01 mg/L 0.1 mg/L 3.18 x MDL

Nitrite as N SM 4500

EPA 300

+30% 90-110% (10% 

PD)

0.01 mg/L 0.05 mg/L 3.18 x MDL

AmmoniaNitrogenSM 4500F +30% 90-110% (10% 

PD)

0.1 mg/L 0.1 mg/L 3.18 x MDL

Fecal SM 9221B +60% See Note6 To be 2 3.18 x MDL
246

Parameter Instrument 

or Method

Precision 

(RPD of 

duplicates)

1 Measurement 

Systematic Error 

(% recovery)

2Alternative 

Measurement 

Sensitivity 

(AMS)

Method 

Detection 

Limit

3

 Minimum 

Level of 

Quantitation 

(ML)

coliforms4calculated MPN/100

mL

Total 

coliforms4

SM 9221 +60% See Note6 To be 

calculated

2 

MPN/100

mL

3.18 x MDL

Total 

Suspended 

Solids 

SM 2540D 30% 90-110% (10% 

PD)

0.5 mg/L 0.5 mg/L 3.18 x MDL

Turbidity Hach 2100 

turbidity 

meter

+2 NTU or 

+5 % of the 

measured 

value, 

whichever 

is greater 

(USGS)

+ 2% 

(Hach)

90-110% (10% 

PD)

0.5 NTU 

(Puckett, 

2002)

0.01 NTU 3.18 x MDL

1 Often referred to as accuracy

2

 Formerly referred to as the Reporting Detection Limit; AMS is the measurement precision 

 uncertainty based on a sample size of seven environmental samples (not blank) and 99% 

 confidence (Irwin, 2004). This should be calculated at the beginning of the field season, 

 during the winter (high flow) and at the end of the field season.

3 Formerly referred to as Practical Quantitation Limit (PQL) and the Limit of Quantification 

 (LOQ) in the SWAMP QAMP (Puckett, 2002). The ML is generally the MDL multiplied by 5 (or some number 

between 1-10 that may be determined by the analytical laboratory). See: 

http://www.epa.gov/waterscience/methods/det/rad/rad.pdf

4 The bacteria detection limit is 2-1600 (20-16,000, etc. if dilutions are needed). This detection limit is consistent 

 with the California Regional Water Quality Control Board’s Surface Water Ambient Monitoring Program 

 (Puckett, 2002).

5 MDLs for nutrients are those recommended by the San Francisco Bay Regional Water Quality Control Board 

 (Peter Krottje, personal communication, June 2005). 

6 Measurement Systematic Error for bacterial parameters requires the addition of a known concentration of bacteria 

to a sample to measure percent recovery. This spike will be acheived using IDEXX QA/QC kits and will be 

repeated with each new lot # of trays or reagent. With this data we hope to establish a % recovery objective that is 

comparable with the EPA advice of 84-116%.

Citations for MQOs:

 Precision obtained from USGS (Wagner et al., 2000) and YSI 85, Oakton, and Hach manuals

 Measurement Systematic error, % recovery numbers obtained from the laboratory and WRD 

guidance.

 MDLs obtained from SWAMP QAMP (Puckett, 2002), Crissy Field Restoration QAPP Ward, 

 2004), and the YSI 85 Manual

 Use EPA’s EMAP http://www.epa.gov/emap/nca/html/docs/c2k_qapp.pdf

 MLs (formerly PQLs) are calculated as 3.18 x MDL
247

4.5.5 Quality Control Requirements

4.5.5.1 Laboratory Quality Control Requirements

There is a broad range in the quality of waters within SFAN. For more pristine waters (those in 

wilderness areas), it is critical that laboratories be able to provide low-level detection of 

pollutants. Some of the approaches required will include laboratory matrix spikes, laboratory 

method blanks, calibration standards, laboratory- and field-duplicated samples, and others as 

appropriate. The definition and use of each of these types of quality control samples are 

explained further below (Puckett, 2002).

Laboratories providing analytical support for chemical or biological analyses will have the 

appropriate facilities to store, prepare, and process samples and appropriate instrumentation and 

staff to provide data of the required quality within the time period dictated by the project 

(Puckett, 2002).

Laboratories will be able to provide information documenting their ability to conduct the 

analyses with the required level of data quality. Such information might include results from 

interlaboratory calibration studies, control charts and summary data of internal QA/QC checks, 

and results from certified reference material analyses and/or spikes (Puckett, 2002). Laboratories 

should provide a laboratory QA plan, SOPs, Analytical Methods Manual, Instrument 

Performance Information, and Control Charts.

Measurement Quality Objectives (MQOs)

Some MQOs and quality control checks are defined below (from Puckett, 2002):

Completeness

Data completeness is the amount of data collected compared against the expected amount. 

SFAN will strive for at least 90% data completeness.

Precision criteria

Precision is the reproducibility of an analytical method. Each laboratory is expected to maintain 

control charts for use by analysts in monitoring the overall precision of the CRM (Certified 

Reference Materials) or LCM. Upper and lower control chart limits (e.g., warning limits and 

control limits) will be continually updated; control limits based on 99% confidence intervals 

around the mean are recommended. The relative standard deviation (RSD) will be calculated for 

each analyte of interest in the CRM based on the last 7 CRM analyses.

 

Laboratory Replicates for Precision

A minimum of one field sample per set of SFAN water samples submitted to the laboratory will 

be processed and analyzed in duplicate to determine precision. The relative percent difference 

among duplicate samples (RPD expressed as percent) will be less than the targets in the 

Precision column in Table 4.10. We will use RPDs to be consistent with 2006 Environmental 

Data Standards Council (EDSC) standardized calculations for precision 

(http://www.envdatastandards.net/content/article/detail/646).
248

In cases where three of more samples are used to estimate precision, for example long term 

precison over time, the relative percent difference (RSD) will be calculated as the CV x 100%. 

A laboratory control spike (LCS) and duplicate (LCSd) will be analyzed to determine percent 

recovery of each specific method. In addition, the State of California ELAP requires that 1 in 20 

samples have a CMS, or client matrix spike. Therefore, in addition to the laboratory spikes, the 

client’s samples are also spiked. However, CMS’ are not conducted for bacteria samples (Mark 

Valentini, personal communication, December 2004). 

Laboratory Method Blank

Laboratory method blanks (also called extraction blanks, procedural blanks, or preparation 

blanks) are used to assess laboratory contamination during all stages of sample preparation and 

analysis.

Surrogates

Surrogates are compounds chosen to simulate the analytes of interest in organic analyses. 

Surrogates are used to estimate analyte losses during the extraction and clean-up process and 

must be added to each sample, including QA/QC samples, prior to extraction. 

Bias Calculations for CRMs and Spikes

In 2006, the Environmental Data Standards Council (EDSC, an interagency group including 

EPA, States and Tribes) standardized the basic calculation and terminology definitions for bias 

using percent differences (PDs, rather than % recovery, see document at: 

http://www.envdatastandards.net/content/article/detail/646). We will do the same to be 

consistent with this recent guidance, which uses the correct (NIST/ISO compliant) terminology 

(bias rather than accuracy). The equation the EDSC give for Percent Different calculations is:

PD = [ Y - X) / X] * 100, where X is the known (usually ―correct‖ or ―expected‖) or spiked 

amount, and Y is the measured concentration. To be consistent with SWAMP and other 

agencies, we may also calculate % recoveries as another way to look at bias. Additional Detail 

on Spikes:

Matrix Spike and Matrix Spike Duplicate

A laboratory fortified sample matrix (commonly called a matrix spike, or MS) and a laboratory 

fortified sample matrix duplicate (commonly called a matrix spike duplicate, or MSD) will be 

used both to evaluate the effect of the sample matrix on the recovery of the compound(s) of 

interest and to provide an estimate of analytical precision. Recovery is the accuracy of an 

analytical test measured against a known analyte addition to a sample. 

Travel Blanks

The purpose of the travel blank is to determine if there is any cross-contamination of volatile 

constituents between sample containers. Travel blanks are not required for other analytes, but are 

encouraged to be utilized for other analytes as possible and appropriate.
249

Field Duplicates

Duplicate samples will be collected for all parameters at an annual rate of 5% of total samples to 

be collected within a given year's monitoring plan. The duplicate sample will be collected in the 

same manner and as close in time as possible to the original sample. This effort is to attempt to 

examine field homogeneity as well as sample handling, within the limits and constraints of the 

situation. The precision for determining precision of field duplicates is described in SOP #10-

Data Analysis. 

Field Blanks

A field blank is designed to assess potential sample contamination levels that could occur during 

field sampling and sample processing. Field Blanks (DI water) are taken to the field, transferred 

to the appropriate container, preserved (if appropriate), and otherwise treated the same as the 

corresponding sample type during the course of a sampling event. Field blanks are to be 

collected at a 5% rate for the following nutrient and bacteria samples. Field blanks for other 

analytes should be conducted upon initiation of sampling, and if field blank performance is 

acceptable, further collection and analysis of field blanks for these other media and analytes need 

only be performed on an as-needed basis, or during field performance audits.

Copies of laboratory QA/QC work will be included with analytical results and kept on file

Table 0.11 QA protocols.

Measurement Parameter QA Protocol

*Total Kjeldahl Nitrogen Duplicates 10% of samples, lab matrix spike

*Nitrate as N Duplicates 10% of samples, lab matrix spike, Field Blank, Trip Blank

*Nitrite as N Duplicates 10% of samples, lab matrix spike, Field Blank, Trip Blank

*Nitrate + Nitrite Duplicates 10% of samples, lab matrix spike, Field Blank, Trip Blank

*Ammonia Duplicates 10% of samples, lab matrix spike, Field Blank, Trip Blank

*Fecal coliforms Lab and field duplicates, Field Blank, Trip Blank

*Total coliforms Lab and field duplicates, Field Blank, Trip Blank

*Total Suspended Solids Lab and field duplicates, Field Blank, Trip Blank

Turbidity

Equipment blanks

*Also refer to laboratory QA manuals for lab parameters
250

4.5.6 Instrument/Equipment Testing, Inspection, and Maintenance Requirements

To minimize or avoid downtime of measurement instruments, all field sampling and laboratory 

equipment will be maintained in good working order. Also, spare equipment or common spare 

parts (e.g., batteries, D.O. membranes, and pH electrodes) will be available so that repairs or 

replacement can be made as quickly as possible and measurements will not be lost. All field 

equipment having manufacturer-recommended schedules of maintenance will receive preventive 

maintenance according to that schedule (see Table 4.11). Other equipment used only 

occasionally will be inspected at least monthly. After use in the field, all equipment will be rechecked for needed maintenance.

4.5.7 Instrument Calibration and Frequency 

An instrument or device used in obtaining an environmental measurement must be calibrated by 

the measurement of a standard. Every instrument or device has a specialized procedure for 

calibration and a special type of standard used to verify calibration. See instrument manuals for 

further details. A log book will be kept to record dates of calibration and any equipment errors 

or failures, battery changes, changes of calibration solutions, and repair notes. The log book will 

also contain calibration methods, this schedule of inspections and calibrations, and a list of 

needed supplies and equipment. When a change in equipment occurs, overlapping 

measurements will be made using both the old and new equipment in order to document 

precision in reproducibility.

Table 0.12 Routine Instrument Inspections and Calibrations.

Parameter Calibration Frequency Acceptance 

Criteria

Corrective Actions

Temperature 

Liquid-in-glass 

thermometer:

Every 3 to 6 months, using a 2-

point calibration check, and 

annually, using a 3-point 

calibration check

10% of the readings taken each day 

must be duplicated, or a minimum 

of 1 reading if fewer than 10 

samples are read.

±1.0 oC Re-test with a different 

thermometer; repeat 

measurement

Temperature 

Thermistor 

thermometer:

Every 3 to 4 months, check 

calibration, annually, using a 5-

point calibration

Same as 

above

Re-test with a different 

thermometer; repeat 

measurement

Specific 

Conductance

Prior to field mobilization, at the 

field site, and calibration check at 

day’s end;

10% of the readings taken each day 

must be duplicated or a minimum 

of 1 reading if fewer than 10 

samples are read.

±5% Re-test; check low battery 

indicator; use a different 

meter; use different 

standards; repeat 

measurement
251

Parameter Calibration Frequency Acceptance 

Criteria

Corrective Actions

Dissolved 

oxygen

Prior to field mobilization, at the 

field site, and calibration check at 

day’s end

±10% Re-enter altitude; re-test; 

check low battery indicator; 

check membrane for 

wrinkles, tears or air bubbles; 

replace membrane; use a 

different meter; repeat 

measurement

Eureka Manta 

Multiprobe 

datalogger

Beginning and end of each 

deployment

See manual

pH meter Prior to field mobilization (three 

point calibration using buffer 

solutions (pH 4,7, and 10)) 

At the field site, and calibration 

check at day’s end (one point 

calibration) 

10% of all reading taken each day 

must be duplicated or a minimum 

of 1 reading if fewer than 10 

samples are read. 

±0.2 pH 

unit;

±0.2 pH unit

RPD ±0.1 

pH unit

Re-test; check low battery 

indicator; use different 

standards; repeat 

measurement

Flow meter 

(velocity meter)

Prior to field mobilization, before 

each sampling run; some flow 

meters required and annual 

calibration by the manufacturer

-All instrument should be visually inspected before use

-Check batteries before use

-Rinse all equipment after use

-Insure that pH electrodes and D.O. membrane remain moist

4.5.8 Inspection/Acceptance Requirements For Supplies And Consumables

Not Applicable.

4.5.9. Data Acquisition Requirements (Non-direct Measurements)

Water quality monitoring data from sources other than this WRD-funded monitoring plan will 

not be entered directly into the SFAN version of NPSTORET. However, other monitoring 

entities will be encouraged to collect appropriate metadata so that their data can be used by other 

entities and most likely by this program. Other groups will be encouraged to upload their data to 

the National version of STORET. SFAN can then use this data if it can be used to help answer 

monitoring questions for existing sites or will help fill in data gaps that this program cannot 

cover. In addition, other data collected by SFAN monitoring programs (e.g., weather and stream 

hydrology data) will be utilized in conjunction with the water quality data.
252

4.5.10 Data Management

A general overview has been provided in sections A6 (Project /Task Description) and A9 

(Documents and Records). Data management is covered in detail in the SFAN Freshwater 

Quality Protocol Narrative including database structure and metadata requirements. SFAN 

personnel will work closely with WRD regarding use of, and modifications to the NPSTORET 

database. 

4.6 Assessment and Oversight

4.6.1 Assessments and Response Actions

Field staff will sometimes be required to work independently, though ideally there will be two 

individuals in the field. Having two individuals not only is a safety measure, but can also serve 

as a quality control measure. In most cases, the primary individual conducting monitoring will 

be the SFAN Water Quality Specialist who has the dual role of Project Leader and Quality 

Assurance Manager. Additional field assistants may be park or SFAN staff or volunteers as 

available. If problems in field sampling arise, the water quality specialist will determine whether

sampling should be re-scheduled or sampling equipment/methods modified. Records will be 

kept of all quality control issues and corrective actions.

If site conditions or method improvements/modifications require protocol revision, the Project 

Leader will discuss these changes with field crew and document protocol revision (see SOP 1: 

Revising the Protocol). If major changes are warranted, the SFAN Aquatic Professionals group 

will meet to discuss recommended changes. Final revisions to the QAPP will be approved by the 

SFAN Aquatic Professionals Group and WRD. If necessary, a group of local technical experts 

(the same group, if possible, as the external peer review team) will meet to discuss methods 

issues.

4.6.2 Reports to Management

Annual summary reports will be provided to WRD and to individual parks by October 30 of each 

year. Additionally, comprehensive reports will be created every three to five years for more 

detailed analysis including trends. These reports will include data from 2-4 years since 

watersheds are monitored on a two-year rotating basis. These comprehensive reports will be 

provided to WRD and to the individual parks with data analysis customized for the individual 

parks. The comprehensive reports will include a Quality Assurance Report explaining the results 

of data completeness and other QA/QC issues.
253

4.7 Data Validation and Usability 

4.7.1 Data Review, Verification, and Validation Requirements

The EPA has recently provided a comprehensive guidance document (EPA 2001), entitled 

Guidance on Environmental Data Verification and Data Validation (EPA QA/G-8). The purpose 

of this guidance is to explain how to implement data verification and data validation, and to 

provide practical advice and references. Although data verification and data validation are 

commonly-used terms, they are defined and applied differently in various organizations and 

quality systems. The Surface Water Ambient Monitoring Program (SWAMP) follows EPA's 

informal guidance on this topic, as provided in EPA 2001, and incorporates the following 

definitions (from Puckett, 2002):

Data Verification is confirmation that what has been entered into the database is what is 

actually on the datasheets. Data verification is the process of evaluating the completeness, 

correctness, and conformance/compliance of a specific data set against the method, procedural, 

or contractual requirements (Puckett, 2002).

Data Validation is an ―analyte-and sample-specific process that extends the evaluation of data 

beyond method, procedural, or contractual compliance (i.e., data verification) to determine the 

analytical quality of a specific data set‖ (Puckett, 2002). In other words, data validation is the 

final step in assuring the accuracy of data transfer from raw to digital form. Questionable data 

are identified, reviewed, and corrected if necessary. Automatic validation that checks the data as 

it is entered will also occur. These automatic validations are programming elements that 

―censor‖ the data based on known ranges. Therefore the data manager would not be allowed to 

enter data that is invalid or nonsense such as 16 for pH or a date in the future. Through this 

process, outliers are identified. Examples of common errors are missed decimal places, 

numerical data placed in the wrong field (for example, the database shows a pH of 12 when 12 is 

actually the water temperature). Outliers can be identified through simply graphing all 

observations for a given station and parameter or graphing all station data together if there is 

only low to medium variability.

4.7.2 Validation and Verification Methods

All data reported for the SFAN Water Quality Monitoring Program will be subject to checks for 

errors in transcription, calculation, and computer input. Field data are initially validated by data 

graphing and recognition of outliers needing verification. These checks are described in the 

protocol narrative and in section A9. 

All laboratory data forms must be accurate and complete. Any changes to the data forms will be 

noted, initialed and dated on the form. Any actions taken as a result of the data review will also 

be noted on the data sheet (Puckett, 2002).
254

4.7.3 Reconciliation with Data Quality Objectives

Any data that do not meet DQO will not be used. If data quality issues arise, a determination 

will be made on whether the error was caused by equipment failure or operator error. If 

additional staff training, equipment repair, or minor revisions to the protocol or SOPs do not 

correct the problem, then the DQOs will be re-evaluated for feasibility of attainment. If they are 

determined to be unattainable, then they will be modified or the use of the parameter(s) in 

question will be evaluated. In some cases, a parameter may be eliminated if no 

reasonable/acceptable DQOs can be attained (Ward, 2004).

4.8 References

American Public Health Association (APHA), American Water Works Association, and Water 

Environment Federation. 1998. Standard Methods for the Examination of Water and 

 Wastewater (18th edition), American Public Health Association, Washington, D.C.

California Department of Water Resources. 1998. Guidelines for preparing quality assurance 

project plans. Sacramento.

Helsel, D. 2005. Nondetects and Data Analysis: Statistics for Censored Environmental Data. 

Wiley. 288 pp., http://www.wiley.com/WileyCDA/WileyTitle/productCd0471671738.html

Irwin, R.J. 2006. Draft Part B Lite (Just the Basics) QA/QC Review Checklist for Aquatic Vital 

Sign Monitoring Protocols and SOPs, National Park Service, Water Resources Division. 

Fort Collins, Colorado, distributed on Internet only at: 

http://www.nature.nps.gov/water/Vital_Signs_Guidance/Guidance_Documents/PartBLite

.pdf

Irwin, R. 2004. Vital Signs Long-Term Aquatic Monitoring Projects: Part B – Planning Process 

Steps: Issues to Consider and then to Document in a Detailed Study Plan that Includes a 

Quality Assurance Project Plan (QAPP) and Monitoring ―Protocols‖ ( Standard 

Operating Procedures). National Park Service, Water Resources Division. 

Puckett, M. 2002. Quality Assurance Management Plan for the State of California's Surface 

Water Ambient Monitoring Program ("SWAMP"). California Department of Fish and 

Game, Monterey, CA. Prepared for the State Water Resources Control Board, 

Sacramento, CA. 145 pages plus Appendices.

U.S. Environmental Protection Agency. 2001. Environmental Monitoring and Assessment 

Program (EMAP): National Coastal Assessment Quality Assurance Project Plan 2001-

2004. United States Environmental Protection Agency, Office of Research and 

Development, National Health and Environmental Effects Research Laboratory, Gulf 

Ecology Division, Gulf Breeze, FL. EPA/620/R-01/002.

U.S. Environmental Protection Agency. 1999. EPA requirements for quality assurance project 

plans (EPA QA/R-5) U.S. EPA Quality Staff (2811R). Washington, DC. 

U.S. Environmental Protection Agency. 2001. Guidance on environmental data verification and 

data validation. QA/G-8.

Wagner, R.J., Boulger, R.W., Jr., Oblinger, C.J., and Smith, B.A., 2006, Guidelines and standard 

procedures for continuous water-quality monitors—Station operation, record 
255

computation, and data reporting: U.S. Geological Survey Techniques and Methods 1-D3, 

51p. + 8 attachments; accessed April 10, 2006, at http://pubs.water.usgs.gov/tm1d3

Ward, K. 2004. Crissy field restoration area monitoring program quality assurance project 

plan (draft). Golden Gate National Recreation Area. 

Welch, B. 2003. San Francisco Bay Area Network Phase II Vital Signs Monitoring Plan. U.S. 

Department of Interior, National Park Service. 
256

SOP #4 Appendix A. Field Data Sheet – Stream Site 
257

SFAN Water Quality Monitoring Program

Field Data Sheet – Stream Site

Station ID: ____________________________ 

Site Location: 

_____________________________________

Date:_________________________________

Time:____________________________PST_

Field Crew ____________________________________

* Take 7 measurements at the beginning of each quarter (Oct., Jan., April, July) to obtain standard deviation for calculating

PQL

** Actual, Calculated, Estimated (Cross out and enter in notes if different from default)

***Note duplicated field measurement values (QA); any equipment issues or observations.

Field Conditions: 

__________________________________________________________________________________________________

______________________________________________________________

Time since last significant rainfall:____________

Notes 

__________________________________________________________________________________________________

______________________________________________________________

________________________________________________________________________________

Flow measurement taken? ______ Flow Severity: □1none □2 low □3 normal □4 flood □5 high □6 dry

Lab Samples taken? (which?)_________________________________________________________

Photographs taken? _______

Stabilization Criteria:

Temp: Thermistor = ±0.2oC

Thermometer = ±0.5oC

Specific Conductivity:

When ≤ 100μS/cm = ±5%

When > 100μS/cm = ±3%

pH: = ±0.1 SU

DO: Amperometric method = ±0.3 mg/L

Parameter *Measurement Units **Value 

Type

Instrument Notes***

Air Temperature oC Actual

H20 Temperature oC Actual YSI 85

Conductivity μS/cm

mS/cm

Actual YSI 85

Specific 

Conductance

μS/cm

mS/cm

Actual YSI 85

Salinity ppt Actual YSI 85

Dissolved 

Oxygen

% Actual YSI 85

Dissolved 

Oxygen

mg/L Actual YSI 85

pH S.U. Actual Oakton

Flow cfs Calculat

ed

Turbidity NTU Actual Hach 2100
258

Entered into NPSTORET□

 Validated □
259

SFAN Water Quality Monitoring Program

Field Data Sheet For Flow Measurements

Station ID ______________________

Site Location 

_____________________________________

Date ____________Time ____________PST

Field Crew ________________________

Flow Instrument:____________________

Flow Measurements:

Gage Height __________ ft

Bed Level __________ ft

Stream Width __________ ft

Begin Time________PST/ Begin Gage Height_________ft End Time________PST / End Gage 

Ht________ft

Station (ft) Depth (ft) Velocity (ft/s) Average V Cumulative Q

REW:

LEW:

V – velocity Q – discharge
260

Notes from USGS Flow Measurement Methods:

 For shallow depths, use 6/10 method

 For deep depths (> 1.5 ft) use the 2/10 and 8/10 method

To get 2/10 depth multiply 6/10 depth by 2

To get 8/10 depth divide 6/10 depth by 2

 Space the verticals so that no sub-section has more than 10% (ideally 5%) of the discharge

 There should be 20-30 sub-sections

 Keep the first sub-section as small as possible (depth will often be zero and assume no flow)

 Streambed should be free of large rocks, obstructions

 Parts of the stream cross-sections with greater depth and velocity should have closer verticals

 Face the bank while taking measurement (stand beside not behind wading rod)

 Position yourself at least 18’ from the wading rode

 Measure velocity for at least 40 seconds

 Check the meter during measurement

 Have an idea what the discharge will be before measurement

 Read gauge height after measurement

 Reach should be straight and uniform; measure downstream of riff
261

SOP #5 Field Methods for Measurements of Core Parameters

5.1 Revision History Log

Prev. Version 

#

Revision Date Author Changes Made Reason for 

Change

New Version 

#

1.0 08/05/05 Mary Cooprider Minor edits Preparation for 

formal peer review

1.01

1.01 3/7/06 Rob Carson Minor edits and 

updates of text 

and tables

Addressing peer 

reviewer comments

1.02

1.02 8/1/06 Rob Carson Updated 

continuous 

monitoring

guidelines with 

Wagner, et al 

2006.

Release of USGS 

report, and 

purchase of new 

equipment.

1.03

Only changes in this specific SOP will be logged here. ―Version numbers increase incrementally 

by hundredths (e.g. version 1.01, version 1.02 ...etc) for minor changes. Major revisions should 

be designated with the next whole number (e.g., version 2.0, 3.0, 4.0 ...). Record the previous 

version number, date of revision, author of the revision, identify paragraphs and pages where 

changes are made, and the reason for making the changes along with the new version number‖ 

(Peitz et al, 2002).

5.2 Acknowledgements

Several SOPs and guidance documents were utilized to develop this SOP. Much of the content 

of this SOP originated in one or more of the following documents:

 Penoyer, P. 2003. Vital Signs Long-Term Monitoring Projects: Part C, Draft Guidance 

on WRD Required Parameter Measurements, General Monitoring Methods and some 

design considerations in Preparation of a Detailed Study Plan (Work in Progress); 

National Park Service – Water Resources Division 

http://science.nature.nps.gov/im/monitor/protocols/wqPartC.doc . 

 Puckett, M. 2002. Quality Assurance Management Plan for the State of California's 

Surface Water Ambient Monitoring Program ("SWAMP"). California Department of 

Fish and Game, Monterey, CA. Prepared for the State Water Resources Control Board, 

Sacramento, CA. 145 pages plus Appendices.

 Wilde, F.D. and Radtke, D.B., eds., chapter sections variously dated, Field 

Measurements: U.S. Geological Survey Techniques of Water-Resources Investigations, 

book 9, chap. A6, available online at http://pubs.water.usgs.gov/twri9A. National field 

manual for the collection of water-quality data (USGS Techniques of Water-Resources 

Investigations Book 9, Chapter A1-A9)
262

 Shelton, L. 1994. Field Guide for Collecting and Processing Stream-Water 

Samples for the National Water Quality Assessment Program. Open-File Report 

94-455. U.S. Geological Survey, Sacramento, CA.

Standard operating procedures from other parks were also followed including SOP#5 –

―Procedures for Collection of Required Field Parameters‖ from the Greater Yellowstone 

Network (O’Ney, 2005) and water quality SOPS from the Crissy Field Restoration Area 

Monitoring Plan (Presidio of San Francisco) (Ward, 2004). 

5.3 Scope and Application

5.3.1 Core/Required Parameters

The Freshwater Workgroup Subcommittee of the National Park Service – Water Resources 

Division provided recommendations for required water quality monitoring parameters (National 

Park Service, 2002). These include:

1) Temperature

2) Specific conductance

3) pH

4) Dissolved oxygen

These parameters are considered the ―core‖ parameters for the SFAN Freshwater Quality 

Monitoring Protocol. These parameters are interrelated and describe the basic water chemistry. 

They are the first indicators of water quality and typically the simplest to measure. If one or 

more of these parameters is out of the normal range for a particular stream or does not fall within 

water quality criteria limits, then concern is raised. The degree of concern is related to the 

extent that the parameter exceeds criteria or typical ranges and the duration of the exceedence. A 

one-time exceedence could indicate an episodic pollutant event or an error in measurement. The 

objective of this SOP is to reduce the possibility of the latter being an option. 

Thorough knowledge of these core parameters is also needed in order to better understand or 

explain levels of other parameters such as nutrients and bacteria. An overview of past 

monitoring for these core parameters is provided in the SFAN Preliminary Water Quality Status 

Report (Cooprider, 2004). This includes background information on factors affecting the core 

parameters as well as their typical ranges in SFAN streams. Water quality criteria for these 

parameters are discussed in the protocol narrative. These criteria will be referenced during data 

analysis procedures (SOP #10). The core parameters are discussed in greater detail in ―Vital 

Signs Long-Term Monitoring Projects: Part C, Draft Guidance on WRD Required Parameter 

Measurements, General Monitoring Methods and some design considerations in Preparation of a 

Detailed Study Plan‖ (Work in Progress) August 6, 2003 Draft Update (Penoyer, 2003). 

The Water Resources Division (WRD) has also noted the importance of flow/discharge 

measurements, biomonitoring, and alkalinity measurements. The first parameter, 

flow/discharge, is a critical component of the SFAN Freshwater Quality Monitoring Protocol. 

The second important parameter, biomonitoring, was included in the list of SFAN Vital Signs 
263

but not chosen as a priority indicator. However, recent aquatic bioassessment data exists for 

many of the SFAN streams. Results of on-going data analyses should provide insight for future 

possible aquatic bioassessment through the long-term monitoring program. Existing aquatic 

macroinvertebrate data will provide a baseline for future monitoring efforts. WRD also listed 

alkalinity as an important indicator. However, it is not an issue in the Bay Area streams since 

they are well-buffered. Lendvay and Benning (2004) provide a good example of this buffering 

in Redwood Creek (GOGA). 

5.4 Measurement Procedures

Details of measurement procedures will focus on the use of a waterproof electronic pH meter and 

a multiparameter probe to measure temperature, specific conductance, and dissolved oxygen. 

Calibration procedures for these instruments are discussed in SOP#3. COMPLETE THESE 

CALIBRATION TASKS BEFORE PROCEEDING. Flow measurements will be discussed in 

SOP #9. 

Because there can be significant diel variation in some of the core parameters (temperature, pH 

and dissolved oxygen in particular), the sites will be visited in the same order during each 

sampling trip in order to ensure that visits will fall into the same two-hour window (wherever 

possible) to minimize the effect of diel variation on single site variability over the long-term 

monitoring project. An effort will be made to collect data on the natural diel range of these 

parameters at particular sites through the use of datalogger probes or through synoptic data 

collection across sites or across the diel (24-hour) period. This would allow cross-calibration of 

values between those collected at some sites in the morning, and others that are regularly visited 

in the afternoon.

The following steps provide an overview of field collection techniques for the core parameters:

Details to be covered include:

 Equilibration of instruments with ambient water

 Location of sensor/probe within sample site

 Measurement techniques for flowing water (riffles or glides/runs) vs. standing water (pools)

 Location of sensor/probe in water column (obtaining a vertical profile)

 Tips for measuring each parameter

 Monthly/weekly and continuous monitoring

5.4.1 Monthly/Weekly Monitoring 

Steps in Collection of Field Measurements: 

1. Test and calibrate field equipment (SOP #3); clean with deionized or distilled water before 

each measurement

2. Obtain a flow measurement at the cross-section where samples are to be collected (SOP #9)

3. Locate the centroid of flow if sampling in a riffle or run/glide

4. Collect water samples for nutrients, bacteria, and sediment (SOPs #6-8)

5. Allow sensors to equilibrate with ambient water while samples are collected (2 minutes)

6. Complete general information on field data sheet
264

7. Collect a vertical profile of field measurements

8. Monitor field measurement readings (take mean of readings over 1 minutes, ending with 

dissolved oxygen)

9. Report the mean value

10. Clean the sensor with deionized or distilled water after taking the measurement

5.4.1.1 Sampling in Riffles/Runs (Centroid of Flow Method)

Standard Operating Procedure #9 for flow/discharge measurements should be followed first. 

Collect field measurements at the centroid of flow. The centroid is the midpoint of that portion 

of the stream width that contains 50% of the total flow. This is calculated in the field by adding 

a ―cumulative discharge‖ column to the flow field sheet. The San Francisco Bay Regional Water 

Quality Control Board’s SWAMP project uses the centroid of flow method (Puckett, 2002). If 

the stream is well-mixed with relatively uniform discharge, then the centroid of flow method can 

be used (Wilde et al., 1999).

If taking measurements in the centroid of flow has the potential to compromise safety, then either 

wade only to a safe distance or take measurements from the bank. Do not attempt to wade in a 

stream for which values of depth multiplied by velocity are greater than or equal to 10 ft2/s. For 

example, a stream only 2 ft deep but with velocities of 5 ft/s or more can be dangerous to wade.

5.4.1.2 Sampling in Pools

Many of the monitoring questions require sampling in both flowing and still habitats within the 

stream. For still habitats (pools) the location and number of measurements points depends upon 

the specific monitoring questions listed in Appendix D of the Protocol Narrative. The USGS 

National Field Manual indicates that for still waters ―measurements made at discrete depths 

through the vertical water column must not be averaged or reported as a median value.‖ Pools in 

SFAN streams and tributaries indicated in the protocol narrative can be up to 3 feet deep during 

the dry season (May-October) and much deeper during the wet season (November-April). 

General guidelines for taking field measurements in pools:

The USGS recommends that if a pool is shallow (< 1 ft), take measurements at a middle depth. 

If the pool is from 1-4 ft deep collect measurements just below the surface, just above the stream 

bottom (taking care not to bury the probe in sediments) and at a location between the two (Wilde 

and Radke, variously dated). This can be done for the core parameters buts not for laboratory 

analytes because it would be cost prohibitive.

5.4.1.3 Equilibration & Stabilization of Sensors

 If water samples are to be collected, then leave the multiparameter probe in the water to 

equilibrate while samples are collected. Before recording a field measurement, the sensors 

must equilibrate to the water temperature at the sampling site. Allow a minimum of two 

minutes for the YSI 85 (multi-parameter probe) to equilibrate to the ambient water 

temperature. Equilibrate in the D.O, mode (Puckett, 2002). Equilibration has 

been achieved when the variability among instrument readings has stabilized according to the 

criteria in 5.1.
265

 The natural variability of surface water typically falls within the ranges listed in the table. 

Therefore, if the instrument is calibrated properly (see SOP #3) then these stabilization 

criteria should be met. 

 Sensors have equilibrated adequately when instrument readings have stabilized, that is, when 

the variability among measurements does not exceed an established criterion. For surface 

waters, allow at least 60 seconds (or follow manufacturer’s guidelines) for sensors to 

equilibrate, and then take instrument readings until the stabilization criteria in Table 5.1 are 

met. Record the median of the final three or more readings as the value to be reported for that 

measurement point.

 For sites at which variability exceeds the criteria of Table 5.1; allow the instrument a longer 

equilibration time and record more measurements. To determine the value to be reported for 

that measurement point, use either the median of the final five or more measurements 

recorded, or apply knowledge of the site and professional judgment to select the most 

representative of the final readings. Be sure to note how the measurement was 

selected in the field notes (Wilde et al., 1999). 

 Allow at least 1 minute for sensors to equilibrate with the water. Obtain readings until the 

stabilization criteria are met. Record the median of the final three or more readings (Wilde et 

al., 1999).

 If the variability in measurements exceeds the criteria listed in the table, allow a longer 

equilibration time for the instruments. To select a final reading for the site, use the median of 

the final five or more measurements recorded or use knowledge of the site and professional 

judgement to select the most representative final readings (Wilde et al., 1999). 

 In order to be efficient, water samples can be collected while the sensors are equilibrating. 

Leave the multi-parameter probe in the water to equilibrate while samples are collected. 

Field measurements are generally taken in the same location as water samples are collected 

(Wilde et al., 1999). Ch. 6
266

Table 0.1 Measurement Stabilization Criteria (core parameters) (from USGS National Field 

Manual) and WRD recommended instrument stabilization criteria for recording field 

measurements. Note the units to be used and recommended calibration frequencies.

Standard Direct 

Field Measurement

Stabilization Criteria 

For Measurements

(variability/repeatability should be within the value 

shown)

1Temperature:

Thermistor Thermometer

Liquid-in-glass Thermometer

 0.2C

 0.5C

2Conductivity (Specific Cond.)

When  100 S/cm

When > 100 S/cm

 5 percent

 3 percent

3

pH:

Meter displays to 0.01  0.1 unit

3Dissolved oxygen:

Amperometric method  0.3 mg/L

** Resolution/Sensitivity is a data quality indicator related to detection limits but typically 

handled differently for field probes than for laboratory parameters. For more information, see 

Part B (http://science.nature.nps.gov/im/monitor/protocols/wqPartB.doc) (Irwin, 2004).

***In the case of field probes, accuracy is typically a ―best case‖ maximum deviation from 

known correct values (typically based on comparisons with known NIST certified reference 

materials or standards). True accuracy is a combination of high precision and low bias (see Part 

B for more details).

1 Recommended frequency of sensor calibration checks is quarterly

2 Recommended frequency of sensor calibration is daily

3 Recommended frequency of sensor calibration is at beginning and end of sampling at each 

station (twice a day minimum) 

5.4.1.4 Field Observations 

Note the field conditions and general observations on the data sheet in Appendix A. Note the 

general field conditions including time of day, rain/no rain, rising/falling limb of hydrograph, 

watercolor, runoff conditions, etc. Also note the land use or any situations out of the ordinary. 

This data may be useful particularly if unusual parameter readings are observed.

Site information to record includes: 

 Site ID, date, time, field personnel

Field observations to record include: 

 Weather: Time since last rain, current heavy rain, dry, cold, etc.

 Water color and other characteristics: Unusual amount of suspended solids, debris, foam 

 Biological activity: Note excessive macrophyte (plants), phytoplankton (microscopic floating 

aquatic plants) or periphyton (microscopic plants and animals firmly attached to aquatic 

substrate) growth and the presence of birds, fish, and spawning fish

 Water odors-sewage, hydrogen sulfide

 In-stream activities-bridge construction, mowing near the stream, livestock watering upstream, 
267

etc.

 Beneficial uses – swimming, wading, irrigation pumps, etc.

5.4.1.5 Field Measurements

1. Stand downstream of sensors to reduce/eliminate affects of streambed disturbance and/or 

potential cross-contamination from other sites. Cross-contamination can also be avoided by 

rinsing field boots as well as the sensors.

2. Go to the centroid of flow as determined above. Obtain measurements directly from the 

water body by immersing the multiprobe instrument. Allow to equilibrate for at least two 

minutes before measurements are recorded. 

3. Measure at multiple depths within the vertical containing the centroid of flow or within the 

pool as outlined in Table 5.2. 

4. Monitor field measurement readings (take mean of readings over 1 minute, ending with 

dissolved oxygen). The value recorded will be the mean of values observed within 1 minute 

after the sensor has equilibrated.

5. Measure at multiple depths in the vertical. The value recorded at the vertical represents the 

mean of values observed within approximately 60 seconds after sensor(s) have equilibrated 

with stream water. Record DO last.

6. The final field-measurement value is the mean of the in situ value for the vertical. The mean 

of pH is calculated as below (see tips for pH measurement)

Depth-integrating and width-integrating sampling methods can be used to collect and composite 

samples that can then be sub-sampled (e.g. using a churn splitter) for some field measurements. 

The same field measurements can also be performed on discrete samples collected with thief, 

bailer, or grab samplers. These samples can yield good data for conductivity, pH, turbidity, and 

alkalinity as long as correct procedures are followed and the water is not anoxic. Do not measure 

temperature or DO on subsamples.

Table 0.2 Recommended Depths for Conducting Field Data Measurements (from Puckett, 2002).

Depth Notes

Water Depth Less than 5 feet 

(<1.5m)

If the water depth is less than 5 feet (1.5m), multi-probe measurements are 

taken at approximately 0.2m (8 in). 

Water Depth Greater than 5 feet 

(>1.5m)

If the water depth at the sampling point exceeds 5 feet (1.5m) in depth, a 

vertical profile of dissolved oxygen, temperature, pH and specific 

conductance are made using the multiparameter probe equipment. *NOTE: 

for most SFAN streams, if the depth is > 5 ft, then the discharge is too great 

to safely and accurately obtain a vertical profile. 

Vertical Depth Profiles and DepthIntegrated Sample CollectionIf vertical profile measurements are being conducted, multi-probe 

measurements are made starting at a depth of 0.2 m (8 in), and are then 

conducted at 1.0 m (3.28 ft) depth intervals. 
268

5.4.1.6 Parameter Specific Details and Tips for Measurement

Temperature (C):

 As a back-up procedure, temperature can be measured with a hand-held, centigrade 

thermometer.

 In wadeable streams, stand so that a shadow is cast upon the site for temperature 

measurement.

 Hold the thermometer by its top and immerse it in the water. Position the thermometer so 

that the scale can be read.

 Ensure that the temperature sensor is completely submerged in the water. Temperature 

readings made with digital instruments are accurate to within ± 0.1° C. 

 Air temperature

 Read air temperature with a dry, calibrated thermometer.

 Place the thermometer about 5 ft above the ground in a shaded area protected from strong 

winds but open to air circulation. Avoid areas of possible radiant heat effects, such as 

metal walls, rock exposures, or sides of vehicles.

 Allow 3 to 5 minutes for the thermometer to equilibrate, and then record the temperature 

and time of day.

 Measure the air temperature as close as possible to the time when the water temperature 

is measured.

 Report routine air temperature measurements to the nearest 0.5°C. 

pH (S.U.):

 ―Is the value real or is the instrument out of calibration?‖ Avoid having to guess at an 

answer by having pH standards in the field to help verify values that fall outside the 

expected range. For example, the expected pH is around 7.0 and the reading is 9.5. A 

known standard can be put in the instrument storage cup to determine if the instrument is 

reading correctly or out of calibration.

 If the pH meter value does not stabilize in several minutes, out gassing of carbon dioxide 

or hydrogen sulfide, or the settling of charged clay particles may be occurring (Rawson, 

1982).

 If out gassing is suspected as the cause of meter drift, collect a fresh sample, immerse the 

pH probe and read pH at one minute.

 If suspended clay particles are the suspected cause of meter drift, allow the sample to 

settle for 10 minutes, and then read the pH in the upper layer of sample without agitating 

the sample.

 In low-ionic strength water (<50μS/cm) the pH measurements may not stabilize and a 

mean or median value must be taken from a range covering several tenths of pH units 

(Penoyer, 2003). 

 To average pH measurements, the pH values must first be converted to the antilog, and 

average value computed, then converted back to the log value.

To compute a mean pH for the stream:

- Convert each pH value to hydrogen-ion activity, using the equation, Activity = 

 10-(pH).

- Calculate the mean of the activity values by adding the values and dividing the 

sum by the total number of values.
269

- Convert the calculated mean activity back to pH units, using the equation, pH =

 (-) (log10)(mean H+ activity).

Specific Conductance (uS/cm) and Conductivity (uS/cm)

 As with pH measurements, having specific conductance standards in the field can help 

verify values that fall outside the expected range. For example, the expected specific 

conductance is around 200 and the reading is 1500. A known standard can be put in the 

instrument storage cup to determine if the instrument is reading correctly or out of 

calibration.

 Be sure to note the units as conductivity may range from uS/cm to mS/cm.

  A common physical problem in using a specific conductance probe (or meter) is 

entrapment of air in the conductivity probe chambers. The presence of air in the probe is 

indicated by unstable specific conductance values fluctuating up to + 100 micro-

 siemens/cm (uS/cm). This can be minimized by slowly, carefully placing the probe into 

the water; and when the probe is completely submerged, quickly move it through the 

water to release any air bubbles.

  For specific conductance, the degrees C is flashing; for conductivity it is not flashing. 

Specific conductance is the conductance measured at 25C. Since conductivity varies 

with temperature, it should always be reported as specific conductance.

 Always rinse the conductivity cell with clean water after each use (YSI Inc., 1998)

 Record the ―raw‖ measurement (all digits). When reporting to STORET, round to the 

nearest two or three significant figures (if the value exceeds 100). If the value exceeds 

1000, record to four significant figures. 

Dissolved Oxygen (mg/L and % saturation):

 Check the sample location sheet for site elevation; calibrate the YSI 85 meter (oxygen 

probe) for elevation. Keeping the probe in its calibration (storage) chamber, press 

―mode‖ until one of the oxygen parameters appears on the screen. Then, press the down 

and up arrows simultaneously. The screen should have a single large number, then ―alt x 

100‖ in the right-hand corner. For an elevation of 400 ft select 4, then press ―Enter‖. 

Wait for the resading to stabilize, then press ―Enter‖ again to accept the calibration value. 

See the YSI 85 manual for detailed instructions (YSI, Inc. 1998). 

 The DO measurement typically takes the longest to stabilize (Penoyer, 2003). This may 

take 5-15 minutes in some cases depending upon the water body and the instrument. 

Record this parameter after temperature, conductivity, and pH. 

 Since dissolved oxygen takes the longest to stabilize, if the electronic DO meter is not 

functioning properly, DO can be measured by Winkler titration (Eckblad, 1978). The 

Winkler titration procedure is described in Appendix B.

 The sensor must be moved back and forth if placed in still water since the sensor 

consumes oxygen. YSI (1998) recommends that the sensor be moved through the 

sample at a rate of 1 ft/s to provide sufficient stirring. If the stream velocity at the 

sampling point exceeds 1 ft/s, the probe membrane can be pointed upstream into the flow 

and manual stirring can be avoided (Rawson, 1982).

 The probe should never be allowed to penetrate the sediments, especially when DO is 

low. If the probe does accidentally hit anoxic sediments it should be allowed to re-
270

equilibrate at least a minute before readings are resumed.

Oxygen meters use a polarographic electrode to measure the dissolved oxygen concentration in 

water. The instrument senses the partial pressure of oxygen at the surface of the membrane, 

rather than the actual concentration of oxygen (weight/volume). The relationship between partial 

pressure and concentration is dependent upon atmospheric pressure and temperature when a 

reading is made in the air (i.e., during the air calibration procedure), whereas, the equilibrium 

solubility of oxygen in water is influenced by temperature, salinity, and pressure (of the gaseous 

phase) (Puckett, 2002). Corrections for these factors must be made either by the instrument, by 

the user during calibration or after readings are taken. The Winkler titration directly measures 

oxygen equivalents and reports dissolved oxygen concentration (weight/volume) in a form that 

requires no corrections.

5.4.2 Continuous Monitoring 

This section described methods for using an in-situ datalogger, or continuous multi-parameter 

probe to gather core parameter values from SFAN freshwater streams. Comprehensive 

guidelines and standard operating procedures for continuous water-quality monitors can be found 

in the USGS Techniques and Methods paper #1-D3 (Wagner, et al. 2006), available online at: 

http://pubs.usgs.gov/tm/2006/tm1D3/pdf/TM1D3.pdf. The procedures in this report should be 

followed for station operation, equipment calibration, and maintenance of continuous meters 

wherever possible. Included below is a brief outline of the use of one such instrument.

The specific procedure below is for the Eureka Environmental Manta® multiprobe. The Manta® 

can record data for temperature, conductivity, dissolved oxygen, and pH as well as two 

additional parameters (with additional sensors) continuously over the length of deployment. 

The entire user’s manual can be found on-line at: 

http://www.eurekaenvironmental.commanta/documents/Manta.pdf

SFAN will employ a continuous probe such as this one which will be moved from watershed to 

watershed on a rotating basis for Olema, Pine Gulch, Redwood, Tennessee Valley, Rodeo, 

Franklin, and Chalone Creek in order to collect diel and seasonal variation of physical and 

chemical parameters at key sites. The continuous probe will be rotated through watersheds, 

including extended deployment at a single stream site, or rotated to different sites in the same 

priority stream. Deployments in each priority stream will last a minimum of two weeks, and 

rotations will continue through the watersheds in the current panel year-round so that each 

priority stream has a minimum of two weeks of continuous data during each season. This will 

allow for a characterization of diel and seasonal variation of core parameters at particular sites in 

priority streams.

The continuous datalogger will most likely be placed near the streambank in order to be properly 

secured. The standard procedure is to deploy the data logger 1ft below the surface. However, 

the location of the logger will be dependent on the monitoring questions and the depth of the 

stream. Since the logger probes must remain fully submerged throughout the year, the location 

of the logger is often limited to the deepest part of a pool in smaller streams or to a part of a 
271

perennial stream with a sufficient water depth to cover the probes. Regular maintenance and 

calibration requirements dictate how long the logger stays in place. 

The continuous datalogger should be left in place for 2 weeks. Leaving it in place for longer than 

3 weeks is not recommended since biofouling is likely to occur (Hydrolab Corporation, 1998). 

After two weeks field personnel should perform the following standard protocol, using the 

USGS Continuous WQ Monitor Field Form in Appendix C of SOP #3: Equipment and Field 

Preparations. 

Standard protocol for the operation and maintenance of a continuous water-quality 

monitor (Modified from Wagner et al (2006))

7. Conduct site inspection

 Record monitor readings, time and monitor conditions

 With an independent field meter, observe and record readings and time near 

the continuous sensor(s)

8. Remove sonde from the monitoring location

9. Clean Sensors

10. Return sonde to the monitoring location

 Record monitor readings and time

 Using an independent field meter, observe and record readings near the 

sensor(s)

11. Remove sonde, rinse thoroughly, and check calibration

 Record calibration-check values

 Recalibrate if necessary (i.e. values are outside the calibration criteria)

12. Return sonde to monitoring location

 Record monitor readings and time

 Using an independent field meter, observe and record readings near the sensor

Datalogger cleaning, calibration, and downloading should be conducted according to the 

manufacturer’s recommendations (Eureka Environmental 2006). Details of these steps are 

included in SOP #3. 

Notes on Continuously Recorded Temperature (from the USGS National Field Manual)

The USGS defines three temperatures of concern when monitoring continuous stream 

temperature: true stream temperature (TST), temperature near sensor (TNS), and temperature 

recorded (TRC) (Stevens et al., 1975). Ideally, all three of these temperatures would be the 

same; however this is not always the case. The true stream temperature is defined as an 

instantaneous measurement obtained in a shaded location in the main flow of the stream outside 

of the influence of tributaries or groundwater influx with a full immersion thermometer 

calibrated against an ASTM standard thermometer. It can also be calculated as the weighted 

average of a cross-section temperature profile. For reasons of safety and convenience, sensors 

for stream temperature recorders are often placed closer to shore than would represent true 

stream temperature (Essig, 1998). The actual temperature of the water surrounding the sensor 

reflects its position in the channel cross-section, and is known as the temperature near sensor 

(TNS). Whether it is the same as the TST may vary depending on flow and time of day (Essig, 
272

1998). The temperature recorded (TRC) is the measurement read and recorded. If the 

thermometer or sensor has been calibrated, then TRC can be adjusted to TNS.

5.5 Data Management

The SFAN Freshwater Quality Protocol Narrative as well as the overall Data Management Plan 

should be consulted for a thorough review of data management procedures. A summary of data 

management tasks is below.

 Record and verify observed or measured data values. This includes completing paper 

forms and entering data into NPSTORET and/or other electronic databases. 

 Schedule and perform regular data transfer and backup. 

 Conduct regular data verification and correction 

 Ensure that field forms, field notebooks and other hardcopy records are secure, organized 

and readily available for viewing, reproduction or transfer upon request and/or at the end 

of each field season.

5.6 Quality Assurance/Quality Control

The QAPP describes methods used to ensure that the data collected is as representative of the 

natural environment as possible. Quality assurance procedures are required in all data collection 

efforts for the long-term monitoring plan. The following should be conducted to ensure the 

quality of data collected (adapted from O’Ney, 2005):

 Field measurements should be made only with calibrated instruments 

 The instruments should be tested, calibrated and error checked against acceptance criteria 

before leaving for the field

 At a minimum, DO and pH shall be calibrated again in the field at the monitoring station 

immediately before taking measurements

 Practice your measurement technique if the instrument or measurement is new to you.

 Each field instrument must have a permanent log book for recording calibrations, error 

check results and repairs. Review the log book before leaving for the field (see also 

SOP#3).

 All manually recorded field measurement data should be collected on field forms

 Automatically recorded data should be obtained electronically and the equipment used 

should be documented on field forms

 Complete records are maintained for each uniquely identified sampling station and all 

supporting metadata should be recorded appropriately (field forms or electronically) 

 Have backup instruments readily available and in good working condition.

 Quality-assurance protocols are mandatory for every data collection effort, and include 

practicing good field procedures and implementing quality-control checks.

 Make field measurements in a manner that minimizes artifacts that can bias the result.

 Check field-measurement precision and accuracy (variability and bias).

 Check measurement sensitivity
273

The SFAN Quality Assurance Project Plan (SOP #4) contains all of the details related to QA/QC 

requirements for field measurements. A summary of this is provided in Table 5. 3 below. Many 

of the QA/QC procedures are covered in SOP#3- Equipment Preparations: Calibration, 

Handling, and Storage. However, there are several QA/QC measures for the field. One of these 

involves calculating measurement sensitivity and is described below. 

Table 0.3 Data Quality Objectives for Field Measurements.

Parameter Instrument 

or Method

Alternative 

Measurement 

Sensitivity 

(AMS)

Method 

Detection 

Limit

Report as: (for STORET)

pH Oakton pH 

testr 30

*** 0.01 pH 0.1 units

Dissolved 

oxygen

YSI 85 *** 0.01mg/L 0.1 mg/L

Salinity YSI 85 *** 0.1 ppt

Temperature YSI 85 *** 0.1 0.20 C with a thermistor and 

0.50 C with a liquid in glass 

thermometer 

Specific 

Conductance 

YSI 85 2.5 uS/cm 0.1 uS/cm rounded number 

―Measurement Sensitivity‖ is a term typically used for laboratory parameters that may often 

yield results near zero. This is not an issue with field measurements that are always above a 

―limit of quantitation‖ (the minimum level of quantitation or ML. The ML is a lower limit below 

which there is no way to accurately determine (i.e., be 100% sure) how much of a compound 

such as nitrate is present. However, with field measurements the lower limits are not a concern. 

For example, specific conductance in a natural stream cannot be zero; there are always ions 

present and this results in some level of electrical conductivity. 

Measurement Sensitivity is used for laboratory parameters while the term ―Alternative 

Measurement Sensitivity‖ (AMS) is used for field parameters. The AMS is more specifically 

defined as ―the measurement precision uncertainty based on a sample size of seven 

environmental samples (not blank) and 99% confidence‖ (Irwin, 2004).

The AMS is calculated as follows:

 Follow the above procedures for equipment equilibration and stabilization

 Follow steps 1-6 for Field Measurements 

 Take seven distinct measurements for each parameter at regular intervals 

 Take the standard deviation of the seven samples (this can be calculated in Excel) and multiply 

by 3.708, the t value for a 99% confidence interval and a sample size of 7 (6 degrees of 

freedom). This number is taken from a standard table of t distribution critical values. 

 Calculate the AMS for each parameter at the beginning of the field season, during the winter 

(high flow) and at the end of the field season. Once a consistent range is developed, this can be 

conducted annually.
274

5.7 References

Cooprider, M. 2004. San Francisco Area Network Preliminary Water Quality Status Report. 

U.S. Department of Interior, National Park Service. 

http://www1.nature.nps.gov/im/units/sfan/wrd.htm

Eckblad, J.W. 1978. Laboratory Manual of Aquatic Biology. Wm. C. Brown Company 

Publishers, Dubuque, Iowa. 231 pp. 

Eureka Environmental Engineering. 2006. Manta Water Quality Multiprobe Startup Guide. 

June 8, 2006 revision. Austin, Texas, USA.

Hydrolab Corporation. 1998. DataSonde 4 and Minisonde Water Quality Multiprobes User’s 

Manual. Revision E. Austin, Texas, USA.

Irwin, R. 2004. Vital Signs Long-Term Aquatic Monitoring Projects: Part B – Planning Process 

Steps: Issues to Consider and then to Document in a Detailed Study Plan that Includes a 

Quality Assurance Project Plan (QAPP) and Monitoring ―Protocols‖ ( Standard 

Operating Procedures). National Park Service, Water Resources Division. 

Lendvay, J.M. and T.L. Benning. 2004. Health Assessment of Redwood Creek Watershed. 

Department of Environmental Science, University of San Francisco. 78 pp. + appendices.

National Park Service. 2002. Recommendations for Core Water Quality Monitoring Parameters 

and Other Key Elements of the NPS Vital Signs Program Water Quality Monitoring 

Component. Freshwater Workgroup Subcommittee. Fort Collins, CO. 

O’Ney, SE. 2005. Procedures for Collection of Required Field Parameters, Version 1.0, Standard 

Operating Procedure #5. In Regulatory Water Quality Monitoring Protocol, Version 1.0, 

Appendix E-SOPs, National Par Service, Greater Yellowstone Network. Bozeman, MT. 

37 pp. plus appendices. 

Peitz, D.G., S. G. Fancy, L. P. Thomas, and B. Witcher. 2002. Bird monitoring protocol for 

Agate Fossil Beds National Monument, Nebraska and Tallgrass Prairie National 

Preserve, Kansas. Prairie Cluster prototype monitoring program. Version 1.00, 

September 6, 2002.

Penoyer, P. 2003. Vital Signs Long-Term Aquatic Monitoring Projects. Part C – Draft Guidance 

on WRD Required Parameter Measurements, General Monitoring Methods, and Some 

Design Considerations in Preparation of a Detailed Study Plan. U.S. Department of 

Interior. National Park Service, Water Resources Division. 

Puckett, M. 2002. Quality Assurance Management Plan for the State of California's Surface 

Water Ambient Monitoring Program ("SWAMP"). California Department of Fish and 

Game, Monterey, CA. Prepared for the State Water Resources Control Board, 

Sacramento, CA. 145 pages plus Appendices.

Shelton, L. 1994. Field Guide for Collecting and Processing Stream-Water Samples for the 

National Water 

Quality Assessment Program. Open-File Report 94-455. U.S. Geological Survey, 

Sacramento, CA.

Wagner, R.J., Boulger, R.W., Jr., Oblinger, C.J., and Smith, B.A., 2006, Guidelines and standard 

procedures for continuous water-quality monitors—Station operation, record 

computation, and data reporting: U.S. Geological Survey Techniques and Methods 1-D3, 

51p. + 8 attachments; accessed April 10, 2006, at http://pubs.water.usgs.gov/tm1d3
275

Ward, K. 2004. Water Quality Standard Operating Procedures. In Draft Crissy Field Restoration 

Monitoring Program Quality Assurance Project Plan, Appendix 1. Golden Gate National 

Recreation Area, U.S. Department of Interior, National Park Service. San Francisco, CA. 

Wilde, F.D., Radtke, D.B., Gibs, Jacob, and Iwatsubo, R.T., eds., September 1999, Collection of 

water samples: U.S. Geological Survey Techniques of Water-Resources Investigations, 

book 9, chap. A4, accessed 9 September 2005 at http://pubs.water.usgs.gov/twri9A4/

YSI Incorporated. 1998. YSI Model 85 Handheld Oxygen, Conductivity, Salinity and 

Temperature System Operations Manual. Revision D. Yellow Springs, Ohio, USA. 
276

SOP #5 Appendix A. Field Data Sheet for Core Parameters
277

SFAN Water Quality Monitoring Program

Field Data Sheet – Stream Site

Station ID: ____________________________ 

Site Location: 

_____________________________________

Date:_________________________________

Time:____________________________PST_

Field Crew ____________________________________

* Take 7 measurements at the beginning of each quarter (Oct., Jan., April, July) to obtain standard deviation for calculating PQL

** Actual, Calculated, Estimated (Cross out and enter in notes if different from default)

***Note duplicated field measurement values (QA); any equipment issues or observations.

Field Conditions: 

______________________________________________________________________________________________________

__________________________________________________________

Time since last significant rainfall:____________

Notes 

______________________________________________________________________________________________________

__________________________________________________________

________________________________________________________________________________

Flow measurement taken? ______ Flow Severity: □1none □2 low □3 normal □4 flood □5 high □6 dry

Lab Samples taken? (which?)_________________________________________________________

Photographs taken? _______

Stabilization Criteria:

Temp: Thermistor = ±0.2oC

Thermometer = ±0.5oC

Specific Conductivity:

When ≤ 100μS/cm = ±5%

When > 100μS/cm = ±3%

pH: = ±0.1 SU

DO: Amperometric method = ±0.3 mg/L

Entered into NPSTORET□

 Validated □

Parameter *Measurement Units **Value 

Type

Instrument Notes***

Air Temperature oC Actual

H20 Temperature oC Actual YSI 85

Conductivity μS/cm

mS/cm

Actual YSI 85

Specific 

Conductance

μS/cm

mS/cm

Actual YSI 85

Salinity ppt Actual YSI 85

Dissolved Oxygen % Actual YSI 85

Dissolved Oxygen mg/L Actual YSI 85

pH S.U. Actual Oakton

Flow cfs Calculate

d

Turbidity NTU Actual Hach 2100
278

SOP #5 Appendix B. Winkler Titration Method for Dissolved 

Oxygen Measurement

Winkler Titration Method

From Eckblad, J.W. 1978. Laboratory Manual of Aquatic Biology. Wm. C. Brown Company 

Publishers, Dubuque, Iowa. 231 pp.

If the electronic DO probe is inoperable, DO should be measured by Winkler titration (Texas 

Natural Resource Conservation Commission, 1997). A Winkler titration kit includes:

 Two 300-mL biochemical oxygen demand (BOD) bottles with stoppers (may substitute a 

300-mL Erlenmeyer flask for titration). 

 One sewage sampler. 

 Manganous sulfate powder pillows. 

 Alkaline-iodide-azide reagent powder pillows. 

 Sulfamic acid powder pillows. 

 10-mL pipettes; 200- or 250-mL graduated cylinder. 

 0.025N phenylarsineoxide (PAO) (replace annually or as needed in field kit). 

 Stable starch reagent indicator solution. (Starch solution is stable for 1 month under field 

conditions. It should be renewed from stock, which is stable for up to 1 year in 

refrigerator.) 

 Scissors or knife for opening powder pillows. 

The following steps summarize Winkler titration procedures:

1. Collect a sample for titration by placing a 300-mL BOD bottle in a sewage sampler and 

lowering the top of the sewage sampler to a depth of 1 ft. 

2. The sewage sampler will fill in 30 to 45 seconds. 

3. The sampler is filled with water when it ceases bubbling. 

4. The sewage sampler should not be withdrawn until it has filled completely. 

5. The sampler should be carried upright until the BOD bottle is removed. 

6. Carefully remove the BOD bottle from the sewage sampler. 

7. The bottle should be filled to the top of the lip. 

8. Gently pour the upper 3 to 4 mL of water out of the flared mouth of the bottle. 

9. Add the contents of one manganous sulfate powder pillow to the full bottle. 

10. Add the contents of one alkaline-iodide-azide reagent powder pillow to the full bottle. 

11. Incline the bottle slightly and recap with a glass stopper in a quick, twisting thrust. 

12. Do not allow air bubbles to be trapped in the bottle. Sometimes this can be accomplished 

by just touching the top of the liquid with the stopper tip and then dropping it into 

position. 

13. Invert the bottle at least 25 times to mix completely and then set the bottle aside out of 

direct sunlight. 

14. A brown flocculent indicates the presence of DO. Allow the flocculent to settle halfway 

down the bottle (approximately 5 minutes). 

15. Invert the bottle another 25 times and let the flocculent settle once again. The flocculent 

will settle very slowly in sea water, which requires a minimum of 2 minutes reaction 
279

time. Results will not be affected if the flocculent refuses to settle or if some of the 

reagent powder does not dissolve. 

16. When the flocculent has settled after the second inversion so that the upper one-third of 

the bottle is clear, or after waiting 2 minutes, add the contents of one sulfamic acid 

powder pillow. 

17. Recap and gently invert the bottle another 25 times until all the flocculent has 

disappeared. The solution should be clear and straw-colored in appearance. The intensity 

of the yellow color is related directly to the original concentration of DO in the sample. A 

clear, pale solution indicates a very low DO concentration. A dark, clear, yellow solution 

indicates a high DO concentration. 

Samples prepared with the addition of sulfamic acid can be stored for 4 hours before completion 

of the Winkler titration. Samples can be stored for a maximum of 6 hours in the dark if the bottle 

is stored at the temperature of collection or water-sealed by putting water around the lip and kept 

at 10 to 20 °C (American Public Health Association, 1995).

As soon as the precipitate has completely dissolved as a result of acidification, the sample is 

ready to titrate.

18. Use a clean, graduated cylinder to transfer 200 mL of the solution to a 300-mL BOD 

bottle or Erlenmeyer flask. 

19. Place the flask on a magnetic stirrer, if this equipment is available. Otherwise, use a 

pipette and bulb, swirling the sample by hand. 

20. Stir the sample at a moderate rate without aerating the sample. Titrate with 0.025N PAO 

until the solution is pale straw-yellow in color. 

21. Add 1 to 2 mL of stable starch reagent and note the blue color, which indicates the 

presence of iodine. A few drops should give the blue indicator color (not gray). If more 

than 1 or 2 mL are needed to produce the color, the sample titration results should be 

rejected and the starch solution replaced. 

22. Continue the titration just until the blue color disappears. Do titration against a white 

background. This step requires either continuous stirring or vigorous swirling to ensure 

that the titration endpoint is accurate. Disregard the reappearance of the blue color after a 

few minutes. 

The total volume (in milliliters) of PAO used in the titration is equal to the DO concentration, 

expressed in milligrams per liter. The DO concentration from the titration should be recorded to 

the nearest 0.1 mg/L. For a 200-mL sample, the volume of titrant added is directly proportional 

to the DO concentration in milligrams per liter. To compute DO for a sample greater or less than 

200 mL, use the following formula:

DO (mg/L) =

200

.

sample volume x titrant added (in mL)

Corrections to Dissolved Oxygen Measurements Made With Dissolved Oxygen Meters

Some DO meters report measurements that are not compensated for salinity. Field DO measured 

with meters that are not salinity compensated and that are measured in waters with specific 

conductance exceeding 1,800 μS/cm, must be corrected. This correction is made by multiplying 
280

the field DO concentrations by a correction factor, which is computed from the following 

formula:

F = 1 -

[0.003439 + 0.361]

x

C

,

(22.1 + T)21,000

where

F = adjustment factor;

T = water temperature in degrees Celsius; and

C= specific conductance in microsiemens per centimeter,

Corrected DO = field DO x F.

The sample collector should record the corrected DO concentration.
281

SOP #6 Field and Laboratory Methods for Monitoring Fecal 

Indicator Bacteria

6.1 Revision History Log

Prev. Version 

#

Revision 

Date

Author Changes Made Reason for Change New Version 

#

1.00 8/5/05 M. Cooprider Minor edits Preparation for 

formal peer review

1.01

1.01 3/23/06 R. Carson Minor edits Addressing peer 

review comments

1.02

1.02 8/11/06 R. Carson Major changes reflecting 

inclusion of monitoring 

for E. coli using QuantiTray

Improves constraints 

of holding time, 

cost, and EPA 

recommendation for 

indicator bacteria 

1.1

Only changes in this SOP will be logged. ―Version numbers increase incrementally by 

hundredths (e.g. version 1.01, version 1.02 ...etc) for minor changes. Major revisions should be 

designated with the next whole number (e.g., version 2.0, 3.0, 4.0 ...). Record the previous 

version number, date of revision, author of the revision, identify paragraphs and pages where 

changes are made, and the reason for making the changes along with the new version number‖ 

(Peitz et al, 2002).

6.2 Acknowledgements 

Other protocols and guidelines for followed during the development of this SOP. Many thanks 

are extended to the authors of these documents: 

Puckett, M. 2002. Quality Assurance Management Plan for the State of California's Surface 

Water Ambient Monitoring Program ("SWAMP"). California Department of Fish and Game, 

Monterey, CA. Prepared for the State Water Resources Control Board, Sacramento, CA. 145 

pages plus Appendices.

Myers, D.N, November 2003, Fecal indicator bacteria: U.S. Geological Survey Techniques of 

Water-Resources Investigations, book 9, chap. A7, 3rd edition, Section 7.1 accessed __date__ at 

http://pubs.water.usgs.gov/twri9A7/ (Chapter sections are cited by author and date.) 

O’Ney, S. 2004. Procedures for Collection of Regulatory Parameters, Version 1.0, Standard 

Operating Procedure #6. In Regulatory Water Quality Monitoring Protocol, Version 1.0, 

Appendix E-SOPs, National Park Service, Great Yellowstone Network. Bozeman, MT. 37 pp. 

plus appendices.
282

Wilde, F.D., Radtke, D.B., Gibs, Jacob, and Iwatsubo, R.T., eds., September 1999, Collection of 

water samples: U.S. Geological Survey Techniques of Water-Resources Investigations, book 9, 

chap. A4, accessed __date__ at http://pubs.water.usgs.gov/twri9A4/

6.3 List of Acronyms Used

APHA American Public Health Association

AWWA American Water Works Association

EPA Environmental Protection Agency

FDA Food and Drug Administration

FIB Fecal Indicator Bacteria

GOGA Golden Gate National Recreation Area

I&M Inventory and Monitoring

JOMU John Muir National Historic Site

MPN Most Probable Number

NAWQA National Ambient Water Quality Assessment

PINN Pinnacles National Monument

PORE Point Reyes National Seashore

RWQCB Regional Water Quality Control Board

SFAN San Francisco Bay Area Network

SOP Standard Operating Procedure

SWAMP Surface Water Ambient Monitoring Program

TMDL Total Maximum Daily Load

USGS United States Geological Survey

WEF Water Environment Federation
283

6.4 Scope and Application

6.4.1 Fecal Indicator Bacteria and Their Relation to Water Quality

Wastes from warm-blooded animals harbor numerous intestinal bacteria that can be pathogenic 

to humans and other animals. These wastes can enter surface waters via surface runoff, 

groundwater flow, direct access of animals to a creek, leaky septic systems, and leaky sewer 

pipes. Fecal indicator bacteria (FIB) are used as indicators of the possible presence of 

pathogenic bacteria that may occur in wastes. Indicator species, as opposed to the pathogenic 

bacteria themselves, are enumerated because they are easier and safer to work with in the 

laboratory. 

The most commonly used fecal indicator organisms or groups include total coliforms, fecal 

coliforms, fecal streptococcus, E. coli, and Enterococcus. The number of fecal coliforms is often 

highly correlated with other indicator species or groups including E. coli and Enterococcus 

though they cannot definitively be used interchangeably (Noble et al., 2000). Unlike total 

coliforms, E. coli and fecal coliforms are more frequently found in mammalian or avian 

intestines. Therefore, they are more pertinent as indicators of fecal material and associated 

pathogens in water. Total coliforms, including species in the genera Klebsiella, Enterobacter, 

and Escherichia, are indicators of all members of the Enterobacteriaceae family. However, 

some members of this family do not pose threats to human health so it is not particularly useful 

to know their occurrence (Turco, 1995). Another coliform, Enterobacter aerogenes is also 

frequently isolated from soils regardless of the presence of animal wastes. Total coliforms are 

ubiquitous in nature (Baxter-Potter and Gilliland, 1988). Numbers of total coliforms and other 

FIB in ―natural‖ surface waters are listed in Table 6.1. 

Table 0.1 Ranges of fecal indicator bacteria typically found in uncontaminated surface water and 

contaminated surface water (from Table 7.1-1 in the USGS National Field Manual).

Bacterial Group Uncontaminated surface water Fecal-contaminated surface water

 colonies/100mL

Total coliform <1 to 80,000 1,200- > 4,000,000

Fecal coliform <1 to 5,000 200 to > 2,000,000

Escherichia coli <1 to 576 126 to > 2,000,000

Fecal streptocococcus <1 to 1,000 400 to > 1,000,000

Enterococcus <1 to 100 100 to > 1,000,000

Clostridium 

perfringens

<1 to 100 100 to > 10,000

Fecal coliforms indicate the presence of feces that may contain pathogens in the genera 

Salmonella, Mycobacterium, Leptospira, Clostridium, and Bacillus, foot-and-mouth disease 

virus, entroviruses, and helminthes (parasitic worms) (Reddy et al, 1981). E.coli is rarely 

pathogenic. However, some pathogenic strains of E. coli can cause gastroenteritis, diarrhea, 

colitis, or dysentery. Strain O157:H7 can be fatal to infants, older adults, and individuals with 

compromised immune systems.

6.4.2 Water Quality Standards for Fecal Indicator Bacteria
284

Water quality standards for FIB have been established to protect human health. The San 

Francisco Bay Regional Water Quality Control Board (Regional Board) sets numeric and 

narrative objectives for water quality (Regional Water Quality Control Board, 1995). Table 6.2 

shows water quality objectives for the primary beneficial uses of SFAN water bodies.

Table 0.2 General numeric objectives for select beneficial uses in surface waters in the San 

Francisco Bay Area.

Beneficial Use Fecal Coliform (MPN/100mL) Total Coliform (MPN/100mL)

Contact recreation Log mean < 200

90th percentile < 400

Median < 240

No sample > 10,000

Non-contact recreation Mean < 2000

90th percentile < 4000

Shellfish harvesting Median < 14

90th percentile < 43

Median < 70

90th percentile < 230

For the purposes of FIB monitoring, waters can be divided into three broad categories of 

beneficial uses including recreational, shellfish-growing waters, and ambient waters. 

Recreational waters are used for ―contact recreation‖ such as swimming or kayaking. Ambient 

waters are used for ―non-contact recreation‖ such as hiking and picnicking.

E.coli and Enterococci are the preferred indicators for contact recreational monitoring since they 

have greater survival in marine waters. Therefore, they are better indicators of swimmingrelated gastroenteritis in marine and freshwaters than total coliforms, fecal coliforms, and fecal 

streptococci. While, the I&M program will not be monitoring recreational waters which 

primarily include marine waters within PORE and GOGA, we will follow the EPA 

recommendations for indicator bacteria species.

6.4.3 Fecal Indicator Bacteria Levels in SFAN Waters

The UC Berkeley report A Review of Water Quality Monitoring Programs in the National Parks 

in Central Coastal California (Stafford and Horne, 2004) contains additional background 

information related to fecal indicator bacteria. Ranges in fecal indicator bacteria concentrations 

in SFAN parks are listed in Table 6.2. Additional information about FIB levels and sources in 

SFAN waters is included in the SFAN Preliminary Water Quality Status Report (Cooprider, 

2004).
285

Table 0.3 Range in Fecal Indicator Bacteria* in SFAN parks (MPN/100mL) based on land use.

Park Overall Land 

Use 

(overall range)

Wilderness 

(mean range)

Grazed

(mean range)

Dairy

(mean range)

GOGA 2 to 300,000 

JOMU 17 to 900 

PINN 3 to 440 (E.coli)

PORE† 17 to 540 1,000 to 46,000 2,400 to 710,000 

* Fecal coliforms unless otherwise indicated

† The overall range in fecal coliforns at PORE was < 200 to > 1 million

Several water bodies within SFAN have elevated levels of FIB. A few of these water bodies are 

on the Clean Water Act Section 303d list due to impairment by fecal coliforms. Sources of fecal 

bacteria within SFAN include agriculture (dairy and beef cattle ranching and vegetable farming), 

residential areas (septic systems), and recreational land uses (equestrian operations and dog 

walking). Other streams are impaired due to their urban location and proximity to sewer pipes.

6.4.4 Tomales Bay Pathogen Total Maximum Daily Load (TMDL) Project

The San Francisco Bay RWQCB has identified Tomales Bay (PORE/GOGA) and its tributaries 

(Lagunitas Creek and Walker Creek) as impaired by fecal coliform. Health concerns have arisen 

due to contamination of shellfish with pathogenic bacteria. SFAN staff has collaborated with 

the RWQCB regarding monitoring of indicator bacteria in Olema Creek a tributary to Lagunitas 

Creek. The RWQCB recently completed a final Total Maximum Daily Load (TMDL) project 

report for pathogens in Tomales Bay (RWQCB, 2004). Implementation of monitoring for the 

Tomales Bay Pathogen TMDL program includes monthly monitoring plus five consecutive 

weeks of monitoring during the winter and summer in order to obtain a geometric mean of the

most probable number (MPN) of fecal coliform bacteria present.

The TMDL Implementation Plan is focused on attaining the water quality standard for shellfish 

harvesting areas of 14 MPN/100 mL for fecal coliforms. The Food and Drug Administration 

(FDA) regulates shellfish harvesting areas based on fecal coliforms. Therefore, although other 

FIB can be used to determine the presence of pathogenic bacteria, PORE is required to monitor 

fecal coliforms as part of the TMDL implementation strategy. In order to maintain consistency 

with other RWQCB Tomales Bay TMDL sites, samples from PORE/GOGA will be analyzed for 

fecal coliforms at the same laboratory used by the RWQCB, whenever possible.

6.4.5 FIB Sampling and Analysis Methods Overview

The definition of the coliform group has traditionally been based on the detection method used 

(lactose fermentation or defined enzyme substrate tests). A common technique for determining 

lactose fermentation involves inoculating multiple test tubes with the water sample. For defined 

enzyme substrate tests, the water sample is combined with a reagent that reacts to detect the 

enzyme β-glucuronidase produced by E. coli, the mixture is distributed in a series of individual 

wells in a tray. Results of the examination of replicate tubes (or wells) and dilutions are reported 

in terms of the Most Probable Number (MPN) of organisms present. This number is based on 

certain probability formulas and is an estimate bacteria density in the sample (APHA, AWWA, 
286

WEF, 1998). Results are reported in units of MPN/100mL. Most Probable Number tests for 

total and fecal coliforms and E. coli usually result in greater recovery of microorganisms than 

other techniques such as membrane filtration (Myers, 2003).

The U.S. EPA recommends testing for E. coli and enterococci indicators in place of total and 

fecal coliform indicators because recent epidemiological studies indicate that E. coli and 

enterococci show a direct correlation with swimming-associated gastrointestinal illness rates, 

while fecal coliforms do not (USEPA, 2003). While SFAN must continue to analyze Tomales 

Bay TMDL samples for fecal coliforms to comply with RWQCB projects, samples from other 

SFAN streams will begin to be analyzed for total coliform and E. coli using enzyme substrate 

methods cited below. Overlap in methods will occur to the degree that is feasible in order to 

ensure long-term comparability of methods and results. One way is to process the Tomales Bay 

TMDL samples at the regional lab for fecal coliform as well as at the in-house lab for E. coli. 

Such overlap would provide more than 70 annual samples that could be analyzed to provide 

information on the comparability of the two methods.

Bacteria are often associated with sediment particles. Therefore, USGS recommends that depthintegrated sampling be conducted for bacteria sampling in the same way that it is conducted for 

sediment. However, the San Francisco Bay RWQCB does not use depth-integrated sampling for 

bacteria or nutrient TMDL monitoring (Peter Krottje, personal communication). The RWQCB’s 

Surface Water Ambient Monitoring Program (SWAMP) also does not collect depth-integrated 

samples for bacteria. Regardless, in many cases with SFAN streams, there is not sufficient 

depth, except during storm events, to obtain a meaningful depth-integrated sample. And, during 

storm events, SFAN stream conditions often preclude safe wading, and therefore, collection of 

depth-integrated samples. In order to maintain consistency at each of the sites and throughout 

the sampling season, it is best to obtain a ―grab‖ or ―hand-dipped’ sample. 

This field SOP will focus on field sample collection including sterile technique to avoid 

contaminating a sample and location of sample in the water column. Details of sample bottle 

labeling, storage, and transport to laboratories (including chain of custody forms) will also be 

discussed. Analysis will be conducted either by an analytical laboratory or by in-house analysis 

using IDEXX Quanti-Tray®/2000. Fecal coliform samples will be analyzed at an EPA approved 

laboratory using the SM 9221E Multiple Tube Technique (Most Probable Number) in ―Standard 

Methods for the Examination of Water and Wastewater‖ (APHA-AWWA-WEF, 1998). 

Recommendations for analysis methods and laboratory selection, including choosing a NELAPcertified lab, are discussed in the SFAN Freshwater Quality Protocol Narrative. Samples that 

will be analyzed for E. coli using Quanti-Tray®/2000 will be processed and handled by the 

SFAN Water Quality Specialist, or properly-trained staff. The principle, procedure, 

interpretation, reporting and quality-control for enzyme substrate testing using SM 9223 Enzyme 

Substrate Coliform Test are included in ―Standard Methods for the Examination of Water and 

Wastewater‖ (APHA-AWWA-WEF, 1998).

For training in the laboratory methods for IDEXX products, short videos are available online at:

http://www.idexx.com/water/video/index.jsp
287

Additional references are available in Appendix A, including instructions for QuantiTray®/2000, an MPN table, the users manuals for the tray sealer. 

6.5 Techniques 

6.5.1 Tips for collection of bacteria samples:

 Collect water samples first before disturbing the sediment

 Note potential sources of contamination at each site

 Wear appropriate disposable, powderless gloves

 Use correct sample-handling procedures to avoid sample contamination

 Establish a routine for sample collection; use a consistent sampling technique

 Obtain training for and practice field techniques under supervision before collecting 

water samples.

 Collect a sufficient number of appropriate types of quality-control samples

 Prevent nose, mouth, eye, and direct skin contact with water 

6.5.2 Aseptic Technique (from O’Ney, 2004)

Disposable latex or rubber gloves should be used to collect bacteria samples. Some individuals 

have severe allergic reactions to latex. Field staff must avoid touching the opening of the sample 

collection container or its cap, or having the sample touch hands or arms. For each sample:

 Wash and scrub hands thoroughly to the mid-forearm, using antibacterial hand soap (or a 

hand sanitizer at 50 ppm chlorine equivalency, if available). 

 Open the sample container taking care to avoid touching the inside surfaces or otherwise 

causing contamination

 Remove a glove by holding it from the wrist side opening inner surface. Avoid any contact 

with the outer surface of the glove.

 Do not touch anything with the exterior of the glove except the sample.

 If you have concern that the glove may be contaminated, discard that glove and use another 

sterile glove.

 With the gloved hand, collect the sample. 

 After sample has been collected, close the sample container, remove and discard the glove 

and place sample in a cooler.

6.5.3 Sample Bottles

Use only sterile 100 mL bacteriologic sample bottles (supplied by the laboratory or purchased). 

It is important to have extra bottles as they occasionally can be swept away in current or 

contaminated. Some laboratories provide bottles with relatively ―waterproof‖ labels already 

attached. Other labels are more susceptible to wear and generally consist of regular paper. If 

this is the case, it is best to place a scotch tape over the label. It is sometimes easier and more 

efficient to label the bottle before sampling; this avoids having to dry off the bottle or write on a 

wet label. Pre-labeling (in the office or field vehicle) can also save time in the field especially 

important when it is raining.
288

Laboratory-supplied bottles may contain a tablet or powdered form of sodium thiosulfate which 

is used to neutralize chlorine. This is required for drinking water samples. This tablet is not 

needed for SFAN surface water samples and does not affect the bacteria. However, in the event 

that chlorine may be present and to be consistent, the tablet or powder should remain in the 

bottle. 

6.5.4 Collecting the Samples

(Adapted from Wilde et al, 1999) 

Prepare for sampling

1. Upon arrival at the field site, set out safety equipment such as traffic cones and signs. 

2. Park vehicle in a location and direction to prevent sample contamination

3. Take extra bottles in case of contamination or loss

4. Take enough bottles to obtain QA/QC samples (see QAPP)

5. Label bottles but leave ―time‖ field blank until actual sample collection

Determine the sampling location

1. Visually inspect the stream from bank to bank and longitudinally, observing velocity, 

width, and depth distribution, and apparent distribution of sediment and aquatic biota 

along the cross section. Note and document the location of stagnant water, eddies, 

backwater, reverse flows, areas of faster than normal flow, and piers or other features 

along the cross section.

2. Check the site list to determine whether the sample is to be collected in a pool or 

flowing area (or both). If sampling from a flowing area, identify the area of the 

stream that appears to be completely mixed (the centroid of flow). This may be 

determined ahead of time from reliable discharge measurements (see Initial Site 

Establishment – SOP#11 and Flow Measurement – SOP#9). Do not disturb the 

sediment before collecting a water sample. 

3. For pools, if shallow (< 1 ft) take measurements at a middle depth. If the pool is from 

1-4 ft deep collect a sample at a depth that meets monitoring objectives (Wilde et al, 

1999). 

4. For flowing water, sub-surface samples are taken at 0.1 m (4 inches) below the water 

surface if water level is < 5 ft (1.5 m). Samples are collected at the surface when 

water depth is < 0.1 m (Puckett, 2002). Sampling from the shoreline of any water 

body (meaning standing on shore and sampling from there) is the least acceptable 

method, but in some cases is necessary (Puckett, 2002).

5. Collect the bacteria sample at the same location as you will be collecting the core 

parameters.

Water samples should be collected from a location in the stream where the stream visually 

appears to be completely mixed. Ideally this would be at the centroid of the flow (Centroid is 

defined as the midpoint of that portion of the stream width, which contains 50% of the total 

flow), but depth and flow etc. do not always allow centroid collection (Puckett, 2002).
289

Collect the sample

Note: Collect water samples first to avoid disturbing the sediment and re-suspending sediment or 

bacteria

The USGS uses the ―Hand-dip‖ method (Myers, 2003) if stream depth or velocity is not 

sufficient to use depth-integrated sampling. The procedure minimizes the collection of surface 

films and avoids contact with the streambed. The method is as follows:

1. Open a sterile, narrow-mouth borosilicate or plastic bottle; grasp the bottle near the 

base, with hand and arm on the downstream side of the bottle.

2. Without rinsing, plunge the bottle opening downward below the water surface. Allow 

the bottle to fill with the opening pointed slightly upward into the current.

3. Remove the bottle with the opening pointed upward toward the water surface and 

tightly cap it, allowing about 2.5 to 5 cm of headspace. Laboratory supplied bottles 

typically have an ―EPA fill line‖ that allows for this amount of headspace. 

4. Inspect each sample, looking for overfilling and (or) the presence of large amounts of 

particulates that might have been captured due to excessive streambed disturbance 

during sample collection. If you note either or both of these conditions, discard the 

sample, making sure there are no residual particulates left in the container, and 

resample. 

5. Place the sample bottle in an ice-chest immediately. [NOTE: Use blue ice (often 

provided by labs), not wet ice to avoid possible contamination by contact with the 

melt water.] Ensure that the bottle label is completed with the date, time, site ID, and 

initials of field personnel. 

6. Check the temperature of the ice-chest and refrigerator (if used); it must be between 

1-4 C. Samples should be stored in the dark.

7. Ensure that the samples are transported to the laboratory for analysis within the 6 

hour EPA hold time. 

6.5.5 Preparing the Samples and Laboratory Analysis

1. Ensure that the sample is processed within the 6-hour EPA hold time, and that the 

sample has been stored at <4°C

2. Mix sample well by inverting bottle numerous times

3. If processing sample at a requested dilution, extract appropriate sample volume and 

add to sterile sample bottle, and fill to 100mL with distilled water.

4. Add contents of Colilert® reagent pack to sample bottle, recap and mix well.

5. Open sterile Quanti-Tray® at the top, and pour in sample and reagent mix.

6. Carefully insert filled tray into sealer gasket, then carefully feed the gasket and tray 

into the sealer

7. Take sealed tray from the return tray of the sealer, remove gasket

8. Place sealed tray into35°C incubator for 24 hours.

9. Remove tray from incubator and observe tray for:

a. Total number of large and small wells that are yellow (more yellow than the 

IDEXX comparator tray.
290

b. Total number of large and small wells that fluoresce blue (more fluorescent 

than the IDEXX comparator tray.

10. Using the numbers obtained in step 9, use the MPN table to determine the mostprobable-number of total coliform bacteria (yellow) and E. coli (blue) from each 

sample.

For complete instructions, and to view training videos, visit the IDEXX website at:

http://www.idexx.com/water/video/index.jsp

Additional references are available in Appendix A, including instructions for QuantiTray®/2000, an MPN table, the users manuals for the tray sealer.

6.6 Field Preparations and Laboratory Coordination 

When starting work with a new laboratory, the Water Quality Specialist should develop a good 

working relationship with a laboratory manager and also a chemist/microbiologist at the 

laboratory. Discuss analytical methods, detection limits, holding times, and laboratory 

constraints such as limited incubator size. Obtain official chain of custody forms from the lab as 

well as any needed bottles, cooler, and ice packs if the laboratory provides these. Discuss 

sample drop-off and pick-up possibilities. Also discuss the labs’ capacity for the number of 

samples you will have. General tasks list include:

 Notify the lab at the beginning of the season, or as early as possible, of your sampling 

schedule

 Call the lab the day before or the morning of sampling to verify sample collection

 If at all possible, schedule sampling early in the week rather than later.

 Fill out the chain of custody form ahead of time except for the sample time; include the 

dilution in the comments field*

* It is critical to know the expected concentrations of coliforms since dilutions 

may be required in order to quantify bacteria (i.e., in order to avoid ―censored data‖ 

that is greater than (>) or less than (<) a detection limit). Refer to the site list for 

dilution information. 

The chain of custody form is a means of tracking samples from receipt in the laboratory through 

analysis, to final disposal of the sample. It should be filled out in ink. The chain-of-custody 

forms travel with the samples during the transfer, and are filed in the laboratory project files. 

Upon arrival at the laboratory, the ―sample custodian‖ at the lab inspects the sample containers to 

ensure that the sample seals are intact and the sample containers have not been damaged. If any 

seals have been broken and/or any sample containers damaged, the sample custodian records the 

condition of the seals and containers on the chain-of-custody form. The sample custodian takes 

custody of the samples by signing, dating, and noting the time in the on the chain-of-custody 

form.
291

Once at the laboratory, if samples need to be subdivided and submitted to another laboratory subcontractor, this information should be noted on the original Chain-of-Custody Form, and a new 

Chain-of-Custody Form with the other lab should be initiated (Puckett, 2002).

6.6.1 Equipment Checklist

Scotch tape

Hand sanitizer

Bottle labels

Disposable gloves

Sterile sample bottles

Data sheets printed on waterproof paper

Ice chest

Thermometer for ice chest

Chain-of-custody form

Sharpie (permanent pen)

Water jug for washing hands

Soap

Also, consult SOP#2 for safety equipment as well as SOP#3 for equipment calibration.

6.7 Quality Assurance/Quality Control (Check with QAPP)

―Depending on the data quality requirements of the study and site conditions, quality control 

samples (field blanks and field replicates) generally constitute from 5 to 20 percent or more of 

the total number of samples collected in a year or during a given period of time (Myers, 2003). A 

field duplicate and a field blank are required as follows:

Field Blank – 1 in every 10 to 20 samples; pass deionized water into a sterile sampling container; 

have container analyzed for FIB

Field Replicate – collect and analyze 1 field replicate for every 10-20 samples. A split sequential 

replicate is recommended. Two samples are collected and each sample is analyzed in duplicate 

(Myers, 2003).

One important element of QA/QC is the development of measurement quality objectives 

(MQO’s) for systematic error/bias as percent recovery. Using the QA/QC kits that are available 

through IDEXX, we will test for percent recovery for each lot number of trays or reagent used in 

our analysis. Eventually, with enough data collected during the first years of sampling, SFAN 

will develop numeric MQO’s for bacterial parameters.

6.8 References 

American Public Health Association, American Water Works Association, and Water 

Environment Federation. 1998. Standard methods for the examination of water and 
292

wastewater (18th ed.), pp. p. 9-47 to 9-70, American Public Health Association, 

Washington, D.C.

Baxter-Potter, W.R. and M.W. Gilliland. 1988. Bacterial pollution in runoff water from 

agricultural lands, J. Environ. Qual. 17:27-34. 

California Regional Water Quality Control Board, San Francisco Bay Region. 1995. Water 

Quality Control Plan-San Francisco Bay Basin (Region 2). 

Cooprider, M. 2004. San Francisco Area Network Preliminary Water Quality Status Report. U.S. 

Department of Interior, National Park Service.

California Regional Water Quality Control Board, San Francisco Bay Region. Pathogens in 

Tomales Bay Total Maximum Daily Load Final Project Report. Oakland, CA. 

Krottje, P. 2005. Personal Communication. San Francisco Bay Regional Water Quality Control 

Board.

Myers, D.N. November 2003, Fecal indicator bacteria: U.S. Geological Survey Techniques of 

Water-Resources Investigations, book 9, chap. A7 (3rd edition), accessed __date__ at 

http://pubs.water.usgs.gov/twri9A/

Noble, R.T., M.K. Leecaster, C.D. McGee, D.F. Moore, V. Orozco-Borbon, K. Schiff, P.M 

Vainik, and S. B. Weisberg. 2000. Southern California Bight Regional Monitoring 

Program: Storm Event Shoreline Microbiology. Southern California Coastal Water 

Research Project. Westminster, CA. 

O’Ney, S. 2004. Procedures for Collection of Regulatory Parameters, Version 1.0, Standard 

Operating Procedure #6. In Regulatory Water Quality Monitoring Protocol, Version 1.0, 

Appendix E-SOPs, National Park Service, Great Yellowstone Network. Bozeman, MT. 

37 pp. plus appendices.

Puckett, M. 2002. Quality Assurance Management Plan for the State of California's Surface 

Water Ambient Monitoring Program ("SWAMP"). California Department of Fish and 

Game, Monterey, CA. Prepared for the State Water Resources Control Board, 

Sacramento, CA. 145 pages plus Appendices.

Reddy, K.R., R. Kaleel, and M.R. Overcash. 1981. Behavior and transport of microbial 

pathogens and indicator organisms in soils treated with organic wastes. J. Environ. Qual. 

10:255-265.

Stafford, S. and A. Horne. 2004. A Review of the Water Quality Monitoring Programs in the 

National Parks in Central Coastal California. Report to the National Park Service. 

Department of Civil & Environmental Engineering, University of California, Berkeley.

Turco, R.F. 1994. Coliform bacteria. In R.W. Weaver et al. (ed.). Methods of Soil AnalysisPart2. Microbilogical and biochemical properties. Soil Science Society of America, Inc. 

Madison, WI. 

U.S. Environmental Protection Agency (EPA). 2003. 40 CFR Part 136: Guidelines establishing 

test procedures for the analysis of pollutants; Analytical methods for biological pollutants 

in ambient water; Final rule. Federal Register, Vol. 68, No. 139.

Wilde, F.D., Radtke, D.B., Gibs, Jacob, and Iwatsubo, R.T., eds., September 1999, Collection of 

water samples: U.S. Geological Survey Techniques of Water-Resources Investigations, 

book 9, chap. A4, accessed __date__ at http://pubs.water.usgs.gov/twri9A4/
293

SOP #6 Appendix A

Quanti-Tray®/2000 Insert Instructions and MPN Table

(hard copy only)

IDEXX Quanti-Tray® Sealer Model 2x User Manual

(hard copy only)

Preventative Maintenance Instructions for Quanti-Tray® Sealer Model 2X

(hard copy only)
294

SOP #7 Field Methods for Sampling Nutrients 

7.1 Revision History Log

Prev. Version 

#

Revision 

Date

Author Changes Made Reason for Change New Version #

1.0 8/5/05 M. Cooprider Minor edits Preparation for 

formal peer review

1.01

1.01 3/16/06 R. Carson Minor Edits Addressing peerreview comments1.02

Only changes in this SOP will be logged. ―Version numbers increase incrementally by 

hundredths (e.g. version 1.01, version 1.02 ...etc) for minor changes. Major revisions should be 

designated with the next whole number (e.g., version 2.0, 3.0, 4.0 ...). Record the previous 

version number, date of revision, author of the revision, identify paragraphs and pages where 

changes are made, and the reason for making the changes along with the new version number‖ 

(Peitz et al, 2002).

7.2 Acknowledgements

SFAN staff borrowed from several other protocols and guidelines. Many thanks are extended to 

the authors of these documents, most notably: 

Puckett, M. 2002. Quality Assurance Management Plan for the State of California's Surface 

Water Ambient Monitoring Program ("SWAMP"). California Department of Fish and 

Game, Monterey, CA. Prepared for the State Water Resources Control Board, Sacramento, 

CA. 145 pages plus Appendices.

O’Ney, S. 2004. Procedures for Collection of Regulatory Parameters, Version 1.0, Standard 

Operating Procedure #6. In Regulatory Water Quality Monitoring Protocol, Version 1.0, 

Appendix E-SOPs, National Park Service, Great Yellowstone Network. Bozeman, MT. 37 

pp. plus appendices.

Wilde, F.D., Radtke, D.B., Gibs, Jacob, and Iwatsubo, R.T., eds., September 1999, Collection of 

water samples: U.S. Geological Survey Techniques of Water-Resources Investigations, book 

9, chap. A4, accessed 2005 at http://pubs.water.usgs.gov/twri9A4/
295

7.3 Scope and Application

7.3.1 Nutrients and Their Relation to Water Quality

Nitrogen and phosphorus are the primary plant nutrients and are ubiquitous in the environment. 

Aquatic systems are either nitrogen limiting or phosphorus limiting in reference to algal growth. 

Algae use nitrogen and phosphorus at a ratio of about 7:1 by mass. A significantly narrower 

ratio means that there is a greater supply of phosphorus than nitrogen and that nitrogen is 

limiting growth. In this case, nitrogen is referred to as the ―limiting nutrient‖. In most Bay Area 

freshwater streams, nitrogen is the limiting nutrient (California Regional Water Quality Control 

Board, 2003).

If a system is nitrogen limiting, then inputs of nitrogen can cause excessive growth 

(eutrophication) or toxicity to aquatic organisms. Eutrophication occurs at lower levels than 

toxicity (California Regional Water Quality Control Board, 2003). Nitrate and un-ionized 

ammonia can cause nutrient toxicity. Excess nutrients can also harm aquatic life through 

depletion of oxygen. Excess algal growth leads to greater respiration by live algae and 

decomposition of dead plant and algal material. Oxygen producing photosynthesis only occurs 

during the day while respiration, an oxygen depleting process, occurs 24 hours a day. Therefore, 

dissolved oxygen is lowest just before dawn.

Nitrogen occurs naturally in several forms in the environment. Organic nitrogen (N) is anything 

that is organically bound including protein and peptide nucleic acids, urea, and synthetic organic 

materials. Organic nitrogen varies from 100ug/L in lakes to more than 20mg/L in raw sewage. 

Organic nitrogen and ammonia together are referred to as Total Kjeldahl Nitrogen (TKN) named 

after the Kjeldahl method. Total Ammonia Nitrogen or TAN is chemically represented as NH4

+

and is present naturally in surface waters and wastewaters. Un-ionized ammonia or UIA is 

chemically represented as NH3 and is toxic to aquatic organisms at low levels. This is of 

particular concern in SFAN streams supporting threatened and endangered species including 

coho salmon and steeelhead trout, California red-legged frog, and the California freshwater 

shrimp. Total oxidized or inorganic N is nitrate and nitrite. Nitrate generally occurs in trace 

quantities in surface water (APHA/AWWA/WEF 1998). Anthropogenic forms of nitrogen 

include fertilizers and wastes from warm-blooded animals that contain ammonia and organic 

nitrogen (among other forms of nitrogen). These wastes can enter surface waters via surface 

runoff, groundwater flow, direct access of animals to a creek, leaky septic systems, and leaky 

sewer lines.

Phosphates also exist in different forms including: orthophosphate, metaphosphate (or 

polyphosphate) and organically bound phosphate. Orthophosphates are produced by natural 

processes and are found in wastewater. Polyphosphate forms are used for treating boiler waters 

and are found in detergents. Poly forms of phosphate can change to the ortho form in water. 

Organic phosphates are a natural part of the environment but may also result from the breakdown 

of organophosphate pesticides. The common mineral source of phosphorus is insoluble rock 

phosphate [Apatite - Ca5(PO4)

3

(F3OH)] (Swaddle, 1997 In Thompson and Chambers, 2000). 
296

7.3.2 Nutrient Levels in SFAN Waters

The UC Berkeley report A Review of Water Quality Monitoring Programs in the National Parks 

in Central Coastal California (Stafford and Horne, 2004) contains additional background 

information related nutrients. Additional information about nutrient levels and sources in SFAN 

waters is included in the SFAN Preliminary Water Quality Status Report (Cooprider, 2004). 

Water quality standards for nutrients are listed in Section 1.0 of the Freshwater Quality Protocol 

Narrative.

The San Francisco Bay RWQCB has identified Tomales Bay and its tributaries, Lagunitas Creek 

and Walker Creek, as impaired by nutrients. Once the nutrient monitoring implementation plan 

is complete, SFAN staff will be collaborating with the RWQCB regarding monitoring of key 

nutrients, primarily nitrogen parameters, in Lagunitas Creek and its tributaries, including Olema 

Creek. A Conceptual Approach for Developing Nutrient TMDLs for San Francisco Bay Area 

Water Bodies was prepared by the San Francisco Bay RWQCB (RWQCB, 2003).

7.3.3 Nutrient Sampling and Analysis Methods Overview

The San Francisco Bay RWQCB does not use depth-integrated sampling for nutrient TMDL 

monitoring (Peter Krottje, personal communication). Also, the RWQCB’s Surface Water 

Ambient Monitoring Program (SWAMP) does not collect depth-integrated samples for nutrients. 

Regardless, in many cases with SFAN streams, there is not sufficient depth, except during storm 

events, to obtain a meaningful depth-integrated sample. In order to maintain consistency at all of 

the sites and throughout the sampling season, it is best to obtain a ―grab‖ or ―hand-dipped’ 

sample.

Monthly monitoring will be conducted for nitrate, and ammonia, and Total Kjeldahl nitrogen.

Collection of samples at each site will take place within the same two-hour window each month, 

where possible, to minimize the effect of diel variation in nitrogen compounds that could 

complicate the detection of trends.
297

Table 0.1 Summary of methods for laboratory parameters (modified from Puckett, 2002).

Parameter Sample Volume 

(mL)

*Method Detection 

Limit (MDL)

Preservation & 

Storage

Holding Time Method

Total Kjeldahl 

Nitrogen

600 mL 0. 10 mg/L Unfiltered; Cool to 

< 4○ C; dark

7 days 

(28 days max)

SM 4500

Ammonia 500 mL 0.10 mg/L Unfiltered; H2SO4, 

preservative, 

Cool to < 4○ C

48 hours; or 28 days 

with preservative

EPA 350.3

Nitrate 150 mL 0.10 mg/L Unfiltered; Cool to 

< 4○ C; dark

48 hours EPA 300 / 

(EPA353)**

Nitrite 150 mL 0.05 mg/L Unfiltered; Cool to 

< 4○ C; dark

48 hours EPA 300 / 

(EPA353)**

* There are often several approved methods and they vary depending on the lab and the type of 

instruments that they have. Also, methods change and improve over time. The important 

consideration is that the labs use a method that has the desired MDL. MDLs are those 

recommended by the San Francisco Bay Regional Water Quality Control Board (Peter Krottje, 

personal communication, 1 July 2005).

7.4 Techniques

7.4.1 Tips for collection of nutrient samples:

● Collect water samples first before disturbing the sediment

● Note potential sources of contamination at each site

● Wear appropriate disposable, powderless gloves

● Use correct sample-handling procedures to avoid sample contamination

● Establish a routine for sample collection; use a consistent sampling technique

● Obtain training for and practice field techniques under supervision before collecting 

water samples.

● Collect a sufficient number of appropriate types of quality-control samples

● Prevent nose, mouth, eye, and direct skin contact with water 

7.4.2 Aseptic Technique (from O’Ney, 2004)

Disposable latex or rubber gloves should be used to collection of nutrient samples. Some 

individuals have severe allergic reactions to latex. Field staff must avoid touching the opening of 

the sample collection container or its cap, or having the sample touch hands or arms. For each 

sample:

 If collecting samples for regulatory purposes, wash and scrub hands thoroughly to the midforearm, using antibacterial hand soap (or a hand sanitizer at 50 ppm chlorine equivalency, if 

available).

 Open the sample container taking care to avoid touching the inside surfaces or otherwise 

causing contamination

 Remove a glove by holding it from the wrist side opening inner surface. Avoid any contact 

with the outer surface of the glove.

 Do not touch anything with the exterior of the glove except the sample.
298

 If you have concern that the glove may be contaminated, discard that glove and use another 

sterile glove.

 With the gloved hand, collect the sample. 

 After sample has been collected, close the sample container, remove and discard the glove 

and place the sample in a 4oC cooler.

7.4.3 Sample Bottles

Use 150 to 600 mL plastic nutrient sample bottles (supplied by the laboratory). It is important 

to have extra bottles as they occasionally can be swept away in current or contaminated. Some 

laboratories provide bottles with relatively ―waterproof‖ labels already attached. Other labels are 

more susceptible to wear and general consist of regular paper. If this is the case, it is best to 

place a scotch tape over the label. It is sometimes easier and more efficient to label the bottle 

before sampling; this avoids having to dry off the bottle or write on a wet label. Pre-labeling (in 

the office or field vehicle) can also save time in the field (important during rain events).

Laboratory-supplied bottles contain a small amount of sulfuric acid preservative for samples to 

be analyzed for ammonia. These bottles should be clearly marked with ―H2SO4‖. Since this is a 

strong acid, avoid contact with skin. Use a clean ―transfer‖ bottle to collect the sample, and then 

transfer it to the bottle containing preservative. Bottles for analysis of other nitrogen parameters 

will not contain preservative. 

7.4.4 Collecting the Samples

(Adapted from USGS-NFM #5)

Prepare for sampling

6. Upon arrival at the field site, set out safety equipment such as traffic cones and signs. 

7. Take extra bottles in case of contamination or loss

8. Take enough bottles to obtain QA/QC samples (see QAPP)

9. Label bottles but leave ―time‖ field blank until actual sample collection

Determine the sampling location

6. Visually inspect the stream from bank to bank and longitudinally, observing velocity, 

width, and depth distribution, and apparent distribution of sediment and aquatic biota 

along the cross section. Note and document the location of stagnant water, eddies, 

backwater, reverse flows, areas of faster than normal flow, and piers or other features 

along the cross section.

7. Check the site list to determine whether the sample is to be collected in a pool or 

flowing area (or both). If sampling from a flowing area, identify the area of the 

stream that appears to be completely mixed (the centroid of flow). This may be 

determined ahead of time from reliable discharge measurements (see Initial Site 

Establishment – SOP#11 and Flow Measurement – SOP#9). Do not disturb the 

sediment before collecting a water sample. 

8. For pools, if shallow (< 1 ft) take measurements at a middle depth. If the pool is from 

1-4 ft deep collect a sample at a depth that meets monitoring objectives (Wilde et al, 

1999)
299

9. For flowing water, sub-surface samples are taken at 0.1 m (4 inches) below the water 

surface if water level is < 5 ft (1.5 m). Samples are collected at the surface when 

water depth is < 0.1 m (Puckett, 2002). Sampling from the shoreline of any water 

body (meaning standing on shore and sampling from there) is the least acceptable 

method, but in some cases is necessary (Puckett, 2002).

10. Collect the nutrient sample at the same location as you will be collecting the bacteria 

sampling and measuring core parameters.

Water samples are collected from a location in the stream where the stream visually appears to 

be completely mixed. Ideally this would be at the centroid of the flow (Centroid is defined as the 

midpoint of that portion of the stream width, which contains 50% of the total flow), but depth 

and flow etc. do not always allow centroid collection (Puckett, 2002).

Collect the sample

Note: Collect water samples first to avoid disturbing the sediment and re-suspending sediment or 

bacteria

The USGS uses the ―Hand-dip‖ method (Myers, 2003) if stream depth or velocity is not 

sufficient to use depth-integrated sampling. The procedure minimizes the collection of surface 

films and avoids contact with the streambed. The method is as follows:

1. Open plastic bottle; grasp the bottle near the base, with hand and arm on the 

downstream side of the bottle.

2. Without rinsing, plunge the bottle opening downward below the water surface. Allow 

the bottle to fill with the opening pointed slightly upward into the current.

3. Inspect each sample, looking for overfilling and (or) the presence of large amounts of 

particulates that might have been captured due to excessive streambed disturbance 

during sample collection. If you note either or both of these conditions, discard the 

sample, making sure there are no residual particulates left in the container, and 

resample. 

4. Place the sample bottle in an ice-chest immediately. [NOTE: Use blue ice (often 

provided by labs), not wet ice to avoid possible contamination by contact with the 

melt water.] Ensure that the bottle label is completed with the date, time, site ID, and 

initials of field personnel. 

5. Check the temperature of the ice-chest and refrigerator (if used); it must be between 

1-4 C. Samples should be stored in the dark.

6. Ensure that the samples are transported to the laboratory within designated EPA hold 

time (see Table 7.1 in this SOP). 

7.5 Field Preparation and Laboratory Coordination

When starting work with a new laboratory, the Water Quality Specialist should develop a good 

working relationship with a laboratory manager and also a chemist/microbiologist. Discuss 

analytical methods, detection limits, holding times. Obtain official chain of custody forms from 

the lab as well as any needed bottles, cooler, and ice packs if the laboratory provides these. 
300

Discuss sample drop-off and pick-up possibilities. Also discuss the labs’ capacity for the 

number of samples you will have. General tasks list include:

 Notify the lab at the beginning of the season, or as early as possible, of your sampling 

schedule

 Call the lab the day before or the morning of sampling to verify sample collection

 If at all possible, schedule sampling early in the week rather than later.

 Fill out the chain of custody form ahead of time except for the sample time

The chain of custody form is a means of tracking samples from receipt in the laboratory through 

analysis, to final disposal of the sample. It should be filled out in ink. The chain-of-custody 

Forms travel with the samples during the transfer, and are filed in the laboratory project files. 

Upon arrival at the laboratory, the ―sample custodian‖ at the lab inspects the sample containers to 

ensure that the sample seals are intact and the sample containers have not been damaged. If any 

seals have been broken and/or any sample containers damaged, the sample custodian records the 

condition of the seals and containers on the chain-of-custody Form. The sample custodian takes 

custody of the samples by signing, dating, and noting the time in the on the chain-of-custody 

form.

Once at the laboratory, if samples need to be subdivided and submitted to another laboratory subcontractor, this information should be noted on the original chain-of-custody form, and a new 

chain-of-custody form with the other lab should be initiated (Puckett, 2002).

Equipment Checklist

Scotch tape

Hand sanitizer

Bottle labels

Disposable gloves

Sample bottles

Data sheets printed on waterproof paper

Ice chest

Thermometer for ice chest

Chain-of-custody form

Sharpie (permanent pen)

Water jug for washing hands

Soap

Also, consult SOP#2 for safety equipment. 

7.6 Quality Assurance/Quality Control 

Duplicate samples should account for 10% of the total number of nutrient samples collected. It 

is also recommended that a field blank and trip blank be conducted (1 for every 20 samples). 

The lab will conduct a ―matrix spike.‖ Also consult the laboratory and request information on 

their quality control as well. Data Acceptability Criteria for Analysis of Water Quality Samples 
301

and QA/QC requirements are discussed further in the QAPP.

7.7 Data Reporting

A data analysis overview is provided in the protocol narrative. Details of data analysis are 

discussed in SOP #10. 

Regardless of the form of the nitrogen measured, it should be reported in units of milligrams of 

nitrogen per liter (mg-N/L), so that there is the same amount of nitrogen in 2mg-N/L of nitrate as 

in 2mg-N/L of ammonia. Labs don’t always report nitrogen this way; sometimes it is reported 

as the nitrate-nitrate. If it were reported in mg/L of ammonia and mg/L of nitrate, it would be 

difficult to compare them, since one molecule of nitrate is much heavier than one molecule of 

ammonia. 

To convert from mg/L of ammonia to mg-N/L of ammonia, use the ratio of the molecular weight 

of nitrogen to the molecular weight of ammonia (14:18). To convert from mg/L of nitrate to mgN/L of nitrate, use the ratio of the molecular weight of nitrogen to the molecular weight of nitrate 

(14:62).

Conversion factors: 

N-molecular weight = 14

Oxygen molecular weight = 16

N/NO3 = 14/14 +48 = 14/62 = 0.2258 (approximate conversion factor)

So if you have 45 mg/L of NO3 that equals 10 mg/L of NO3-N

45 mg/L NO3 * 14N/62 NO3 = 10 mg/L of nitrate-N

NH3:

N = 14

H = 1

N/NH3 = 14/14 +3 = 14/17 = 0.8235 (conversion factor)

7.7.1 Calculating Unionized Ammonia 

Ammonia results are often reported as total ammonia (TAN). The unionized ammonia (UIA), 

which is the toxic fraction, can be calculated as follows:

TAN x conversion factor from Table 1 = UIA (mg/L) 

Using the stream and pH and temperature at the time of sample collection, determine the 

conversion factor from Table 1.
302

Table 0.2 Fraction of unionized ammonia in aqueous solution at different pH values and 

temperatures. Calculated from data in Emmerson et al. (1975). 

Tempenlt\lre 

42.0 46.4 50.0 S3.6 57.2 60.1 64.4 88.0 71.6 75.2 78.8 82.4 116.0 88.6 

pH ("F) 

8 8 10 12 14 18 18 20 22 24 28 28 30 32 

(•C) 

7.0. .0013 .0016 .0018 .0022 .0025 .0029 0034 .0039 .0046 .0052 0060 .0069 .0060 0093 

7.2 .0021 .0025 .0029 .0034 .0040 .0046 .0054 .0062 .0072 .0083 .0096 .0110 .0126 .0150 

7.4 .0034 .0040 .0046 .0054 .0063 .0073 .0065 .0098 .0114 .0131 .0150 .0173 .0198 .0236 

7.6 .0053 .0063 .0073 .0086 moo .0116 .0134 .0155 .0179 .0200 .0236 .0271 .0310 .0369 

7.8 ,0084 .0099 ,0116 .0135 .0157 .0182 .0211 .0244 .0281 .0322 ,0370 .0423 .0482 057;2 

8.0 ,0133 ,0156 .0182 .0212 .0247 .0286 .0330 .0381 .0438 .0502 ,0574 .0654 .0743 .0877 

8.2 .0210 .0245 .Q286 .0332 .D385 .0445 .0514 .0590 .0676 .0772 .0880 .0998 .1129 .1322 

8.4 .0328 .0383 .0445 .0517 .0597 .0688 .o790 .0904 '1031 .1171 .1326 .1495 .1678 .1948 

8.1! .0510 .0593 .0688 .0795 .0914 .1048 .1197 .1361 ,1541 .1737 .1950 .2178 .2422 .2768 

8.8 .0785 .0909 .1048 .1204 .1376 ,1566 .1773 .1998 .2241 .2500 .2774 .3062 .3362 .3776 

9.0 .1190 .13.68 .1565 .1782 .2018 .2273 .2546 .2836 .3140 .3456 .3783 .4116 .4453 .4902 

9.2 .1763 .2008 .2273 .2558 .2861 .3180 .3512 .3855 .4204 .4557 .4909 .5258 .5599 .6038 

9.4 .2533 .2847 .3180 .3526 .3884 .4249 .4618 .4985 .5348 .5702 .6045 .6373 .6685 .7072 

9.6 .3496 .3868 .4249 .4633 .5016 ,5394 .5762 .6117 .8456 .6m .7078 .7358 .7617 .7929 

9.8 .4600 .5000 .5394 .5718 .6147 .6499 .6831 .7140 .7428 .7692 .7!il33 .8153 .8351 .8585 

10.0 .5745 .6131 .8498 .6844 .7166 .7463 .7735 .7983 .8207 .8408 .8588 .8749 .8892 .9058 

10.2 .6815 .7152 .7463 .7746 .8003 .8234 .8441 .8625 .8788 .8933 .9060 .9173 .9271 .9389 
303

7.8 References 

American Public Health Association, American Water Works Association, and Water 

Environment Federation. 1998. Standard methods for the examination of water and 

wastewater (18th ed.), pp. p. 2-8 to 2-11, American Public Health Association, Washington, 

D.C.

California Regional Water Quality Control Board, San Francisco Bay Region. 1995. Water 

Quality Control Plan-San Francisco Bay Basin (Region 2). 

California Regional Water Quality Control Board, San Francisco Bay Region. 2003. Conceptual 

Approach for Developing Nutrient TMDLs for San Francisco Bay Area Water Bodies. 

Oakland, CA.

Cooprider, M. 2004. San Francisco Bay Area Network Preliminary Water Quality Status Report. 

U.S. Department of Interior, National Park Service. 

http://www1.nature.nps.gov/im/units/sfan/wrd.htm

O’Ney, S. 2004. Procedures for Collection of Regulatory Parameters, Version 1.0, Standard 

Operating Procedure #6. In Regulatory Water Quality Monitoring Protocol, Version 1.0, 

Appendix E-SOPs, National Park Service, Great Yellowstone Network. Bozeman, MT. 37 

pp. plus appendices.

Puckett, M. 2002. Quality Assurance Management Plan for the State of California's Surface 

Water Ambient Monitoring Program ("SWAMP"). California Department of Fish and 

Game, Monterey, CA. Prepared for the State Water Resources Control Board, Sacramento, 

CA. 145 pages plus Appendices.

Stafford, S. and A. Horne. 2004. A Review of the Water Quality Monitoring Programs in the 

National Parks in Central Coastal California. Report to the National Park Service. 

Department of Civil & Environmental Engineering, University of California, Berkeley.

Swaddle, T.W. 1996. Inorganic Chemistry: An Industrial & Environmental Perspective. 1

st

Edition; Academic Press. 482 pp. 

Thompson, B. and Chambers, S. 2000. Pasquotank River Water Quality Program. 

Environmental Research Lab, Department of Geosciences, Elizabeth City State University, 

Elizabeth City, NC. http://www.ecsu.edu/ECSU/AcadDept/Geology/prwqp.htm

U.S. Environmental Protection Agency. 1986. Quality Criteria for Water. Office of Water, 

Regulations, and Standards. Washington, D.C.

Wilde, F.D., Radtke, D.B., Gibs, Jacob, and Iwatsubo, R.T., eds., September 1999, Collection of 

water samples: U.S. Geological Survey Techniques of Water-Resources Investigations, book 

9, chap. A4, accessed __date__ at http://pubs.water.usgs.gov/twri9A4/
304

SOP #8 Field and Laboratory Methods for Sediment

8.1 Revision History Log

Prev. Version 

#

Revision 

Date

Author Changes Made Reason for 

Change

New Version #

1.0 8/8/05 M. Cooprider Minor edits, 

incorporated 

comments from 

technical reviewer

Preparation for 

formal peer 

review

1.01

1.01 3/23/06 R. Carson Minor Edits Addressing 

formal peer 

review 

comments

1.02

Only changes in this SOP will be logged. ―Version numbers increase incrementally by 

hundredths (e.g. version 1.01, version 1.02 ...etc) for minor changes. Major revisions should be 

designated with the next whole number (e.g., version 2.0, 3.0, 4.0 ...). Record the previous 

version number, date of revision, author of the revision, identify paragraphs and pages where 

changes are made, and the reason for making the changes along with the new version number‖ 

(Peitz et al, 2002).

8.2 List of Acronyms Used for SOP #8

APHA American Public Health Association

DI depth-integrated

DIW deionized water

EWI equal width increment

FISP Federal Interagency Sedimentation Project

FTU formazin turbidity unit

GOGA Golden Gate National Recreation Area

I&M Inventory and Monitoring 

JOMU John Muir National Historic Site

JTU Jackson candle turbidity unit

LEW left edge of water

NPS National Park Service

NTU nephelometric turbidity unit

PINN Pinnacles National Monument

PORE Point Reyes National Seashore

REW right edge of water

RWQCB Regional Water Quality Control Board

SFAN San Francisco Bay Area Network

SOP standard operating procedure

SSC suspended sediment concentration

TMDL total maximum daily load
305

TSS total suspended solids

TTS turbidity threshold sampling

USDA United States Department of Agriculture

USGS United States Geological Survey

USEPA United States Environmental Protection Agency

8.3 Scope and Application

The purpose of this standard operating procedure (SOP) is to provide detailed guidance on 

methods of sediment sampling in the water column and analysis of sediment samples for 

turbidity, total suspended solids, and suspended sediment concentration. This SOP also provides 

guidance on operation of a turbidity threshold sampling station. Sampling locations and 

frequencies for 10 watersheds in four National Park Service (NPS) units of the San Francisco 

Bay Area network (SFAN) are discussed.

8.3.1 Introduction 

Sources of sediment in streams include erosion from stream banks, runoff from various source 

areas within a watershed, and re-suspension from the streambed during storm events. Some 

suspended solids can also originate from algal and bacterial growth. Sediments are deposited in 

areas where stream flow is slow. For example, gravel bars form along streambanks where flow 

is slower since a slower flow cannot transport as much sediment as high flows. Erosion and 

sedimentation are natural processes. However, agriculture and land development can accelerate 

these processes and result in an imbalance in the amount of sediment in a stream system.

The amount of sediment in water is quantified as milligrams per liter (mg/L) of total suspended 

solids (TSS). The method for determining TSS utilizes a sub-sample (100mL) of the overall 

sample. The method for determining suspended sediment concentration (SSC) is very similar to 

the TSS method except that the entire sample is used. Turbidity, another measurement of 

suspended sediment, is the capacity of suspended solids including clay, silt, finely divided 

organic and inorganic matter, soluble colored compounds, plankton, and microscopic organisms 

in water to scatter light (American Public Health Association et al., 1998). Turbidity is often 

measured in Nephelometric Turbidity Units (NTU). Other equivalent units that are used include 

Formazin Turbidity Units (FTU) and Jackson Candle Turbidity Units (JTU). High turbidity 

water can be described as cloudy or milky.

8.3.2 Sediment Impaired Waters within SFAN

In 2000, the San Francisco Bay Regional Water Quality Control Board (―Regional Board‖) 

identified both Lagunitas Creek and Tomales Bay as impaired by sediment. These watersheds 

are located in western Marin County within Golden Gate National Recreation Area (GOGA) and 

Point Reyes National Seashore (PORE). San Francisquito Creek is also listed as sediment 

impaired. West Union Creek, a tributary of San Francisquito Creek in San Mateo County, flows 

through Phleger Estate in GOGA. The Regional Board has established a timeline for 
306

development of Total Maximum Daily Loads (TMDLs) associated with these impairment 

listings (Table 8.1). 

Other watersheds within SFAN are negatively impacted by sediment but are not specifically 

listed but the Regional Board. One example is Strentzel Creek, partly located within John Muir 

National Historic Site (JOMU). Strentzel Creek is within the Alhambra Creek watershed in 

Contra-Costa County. Redwood Creek (GOGA) and other watersheds within SFAN also have 

sediment-related issues.

Table 0.1 San Francisco Bay Regional Water Quality Control Board TMDL Project Timeline as 

of 6-29-05.

Water body Park Unit Pollutant

Project Report 

Completion

Regional Board 

Adoption Date

San Francisquito 

Creek

GOGA Sediment Dec. 2005 Dec. 2006

Lagunitas Creek PORE, GOGA Sediment Dec. 2006 Feb. 2008

Tomales Bay GOGA, PORE Sediment Dec. 2007 Dec. 2008

These streams are listed because of habitat degradation due to deposition of fine sediments and 

due to their significance in providing critical habitat for threatened and endangered anadromous 

fish in the Bay Area. Populations of steelhead, salmon, and other native aquatic species have 

declined in the past fifty years in Bay Area streams. Other problems associated with excess 

sediment are related to water supply and include high turbidity and filling in of reservoirs (San 

Francisco Bay Regional Water Quality Control Board, 2003).

An approach for developing sediment TMDLs in San Francisco Bay Area streams was 

developed by the Regional Board in 2003. The first step in developing sediment TMDLs is to 

determine what factors impact fish populations (e.g., lack of flow, too much sediment, and fish 

migration barriers). These analyses also help establish priorities for watershed assessment, 

management, and restoration. Where sediment is verified to be a limiting factor, a sediment 

budget study will be conducted in order to quantify sediment inputs and outputs in a stream. A 

sediment budget study seeks to identify all sources of sediment and quantitatively estimate the 

amount of sediment transport to streams (San Francisco Bay Regional Water Quality Control 

Board, 2003).

SFAN staff is coordinating with the Regional Board. At this time it is uncertain what 

requirements there will be for sediment monitoring in the Olema, Lagunitas, and West Union 

Creek watersheds in association with the Sediment TMDL. Point Reyes National Seashore has 

monitored TSS in Olema Creek since 2000. Monitoring for TSS in GOGA began as early as 

1964 in some watersheds. SFAN also recently began water quality monitoring in West Union 

Creek, a tributary to San Francisquito Creek. In addition, in order to facilitate the development 

of a sediment TMDL for Tomales Bay and Lagunitas Creek, a Turbidity Threshold Sampling 

(TTS) unit was installed in Olema Creek, a tributary to Lagunitas Creek, in December 2002. 

This unit includes an automatic pump that collects water samples at a set of turbidity 

―thresholds‖ during a storm event. Samples are then analyzed for SSC. The turbidity, SSC, and 
307

water level data associated with the TTS station provide insights into the sediment transport 

dynamics within the creek.

8.3.3 Water Quality Criteria Recommendations for Sediment

Visible turbidity is considered to be greater than 5 NTU (Strausberg, 1983). Turbidities of 25 

NTU or greater have caused reductions in juvenile salmonid growth (Sigler et al., 1984). The 

National Park Service Water Resources Division uses a ―screening criteria‖ of 50 NTU to 

determine water quality exceedences in its Baseline Water Quality Inventory and Analysis 

Reports (National Park Service, 2003). More damage to fish and macroinvertebrates is probable 

if high turbidities remain in a stream system (Newcombe and MacDonald, 1991).

The UC Cooperative Extension Fact Sheet on Fishery Habitat provides a summary of the effects 

of varying turbidity and TSS concentrations on salmonids (Larsen, 1999; Lloyd, 1987). 

Juvenile and adult salmon experience moderate stress when exposed to more than six days of 

TSS greater than 10 mg/l or one day of exposure to TSS > 50 mg/L (Newcomb and Jensen, 

1996). High TSS (> 300 mg/L; ~ >40 NTU) inhibits fish feeding, can clog fish gills and can 

cover gravel spawning-beds (Creek Connections, 2004; Horne, 2003). Table 8.2 summarizes 

recommended water quality criteria. Ecoregion II refers to the ―Western Forested‖ Region that 

includes GOGA, MUWO, and PORE. Ecoregion III is the ―Xeric West‖ that includes PINN and 

JOMU.

Table 0.2 Recommended criteria for sediment.

Sigler et al., 

1984

Newcomb 

and Jensen, 

1996

EPA 

Aggregate 

Ecoregion II 

Criteria 

(2003)

EPA 

Aggregate 

Ecoregion 

III Criteria 

(2003)

Acute Total Suspended 

Solids

> 50 mg/L

Chronic (>6 days) Total 

Suspended Solids (TSS)

> 10 mg/L

Turbidity 25 NTU 1.30 NTU 2.34 NTU

Total suspended solids are listed in milligrams per liter (mg/L)



Turbidity is listed as nephelometric turbidity units (NTU)

In streams, the most desirable algae species are the diatoms, the golden brown algae. The 

golden brown color of coastal California streams is due to a thin coating of diatoms on the rocks 

and cobble. These diatoms can move slowly and form a nutritious biofilm on the rocks that is a 

major food supply for valuable insect larvae such as mayflies, caddis flies and snails. Clear 

water with low TSS is vital since not only must sunlight reach the steam bed but sediment-laden 

water will scour the rocks killing the diatom biofilm (Stafford and Horne, 2004). Certain species 

of macroinvertebrates are also sensitive to changes in sediment. Maintaining streams with TSS 

levels low enough to support fish, algae and other aquatic life is a significant concern for SFAN.
308

8.3.4 Sediment Levels in SFAN Waters

Total suspended solids and turbidity have been measured in GOGA since 1964. At Pinnacles 

National Monument (PINN), TSS has been measured from 1997 to 2001, not including 1999. At 

PORE, TSS has been monitored since 1997. A summary of TSS and turbidity data is included in 

Tables 8.3 and 8.4.

Table 0.3 Total Suspended Solids in mg/L.

PORE GOGA PINN

Maximum 1281 8000 240

Median 0.8 23 < 5 mg/L (detection limit)

Mean 10.2 98 154

# of observations 465 614 10

Table 0.4 Turbidity in Nephelometric Turbidity Units (NTU).

GOGA

Maximum 255, 270

Median 22.8

Mean 35.7

Note: Data is not currently available for PORE. 

PINN did not collect turbidity data. Data included

in this table is from 1964 to 2002 from the GOGA 

database (up to 1999) and subsequent stables studies (2000-2001).

8.3.5 Sediment Monitoring Rationale & Objectives

8.3.5.1 Sediment Concentration and Turbidity Comparisons 

Investigations regarding the comparability of TSS and SSC analytical results conclude that SSC 

and TSS collected from natural waters ―are not comparable and should not be used interchangeably‖ (Gray et. al., 2000). The methods for analyzing TSS and SSC are essentially the same 

except that SSC measurements are derived from the entire natural water sample while TSS 

samples are derived from a subsample (usually 100 ml of a 1 liter sample) of the natural water 

sample. Subsampling by either pipette or pouring from an open mouth bottle tends to produce a 

sand-deficient sample (Glysson et al., 2000). Therefore, TSS is typically slightly less than SSC 

(Glysson and Gray, 2002). Originally, TSS was developed as a proxy for SSC in wastewater 

samples. This comparability breaks down when conducted on natural water samples. 

Turbidity is a measure of interference in the water column produced by both mineral and organic 

particles. Monitoring efforts in the northern coast of California show that at certain times, the 

organic component of the flow can account for 60 – 80% of the turbidity measured at a site 

(Madej et al., 2002). TSS and SSC do not include this organic component.

There is a range of literature available showing that TSS and turbidity information can be 

correlated resulting in well-established relationships (Packman et al., 2000; Lewis et al., 2002). 

The same cannot be done with SSC and TSS (Glysson and Gray, 2002). While better correlation 
309

is found in samples with low sand content, there is a wide variability in these conditions between 

stations. While direct correlations between these parameters are problematic, the NPS proposes 

collection of TSS or SSC in addition to turbidity. Results of paired analysis (turbidity and either 

TSS or SSC) will be used to report results for each of the monitored stations. 

8.3.5.2 Sediment Monitoring Questions

1. Is turbidity chronically high (how long does turbidity remain in a stream after the peak 

of a storm event)? Justification: Chronic turbidity is more of a concern for fish then 

sediment spikes that are typical in winter storms in coastal California; fish find refuge during 

storms. This can also help determine whether management practices to reduce erosion are 

effective. In addition, data can be plotted with lines indicating various turbidity thresholds;

see Section 1.3 of this SOP. 

2. Are the magnitudes of the winter spikes changing? Justification: This helps assess the 

condition of the land and determine whether the sediment load is increasing or decreasing 

over time. This can also help determine whether management practices to reduce erosion 

are effective.

3. What and where are the sources of sediment within the watersheds? Justification: If 

problems are identified through questions #1 and #2, the sediment sources will need to be 

identified. Much sediment reduction work is conducted via geomorphology or other surveys 

and may not necessarily require water quality sampling for sediment. It is critical 

that park and network staff work together to identify sediment sources and discuss possible 

site locations for sediment monitoring if it is deemed necessary.. 

4. Is there a significant relationship between turbidity and SSC during a storm event or at other 

times of the year? Justification: Once a relationship is established, turbidity can be used as 

the primary indicator of sediment water quality. Turbidity is a more simple and cost 

effective means of monitoring sediment. 

Monitoring questions #2 and #4 require a turbidity threshold sampling station and therefore 

would only apply to Olema Creek. Monitoring question #3 may be beyond the scope of the I&M 

program but is included here since it is important for the parks. Monitoring as part of the 

freshwater quality protocol will focus on question #1. However, additional information related 

to questions #2, 3, and 4 is provided in this SOP as reference. Table 8.4 provides information 

about monitoring location and frequency for each of the sediment monitoring questions.
310

Table 0.5 Sediment monitoring questions, location, sampling frequency and analysis.

Monitoring 

Question

Watershed Location Frequency Analysis

Chronic 

turbidity

All; in-situ 

sensor priority: 

Lagunitas, 

Olema, 

Redwood, Pine 

Gulch, West 

Union

All water quality 

monitoring sites, insitu turbidity sensors 

at stream gauges if 

applicable

After storms and 

continuously (rotate 

the in-situ turbidity 

sensor to cover all 

watersheds) 

Turbidity by 

turbidimeter and in-situ 

sensor; TSS

Magnitude of 

sediment 

spikes

All At long-term water 

quality monitoring 

stations or fish index 

reaches

2-3 storm events each 

annually (must catch 

peak of storm event)

Turbidity, TSS, particle 

size

Sediment 

sources

As needed Upstream and 

downstream of 

suspected sources

Storm events; coarse 

level erosion inventory

Turbidity, TSS

Turbidity vs. 

SSC

Olema Bear Valley Rd. 

bridge, TTS station

As many winter storm 

events as possible

Turbidity by in-situ 

sensor, SSC

Watersheds to be monitored for chronic turbidity (question #1) include Lagunitas Creek, Olema 

Creek, Redwood Creek, Pine Gulch, West Union Creek, Strentzel Creek, Rodeo Creek, 

Tennessee Valley, Chalone Creek, and Franklin Creek. Water samples should be collected as 

soon as possible after a storm peak. Collect at least 1-2 samples near the peak, then daily until 

the water clears (Randy Klein, personal communication, 5 July 2005). Just 4-5 samples during 

the recessional limb of a hydrograph can be useful since this is when chronic turbidity occurs 

(Randy Klein, personal communication, 5 July 2005). 

8.4 Field Techniques

8.4.1 Introduction

Sampling during storm events presents unique challenges in the San Francisco Bay Area. Winter 

weather is unpredictable with significant variation in rainfall quantity and distribution among and 

within the parks. Watersheds are small and stream stage and velocity can increase rapidly in a 

very short period. The I&M Freshwater Dynamics protocol will include measuring stream stage 

and velocity in order to create a hydrograph. The hydrograph is a very useful tool to predict 

stream flow. In planning sediment sampling events, it is important to be aware of impending 

weather conditions and to be familiar with each stream’s hydrograph. 

8.4.2 Preparations and Field Rinsing of Equipment

(Adapted from Radtke and Wilde, 2002)

Most equipment used for sample collection and processing is field rinsed with the water to be 

sampled just before the water samples are collected. The purposes of field rinsing are to 

condition, or equilibrate, the equipment to the sample environment and to help ensure that all 

cleaning solution residues have been removed before sampling begins.
311

To field rinse a surface-water sampler and sample bottle:

1. Put on appropriate disposable, powderless gloves.

2. Partially fill and rinse the sampler and bottle with the water to be sampled (rinse water). 

Avoid getting sand in the rinse water. If there is not a sufficient amount of sample water, 

use deionized water (DIW). 

3. Shake vigorously to rinse. Discard the rinse water by swirling the solution out of the 

bottle or sampler. Swirl and then drain the rinse water from the sampler through the 

nozzle. Shake off adhering water droplets. 

Equipment Checklist 

Gloves

Bottles appropriate for DH 48 sampler

DH 48 wading sampler

Velocity meter

Tape measure/tag line

Chaining pins

Personal flotation device and other safety equipment

Watch

Data sheets/Rite in the RainTM notebook

8.4.3 Isokinetic, Depth-Integrated Sampling

Because suspended sediment concentration varies from the water surface to the stream bed and 

laterally across a stream, depth integrated sampling will be utilized. This will help ensure that 

the entire water column of the stream is adequately represented. For depth-integrated sampling 

within SFAN, the equal-width-increment (EWI) method will be used. Consult the USGS 

National Field Manual for specific information regarding this method. 

There are several different kinds of samplers used for depth-integrated sampling; SFAN uses the 

sampler model DH-48. For isokinetic sampling with a bottle sampler, the mean velocity of the 

vertical that is sampled must exceed 1.5 ft/s (Webb et al., 1999). In the sampling operation the 

intake nozzle is oriented into the current and held in a horizontal position while the sampler is 

lowered at a uniform rate from the water surface to the stream bottom and instantly reversed. The 

sampler continues to take its sample throughout the time of submergence. For detailed 

specifications, sampler assembly, and instructions for use of the DH-48 sampler see the Federal 

Interagency Sedimentation Project information on the DH-48 sampler ((FISP, 1958). This 

information can be found at http://fisp.wes.army.mil/Instructions%20US%20DH48%20001010.PDF or in Appendix A of this SOP.

Before field work, clean appropriate parts of the sampler and store in plastic for transport to the 

field site. All sampling equipment should be checked prior to heading out into the field. A clean 

sampling container and nozzle should be used for every sample. Refer to the pre-field check list 

for the D-48 isokinetic sampler in Table 8.5. 
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Table 0.6 Pre-field check list for D-48 hand-held samplers (adapted from the Federal Interagency 

Sedimentation Project (FISP, 1958) and Webb and Radtke, 1998, Selection of Equipment for 

Collection of Water Samples.

 Items Comment

Sampler body Inspect sampler body for damage and missing parts.

Air exhaust port Both ends should be clear and unobstructed to ensure inflow efficiency.

Nozzle The yellow nozzle should be straight with no visible signs of damage, check for 

damage to the threads on the nozzle; also inspect the bore for straightness and 

any signs of burrs or deformity. If damage or burrs are found in the bore or at 

either opening, it should be discarded and replaced with a new nozzle.

Bottle gasket If the gasket is hard to the touch torn, or will not fit flush in the gasket seat of 

the sampler, it should be discarded and replaced. If the gasket is in good 

condition, it should remain in place once it is pressed into the seat. 

Sampling container Inspect the bottle for cracks and ensure that it is clean.

Wading rod and extensions Check for damage to screw threads.

Mechanical Operation Test the overall working condition of the sampler.

Laboratory results from

analysis of sampler blank

Make sure the sampler has been quality assured with an

annual equipment blank and certified for water-quality use.

Separate sets of sampler 

components and back-up 

components

If at all feasible, for a given field trip when collecting

multiple water samples, prepare and use separate sets of

sampler bottles, caps, and nozzles for each sampling site.

Have backup equipment available on-site.

Field-cleaning supplies and 

blank water

If separate sets of sampler components are not available, then clean equipment 

between sampling sites and be prepared to process the number of field blanks 

needed to document that equipment was adequately cleaned.

Preparation for sampling:

 Set up a tape measure or tag line across the stream, record the left edge of 

water (LEW), facing downstream, and the right edge of water (REW) and 

width (see data sheets in Appendix B).

 Obtain a discharge measurement noting the range in velocities across the 

channel. Consider whether the distribution of sediment will change during 

sample collection. 

 Velocity must at least 1.5 ft/s but should not exceed 9.0 ft/s in order to collect 

an isokinetic sample with the DH-48 (Webb et al., 1999).

 When choosing a cross sectional width to sample, avoid side channel eddies. 

The depth-integrated sampler cannot be used where there is upstream eddy 

flow.

 Maximum safe wading depths depend on the size of the field technician, the 

stream velocity, and the streambed material. In general, do not attempt to 

wade in a stream for which values of depth multiplied by velocity are greater 

than or equal to 10 ft2/s. Caution should also be used if the stream depth is 

greater than 3 ft. 

 Always wear a personal flotation device and be familiar with other safety 

procedures listed in SOP#2-Personnel Training and Safety. 

 A rope deployed depth-integrated sampler such as the DH-59 can be utilized 

from a bridge during high flows where the wading sampler cannot be used. 

The DH-59 is recommended for high road bridges such as Bear Valley Rd. 
313

over Olema Creek, Hwy. 1 over Redwood Creek, and Hwy. 146 over Chalone 

Creek). 

 Alternatively, for depths too deep to wade, the DH-48 has wading rod 

extensions in 3-ft lengths that can be added for use from a boat or low bridge 

(e.g., pedestrian trail bridges over Franklin Creek, Rodeo Creek, and Bear 

Gulch). With all extensions, the maximum sampling depth is 9 ft.

● A plastic 500mL sample bottle should be used for depth-integrated sampling. 

Ensure that the sampling bottle is not cracked. 

Depth-integrated sampling technique: (adapted from Webb et al., 1999)

1) Divide the channel into 10-15 vertical panels (―increments‖), no more than 20 depending on 

the width of the channel and the range in velocities. For a cross-sectional width of < 5 ft, use 

as many increments as practical, but equally spaced a minimum of 3 in. apart. For a width of 

> 5 ft use a minimum of 10 equal width increments. 

2) Starting at the LEW, take a sample from the midpoint of each vertical into the same bottle.

3) Lower the sampler until slight contact is made with the streambed.

4) Do not pause upon contacting the streambed. Raise the sampler immediately at a constant 

transit rate to complete the vertical traverse. The descending transit rate does not have to 

equal the ascending transit rate, but each rate must be unidirectional and constant, until the 

sampler bottle is full.

5) Take care not to disturb the stream bed or disrupt flow (be aware of your location the stream)

6) Fill the bottle 75-90% full (approximately 375 to 420 mL). If the bottle becomes entirely full 

full, the sample should be discarded since it may not be representative (Federal Interagency 

Sedimentation Project)

10) Note the stage height. If it is changing rapidly, move fast across the stream as 

you fill the bottle.

11) Dry the bottle and label each bottle with site location ID, date, time and initials of field crew. 

It is helpful to partially fill out the label before heading into the field.

12) Place the bottle in a cooler with blue ice and keep chilled at 4°C in the dark. Samples should 

be analyzed for SSC as soon as possible (within 24hrs), and should not be stored more than 

seven days. Turbidity measurements should be taken as soon as possible within 24 hrs. 

(American Public Health Association et al, 1998). 
314

Figure 0.1 From USGS National Field Manual (Webb and Radke, 1998).

8.4.4 Non-isokinetic Sampling 

For isokinetic sampling with a bottle sampler, the mean velocity of the vertical that is sampled 

must exceed 1.5 ft/s. If this minimum velocity is not met, collect grab samples using an open 

mouth sampler at the centroid of flow approximately 12 inches below the water surface, if 

possible. The hand-held bottle sampler is the simplest type of open-mouth sampler. A bottle is 

dipped to collect a sample where depth and velocity are less than the minimum requirements for 

depth-integrating samplers.

8.4.5 Turbidity Threshold Sampling 
315

Due to the status of Lagunitas Creek and Tomales Bay as sediment-impaired waters, Olema 

Creek, a tributary to Lagunitas Creek, was chosen as a location to conduct turbidity threshold 

sampling (TTS). As part of this pilot project, Point Reyes National Seashore contracted with 

Graham Matthews & Associates to perform the installation of the TTS unit and to provide 

training for operation of the TTS unit. In December 2002, the TTS unit was installed at the 

Olema Creek stream gauge at the Bear Valley Road Bridge near the park headquarters. Over the 

past few years, the consultant has made numerous system modifications and park staff has been 

learning the operation and maintenance of the system. The system was fully functional in May 

2003. Subsequent storms have damaged this sampling station and the functionality of the TTS 

unit. Repairs will be made, and the unit will be brought back online as time and funding permit.

8.4.5.1 Introduction

Turbidity threshold sampling involves methodology and instrumentation developed by the U.S. 

Department of Agriculture (USDA), Forest Service, Redwood Sciences Laboratory (Lewis, 

1996; Lewis and Eads, 1996; Eads and Lewis, 2002; Lewis, J., R. Eads, and N. Cambell-Lund, 

2002). The TTS procedure involves collecting water samples that are distributed over a range of 

rising and falling sediment concentrations in a stream. The data resulting from TTS can be used 

to determine suspended sediment loads by establishing a relationship between sediment 

concentration and turbidity. A general description of turbidity threshold sampling was written by 

Rand Eads (2001) and is included below. The document with photos of TTS station components 

can be found at http://www.fs.fed.us/psw/topics/water/tts/tts_inst.shtml .

The Importance of Automated Data Collection:

The ability to collect useful information about suspended sediment transport and water 

discharge is dependent on the timing and frequency of data collection during storms. All 

river systems, particularly smaller watersheds that respond very quickly to rainfall, 

benefit from automated data collection. In rain dominated regions most suspended 

sediment is transported during a small number of events. Although it is possible to rely 

solely on manual measurements, important storm flows are usually infrequent and 

difficult to predict. When they do occur, trained personnel may not be available to collect 

the required information. Infrequent, systematic manual sampling will not provide 

adequate information to make credible suspended sediment load estimates under these 

conditions. As of yet, there is no reliable method to directly measure suspended sediment 

concentration in the field. Usually water discharge is not a good predictor of sediment 

concentration for rivers and streams that transport the bulk of their sediment load as fines 

because the delivery of sediment to the channel from hillslopes, roads, and landslides is 

highly variable. For rivers that transport mostly sand, water discharge and concentration 

may be more closely coupled if transport depends mainly on stream power to mobilize inchannel sources that are not easily flushed from the system. However, in streams 

transporting fine sediment, a sampling scheme that employs a parameter such as 

turbidity, which can be well correlated with suspended sediment concentration, can be 

expected to improve sampling efficiency and load estimation. Turbidity threshold 

sampling collects physical samples that are distributed over a range of rising and falling 

turbidities (Lewis and Eads: 1996, 1998 and 2000). The resulting set of samples can be 

used to accurately determine suspended sediment loads by establishing a relationship 
316

between sediment concentration and turbidity for any sampled period and applying it to 

the continuous turbidity data. 

How Turbidity Threshold Sampling Works:

Turbidity is an optical measure of the number, size, shape, and color of particles in 

suspension. A number of manufacturers offer turbidity probes that can be deployed on a 

continuous basis in streams. The optical properties of sediment, mainly size and shape, 

have a large influence on the magnitude of the turbidity signal. For instance, sand 

particles return a much lower turbidity signal for a given concentration than silt and clay 

particles of the same concentration. TTS utilizes turbidity thresholds, points at which 

physical samples are collected, distributed across the entire range of expected rising and 

falling turbidities. Contamination of turbidity probe’s optics by debris, algae, or 

macroinvertebrates can lead to a noisy, or progressively increasing, turbidity signal. 

Sensors with reliable optical wipers, such as the DTS-12, manufactured by FTS, can 

reduce optical fouling and are recommended to improve data quality. Careful design of 

the turbidity probe’s housing and mounting hardware can reduce fouling from large 

organic debris. 

Turbidity thresholds are selected by taking into consideration the maximum expected 

turbidity value for a stream, the range of the turbidity probe, and the number of desired 

physical samples based on the magnitude of the storm. In our experience, using a squareroot scale to distribute the thresholds provides an adequate pairing of turbidityconcentrations to produce acceptable regressions. For the smallest storms, three or four 

samples should be adequate, while large events may produce 5 to 15 samples. Different 

sets of thresholds are used when turbidity is rising and falling, with more thresholds 

required during the much more prolonged falling period. The user can fine-tune the 

distribution of thresholds to maximize efficiency. A set of rules, in addition to the 

predefined turbidity thresholds, aids in reducing sampling during short duration turbidity 

spikes, ensures that a ―startup‖ sample is collected at the beginning of a storm, and 

defines reversals in turbidity. The rules permit continued sampling when turbidity levels 

exceed the turbidity probe’s range, and they allow collection of non-threshold, manually 

triggered samples to be paired with depth-integrated samples or to augment sample 

numbers if desired.

Closely spaced turbidity measurements produce interesting trends in sediment transport 

such as spikes superimposed on the storm turbidigraph that often indicate landslides or 

streambank failures upstream. In the case of nested watersheds, the timing and magnitude 

of these sediment pulses may provide additional information about cumulative effects, or 

dilution, downstream. Authenticity of these turbidity spikes is confirmed when physical 

samples taken during the spikes have higher concentrations than surrounding samples.
317

Instrumentation:

Data Logger and Sampling Logic

A programmable data logger is required to make the required sampling decisions. For 

remote locations, it is important that the data logger has low power requirements in order 

to preserve the battery’s capacity. The TTS program only requires input information 

about stage and turbidity to decide what actions to take. Wake-up intervals are either set 

at 10-minutes for small, flashy watersheds, or at 15-minute intervals for larger basins. At 

the beginning of each wake-up interval, the OBS-3 turbidity probe, under control of the 

program logic, collects 60 measurements in 30 seconds (mention of product names is not 

an endorsement by the USDA Forest Service). Next, the raw turbidity values are sorted 

and the median value is determined. We have found that these two operations effectively 

reduce outlier values. In the case of the DTS-12, the sampling frequency and period, and 

reported statistics, are controlled by the sensor's onboard processor. The program next 

collects 150 stage readings in three seconds from a pressure transducer and computes the 

mean stage. The mean stage is then compared against the minimum operating stage to 

determine if the turbidity probe and sampler intake are adequately submerged (stage is 

above "baseflow") to allow sampling. If the program logic determines that a sample is 

required, based on the rules discussed above, it activates an automatic water sampler to 

collect one sample. Other instruments, such as tipping bucket rain gages and water 

temperature probes, may be connected to the data logger to provide additional 

information. Finally, all pertinent records are written to data logger memory. The TTS 

logic, discussed above, has been developed for Campbell data loggers. The TTS program 

is executed from the Campbell CR10X data logger platform

Turbidity Probe

The OBS-3 turbidity probe, manufactured by D&A Instrument Company, is a backscatter 

nephelometer that emits infrared radiation (IR) into the water column. The distance the 

IR penetrates the water depends on the probe's optical configuration and the amount and 

type of sediment in suspension. The penetration, or volume sampled, decreases with 

increasing concentration of material. The scattered IR returned to the sensor’s detector is 

a function of particle size and shape and the number of particles in suspension. 

Comparisons made with different turbidimeters should be viewed with some skepticism 

due to inconsistencies in light sources, calibrations, and the sampled volume. Periodic 

calibration of the turbidity sensor in formazin standards is required to compensate for 

instrument drift and scratched optical surfaces. Sensors with a small viewing area (1 cm 

or less) reduce the chance that large debris will be viewed by the optics and allow for 

shallow deployment. Small viewing areas often do not provide adequate sampling 

volume and may produce noisy data. Large viewing areas (7 to 25 cm) have the opposite 

characteristics. A viewing area of 4 to 7 cm is a good choice. 

The turbidity probe housing reduces contamination from organics by shedding debris. 

The housing, if properly designed, can reduce hydrodynamic noise caused by turbulence 

and the entrainment of air or re-suspension of sediment close to the sensor. The housing 

also protects the sensor from direct impacts by large submerged organic debris. 
318

Note: The DTS-12 turbidity sensor is now more commonly used, is the recommended 

sensor, and is self-cleaning (Randy Klein, personal communication, 7 July 1005).

Sampling Boom

The boom positions the turbidity probe and sampler intake at the appropriate position and 

depth in the stream. Since the boom is articulated, large floating organic debris can, on 

impact, lift the vertical arm of the boom to the surface and pass underneath. Increasing 

water velocity and depth pushes the vertical boom arm downstream, raising the turbidity 

sensor higher in the water column. A counterweight prevents the boom from rising to the 

water surface. The highest probability of contamination by organics, and resulting loss of 

data, occurs during flood stages when organic material is recruited from flood plains. A 

bank-, cable-, or bridge-mounted retrievable boom is desirable for all but the smallest 

streams to allow debris removal during high flows. The depth of the turbidity probe can 

be adjusted as needed to position the probe above the zone of bedload transport and 

below the water surface. Changing the depth of the turbidity probe can change the ratio of 

coarse and fine particles sampled by both the turbidity probe and sampler intake. 

-By Rand Eads,Redwood Sciences Laboratory, 2001.

TTS is a high level of monitoring and is very intensive in terms of maintenance/troubleshooting 

and the number of samples that are collected. For example, 200 samples could be collected 

during a few storm events. A significant amount of time is also required to correct turbidity data. 

For other streams besides Olema, a lower level of monitoring can be just as effective. For a 

turbidity threshold sampling station, instead of fixing on one turbidity threshold as a standard, it 

is useful to determine the number of hours that turbidity exceeded various thresholds such as 25, 

50, 100, 200, 500, and 2000 NTU ((Randy Klein, personal communication, 7 July 2005).

Without a TTS unit it is difficult to capture the peak of a storm event. A useful alternative is to 

take samples during the recessional limb of a storm since this is where chronic turbidity occurs. 

Even four to five samples can provide enough points to create a recessional turbidity curve. Four 

to five samples from four storm events can provide enough points to have an overlay that fits 

well over the curve produced from 200+ samples collected by the Isco automatic sampler. 

Overlaying these curves on each other also allows you to see the point at which watershed size 

and geology affects on the curve disappear. Focus on taking 1-2 samples immediately after the 

storm peak then one every day until the water clears. Favor more samples closer to the peak 

(Randy Klein, personal communication, 7 July 2005).

8.4.5.2 TTS Program 

The Turbidity Threshold Sampling Program for the CR10X datalogger contains all of the 

program information including turbidity threshold codes, sample codes, subroutines, pressure 

transducer and turbidity sensor wiring and connections and other electronic aspects of the 

program (Lewis et al., 2002). The program ―wakes-up‖ and records measurements every 10 

minutes at the Olema TTS station. The OBS-3 sensor measures turbidity at 0.5 second intervals 

for 30 seconds for a total of 60 readings. The median turbidity of these readings is then saved. 
319

The median turbidity and average stage values are used to trigger a pumping sampling if the 

sampling criteria are satisfied (Lewis et al., 2002).

Detailed instructions on programming the data logger, initializing a new station, connecting to an 

existing station, and retrieving data from a TTS station are included in the TTS Field Manual in 

Appendix C.

8.4.5.3 Summary of Field Tasks and Data Analysis for TTS

1. Check the station weekly and during every storm event (see Table 8.6)

2. Troubleshoot station instrumentation as needed

3. Calibrate turbidity

4. Calibrate sediment concentration using depth integrated (DI) sampling during a 

storm event

5. Conduct laboratory and data analysis including:

● Conduct laboratory analysis for SSC

● Develop a standard procedure for data management

● Develop turbidity - sediment rating curve (TTS rating curve)

● Plot DI sample turbidity against ISCO sampler turbidity

● Plot DI sample SSC against ISCO sample SSC 

Table 0.7 TTS Weekly Field Visits (complete these tasks in the order listed).

Task Notes

Observer Record In the yellow ―Rite in the Rain‖ ® station notebook record the 

following:

▪ Date, time, observer initials, battery IDs

▪ Presence of sediment, debris, or obstructions affecting turbidity 

 probe. Wait until after data collection to correct problems

▪ View Left, Right, and Inside State

Check the ISCO Sampler ▪ Note the ―next sample‖ value displayed by ISCO

▪ If > 2 minutes until a wakeup, inspect samples

▪ If volumes are too low* or high, see ―Troubleshooting‖ in the 

 TTS field manual (Appendix C)

Interrogate the data logger ▪ Launch the PC208Q software and connect to data logger.

▪ View and record the current values in the numeric window.

▪ Staff plate reading must be verified within 5 minutes of data 

 record on display in numeric window

Optional: collect a DI or AUX sample ▪ Set appropriate sample flag

▪ Collect the sample at the next wakeup

▪ Update your record of staff plate readings and current values 

 shown in the numeric window

Retrieve Data ▪ Choose between a ―snapshot‖ data check and a Data Dump

▪ If dumping, set Dump Flag. (Confirm staff plate reading). 

▪ Collect data, then disconnect from data logger and exit 

 PC208 W program.

Service turbidity probe ▪ Remove debris and sediment from housing, mounting 

 apparatus, etc.

▪ Inspect/remove debris from inside housing.

▪ During non-storms, clean optics if necessary
320

Service flume or weir or rated section (section 

with hydrologic rating curve)

▪ Clear branches and debris

▪ Shovel sediment deposits downstrream through flume. 

▪ Flush stilling well intakes if needed.

▪ Record changes in staff plate readings.

ISCO Sampler Only if data is dumped, change ISCO bottles 

and reset distributor arm

System batteries Replace low Gel cell battery only after confirming 9V > 9.0 volts

Dessicants Check/replace dessicants

Additional Tasks ▪ See maintenance schedule

▪ Troubleshoot suspect equipment

Plot the data ▪ Run R_FieldPlot to graph the data

Complete the electronic field form Run the Corel Database program to create an electronic field 

form incorporating your comments from the station notebook.

*ISCO sample bottles are 1000mL, the minimum sample volume for SSC analysis is 350 mL.

8.4.5.4. Calibrating the TTS Station

The USGS protocol for wading vs. bridge sampling is when the velocity x depth is > 10, then use 

a rope deployed sampler (DH 59) for DI sampling from a bridge. Otherwise, use common sense 

to determine when to use the DH 48 wading sampler. Calibration should be conducted during a 

storm event in order to capture a large range of turbidities. Ideally, the DI sample would be 

taken during the largest storm event in order to have the most turbidity thresholds (all thresholds 

that would occur for that particular stream). The TTS station needs to be calibrated several times 

at different stages in the hydrograph. Depth-integrated sampling needs to be done for each new 

turbidity threshold so that a rating curve can be developed. DI samples represent the crosssectional average sediment concentration and are used as ―truth‖ to correct the TTS station ISCO 

pumped samples that are not flow-weighted but are point samples. The DI sample field data 

sheet is in Appendix B.

Sediment Calibration 

1) Set up a tape measure across the stream, record LEW and REW, and width.

2) Measure the range in velocities across the channel.

3) See Section 2.3 for details on collecting a depth-integrated sample.

4) Divide the channel into 10-15 panels (no more than 20) depending on with of channel and 

range in velocities.

5) Download datalogger (―collect all‖ on PC208W program).

6) Follow page 10 of the TTS Field Manual ―Collecting a DI Sample‖.

7) Collect the DI sample at approximately the same time as the ISCO sampler. You want to be 

halfway through your DI sampling when the ISCO pumps. The Olema Creek gauge at the 

Bear Valley Road bridge takes 35 seconds to start the rinse. It finishes pumping after 2 

minutes and 20 seconds. 

8) Collect several samples during the storm as long as it is safe to do so.

9) Conduct laboratory analysis for SSC on the DI samples and the ISCO samples following 

Section 3.1 in this SOP.
321

Turbidity calibration

Calibrate turbidity once a month. The turbidity probe should be approximately five inches below 

the water surface or at 50% of the depth. Collect a grab sample immediately downstream of the 

turbidity probe. Insert the sample bottle facing down and then turn horizontally so that the 

mouth of the bottle is facing upstream. Compare the field turbidity meter (e.g., Hach 2100P) 

reading with the turbidity probe reading. Consult the OBS-3 instruction manual for specific 

information about the turbidity probe (D&A Instrument Company, 2001). See Section 3.2.1 of 

this SOP and the Hach manual for detailed instructions on the Hach 2100P turbidimeter (Hach, 

2001).

8.5 Sample Preservation, Storage, and Analysis

8.5.1 Suspended Sediment Concentration (SSC) and Total Suspended Solids 

(TSS)

Samples should be analyzed for suspended sediment concentration or total suspended solids as 

soon as possible (within 24hrs) and should not be stored more than seven days. The laboratory 

method for analyzing SSC is included in Appendix D. The TSS method follows the American 

Public Health Association (APHA) method (APHA et al., 1998). Laboratory analysis for SSC 

will be conducted at a certified laboratory. Analysis for TSS will be conducted either at a 

certified lab or at the GOGA wet lab. The SFAN water quality specialist and other trained staff 

will conduct the analyses. However, due to staff time constraints with the 7 day holding time 

and the need to sample during storm events, it may be necessary to have an outside laboratory 

analyze the samples. 

8.5.2 Turbidity

Turbidity is time sensitive, so measurements should be obtained in the field. Biodegradation, 

settling, or sorption of particulates in a sample or precipitation of humic acids and minerals can 

affect the turbidity. 

8.5.2.1 Turbidimetric Determination Using a Cuvette-Based Turbidimeter 

It is highly recommend that program staff read the USGS National Field Manual Chapter section 

on Turbidity (Anderson, 2004). The following information about equipment calibration and 

maintenance is taken from both the National Field Manual and the Hach 2100P turbidimeter 

equipment manual (Hach, 200l). 

Equipment and supplies:

Turbidimeter

Turbidity stock solutions and standards

Formazin stock suspension (StablCal ®)

Manufacturer provided secondary turbidity standards (Gelex ®)

Sample cells (10 mL cuvettes), clear colorless glass

Sample bottle (preferably one that does not adsorb suspended sediment; use an amber glass 

bottle if the sample is to be stored temporarily. 
322

Silicon oil, optical grade

Paper tissues, extra lint free

Disposable gloves

Deionized water for rinsing

Non-phosporus detergent for cleaning sample cells

#2 single-hole stopper and syringe for degassing samples

Maintenance & Calibration of the Turbidimeter (see also Anderson, 2004 and Hach Instrument 

Manual, 2001)

● Protect instruments from extreme temperatures.

● Shield the instrument from direct sunlight.

● Check and replace batteries regularly.

● Follow the Hach manual for specific calibration procedures and preparation of 

formazin standards.

●Formazin standards are affected by temperature. To avoid the affects of 

temperature changes on the calibration, perform the Formazin and the secondary 

standard calibration at room temperature in the lab. Use three calibration 

standards that bracket the anticipated range of turbidity. 

● Conduct instrument checks against the secondary standards in the field.

● Use the Gelex® standards for instrument verification only, not for calibration

● Periodically check two turbidimeters against each other.

● Discard turbidity standards that have expired and never pour used standard 

solution back into a stock container.

● Keep sample cells clean inside and out.

● Wash sample cells with non-phosphate detergent between each use and rinse 

with deionized water so that all detergent is removed.

● Let cells air dry in a dust-free environment.

Collecting Samples for Turbidity Measurement

● Turbidity measurements can be taken from either a grab-sample at the centroid 

of flow, from a pumped sample (ISCO sampler), or from a depth-integrated 

(discharge-weighted) sample.

● Turbidity measurements should be made in the field whenever possible. If it is 

necessary to store samples, the holding time should not exceed 24hrs (ASTM 

International, 2003a). Samples should be stored at < 4°C to prevent 

biodegradation of solids.

Obtaining Turbidity Measurements:

● Shake the sample bottle vigorously to disperse all of the solids. 

● Pour the sample into a sample cell to the line marked on the neck. Do not touch 

the cell walls with fingers.

● Remove air bubbles by degassing via vacuum produced using the stopper and 

syringe apparatus (see USGS National Field Manual, Anderson, 2004).

●Remove condensation from the cell with a clean, soft lint-free cloth or tissue.
323

● Apply a thin coat of silicon oil on the outside of the cell about every third time 

the cell is wiped free of moisture. The oil will mask minor imperfections and 

scratches; too much oil will attract dirt and could foul the cell compartment. 

● Be sure that the sample is correctly oriented. Insert the sample cell so that the 

arrow on the cell faces the notch on the turbidimeter sample cell chamber. 

● Press the ―read‖ button to obtain a turbidity reading.

● Turbidity readings can be affected by unmatched cell orientation, condensation, 

gas bubbles, fingerprints, scratches, or dirt on the surfaces of the sample cell or 

turbidity probe. 

● Avoid trying to run extremely high color or organic matter samples or else 

dilute. Otherwise the sample may be over range.

● Use in low light. 

● Use on a level surface to help avoid stray light entering the measurement chamber.

Reporting Turbidity

● Turbidimeter specifications to include in the NPSTORET database are provided in Table 8.8.

● Guidelines for reporting turbidity measurements are included in the Table 8.9.

Table 0.8 Hach 2100P Turbidimeter Specifications.

Resolution Measurement Range % Difference from NTU Standards

0.01 NTU <10 to 1,000 NTU -5%, 20, to 950 NTU

Table 0.9 From USGS National Field Manual, Section 6.7 (Anderson, 2004).

8.5.2.2 In-Situ Turbidity Sensor 

An OBS turbidity sensor is currently included with the turbidity threshold sampling station on 

Olema Creek. Additional sensors will be purchased as funding allows. These sensors would bed 
324

rotated from watershed to watershed annually and would be used in conjunction with sampling 

for suspended sediment concentration. See the OBS instruction manual from D&A Instrument 

Company for wiring, configuration, calibration and other specific features and tasks (D&A 

Instrument Company, 2001). 

8.6 Quality Assurance/Quality Control

Field and laboratory duplicates are required. Analyze at least 10% of the sediment samples in 

duplicate. Duplicate determinations should agree within 5% of their average weight (American 

Public Health Association et al., 1998). Field and lab blanks are also required. See the SFAN 

Quality Assurance Project Plan, SOP#4, for more details. 

8.7 References 

American Public Health Association, American Water Works Association, and Water 

Environment Federation. 1998. Standard methods for the examination of water and 

wastewater (18th ed.), pp. p. 2-8 to 2-11, American Public Health Association, Washington, 

D.C.

Anderson, C.W. August 2004. Turbidity: U.S. Geological Survey Techniques of WaterResources Investigations, book 9, chap. A6, section 6.7 accessed June15, 2005 from 

http://water.usgs.gov/owq/FieldManual/Chapter6/6.7_contents.html

ASTM International. 2003. D-1889-00Standard test method for turbidity of water, In ASTM 

International, Annual Book of ASTM Standards, Water and Environmental Technology, 

2003, v. 11.01, West Conshohocken, PA. 6 p.

Creek Connections (2004): Turbidity Information Sheet. Creek Connections: Allegheny College. 

Accessed March 25, 2004 at 

http://creekconnections.allegheny.edu/Chemistry/TurbidityMain.html

D&A Instrument Company. 2001. Instruction Manual for OBS-1 & 3 Suspended Solids and 

Turbidity Monitor. Port Townsend, Washington. 41 pp. 

Eads, R. 2001. Turbidity Threshold Sampling. Redwood Sciences Laboratory, U.S.

Department of Agriculture, Forest Service. Arcata, CA. 

http://www.fs.fed.us/psw/topics/water/tts/tts_inst.shtml

Eads, R. and J. Lewis. 2002. Continuous turbidity monitoring in streams of Northwestern 

California. In: Turbidity and other sediment surrogates workshop (ed. by G.D. Glysson & 

J.R. Gray). 30 April - 02 May 2002, Reno, Nevada. 3 p.

Federal Interagency Sedimentation Project. 1958. Operating instructions for US DH-48 

suspended-sediment hand sampler--Interagency Report J: Minneapolis, Minnesota, St. 

Anthony Falls Hydraulics Laboratory, 5 p. Accessed June 9, 2005 from 

http://www.fisp.wes.army.mil

Glysson, G.D. and J.R. Gray. 2002. Total suspended solids data for use in sediment studies. 

Turbidity and Other Sediment Surrogates Workshop, April 30-May 2, Reno, NV.

Glysson, G.D., J.R. Gray, and L.M. Conge, 2000. Adjustment of Total Suspended Solids Data 

for Use in Sediment Studies,‖ in the Proceeding of the ASCE’s 2000 Joint Conference on 

Water Resources Engineering and Water Resources Planning and Management, July 30-

August 2, 2000, Minneapolis, MN, 10 p. 
325

Gray, J.R, G.D. Glysson, L.M. Turcios, and G.E. Schwarz. 2000. Comparability of suspendedsediment concentration and total suspended solids data. U.S. Geological Survey, WaterResources Iinvestigations Report 00-4191, Reston, Virginia. 

Hach Company. 2001. Model 2100P Portable Turbidimeter Instrument and Procedure Manual. 

Loveland, Colorado. 76 pp. 

Horne, A. J. (2003): Personal Communication, In S. Stafford (Ed.), Berkeley, CA. International 

Organization for Standardization, 1999, Water quality —determination of turbidity: Geneva, 

Switzerland, International Organization for Standardization, ISO 7027, 10 p.

Larsen, R., E. (1999): Fact Sheet No. 28: Fishery Habitat: 3) Sediment and Pollutants. UC 

Davis, University of California Cooperative Extension. Accessed March 25, 2004 at 

http://danr.ucop.edu/uccelr/h28.htm

Lewis, D.J., K.W. Tate, R.A. Dahlgren, and J. Newell. 2002. Turbidity and total suspended 

solid concentration dynamics in streamflow from California oak woodland watersheds. 

USDA Forest Service Gen. Tech. Rep. PSW- GTR-184. 2

Lewis, J. 1996. Turbidity-controlled suspended sediment sampling for runoff-event load 

estimation. Water Resour. Res. 32(7): 2299-2310.

Lewis, J., and R. Eads. 1996. Turbidity-controlled suspended sediment sampling. Watershed 

Management Council Newsletter 6(4): 1&4-5.

Lewis, J. and R. Eads. 1998. Automatic Real-Time Control of Suspended Sediment Sampling 

Based Upon High Frequency in situ Measurements of Nephelometric Turbidity. Proceedings 

of the Federal Interagency Workshop, Sediment Technology for the 21'st Century, St. 

Petersburg, FL, February 17-19, 1998.

Lewis, J. and R. Eads. 2001. Turbidity Threshold Sampling For Suspended Sediment Load 

Estimation. Proceedings Of The Seventh Federal Interagency Sedimentation Conference, 

March 25- 29, 2001, Reno, Nevada.

Lewis, J., R. Eads, and N. Cambell-Lund. 2002. Turbidity Threshold Sampling Program. 

Redwood Sciences Laboratory, U.S. Department of Agriculture, Forest Service. Arcata, CA. 

Lloyd, D. S. (1987): Turbidity as a water quality standard for salmonid habitats in Alaska. North 

American Journal of Fisheries Management 7, 34-35.

Madej, M.A., M. Wilzbach, K. Cummins, C. Ellis, and S. Hadden. 2002. The contribution of 

suspended organic sediments to turbidity and sediment flux. Turbidity and Other Sediment 

Surrogates Workshop, April 30-May 2, Reno, NV.

National Park Service. 2003. Baseline Water Quality Data Inventory and Analysis, Point Reyes 

National Seashore. Water Resources Division. Technical Report NPS/NRWRD/NRTR2000/280.

Newcombe, C. P. and J. O. Jensen. 1996. Channel suspended sediment and fisheries: a 

synthesis for quantitative assessment of risk and impact. No Amer. Fisheries Man 16 

(4):693-719).

Newcombe, C.P. and D.D. MacDonald. 1991. Effects of Suspended Sediments on Aquatic 

Ecosystems. North American Journal of Fisheries Management. 11: 72-82. 

Packman, J.J., K.J. Comings, and D.B. Booth. 2000. Using turbidity to determine total 

suspended solids in urbanizing streams in the Puget Lowlands. College of Forest 

Resources, University of Washington, Seattle, WA. 

Peitz, D.G., S. G. Fancy, L. P. Thomas, and B. Witcher. 2002. Bird monitoring protocol for 

Agate Fossil Beds National Monument, Nebraska and Tallgrass Prairie National 
326

Preserve, Kansas. Prairie Cluster prototype monitoring program. Version 1.00, 

September 6, 2002

Radtke, D.B. and F.W. Wilde. 2002. General Information. U.S. Geological Survey Techniques of 

Water-Resources Investigations, book 9, chap. A5, accessed June 29, 2005 from 

http://water.usgs.gov/owq/FieldManual/chapter5/pdf/generalinfor.pdf

San Francisco Bay Regional Water Quality Control Board, San FrancISCO Bay Region 1995. 

Water Quality Control Plan – San FrancISCO Bay Basin (Region 2). 

San Francisco Bay Regional Water Quality Control Board. 2003. Conceptual Approach for 

Development Sediment TMDLs for San FrancISCO Bay Area Streams. Oakland, CA. 

Sigler, J.W., T.C. Bjornn and F.H. Everest. 1984. Effects of Chronic Turbidity on Density of 

Steelheads and Coho Salmon. Transactions of the American Fisheries Society, 113: 142-150.

Stafford, S. and A. Horne. 2004. A review of the water quality monitoring programs in the 

National Parks in central coastal California. Report to the 

National Park Service. University of California, Berkeley.

Strausberg, S. I. (1983): Turbidity interferes with accuracy in heavy metal concentrations. 

Industrial Wastes 29, 16-21.

U.S. Environmental Protection Agency, 1993, Methods for the determination of inorganic 

substances in environmental samples: Cincinatti, Ohio,U.S. Environmental Protection 

Agency EPA/600/R–93/100, 178 p.

U.S. Environmental Protection Agency, 1999, Guidance manual for Agency, Office of Water, 

EPA 815-R-99-010, variously paged. 

Webb, W.E., D.B. Radtke, and R.T. Iwatsubo. September 1999. Surface Water Sampling: 

Collection Methods at Flowing-Water and Still-Water Sites.

U.S. Geological Survey Techniques of Water-Resources Investigations, book 9, chap. A4, 

accessed June 6, 2005 from 

http://water.usgs.gov/owq/FieldManual/chapter4/html/Ch4_contents.html

Webb, W.E. and D.B. Radke. 1998. Collection of Water Samples. U.S. Geological Survey 

Techniques of Water-Resources Investigations, book 9, chap. A4, accessed June 6, 2005 

from http://water.usgs.gov/owq/FieldManual/chapter4/html/Ch4_contents.html
327

SOP #8 Appendix A Sampling with the US DH-48 DepthIntegrating Suspended-Sediment Sampler 

http://fisp.wes.army.mil/Instructions%20US%20DH-48%20001010.PDF
328

SOP #8 Appendix B Depth Integrated Sampling Form Stream 

Flow Measurement Field Form
329

Depth Integrated (DI) Sampling for Sediment Calibration of Turbidity Threshold 

Sampling Station

Date: _________________ 

Site ID: _________________

Personnel: ____________

Stream section/location: _____________________________________________

Flow (velocity): ________________

LEW: ______ft REW: _____ft

Stream Width: _____ ft

BT (being time): ______ ET (end time): _____

BSH (beginning stage height): _____ ESH (ending stage height): _____

Bottles: _____

# of verticals (# of times in the water):______________

Panel size: _________

Type of sample (DI or AUX): ______

Equipment: DH 48 or other_____________

Pass: ______

Weather: _______________________________________________________________

ISCO bottle #: _______

ISCO sample time: ________

Notes: 
330

SFAN Water Quality Monitoring Program

Field Data Sheet For Flow Measurements

Station ID ______________________

Site Location 

_____________________________________

Date ____________Time ____________PST

Field Crew ________________________

Flow Instrument:____________________

Flow Measurements:

Gage Height __________ ft

Bed Level __________ ft

Stream Width __________ ft

Begin Time________PST/ Begin Gage Height_________ft End Time________PST / End Gage 

Ht________ft

Station (ft) Depth (ft) Velocity (ft/s) Average V Cumulative Q

REW:

LEW:

V – velocity Q – discharge

Notes from USGS Flow Measurement Methods:  For shallow depths, use 6/10 method
331

 For deep depths (> 1.5 ft) use the 2/10 and 8/10 

method

To get 2/10 depth multiply 6/10 depth by 2

To get 8/10 depth divide 6/10 depth by 2

 Space the verticals so that no sub-section has more 

than 10% (ideally 5%) of the discharge

 There should be 20-30 sub-sections

 Keep the first sub-section as small as possible (depth 

will often be zero and assume no flow)

 Streambed should be free of large rocks, obstructions

 Parts of the stream cross-sections with greater depth 

and velocity should have closer verticals

 Face the bank while taking measurement (stand beside 

not behind wading rod)

 Position yourself at least 18’ from the wading rode

 Measure velocity for at least 40 seconds

 Check the meter during measurement

 Have an idea what the discharge will be before 

measurement

 Read gauge height after measurement

 Reach should be straight and uniform; measure 

downstream of riffle
332

SOP #8 Appendix C Turbidity Threshold Sampling Field 

Manual 
333

SOP #8 Appendix D Laboratory Procedures For Determining 

Suspended Sediment Concentration
334

SOP #8 Appendix E Turbidimeter Instrument Log 
335

SOP #9 Field Measurements for Flow Measurements

9.1 Revision History Log

Prev. Version 

#

Revision 

Date

Author Changes Made Reason for 

Change

New Version #

1.0 8/3/05 Mary 

Cooprider

Minor changes Finalizing for 

formal peer 

review

1.01

1.01 3/9/06 Rob Carson Minor updates to text 

and tables

Addressing peer 

reviewer 

comments

1.02

Only changes in this SOP will be logged. ―Version numbers increase incrementally by 

hundredths (e.g. version 1.01, version 1.02 ...etc) for minor changes. Major revisions should be 

designated with the next whole number (e.g., version 2.0, 3.0, 4.0 ...). Record the previous 

version number, date of revision, author of the revision, identify paragraphs and pages where 

changes are made, and the reason for making the changes along with the new version number‖ 

(Peitz et al, 2002).

9.2 Acknowledgements

Significant portions of this SOP were taken directly from the Greater Yellowstone Network’s 

(GRYN) SOP #5 – Procedures for Collection of Required Field Parameters (O’Ney, 2005). We 

appreciate the time and effort devoted to this and other SOPs written by Susan O’Ney.

9.3 Introduction

The San Francisco Bay Area Network (SFAN) Water Quality Status Report provides an 

overview of flow monitoring locations and history within the SFAN parks (Cooprider, 2004). 

Stream gauges are located in watersheds within Golden Gate National Recreation Area (GOGA), 

John Muir National Historic Site (JOMU), and Point Reyes National Seashore (PORE). These 

stream gauges are equipped with a pressure transducer water level monitor and automatically 

record stage height at 10-15 minute intervals. These stream gauges have been managed by the 

individual parks. However, SFAN staff is currently considering methods of consolidating the 

maintenance and operation of these stations into the SFAN Freshwater Dynamics program. Staff 

implementing the Freshwater Dynamics program will focus on creating hydrographs (rating 

curves), operating the stream gauges, and managing the data. Stream flow measurements will be 

taken at cross sections near these gauges in order to obtain a stream flow rating curve that 

provides a relationship between stream stage and stream discharge. Once a rating curve is 

established for a stream gauge then water level can be used to predict stream flow. In addition to 

automated stream gauges, there are also several staff gauges located throughout the parks. Some 

of the SFAN long-term water quality monitoring stations are co-located with stream gauges 

and/or staff gauges.

Flow measurements collected in conjunction with water sample collection and stream chemistry 

measurements are critical to the SFAN Water Quality Monitoring Program. First, flow 
336

measurements are necessary to determine where to collect field measurements and samples. 

Flow measurements also provide useful information about seasonal variability in water quality 

parameters and pollutant load estimates. Therefore, quantitative stream flow will be assessed at 

all water quality monitoring sites where practical. Where time or stream conditions do not 

permit flow measurements then a qualitative estimate will be provided. Other methods and 

instructions on when to use a particular method will be discussed further in the SOP.

9.4 Calibration

9.4.1 Calibration of Current Velocity Meters (Flow meters) (from O’Ney, 2005)

All technicians should review ―Measurement of Stream Discharge by Wading‖ by Michael 

Nolan and Ronald R. Shields, USGS Water Resources Investigations Report 00-4036, available 

on CD. Also, refer to USG Technical Memorandum, found at 

http://water.usgs.gov/admin/memo/SW/sw99.06.html for the care of vertical axis current meters.

Field teams may be using one of three types of current velocity meters, a photooptical impeller 

type meter (e.g., Swoffer Model 2100) a vertical axis meter (e.g., Price type AA), or an 

electromagnetic type meter (e.g., Marsh McBirney Model 201D). General guidelines regarding 

performance checks and inspection of current meters are presented below. Consult the operating 

manual for the specific meter and modify this information as necessary.

9.4.2 General Performance Checks

(From Peck et al., 2001 ) 

9.4.2.1 Photoelectric Impeller Meters (e.g., Swoffer Model 2100)

 Check that the calibration adjustment cover screws are tightly fitted on the display case.

 Periodically check the condition of the connector fitting between the display unit and the 

sensor.

 Connect the sensor to the display unit and check the calibration value stored in memory. 

If this value is less than the correct value for the display unit-sensor rotor combination, 

replace the batteries.

 Periodically perform a spin test of the rotor assembly, following the instructions in the 

meter’s operating manual. A displayed count value of 300 or greater is indicative of 

satisfactory performance at low current velocities.

 If a buzzing sound occurs when the rotor assembly is spun by hand, or if the shaft shows 

visible wear, replace the rotor assembly.

 Periodically examine the thrust-bearing nut on the rotor assembly. If a ―cup‖ begins to 

form on the bottom surface of the nut, it should be replaced.

9.4.2.2 Vertical-axis Meters (from Smoot and Novak, 1968)

 Inspect the bucket and wheel hub assembly, yoke, cups, tailpiece, and the pivot point 

each day before use.

 Inspect the bearings and check the contact chamber for proper adjustment.
337

 Periodically conduct a spin test of the meter. The minimum spin time is 1.5 minutes, 

while the recommended time is between 3 and 4 minutes.

9.4.2.3 Electromagnetic Meters

 Check the meter calibration daily as part of morning routine. Calibration value should be 

2.00 + 0.05.

 Once per week, check the zero value using a bucket of quiescent water. Place the 

probe in the bucket and allow to sit for 30 minutes with no disturbance. The 

velocity value obtained should be 0.0 + 0.1. Adjust the meter zero if the value is 

outside this range.

● An annual calibration by the manufacturer or by the USGS Hydrologic 

Instrumentation Facility (Stennis Space Center, Mississippi) is recommended. 

9.5 Measurements Techniques

Stream discharge will be measured quantitatively by using the USGS method for measurement 

of stream discharge (Rantz et al., 1992). The flow velocity (ft/s) will be taken using the MarshMcBirney Flo-Mate, Swoffer 2000 flow meter, or pygmy meter. A top-setting wading rod 

(measured in tenths of feet) and a tape measure with gradations every tenth of a foot are also 

required equipment. A cross-section of the stream is chosen and the stream is divided into 

panels or sections. The width, depth, and velocity of each section are then recorded. Discharge 

is the sum of measurements in each panel and is recorded in cubic feet per second (ft3/s or cfs).

Field personnel are encouraged to review the USGS tutorial CD Measurement of Stream 

Discharge by Wading (Nolan and Shields, 2000). It provides details on the process and theory of 

stream flow measurements and proper methods and equipment. It is also important to have a 

hydrologist or someone well-versed in discharge measurement techniques to assist with training 

of field personnel. Consult the SFAN Freshwater Dynamics Monitoring Protocol (in 

development) for more background and details on flow monitoring. Coordinate with the 

Freshwater Dynamics program personnel when possible. 

Stream discharge measurements can be obtained from the following:

 USGS gauging station

 National Park Service stream gauge with established rating curve

 Mechanical flow meter (e.g., Pygmy current meter, AA, Swoffer 2000)

 Electric flow meters (e.g., Marsh-McBirney Flo-Mate)

 Orange peel or trained eye estimate

 Qualitative descriptions

9.5.1 Quantitative Methods (from O’Ney, 2005; Adapted from Texas Commission 

on Environmental Quality, 2003)

9.5.1.1 Introduction

Flow/discharge measurements representative of field conditions are needed to determine where 

to collect field measurements and samples. When flow is measured first, take care not to deploy 
338

a multiprobe instrument or to collect water samples in the area disturbed during flow 

measurement. The method (or instrument) used to measure flow must be reported. 

When flow cannot be measured:

The following are two exceptions to the requirement for obtaining flow measurements:

 No flow and pools. If there is no flow at a stream site, and accessible, isolated pools 

remain in the stream bed, collect and report the required field data and laboratory samples 

from the pools and report instantaneous flow. Under these conditions, report flow (ft3/s) 

as zero. 

 Dry. If the stream bed holds no water, no sampling is required. Report that the stream 

was "dry" in the observations.

9.5.1.2 Measuring Flow 

Several methods exist for measuring discharge but most methods share several similar steps. 

They include:

1. Selection and calibration of a current meter or other means of determining velocity

2. Proper site selection

3. Dividing the channel cross-section into equal increments (usually 20 or more)

4. Making the current measurements (by meter or other means) at several points in the 

vertical while allowing enough time for the device to stabilize (40 seconds for most 

current meters)

5. Determining the mean velocity at each vertical

6. Tabulating the data in field notes

7. Making field computations using the tabulated data

Equipment used to measure discharge or flow (e.g. current meters) should be tested/calibrated 

prior to mobilization to the field. Consult the manufacturers’ manual for specific calibration 

methods and appropriate applications for selected current meter and other devices used in the 

flow/discharge determinations.

9.5.1.2.1 Recording flow data: Record the following information on a flow measurement form 

(see Appendix A) for a blank form):

 Station location and station ID

 Date

 Time the measurement is initiated and ended

 Name of person(s) measuring flow

 Total stream width and width of each measurement section

 The midpoint, section depth, and flow velocity for each cross section

 Staff gage reading

Do not round values when recording flow data. For example, if the velocity is 1.99 do not round 

to 2.0. If each value is rounded on the worksheet, it could introduce an error in the final value. 

Only the final value is rounded.

9.5.1.2.2 Establishing a cross section profile: Stretch the measuring tape across the stream at 

right angles to the direction of flow. When using an electronic flow meter, the tape does not have 
339

to be exactly perpendicular to the bank (direction of flow). When using a propeller or pygmy 

type meter, however, make corrections for deviation from perpendicular. Measure and record 

the stream width between the points where the tape is stretched (waters edge to waters edge).

If necessary, the measuring cross section can be modified on smaller, low-flow streams. This can 

be done by building dikes to cut off dead water and shallow flows, remove rocks, weeds, and 

debris in the reach of stream 1 to 2 meters upstream from the measurement cross section. After 

modifying a streambed, allow the flow to stabilize before starting the flow measurement.

9.5.1.2.3 Determining the number of flow cross sections: Determine the spacing and location of 

flow measurement cross sections. Some judgment is required, depending on the shape of the 

stream bed. Measurements must represent the velocity within the cross section. Fewer 

measurements are needed if the stream banks are straight, the depth nearly constant, the bottom 

is free of large obstructions, and the flow is homogeneous over a large section. Flow 

measurement sections should be of equal width, unless an obstacle or other obstruction prevents 

an accurate velocity measurement at that point. No single cross section should have greater than 

10 percent of the total flow. The rule of thumb is as follows:

 If the stream width is less than 5 feet, cross sections widths are 0.5 feet.

 If the stream width is greater than 5 feet but less than 10 feet, the minimum 

number of cross sections is 10.

 If the stream width is greater than 10 feet, the preferred number of cross 

sections is 20 to 30.

9.5.1.2.4 Determining the midpoint of the cross section: To find the midpoint of a cross section, 

divide the cross section width in half, as described below.

 The total stream width is 26 feet with 20 cross sections, and the width of each 

cross section is equal to 1.3 feet (26/20 = 1.3).

 Divide 1.3 feet in half to get the midpoint of the cross section, 0.65 feet. In 

this example the measuring tape at waters edge is set at 0.0 feet.

 Add 0.65 to 0.0 to get the midpoint of the first section, 0.65 feet.

 Find each subsequent midpoint by adding the section width (1.3 feet) to the 

previous midpoint. 

 Use the measuring tape to place the top-setting wading rod at 0.65 feet (from 

the bank) for the first measurement.

 Using a top setting wading rod, measure the depth at the midpoint of the first 

cross section and record to the nearest 0.01 feet. Total depth at each cross 

section is measured with the depth gauge rod. The depth is entered into 

Column C of the flow measurement form. Each single mark represents 0.10 

feet, each double mark represents 0.50 feet, and each triple mark represents 

feet. See Figure 9.1, Top-Setting Wading Rod.

9.5.1.2.5 Adjusting the sensor depth at a cross section: Adjust the position of the sensor to the 

correct depth at each midpoint. The purpose of the top setting wading rod is to allow the user to 
340

easily set the sensor at 20, 60, and 80 percent of the total depth. See Figure 9.1, Top-Setting 

Wading Rod.

 If the depth is 1.5 feet or less, only one measurement is required at each cross 

section. To set the sensor at 60 percent of the depth, line up the foot scale on 

the sliding rod with the tenth scale, located on top of the depth gauge rod. If, 

for example, the total depth is 1.1 feet, then line up the 1 on the foot scale with 

the 1 on the tenth scale (Marsh McBirney 1990).

 If the depth is greater than 1.5 feet, two measurements are taken at 20 and 80 

percent of the total depth.

 20 percent of the depth. Multiply the total depth by 2. If the total 

depth is 3.1 feet, the rod would be set at 6.2 feet (3.1 x 2). Line up the 

6 on the sliding rod with the 2 on the tenth scale.

 80 percent of the depth. To set the sensor at 80 percent of the depth, 

divide the total depth by two. For example, the total depth is 3.1 feet and 

the rod would be set at 1.05 feet (3.1/2). Line up the 1 on the sliding rod 

between the 0 and 1 on the tenth scale. Use the average of the two 

velocity measurements in the flow calculation. See Columns D and E on 

the flow measurement form. When the depth is greater than 2.5 feet, 

never set the wading rod at the actual depth. In this case, it would not be 

set at 3.1 feet.

Note: The point where the rod is set for 20 and 80 percent of the depth will not equal values 

derived by calculating 20 and 80 percent of the total depth.
341

Figure 0.1 Top setting wading rod.
342

9.5.1.2.6 Measuring velocity: Follow these steps to measure velocity:

1. Position the meter at the correct depth and place at the midpoint of the flow 

measurement section. Measure and record the velocity and depth. While 

measuring velocity with an electronic flow meter, keep the wading rod 

vertical and the flow sensor kept perpendicular to the tape, rather than 

perpendicular to the flow. When using a propeller or pygmy-type meter, 

however, the instrument should be perpendicular to the flow.

2. Permit the meter to adjust to the current for a few seconds. Measure the 

velocity for a minimum of 40 seconds (preferably 2 minutes with the Price 

and pygmy meters).

3. When measuring the flow by wading, stand in the position that least affects 

the velocity of the water passing the current meter. The person wading stands 

a minimum of 1.5 feet downstream and off to the side of the flow sensor.

4. In cases where the flow is low and falling over an obstruction, it may be 

possible to measure the flow by timing how long it takes to fill a bucket of 

known volume.

5. Avoid measuring flow in areas with back eddies. The first choice would be to 

select a site with no back-eddy development. However, this cannot be avoided 

 in certain situations. Measure the negative flows in the areas with back 

eddies. These negative values will be included in the final flow calculation.

9.5.1.3 Calculating Flow

Follow these steps when calculating flow: Calculate flow at each cross section by multiplying the 

width (W) x depth (D) x velocity (V) to determine flow in cubic feet per second (cfs or ft3/sec). 

See Figure 9.2, Stream Flow (Discharge) Measurement.

Q = Total Flow (or discharge), W = Width, D = Depth, V = Velocity.

Q = (W1 x D1 x V1) + (W2 x D2 x V2) + ...... (Wn x Dn x Vn)

 When flow is calculated for each cross section add them together for the total 

stream flow (refer to Figure 9.2).

 For each individual cross section flow, do not round values. For example, if the 

calculated flow for a cross section is 1.23956, do not round. If each value is 

rounded on the worksheet, it could introduce an error in the final value.

 Do not treat cross sections with negative flow values as zero. Negative values 

obtained from areas with back eddies should be subtracted during the summation 

of the flow for a site.
343

Figure 0.2 Flow calculations.

9.5.1.4 Reporting Final Flow Values

Report instantaneous flow as follows:

 Report values less than 10 but greater than 0.1 cfs to the nearest tenth (for example, 

9.35 to 9.4).

 Report values greater than 10 cfs to the nearest whole number (for example, 20.62 to 

21).

 Report actual values less than 0.1 cfs but greater than or equal to 0.01 cfs. These 

values should not be rounded (for example, 0.07 would be reported as 0.07).

 Report flow values < 0.01 cfs as < 0.01. See Table 3-11, Final Format for Reporting 

Field Data.

When reporting final flow values, it is also useful to include the number of days since the last 

significant precipitation. Significant precipitation is defined as any amount that visibly 

influences water quality. Water quality in small to medium streams and in the headwaters of 

many reservoirs is influenced by runoff during and immediately after rainfall events. This 

influence is site specific and poorly studied. To understand and regulate the adverse effects of 

runoff, the SFAN would like to associate recent rains with ambient water quality, using a 

parameter defined as days since last significant precipitation.

Using best professional judgment, record the number of days, rounded to the nearest whole 

number, since a rainfall event that may have influenced water quality. Here are some guidelines:

 If it is raining when the sample is collected, or has rained within the last 24-hours, report 

a value of <1.

 If it has been a long time since a significant rain, record this as greater than that particular 

value, for example >7 days.

If confidence about the recent history of precipitation is low, don’t report a value.
344

9.5.2 Alternative Methods

A qualitative flow measurement cannot always be obtained using the USGS established method. 

Equipment limitations and safety considerations may preclude taking flow measurements. Since 

flow measurements can be very important in determining pollutant loads or explaining measured 

parameters it is often useful to obtain an estimate. This usually occurs during storm events when 

stream flow is too high to safely obtain a traditional flow measurement. However, storm flows 

are often needed in order to understand pollutant loads. One method that can be used to estimate 

flow is the ―orange peel‖ method. Citizen (volunteer) monitoring groups often employ this 

method as a safe, cost effective technique.

1. Establish a longitudinal stream length to measure and stretch the measuring tape across 

that length (from Point A to Point B). The length will depend on the velocity of the 

stream but 1-3 meters usually works well.

2. Using a stopwatch, record how long it takes the orange peel to float from Point A to Point 

B.

3. Throw the orange peel into the center of the stream. If available, have another person 

start and stop the stopwatch at your command.

4. It is recommended that you do this three times and take the mean of your three estimates. 

Alternatively, have other field crew members conduct the estimates.

5. As you become more familiar with each stream and obtain more and more flow 

measurements, you may find over time that you can estimate flow simply through visual 

observation. This can provide more information than a strictly qualitative estimate such 

as flow severity. Always indicate on the data sheet and in the database that your 

flow/discharge value was estimated.

9.5.3 Qualitative Methods

Flow severity, a qualitative estimation of flow is commonly used in water quality monitoring and 

is included as a field in NPSTORET. It is also used by the San Francisco Bay Regional Water

Quality Control Board’s Surface Water Ambient Monitoring Program (SWAMP). The SWAMP 

program monitors several sites within the SFAN parks.

Flow severity should be recorded for each visit to a freshwater streams. It should be recorded 

regardless of whether or not it was possible to measure flow. There are no numerical flow 

guidelines associated with flow severity. This is an observational measurement that is highly 

dependent on the stream and knowledge of monitoring personnel. It is a simple but useful piece 

of information when assessing water quality data. For example, a bacteria value of 10,000 with a 

flow severity of 1 would represent something entirely different than the same value with a flow 

severity of 5. See Table 9.1 for detailed descriptions of flow severity values. The six flow 

severity values are; No Flow (1), Low Flow(2), Normal(3), Flood(4), High(5), Dry(6). The 

following table includes descriptions of severity values.
345

Table 0.1 Flow Severity Values.

Value Notes

1 No Flow - When a flow severity of one (1 = no flow) is recorded for a sampling visit, then 

a flow value of zero ft3/s should also be recorded for that sampling visit. A flow severity 

of one (1) (no flow) describes situations where the stream has water visible in isolated 

pools. There should be no obvious shallow subsurface flow in sand or gravel beds 

between isolated pools. Low flow does not only apply to streams with pools. It also 

applies to long reaches of bayous and streams that have no detectable flow but may have 

water from bank to bank.

2 Low Flow - When stream flow is considered low a flow severity value of two (2) is 

recorded for the visit and the corresponding flow measurement is also recorded for that 

visit. In streams too shallow for a flow measurement but in which water movement is 

detected, record a value of < 0.10 cfs. Note: Use a stick or other light object to verified the 

direction of water movement, i.e., movement is downstream and not the affect of wind. 

What is low for one stream could be high for another.

3 Normal Flow - When stream flow is considered normal, a flow severity value of three (3) 

is recorded for the visit and the corresponding flow measurement is also be recorded for 

that visit. Normal is highly dependent on the stream. Like low flow, what is normal for 

one could be high or low for another stream. 

4 and 5 Flood and High Flow - Flow severity values for high and flood flows have long been 

established by USEPA and are not sequential. Flood flow is reported as a flow severity of 

four (4) and high flows are reported as a flow severity of five (5). High flows would be 

characterized by flows that leave the normal stream channel but stay within the stream 

banks. Flood flows are those which leave the confines of the normal stream channel and 

move out on to the flood plain.

6 Dry - When the stream is dry a flow severity value of six (6 = dry) is recorded for the 

sampling visit. In this case the flow is not reported. This will indicate that the stream is 

completely dry with no visible pools.

9.6 Data Analysis & Reporting

The National Park Service Water Resources Division uses a database that is a modification of 

EPA’s STORET database. This database, NPSTORET, has five digit parameter codes. Table 9.2

outlines the different types of flow parameters, and their associated codes included in 

NPSTORET. 

Flow values should be reported in (ft3/s). The flow measurement method should be reported 

along with the flow severity value or estimate. The flow severity value should be reported as a 

descriptive characteristic with the numerical value in parentheses (e.g. Normal Flow (3) or Flood 

Flow (4)). Reporting of the quantitative value for flow is recommended, but not required.
346

Table 0.2 NPSTORET Flow Monitoring Codes and Definitions.

Flow Notes

Flow (00061) Measurements reported in cubic feet per second. Report 

instantaneous flow as follows:

•Report values less than 10 but greater than 0.1 cfs to the nearest 

tenth (for example, 9.35 to 9.4).

•Report values greater than 10 cfs to the nearest whole number (for 

example, 20.62 to 21).

•Report actual values less than 0.1 cfs but greater than or equal to 

0.01 cfs. These values should not be rounded (for example, 0.07 

would be reported as 0.07).

•Report flow values < 0.01 cfs as < 0.01. 

Flow method (89835)

Refer to codes in NPSTORET

Flow, severity (01351) When there is no flow (pools) report a flow severity of 1, and the 

instantaneous flow (00061) as 0.0 cfs. If the stream is dry, record 

only the flow severity value of 6. (No Flow (1), Low Flow(2), 

Normal(3), Flood(4), High(5), Dry(6))

9.7 References

Cooprider, M. 2004. San Francisco Bay Area Network Preliminary Water Quality Status Report. 

Available at http://www1.nature.nps.gov/im/units/sfan/wrd.htm

Marsh-McBirney. 1990. FLO-MATE model 2000 portable water flow meter- installation and 

instruction manual. Frederick, MD.Nolan, K.M. and R.R. Shields. 2000. Measurement of 

stream discharge by wading. U.S. Geological Survey Water Resources Investigation 

Report 00-4036. Version 1.1. On CD. 

O’Ney SE. 2005. Procedures for Collection of Required Field Parameters, Version 1.0, Standard

Operating Procedure #5. In Regulatory Water Quality Monitoring Protocol, Version 1.0, 

Appendix E – SOPs, National Park Service, Greater Yellowstone Network. Bozeman, MT. 

37 pp. plus appendices

Peck, D.V., J.M. Lazorchak, and D.J. Klemm. 2001. Environmental monitoring and assessment 

program-surface waters: Western pilot study field operations manual for wadeable streams. 

U.S. Environmental Protection Agency.

Rantz, S.E. 1982. Measurement of discharge by conventional current-meter method. U.S. 

Geological Survey Water-Supply Paper 2175.

Smoot GF, and Novak CE. 1968. Calibration and Maintenance of Vertical-axis Type Current 

Meters. Book 8, Chapter B2 IN: Techniques of Water-Resources Investigations of the United 

States Geological Survey. U.S. Government Printing Office, Washington, D.C.
347

Texas Commission on Environmental Quality. 2003. Surface water quality monitoring 

procedures, Volume 1: Physical and chemical monitoring methods for water, sediment and 

tissue. RG 415. Also available on-line at http://www.tceq.state.tx.us/publications. 198 p.
348

SOP #9 Appendix A Field Form for Recording Flow 

Measurements 

filler 
349

SFAN Water Quality Monitoring Program

Field Data Sheet For Flow Measurements

Station ID ______________________

Site Location 

_____________________________________

Date ____________Time ____________PST

Field Crew ________________________

Flow Instrument:____________________

Flow Measurements:

Gage Height __________ ft

Bed Level __________ ft

Stream Width __________ ft

Begin Time________PST/ Begin Gage Height_________ft End Time________PST / End Gage 

Ht________ft

Station (ft) Depth (ft) Velocity (ft/s) Average V Cumulative Q

REW:

LEW:

V – velocity Q – discharge

Notes from USGS Flow Measurement Methods:

 For shallow depths, use 6/10 method

 For deep depths (> 1.5 ft) use the 2/10 and 8/10 

method

To get 2/10 depth multiply 6/10 depth by 2

To get 8/10 depth divide 6/10 depth by 2

 Space the verticals so that no sub-section has more 

than 10% (ideally 5%) of the discharge

 There should be 20-30 sub-sections
350

 Keep the first sub-section as small as possible (depth 

will often be zero and assume no flow)

 Streambed should be free of large rocks, obstructions

 Parts of the stream cross-sections with greater depth 

and velocity should have closer verticals

 Face the bank while taking measurement (stand beside 

not behind wading rod)

 Position yourself at least 18’ from the wading rode

 Measure velocity for at least 40 seconds

 Check the meter during measurement

 Have an idea what the discharge will be before 

measurement

 Read gauge height after measurement

 Reach should be straight and uniform; measure 

downstream of riffle
351

Example flow calculation worksheet

Stream: Bear Gulch Location: Chalone Creek, PINN

Site: BG 2

Date: 2/26/2004 Crew: MC, MK

Time: 13:41 Comments:

Stage Height:

Distance 

(ft)

Depth (ft) Velocity 

(ft/s)

Width (ft) Area (ft2) Flow (cfs)

2.4 0.18 0.00 1.75 0.32 0.000

3.5 0.40 0.20 1.05 0.42 0.084

4.5 0.45 1.15 1 0.45 0.518

5.5 0.60 1.50 1 0.60 0.900

6.5 0.62 1.10 1 0.62 0.682

7.5 0.65 1.50 1 0.65 0.975

8.5 0.55 1.45 1 0.55 0.798

9.5 0.75 1.54 1 0.75 1.155

10.5 0.72 1.72 1 0.72 1.238

11.5 0.75 1.62 1 0.75 1.215

12.5 0.78 1.35 1 0.78 1.053

13.5 0.70 1.31 1 0.70 0.917

14.5 0.55 1.42 1 0.55 0.781

15.5 0.65 1.18 1 0.65 0.767

16.5 0.60 0.00 1 0.60 0.000

17.5 0.50 0.00 1 0.50 0.000

18.5 0.30 0.00 1 0.30 0.000

19.5 0.32 0.00 1 0.32 0.000

20.5 0.20 0.00 0.95 0.19 0.000

21.4 0.00 0.00 -10.25 0.00 0.000

-10.7 0.00 0.000

0 0.00 0.000

0 0.00 0.000

0 0.00 0.000

0 0.00 0.000

0 0.00 0.000

0 0.00 0.000

0 0.00 0.000

0 0.00 0.000

0 0.00 0.000

0

Total flow 

(cfs):

11.08

Stage height (ft):
352

SOP 10 Data Analysis 

10.1 Revision History Log

Prev. Version 

#

Revision 

Date

Author Changes Made Reason for Change New Version #

1.0 8/5/05 M. Cooprider Additional guidance on 

data analysis and 

presentation

Preparation for 

formal peer review

1.01

1.01 3/23/06 R. Carson Minor Edits on treatment 

of censored data and 

controlling sensitivity; 

precision and bias

Addressing formal 

peer review 

comments

1.02

1.02 9/28/06 R. Carson Inserted Sample Size and 

MDD tables

Quantify statistical 

objectives

1.03

Only changes in this SOP will be logged. ―Version numbers increase incrementally by 

hundredths (e.g. version 1.01, version 1.02 ...etc) for minor changes. Major revisions should be 

designated with the next whole number (e.g., version 2.0, 3.0, 4.0 ...). Record the previous 

version number, date of revision, author of the revision, identify paragraphs and pages where 

changes are made, and the reason for making the changes along with the new version number‖ 

(Peitz et al, 2002).

10.2 Introduction and Acknowledgements 

Water quality data typically has a non-normal distribution due to a lower bound of zero, the 

presence of outliers, and positive skewness. Seasonality and autocorrelation are also common as 

well as covariance with other variables such as discharge (Helsel and Hirsch, 2002). Water 

quality data is usually highly variable, both temporally and spatially. Data characteristics often 

utilized for water quality data include: a measure of the center of the data, a measure of spread 

or variability, a measure of the symmetry of data distribution, and possibly estimates of extremes 

(Helsel and Hirsch, 1992). This SOP provides guidance on how to prepare and analyze data 

given these characteristics. Sections of this SOP were obtained from the Greater Yellowstone 

Network SOP#9 - Data Analysis Procedures in the Regulatory Water Quality Monitoring 

Protocol (O’Ney, 2004). David Lewis (University of California Cooperative Extension) also 

provided valuable insight. Finally, the internet accessible text, Statistical Methods in Water 

Resources (Helsel and Hirsch, 1992) was frequently consulted. While the basics of water quality 

data analysis are covered here, this statistics text should be followed for greater details.
353

10.3 Preparing the Raw Data Set for Analysis 

10.3.1 Sample Sizes and Minimum Detectable Differences and Quantifying Data 

Quality

USGS NAWQA protocols recommend a minimum of two years of consecutive monthly 

monitoring (Gilliom et al., 2001) for rotating basin designs. A phasing-in approach (gradually 

adding more watersheds over time) will also be considered depending upon funding. This would 

allow longer-term data sets for trends, without two-year gaps. Where annual monitoring is 

mandated by state TMDL project, then we will monitor every year and be able to analyze for 

long-term trends without two-year gaps (an example would be Olema Creek).

Sample size is a critical element of the power of statistical analysis. Sample size is determined 

largely by sampling design, and is one of three critical elements including confidence level and 

power that determine our ability to detect a change in water quality. Sample sizes will vary 

slightly depending on annual rainfall patterns and other conditions affecting how long a stream 

holds water, but a summary of anticipated sample sizes is shown in Table 10.1, below. 

Table 0.1 Sample Size Summary for SFAN Priority Streams.

Stream # of Sites* 

Proposed(Alt.)

# Samples 

/Site/Yr **

# Samples *** 

/Watershed/Yr

Park # Samples 

/Park/Yr

Olema 6(2) 13

18-20 FIB 

samples

72-96

(108-144 FIB 

samples)

PORE FY07-FY08

144-180

FY09-FY10

147-183

Pine Gulch 3 12 36 PORE 

Lagunitas 3 13 39 PORE / 

GOGA

Rodeo 2(1) 13 26-39 GOGA FY07-FY08

52-104

FY09-FY10

129-204

Tennessee 2(1) 7 14-21 GOGA

Nyhan/

Oakwood

0(2) 7-10 14-20 GOGA

Redwood 9(3) 7-13 117-156 GOGA/M

UWO

West Union 2(3) 7-12 24-48 GOGA

Franklin 1 12 12 JOMU 17-22

Strentzel 0(5) 2 10 JOMU

Chalone 5(3) 7-13 35-104 PINN 65-104

* The number of sites listed per stream is the proposed # with the alternate # of sites in 

parentheses (i.e. 6(2) means six proposed sites, with two alternate sites).

** The number of samples per site per year depends on the presence of water in intermittent 

streams during the dry season.

*** The number of samples per watershed per year depends on the availability of funding to 

sample alternate as well as proposed sites.

Based on data from a limited number of sites for the past two years, SFAN has been able to 

approximate the minimum detectible differences (MDD) that we will be able to distinguish given 

the sample sizes in the current protocol (Table 10.2). These approximations were based on 

available data for core parameters from long-term sites on Olema Creek. Those parameters for 
354

which we are unable to estimate the variation of the parameters of the population due to lack of 

baseline data, have estimated power and MDD goals that will be re-evaluated and updated as 

data is collected. 

Table 0.2 Minimum Detectable Differences for SFAN Sampling Design.

Confidence Level (1-α*100) Power (1-β *100) MDD (% change)

Core Parameters 95% 95% 15% (20% for SC)

Nutrients 95% 90% 30%

Sediment 95% 80% 40%

Bacteria 95% 80% 50%

Because we do not have consistent or complete past data for either nutrient or sediment 

parameters for sites in SFAN priority streams, we have set some general goals based on initial 

estimates using the sample sizes in the current protocol. Because both bacteria and sediment 

parameters have high variation in SFAN streams, we have set more reasonable goal of being able 

to detect a larger change with slightly less power. Through evaluation of collected data, we 

should be able to refine our power and MDD calculations for these parameters, resulting in 

greater power to detect smaller change.

Due to the judgmental or targeted nature of the current sampling design, we cannot currently 

make statistically-supported inferences about the percentage of impaired miles in priority 

watersheds based on sampling at targeted locations. However, with long-term data from sites at 

various levels of the watershed including a reference or upper watershed site and a site at the 

bottom of a watershed, broad inferences can be made to the watershed as a whole. With the 

integration of randomly-selected sites that will assure geographic coverage for SFAN 

watersheds, we will be able to integrate statistically-unbiased inferences of the percentage of 

impaired stream miles, as well as the natural ranges of water-quality and long-term trends for 

water quality in freshwater systems of SFAN.

Ensuring the quality of the data collected is crucial prior to performing data analyses. Detailed 

information about the data quality procedures for this protocol are available in SOP#4 the 

Quality Assurance Project Plan. Below is a brief summary of the field methods that will allow 

SFAN to quantify the effect of errors and changes in method, equipment and personnel that are 

an inevitable part of long-term monitoring (Table 10.3)
355

Table 0.3 SFAN Data Quality Assurances.

Data Quality Issue SFAN Data Quality Assurances

Sensitivity  For lab parameters: Calculation of both Method Detection Limit 

(MDL) and Minimum Level of Quantitation (ML).

 For field or ―core‖ parameters: Quarterly collection of seven 

replicate samples or measurements in order to calculate the 

Alternative Measurement Sensitivity (AMS).

Precision  For Field Measurements: Duplicate at least one measurement, or 

10% of a days’ samples (whichever is larger).

 For Lab Measurements: Duplicate analysis of 10% of samples. 

Report the Relative Percent Difference (RPD). 

Bias  Maintain consistent personnel and methodology where possible.

 Overlap* a minimum of seven (7) measurements when personnel 

changes, thirty (30) when a method or equipment changes, and 

fifty (50) when replacing surrogate estimators like FIB.

 Analyze such overlapping samples to determine the contribution 

of bias (if any) to any variance in the data.

 Control bias by: Use and analysis of ―blank‖ samples (Field, 

Trip or Lab Blanks) to determine contamination by methodology.

―Accuracy‖  For the purposes of this protocol, the term ―accuracy‖ should be 

taken to be the ―uncertainty in accuracy‖ and is a combination of 

random error (precision) and systematic error (bias) components 

that are due to sampling and analytical operations. Measurement 

uncertainty will be controlled quantitatively through calculations 

of sensitivity, precision and bias.

10.3.2 Censored Data and Outliers

Water quality data is often ―censored‖ or reported as less than the detection limit. In some cases, 

there are also instances of data values greater than or equal to the upper detection limit. This 

occurs most frequently with fecal coliform data since the proper dilution, based on the expected 

range, is sometimes difficult to predict particularly during storm events. Censored data is 

considered outside the range of quantitation (i.e., it cannot be quantified and a number cannot be 

assigned to it) and generally should not be statistically analyzed. However, censored data are 

presented as less than or greater than the ML in order to compare it to water quality criteria 

(Irwin, 2004). Therefore, although these data should not be included in statistical analysis, they 

are still useful for water quality assessment.

More advanced methods for dealing with censored data are outlined in Ch. 13 in Helsel and 

Hirsch (1992). This chapter describes how observed data may be combined with censored data 

in order to calculate estimates of summary statistics. Also refer to the recent publication 

Nondetects and Data Analysis: Statistics for Censored Environmental Data (Helsel, 2004).

The SFAN Quality Assurance Project Plan (SOP#4) describes the details of data quality 

objectives and measurement quality objectives in relation to data reporting. A summary of how 

data should be reported is as follows:
356

 Values below the Method Detection Limit (MDL) are to be reported as a (<) sign followed 

by the actual MDL value, and flagged with a ND = not detected.

 Values between the MDL and the ML (or quantification limit) should be reported with the 

detection condition of ― *Present <QL‖ or Present, below quantification limit. This 

condition will trigger the database to enter *Present, <QL into the result field. These 

values are considered semi-quantitative. 

 Values above the ML (or quantification limit) are deemed as acceptable values without 

reservation, and are shown as the actual measured value, and assigned a QA code of A 

(acceptable without reservation).

Do not immediately remove outliers from a data set because they appear unusual. It is important 

to first verify that no human errors have been made such as copying a number wrong or putting a 

decimal point in the wrong place. Rather than eliminating possibly important data in order to use 

standard statistical analyses (e.g., tests requiring normally distributed data), methods that are 

resistant to outliers should be utilized. (Helsel and Hirsch, 1992). Some of the summary statistics 

that are resistant to outliers are discussed in Section 3.0 of this SOP.

10.3.3 Replicates and Data Transformations

Replicates should be averaged together and the single mean value used in their place for analysis, 

or the median value may be used. The standard deviation or range of the replicates provides an 

estimate of the variability in the measurement technique (Stafford and Horne, 2004).

The goal of data transformations is to ―make data more symmetric, to make data more linear, and 

to make data more constant in variance‖ (Helsel and Hirsch, 2002). Some examples include 

logarithmic transformations and adjusting data for flow. Use logarithmic transformations with 

fecal indicator bacteria (FIB) data since transforming allows for a more simple data analysis and 

graphical display of data with a range that often spans over several orders of magnitude. Log 

transformations are also commonly used with discharge measurements and sometimes with 

nutrient data. Basically, use log transformations on data when there is a broad range of data. 

It is helpful to display both the transformed data and non-transformed data to understand how 

transformations affect the data. This is particularly useful when presenting to a general audience 

(Dave Lewis, personal communication, 29 July 2005).

Flow adjusted or flow-weighted data is simply the concentration (C) of the analyte divided by 

the discharge (Q). Transformations (either logarithmic or flow-adjusted) can make the data more 

―normal‖ (symmetric) and increase the possibility of using parametric statistics which are 

slightly more powerful at determining statistical differences. Transforming the data does not 

change the median and interquartile range (IQR). However, transforming does change the mean 

and standard deviation (Helsel and Hirsch, 1992). This is why both the mean and standard 

deviation as well as the median and IQR are reported for water quality data or any other data that 

is typically non-parametric. 
357

10.4 Data Analysis

Before data analysis: 

 Review data promptly to detect potential outliers or errors

 Conduct log transformations on bacteria data and calculate flow-weighted data

 Use the mean of replicate samples for statistical analysis

 Don’t conduct statistical analyses on censored data but use all data for overall comparisons 

against water quality criteria.

 Export data from the NPSTORET to Microsoft Excel to conduct analysis. Further analysis can 

be conducted with other statistical software. However, NPSTORET does have several 

statistical and graphical functions that could be used as they become available. 

Use graphs before data analysis to learn more about the data set. A plot of raw data values (for 

one site) against time is an important preliminary tool to assist in visualizing the data distribution 

and to provide a check for temporal patterns and extreme values (outliers). 

10.4.1 Summary Statistics and Tabular Data Presentation 

The following descriptive statistics should be performed: 

Mean 

Standard Error 

Median

Std. deviation

Variance

Kurtosis (peakedness)

Skewness (lack of symmetry about the mean)

Range/Interquartile Range (IQR)

Minimum

Maximum

Sum

Count

Confidence intervals for mean and median (95 or 99% confidence level)

 Use all data (including censored data) for comparison against water quality criteria.

 Analyze reference or control sites separately to determine a baseline for specific streams. 

 To limit seasonal variability, conduct statistical tests on each of the different seasons.

 Summarize data for each site and for each parameter seasonally and annually

 Summarize data from all stations within each watershed seasonally and annually. 

 Compare data from stations upstream and downstream of a suspected pollution source or 

tributary. 

 Use flow (discharge) weighted data and group data by season to account for seasonal variation.

 Discrete and continuous data should be analyzed separately. However, data from the same 

days may be compared for quality control and to obtain a relationship between the datalogger 

readings and instantaneous monthly/weekly data.
358

 Determine the inherent variability of a sampling technique by calculating the standard 

deviation of replicates (see as Section 3.1.2 below)

 Present data in tabular form for each station and watershed as follows:

SFAN I&M Water Year 2006 Water Quality Data - Station ID 

Date pH TEMP DO COND Total NH3 NH3-tox NO3 Total N FC TURB

_ Nov 06

_ Dec. 06

_ Jan 06

_Feb 06

_March 06

_April 06

_May 06

_June 06

_July 06

_Aug 06

_Sept 06

_Oct 06

Statistics

Mean 

Std. Error

Median

Std. Dev.

Variance

Kurtosis

Skewness

Range

Min

Max

Sum

Count

Confidence 

Level
359

 Next, summarize all data and compare to water quality criteria using the following example

 (from Rugg, 2000).

10.4.1.1 Statistics for fecal coliform data

In addition to the above summary statistics, a geometric mean should be calculated for fecal 

coliform and E. coli data. 

For the Olema Creek data (Pathogen TMDL sampling), calculate the 30-day geometric mean of 

samples from five consecutive weeks to determine whether standards are being exceeded. Water 

quality standards are listed in SOP#6 and in the Protocol Narrative. To calculate the estimated 

geometric mean (In O’Ney, 2005; adapted from WY-DEQ 1999):

1. convert each CFU count/100ml to its log

2. add the logs

3. divide the total of the logs by the number of samples to get the mean

4. take the antilog of (3); that number is the geometric mean (in CFU/100mL)

Example: test results are 760, 3100, 300, 632 and 805

Arithmetic mean = 760 + 3100 + 300 + 632 + 805 = 5597 / 5 = 1119.4

Arithmetic median = 760

Geometric mean = 816.58

log10 760 = 2.88

log10 3100 = 3.49 

log10 300 = 2.48 

log10 632 = 2.80 

log10 805 = 2.91 
360

sum of the logs = 14.56

mean of the logs = 14.56/5= 2.912

antilog 2.912 = 816.58

An alternative method is to multiply the CFU counts/100ml together and take the nth root, where 

n = number of samples (5 in this example). Using the test results above:

760 x 3100 x 300 x 632 x 805 = 3.6 x 1014

(3.6 x 1014)1/5 or (3.6 x 1014).2 = 815.19

Results from field blanks should also be reviewed to establish that a sample is not being 

contaminated by conditions associated with the collection or custody of a sample or by crosscontamination during sampling or shipping. Another way to determine whether field methods are 

adequate is to calculate precision from duplicates. Fecal coliform duplicate precision is 

calculated for the Number of Colonies /100 ml value (not the log transformation) and is typically 

set at ±50%. See section 3.2 in this document for guidance on calculating precision. 

10.4.1.2 Calculating Precision

The following is an explanation for calculating precision of field duplicates. Other QA/QC 

measures, including calculating precision of lab duplicates, are discussed in SOP #4.

(In O’Ney, 2004; Adapted from WY-DEQ, 2000)

Precision is defined as how closely repeated measurements agree with each other. Precision 

indicates the degree of agreement between sequential independent samples at a site, collected 

by applying the same collection method. If the sample is representative and the sampling 

methods are consistent, two or more measurements made consecutively with a field 

instrument usually agree very closely (less than 10 per cent difference). Estimates of 

precision are also known as sampling error. Precision should be calculated as soon as results 

from duplicate analyses are available, no later than 7 days after receipt from laboratory.

The precision measurement is calculated using the relative percent difference (RPD) 

between duplicate sample results per analyte (parameter). For duplicate samples, the 

smaller test result is subtracted from the larger test result. The resulting difference is 

divided by the average of the two results, and the result is multiplied by 100 to express 

the number as a percent. The formula is: [(S1 - S2) / ((S1 + S2)/2)] x 100 = RPD, where 

S1 is the larger test result value.

For precision results, not only should RPDs be reported, but also raw numbers. This will 

allow for calculation of uncertainty statistics later, should this be needed.
361

10.4.2 Graphical Data Presentation

Important graphical features or comparisons to utilize include:

 Location (line) showing detection limit on graph

 Distance from suspected source or distance from source

 Display pH, D.O., and temperature on one chart to show relationships 

 Parameter against time (shows seasonal changes) for each station

 Parameter against time for all stations in a watershed

 Site comparisons for each parameter

 Display all data for one station on one page

 For continuous data, graph daily, monthly, and seasonally

 Relationships of conductivity to fecal coliforms

 Relationship of flow to all other variables

Chapter 2 (Graphical Data Analysis) and Chapter 16 (Presentation Graphics) of Statistical 

Methods in Water Resources (Helsel and Hirsch, 1992) should be followed for graphical data 

analysis. Tables can be used in association with graphs but presentation of data should not rely 

solely on tables. Graphics should generally include: 

1) histograms (e.g., streamflow vs. number of occurrences): useful for depicting large 

differences in shape or symmetry. They are better for data that have natural categories or 

groupings; they are not as good with continuous data since it is difficult to depict this type of 

data accurately in a discrete group. It would work well for the number of sites exceeding 

different levels of water quality criteria (e.g., non-contact recreation and contact recreation). 

2) simple box plots (box and whiskers plot) Whiskers are drawn to the points of maximum and 

minimum data, a box depicting the 25th and 75th percentile is drawn, and a horizontal line 

through the box depicts the median. These can be used for reviewing one set of data or for 

comparing multiple data sets. ―They are valuable guides in determining whether central 

values, spread, and symmetry differ among groups of data.‖ They can be used to determine 

whether tests based on the assumption of normality can be used (Helsel and Hirsch, 1992). 

3) scatterplots – relationship between two variables (e.g., flow vs. fecal coliforms); a 

―smoothe‖ may be used to help determine the relationship of x to y. The preferred procedure 

for this is LOWESS (LOcally WEighted Scatterplot Smoothing) (Helsel and Hirsch, 1992).

Summary tables, histograms, and box and whisker plots can be used to show median and 

interquartile ranges (non-parametric), mean and standard deviation (parametric), and 95% 

confidence intervals for means and medians. Example histograms and box plots are illustrated in 

Figures 10.1 and 10.2, respectively (from Stafford and Horne, 2004).
362

Figure 0.1 Example data summary chart.

6 7 8 9 10

100.0%

99.5%

97.5%

90.0%

75.0%

50.0%

25.0%

10.0%

2.5%

0.5%

0.0%

maximum

quartile

median

quartile

minimum

 10.800

 9.300

 8.800

 8.100

 7.800

 7.400

 7.000

 6.800

 6.400

 6.058

 6.000

Quantiles

Mean

Std Dev

Std Err Mean

upper 95% Mean

lower 95% Mean

N

7.4406991

0.5662879

0.0180251

7.4760712

7.4053271

 987

Moments

p H

The heights of the bars in the histogram represent the number of times an observation 

was recorded. The outlier box-plot above the histogram shows the interquartile range 

within the box. The line across the middle of the box identifies the median sample value. 

The diamond represents the mean and 95% confidence interval. The lines extending 

from each end of the box, or the whiskers, encompass the quartiles +/- 1.5x (interquartile 

range). Points beyond the whiskers indicate extreme values that are possible outliers. 

The bracket along the edge of the box identifies the shortest half, or the densest 50% of 

the observations. To the right of the histogram, the quantiles and moments are displayed. 

The total number of observations is listed as N.

from Stafford and Horne, 2004
363

Figure 0.2 Example box and whiskers plot, quantiles, and mean and standard deviation 

summaries by month. 

p H

6

7

8

9

1 0

1 2 3 4 5 6 7 8 9 1 0 1 1 1 2

month

1

2

3

4

5

6

7

8

9

1 0

1 1

1 2

Lev el

 6

 6

 6

 6.2

 6.25

 6.03

 6.65

 7.3

 6.6

 6.31

 6.6

 6.06

Minimum

 6.8

 6.74

 6.8

 6.6

 6.776

 6.793

 7.4

 7.5

 6.9

 6.6

 6.9

 6.824

10%

 7

 6.9

 7.2

 6.8525

 7

 7.4

 7.5

 7.5

 7

 6.8

 7.1

 7

25%

 7.4

 7.1

 7.53

 7.225

 7.2

 7.725

 7.8

 7.6

 7.495

 7.3

 7.6

 7.39

Median

 7.7

 7.65

 7.8

 7.64

 7.45

 8.2

 8.015

 7.8

 8.5

 7.685

 7.8

 7.6

75%

 8

 7.9

 8

 8

 7.824

 8.5

 8.888

 8.38

 8.87

 8.22

 7.9

 7.8

90%

 9.1

 8.7

 8.6

 8.3

 8.2

 9.3

 9.7

 8.5

 9.1

 9.2

 8.7

 10.8

Maximum

Quantiles

1

2

3

4

5

6

7

8

9

1 0

1 1

1 2

Lev el

 117

 133

 165

 80

 53

 88

 85

 21

 30

 53

 69

 93

Number

 7.34658

 7.22684

 7.45412

 7.25337

 7.21811

 7.73273

 7.87094

 7.72381

 7.70433

 7.34094

 7.46609

 7.34860

Mean

0.504041

0.494876

0.473718

0.514993

0.409939

0.677939

0.559012

0.320788

0.785821

0.665173

0.415367

0.531717

Std Dev

0.04660

0.04291

0.03688

0.05758

0.05631

0.07227

0.06063

0.07000

0.14347

0.09137

0.05000

0.05514

Std Err Mean

 7.2543

 7.1420

 7.3813

 7.1388

 7.1051

 7.5891

 7.7504

 7.5778

 7.4109

 7.1576

 7.3663

 7.2391

Lower 95%

 7.4389

 7.3117

 7.5269

 7.3680

 7.3311

 7.8764

 7.9915

 7.8698

 7.9978

 7.5243

 7.5659

 7.4581

Upper 95%

Means and Std Deviations

Oneway Analysis of pH By month

from Stafford and Horne, 2004 

I I 
364

In the example in Figure 10.2, data from all stations is grouped together for each month. ―Level‖ 

is referring to month. One drawback of using maximum and minimum values is that as the data 

set grows, the most extreme values just keep extending and don’t necessarily reflect common 

conditions. They are useful for immediate management decisions, since they often indicate 

something is wrong, but are not as useful for an overall sense of the water quality conditions.

10.4.3 Long-term trend analysis 

Long-term trend analysis is generally conducted on five to ten years of data more. However, 

data for most SFAN watersheds will be collected on two-year intervals. Trend analysis can be 

conducted on 4, 6, and 8 years of data and so on. The basic question in trend detection is ―What 

is the affect of time on the given parameters?‖ If time is shown to have an affect, then we to ask 

―Are changes sudden or gradual?‖ and ―What is the extent of the change?‖ Trend analysis should 

account for flow in order to be meaningful. Trend analysis should also account for seasonal 

differences. The ability to detect trends is dependent upon the variability of the data, as well as 

the responsiveness of the indicators (parameters), and sample size (Irwin, 2004). 

10.4.3.1 Basic trend analysis: Graphing and other useful tools

For trend analysis, at a minimum, produce histograms displaying data from multiple years. 

Combine all data from all stations and display the maximums, means, range and number of water 

quality criteria exceedences (if applicable). Use the following graphs from Rugg (2000) as a 

guide.

Figure 0.3 Histograms displaying data from multiple years, such as these from Rugg 2000.
365

When graphing data for more than one year, seasonal patterns may be readily apparent. Each 

seasonal effect (strata) should be partitioned and graphed alone so that trends which develop over 

the long-term become visually clear. Examples of partitioned graphic representations are: 

- the concentration of a particular variable (y-axis) during low-flow periods (x-axis), 

- suspended sediments during winter storm events (refer to stream hydrograph), 

- nutrient values during the spring and summer (high productivity) 

- dissolved oxygen during peak temperature periods (summer)

Tips:

 If the same data is used for long-term trends and short-term exceedences measured values can 

be averaged over each quarter, so that there is just one value per quarter.

 The above approach can also be used for analysis of large (past) data sets with varying 

 sampling frequencies

Maps displaying water quality trends are also a useful tool. Water quality stations can be 

identified by an increasing or decreasing trend or no trend. Another possibility is to utilize (or 

create) a water quality index to present SFAN data to a wide audience. One good example of a 

WQI was developed by the Washington Department of Ecology (Hallock, 2002). 

10.4.3.2 Trend Detection (modified from Hirsch et al., 1991)

Other routine trend analyses can be done according to Helsel’s Internet Published Text Book 

(Helsel and Hirsch 1992). Consult Ch. 12 of the Helsel and Hirsch (1992) text for techniques for 

trend analysis. This includes accounting for the affect of flow, other seasonal affects, and 

addresses both parametric and nonparametric statistics. Stafford and Horne (2004), suggest the 

use of monotonic trends to look for gradual changes in water quality. The protocol narrative also 

discusses various data analysis scenarios based on the distribution of the data (parametric, nonparametric, or mixed) and whether the data is flow-weighted. The Helsel and Hirsch (1992) text 

covers this in greater detail.

Tables 10.4 through 10.7 summarize recommendations for monotonic and step trend detection, 

depending on the type of data under analysis. Monotonic trends are to be used for gradual 

changes, and step trends are to be used before and after a change at a specific point in time. The 

monotonic trend hypothesis is more commonly used for general monitoring unless there is a 

reason to test for a step trend. The step trend hypothesis may be used after implementation of

best management practice if there is expected to be a detectable change. The parameters 

classified as "mixed" in the first two tables have both parametric and nonparametric components 

that are typically executed in separate steps.

Regression on season uses a periodic function of time of year, as does Tobit regression on 

season. Tobit regression is a type of linear regression that considers both censored and noncensored values of the response variable, and uses maximum-likelihood estimation for 

determining slope and intercept of the modeled trend line (Hoppe, 2003). 

Deseasonalizing is done by subtracting seasonal medians from each of the values to be regressed. 

The Seasonal Kendall test is the Mann-Kendall test for trend done for each season, with the 
366

Seasonal Kendall test statistic being the sum of the several Mann-Kendall test statistics. The 

seasonal Kendall trend test accounts for seasonal variations in concentrations by comparing 

ranks of data from the same recurring time intervals; for example, in a four-season year, 

springtime values are compared only to other springtime values, summer values to summer 

values, and so forth.

LOWESS is locally weighted scatterplot smoothing. The LOWESS curve represents a nonlinear, 

smoothed relation between two variables (instantaneous discharge and each water quality 

parameter). The method uses a series of weighted least squares regressions; observations are 

weighted by both distance from the fitted line and the magnitude of residuals from the previous 

regression. LOWESS is more desirable than simple regression because it makes no assumptions 

of data linearity or normality (Hoppe, 2003). Flow may be replaced by a transformation of flow 

in any of these analyses. 

The Seasonal Rank Sum test is the Rank Sum test (also known as the Mann-Whitney ―U‖ test 

(Kirchner, 2003), done for each season, with the Seasonal Rank Sum test statistic being the sum 

of the several test statistics. 

Table 0.4 Options for testing monotonic trends in uncensored water quality data

Not Flow Adjusted Flow Adjusted

Fully parametric

Regressions of 

concentration on time 

and season

Regression of concentration on time, 

season, and flow

Mixed

Regression of 

deseasonalized 

concentration on time

Seasonal Kendall on residuals from 

regression of concentration on flow

Nonparametric Seasonal Kendall

Seasonal Kendall on residuals from 

LOWESS of concentration on flow

Table 0.5 Options for testing step trends in uncensored water quality data.

 

Not Flow Adjusted Flow Adjusted

Fully parametric

Analysis of covariance 

of concentration on 

season and group 

(before and after)

Analysis of covariance concentration on 

season, flow and group

Mixed

Two-sample t test on 

deseasonalized 

concentration

Seasonal Rank Sum on residuals from 

regression of concentration on flow

Nonparametric Seasonal Rank Sum

Seasonal Rank Sum on residuals from 

LOWESS of concentration on flow
367

Table 0.6 Options for testing for monotonic trends in censored water quality data.

Not Flow Adjusted Flow Adjusted

Fully parametric

TOBIT regression of 

concentration on time 

and season

TOBIT regression of concentration on 

time, season and flow

Nonparametric Seasonal Kendall no test available

Table 0.7 Options for testing for step trends in censored water quality data.

Not Flow Adjusted Flow Adjusted

Fully parametric

TOBIT analysis of 

covariance of 

concentration on season 

and group

TOBIT analysis of variance of 

concentration on season, flow and group

Nonparametric Seasonal Rank Sum no test available
368

10.5 References

Hallock, D. 2002. A Water Quality Index for Ecology’s Stream Monitoring Program. 

 Washington Department of Ecology. 17pp. + app.

Helsel, D.R. and Hirsch R.M. 1992. Statistical Methods in Water Resources. Studies in 

Environmental Science 49, Elsevier Publishing, NY. 

http://water.usgs.gov/pubs/twri/twri4a3/pdf/twri4a3.pdf

Helsel D. 2004. Nondetects and Data Analysis: Statistics for Censored Environmental Data. 

Wiley. 288 pp. 

 http://www.wiley.com/WileyCDA/WileyTitle/productCd-0471671738.html

Hoppe, M. C. 2003. Ground and surface water quality. New York-New Jersey Highlands 

Regional Study Technical Report. U.S. Forest Service. Accessed 2 April 2004 at 

http://www.fs.fed.us/na/highlands/atechnical_report/index.html

Irwin, R. 2004. Vital Signs Long-Term Aquatic Monitoring Projects: Part B – Planning Process 

Steps: Issues to Consider and then to Document in a Detailed Study Plan that Includes a 

Quality Assurance Project Plan (QAPP) and Monitoring ―Protocols‖ (Standard Operating 

Procedures). National Park Service, Water Resources Division

Kirchner, J. 2003. EPS 120 Reader: Analysis of environmental data. Berkeley.

O’Ney, S. 2004. Data Analysis Procedures. Version 1.0, Standard Operating Procedure #9. In

Regulatory Water Quality Monitoring Protocol, Version 1.0, Appendix E-SOPs, National 

Park Service, Greater Yellowstone Network. Bozeman, MT. 37 pp. plus appendices.

Peitz, D. G., S. G. Fancy, L. P. Thomas, and B. Witcher. 2002. Bird monitoring protocol for 

Agate Fossil Beds National Monument, Nebraska and Tallgrass Prairie National 

Preserve, Kansas. Prairie Cluster prototype monitoring program. Version 1.00, 

September 6, 2002.

Rugg, M. E. 2000. Marin-Sonoma Counties agricultural runoff influence investigation – 1999-

2000 summary. California Department of Fish and Game

Stafford, S. and A. Horne. 2004. A review of the water quality monitoring programs in the 

National Parks in central coastal California. Report to the National Park Service. 

University of California, Berkeley. 

Wyoming Department of Environmental Quality. 1999. Manual of Standard Operating 

Procedures for Sample Collection and Analysis. Water Quality Division, Watershed 

Program. Cheyenne, Wyoming. August 1999 and revisions. 

http://deq.state.wy.us/wqd/watershed/10574-doc.pdf Accessed 08/20/04

Wyoming Department of Environmental Quality. 2000. Quality Assurance Project Plan (QAPP) 

for Beneficial Use Reconnaissance Project (BURP) Water Quality Monitoring. 

Cheyenne, Wyoming. Water Quality Division, Watershed Program. September 2000.

http://deq.state.wy.us/wqd/watershed/10573-doc.pdf Accessed 08/20/04.
369
370

SOP #11 Data Reporting 

11.1 Revision History Log

Prev. Version 

#

Revision 

Date

Author Changes Made Reason for Change New Version #

1.0 8/5/05 M. Cooprider Minor edits Preparation for 

formal peer review

1.01

1.01 3/23/06 R. Carson Minor edits Addressing formal 

peer review 

comments

1.02

Only changes in this SOP will be logged. ―Version numbers increase incrementally by 

hundredths (e.g. version 1.01, version 1.02 ...etc) for minor changes. Major revisions should be 

designated with the next whole number (e.g., version 2.0, 3.0, 4.0 ...). Record the previous 

version number, date of revision, author of the revision, identify paragraphs and pages where 

changes are made, and the reason for making the changes along with the new version number‖ 

(Peitz et al, 2002).

11.2 Introduction

Reporting results is a critical component of long-term vital signs monitoring in order to ensure 

that information generated through the program is available to all levels of park management 

including planning, interpretation, maintenance, and law enforcement. An overall 

communication strategy is being developed and will be updated in the document: SFAN 

Communication and Outreach Strategy.

The overall strategy provides detailed information about required reports including 1) annual 

reports and 2) Analysis AND synthesis reports. Suggested formats are documented in the SFAN 

Data Management Plan – Appendix C (Press, 2005)

In order to complete the annual report, the SFAN Data Management Team will work with the 

water quality specialist to ensure that data from the network’s version of NPSTORET is provided 

to WRD on an annual basis. An additional requirement for WRD is to provide a report that 

includes a paragraph summary for each parameter plus summary graphs of each site. In addition, 

summary paragraphs will be provided for each watershed including any proposed management 

activities related to water quality improvements. Recommendations for revising the protocol 

(changing monitoring intervals and timing, moving/adding sites, etc.) will also be proposed. 

These annual reports will also be provided to the SFAN parks, and can be used to report to 

GPRA and can be included in the AAWRP annual report to Congress. 

A comprehensive data analysis and synthesis will be written every few years in addition to more 

simplified, general annual summaries. Having this extra time allows for more thorough data 

analysis and review of protocols and may give greater opportunity for adaptive management. 
371

In addition, the Water Quality Specialist will be responsible for contributing to the Annual 

Administrative Report and Workplan required by each network along with additional outreach 

products summarized in Table 11.1.

Table 0.1 Summary of reporting and communication products..

Communcaction 

Product

Lead Audience Schedule Summary

Annual Report: Water Quality 

Specialist

Park Resource 

Managers

Annually Formatted as described in Data 

Management Plan – Appendix C. 

- Archive old data and document 

monitoring activities

-Describe current condition of the 

resources

-Document changes in the monitoring 

protocol

-Increase communication within the park 

and network

Analysis and 

Synthesis Report 

-

PORE 

Hydrologist

Park Resource 

Managers

3-5 years Formatted as described in Data 

Management Plan – Appendix C. 

- Determine patterns and trends

-Discover correlations among resources 

being monitored

-Analyze data to determine the level of 

change that can be detected using the 

existing sampling 

 scheme

-Provide context, interpret data for the 

park within a multi-park, regional, or 

national context

-Recommend changes to management 

practices

Program and 

Protocol Reviews

Network 

Coordinator

Program Lead, 

Water Quality 

Steering Committee, 

I&M Technical 

Steering Committee, 

Water Resource 

Division 

5 years -Periodic formal reviews of operations 

and results

-Review of protocol design and product 

to determine if changes are needed

-Part of the quality assurance – peer 

review process

Executive Briefing Water Quality 

Specialist

Program Managers, 

Superintendents, 

Front line 

interpretation staff

Annually 

(upon 

completion of 

annual report)

Two-page summary that lists monitoring 

objectives and questions, discusses 

annual results, and provides a regional 

context. 

Vital Sign Report 

Card

Network 

Coordinator

Program Managers, 

Superintendents, 

Front line 

interpretation staff

3-5 years 

(upon 

completion of 

Analysis and 

Synthesis 

Report

Two-page summary that aggregates 

trend data into an index. Provides 

Web Site Intranet Water Quality 

Specialist

Park Staff Annually or as 

needed

Post all completed reports
372

Communcaction 

Product

Lead Audience Schedule Summary

Web Site Internet Water Quality 

Specialist

Park Staff, General 

Public

Annually or as 

needed

Post all Executive Briefings, Report 

Cards, 

Park Presentations Water Quality 

Specialist

Park Staff Annually Provide a presentation to park staff 

during senior staff, all employee, or 

division meetings at each park upon 

request. Gives staff an opportunity to 

ask questions about the program.

IM Update Water Quality 

Specialist

Park Staff Quarterly This one-page monthly e-mail provides 

park staff with a short update on vital 

signs projects. Text should be no more 

than one paragraph. 

Photos Water Quality 

Specialist

For all reports and 

publication

Continuous High quality publication quality photo 

are needed to support all communication 

products. For digital photos that means 

300 pixels per inch resolution in a plain 

or compressed TIF format. Specialist 

should make every effort to document 

ongoing work, special incidents, site 

visits for communication purposes. 

In addition to data reports, a quality assurance should also be produced every few years to 

explain the results of data completeness and other QA/QC issues. See the Quality Assurance 

Project Plan (SOP #4) for more details. 

11.3 Report Format 

Reports should be standardized with other I&M reports but will generally be written in 12 point 

Times New Roman text. Tables, figures, and photographs are encouraged to present data and 

site conditions. The following is the suggested outline by Peitz and Rowell (2004):

TITLE PAGE

 Title

 Author(s)

 Institutions

 Prepared for

 Date

TABLE OF CONTENT PAGE (optional)

EXECUTIVE SUMMARY PAGE (abstract)

1.0 INTRODUCTION

1.1 Background

1.2 Justification for Study

1.3 Objectives
373

2.0 METHODS

2.1 Study area(s) 

2.2 Field method(s)

2.3 Analytical method(s)

3.0 RESULTS

4.0 DISCUSSION

5.0 MANAGEMENT IMPLICATIONS

6.0 ACKNOWLEDGEMENTS

7.0 LITERATURE CITED

11.4 Review Procedure

11.4.1 Internal Review

One or more editorial reviews should be sought before submitting the report for review by staff 

in the park(s) where monitoring occurred and before external review. Internal review by 

person(s) skilled in technical writing for clarity and directness should fulfill this review 

requirement. Internal reviews will be conducted by the SFAN Aquatics Group or other SFAN 

staff or individuals known to be skilled in writing and editing.

If reports are written to update findings only and they do not deviate significantly from 

previously reviewed and distributed reports than the review process may stop here. However, 

review by park staff and subsequent external reviews must be sought for new reports or those 

that deviate significantly from previously reviewed and distributed reports. Also, if management 

activities within a park are not clearly understood than park review should be sought for a report 

to clarify results and management implications.

11.4.2 Park Review

Park staff, generally the Resource Managers are in a unique position since they can supply 

details about management activities that may influence findings presented in a report. Also, they 

will most likely be directly involved in applying management recommendations to their 

respective parks. Therefore, review by park staff is vital to the interpretation of findings and the 

assessment of proposed management implications. Review by park staff should be conducted 

before a report is submitted for external review.

11.4.3 External Review

External review by two or more experts in water quality monitoring should be sought for the first 

report in a series of annual reports. In addition, analytical methods employed on data presented 

in the report need to be reviewed by one or more statisticians. If a report updates a previously 
374

reviewed and distributed report than external review is not required. However, external reviews 

must be sought for new reports or those that deviate significantly from previously reviewed and 

distributed reports. In order to conserve reviewer time, external reviews must follow the internal 

and park review process.

11.5 Distribution Procedure

11.5.1 Identifying Stakeholders

The primary stakeholders in our Water Quality Monitoring efforts are park staff. Additional 

stakeholders include the SFAN I&M program and the San Francisco Bay Regional Water 

Quality Control Board. Other potential stakeholders include any of the national water quality 

monitoring programs, universities and the general public.

11.5.2 Distributing the Report

Reports will be provided to the respective parks where water quality monitoring was conducted. 

Additionally, a copy will be kept on file with the SFAN office of the National Park Service, 

Sausalito, California and made available to all interested parties upon request. 

All data collected by the SFAN is public property and is subject to requests under the Freedom 

of Information Act (FOIA). The data management plan for Channel Island National Park (Dye 

1998) describes appropriate procedures to respond to FOIA requests, including the protection of 

sensitive data such as endangered species locations. In the future, reports containing nonsensitive data will be disseminated through a website. Through the website, those requesting 

data will be asked to provide information to document by whom and for what purpose the report 

is being used. By documenting requests, users can be informed when updated reports are 

available. Users requesting paper copies will be documented also.

11.6 References

Dye, L. C. 1998. Data management plan: Channel Island National Park. National Park Service 

Technical Report 98-04.

Peitz, D.G., S. G. Fancy, L. P. Thomas, and B. Witcher. 2002. Bird monitoring protocol for 

Agate Fossil Beds National Monument, Nebraska and Tallgrass Prairie National 

Preserve, Kansas. Prairie Cluster prototype monitoring program. Version 1.00,

September 6, 2002.

Peitz DG, Rowell GA. 2004. Fish community monitoring in prairie park streams with emphasis 

on Topeka Shiner (Notropis Topeka). Prepared for: Prairie Cluster Prototype Long-Term 

Ecological Monitoring Program. Version 1.00 (February 2, 2004).
375

Press, D. 2005. DRAFT San Francisco Bay Area Network Data Management Plan In Appendix 7 

 of the SFAN Draft Phase III Vital Signs Monitoring Plan. U.S. Department of Interior, 

 National Park Service. 
376

SOP #12 Site Selection and Documentation 

12.1 Revision History Log

Prev. Version 

#

Revision 

Date

Author Changes Made Reason for Change New Version #

1.0 3/9/06 Rob Carson Minor Edits to text Addressing peer 

reviewer comments

1.01

Only changes in this SOP will be logged. ―Version numbers increase incrementally by 

hundredths (e.g. version 1.01, version 1.02 ...etc) for minor changes. Major revisions should be 

designated with the next whole number (e.g., version 2.0, 3.0, 4.0 ...). Record the previous 

version number, date of revision, author of the revision, identify paragraphs and pages where 

changes are made, and the reason for making the changes along with the new version number‖ 

(Peitz et al, 2002).

12.2 Acknowledgements

O’Ney SE. 2005. Initial Site Establishment, Version 1.0, Standard Operating Procedure #1. In 

Regulatory Water Quality Monitoring Protocol, Version 1.0, Appendix E – SOPs, National Park 

Service, Greater Yellowstone Network. Bozeman, MT. 37 pp. plus appendices

12.3 Field Preparation and Site Selection

12.3.1 Permission and Access

Some sites are located on private lands or local or state government lands. In these cases it is 

necessary to obtain some form of permission. This may range from a phone call notifying the 

landowner of a sampling event to obtaining a permit. For example, California State Parks 

require a permit. Be sure to consider not only the site location but also the access route. 

Although a site may be on National Park lands, a road, trail, or parking outside Park lands may 

be required to access the site. 

Other agreements include a Memorandum of Understanding (MOU) with other agencies that are 

conducting monitoring on parklands. This can be useful in setting guidelines, study boundaries, 

and coordinating efforts. A MOU with the San Francisco Bay Regional Water Quality Control 

should be established in order to coordinate I&M monitoring efforts with the Surface Water 

Ambient Monitoring Program (SWAMP) efforts. 

On both National Park and private lands site access may require a key or combination to a lock. 

Contact a park representative or landowner when necessary. 

12.3.2 Site Selection
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Sampling locations have been described in tables and maps in the Appendix D through F of the 

Protocol Narrative. The purpose of the site location descriptions is to provide the individual with 

enough information to drive or walk to a site. The tables also indicate the time of data and type 

of habitat (flowing or standing water) to be sampled. However, the exact place to collect 

samples is not specified. To establish sites follow the tips in the following section.

12.3.2.1 Tips for Site selection

(Adapted from O’Ney, 2005)

 Avoid culverts since streams may be impacted by roads and trails; in most cases establish a 

site at least 20 m upstream of a culvert. This reduces the affect of the road. For large roads 

and/or water that is ―backed-up‖ against the culvert or bridge; move site further upstream. 

 Verify each site using GPS where possible and attention to maps and access directions

 Safety and access (i.e., not only how to get to the stream, but how to reach the sample site). 

The most common hindrances to site access are steep banks and dense stands of poison oak, 

blackberry and stinging nettle.

 Consider appropriate locations for measuring flow. Straight channel reaches where flow is 

uniform are ideal.

 Consider the monitoring objectives and questions, types of data needed, equipment needs, 

and sampling methods (see the site location tables; also see the table of monitoring questions 

and related sampling location (habitat), and time of day).

 Obtain all available historical information on the site location.

 Sites immediately upstream or downstream of tributaries or point sources should also be 

avoided to minimize problems caused by backwater effects or poorly mixed flows. Typically, 

a distance of 5 stream widths below the influence of a tributary is adequate distance to ensure 

mixing. Complete vertical and lateral mixing within the cross section is generally desirable.

 Samples collected directly downstream from a bridge should be avoided, as they can be 

contaminated from the bridge structure or runoff from the road surface.

 Access to any sampling site is directly related to monitoring program cost. Bridges are 

frequently chosen for establishment of water quality monitoring stations due to access during 

most flows and they permit sampling at any point across the stream width. Samples should be 

collected upstream of the bridge. 

 Monitoring of turbulent streams or during peak flows can be a safety concern for monitoring 

personnel. Monitoring locations should be chosen that allow sampling at peak flow with 

minimal risk to sampling personnel. 

12.3.2.2 Randomization in Site Selection

Stream selection and site locations within a stream have been selected judgmentally for a variety 

of reasons described further in the Protocol Narrative. It is important to have some level of 

randomness incorporated into the water quality sampling regime. Within a flowing water or 

standing water area, the exact sampling spot can be chosen randomly. In flowing water, it is 

important to collect samples and parameter measurements in the centroid of flow whenever 

possible. Therefore, in order to maintain a level of randomness, within the desired sampling 

strata (run, riffle or pool) a random-number generator can be used to specify the distance to 

move parallel (positive-upstream or negative-downstream direction) to the stream flow direction 

while remaining in some desired sampling strata, and within the centroid of the stream. For 
378

standing water, it is helpful to sketch the pool first. Then, using a random number table, choose 

two numbers to represent the width and length of the sampling spot from the edge of the pool. 

Where these intersect is the sampling location. 

To be consistent with the USGS centroid or cross-section flow protocol for data comparability, 

then only randomize lengthwise (direction of flow of the stream) when flow is present and once 

there, collect the sample using the USGS centroid/cross section protocol. 

Another randomization method is to use a stopwatch in the following way: The investigator 

starts the digital stopwatch so that single digits (at far right, ignore other numbers farther to the 

left) are racing fast. Let it run a while then have someone else call ―start‖ then record the last 

digit (for example, say it the last digit to the right is ―4‖, then if one is sampling riffles only, go 

0.4 of the total length of the riffle upstream from the start and sample in the centroid, and if the

cross section can’t be made there due to logistics, make it in the closest spot upstream feasible. 

This method can be used to determine the distance up or downstream within the centroid one 

should sample.

12.4 Site Documentation

12.4.1 Establishing a Preliminary Profile of Field Measurements

(from O’Ney, 2005)

After a tentative selection of a sampling site is completed, the next step is to develop a 

preliminary profile of required field measurements (discharge, temperature, dissolved oxygen, 

conductivity, pH) at various locations along the cross section. The field measurement profile is 

used to indicate reach homogeneity. To obtain data representative of the section, the variability 

of discharge and field measurements across the stream must be known (NPS, 2003).

To establish a profile of field measurements:

1. Establish a cross sectional profile of stream discharge (see SOP #9 – Field Methods for 

Flow Measurements).

2. Check the cross-sectional profile data of the stream site to determine the variability of 

discharge per unit width of the stream. 

3. Determine the increment (vertical) at which discharge in that increment is equal 

(approximately) on both sides of that point. This is the centroid of flow, and the point at 

which measurements for core parameters should be obtained.

4. Make individual measurements of required field parameters (temperature, dissolved 

oxygen, pH and conductivity) at a number of equally spaced verticals along the cross 

section and at multiple depths within each vertical.

5. Check the cross-sectional profile data to determine the variability of core field parameters 

per unit width of the stream.

6. Field-measurement profiles of stream variability are needed for low- and high-flow 

conditions and should be verified at least every 2 years.

Record the information collected in 1-5 above. Include in Field Folders for each station.
379

12.4.2 Obtaining Station Coordinates

(Adapted from WY-DEQ, 1999)

If the cross sectional profile of stream discharge and field measurements indicates that the 

section is not homogeneous, then repeat the procedure at additional locations until a suitable site 

has been identified.

After determining the station location, use GPS equipment to obtain station coordinates. GPS 

location data are collected by GRYN field technicians for each monitoring station. Readings are 

taken near the water’s edge. Technicians record the GPS field file, GPS start time and stop time, 

GPS latitude/longitude coordinates, and after the files are processed, fill in the corrected 

latitude/longitude coordinates on the Field Data sheet. After the GPS field files are differentially 

corrected, the location data are entered onto NPSTORET station files, Field Data sheets and field 

log books. All GPS data files will be sent electronically to the GRYN Bozeman office to be 

archived.

Field technicians are referred to the GRYN Data Manager for details on using GPS equipment 

and software. On-line training is available. The GRYN should provide initial and refresher 

training as necessary

.

12.4.3 Photographic Documentation

Develop a standardized naming system for the photographs such as site ID and direction. 

Photographic documentation has many purposes and one of them is to track site changes over 

time. For this purpose, we want to document periphyton, riparian cover, location and extent of 

gravel bars 

(Adapted from WY-DEQ, 1999):

Each sampling site must be documented with a series of photographs to establish site conditions. 

These photographs will be used to accurately relocate monitoring sites and to document field 

conditions. Individual photographs are taken looking upstream and downstream from the base of 

the sampling reach. 

Photographs should be identified with:

 The photograph number, frame and/or roll;

 Date and time, even if the photographs are automatically date stamped by the camera;

 The subject;

 The location in narrative format and lat/long coordinates;

 The photographer;

 Witnesses, if any;

 The location from which the photograph was taken; and

 A short narrative related to the photographs

New photographs should be taken at the beginning of each field season (i.e., summer/fall before 

the next water year), and whenever site conditions change significantly.
380

12.4.4 Establishing NPS-STORET project files

(from O’Ney, 2005)

Field personnel are responsible for establishing and maintaining electronic and paper project and 

site files. NPS policy requires specific information on surface water sampling sites. Technicians 

are referred to http://science.nature.nps.gov/im/monitor/protocols/wqPartE.doc for detailed 

discussions of NPS data and metadata requirements, and to Data Management Procedures 

(SOP#8) of this protocol for detailed instructions. 

Project files should be established prior to site reconnaissance visits, using the NPSTORET 

database template. Project, station, and metadata information are only entered once (unless a new 

project is started, new stations are added, or procedures change). All monitoring results 

collected at stations are assigned to projects. For Project ID, enter SFAN followed by WQ to 

indicate that it is a water quality project and then a sequence number (e.g. the first project in the 

Network would be SFANWQ01). Most of the information entered about the Project on the Main 

and Additional Info tabs should be readily available in network planning documents. You can 

paste in relevant information directly from a monitoring plan or other document. Additionally, 

the entire document can be stored as an Adobe Acrobat PDF file in the database (Documents 

screen) to permanently associate important reference material directly with the data. Other 

references (entered in the Metadata template) can be associated with the project on the Citations 

tab.

Refer to Data Management Procedures in the protocol narrative for the minimum information 

required for establishing electronic project files in NPS-STORET, and details for entry.

12.4.5 Entering Station Information in NPSTORET

Prepare a description of the location, and compile other required information (including digital 

photograph) for establishing NPS-STORET files. Upon returning to the office, enter all 

information into the SFAN water quality database. Some example station IDs are included in 

Table 12.1. 

Table 0.1. Station IDs for water quality sampling locations

Water body Location Description Station ID

Chalone Creek South wilderness, PINN_I&M_CHA1

Gerbode Creek Above Rodeo Creek confluence GOGA_I&M_ROD6

Olema Creek At Bear Valley Rd. bridge, upstream PORE_I&M_OLM11

Franklin Creek Franklin Creek at JOMU bridge JOMU_I&M_FRA1

The NPSTORET site naming convention for Station ID’s is:

Park Code_Project Grouping_Station name/abbreviation/code

STORET allows station Ids with up to 15 characters. For old station ideas, most systems allow 

you to carry along secondary station names so those names can be preserved. 

Works well for sorting stations
381

12.4.6 Entering Additional Information Into NPSTORET

In addition to the information required for site establishment, information must be entered related 

to the parameters collected at each site. See the SFAN Quality Assurance Project Plan (SOP #4) 

and Protocol Narrative for additional information.

12.4.7 Creating Field Folders

Selected information that is needed for reference while at a sampling station is kept in a field 

folder. The field folder contains information needed by trained personnel to locate and safely 

collect and process water quality samples, and is taken along on each sampling trip. Assemble a 

field folder for each sampling station to contain the following:

 Station description:

o Location of gaging station (if one is present) and USGS contact information.

o Location of sample-collection sites. Actual sampling locations may differ slightly 

depending on flow conditions.

o Hydrologic and geologic maps, if available.

o Name of landowner, tenant, or other responsible party.

o Current copy of research and collection permit (if site located within NPS 

boundaries)

o Site access instructions (for example, call owner or site operator before arrival at 

site, obtain key to unlock security gate).

o Photographs to document site conditions.

 Maps to site (state and local)

 Profiles of cross section of stream channel at sampling locations

o Stream bottom geometry

o Physical and chemical measurements

 Safety information (SOP#3):

o Nearest emergency facilities.

o Phone numbers (home) of project manager or supervisor.

o Traffic condition and traffic plan showing where to park, placement of flags and 

cones.

o Location of power lines.

o Environmental hazards, such as weather and animals.

 Sampling schedule 

o Laboratory analyses to be requested and associated codes

o When to collect samples

o Bottle types needed for each analytical schedule

 Sampling instructions:

o Discharge curves and velocity cross sections

o Discharge rating curves and/or tables
382

o Preservation, storage, and handling requirements

o Quality control sample requirements

 Shipping instructions (if applicable)

o Amount of ice to use and holding time requirements

o Mailing labels to and from laboratory

o Location of nearest post office or shipping agent

 Field forms and examples of completed forms for both required and regulatory field 

parameters:

o Analytical service request forms

o Permission forms and data collection forms

 Laboratory Chain of Custody Forms including proper dilutions for fecal indicator bacteria 

 samples.

 Equipment check lists

 Other local information including park contacts, local advisories (fire, flood, landslide, 

rock fall, problem exotics), etc.

12.5 Equipment Installation

12.5.1 Installation of a Staff Gauge

(Adapted from USGS, 1999)

For recurring discharge measurements at a monitoring location, it is usually best to install a staff 

gage (non-recording) in the absence of any nearby automated (recording) gaging station. A staff 

gage is a scale (usually enameled steel) placed in a stream to show the elevation of the water 

surface. It is calibrated by referencing the numbered height on the gage to the surveyed 

elevation of the water surface and its associated flow at the time of installation. A rating curve 

or stage-discharge relationship is then developed from numerous stage measurements and 

discharge computations made at the site during variations in flow by plotting stage versus

discharge (typically gage height in feet versus discharge in cubic feet per second) on log-log 

paper. The more points, the more precise the rating curve is likely to be. 

Vertical staff gages are used as reference gages for setting a recording device. The vertical staff 

gage can be used in a stilling well or in a stream. Standard staff gages should be purchased, and 

installed on a 4x4 post (or affixed to a permanent structure such as a bridge) adjacent to the 

sampling station. The staff gage should be located in an area that will provide some degree of 

protection from debris flows, etc. The staff gages installed at specific water monitoring locations 

will be read at the time water samples are taken to determine the stage or elevation of the water 

surface at that location. Anchored in the stream bed, the gage will consist of a vertical scale that 

is permanently marked in increments of 0.01 feet and the stage reads directly from these 

markings to the nearest 0.01 feet. Stream stage is defined as the elevation of the water surface 

above an arbitrary zero datum at that specific point in the stream. Thus, the zero discharge point 

does not necessarily correspond to a stage of zero.
383

12.5.2 Installation of an Automatic Stage Recorder and Establishing a Rating 

Curve

Measuring continuous discharge requires the installation of a pressure transducer and electronic 

data logger in conjunction with the staff gage. A Keller pressure transducer and Campbell 

Scientific data logger are recommended, however, there are numerous other pressure transducers 

and data loggers that would also be adequate (O’Ney, 2005). SFAN currently uses Druck and 

Global Water pressure transducers. Follow the operating instructions provided by the 

manufacture. 

The best way to install the pressure transducer/data logger in surface water is to use a 2" pipe to 

protect the sensor and the data logger. You can use PVC schedule 40, or ABS sewer drain pipe.

The best protective pipe is PVC schedule 40 electrical conduit. This light grey pipe has UV 

protectors and pre-formed "sweeps" or bends which enable the pipe to conform to the contours of 

the river bank. The sensor will slide down through 45 or 90 degree sweeps. The pipe may be 

buried in the river bank, secured with rocks, or fastened to the bank with large staples made by 

bending pieces of concrete reinforcing steel in half and driving them into the bank. The pipe 

should have several large (1/2" diameter) holes drilled near the sensor location in order to 

eliminate velocity effects on the sensor. Also, a smaller 1/4" hole should be drilled near the top 

of the pipe to allow air movement when the water goes up and down. A standard slip cap or a 

locking well cap can be used to protect the top of the data logger. You can also adapt the pipe 

for a screw-on cap.

Depending on site conditions, it may be more appropriate to install the sensor and data logger in 

a stilling well. Various kinds of automatic stage recorders can be set up in stilling wells. A 

stilling well is a chamber that is hydraulically connected to the stream through intake pipes. The 

stilling well eliminates turbulence that may occur in the stream and the elimination of waves and 

surges results in more accurate readings. Manufacturers' instructions are followed for the 

specific installation and operation.

The next step is to establish a rating curve by making a series of independent flow measurements 

and simultaneous staff gage measurements for that station at different water levels using the 

velocity-area method (see Field Methods for Measurement of Core Parameters, SOP#5). The 

rating curve converts stage height to discharge. Discharge measurements using the velocity-area 

method should be made over a range of stage heights. Discharge rating curves are usually 

determined empirically by means of periodic measurements of discharge and stage using a 

current meter (minimum of 10 per year is recommended initially). However the rating curve 

may shift over time and periodic measurements are necessary after the first year to either confirm 

the permanence of the rating or to follow changes/shifts in the rating. It is important that the 

rating curve include measurements made at flow extremes (e.g. flood conditions) and under ice 

conditions to be most accurate. Volume 2 of USGS WSP 2175 (Rantz et. al., 1982) discusses 

stage-discharge relations ranging from simple to complex and the various parameter variables 

(slope, velocity index) that should be considered when computing discharge rating curves under 

more complex situations.
384

It is recommended that for at least the first year of sampling, discharge measurements be taken 

for each sampling event, to help establish a reliable stage/discharge relationship.

12.6 References

National Park Service. 2003.Vital signs long-term aquatic monitoring projects: Part C, draft 

guidance on WRD required and other field parameter measurements, general monitoring 

methods and some design considerations in preparation of a detailed study plan, (work in 

progress)‖, August 6, 2003. Draft. Available at: 

http://science.nature.nps.gov/im/monitor/protocols/wqPartC.doc

National Park Service. 2004. Part E: Draft guidance on data archiving and reporting in STORET. 

Available at http://science.nature.nps.gov/im/monitor/protocols/wqPartE.doc

O’Ney SE. 2005. Initial Site Establishment, Version 1.0, Standard Operating Procedure #1. In 

Regulatory Water Quality Monitoring Protocol, Version 1.0, Appendix E – SOPs, 

National Park Service, Greater Yellowstone Network. Bozeman, MT. 37 pp. plus 

appendices

Rantz, SE., and others. 1982. Measurement and computation of streamflow, Volume 1, 

measurement of stage and discharge: U. S. Geological Survey Water Supply Paper 2175. 

284 p. 

U.S. Geological Survey, variously dated, National field manual for the collection of waterquality data: U.S. Geological Survey Techniques of Water-Resources Investigations, 

book 9, chaps. A1-A9, available online at http://pubs.water.usgs.gov/twri9A

Wyoming Department of Environmental Quality. 1999. Manual of Standard Operating 

Procedures for Sample Collection and Analysis. Available at

http://deq.state.wy.us/wqd/watershed/10574-doc.pdf Accessed 08/02/04.
385

The U.S. Department of the Interior (DOI) is the nation's principal conservation agency, charged with the mission "to protect and 

provide access to our Nation's natural and cultural heritage and honor our trust responsibilities to Indian tribes and our 

commitments to island communities." More specifically, Interior protects America’s treasures for future generations, provides 

access to our nation’s natural and cultural heritage, offers recreation opportunities, honors its trust responsibilities to American 

Indians and Alaska Natives and its responsibilities to island communities, conducts scientific research, provides wise stewardship 

of energy and mineral resources, fosters sound use of land and water resources, and conserves and protects fish and wildlife. The 

work that we do affects the lives of millions of people; from the family taking a vacation in one of our national parks to the 

children studying in one of our Indian schools.

NPS D-39, October 2006
386

National Park Service

U.S. Department of the Interior

Natural Resource Program Center

1201 Oakridge Drive. Suite 150

Fort Collins, Colorado 80525

www.nps.gov

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