333

National Park Service

U.S. Department of the Interior

Natural Resource Stewardship and Science

Water Quality Monitoring Protocol for Inland Lakes

Great Lakes Inventory and Monitoring Network, Version 1.1

Natural Resource Report NPS/GLKN/NRR—2015/1027
ON THE COVER

Overlooking Chapel Lake at Pictured Rocks National Lakeshore, Michigan.

Photograph by Joan Elias.
Water Quality Monitoring Protocol for Inland Lakes

Great Lakes Inventory and Monitoring Network, Ver. 1.1

Natural Resource Report NPS/GLKN/NRR—2015/1027

Joan Elias1, Richard Axler2, Elaine Ruzycki2, and David VanderMeulen1*

1National Park Service

Great Lakes Inventory and Monitoring Network 

2800 Lake Shore Drive East

Ashland, Wisconsin 54806

* Contact author: david_vandermeulen@nps.gov

2 Center for Water and the Environment

Natural Resources Research Institute

University of Minnesota–Duluth

5013 Miller Trunk Highway

Duluth, Minnesota 55811

September 2015

U.S. Department of the Interior

National Park Service

Natural Resource Stewardship and Science 

Fort Collins, Colorado
ii

The National Park Service, Natural Resource Stewardship and Science office in Fort Collins, 

Colorado, publishes a range of reports that address natural resource topics. These reports are of 

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the U.S. Government.

This report is available in digital format from the Great Lakes Inventory and Monitoring Network

website (http://science.nature.nps.gov/im/units/glkn/monitor/lakes.cfm), and the Natural Resource 

Publications Management website (http://www.nature.nps.gov/publications/nrpm/). To receive this 

report in a format optimized for screen readers, please email irma@nps.gov.

Please cite this publication as:

Elias, J. E., R. Axler, E. Ruzycki, and D. VanderMeulen. 2015. Water quality monitoring protocol 

for inland lakes: Great Lakes Inventory and Monitoring Network, version 1.1. Natural Resource 

Report NPS/GLKN/NRR—2015/1027. National Park Service, Fort Collins, Colorado.

NPS 920/129697, September 2015
iii

Contents

Page

Figures..................................................................................................................................................vii

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

Revision History Log............................................................................................................................ix

Acknowledgments.................................................................................................................................xi

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

1.1 Rationale for Selecting This Resource to Monitor...................................................................1

1.2 Key Variables of Interest..........................................................................................................1

1.2.1 Temperature......................................................................................................................2

1.2.2 Specific Electrical Conductivity (EC25 or SC25)............................................................2

1.2.3 pH .....................................................................................................................................2

1.2.4 Dissolved Oxygen (Concentration and % Saturation)......................................................3

1.2.5 Lake Level........................................................................................................................3

1.2.6 Water Clarity ....................................................................................................................4

1.2.7 Major Ions ........................................................................................................................4

1.2.8 Dissolved Silica (SiO2).....................................................................................................5

1.2.9 Dissolved Organic Carbon (DOC) ...................................................................................5

1.2.10 Nutrients (Total Phosphorus [TP], Total Nitrogen [TN], Nitrate+Nitrite-N 

[NO3+NO2-N], and Ammonium-N [NH4-N])...........................................................................6

1.2.11 Chlorophyll-a..................................................................................................................6

1.3 Background and History; Description of Resource..................................................................6

1.3.1 Water Quality Monitoring Efforts by Parks.....................................................................7

1.3.2 Description of Parks’ Inland Lakes..................................................................................9

1.4 Measurable Objectives ...........................................................................................................10

1.5 Quality Assurance and Quality Control .................................................................................11

2.0 Sample Design ...............................................................................................................................13

2.1 Rationale for Selecting This Sampling Design.......................................................................13

2.1.1 Random Versus Nonrandom Selection of Lakes............................................................13

2.1.2 Current Lake-Monitoring Programs of States Within the Great Lakes 

Region .....................................................................................................................................14
iv

Contents (continued)

Page

2.1.3 Great Lakes Network Design .........................................................................................15

2.1.4 Legal Designations of Lakes Within the Great Lakes Network.....................................21

2.2 Frequency of Sampling...........................................................................................................22

2.3 Location of Sites.....................................................................................................................25

2.4 Depths of Sampling ................................................................................................................25

2.5 Timing of Sampling................................................................................................................26

3.0 Sampling Methods.........................................................................................................................27

3.1 Field Season Preparations and Equipment Setup ...................................................................27

3.2 Details of Taking Field Measurements and Collecting Samples............................................29

3.2.1 Sequence of Activities During Field Workday...............................................................29

3.2.2 Arrival at Monitoring Site - Recording Field Information.............................................30

3.2.3 Measurement of Field Parameters..................................................................................32

3.2.4 Collection of Water Samples..........................................................................................32

3.3 Post-Collection Sample Processing........................................................................................33

3.3.1 In-house Laboratory Work .............................................................................................33

3.3.2 Shipping Samples to Contract Laboratory .....................................................................34

3.3.3 Equipment Cleaning and Storage ...................................................................................34

3.3.4 Data Entry and Management..........................................................................................34

3.4 End of Field Season Procedures.............................................................................................37

3.5 Quality Assurance/Quality Control ........................................................................................37

4.0 Data Handling, Analysis, and Reporting .......................................................................................41

4.1 Metadata Procedures ..............................................................................................................41

4.2 Overview of Database Design ................................................................................................41

4.3 Data Entry, Verification, Certification, and Editing...............................................................42

4.4 Data Archival Procedures.......................................................................................................42

4.5 Quality Assurance and Quality Control Pertaining to Data Entry and 

Management .................................................................................................................................43

4.6 Routine Data Summaries........................................................................................................43
v

Contents (continued)

Page

4.7 Methods for Long-Term Trend Analysis ...............................................................................44

4.8 Reporting Schedule ................................................................................................................45

4.9 Report Format with Examples of Summary Tables and Figures............................................45

5.0 Personnel Requirements and Training ...........................................................................................47

5.1 Roles and Responsibilities......................................................................................................47

5.1.1 Project Manager..............................................................................................................47

5.1.2 Assistant Project Managers ............................................................................................48

5.1.3 Field Personnel (Field Crew Member/Leader)...............................................................49

5.1.4 Data Manager .................................................................................................................49

5.2 Crew Qualifications................................................................................................................49

5.3 Training Procedures................................................................................................................50

6.0 Operational Requirements..............................................................................................................51

6.1 Annual Workload and Field Schedule....................................................................................51

6.2 Facility and Equipment Needs................................................................................................51

6.3 Budget Considerations............................................................................................................51

6.3.1 Equipment and Supplies.................................................................................................51

6.3.2 Staff Salaries...................................................................................................................52

6.3.3 Vehicles and Travel........................................................................................................52

6.3.4 Analytical Laboratory Costs...........................................................................................52

6.3.5 Total Estimated Annual Costs........................................................................................54

6.4 Procedures for Revising and Archiving Previous Versions of the Protocol...........................54

Literature Cited ....................................................................................................................................57

Index to Standard Operating Procedures .............................................................................................67

vii

Figures

Page

Figure 1. Trend analysis of long-term monitoring of total phosphorus in summer. ...........................23

Figure 2. Trend analysis of long-term monitoring of Secchi depth in summer. .................................24

Tables

Page

Table 1. Ion balance typical for fresh water in the upper Midwest (Wetzel 2001, Horne 

and Goldman 1994)................................................................................................................................4

Table 2. Summary of water quality data available for inland lakes at Great Lakes 

Network parks........................................................................................................................................7

Table 3. Number of lakes >1 hectare in six Great Lakes Network parks............................................10

Table 4. Summary of different types of sampling designs..................................................................17

Table 5. Summary of numbers of lakes and ponds in the six Great Lakes Network parks 

with inland lake resources, classified by size (surface area)................................................................18

Table 6. Index lakes in the Great Lakes Network’s sampling design. Maximum depth 

(Zmax) is included when known. Thermal arrays are deployed at lakes shown in bold font. ..............19

Table 7. Number of years required to detect a change in dissolved oxygen (DO) 

saturation in different Great Lakes Network lakes and depth strata ....................................................24

Table 8. Checklists of equipment and supplies for monitoring water quality of inland 

lakes. ....................................................................................................................................................27

Table 9. Checklist of activities to be conducted prior to sampling inland lakes. ................................28

Table 10. Typical sensor performance specifications (Penoyer 2003). ..............................................33

Table 11. Example range of analytical methods, method detection limits (MDLs), 

containers, preservation methods, and holding times. .........................................................................35

Table 12. Summary of QA/QC procedures pertaining to sampling methods......................................38

Table 13. Ideal calibration frequencies and acceptance criteria for field instruments. .......................39

Table 14. Summary of QA/QC procedures pertaining to data management.......................................43

Table 15. Estimates of laboratory costs for analysis of water quality parameters. Costs in 

bold font reflect per sample prices for 2015. ......................................................................................53

Table 16. Total estimated annual costs for monitoring water quality at GLKN inland 

lakes. ....................................................................................................................................................54

ix

Revision History Log

The following table lists all edits and amendments to this document since the original publication 

date. Information entered in the log must be complete and concise. Users of this standard operating 

procedure will promptly notify the project manager and/or the Great Lakes Network (GLKN) data 

manager about recommended and required changes. The project manager must review and 

incorporate all changes, complete the revision history log, and change the date and version number 

on the title page and in the header of the document file. For complete instructions, please refer to 

Revising the Protocol, SOP #13.

Revision 

Date

Previous 

Version #

New 

Version #

Author (with 

title and 

affiliation)

Location in Document and 

Concise Description of 

Revision

Reason for 

Change

5/01/2015 1.0 1.1 David 

VanderMeulen, 

GLKN

Updated the NPS contact 

author, dropped and added 

index lakes, added information 

about continuous monitoring 

and differentiated it from 

discrete monitoring, added 

details concerning deployment, 

operation, and data 

management for thermal arrays, 

removed references to VSIMS, 

and added information about 

Aquarius Informatics and data 

certification, added information 

about the use of web-based data 

summaries and reporting, 

updated personnel section to 

reflect that many park staff are 

paid by GLKN to implement 

water quality monitoring at 

their respective parks, removed 

information about estimated 

startup costs, updated estimated 

annual cost of equipment, 

supplies, salaries, analytical 

costs, and total estimated 

annual costs, added or updated 

references, fixed a handful of 

grammatical errors throughout, 

and deleted Tables 15, 16, and 

18.

To clarify and 

update protocol 

narrative based 

on changes that 

have occurred 

since Version 

1.0 was 

published in 

2008

xi

Acknowledgments

We would like to thank S. Magdalene and D. Engstrom for discussions early in the planning process 

for this protocol. Thanks also go to the following Great Lakes Inventory and Monitoring Network 

staff: E. Beever for drafting sections on analysis of data, M. Hart for drafting the data management 

portion of the protocol, S. Sanders for text on reporting, and T. Ledder for discussion related to field 

methods, sampling handling, and quality assurance/quality control.

We relied heavily on the monitoring protocols of others, especially those of the Greater Yellowstone 

Network, San Francisco Area Network, and Southwest Alaska Inventory and Monitoring Network.

Finally, we would like to acknowledge the many reviewers who provided valuable comments on an 

earlier version of this protocol.

1

1.0 Background and Objectives

Inland lakes are important and valuable resources at six of the parks of the Great Lakes Network 

(Apostle Islands National Lakeshore [APIS], Indiana Dunes National Lakeshore [INDU], Isle Royale 

National Park [ISRO], Pictured Rocks National Lakeshore [PIRO], Sleeping Bear Dunes National 

Lakeshore [SLBE], and Voyageurs National Park [VOYA]). The Great Lakes Network (hereafter, 

GLKN or the Network) parks encompass a variety of aquatic habitats and biota, including 129 named 

lakes, totaling nearly 41,000 ha (101,000 acres) (Lafrancois and Glase 2005). 

This protocol addresses monitoring of inland lakes to assess change in basic limnological parameters, 

including those mandated by the National Park Service (detailed below), for the purpose of tracking 

changes in water quality over time.

1.1 Rationale for Selecting This Resource to Monitor

Water quality is generally high throughout GLKN parks, though threats exist from atmospheric 

deposition, urban and agricultural runoff, wastewater discharges and seepage from septic systems, 

recreational use, and other anthropogenic impacts. Network lakes listed as impaired under Section 

303(d) of the Clean Water Act are only so designated because of fish consumption advisories 

(Ledder 2003). All lakes in the State of Michigan have fish consumption advisories (FCAs) for 

mercury (MDCH 2004), as do most lakes in VOYA (MPCA 2006, NPS 2005) and Lake George, at 

INDU (NPS 2005). In addition, Siskiwit Lake, at ISRO, has a FCA for polychlorinated biphenyls 

(PCBs) and Big Glen Lake, at SLBE, has a FCA for PCBs and chlordane. When lagoons are 

connected to Lake Superior, they are under FCAs for PCBs (NPS 2005); however, these lagoons are 

sometimes isolated from the lake. All waterbodies within INDU, ISRO, PIRO, and SLBE are 

designated Outstanding State Resource Waters, and all those in VOYA are designated Outstanding 

Resource Waters. Lake Superior waters within APIS boundaries are designated Outstanding Natural 

Resource Waters by the state, and Lake Superior as a whole is designated as federal Outstanding 

Resource Waters (Ledder 2003).

Although the water quality of most inland lakes is currently relatively good at GLKN parks, 

conditions can change quickly. It is important to detect change as early as possible, in order to 

maximize the potential for effective management actions. Park lakes are used extensively by visitors 

for fishing, boating, swimming, and other recreational activities. The four large lakes at VOYA are 

impounded for generating hydropower; the levels are controlled through an international agreement 

(The International Joint Commission). Because the preservation of lake water quality and quantity is 

of utmost importance to park managers, researchers, and the general public, monitoring basic water 

quality ranked among the highest of the Network’s vital signs (Route 2004).

1.2 Key Variables of Interest

A national review panel assembled by the National Park Service–Water Resources Division (NPSWRD) recommended a suite of five parameters be measured across all NPS monitoring networks 

(NPS 2002). In addition to these five mandated parameters (temperature, pH, specific conductance, 

dissolved oxygen, and flow/water level) we added a measure of water clarity (Secchi depth or 

transparency tube depth) to our core suite. The core suite was ranked highest among potential vital 
2

signs for aquatic systems of GLKN parks, although it was recognized that these measurements were 

less diagnostic of water quality degradation than biotic communities and other water quality 

variables, such as nutrient concentrations. 

Inputs of excess nutrients, invasion and spread of exotic species, and contaminants from atmospheric 

fallout and surface runoff, and how these stressors affect the chemical and biological functions of 

lakes are key issues of concern. By monitoring an advanced suite of parameters (nitrogen and 

phosphorus species, dissolved organic carbon, major ions, dissolved silica, and chlorophyll-a), we 

will provide data for a more thorough understanding of changes in lakes over time.

1.2.1 Temperature 

Water temperature exerts a major influence on the activity, growth, distribution, and survival of 

aquatic biota. Fish, insects, zooplankton, phytoplankton, and other aquatic organisms all have 

preferred temperature ranges for optimal health and reproduction. Temperature is also important 

because of its influence on water chemistry and physical processes, such as evaporation, oxygen (and 

other gas) diffusion rates, chemical reaction rates, particle settling velocities (via viscosity), and the 

stability of thermal stratification. Temperature, via its effect on water density, also acts to structure 

deeper lakes into distinct layers with profound physical and chemical differences that create a 

diversity of habitats for organisms (e.g., Wetzel 2001).

1.2.2 Specific Electrical Conductivity (EC25 or SC25) 

Electrical conductivity is a measure of the capacity of water to conduct an electrical current. Specific 

conductivity (called EC25 or SC25) is the “raw” conductivity normalized to unit length and crosssection at 25°C. This normalization eliminates its temperature dependent variability and makes it a

good estimator and surrogate measure of the concentration of total dissolved ions in the water. The 

magnitude of SC25 is controlled largely by geology (rock types) in the watershed, which determines 

the chemistry of the watershed soil and ultimately the lake. The size of the watershed relative to the 

area of the lake (Aw:Ao ratio) also affects SC25, with a larger ratio indicating that relatively more 

water drains into the lake because of a larger catchment area and has more contact with soil before 

reaching the lake. Increased SC25 may indicate a number of sources of pollutants, such as 

wastewater from sewage treatment plants or on-site septic systems, urban runoff from roads 

(especially road salt), agricultural runoff, and atmospheric deposition. Increased conductivity from 

runoff into soft waters can be a major stressor to salmonids, shoreline and nearshore plants, and other 

aquatic organisms. Conductivity is an important indicator of polluted runoff that may contain excess 

nutrients, organic matter, pathogenic microbes, heavy metals, and organic contaminants. SC25 

increases naturally due to evaporative salt concentration and respiration, which increases bicarbonate 

and carbonate concentrations. It is also an excellent ‘tracer’ of water masses in the lake, as well as 

tributary and groundwater inflows. 

1.2.3 pH 

The pH value is the negative logarithm of the hydrogen ion (H+) activity in the water. At higher pH 

levels, fewer free hydrogen ions are present; a change of one pH unit (e.g., pH 7 to pH 8) reflects a 

tenfold change in the concentrations of the hydrogen ion. A closely related parameter is the alkalinity 

or acid-neutralizing capacity (ANC,) which is a measure of the buffering capacity of the water. The 
3

pH of water determines the solubility and biological availability of chemical constituents such as 

nutrients (phosphorus, nitrogen, and carbon) and heavy metals (e.g., lead, copper, cadmium). pH is 

generally used to set water quality criteria for lakes and streams because of its potential impacts to 

the life cycle stages of aquatic macroinvertebrates and certain salmonids that can be adversely 

affected when pH levels are above 9.0 or below 6.5 (Stednick and Gilbert 1998). The mobility of 

many metals is also enhanced by low pH and can be important in assessing mining impacts. 

Estimating the toxicity of ammonia, aluminum, and some other contaminants requires accurate pH 

values. Daily and seasonal variability in pH is associated with natural changes in biological 

photosynthesis and respiration, as well as inputs from runoff and atmospheric deposition (e.g., 

Schindler 1988, Schindler et al. 1985). When nutrient pollution results in higher algal and plant 

growth (e.g., from increased temperature or excess nutrients), pH levels may increase, as allowed by 

the buffering capacity of the lake. Although these small changes in pH are not likely to have a direct 

impact on aquatic life, they greatly influence the availability and solubility of all chemical forms in 

the lake and may aggravate nutrient problems.

1.2.4 Dissolved Oxygen (Concentration and % Saturation)

Dissolved oxygen (DO) is a measure of the amount of oxygen in solution. Oxygen solubility is 

controlled largely by water temperature and the partial pressure of oxygen within gasses in contact 

with the solution. Its concentration in any stratum of water is determined by the net difference 

between its sources and its sinks. Oxygen transfer from the atmosphere to the water and from one 

depth to another depends on its diffusion rate, which is highest in the upper, turbulent wind-mixed 

layer (epilimnion) and very low in the hypolimnion. The largest source of O2 is the atmosphere, but 

phytoplankton and macrophyte photosynthesis produce O2 during daylight hours and tributaries can 

contribute significant DO to specific layers of water. The major sink for DO is respiration by 

animals, plants, and microbes, occurring throughout the day. Because photosynthesis is light 

dependent, and surface mixing is largely dependent on wind energy and morphometry (in the sense 

of wave height and fetch), DO levels can vary throughout the day, season, and with depth. 

Temperature controls the potential O2 saturation, although water can supersaturate from high 

turbulence (e.g., waterfalls) or photosynthesis from algal blooms in hypereutrophic lakes. 

A DO level >1 mg/L is generally accepted as a chronic minimum for most aquatic animals; 5 mg/L is 

a chronic minimum for the maintenance and survival of most aquatic organisms and is a common 

regulatory criterion for supporting a cold water fishery. As water becomes warmer it can hold less 

DO. If the water becomes too warm, even if 100% saturated, O2 levels may be suboptimal for many 

species of trout. Mid-summer may be a critical time for some fish because epilimnetic water is too 

warm for them, and while hypolimnetic water may be an optimal temperature, it may have too little 

oxygen. 

1.2.5 Lake Level

Accurate lake level measurements are highly recommended as per NPS monitoring guidelines (NPS 

2002) and are needed primarily because of their importance in defining the spatial extent of littoral 

zones. These shallow water areas provide critical habitat for many aquatic organisms and are nursery 

areas for both planktivorous and piscivorous fish at various stages of their life cycles. Accurate 
4

volumetric estimates, hydrologic budgets, heat budgets and mass balance budgets for chemical 

compounds and oxygen also require accurate lake levels. In reservoirs and lake level controlled 

systems such as Lake Kabetogema in VOYA, lake levels and discharge from the lake are 

controversial management issues (Kallemeyn et al. 2003). Fluctuations in lake level are also 

important in terms of nearshore development, wetland conservation and function (Mitsch and 

Gosselink 2000), and nutrient and mercury cycling (Christensen et al. 2004).

1.2.6 Water Clarity

Although not a mandated parameter, GLKN has included a measure of water clarity (Secchi depth 

and/or transparency tube depth) in the core suite of parameters because of its fundamental 

importance to whole-lake ecology, ease of measurement, and the fact that it will always be measured 

along with core suite profiles. Light penetration, for which water clarity is a surrogate, is an 

important regulator of rate of primary production and plant species composition, including the 

balance between phytoplankton and macrophyte production in shallow lakes (e.g., Moss et al. 1996). 

Water clarity provides a visual measurement that relates directly to the aesthetic perceptions of the 

general public. Secchi depth can also be an effective indicator of non-algal suspended sediment 

loading from agricultural and urban runoff and from shoreline erosion (Swift et al. 2006, Holdren et 

al. 2001, Preisendorfer 1986). Secchi depth transparency has a long history of use in lake monitoring 

programs as an excellent indicator of trends in phytoplankton biomass (e.g., WOW 2005, Goldman 

1988), and is an integral component of Upper Great Lakes States Monitoring programs (e.g., WDNR 

2005; MPCA 2005a, 2004c; MDEQ 2004, 2001).

1.2.7 Major Ions 

 Cations––calcium (Ca+2), magnesium (Mg+2), sodium (Na+), and potassium (K+)

 Anions––SO4-2, Chloride (Cl-), and alkalinity (CaCO3)

The chemical composition of a lake is a function of land use, climate, and basin geology. Each lake 

has an ion balance of the three major anions and four major cations (Table 1). The ionic 

concentrations influence the lake’s ability to assimilate pollutants (e.g., acidification) and maintain 

nutrients in solution. For example, calcium carbonate (CaCO3) in the form known as marl can 

precipitate phosphate from the water, thereby removing this important nutrient from the water. High 

Ca+2 and Mg+2 directly reduce the bioavailability and toxicity of many heavy metals, and indirectly 

affect mercury cycling (e.g., Horne and Goldman 1994, Driscoll et al. 1994, Driscoll et al. 1995).

Table 1. Ion balance typical for fresh water in the upper 

Midwest (Wetzel 2001, Horne and Goldman 1994).

Cations Percent Anions Percent

Ca+2 63% HCO3

-

73%

Mg+2 17% SO4

-2

16%

Na+15% Cl10%

K

+

4%

other < 1% other < 1%
5

Bicarbonate and carbonate ions, which are estimated by alkalinity, dominate the major anions. 

Alkalinity directly estimates the majority of the buffering capacity of the water and is used to 

estimate sensitivity to acid precipitation. Sulfate concentrations provide a measure of the potential 

accumulation of sulfur due to acidic deposition of SOx compounds and are important for assessing 

acid deposition effects. Sulfate is also a critical parameter for understanding and modeling mercury 

cycling because sulfate-reducing bacteria in anoxic environments are the primary source of methyl 

mercury, the major fraction involved in the bioaccumulation of mercury in food webs (e.g., Driscoll 

et al. 1994). Chloride (Cl-) is a particularly good indicator of wastewater plumes as well as inputs and 

accumulation of road salt. It may be used as a tracer, as it moves through soil without significant 

absorption or adsorption.

The concentration of the major ions and their relative ratios influence the species of organisms that 

can best survive in a lake, in addition to affecting many important chemical reactions that occur in 

the water. Zebra mussels (Dreissena polymorpha), for example, require levels of calcium typically 

higher than those found in Lake Superior water, though this exotic species has invaded several inland 

lakes at SLBE. Humans can have profound influences on the characteristics of lake chemistry, 

including ion concentrations. Modification of natural shoreline vegetation and increasing the amount 

of impervious surfaces surrounding a lake cause increased runoff, which can carry chloride and 

potassium from the use of road salt.

1.2.8 Dissolved Silica (SiO2)

Silica is considered an essential micronutrient for microorganisms and diatom algae. These 

organisms use silica to form shells and other protective structures. Diatoms are capable of using large 

amounts of silica, and may be growth-limited when silica is in short supply. 

1.2.9 Dissolved Organic Carbon (DOC)

Dissolved organic carbon (DOC) is usually the largest fraction of organic material in the open waters 

of lakes. (Exceptions generally involve hypereutrophic lakes with intense blooms of algae or an 

abundance of aquatic plants that die off in the fall.) It is derived primarily from decomposing 

material in the watershed that is leached into stream and groundwater inputs and washed in from 

wetlands with abundant sphagnum mosses (Wetzel 2001, Schindler and Curtis 1997). Typically, a 

lesser amount is contributed by algae, both from extracellular leakage and via decomposition; 

concentrations may be high following intense algae blooms. DOC plays important roles in freshwater

ecosystems , including 1) affecting acid-base chemistry and metal cycling (e.g., copper, mercury, 

aluminum), and potential toxicity; 2) acting as a source of energy and nutrients to the microbial food 

chain, thereby influencing nutrient availability; 3) attenuating UV-B radiation; 4) attenuating PAR 

(photosynthetically active radiation) and thereby regulating primary production; and 5) influencing 

the heat budget of the lake by absorbing sunlight (Gergel et al. 1999, Schindler and Curtis 1997). 

Anthropogenic stressors, such as global warming, ozone losses, acidification, and intensive logging 

are cause for concern as they may be altering the concentration and distribution of DOC, resulting in 

adverse effects on lakes.
6

1.2.10 Nutrients (Total Phosphorus [TP], Total Nitrogen [TN], Nitrate+Nitrite-N [NO3+NO2-N], 

and Ammonium-N [NH4-N])

Nitrogen and phosphorus are the two most influential nutrients in terms of regulating phytoplankton 

and aquatic macrophyte growth. Excessive inputs of nutrients can lead to excessive algal growth and 

eutrophication (Wetzel 2001, Horne and Goldman 1994) and are the most important threat to Upper 

Midwest lakes (MPCA 2004a; MDEQ 2004; WDNR 2005). 

Nutrients are carried into a waterbody primarily through surface runoff and percolation through the 

surrounding rocks and soils. Bioavailable forms of phosphorus and nitrogen (dissolved phosphate, 

nitrate, and ammonium) are typically highest in the spring due to snowmelt runoff and the mixing of 

accumulated nutrients from the bottom during spring turnover. Concentrations typically decrease in 

the epilimnion during summer stratification, as nutrients are taken up by algae and eventually 

transported to the hypolimnion when the algae die and settle out. When stratified, any input of 

nutrients into the upper lake water may trigger a bloom of algae. In less productive systems, such as 

many of those in GLKN parks, significant amounts of available nitrogen may be deposited during 

rainfall or snowfall events (wet deposition) and through the less obvious deposition of aerosols and 

dust particles (dry deposition). Nitrogen and phosphorus in dry fallout and wet precipitation may 

come from dust, fine soil particles, and fertilizer from agricultural fields.

1.2.11 Chlorophyll-a 

The concentration of chlorophyll-a, the primary photosynthetic pigment in all green plants including 

phytoplankton, is a nearly universally accepted measure of algal biomass in the open waters of lakes 

(e.g., Wetzel 2001, Wetzel and Likens 2000). However, it may also be important to examine the algal 

community microscopically on occasion, because the mix of species can influence chlorophyll-a

concentration, as different algal groups have different proportions of chlorophyll-a versus other 

pigments. Hence, chlorophyll-a is not always an accurate measure of biomass, and the mix of species 

may influence lake management decisions. Chlorophyll-a concentrations are expected to be dynamic, 

reflecting changes in algal abundance through the ice-free growing season. Consistent and directional 

trends in chlorophyll-a concentrations are good indicators of change in a lake’s trophic status 

(Wetzel 2001, Carlson and Simpson 1996, Horne and Goldman 1994).

1.3 Background and History; Description of Resource

Several efforts have been undertaken in recent years to organize and synthesize aquatic resource data 

from GLKN parks. Most recently, Lafrancois and Glase (2005) published a summary and synthesis 

of information from over 600 studies. This synthesis will help guide management, future research, 

and monitoring efforts. The authors noted that much of the existing research in Great Lakes area 

parks was from short-term projects conducted by many different people without common methods or 

objectives, and that a comprehensive, network-wide analysis of the available information for use in 

identifying and addressing large-scale water resource issues had not been done previously. 

Ledder (2003, 2005) summarized relevant numeric water quality standards in addition to compiling 

lists of designated uses for parameters of interest to the water quality monitoring project. Her 
7

summaries included relevant water quality criteria, waterbodies that are listed under section 303(d) of 

the Clean Water Act, and waterbodies with Outstanding Resource Waters designation. 

Historical water quality data for inland lakes of the parks consist of lake profile data (temperature, 

dissolved oxygen, specific conductivity, pH, and Secchi depth) as well as various other physical, 

chemical, and biological (chlorophyll-a) parameters (Table 2). See Lafrancois and Glase (2005) for a 

more complete listing of aquatic research and monitoring efforts in GLKN park units. The Natural 

Resources Research Institute (NRRI) at the University of Minnesota–Duluth analyzed water quality 

data collected between 1997 and 2003 from lakes at SLBE, PIRO, and APIS (Axler et al. 2006). 

Other in-depth analyses of water quality data at ISRO and VOYA have been published recently 

(Kallemeyn et al. 2003, Kallemeyn 2000).

The National Park Service–Water Resources Division (NPS-WRD) retrieved data from several EPA 

databases, including STOrage and RETrieval System (STORET), and summarized these data for 

national park units (NPS 1999 [APIS], 1997 [SLBE], 1995a [ISRO], 1995b [PIRO], 1995c [VOYA], 

1994 [INDU]). Summaries include exceedance data, by station.

1.3.1 Water Quality Monitoring Efforts by Parks

Water quality monitoring programs conducted by the parks vary widely, and in most parks, have 

changed over time. Park funding and turnover of personnel have fluctuated, and the parks are not 

always able to continue monitoring programs on schedule. A brief synopsis of park water quality 

monitoring programs follows.

Until 1988, water quality studies at APIS were largely synoptic rather than routine monitoring 

efforts. At that time, Michigan Technical University established a monitoring program that the park 

has attempted to continue, conducting routine monitoring with a multi-parameter sonde every two to 

three years at five sites in Lake Superior and in three lagoons. More intensive physical, chemical, and 

biological monitoring was conducted by different research groups at the same sites in 1996 and 2004.

Table 2. Summary of water quality data available for inland lakes at Great Lakes Network parks.

Park Source

Period of 

Record Water Quality Parameters (Lakes)

VOYA Kallemeyn et al.

(2003)

2003 chlorophyll and TP (Rainy, Sand Pt, Namakan, Kabetogama)

NRRI CAL 2002 chlorophyll and TP (Rainy, Sand Pt, Namakan, Kabetogama)

Hargis (1981) 1978–1980 core suite, chlorophyll, % light transmittance (Rainy, Sand Pt., 

Namakan, Kabetogama, Ek 1978–1980; 19 interior 

lakes1979–1980)

Payne (1991) 1977–2000 chlorophyll, Secchi, TN, TP, alkalinity, cations, anions (Rainy, 

Sand Pt., Namakan, Kabetogama, 19 interior, 2 streams); 

USGS & NPS

Payne (2000) 1999 Rainy, Sand Pt., Namakan, Kabetogama

VOYA/USGS 1981/83 1981 Namakan and Kabetogama, 1983 Rainy and Sand Pt. 

11xs/summer, 26 interior lakes at least once

Kepner (1988) NA (Rainy, Sand Pt., Namakan, Kabetogama)

MPCA 2000 (12 lakes)
8

Table 2. Summary of water quality data available for inland lakes at Great Lakes Network parks

(continued).

Park Source

Period of 

Record Water Quality Parameters (Lakes)

Eibler (2001) 1983–2000 chlorophyll, Secchi, alkalinity (Kabetogama, Rainy, maybe 

Namakan and Sand Pt.); MNDNR; 1x/summer

Newell (1987)

Webster (1995)

1978–1995 USEPA-LTM; (Cruiser, Loiten, Locator, Shoepack)

Whitman (2001) 1997–1998 chlorophyll, pH, ANC, SO4 (Locator and Mukooda)

INDU NPS 1990–2000 alkalinity, NH4, Cl, SC25, dissolved oxygen, NO3, NO2, pH, 

TP, hardness, turbidity

Arihood (1975) 1973–1974 chemical, organic, bacteriological; ground and surface waters

Hardy (1983) 1978–1980 core suite, periphyton, bacteriological

Whitman et al. 

(1995)

1991 core suite, bacteriological

Simon et al. (1997) pH, conductivity. major ions, nutrients, morphometry; (4 lakes)

ISRO NRRI CAL 1996 Secchi, core suite, chlorophyll, nutrients, major ions

1997 SC25, DOC, color- 32 lakes

Stottlemeyer (2000) 1980–1996

Kallemeyn (2000) 1995–1997 summarized data, core and advanced

Gorski (2002) 1998–1999 DOC and Hg

PIRO Handy and Twenter 

(1985)

1979–1981 once/year (Chapel, Beaver, Kingston, Grand Sable), temp, 

SC25, pH, and advanced suite

Loope (1998) review of six inland lakes

Kamke (1987) 4 lakes (Chapel, Beaver, Kingston, Grand Sable)

PIRO (1998)

1970–2002, 

intermittent

lake profiles (core parameters) and field notes

only 1998 and 1999 multiple/year, the rest once/year

APIS Balcer and

McCauley (1989) 1986–1989 fecal bacteria, nutrients, sediment composition, core suite (Lake Superior, lagoons)

Rose (1988) 1983 USGS–Outer Island Lagoon; 2x/summer; core suite, anion, 

cations, nutrients

Rose (1988) 1984 USGS–Michigan Island Lagoon; 2x/summer; core suite, anion, 

cations, nutrients

MTU (1997) 1996 Michigan, Outer, Stockton Islands Lagoons; core suite, 

chlorophyll, nutrients, zooplankton, benthos; June, July, Aug.

Axler et al. (2006) 2005 Michigan, Outer, Stockton Islands Lagoons; core suite, 

chlorophyll, nutrients, zooplankton, benthos; June, Aug., Oct.

SLBE SLBE 1997–2003 Secchi, profiles, water chemistry

Murphy (2001, 2002) 2000–2002 core suite, turbidity, nutrients, major ions; inland lakes and 

rivers

Last et al. (1995) 1994–1995 core suite, chlorophyll-a

Notes: NRRI-CAL = Natural Resources Research Institute Central Analytical Laboratory; MPCA = Minnesota 

Pollution Control Agency.

Intensive and extensive water quality studies have been conducted at INDU over the years 

(Lafrancois and Glase 2005). Researchers often focused on contaminants from industrial waste, 

although basic water quality parameters were also measured. From 1990 through 2000, the park 

monitored alkalinity, ammonium, chloride, specific conductance, dissolved oxygen, nitrate, nitrite, 
9

pH, total phosphorus, hardness, and turbidity of Long Lake. The park conducts routine 

bacteriological monitoring at Lake Michigan beach sites.

Two long-term water quality monitoring projects have occurred at ISRO––one at the Washington 

Creek gaging station, and the other a study of the Wallace Lake watershed. A number of additional 

inland lakes have been studied intensively for short periods of time, although no long-term water 

quality monitoring has been conducted on ISRO’s inland lakes.

Most of the inland lakes at PIRO have been sampled at least once, with few lakes receiving greater 

attention in the form of synoptic studies. Beginning in 1994, annual data were collected, once in midsummer, on six lakes with a multi-parameter sonde. For the first three years (1994–1996), nitrate, 

phosphate, and chlorophyll-a were also measured. 

Prior to 2001, most water quality sampling at SLBE was conducted as part of synoptic studies to 

address particular concerns in a given lake or stream (e.g., nutrient loading downstream from a fish 

hatchery). However, park staff have conducted water quality monitoring routinely in most lakes of 

the park since 2001. Parameters typically measured were Secchi depth; profiles of temperature, 

dissolved oxygen, specific conductance, and pH; and less routinely, total dissolved solids, sulfate, 

calcium hardness, total hardness, total nitrogen, total phosphorus, nitrate, ammonium, alkalinity, true 

color, and chlorophyll-a. Bacteriological monitoring is also conducted weekly at beach sites from 

mid-May through mid-September. 

The four large, regulated lakes at VOYA have been monitored for the past 25 years, every two weeks 

from May until October. Parameters measured in this program are temperature and dissolved oxygen 

profiles, alkalinity, pH, conductivity, and Secchi depth. Chlorophyll-a has also been measured on 

these lakes since 2000. Inland lakes of the park have not received the same continuous monitoring 

effort, though many intensive project-based studies have been conducted. Kallemeyn et al. (2003) 

analyzed and summarized historical water quality data of inland lakes.

1.3.2 Description of Parks’ Inland Lakes 

The inland lake resources of GLKN parks are astounding, numbering in the thousands. Lakes greater 

than one hectare number in the hundreds, with VOYA, alone, containing nearly 300 (Table 3).

The water chemistry of inland lakes varies widely across the Network. Lakes in SLBE are underlain 

by limestone, and hence have relatively high pH values (most lakes >8.0), high buffering capacity 

(alkalinity of most lakes >125 mg/L), and high conductivity values (many lakes SC25>300 μS/cm). 

Pictured Rocks National Lakeshore contains a meromictic lake (Chapel Lake), >42 m deep, and a 

naturally acidic lake (Legion Lake), with pH values generally <5.0 and alkalinity near zero (Loope 

1998). Some lakes at VOYA are underlain by granitic bedrock of the Canadian Shield, while others
10

Table 3. Number of lakes >1 hectare in six Great Lakes Network parks. Number of 

inland lakes between 1 and 10 hectares in parentheses. Data from the National 

Hydrologic Database.

Park 

Number of Inland Lakes

>1 Hectare (1–10 ha)

Apostle Islands National Lakeshore 11 (10)

Indiana Dunes National Lakeshore 8 (8)

Isle Royale National Park 77 (59)

Pictured Rocks National Lakeshore 24 (10)

Sleeping Bear Dunes National Lakeshore 24 (7)

Voyageurs National Park 299 (268)

are underlain by thick calcareous drift. The differences in water chemistry within this park are great; 

some lakes are poorly buffered, some are well-buffered, some have noxious blooms of blue-green 

algae, and some are oligotrophic (Kallemeyn et al. 2003).

Accessibility of lakes also varies across the Network, which affects the types of stressors influencing 

the lakes’ water quality. Many park lakes require substantial time and effort to gain access. For 

example, Lake Manitou (SLBE) requires a boat ride across Lake Michigan waters and then a portage 

of approximately 4 km (2.5 mi); Lake Desor (ISRO) requires approximately an hour of boat 

transportation on Lake Superior followed by a steep off-trail bushwhack portage of approximately 

1.6 km (1 mi). Lakes such as these receive little recreational pressure and no developmental effects. 

The primary stressors are likely due to atmospheric deposition and global climate change. The large 

lakes at VOYA receive house-boat use, and are therefore at risk from inputs of excess nutrients from 

gray water discharge and failing sewage holding tanks. Many lakes within the Network are located 

alongside of roads, accessed via boat ramps, and contain developed areas of shoreline. These lakes 

are affected by stressors such as road salt, runoff, oil and gas, failing septic tanks, invasive species, as 

well as the same atmospheric threats that face remote lakes.

With this monitoring protocol, we hope to encompass the variety of existing lake conditions and 

stressors affecting the lakes. The sampling design and methods of field sampling are described in the 

following sections (2.0 Sample Design, and 3.0 Field Methods).

1.4 Measurable Objectives

Our overall goal is to develop a program for monitoring water quality in inland lakes that will 

contribute to an understanding of the health of aquatic ecosystems and provide insights on likely 

water resources issues in park units of the Great Lakes Network. 

Our specific objective is to monitor basic limnological parameters that describe water quality of 

select inland lakes in order to describe the current status and trends (i.e., magnitude and direction of 
11

change) of these lakes. We will examine parallel trends across lakes within park units and across the 

Network as a whole, and compare our results with other regional datasets.

1.5 Quality Assurance and Quality Control

Quality control is the planned and systematic pattern of all actions, or controls, necessary to provide 

adequate confidence that a project outcome optimally fulfills expectations. Quality assurance is a 

program for the systematic monitoring and evaluation of the various aspects of a project to ensure 

that standards of quality are being met. Together, quality assurance/quality control (QA/QC) is a 

significant part of any monitoring program. It is a broad management concept of maintaining the 

ability to provide reliable information, requiring the complete integration of field and laboratory 

systems of sample collection and analysis. QA/QC incorporates peripheral but essential operations 

such as survey design, equipment preparation, maintenance tasks, data handling, and personnel 

training. The objective of QA/QC is to ensure that the data generated by a project are meaningful, 

representative, complete, precise, accurate, comparable, and scientifically defensible (O’Ney 2005a). 

This protocol includes QA/QC procedures that must be followed, beginning with field preparations, 

through the collection of data, to the final analyses and reporting of results. See standard operating 

procedure (SOP) #12 for QA/QC details.

13

2.0 Sample Design

2.1 Rationale for Selecting This Sampling Design

As we developed our sampling design, we explored the advantages and disadvantages of randomly 

selecting lakes for monitoring versus a nonrandom selection of lakes. We also considered the 

sampling designs of Minnesota, Wisconsin, and Michigan - three of the four states in which Network 

parks are located. These three states have the greatest numbers of lakes of the lower 48 states, and all 

three have active water quality monitoring programs. 

In the following paragraphs, we describe random, or probabilistic, and nonrandom, or targeted, 

selection of lakes for monitoring; we summarize the water quality monitoring programs of the three 

states; and we explain our design for discrete and continuous long-term monitoring of water quality 

of inland lakes in the Great Lakes Network.

2.1.1 Random Versus Nonrandom Selection of Lakes

Historically, monitoring programs for lakes have focused on either representative lakes or on specific 

lakes of particular interest. Examples of lakes selected for particular reasons include:

 Lakes with outstanding resource value––for example, the Lake Tahoe, California-Nevada 

program (Goldman 1988, Jassby et al. 2003), Lake Michigan (Madenjian et al. 2002), Crater 

Lake, Oregon (LaBounty and Larson 1996); 

 Lakes representative of a class of lake types, for example, meso-oligotrophic (e.g., Castle 

Lake, California; Jassby et al. 1999, Goldman et al. 1989), eutrophic (Clear Lake, California; 

Suchanek et al. 2002), acid-sensitive Canadian shield lakes (Schindler et al. 1985, Schindler 

1988);

 Lakes within a geographic area, for example, lakes and reservoirs of the southeastern U.S. 

(Reckhow 1988), lakes of the northeastern United States (Messer et al. 1991), long-term 

ecological research of North Temperate Lakes (Magnuson et al. 2006, Magnuson et al. 1984), 

recreational lakes in Vermont (Smeltzer et al. 1989);

 Economically important lakes under heavy anthropogenic stress, for example, Lake Mendota, 

Wisconsin (Lathrop et al. 1996); Lake Washington, Washington (Edmonson et al. 1956); 

Lake Okechobee, Florida (Steinman et al. 2001); Lake Minnetonka, Minnesota (Barten 

2004); Lake Mead, Nevada-Arizona (Paulson and Baker 1983, LaBounty and Horn 1997); 

Lake Tahoe, California-Nevada (Jassby et al. 1999).

Such nonrandom selection of lakes in a monitoring program allows results to be used in answering 

specific questions about a particular lake or suite of lakes. The main disadvantage of this design, 

however, is that inferences cannot be extended to lakes beyond those that are sampled. 

Beginning with concerns about the potential degradation of softwater lakes throughout the U.S. due 

to acidic deposition, the U.S. Environmental Protection Agency (EPA) initiated the development of a 

framework for probabilistic design and sampling. The approach has now moved beyond the acid-rain 
14

question to provide an approach that allows quantitative (i.e., with known statistical confidence) 

descriptions of aquatic resources. 

A probabilistic, randomized sampling scheme is particularly well suited to examining large 

populations of lakes, to groups of lakes that have little prior information, and where one wishes to 

characterize populations or groups with a particular degree of statistical confidence. The advantage 

of a random design is that probabilistic statements can be made about differences in means. This 

ability to make statistical inferences to a large population of lakes from a relatively small number that 

are actually sampled makes the randomized method appear preferable because a comparison between 

groups of lakes or a trend over time can be justified with confidence limits. An important 

disadvantage of the randomized design is that in order to make useful probabilistic statements about 

responses in a larger population of lakes within a few years, the number of lakes in the sampling 

program must be relatively large (20% to 30% of the total population of lakes; e.g., Loeb 2002). 

2.1.2 Current Lake-Monitoring Programs of States Within the Great Lakes Region

It is important that GLKN develops a program for monitoring water quality that is comparable with 

and acceptable to other regional monitoring programs, especially the states. Monitoring programs in 

Minnesota, Wisconsin, and Michigan have been in existence for many years, and all three have 

undergone changes in the past few years to enable the states to more efficiently comply with their 

assessment and reporting responsibilities for the federal Clean Water Act (see 

http://www.pca.state.mn.us/publications/reports/strategicplan.html for Minnesota, 

http://www.dnr.state.wi.us/org/water/MonitoringStrategy.pdf for Wisconsin, and 

http://www.michigan.gov/deq/0,1607,7-135-3313_3686_3731---,00.html for Michigan). 

The three state programs use different strategies in their attempt to maximize the efficiency of their 

monitoring and assessment programs, although all are fundamentally similar in that a set of sentinel 

or index lakes is sampled on a regular basis. Index lakes were selected nonrandomly, for different 

reasons among states. In brief, all three states involve volunteers to monitor Secchi depth, which is an 

established indicator of either algal biomass or suspended sediment (Carlson and Simpson 1996). All 

three states are also developing additional volunteer programs to collect water samples for 

chlorophyll-a and/or nutrients. 

In Minnesota, the DNR samples all large lakes (>200 ha) on a 10-year cycle. Volunteers collect 

Secchi depth data on medium-sized lakes (40–200 ha). In addition, the Minnesota Pollution Control 

Agency (MPCA) conducts more intensive seasonal diagnostic studies at an unspecified number of 

lakes, based on need as indicated by either Secchi data or Landsat 7 satellite imagery (Kloiber et al. 

2002a, 2002b). Wisconsin DNR monitors 65 index lakes and 110 randomly selected lakes (without 

replacement) annually, on a six year rotation (WDNR 2005). In addition, volunteers measure Secchi 

depth on approximately 600 lakes. This volunteer program includes collection of water samples for 

nutrients and chlorophyll-a on a subset of lakes. Michigan’s program is similar to Wisconsin’s in that 

it includes both index and randomly-selected lakes, but uses a 15 year rotation. Michigan volunteers 

monitor Secchi depth, total phosphorus, and chloroplyll-a on more than 300 lakes. 
15

Wisconsin and Michigan are collaborating with Minnesota regarding the use of satellite imagery to 

supplement the transparency database. This technique has the potential to generate historical Secchi 

estimates, because past images and their spectral data are potentially available. In the future, the 

Network may find it useful to participate in this satellite imaging analysis of Secchi transparency to 

supplement lake data in remote areas.

2.1.3 Great Lakes Network Design

The Network examined the monitoring programs of the three states and weighed the advantages and 

disadvantages of different sampling designs. A summary of several sampling designs is included in 

Table 4. Consistency of the Network’s monitoring design and protocol with neighboring state 

programs is desirable to facilitate data comparisons and allow statistical inferences using regional 

data. 

The selection of lakes to include in the GLKN monitoring program must be based on the questions of 

interest, without jeopardizing the safety of field personnel. Development of detailed monitoring 

questions was an important initial phase that preceded the identification of target populations and 

subsequent development of sample designs. Question development was an iterative process with 

input from park managers, GLKN staff, and cooperating scientists. Our monitoring questions relate 

to individual lakes, lakes aggregated within each park, and lakes across the Network and region. As 

we began to develop the protocol, it became clear that we would not be able to address the questions 

regarding the general health of the lakes in a park or across parks in a statistically adequate manner 

while staying within our budget. Answering questions about all lakes within a park or all lakes across 

the Network requires either a complete census of lakes or a random selection of lakes, which allows 

inference to the population of lakes as a whole. A complete census of lakes is not feasible, as the 

Network contains well over 1,000 lakes (Table 5). A random selection of lakes is not desirable 

because many lakes are inaccessible and would require more than a day of off-trail, backcountry 

travel to reach. 

This realization led to the design that will best provide for assessments of individual lakes. We will 

address questions at broader spatial extents through comparisons of trends across lakes. (See section 

4, below––Data Management, Analysis, and Reporting, and SOP #9––Data Analysis, for more 

details).

We selected lakes at each park such that they are spatially distributed throughout each park and span 

gradients of chemical and physical parameters, visitor use, and watershed area. Some lakes are of 

particular interest to a park. If lakes are connected via stream or channel, we selected the downstream 

lake, as it serves as an integrator of its drainage system. The lakes included in the sampling design 

(Table 6), referred to as “index lakes,” will be sampled annually. Additional lakes will be sampled on 

a longer rotation at some parks as funding permits.

Continuous water temperature profile data will be collected from a subset of index lakes across four 

parks (ISRO, PIRO, SLBE and VOYA) with a significant number of inland lakes >1 ha (Table 6). 

This monitoring will address specific park management questions such as availability of suitable 
16

habitat to support cold-water fisheries, or to assess regional trends in the timing of ice on and ice off 

and other climate change driven phenomena.
17

Table 4. Summary of different types of sampling designs.

Parameter Random Stratified Systematic Non-random

Lake Sampled lakes are 

chosen randomly from 

geographic area

Randomly chosen from each 

geographic region (state, county, 

ecoregion) or within some other 

classification e.g., (recreational, 

beneficial use, drainage type, trophic 

status, surface area, max. depth)

Sample every lake along a 

transect, using a randomly chosen 

transect starting point

Choose lake based on convenience, 

access, proximity, or interest

Site Randomly chosen 

from within the lake 

area

Randomly selected from within 

regions of lake

Sample at equidistant sites along 

transect of lake (distance selected 

a priori), starting with a randomly 

chosen point

Sample at the dam, over the deepest 

part of the lake, or other location based 

on interest

Depth Randomly chosen Randomly chosen within each depth 

region (e.g., epilimnion, hypolimnion, 

photic zone)

Sample at preset intervals, starting 

with a randomly chosen depth

Sample at the surface, at preset 

intervals surface to bottom, or at 

discreet depth for particular interest

Date Randomly chosen Randomly chosen within each 

season, month, or limnological period

Sample every two weeks, starting 

with a randomly chosen date

Sample on chosen day for reasons of 

convenience

Time Randomly chosen Randomly chosen within each diel 

period (e.g., morning, afternoon, 

evening), or some other division of 

day

Sample every two hours, starting 

with a randomly chosen time

Sample times based on convenience
18

Table 5. Summary of numbers of lakes and ponds in the six 

Great Lakes Network parks with inland lake resources, 

classified by size (surface area).

Park Size class (ha)

Named 

Lakes

Unnamed 

Lakes

TOTAL

>1 ha

APIS >1000 -- --

100–1000 -- --

10–100 1 --

1–10 2 7 10

<1 1 65

Total 76

INDU >1000 -- --

100–1000 -- --

10–100 -- --

1–10 2 7 9

<1 -- 49

Total 1 56

ISRO >1000 -- --

100–1000 5 --

10–100 22 --

1–10 15 45 87

<1 -- 189

Total 42 234

PIRO >1000 -- --

100–1000 2 --

10–100 5 --

1–10 7 10 24

<1 2 96

Total 16 106

SLBE >1000 1 --

100–1000 3 --

10–100 11 2

1–10 6 1 24

<1 6 3

Total 27 6

VOYA >1000 4 --

100–1000 3 1

10–100 19 8

1–10 3 265 299

<1 -- 237

Total 29 511
19

Table 6. Index lakes in the Great Lakes Network’s sampling design. 

Maximum depth (Zmax) is included when known. Thermal arrays are 

deployed at lakes shown in bold font.

Park Lake Name Area (ha) Z max (m)

APIS Outer Island Lagoon 22 1.7

Total 1

INDU Middle Calumet Lagoon 32 3.0

Total 1

ISRO Siskiwit 1635 46

Desor 428 14

Richie 216 11

Feldtmann 186 3

Sargent 143 14

Harvey 55 4

Beaver 20 5

Ahmik 10 3

George 3.8 3

Total 9

PIRO Beaver 310 10

Grand Sable 255 26

Chapel 28 42

Trappers 20 2

Legion 14 10

Miners 5 4

Total 6

SLBE Manitou 104 14

Florence 32 8

Shell 41 4

Bass (Leelanau County) 38 7

Loon 37 20

North Bar 12 10

Total 6

VOYA Shoepack 124 7

Little Trout 97 29

Locator 57 16

Cruiser 47 28

Peary 45 5

Ek 36 6

Brown 31 8

Ryan 14 4

Total 8

Apostle Islands National Lakeshore––Outer Lagoon is included in the sampling design. There are 

two other island lagoons and one mainland site that were monitored by GLKN from 2007–2012, but 

they are periodically connected to and flushed by Lake Superior. This connection creates high inter 

and intra-variability in water quality, and is exceedingly problematic when assessing long term 

trends. Outer lagoon is shallow and may not always meet the EPA criterion of a lake (>1m in depth; 

Baker et al. 1997), depending primarily on Lake Superior water level, but is of particular interest to 

the park because of recent evidence of high mercury levels throughout the food chain (J. Wiener, 
20

pers. comm.), and to park partners due to the presence of a rare diatom species (Semiorbis 

hemicyclus) not found in any other lakes monitored in the Network (M. Edland, pers. comm). Outer 

Lagoon, and the two lagoons and mainland site previously monitored essentially comprise the park’s 

inland lakes, as the remaining lentic waterbodies are transient beaver ponds.

Indiana Dunes National Lakeshore––Middle Calumet Lagoon is an interdunal lagoon and the only 

lake included in the sampling design. Lake George, a relatively recently constructed lake, was 

sampled in 2006, but was deemed unsuitable because it is more of a lotic than lentic environment. 

Long Lake, which is shallow and polymictic, was monitored from 2006 to 2012. However, 

monitoring was discontinued in 2013 due to lowering water levels, which is causing the lake to 

transition to a wetland marsh. Additional interdunal lagoons may be added to the sampling design in 

the future, depending on preliminary sampling results, budget, and interest to the park.

Isle Royale National Park––We ordinated historical lake chemistry data (nonmetric 

multidimensional scaling via PCORD; McCune and Mefford 1999) and compared our results with 

those of Carlisle (2000; in Crane et al. 2006), who used both chemical and physical data, to 

determine types of lakes on the island. We then selected nine lakes, some from each quadrant of the 

ordination plots, ensuring they spanned the spatial extent of the island. The lakes also spanned

gradients of recreational use, surface area, depth, and watershed area. The number of lakes selected is 

restricted largely by budget. Continuous (1-hour intervals) year round surface to bottom (1-meter 

intervals) water temperature data (referred to as a thermal array hereon) will be collected from Lake 

Richie at the same site where discrete monitoring will take place. This water temperature data will 

help to address park management concerns about availability of suitable habitat for cisco (Coregonus 

artedi), which historically was present in the lake but has not been documented since 1929 (Hubbs 

and Lagler 1949). As the park has concerns that water quality sampling may disrupt successful 

nesting of common loons (Gavia immer), an endangered species in Michigan, we will work with park 

staff to ensure water quality sampling personnel are trained in recognizing loon behaviors and avoid 

undue stress on nesting loons. In future years, additional lakes may be sampled on a rotational basis 

as funding permits. 

Pictured Rocks National Lakeshore––Six lakes are included in the sampling design, spanning the 

spatial extent of the park. The selected lakes span gradients of surface area, depth, watershed area, 

and recreational use. If two or more lakes are connected (e.g., Beaver and Little Beaver lakes), we 

selected the downstream lake as an integrator of that system. A thermal array will be deployed at 

Grand Sable Lake at our discrete monitoring site. Water temperature data from this array will allow 

for assessment of suitable habitat for salmonids (historically stocked in the lake but not in recent 

years) and help to answer basic limnological questions related to changes in the timing of ice on/off, 

depth, timing, and strength of thermal stratification. Additional lakes beyond the six index lakes may 

be sampled on a rotational basis, as time and funding permits. No lakes in the Inland Buffer Zone are 

included, nor were they considered, because the park does not own the land surrounding them. The 

Network will explore the possibility of sharing data with partners conducting monitoring of lakes in 

the Inland Buffer Zone. 
21

Sleeping Bear Dunes National Lakeshore––Six lakes were selected as index lakes, based primarily 

on results of ordinations of past lake chemistry data (as described above for Isle Royale National 

Park). The lakes span the spatial extent of the park, as well as distance from roads and gradients of 

recreational use, surface area, and depth (watershed size is currently not known). A thermal array 

will be deployed in Manitou Lake at our discrete monitoring site. Data from this array will be used to 

answer limnological questions related to changes in the timing of ice on/off, depth, timing, the and 

strength of thermal stratification, and will be compared with climatological data collected by a 

nearby weather station operated and maintained by the Network. Lakes that are partially within park 

boundaries but are actively monitored by other organizations were not considered so as to avoid 

duplication of effort. We will share data and expertise with these other organizations. Additional 

lakes beyond the index lakes may be sampled on a rotational basis, as funding permits. 

Voyageurs National Park––Eight lakes were selected as index lakes based largely on a classification 

of lakes (Schupp 1992). The lakes have a long history of data collection, span a gradient of 

recreational pressure, and are spatially dispersed across the park. We selected downstream lakes 

when one or more are connected via surface stream or channel. A thermal array will be deployed at 

Little Trout Lake at our discrete monitoring site. This water temperature data will help to address 

park management concerns about availability of suitable habitat for lake trout (Salvelinus 

namaycush). The population of lake trout has been in decline recently (MNDNR 2010) and no lake 

trout were found during a 2014 survey by the Minnesota Department of Natural Resources staff in 

2014 (R. Maki, pers. comm.).Water quality monitoring at the four large lakes (Namakan, Rainy, 

Sand Point, and Kabetogama) is currently base-funded by the park. Staff at VOYA conduct water 

quality monitoring of these lakes annually, twice a month, using methods comparable to those 

employed by Network staff. Therefore, the Network excluded these lakes from the design. In 2006, 

we sampled 22 inland lakes (excluding the four large lakes), and hope to sample all of these lakes, 

beyond the index lakes, on a rotational basis

In summary, we will monitor the index lakes shown in Table 6 on an annual basis. Additional lakes 

will be sampled on a longer rotation as funding permits.

2.1.4 Legal Designations of Lakes Within the Great Lakes Network

All of the inland lakes in INDU, ISRO, PIRO, SLBE, and VOYA are designated as Outstanding 

Natural Resource Waters by their respective states. Many of these same lakes, however, are listed as 

impaired under section 303(d) of the Clean Water Act (CWA). All lakes in ISRO, PIRO, SLBE, and 

most lakes in VOYA are listed due to fish consumption advisories for mercury (NPS 2005, MDCH 

2004, MPCA 2006). Additionally, Siskiwit Lake (ISRO) is listed due to fish consumption advisories 

for PCBs (NPS 2005). Little Sand Bay and Julian Bay (APIS) are intermittently connected to Lake 

Superior; when connected to the Great Lake, these lagoons are included on the 303(d) list for fish 

consumption advisories for PCBs (NPS 2005). 

NPS-WRD has advised that newly-developed monitoring protocols include the water quality 

variables that have caused resource waters to be designated as impaired on the 303(d) list (Irwin 

2008). GLKN has monitoring protocols for bioaccumulative contaminants, focused on bald eagles 

(Haliaeetus leucocephalus) (Route et al. 2009) and mercury in fish or other aquatic organisms 
22

(Wiener et al. 2009). We expect to monitor inland lakes in the Network through these protocols on 

bioaccumulation.

2.2 Frequency of Sampling 

For discrete monitoring a trade-off exists between the number of lakes sampled within a given year 

and the number of repeat visits made within a year. The same trade-off exists for continuous 

monitoring as periodic site visits are necessary to maintain, calibrate, and download data from 

sensors (i.e., thermal arrays). Variability of lake characteristics within a season is often high and may 

be comparable to the variability between years for some parameters, even for pristine lakes with no 

apparent long-term trends (e.g., Goldman et al. 1989).

Because of this seasonal variability, for discrete monitoring most state water quality programs collect 

data several times during the ice-free season, which usually extends from approximately May 

through October in the upper Midwest. Frequently collected data aid in understanding important 

issues, such as the onset of blooms of noxious algae and temporal patterns in temperature and 

dissolved oxygen.

Studies of annual and seasonal means of chlorophyll and total phosphorus concentrations in north 

temperate lakes spanning a range of trophic states (Hanna and Peters 1991, Marshall et al. 1988, 

Marshall and Peters 1989) led to the following conclusions:

 Sampling a single site per lake each visit was adequate to detect intra- or interannual trends; 

relatively little overall precision was gained by sampling multiple sites within a lake.

 Several visits within a year or within the open water season were required to characterize 

annual water quality as indicated by chlorophyll-a. Three to seven observations produced a 

coefficient of variation of 20% in oligotrophic lakes; 10 visits were needed for the same 

precision in more productive lakes.

 Differences between surface sampling and integrated euphotic-zone sampling were relatively 

small (also supported by Knowlton and Jones [1989]). (In the GLKN region, only Michigan 

uses the euphotic zone sampling scheme and only for chlorophyll-a.)

 Sampling effort should be directed to more visits over the course of a season rather than 

increasing replication on a sampling date, given that characterizing seasonal or annual means 

is the goal. 

Analyses of Vermont’s Lay Monitoring Program data for total phosphorus (TP), chlorophyll-a, and 

Secchi depth (Smeltzer et al. 1989) showed Secchi depth had the lowest variance of the three 

measures and therefore provided the most powerful ability to detect change over time. Chlorophyll-a

was the most variable and TP was intermediate. The coefficient of variation (CV) of the long-term 

mean declined as a function of number of samples per year and the number of years of sampling for 

each variable, however increasing the sampling frequency beyond approximately four times per year 

yielded diminishing returns. Smeltzer et al. (1989) also found that 10 years of TP or chlorophyll-a

data would not provide a sufficiently precise baseline against which a 20% change could be 
23

statistically detected (t-test, p<0.05 with a power of 80%) (Figure 1). A 10-year baseline of Secchi 

data, collected once or twice a month, would permit a future 20% change to be detected (Figure 2). 

Larger changes (e.g., 40%) would be detectable for all three variables, after collection of 10 years of 

monitoring data. 

Analysis of Minnesota Secchi data from many sets of lake data yielded a similar result to Vermont’s 

(Heiskary and Lindbloom 1993). Ten years of monthly Secchi data will allow detection of a change 

of 20% for a given year from the 10-year baseline when ά = 0.10 and power (1-β) = 0.90 (MPCA 

2005a, 2005b). It is reasonable to expect somewhat less detectable trends in TP and chlorophyll-a, 

based on Minnesota’s climatic similarities with Vermont and a similar abundance of glacial lakes in 

coniferous and mixed hardwood/coniferous watersheds, although detection levels cannot be precisely 

verified at this time. 

Analyses of select data sets from Pictured Rocks and Sleeping Bear Dunes national lakeshores shows 

a wide range in the amount of time required to detect change in dissolved oxygen (G. Host, 

unpublished data). One can expect to detect a trend in percent saturation of dissolved oxygen in 

defined depth strata after four to 19 sampling years (Table 7).

Figure 1. Trend analysis of long-term monitoring of total phosphorus in summer (Smeltzer et al. 1989).

0

10

20

30

40

50

60

70

80

90

100

1 2 3 4 5 6 7 8 9 10 100

Years of Monitoring

Power %

Annual

Bimonthly

Monthly

2x/mo

Weekly

2x/wk
24

Figure 2. Trend analysis of long-term monitoring of Secchi depth in summer (Smeltzer et al. 1989).

Table 7. Number of years required to detect a change in dissolved oxygen (DO) 

saturation in different Great Lakes Network lakes and depth strata. Calculations 

assume ά = 0.1, power (1 - β) = 0.80, rate of change = 20%, and sampling frequency 

of three times during the open water season. CV = coefficient of variation.

Lake (Park) Depth Stratum (m) Mean (% DO) CV # Years

Florence (SLBE) 1-3 96.8 0.051 4

Manitou (SLBE) 1-3 95.3 0.072 5

Manitou (SLBE) 6-7 87.8 0.065 5

Chapel (PIRO) 6-7 7.86 0.455 19

Sampling frequency requires a pragmatic compromise among statistical rigor, logistics, and cost. For 

our discrete monitoring the Network will visit each sampling lake three times during the open water 

season when lakes are likely to be stratified. Analyses of existing data, such as those described 

above, help us understand the limitations of our sampling design. We do not expect to be able to 

detect changes in most variables after only a few sampling years, and realize that it make take many 

years to detect changes in some highly variable parameters. Given our sampling frequency, we 

expect even the least variable parameter to require more than 10 years of monitoring data before we 

will be able to detect a 20% change with 80% power.

0

10

20

30

40

50

60

70

80

90

100

1 2 3 4 5 6 7 8 9 10 100

Years of Monitoring

Power %

Annual

Bimonthly

Monthly

2x/mo

Weekly

2x/wk
25

2.3 Location of Sites

A single sampling site, typically located in the deepest part of the lake, will be the routine location 

for measuring all water quality variables. Thermal arrays will be deployed at the same locations as 

the discrete sampling sites in lakes where both monitoring activities take place. Sampling the deepest 

part of the lake allows sampling every possible depth to the bottom, and has a long history in 

limnology. Except for shallow lakes, this type of sampling ignores the littoral zone and always avoids 

the nearshore zone, as well as embayments and other features related to morphometry. In reservoirs, 

or in some lakes in which water levels are partially controlled, spatial variation across the length of 

the system, from inlet to outlet, typically forms major physical, chemical, and biological gradients 

that are important for understanding and managing the system (e.g., Wetzel 2001). Because the 

Network will not be sampling any large reservoirs, this spatial heterogeneity is not an issue for 

characterizing overall trends over time. Hanna and Peters (1991) have shown that a single sampling 

site per lake is adequate to characterize phosphorus and chlorophyll concentrations, given that each 

site is visited several times within a season.

2.4 Depths of Sampling

The depths of sampling for laboratory analyses of water chemistry varies widely among monitoring 

programs, ranging from multiple discrete depths and high frequency research programs, to the EPAEMAP, EPA-NSWS (National Surface Water Survey), and EPA-NES (National Eutrophication 

Survey) snapshot surveys (Paulsen et al. 1998, Messer et al. 1991), in which water is collected at a 

single depth (primarily <1 m). In some EPA surveys, bottom water has been collected if the lake was 

thermally stratified. Some programs use a pump with an inlet tube that is raised and lowered to 

provide an integrated sample. The State of Michigan steadily lowers a glass bottle to twice the Secchi 

depth, collecting a single sample that integrates over the entire euphotic zone (MDEQ 1997). This 

integrated sample is used for chlorophyll-a in an attempt to provide a better coupling between Secchi 

transparency and chlorophyll-estimated algal biomass (MDEQ 2001, 2004). Although conceptually 

reasonable, this procedure is questionable in that it adds some logistical difficulty to collecting the 

sample, it means that nutrients and chlorophyll are collected from different water masses, it 

potentially introduces errors associated with the qualitative nature of the bottle-filling process, and 

the euphotic zone is not necessarily twice the Secchi depth (Davies-Colley and Vant 1988, Lind 

1979). In Minnesota and Wisconsin, a vertically integrated sample from 0–2 m is collected using a 2-

m-long plastic pipe. This type of sampler reduces the contribution of algae surface scums (MPCA 

2004a, 2004b) and collects an integrated column of water into a single sample. The main advantage 

of this integrated tube sampling device is that a larger stratum of water in the epilimnion is sampled, 

which reduces the effect that surface algal scums can exert on the seasonal chlorophyll means.

None of these techniques has achieved general acceptance among the community of limnologists. 

Because of its simplicity, many programs use a surface dip as a primary sample, assuming that the 

epilimnion is completely mixed and that the surface sample is a good estimator of epilimnetic 

conditions. Such assumptions are not always valid, particularly on warm, calm days when multiple 

thermal (and therefore chemical and biological) gradients may form for periods of hours to days 

(e.g., Moss 1998, WOW 2005).
26

Intensive sampling at multiple depths can best allow for calculating whole-lake nutrient budgets, if 

combined with morphometric data (lake shape, area, volume, maximum and mean depth, shoreline 

development, percent littoral zone). However, Carlson and Simpson (1996) pointed out that this 

method may miss significant gradients, and that sequential sampling, with a randomized starting 

depth, can correct for this potential bias. Research programs that use such a costly sampling program, 

however, typically have background data and infer gradients from core suite profiles to best select 

sampling depths to minimize this source of error. 

After considering all of the above sampling strategies, the Network decided to use a 0–2 m 

integrating tube sampler, following the protocol used by Wisconsin and Minnesota (WDNR 2004) 

and many other states. We will collect a near-bottom sample (ca. 1 m from bottom) via Van Dorn 

sampler during mid-summer, when lakes are stratified, for analysis of TP.

2.5 Timing of Sampling

For our discrete monitoring we will attempt to visit a given lake at approximately the same time of 

day each time we sample to minimize variation due to diurnal fluctuations. Temperature sensors on 

our thermal arrays collect data every hour year round.
27

3.0 Sampling Methods

This section summarizes the information presented in greater detail in the standard operating 

procedures (SOPs) #1 (Pre-Season Preparation), #6 (Field Measurements and Water Sample 

Collection), #7 (Processing Water Samples and Analytical Laboratory Requirements), and #11 (PostSeason Procedures). The section ends with an overview of quality assurance and quality control 

(QA/QC) procedures, which pertain to all aspects of sampling. The details of QA/QC are presented 

in SOP #12.

3.1 Field Season Preparations and Equipment Setup

(Summary of SOP #1: Pre-Season Preparations)

All details of field work need to be planned well in advance. Checklists help ensure that personnel, 

equipment, and supplies will be prepared in a timely and orderly manner.

Table 8 summarizes which of the SOPs contain key checklists of equipment and supplies for water 

sampling. Field personnel should check the inventory of equipment and supplies against these lists to 

verify that no necessary equipment or supply is missing. All equipment, meters, and probes should be 

checked to verify that they are functioning properly. If needed, replacement equipment or supplies 

should be ordered well in advance of the onset of sampling, to allow time for inspection, pilottesting, and calibration of replacements.

Table 8. Checklists of equipment and supplies for monitoring water 

quality of inland lakes.

Checklist Location

Safety equipment and supplies SOP #2

Decontamination equipment and supplies SOP #5

Field equipment and supplies SOP #6

Laboratory equipment and supplies SOP #7

Table 9 provides general guidance for activities conducted prior to the field season. Additional 

considerations are as follows:

1) Copies of field information on waterproof paper should be kept in two types of 3-ring 

binders: a project binder and a site binder. The project binder should contain reference 

information relevant to general field sampling procedures with tabs identifying each 

procedure for easy access during field work, including QA/QC reminders, copies of all SOPs 

relating to safety, decontamination, sample collection and processing, copies of equipment 

instructions and troubleshooting, calibration logs (may be a separate binder), extra field 

forms, material safety data sheets (MSDSs) for field supplies that contain hazardous 

chemicals or materials, and analytical service request and chain-of-custody forms. Site 

binders should contain reference information specific to each sampling station, including a 
28

Table 9. Checklist of activities to be conducted prior to sampling inland lakes.

√ Activity Approximate Date Responsible Person

Prepare calendar of planned 

field trips Before Feb. 1 Project manager

Review sampling methods Jan. - Feb. Project manager

Review checklists of 

equipment and supplies Jan. - Feb. Project manager or crew leader

Charge/replace batteries Feb. and prior to each 

sampling day Field personnel

Clean and test equipment, 

repair or replace as needed 

Jan. - Feb. and prior to 

each sampling day

Project manager or crew 

leader

Prepare equipment blanks Feb. Project manager or crew 

leader

Check expiration dates of 

reagents and calibration 

standards

Feb. Crew leader

Contract for lab analyses Jan. - Feb. Project manager

Prepare list of items to be 

ordered; order supplies Jan. - Feb. Crew leader

Train field personnel Jan. - Feb. Project manager

Obtain permission for site 

access, if necessary Feb. Project manager or crew leader

Confirm current research and 

collection permits Jan. - Feb. Project manager

Check field vehicle for safety 

equipment and supplies 

Feb. and prior to each 

sampling day Crew leader

Update site binders Jan. - Feb. Project manager or crew 

leader

Prepare headers on field data 

forms, chain of custody forms, 

analytical service request 

forms; bottle labels

Prior to each sampling 

round Crew leader

Review sample collection, 

processing and 

documentation information 

Feb.

(Refer to SOPs #6 & 7)

Project manager and all crew 

personnel

Notify contract analytical 

laboratory of planned sample 

shipments

Prior to each sampling 

round and day of shipment Crew leader

Make travel reservations and 

arrangements as needed 

Feb. and prior to each 

sampling round

Project manager and crew 

leader

Provide supervisor with field 

trip and check-in schedule 

Prior to each sampling 

round Crew leader
29

complete description of and directions to the monitoring site, location coordinates, maps, and 

photos, copies of previous field forms, and data tables summarizing all previous 

measurements of field variables and analytical laboratory results. Both project binder and site 

binders should be taken along on each sampling trip, and thoroughly reviewed beforehand.

2) Field personnel should be adequately experienced or trained in using field and water quality 

sampling equipment. This experience is best obtained through a combination of classroom 

and hands-on training while pilot-testing equipment at a nearby waterbody. Personnel should 

be familiar with the instruction manuals, particularly with regard to calibration and 

maintenance procedures.

3) Meters, probes, and sensors should undergo appropriate annual, weekly, and daily 

calibration. (See Table 13 for calibration frequencies and acceptance criteria.) 

4) Conduct field reconnaissance, if necessary. 

5) Pack all field gear to minimize shock and vibration during transport. Pack gear into organized 

and labeled boxes or cartons, to facilitate inventory and management of supplies. 

6) Inspect motorized field vehicles to verify that they are tuned up and working properly. 

Ensure that vehicles meet space, power, and towing requirements.

3.2 Details of Taking Field Measurements and Collecting Samples

(Summary of SOP # 6: Field Measurements and Water Sample Collection)

3.2.1 Sequence of Activities During Field Workday

This subsection provides a general overview of all sampling tasks, while the next subsections contain 

more detailed descriptions of particular tasks. Following is the sequence of activities during any 

given field day:

1) Review the checklist of field gear.

2) Create a new field form for each monitoring station, printed on waterproof paper.

3) Sample bottles and labels should be prepared in advance and placed in a cooler.

4) Conduct daily calibration of appropriate meters and probes.

5) Inspect motorized field vehicles at the beginning of every field day, including all safety and 

directional lights, oil, gasoline, and tire air pressure levels.

6) Drive to boat landing. Load boat with sampling gear, launch boat, and navigate to monitoring 

site. Set up a clean work space on the boat for sampling.

7) Refer to description of monitoring station location, directions, and photo to verify correct 

location. Verify coordinates on GPS unit.
30

8) Measure field water quality variables, conduct sampling, and/or deploy sensors per SOP #6. 

Collect water sample from the highest nutrient depth last, which is usually the bottom 

sample.

9) Be sure that all samples are correctly labeled and preserved on ice.

10) Navigate to benchmarker and measure water level relative to marker, per SOP #4.

11) Verify that the field form is completely filled out, and initial the form.

12) If sampling from more than one monitoring station in a day, go back to step 7.

13) Upon return to shore, inspect boat, trailer, and all equipment that has come into contact with 

the water for invasive species. Follow procedures for decontamination of equipment per SOP 

#5.

14) After returning to the office or lab, clean sampling equipment per SOP #6. Rinse sensors with 

deionized water and perform calibration re-checks, as detailed in SOPs #6 and #12.

15) Conduct sample processing per SOP #7. Refrigerate or freeze samples, as required. Conduct 

in-house laboratory work and package samples for sending to contract analytical laboratory.

16) Enter or import data into NPSTORET or Aquarius as soon as possible after collecting field 

data and receiving results of laboratory analyses.

3.2.2 Arrival at Monitoring Site - Recording Field Information

Waterproof field forms should be prepared ahead of time, labeled with the project and station IDs. 

Field sampling information forms are used to record the physical and chemical water quality 

variables measured at the time of sample collection. Field forms should be utilized for both routine 

and non-routine monitoring (e.g., if only a subset of data is collected, or if additional monitoring 

occurs at a lake beyond the typical three visits per season). In addition to recording the field 

variables, any samples collected for laboratory analyses must be so indicated. Documentation should 

include calibration data for each instrument, field conditions at the time of sample collection, visual 

observations, and other information that might prove useful in interpreting these data in the future.

Upon arrival at the sampling station, record general observations of the appearance of the water (e.g., 

water color and odor) and other information related to water quality and water use (e.g., fishing and 

swimming). 

General observations should include information that will be useful in interpreting water quality 

information, such as: 

 Water appearance. General observations on water may include color, unusual amount of 

suspended matter, debris, or foam. 

 Weather. Recent meteorological events that may have impacted water quality include heavy 

rains, cold front, lack of precipitation, or heavy precipitation. 
31

 Biological activity. Excessive macrophyte, phytoplankton, or periphyton growth. The 

observation of water color and excessive algal growth is important in explaining high 

chlorophyll-a values. Other observations to note include fish, birds, or spawning fish. 

 Unusual odors. Examples include hydrogen sulfide, mustiness, sewage, petroleum, 

chemicals, or chlorine. 

 Watershed or in-lake activities. Shoreline, inlet stream, or drainage-basin activities or events 

such as bridge construction, shoreline mowing, new construction, high densities of fast 

moving boats or personal water craft close to shore. 

 Other things related to water quality and lake uses. If the water quality conditions are 

exceptionally poor, note that standards are not met in the observations (for example, 

dissolved oxygen is below minimum criteria). Uses may include swimming, wading, boating, 

fishing, irrigation pumps, or navigation. This type of information may be used in evaluating 

standards compliance.

While at each monitoring site, the information recorded on field data sheets should include: 

 Date

 Time of arrival

 Names of field team members

 GPS coordinates, to verify location

 Current weather (air temperature, wind speed and direction, wave height) and relevant notes 

about recent weather (storms or drought)

 Observations of water quality conditions

 Description of any photographs taken

 Multiprobe (model), calibration date, and field measurements of core suite variables

 List of samples collected and collection times for advanced suite variables or quality 

assurance samples and method of collection (e.g., integrating tube or grab)

 Whether any samples were not collected, and reason

 Water level measurement 

 Any other required metadata for NPSTORET or Aquarius data entry

 Time of departure
32

All entries should be made clearly. If an incorrect entry is made, a single heavy line should be drawn 

through the incorrect entry and the correction made. All corrections should be initialed and dated. 

The completed field forms will be maintained in chronological order by station, copied into project 

binders and the originals maintained on file indefinitely. Field data are reviewed annually by network 

personnel (see SOP #8, Data Entry and Management, for details).

3.2.3 Measurement of Field Parameters

Field measurements must be collected from an undisturbed area, and multiprobe instruments must be 

allowed to stabilize (Table 10). Take a replicate reading for every 10 readings; values should agree 

within 10% or the acceptance criteria in Table 10, whichever is larger. Use a Secchi disk and/or 

transparency tube to measure the water clarity. Deploy, retrieve, and/or download data from the 

thermal array, if applicable.

3.2.4 Collection of Water Samples 

Collect water sample(s) with an integrated sampling tube for 0–2 m samples and Van Dorn for nearbottom samples. In the field log book and on the field data sheet, record information related to the 

sample collection, including: 

1) Lake name and site identification code.

2) Sample date, time, and depth. 

3) The amount of sample collected.

4) Whether duplicate samples for quality control were collected at this site. 

5) Any additional notes or observations pertinent to this sample or location for this sampling 

period. 

Always keep the following in mind: 

 Sample containers should be labeled in indelible ink with, at a minimum, the station name, 

date and time of collection, and preservation method, if applicable. 

 To ensure the integrity of the sample, be aware of possible sources of contamination. 

Contamination introduced during each phase of sample collection and processing is additive 

and usually is substantially greater than contamination introduced elsewhere in the sample 

handling and analysis process. 

 Use appropriate procedures and quality-assurance measures that ensure sample 

representativeness and integrity and that meet study criteria. The degree to which a sample 

can be considered representative of a waterbody depends on many interrelated factors 

including temporal and spatial homogeneity of the waterbody, sample size, and the method 

and manner of sample collection.
33

Table 10. Typical sensor performance specifications (Penoyer 2003).

Sensor

Expected 

Range

Reporting 

Resolution*

Estimated 

Bias Stabilization Criteria

Temperature -5°C to 45°C 0.01°C ±0.15°C Thermistor: ± 0.2°C

Glass: ± 0.5°C

Specific 

Conductivity 

(SC25)

0 to 2000

μS/cm

μS/cm

(range 

dependent)

±0.5% of 

reading + 1 

μS/cm

≤100 μS/cm: ± 5%

>100 μS/cm: ± 3%

PH 1 to 14 units 0.01 unit ±0.2 units ± 0.1 standard unit

Dissolved 

Oxygen (Conc.) 0 to 50 mg/L 0.01 mg/L

0 to 20 mg/L: 

±0.2 mg/L

20 to 50 mg/L: 

±0.6 mg/L

± 0.3 mg/L

Dissolved 

Oxygen (% sat.) 0%–200% 0.1% ca. ±2 % ±2%

Depth – Z 

(pressure sensor) 0–>100 m 0.1 m ca. 0.1 m 0.1 m

* Resolution specifications are supplied by the manufacturers of the measuring meters. They are not necessarily 

closely related to real-world (outdoor) precision or bias, and are sometimes more related to the number of 

significant figures reported rather than how accurate the extra significant figures are. This is why we will control 

measurement sensitivity in the actual outdoor measuring environment at least once a year by calculating alternative 

measurement sensitivity (AMS; see Irwin 2008 for more details on AMS).

3.3 Post-Collection Sample Processing

(Summary of SOP #7: Processing Water Samples and Analytical Laboratory Requirements)

Upon return to the office or home base, conduct in-house laboratory work, prepare and ship sample 

bottles, clean and prepare equipment for storage, and enter or import data from field forms into 

NPSTORET.

3.3.1 In-house Laboratory Work

Upon return from the field, keep sample bottles refrigerated prior to processing or analysis.

Process samples according to SOP #7 and specific laboratory instructions. If any of the water quality 

analyses are done in-house (for example, alkalinity titrations), conduct these procedures as soon as 

possible after returning from field work, ensuring that the maximum holding times for these variables 

are not exceeded. Store processed samples in the refrigerator or freezer, as appropriate, until shipping 

to the contract laboratory.
34

3.3.2 Shipping Samples to Contract Laboratory

Prior to shipping samples, notify the laboratory of how many samples of what type and when to 

expect shipment. Ensure that laboratory personnel will be available to receive the shipment. Check 

that the sample bottles are correctly labeled according to the protocols of the contract laboratory and 

that caps are securely tightened. Complete the analytical services request and chain-of-custody forms 

provided by the laboratory. Pack samples carefully in the shipping container according to laboratory 

protocols, to prevent bottle breakage, shipping container leakage, and sample degradation. 

Table 11 summarizes the variety of methods, detection limits, preservation techniques, and holding 

times for water samples addressed by this protocol. Methods conform to those used by Minnesota, 

Wisconsin, and Michigan for state certification of environmental laboratories involved in Clean 

Water Act or drinking water sample analysis (MDH 2005, WSLH 2003, MDEQ 2005). They are also 

used by EPA-funded research projects of natural waters in the upper midwestern United States. Refer 

to SOP #6 for additional details regarding sample collection and preservation.

The selection of a contract laboratory will include criteria regarding the laboratory’s ability to 

provide method limits of quantitation (ML) adequate for the dilute, oligotrophic lakes included in this 

monitoring protocol. Desired MLs and method detection limits (MDL) for water chemistry 

parameters are based on examination of historical data, the occurrence of low nutrient lakes in 

several of the parks, and the MDLs achievable using the standard water chemistry methods that 

research limnologists currently use. See SOP #12 for details regarding analytical detection levels 

required for GLKN water quality monitoring.

3.3.3 Equipment Cleaning and Storage

Clean all sample collection and storage containers and labware in a 0.1N HCl acid bath followed by 

deionized water rinses per SOP #7. Monitoring equipment should be cleaned and packed for storage. 

Keep equipment and supplies properly organized and labeled so they can easily be inventoried using 

the checklists.

3.3.4 Data Entry and Management

Download, enter, or import field and laboratory data into appropriate spreadsheets and databases as 

soon as possible to minimize error, per SOP #8. Refer to the instrument manufacturer’s instruction 

manual for details on downloading data from field data loggers.
35

Table 11. Example range of analytical methods, method detection limits (MDLs), containers, preservation methods, and holding times.

Analyte

Analytical

(Note 1) Method # Det. Limit

Vol. 

(ml) Filter Preservation

Sample 

Bottle

(Note 2) Hold Time

Alkalinity

Titrimetry 310.1 EPA-NERL 10 mg/L 4oC 14 days

Spec. auto. 310.2 EPA-NERL 10 mg/L 4oC 14 days

Titrimetry NFM USGS-OWQ 0.01 meg/L Note 4 None none

Calcium

ICP 3120B APHA 10 ug/L Note 3 pH<2 HNO3 P or G 6 mos

Titrimetry 215.2 EPA-NERL 0.5 mg/L Note 3 4oC 6 mos

FAA I-3152 USGS-NWQL 0.1 mg/L 250 mL Note 3 pH<2 HNO3 P 180 days

Chloride

IC 300.0 EPA-NERL 0.02 mg/L 4oC P or G 28 days

Colorimetry 325.2 EPA-NERL 1 mg/L 4oC 28 days

Titrimetry 4500-Cl APHA 0.15 mg/L 100 mL 4oC P or G 28 days

Chlorophyll-a Spect. 10200 APHA 2 ug/L <1 L Note 4 Freeze filter P 30 days

DOC

Spect. 415.3 EPA 0.018 mg/L 125 Note 3 pH<4 H2SO4 G 28 days

Spect. 0-1122-92 USGS 0.1 mg/L 4oC AG

K

ICP 3120B APHA 0.3 mg/L Note 3 pH<2 HNO3 P or G 6 mos

FAA 3111B APHA 5 ug/L Note 3 pH<2 HNO3 P or G 6 mos

Mg

ICP 3120B APHA 20 ug/L Note 3 pH<2 HNO3 P or G 6 mos

FAA 3111B APHA 0.5 ug/L Note 3 pH<2 HNO3 P or G 6 mos

Na

ICP 3120B APHA 30 ug/L Note 3 pH<2 HNO3 P or G 6 mos

FAA 3111B APHA 2 ug/L Note 3 pH<2 HNO3 P or G 6 mos

Source: National Environmental Methods Index website (https://www.nemi.gov/home/)

This list is not an endorsement of any particular method or laboratory for any particular analyte. Rather it is to be used as a reference for the range of analytical methods available for 

each analyte. There are surface water conditions (pH, turbidity, other elements) that make a particular method unsuitable for a particular situation. As GLKN is monitoring surface 

water, the methods listed were chosen as representative of the lower range of detection limits.

APHA= Clesceri et al. (1998).

Note 1. CIE-UV= capillary ion electrophoresis with UV detection, FAA = flame atomic absorption, FIA = flow injection analysis, IC= ion chromatography, ICP = inductively coupled 

plasma, Spec. auto = spectroscopy with autoanalyzer

Note 2. P = plastic (polypropylene), G=glass, AG=amber glass

Note 3. 0.45 μm membrane filter. Pre-filter for dissolved portion analysis.

Note 4. 0.45 μm glass fiber filter.

Note 5. USGS 2003= Patton and Kryskalla (2003).
36

Table 11. Example range of analytical methods, method detection limits (MDLs), containers, preservation methods, and holding times

(continued).

Analyte

Analytical

(Note 1) Method # Det. Limit

Vol. 

(ml) Filter Preservation

Sample 

Bottle

(Note 2) Hold Time

NH4-N

Selective elec. 4500-NH3E 0.08 mg/L 4oC/pH2,0oC 24 h/28 d

Colorimetry 350.2 EPA-NERL 0.08 mg/L pH<4 H2SO4 28 days

Titrimetry 4500-NH3 APHA 5 mg/L 4oC/pH2,0oC 24 h/28 d

SiO2

ICP 3120B APHA 20 ug/L Note 3 pH<2 HNO3 P or G 6 mos

Spect. 4500- SiO2 D APHA 0.04 mg/L Note 3 No, 4oC P 28 days

FIA-Spect. 4500- SiO2 F APHA 0.78 ug/L Note 3 No, 4oC P 28 days

SO4

IC 4110C APHA 75 ug/L Note 3 pH<4 H2SO4 P or G

CIE-UV D6508 ASTM 0.1 mg/L Note 3 pH<4 H2SO4 ASAP

Spect. 37512 EPA-NERL 0.5 mg/L Note 3 pH<4 H2SO4 P or G 28 days

TP

Spect. I-2606 USGS-NWQL 0.001 mg/L 125 mL MgCl 4oC BrownP 30 days

Alkaline P USGS 2003 0.01 mg/L 120 ml Note 5 4oC /H2SO4 48 h/30 d

ICP 200.7 EPA-NERL 60 ug/L pH<2 HNO3 P 6 mos

TN

Alkaline P USGS 2003 0.03 mg/L 120 ml Note 5 4oC /H2SO4 48 h/30 d

Titrimetry 4500-N 0–100 mg/L 4oC AG 7 days

Combustion 440.0 EPA-NERL 0.1 mg/L Filter 100 days

Source: National Environmental Methods Index website (https://www.nemi.gov/home/)

This list is not an endorsement of any particular method or laboratory for any particular analyte. Rather it is to be used as a reference for the range of analytical methods 

available for each analyte. There are surface water conditions (pH, turbidity, other elements) that make a particular method unsuitable for a particular situation. As GLKN is 

monitoring surface water, the methods listed were chosen as representative of the lower range of detection limits.

APHA= Clesceri et al. (1998).

Note 1. CIE-UV= capillary ion electrophoresis with UV detection, FAA = flame atomic absorption, FIA = flow injection analysis, IC= ion chromatography, ICP = inductively 

coupled plasma, Spec. auto = spectroscopy with autoanalyzer

Note 2. P = plastic (polypropylene), G=glass, AG=amber glass

Note 3. 0.45 μm membrane filter. Pre-filter for dissolved portion analysis.

Note 4. 0.45 μm glass fiber filter.

Note 5. USGS 2003= Patton and Kryskalla (2003).
37

3.4 End of Field Season Procedures

(Summary of SOP # 11: End-of-Field Season Procedures)

When sensor probes are to be stored for extended periods of time, thoroughly clean sensors, remove 

batteries, and store the sonde according to specific instructions in SOP #11 and the manufacturer’s 

manual. Store calibration standards and electrolyte solutions in a temperature-controlled 

environment. Ensure that containers are dated upon receipt and upon opening; observe expiration 

dates. 

3.5 Quality Assurance/Quality Control 

The objective of quality assurance/quality control (QA/QC) is to ensure that the data collected for a 

project are meaningful, representative, complete, precise, accurate, comparable, and scientifically 

defensible (O’Ney 2005a). It is a broad management concept requiring the complete integration of 

field and laboratory systems of sample collection and analysis. The QA/QC procedures that pertain to 

sample collection and processing are focused on: 1) ensuring that any given field or laboratory 

measurement accurately represents the water resource at the time the sample was collected, 2) 

ensuring that water quality data are comparable across all sampling dates, and 3) verifying that no 

contamination has been introduced to the sample at any time. These activities range from instrument 

calibration, to specification of field methods and laboratory detection limits, to analysis of sample 

blanks and spikes. Table 12 summarizes the QA/QC procedures pertaining to sampling methods that 

will be followed in this protocol.

One important aspect in the accuracy and precision of a water quality monitoring program is the 

correct selection of probes for measuring field variables and their subsequent calibration and 

maintenance schedule. Table 10 (above) lists typical field sensor performance specifications that 

should be expected from monitoring equipment for this protocol. Table 13 summarizes the ideal 

calibration frequency and minimum acceptance criteria for these sensor probes. The reality of 

logistical constraints at back country sites may preclude calibration and checks of calibration at the 

ideal frequency. Calibration logs for multi-parameter sondes will be maintained and will document 

the frequency of calibration and calibration checks. Ensure calibration standards are not used beyond 

expiration dates. Refer to SOP #6 for guidelines on potential field measurement problems.

The detection limits for water quality variables specified in Table 11 are based on examination of 

historical data and the occurrence of dilute concentrations of water quality variables in natural 

waters. Many commercial laboratories do not routinely analyze samples using these lower detection 

limits, even if they have the proper instrumentation, because their primary work load is wastewaterrelated with much higher concentrations. Therefore, the process of selecting a contract analytical 

laboratory will include consideration of whether the lab has experience analyzing naturally dilute 

waters.

Quality Control (QC) involves specific tasks undertaken to determine the reliability of field and 

laboratory data. It is accomplished internally by routine analysis of blanks, duplicates, and spikes in 

the day-to-day operation of a laboratory, or externally by incorporating field-originated blanks, 
38

duplicates, and spikes into the set of the samples collected during a water quality survey. We will 

include the following QA/QC routines:

1) Equipment blanks prior to the field sampling, to ensure no extraneous sources of 

contamination are introduced into the samples.

2) Submit duplicate water samples, at the rate of approximately 10%, so that the reported data 

are precise, or the results of analyses are reproducible.

3) Document the sensitivity of multiprobes through an estimation of the limits of detection 

known as alternative measurement sensitivity (AMS).

4) Replicate multiprobe field measurements at the rate of approximately 10%. Calculate the 

relative percent difference to document precision of the multiprobe.

Table 12. Summary of QA/QC procedures pertaining to sampling methods.

Procedure Description/reason

Instrument calibration logs Each instrument must have a calibration log. Calibration schedule must be 

observed, using fresh calibration standards.

Project binder

Containing: checklist of QA/QC reminders, copies of decontamination, sample 

collection and processing SOPs, copies of equipment calibration and 

troubleshooting instructions, ASR and COC forms, blank field forms.

Site binders

Containing: GPS coordinates for verification of correct sampling location, table 

of previous field measurements to compare with new measurements, map and 

directions to site.

Field forms Field forms are the only written record of field measurements, so copies are 

placed in project binders and originals must be kept on file indefinitely. 

Field instrument methods Require consistent measurement methods and detection limits 

Sample preservation and 

minimum holding time Water samples are maintained as close to sampling conditions as possible.

Chain-of-custody 

A chain-of-custody includes not only the form, but all references to the sample, 

including information that allows tracing the sample back to its collection and 

documents the possession of the samples from the time they were collected 

until the sample analytical results are received. 

Laboratory methods Require consistent analytical methods and detection limits
39

Table 13. Ideal calibration frequencies and acceptance criteria for field instruments.

Parameter

USEPA 

Method

Minimum Calibration 

Frequency and QC checks

Acceptance 

Criteria Corrective Actions

Temperature: 

thermometer

170.1 Annually, 2-point check with NIST 

thermometer

±1.0oC Re-test with a different 

thermometer; repeat 

measurement 

Temperature: 

thermistor

170.1 Annually, 2-point check with NIST 

thermometer

±1.0oC Re-test with a different 

thermometer; repeat 

measurement 

Specific 

Conductance 

(SC25)

120.1 Daily, prior to field mobilization; 

calibration check prior to each 

round of sampling; 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 

RPD 10%

pH 150.1 Daily, prior to field mobilization 

(two buffers should be selected 

that bracket the anticipated pH of 

the water body to be sampled 

with an independent third buffer 

selected to check instrument 

performance in that range); 

±0.05 pH unit

Re-test; check low battery 

indicator; use different 

standards; repeat measurement; 

don’t move cords or cause 

friction/static 

Calibration check w/ third buffer 

prior to each round of sampling 

±0.1 pH unit

10% of the readings taken each 

day must be duplicated or a 

minimum of 1 reading if fewer 

than 10 samples are read.

RPD 10%

Dissolved 

Oxygen 

360.1 Daily, prior to field mobilization; 

check at the field site if elevation 

or barometric pressure changed 

since calibration 

0.2 mg/L 

concentration 

or

±10%

saturation

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; allow more time 

for stabilization 

Depth -- Daily, prior to field mobilization, 

check at the field site. Check 

annually against commercially 

purchased brass sash chain 

labeled every 0.5 m to ensure 

that it reads zero at the surface 

and varies <0.3 m for depths <10 

m and no more than 2% for 

greater depths. 

±0.1 m Retest, check low battery 

indicator; repeat measurement; 

use with accurately calibrated 

line

Transparency 

tube

-- Transparency tubes have a 100-

or 120-cm scale; ensure tube is 

clean

±1.0 cm for 

transparency 

tube

Transparency tube

Marked lines 

(e.g., Secchi, 

Van Dorn)

-- Check markings annually against 

brass sash chain. If lines are 

heated (for decontamination) 

check prior to each round of 

sampling.

±1%, 0–10 m

±2%, >10 m

Re-mark line.

41

4.0 Data Handling, Analysis, and Reporting

4.1 Metadata Procedures

Metadata allows potential data users to evaluate the quality and usefulness of the data based on an 

understanding of the complete process under which it was collected and maintained. In this respect, 

all of the protocol documentation, including standard operating procedures (SOPs), is part of a 

dataset’s metadata. A reference to the appropriate version of these documents is part of the metadata 

for any particular element of a dataset. Although perhaps obvious, all data must have an associated 

value for the date and time they were collected.

Most of the remaining metadata will be recorded directly in the protocol-specific databases and 

tables. We will enter or import all required metadata for NPSTORET and Aquatic Informatics’ 

Aquarius database; the data and metadata will ultimately be moved to the EPA STORET database or 

for Aquarius maintained by NPS-WRD staff in Ft. Collins, Colorado. 

For metadata associated with geospatial data, we will abide by Executive Order 12906, which 

mandates that every federal agency document all new geospatial data it collects or produces using the 

Federal Geographic Data Committee (FGDC) Content Standard for Digital Geospatial Metadata 

(CSDGM; www.fgdc.gov/metadata/contstan.html). All GIS data layers will be documented with 

applicable FGDC and NPS metadata standards. The Network will also generate FGDC-style 

metadata for non-spatial datasets that meet this standard, absent only the geospatial-specific 

elements.

Although it is not required, we will make every effort to complete Biological Data Profiles 

(www.fgdc.gov/standards/status/sub5_2.html) for appropriate datasets and add associated metadata 

to the National Biological Information Infrastructure (NBII; www.nbii.gov/datainfo/metadata) 

Clearinghouse.

For more details on the Great Lakes Network’s overall strategy for metadata generation, 

management, and distribution see chapter 8, Data Documentation, of GLKN’s Data Management 

Plan (Hart and Gafvert 2006) and the appendices of that document. 

4.2 Overview of Database Design

The NPS-WRD has established a policy that all I&M water quality monitoring data will be made 

compatible with, and be uploaded to, the EPA’s STORET database. The WRD developed a 

Microsoft Access database tool, NPSTORET, which duplicates most of the EPA data and table 

structures in, to facilitate easier movement of I&M Networks’ water quality data into EPA Water 

Quality Exchange (WQX) framework. We will use NPSTORET as the primary data entry tool and 

data transfer mechanism to WRD. In addition, GLKN uses Aquatic Informatics’ Aquarius system for 

storage and visualization of continuously monitored water quality data from automated loggers (i.e., 

water temperature data from thermal arrays).

The Network will maintain one master copy of NPSTORET at the Ashland office on a central server. 

This is the only copy of NPSTORET that can be used to export data to other locations (WRD). 
42

Additional copies of NPSTORET can be used by Network staff or cooperators, but they can only be 

used as a conduit for data entry and the importation of data to GLKN’s master version of 

NPSTORET. For analysis, the data from the master copy of NPSTORET must be used. The Network 

will continue to improve tools for automating analysis and visualization of the information contained 

in the NPSTORET and Aquarius datasets.

4.3 Data Entry, Verification, Certification, and Editing

Detailed instructions for the data entry procedures for this protocol are given in SOP #8, Data Entry 

and Management. As described above (Section 3, Field Methods), three general classes of water 

quality data are collected. The first is field observations and measurements that are recorded on data 

sheets in the field. These field sheets will be entered into a digital file. The second class of data is the 

results of testing performed by contract analytical laboratories. The last class of water quality data is 

digital data that have been collected by multiprobe sondes and other field data loggers. GLKN will 

develop formatting routines to be applied to the digital files prior to importation of data into 

NPSTORET or Aquarius. 

Data verification starts with the QA/QC steps that are outlined in the SOPs associated with this 

protocol. If data being imported into NPSTORET do not pass a QA/QC test, NPSTORET prompts 

the user to make corrections and re-import the data. Data that are outside the expected rate of change 

for a parameter based on previous records for that parameter will be flagged for further review by an 

expert. 

Quality assurance/quality control checks are performed as data are imported into NPSTORET or 

Aquarius and again when the data are transferred to WRD. The Network’s water quality data records 

are regarded as being in provisional status until they are returned to GLKN from WRD, or are 

accepted by WRD without changes after the final QA/QC steps. Once returned to GLKN by WRD, 

and after appropriate documentation is completed, the dataset is officially considered certified. Only 

qualified users who have been trained and given edit permissions are allowed to edit data in 

NPSTORET or Aquarius. These procedures protect the integrity of the data and allow the history of 

each data record to be traced.

4.4 Data Archival Procedures

Data archiving serves two primary functions: it provides a source to retrieve a copy of any dataset 

when the primary dataset is lost or destroyed, and it provides a data record that is an essential part of 

the QA/QC process. The unedited files are the original data for digital data. The archival of the 

printed data forms for this protocol is described in SOP #8.

The Network will create duplicate files of all digital data at the earliest opportunity. At least two 

complete copies of any water quality dataset are required by WRD, including digital replicas 

(scanned versions) of hard copy data sheets. Digital field data that are entered directly into a field 

computer or collected from a data logger will be backed up to a second medium at the earliest 

possibility. The data files on field computers and loggers must not be erased until the integrity of 

these data files are verified on the duplicate storage medium. 
43

The Network’s master version of NPSTORET is maintained on a central server in the Ashland Office 

that is backed up daily, and backed up off-site weekly. Complete details of the GLKN Server 

archiving procedure are found the Infrastructure chapter of GLKN’s Data Management Plan (Hart 

and Gafvert 2006); the general strategy for data archiving is also described in this plan and its 

appendices. 

4.5 Quality Assurance and Quality Control Pertaining to Data Entry and Management

Quality assurance and quality control procedures are crucial during every step of data entry and data 

management. Details of such QA/QC regarding data management are provided in SOP #8 and are 

summarized below in Table 14.

Table 14. Summary of QA/QC procedures pertaining to data management.

Procedure Description

Instrument calibration logs Each instrument must have a calibration log.

Field forms Field forms are the only written record of field measurements, so copies are placed 

in project binders and originals must be kept on file indefinitely. 

Estimating precision 

The precision measurement is calculated using the Relative Percent Difference 

(RPD) between duplicate sample results per analyte. Precision estimates should be 

performed within 7 days of receipt of laboratory results. 

Electronic data entry Approximately 10% of electronic data entries should be spot checked on a random 

basis for errors. If errors are found, another 10% are spot checked. 

Data archiving 

Program sampling data and associated records are archived in boxes and stored at 

the GLKN Ashland office. Boxes are numbered consecutively by year, project, and 

station number.

Data validation Data validation is the process that determines whether data collection quality 

control objectives were met. 

Data validation reports Data validation reports provide a narrative that discusses any deviations from 

QA/QC procedures and the impacts of those deviations. 

Data verification Data verification demonstrates that a data set will qualify as credible data. 

Data certification

Data certification demonstrates that data are complete for the period of record; 2) 

they have undergone and passed the quality assurance checks; and 3) that they 

are appropriately documented and in a condition for archiving, posting and 

distribution as appropriate.

Data verification reports Data verification reports document the results of the data verification procedure. 

Data qualification codes Data must be fully qualified before uploading to the Water Resources Division 

4.6 Routine Data Summaries

Brief characterizations of the data from each lake, across each NPS unit in which sampling occurred 

and for the network as a whole, will be performed following each sampling year after all QA/QC 

procedures have been completed. For each water quality variable, these descriptive statistics may 
44

include mean, median, maximum, and minimum values by lake; and these same values with the 

addition of skew, kurtosis, and measures of variability (e.g., coefficient of variation, standard error, 

95% confidence intervals) among lakes within each NPS unit. These broader-extent analyses can 

inform managers whether anomalous values recorded from a given lake (or even across all lakes 

within one park) were also observed at broader spatial extents that year (e.g., across a given park, or 

in other parks). Given the relevant legislation (e.g., Clean Water Act of 1972), it may be of interest to 

the individual parks and to other entities to assess the proportion of measurements during a time 

period or across a domain (at a single point in time) that exceed specific water quality criteria or predetermined thresholds. As with nearly all percentage data, arcsine transformations must be performed 

on those percentage data before statistical analyses can be performed. However, back-transformed 

values will be used for graphical presentation and other reporting. 

In addition to these descriptive statistics, analytical approaches may also include estimation of 

interannual change, graphic approaches (e.g., comparison of mean and variability in a parameter in 

the current year versus past years), and occasionally qualitative analysis (Guthery et al. 2001), as 

well as modeling, correlational analyses, and various parametric and nonparametric analyses. 

4.7 Methods for Long-Term Trend Analysis 

After at least three sampling seasons of monitoring data are collected at a given lake, more intensive 

analyses of change may be performed for each lake. In addition to repeated-measures, time-series, 

regression, and non-parametric equivalents of various methods such as Mann-Kendall, monitoring 

data may also be evaluated through Monte Carlo simulation analyses, Bayesian analyses, and 

comparisons of period means. For the latter-most approach, one is often interested in comparing 

values before and after an important event (e.g., change in management policy, remarkable 

anthropogenic disturbance, natural catastrophe, drought), and considers years within each of the two 

periods as replicates. The seasonal Kendall test is one of several preferred nonparametric tests for 

evaluating interannual trends in water quality (Hirsch et al. 1991). The test, which accounts for intraannual variability, has been used widely for more than 15 years, and usually requires five to ten years 

of data. In the test, one can define “seasons” as months, quarters, ice-on/off periods, by limnological 

stratification, or by any other criterion. The examination of interannual change is subsequently 

performed on each of the seasons; the average of all the seasons’ slopes becomes the final trend line. 

Trends in parameters that are analyzed with respect to biotic and abiotic covariates that may affect 

water quality will be examined, although cause-effect relationships may be investigated more 

thoroughly by NPS partners and collaborators (e.g., USGS-WRD, university investigators). 

In addition to analyzing each variable separately, several abiotic indicators of water quality that are 

not correlated and that naturally could be considered a homogeneous group of parameters could be 

analyzed collectively through multivariate ordinations (e.g., nonmetric multi-dimensional scaling) of 

resource conditions through time, following West and Yorks (2002). This approach effectively 

integrates information across many indicators, and can suggest whether water quality at individual 

lakes is moving in the same direction in multidimensional ordination space. Furthermore, joint plots 

can be overlaid on the ordination, and can suggest which variables correlate most strongly to the 

direction of changes. Multivarite analyses can help suggest cause-and-effect relationships and are 
45

useful as hypothesis-generating tools. Multivariate ordinations are also useful for relating waterquality conditions with abundance or presence data from many species (e.g., diatoms) (McCune and 

Grace 2002). 

See SOP #9 for additional details on data summaries and analyses.

4.8 Reporting Schedule

One of the Network’s main goals is to ensure that the results and knowledge acquired through the 

water quality monitoring program are shared with all appropriate parties, especially the parks and 

their natural resource managers. We will strive to provide park managers with clear, meaningful 

products in a timely manner to convey our findings. Because our monitoring data will be of interest 

to a broader community, we will also provide our reports to the states, the NPS I&M Division, and 

when appropriate, submit them to peer-reviewed journals for publication. We will also present our 

findings orally and in poster format at regional meetings, such as the Western Great Lakes Research 

Conference, the St. Croix Research Rendezvous, or the Lake of the Woods Research Conference.

As mentioned above, routine data summaries will be conducted annually for lakes and parks that are 

sampled within that year. The summaries will be compiled from data that has been uploaded to the 

EPA’s STORET database or the Aquarius database by NPS-WRD. Hard copy or web-based 

summary reports will be produced periodically, after the data is certified, with the primary audience 

being the parks. 

More comprehensive reports, with analyses of trends, will occur after three or more seasons of 

sampling. For stations that are located where no previous monitoring has occurred, three sampling 

periods are the minimum needed to establish a time series sufficiently powerful to detect meaningful 

levels of change (e.g., 20%) through time. 

The target audience of the analysis and synthesis reports will be the parks, the Network, both 

regional and Servicewide I&M, and the broader scientific community. Drafts of these reports will be 

reviewed internally and sent to the parks, and possibly outside sources, for further review. The extent 

of review will depend on how analytically complicated the methods are and the gravity of inference 

and recommendations.

4.9 Report Format with Examples of Summary Tables and Figures 

Both annual summaries and reports that include detailed analyses on trends should adhere to 

Servicewide I&M reporting guidelines for Natural Resource Data Summary reports (for annual 

summaries) and Natural Resource Reports (for detailed analysis reports). Refer to the Natural 

Resource Publications Management website for the most up-to-date guidelines and formats

(http://www.nature.nps.gov/publications/NRPM/index.cfm). Reports should include tables and 

figures appropriate for the data and for the intended audience.

47

5.0 Personnel Requirements and Training

5.1 Roles and Responsibilities

The water quality monitoring program at the Network is staffed by a project manager (GLKN aquatic 

ecologist, GS/11) and two assistant project managers (GLKN aquatic ecologists, GS/9s). The project 

manager and the assistant project managers are permanent full time employees. The assistant project 

managers primarily focus on leading fieldwork for separate water quality monitoring protocols 

(inland lakes or large rivers) during the field season, but also have many overlapping responsibilities 

throughout the year. The assistant project managers will each supervise at least one seasonal crew 

member at the GS/4 or GS/5 level, and along with the crew members may be stationed at one of the 

parks. 

The field crews will work on this water quality monitoring project for a limited number of pay 

periods per year, and may spend the remaining part of their time on other Network or park projects. 

The Network will explore the possibility of sharing seasonal positions with the parks. When a park 

has an aquatic person on staff, the Network will make use of such existing staff expertise on the crew 

when possible, paying for the time spent on I&M monitoring activities, and will provide the same 

training to the park person as to the rest of the crew members. The field crews will monitor water 

quality in both rivers and lakes; the responsibilities, training, and qualifications of the crew are the 

same for both protocols.

5.1.1 Project Manager

The role of the project manager is to serve as a liaison among other related water quality monitoring 

projects conducted by partners (e.g., state monitoring programs), park staff, other Network staff 

(field personnel, data manager), contracted analytical laboratories, and other GLKN project

managers. The individual will coordinate with resource management staff at the parks to ensure parks 

are informed of monitoring activities. Specific responsibilities of the project manager include the 

following:

 Coordinate field schedules and availability of supplies with field personnel.

 Develop a training program for field personnel.

 Develop, document, and oversee the implementation of standard procedures for field data 

collection and data handling.

 Coordinate logistics with park staff.

 Develop QA/QC measures for the project, supervise staff training, and conduct quality 

assurance checks of field sampling techniques at least once, mid-season, with each field 

crew.

 Contract with analytical laboratories for analysis of water samples, ensure lab results meet

program needs (e.g., QA/QC procedures, meaningful minimum detection limits for dilute 

waters, adequate reproducibility of replicate samples).
48

 Supervise or perform data entry, verification, and validation.

 Summarize data and analyze data, prepare reports.

 Serve as the main point of contact concerning data content.

The project manager will also work closely with the data manager in the following capacities: 

 Complete project documentation (i.e., metadata) in appropriate databases.

 Develop data verification and validation measures for quality assurance.

 Establish and implement a procedure to officially certify water quality datasets.

 Ensure staff are trained in the use of database software and quality assurance procedures.

 Coordinate changes to the field data forms and the user interface for the project database.

 Identify sensitive information that requires special consideration prior to distribution.

 Manage the archival process to ensure regular archival of project documentation, original 

field data, databases, reports and summaries, and other products from the project.

 Define how project data will be transformed from raw data into meaningful information and 

create data summary procedures to automate and standardize this process.

 Establish meaningful liaisons with state counterparts to promote sharing of data on a timely 

basis.

5.1.2 Assistant Project Managers

Assistant project managers are largely responsible for implementing the inland lakes and large rivers 

water quality monitoring protocols. Specific responsibilities include:

 Assist with coordination of field schedules and supplies.

 Supervising and training field personnel.

 Coordinate logistics with park staff.

 Help ensure all aspects of QA/QC are met.

 Perform data entry, verification, and validation.

 Train other staff in the use of database software.

 Assist with data analysis and report writing.
49

5.1.3 Field Personnel (Field Crew Member/Leader) 

The role of field personnel is to conduct all field work related to the monitoring project. Field 

personnel will include both a crew leader and a crew member. The crew leader is responsible for 

contacting the parks prior to each sampling event to ensure logistical requirements will be met. Crew 

leaders and crew members may be park staff that coordinate with their respective parks and the 

Network project manager. Responsibilities for Network or park crew leaders and crew members 

include the following: 

 Complete all training for field sampling, sample handling, and boat operation, if required by 

park.

 Complete all phases of field season preparation.

 Collect data and samples according to developed protocols.

 Pack and ship samples to analytical laboratory.

 Maintain accurate field and office notes.

 Ensure that all QA/QC procedures are implemented.

 Maintain and calibrate equipment according to protocols and manufacturers’ directions.

 Communicate progress and accomplishments with the project manager during and after 

sampling at each park unit, and report any deviations from sampling protocols.

 Download, enter, and verify data into databases as required.

 Maintain documentation of important details of each field data collection period, including 

explanations of all deviations from standard procedures.

 Maintain hard copies of data forms and send original data forms to archive on a regular basis.

 Represent the National Park Service and the Network in a professional manner, and assist in 

maintaining positive communication among the Network, park staff, and the public.

5.1.4 Data Manager 

The data management aspect of the monitoring effort is the shared responsibility of the data 

collectors first, then the project manager, and finally the network data manager. Typically, field 

personnel are responsible for data collection, data entry, data verification, and validation. The data 

manager is responsible for data archiving, data security, dissemination, and database design. The data 

manager, in collaboration with the project manager, also develops data entry forms and other 

database features (as part of quality assurance) and automates report generation.

5.2 Crew Qualifications 

The crew leader must have a bachelor’s or advanced degree in biology, chemistry, or other related 

physical or biological science. Field experience is mandatory and laboratory experience is preferred. 
50

Prior leadership experience and good decision-making skills are highly desirable, as is experience 

with boats, motors, and canoes.

Crew members should have a background in biology, chemistry, or other related physical or 

biological science, although an undergraduate degree is not required. Prior field experience, 

including that with boats, motors, and canoes, is highly desirable and laboratory experience is 

preferred.

All crew members must be physically fit, able to work long hours in inclement weather, and able to 

carry heavy loads. Sampling at some parks may involve camping for several days at a time and 

portaging between lakes.

5.3 Training Procedures

Prior to data collection, field personnel must become familiar with the use, calibration, and 

maintenance of all meters and probes planned for use in the monitoring project. A combination of 

classroom and field training will be required prior to each field season. Personnel who were 

previously trained for this monitoring project will participate in a review of all methods and 

techniques. Specific details of the training procedures are covered in SOP #2 and will include:

 Basic limnological concepts and field sampling techniques.

 Review of all SOPs for the project.

 Calibration, operation, and maintenance of all field and laboratory meters and probes used in 

the project.

 Methods for sample collection.

 Methods for cleaning equipment. 

 Methods for handling and preserving samples.

 Completion of field data forms, sample labels, chain of custody forms, analytical service 

request forms.

 Data entry procedures.

 Completion of field and calibration logbooks.

 Use of GPS equipment.

 Park-specific training requirements (e.g., boat operation, navigation, radios).

 NPS-specific training (e.g., computer use, credit card, travel).
51

6.0 Operational Requirements

6.1 Annual Workload and Field Schedule

The annual workload and schedule for the monitoring of water quality in inland lakes must be 

viewed within the context of the other planned water quality monitoring activities. We prepared the 

estimated workload and schedule for monitoring of inland lakes and large rivers together, but 

anticipate additional related protocols in the future (e.g., wadeable streams). As these additional 

protocols become part of the GLKN monitoring program, the workloads are likely to change. 

Parks with inland lakes are APIS, INDU, ISRO, PIRO, SLBE, and VOYA. We will monitor water 

quality at each selected index lake three times during the open water season (May to October). We 

likely will deploy and maintain thermal arrays in one or more inland lakes at ISRO, PIRO, SLBE, 

and VOYA, which typically requires at least two additional days in the field above and beyond the 

usual three monitoring days per lake each season. The time it takes to conduct field work is always 

weather dependent, and this is especially true at parks where travel on Lake Superior or Lake 

Michigan is required (SLBE, ISRO, and APIS). Sampling can be delayed and field crews can be 

stranded for days when wind and waves prohibit boat travel. We estimate sampling to take from one 

day at INDU, to as much as 10 or more days at VOYA and ISRO, including travel time. Initial 

estimates of time required to sample at each park (explained in more detail, below, under staff 

salaries) assume minimal weather-related delays.

6.2 Facility and Equipment Needs

At each park, the field crew will need a facility with a sink and counter-top space where they can 

calibrate instruments, clean and store equipment, and process samples. They will also need a 

refrigerator and freezer for storing samples prior to shipment to an analytical laboratory, and secure 

space for storing a boat, motor and gasoline, canoe, and other field equipment. Availability of needed 

space varies across park units, but all park units with inland lake resources can meet the basic 

necessities with the exception of APIS, which does not have laboratory space. The Network office is 

located near APIS, however, and can provide the needed laboratory space.

6.3 Budget Considerations

6.3.1 Equipment and Supplies

Costs associated with purchase of equipment and supplies related to fieldwork and laboratory 

activities are now associated with replacing equipment as it wears out or becomes obsolete, or when 

supplies need to be replenished. Some of the parks already had some of the necessary sampling gear 

and equipment when this protocol was first implemented, and continue to replace gear and equipment 

as necessary. When possible, we will coordinate with the parks in the use of their equipment. 

Sampling at APIS, ISRO, and the islands of SLBE requires large boats for travel on the Great Lakes. 

The Network owns two boats, with motors, trailers, and other necessary equipment, appropriate for 

use on Lake Superior at APIS and ISRO. SLBE owns boats appropriate for traveling to North and 

South Manitou islands and will provide transportation for water quality field crews as necessary. The 

Network and VOYA jointly own a boat, motor, and trailer to be shared by park and Network staff at 

that park. Boats or canoes appropriate for inland lakes are available to the Network at all the parks, 
52

though Network-owned crafts may be required in the future. The Network purchases supplies related 

monitoring under this protocol, and for some parks provides funds to help cover fuel costs and boat 

operator salaries when parks assist in transporting Network staff. Annual expenses related to 

equipment, supplies, and fuel expenses typically range from $10,000 to $15,000.

6.3.2 Staff Salaries

From 2011 to 2014 annual salary expenses related to inland lake water quality monitoring at six 

Network parks ranged between $190,000 and $215,000, taking into account the following:

 annual salaries for the Network project manager and assistant project manager,

 six-to-eight pay periods for a Network seasonal crew member duty stationed at ISRO,

 six-to-ten pay periods for a VOYA permanent crew leader shared with the Network, and 

 Various salary expenses for park staff at four parks who conduct inland lake monitoring work 

for the Network.

The project manager’s annual salary is divided between the I&M Division and WRD, with the 

majority of salary typically assigned to WRD. The Network data manager’s salary is covered entirely 

by the I&M Division and is not reflected in the annual salary expenses above. The salary estimates 

include staff time for project management, training, pre-season preparation, sampling, processing 

samples, packing and shipping samples, data entry, analysis, reporting, and other various tasks 

associated with the monitoring effort.

6.3.3 Vehicles and Travel 

We expect travel expenses to be approximately $7,500 annually. This estimate includes GSA 

vehicles and travel (lodging and per diem), and is based on the following assumptions:

1) GSA vehicles will be shared with other monitoring projects or parks, when possible.

2) Park housing will be available at ISRO, VOYA, SLBE, and PIRO.

3) The program manager will travel to Network parks on a rotational basis to assist with 

monitoring activities and provide oversight on water quality monitoring activities for the 

Network

4) Park staff that serve as crew leaders will work with the project manager and assistant project 

managers, and will occasionally travel to other parks as needed.

6.3.4 Analytical Laboratory Costs

Monitoring guidelines established by WRD include strong recommendations for selecting an 

analytical laboratory that has been accredited by the federal National Environmental Laboratory 

Accreditation Program (NELAP). The Network will assess the differences in detection and reporting 

limits among NELAP-approved, state accredited, and research laboratories, along with other criteria, 

prior to selecting a contract laboratory. The laboratory selected by GLKN must be able to detect and 
53

report concentrations appropriately low such that changes in water quality variables can be detected 

early in the naturally dilute waters occurring throughout the Network. The laboratory selected must 

meet the detection limits outlined in SOP #12 and have a rigorous QA/QC plan. 

For the purpose of estimating a budget for monitoring water quality of inland lakes, we use the costs 

quoted by CT Laboratories and the St. Croix Watershed Research Station, which are the two 

analytical laboratories that currently process Network water samples (Table 15). The estimates from 

the other laboratories are included as examples of what our costs might be if we selected one of them 

instead.

Table 15. Estimates of laboratory costs for analysis of water quality parameters. Costs in bold 

font reflect per sample prices for 2015.

CT Laboratories

Natural 

Resources 

Research Institute

St. Croix 

Watershed 

Research Station

Central Michigan 

University

Alkalinity $10 $12 $4 $6

DOC $18 $18 $15

Cl $8

$23 (Cl w/ SO4)

$10 $5

SO4 $8 $10 $7

Na, K, Mg, Ca $32 $23 NA

TP $18

$28 (dual TP and 

TN)

$32 (dual TP and 

TN)

$7

TN $18 (as TKN)

NH4-N $12 $11

$32 (dual w/ 

NO3/NO2-N)

$1

NO3+NO2-N $12 $12 $10.50

Chlorophyll-a $27 $34 $16 $13

SiO2 $9 $10

We expect to measure nutrients (TP, TN, NO3+NO2-N, NH4-N) and chlorophyll-a each sampling 

visit, or three times per survey-year, one near-bottom TP sample per year, and the remaining 

parameters once per survey-year. Annual estimated laboratory analysis costs associated with inland 

lake monitoring (samples, duplicates, and equipment blanks) are typically about $15,000 but may be 

higher if funding is available and additional lakes are monitored. 
54

6.3.5 Total Estimated Annual Costs 

Annual monitoring costs ($123,500; Table 16) at the six parks with inland lake resources are high––

more than the Network receives from WRD (approx. $150,000). Monitoring water quality of large 

rivers (Magdalene et al. 2008), diatoms (Ramstack et al. 2008), and wadeable streams (protocol in 

preparation) are not included in these estimates, putting the total cost of monitoring water quality 

well beyond the funding WRD provides. Because of the importance of water quality to GLKN parks, 

the Network is contributing substantial I&M funds to implement these water quality monitoring 

protocols.

Table 16. Total estimated annual costs for monitoring water quality at 

GLKN inland lakes.

Item Cost

Annual equipment and supplies $10,000–$15,000

Salary and benefits $190,000–$215,000

Travel $7,500

Laboratory analyses $15,000

Total $222,500–$252,500

6.4 Procedures for Revising and Archiving Previous Versions of the Protocol

As our water quality monitoring program matures, revisions to both the protocol narrative and 

specific standard operating procedures (SOPs) are likely. Documenting changes and archiving copies 

of previous versions of the protocol and SOPs are essential for maintaining consistency in the 

collection of data and for appropriate interpretation of the data summaries and analyses. The 

NPSTORET database contains a field for each monitoring component that identifies which version of 

the protocol was being used when the data were collected. 

The rationale for dividing a sampling protocol into a protocol narrative with supporting SOPs is 

based on the following: 

 The protocol narrative is a general overview of the protocol that gives the history and 

justification for doing the work and an overview of the sampling methods, but does not 

provide all methodological details. The protocol narrative will only be revised if major 

changes are made to the protocol. 

 The SOPs are specific step-by-step instructions for performing a given task. They are 

expected to be revised more frequently than the protocol narrative. 

 Usually, when a SOP is revised, it is not necessary to revise the protocol narrative to reflect 

the specific changes made to the SOP. 

All versions of the protocol narrative and SOPs will be archived. 

The steps for changing the protocol (either the protocol narrative or the SOPs) are outlined in 

Procedures for Revising the Protocol, SOP #13. Each SOP contains a Revision History Log that must 
55

be updated each time a SOP is revised, to explain why the change was made and to assign a new 

version number to the revised SOP. The new version of the SOP or protocol narrative should then be 

archived in the appropriate folder of the GLKN database structure.

57

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67

Index to Standard Operating Procedures

SOP #1: Pre-season Preparation 

SOP #2: Training and Safety

SOP #3: Using the GPS 

SOP #4: Measuring Water Level 

SOP #5: Decontamination of Equipment to Remove Exotic Species

SOP #6: Field Measurements and Water Sample Collection

SOP #7: Processing Water Samples and Analytical Laboratory Requirements 

SOP #8: Data Entry and Management 

SOP #9: Data Analysis 

SOP #10: Reporting

SOP #11: Post- Season Procedures 

SOP #12: Quality Assurance/Quality Control

SOP #13: Procedure for Revising the Protocol

Standard Operating Procedure #1: Pre-Season 

Preparation

Version 1.1

In Water Quality Monitoring Protocol for Inland Lakes

Prepared by

Richard Axler and Elaine Ruzycki 

Center for Water and the Environment

Natural Resources Research Institute

University of Minnesota-Duluth

5013 Miller Trunk Highway

Duluth, Minnesota 55811

and

Joan Elias and David VanderMeulen*

National Park Service

Great Lakes Inventory and Monitoring Network 

2800 Lake Shore Drive East

Ashland, Wisconsin 54806

* Contact author: david_vandermeulen@nps.gov

September 2015

Suggested citation: 

Axler, R., E. Ruzycki, J. Elias, and D. VanderMeulen. 2015. Standard operating procedure #1: Preseason preparation. In J. E. Elias, R. Axler, E. Ruzycki, and D. VanderMeulen. 2015. Water quality 

monitoring protocol for inland lakes: Great Lakes Inventory and Monitoring Network, version 1.1. 

Natural Resource Report NPS/GLKN/NRR—2015/1027. National Park Service, Fort Collins, 

Colorado.

Standard Operating Procedure #1: Pre-Season Preparation, Version 1.1 September 2015

Water Quality Monitoring Protocol for Inland Lakes, Version 1.1 i

SOP1 – Contents

Page

Revision History Log............................................................................................................................iii

Acknowledgements...............................................................................................................................iii

1.0 Introduction......................................................................................................................................1

1.1 Read the Entire Protocol ..................................................................................................................3

1.2 Prepare Calendar of Planned Field Sampling ..................................................................................3

1.3 Review Checklists of Equipment and Supplies ...............................................................................5

1.4 Confirm/Apply/Renew Research and Collecting Permits ...............................................................5

1.5 Review Sample Collection, Processing, and Documentation ..........................................................5

1.6 Update Field and Office Binders .....................................................................................................5

1.7 Clean and Test Equipment...............................................................................................................7

1.8 Vehicle, Boat, and Safety Gear........................................................................................................7

1.9 Training and Safety..........................................................................................................................7

1.10 Field Reconnaissance.....................................................................................................................8

1.11 Travel Arrangements .....................................................................................................................9

1.12 Communicate with Supervisor.......................................................................................................9

1.13 Equipment Blanks..........................................................................................................................9

1.14 Literature Cited ............................................................................................................................11

SOP1 – Tables

Page

Table 1. Checklist of activities to be conducted prior to sampling inland lakes. ..................................1

Table 2. Example of calendar of planned field sampling......................................................................3

Table 3. Checklists of equipment and supplies for monitoring water quality of inland 

lakes. ......................................................................................................................................................5

Standard Operating Procedure #1: Pre-Season Preparation, Version 1.1 September 2015

Water Quality Monitoring Protocol for Inland Lakes, Version 1.1 iii

Revision History Log

The following table lists all edits and amendments to this document since the original publication 

date. Information entered in the log must be complete and concise. Users of this standard operating 

procedure will promptly notify the project manager and/or the Great Lakes Network (GLKN) data 

manager about recommended and required changes. The project manager must review and 

incorporate all changes, complete the revision history log, and change the date and version number 

on the title page and in the header of the document file. For complete instructions, please refer to 

Revising the Protocol, SOP #13. 

Revision History Log:

Previous 

Version 

#

Revision 

Date

Author (with 

title and 

affiliation)

Location in Document 

and Concise 

Description of Revision Reason for Change

New 

Version 

#

1.0 5/01/2015 David 

VanderMeulen, 

GLKN

updated the NPS contact 

author, minor edits to 

Table 2, updated the web 

link for obtaining a 

Research and Collecting 

Permit, added references 

to GLKN and park 

Safety Plans, fixed a 

handful of grammatical 

errors throughout

To clarify and update 

SOP based on changes 

that have occurred 

since Version 1.0 was 

published in 2008

1.1

Add rows as needed for each change or set of changes tied to an updated version number

Acknowledgements

We relied upon documents by O’Ney (2005) and the U.S. Geological Survey (USGS 2005) for 

guidance in writing this standard operating procedure.

Standard Operating Procedure #1: Pre-Season Preparation, Version 1.1 September 2015

Water Quality Monitoring Protocol for Inland Lakes, Version 1.1 1

1.0 Introduction

Prior to the field season, many preparations must be completed to ensure sampling can be undertaken 

according to schedule. The field season for sampling inland lakes of the Great Lakes Inventory and 

Monitoring Network (Network) parks is generally from May through October. All details for the 

season need to be planned well in advance. Field preparations should begin in January to allow 

enough time for ordering new supplies and equipment, if necessary. Table 1 provides a checklist and 

general guidance for activities conducted prior to sampling. Many of these activities are discussed in 

more detail in other SOPs.

Table 1. Checklist of activities to be conducted prior to sampling inland lakes.

√ Activity Description

Prepare calendar of planned field trips Includes sampling dates, locations, personnel

Review sampling methods to determine if 

revision is needed 

Check web reference to see if method has been updated 

from version currently used 

Review checklists of equipment and 

supplies required; prepare list of items to be 

ordered

Check each Standard Operating Procedure for detailed 

equipment lists; check expiration dates of reagents, 

standards, and other chemicals 

Order supplies 

Includes calibration standards, pre-cleaned bottles for 

sample collection (if not provided by the contract analytical 

laboratory) , sample preservation solutions 

Clean and test equipment; charge or 

replace batteries as needed 

Includes multiparameter sonde, integrated sampling tube, 

Van Dorn, back-up instruments, ropes, thermometers, 

camera, GPS unit, cell phone or radio 

Ensure the latest versions of software are 

being used Includes mulitparameter sonde, data-logger, computer

Prepare equipment blanks Must be done annually 

Obtain permission for site access, if 

necessary 

Confirm current park research and 

collection permits 

Check field vehicle and boat for safety 

equipment and supplies 

Includes material safety data sheets, flares, flashlight, 

gloves, extra sampling bottles, etc.

Schedule boat training, if necessary

Update field folder Include maps, site information, field forms, sampling 

procedures 

Prepare headers on field data forms, chain 

of custody forms, analytical service request 

forms, bottle labels

Header information should be cross-checked with metadata 

to permit entry into NPSTORET 

Review sample collection, processing, and 

documentation information 

Includes methods, lab codes, bottle type, and sample 

collection and processing procedures; sample shipment; 

quality control samples. (SOPs #6 and #7) 

Make travel reservations and arrangements 

as needed 

Provide supervisor with schedule 

Standard Operating Procedure #1: Pre-Season Preparation, Version 1.1 September 2015

Water Quality Monitoring Protocol for Inland Lakes, Version 1.1 3

1.1 Read the Entire Protocol

Periodically read through the entire protocol, including all standard operating procedures (SOPs). Be 

sure to understand the purpose for which the various types of data will be collected and review the 

SOPs for the types of measurements and samples needed. Be alert for portions of the protocol or 

SOPs that may be in need of revision, and bring these sections to the attention of the appropriate 

supervisor.

1.2 Prepare Calendar of Planned Field Sampling

Well in advance of the field season, prepare a calendar of sampling dates for the entire season. Allow 

for the possibility of bad weather days, when sampling may have to be postponed. Include the 

location of sampling, dates, parameters to be measured, personnel, and any additional relevant notes 

(Table 2).

Table 2. Example of calendar of planned field sampling.

Location Sampling Dates WQ Variables Personnel Notes

Indiana Dunes May 1-5 core suite, chl a, TP, TN, 

NO2+NO3-N, NH4-N, 

park biotechs

Indiana Dunes July 1-5 core suite, chl a, TP, TN, 

NO2+NO3-N, NH4-N, alk, 

cations, anions, DOC

park biotechs include advanced suite; 

collect bottom water sample 

for analysis of TP/TN if lakes 

are stratified

Indiana Dunes Sep. 1-5 core suite, chl a, TP, TN, 

NO2+NO3-N, NH4-N, 

park biotechs

Voyageurs June 10-25 core suite, chl a, TP, TN, 

NO2+NO3-N, NH4-N, DOC

LeDuc,

park biotech

Voyageurs July15 - 30 core suite, chl a, TP, TN, 

NO2+NO3-N, NH4-N, alk, 

cations, anions, DOC

LeDuc,

park biotech

include advance suite; collect 

bottom water sample for 

analysis of TP/TN if lakes are 

stratified

Voyageurs Aug. 15- 30 core suite, chl a, TP, TN, 

NO2+NO3-N, NH4-N, DOC

LeDuc,

park biotech

Standard Operating Procedure #1: Pre-Season Preparation, Version 1.1 September 2015

Water Quality Monitoring Protocol for Inland Lakes, Version 1.1 5

1.3 Review Checklists of Equipment and Supplies

Checklists help ensure that equipment and supplies will be ordered on time, data collection activities 

will be completed appropriately, and data quality objectives will be met. Review the detailed 

equipment lists that are included with each standard operating procedure (Table 3). Pay attention to 

expiration dates on reagents, calibration standards, and all other chemicals. Prepare a list of 

equipment and supplies that must be ordered and present it to the project manager.

Table 3. Checklists of equipment and supplies for monitoring 

water quality of inland lakes.

Checklist Location

Safety equipment checklist SOP #2

Decontamination equipment and supplies SOP #5

Field supplies and equipment checklist SOP #6

Laboratory equipment and supplies SOP #7

1.4 Confirm/Apply/Renew Research and Collecting Permits 

For sampling stations located within park boundaries, a Research and Collecting Permit must be 

obtained before any work can be done. To renew or apply for the permit, go to the following website: 

https://irma.nps.gov/rprs/Investigator/Index

Follow the directions for renewing an existing permit, or if your project is not already in the system, 

then follow the directions to apply for a new permit. Work with the research coordinator at each park.

1.5 Review Sample Collection, Processing, and 

Documentation

Conduct a thorough review of “Field Measurements and Water Sample Collection” (SOP #6) and

“Processing Water Samples and Analytical Laboratory Requirements” (SOP #7).

Check with the project leader to determine current contract analytical laboratory information. 

Contact the laboratory to verify lab codes and procedures. Obtain copies of Analytical Services 

Request (ASR) and Chain of Custody (COC) Forms.

1.6 Update Field and Office Binders

Field binders should contain reference information specific to each sampling station, including maps, 

photos, previous data, field forms, and summaries of sampling and quality assurance/quality control 

(QA/QC) procedures. The office binder should contain reference information relevant to general field 

sampling procedures, including QA/QC reminders, copies of all SOPs relating to safety, 
Standard Operating Procedure #1: Pre-Season Preparation, Version 1.1 September 2015

Water Quality Monitoring Protocol for Inland Lakes, Version 1.1 6

decontamination, sample collection and processing, copies of equipment instructions and 

troubleshooting, calibration logs, Material Safety Data Sheets (MSDSs), and ASR and COC forms. 

The field binder should be taken along on each sampling trip. 

Each year, prior to the sampling season, the field binder for each monitoring site should be reviewed 

and the following information updated as needed: 

 Location of lake level gage or benchmark (if one is present).

 Location of sample-collection sites. Review field notes for any indication that the location 

for sample collection may need revision. Update protocol if necessary. 

 Name of landowner, tenant, or other responsible party. If the sampling station is located on 

private land, ownership may change. Verify. 

 Current copy of research and collection permit (if site located within NPS boundaries). 

Check dates on permit. Renew/apply as described above. 

 Site access instructions (for example, call owner or site operator before arrival at site, obtain 

key to unlock security gate). Confirm contact person, procedure, and phone numbers. 

 Photographs to document site conditions. Take new digital photograph annually. 

 Maps to site (state and local). Review map for accuracy; update if necessary. 

 Review previously collected chemical, physical, and biological data. A summary of 

previously-collected data or copies of previous field data sheets should be in the field folder 

so that water column profiles and Secchi data can be compared to previous surveys. 

Familiarity with previously collected data is a critical quality assurance (QA) element for 

early detection of possible instrument malfunction.

 Summaries of field procedures, QA/QC procedures, instrument stabilization criteria, etc.

Prepare brief outlines reminding field personnel of routine procedures, including all changes 

from the previous year.

Each year, prior to the sampling season, the office binder should be reviewed and the following 

information updated as needed: 

 Safety information (SOP #2). Verify/update “Medical Information Form for Field Personnel” 

and “Emergency Contact Form”. 

 Sampling schedule and instructions. Ensure the following information from SOP #6 (Field

Measurements and Water Sample Collection) is included in the office binder: laboratory 

analyses to be requested and associated codes, when to collect samples, bottle types needed 

for each analytical schedule, preservation requirements, quality control sample requirements, 
Standard Operating Procedure #1: Pre-Season Preparation, Version 1.1 September 2015

Water Quality Monitoring Protocol for Inland Lakes, Version 1.1 7

and shipping instructions. Verify information is correct and report and reconcile any 

discrepancies to supervisor. 

 Decontamination procedures (SOP #5). Ensure that the most recent information on presence 

of exotic species and need for decontamination of equipment has been incorporated into the 

Hazard Analysis and Critical Control Plan (HACCP) for each park. Update office binder with 

the latest information. If the order of lakes to be sampled must change due to new 

infestations, be sure sampling schedule is updated.

 Analytical service request forms, data collection field forms, chain of custody forms, sample 

bottle labels. Prepare as much of the field forms as possible in advance. For each station, 

complete the header information, including the project ID, station ID and station name and 

other required metadata for NPSTORET. Place enough blank field forms in office folder to 

last entire field season.

 Ensure that copies of the current field procedures are included in the office folder. Include 

calibration and maintenance procedures specific to the instruments to be used.

1.7 Clean and Test Equipment

Clean and test all sampling equipment, including multiparameter sonde, temperature sensors, Van 

Dorn and integrated tube samplers, camera, GPS units, and any back-up meters. Check calibration of 

metered ropes to ensure accurate depth measures. Start each new field season with fresh batteries and 

replace spares in field tool kit. Ensure the latest versions of software are loaded onto the multi-probe, 

data-logger, and computer.

1.8 Vehicle, Boat, and Safety Gear

Check maintenance schedule of field vehicle and arrange maintenance, if needed. Check boats and 

vehicle for safety equipment such as MSDS sheets, flares, spare tire, triangles, cones, first aid kit. 

Prepare a list of supplies needed and present list to supervisor. If using a trailer, ensure that tail-lights 

are in working order. Check that field tool-kit is complete and replace tools, as needed.

1.9 Training and Safety

Keep current with training and the laboratory requirements associated with your data collection 

activities. New technicians will need basic skills training, including classroom instruction, hands-on 

training, and pilot-testing of equipment. Continuing field staff should attend refresher training and 

review Network and park safety plans annually. If boat training is needed, be sure to schedule the 

training with the park early in the season. Initial and periodic refresher courses in basic first aid and 

CPR are required.
Standard Operating Procedure #1: Pre-Season Preparation, Version 1.1 September 2015

Water Quality Monitoring Protocol for Inland Lakes, Version 1.1 8

1.10 Field Reconnaissance

Make field reconnaissance trips, if possible. Visit the sampling sites to be sure that conditions have 

not changed from the previous year. Note conditions that could affect sampling operations, such as 

the seasonal high or low water levels, or site access peculiarities. In parks where lakes are accessible 

via roads, ensure all roads are passable and landing areas are accessible. In cases where lakes are not 

accessible via roads, communicate with park backcountry staff to learn of potential trail closings or 

other hindrances to sampling. When boats or canoes will be kept at certain lakes for the season, work 

with park staff to get the boats/canoes on site, hidden (if necessary), and secure.
Standard Operating Procedure #1: Pre-Season Preparation, Version 1.1 September 2015

Water Quality Monitoring Protocol for Inland Lakes, Version 1.1 9

1.11 Travel Arrangements

Make travel arrangements. Because hotel and campground reservations may be difficult to 

impossible to obtain at certain times of year, it is important to review the sampling schedule and plan 

ahead. Submit park housing requests well in advance of the sampling season.

1.12 Communicate with Supervisor

Ensure the project manager is informed of supply needs, problems with instruments, changes in 

sampling schedule, changes in sampling site conditions, and other needs that may have an impact on 

the project budget, data collection, schedule, or sampling design.

1.13 Equipment Blanks

An equipment blank should be conducted annually at each park where sampling is scheduled, at least 

four weeks prior to using the equipment in the field to ensure adequate time for analysis and review 

of results. Equipment blanks should be collected in a designated clean area of the sample processing

laboratory. The blank consists of deionized water that is passed sequentially through each component 

of the sample collection and processing equipment. Equipment blanks should also be conducted 

when a new cleaning procedure is instituted and when new equipment will be used for the first time.

Procedure 

 Fill the integrated sampling tube or Van Dorn with deionized water (DIW).

 Dispense water from integrating tube or Van Dorn into cubitainer or carboy.

 From cubitainer or carboy, dispense water directly into appropriate analyte bottles, or filter 

first, according to instructions for each analyte (SOP #7).

 Preserve samples according to instructions for each analyte in SOP #7.

If the equipment-blank data indicate that the equipment does not introduce contaminants that will 

bias study results, sampling can proceed. If the equipment-blank data indicate unacceptable 

concentrations of analytes of interest, the cause must be identified and the equipment or cleaning 

procedures must be changed or modified before sampling can proceed. 

Standard Operating Procedure #1: Pre-Season Preparation, Version 1.1 September 2015

Water Quality Monitoring Protocol for Inland Lakes, Version 1.1 11

1.14 Literature Cited

O’Ney, S.E. 2005. Standard operating procedure #2: Pre-season activities, Version 1.0. In Regulatory 

water quality monitoring protocol, Version 1.0, Appendix E. Bozeman (MT): National Park 

Service, Greater Yellowstone Network. 

USGS. 2005. National field manual for the collection of water-quality data: U.S. Geological Survey 

Techniques for Water-Resources Investigations, book 9, chaps. A1-A9.

Standard Operating Procedure #2: Training and 

Safety

Version 1.1

In Water Quality Monitoring Protocol for Inland Lakes

Prepared by

Joan Elias and David VanderMeulen*

National Park Service

Great Lakes Inventory and Monitoring Network 

2800 Lake Shore Drive East

Ashland, Wisconsin 54806

* Contact author: david_vandermeulen@nps.gov

September 2015

Suggested citation: 

Elias, J. E. and D. VanderMeulen. 2015. Standard operating procedure #2: Training and safety. In J. 

E. Elias, R. Axler, E. Ruzycki, and D. VanderMeulen. 2015. Water quality monitoring protocol for 

inland lakes: Great Lakes Inventory and Monitoring Network, version 1.1. Natural Resource Report 

NPS/GLKN/NRR—2015/1027. National Park Service, Fort Collins, Colorado.

Standard Operating Procedure #2: Training and Safety, Version 1.1 September 2015

Water Quality Monitoring Protocol for Inland Lakes, Version 1.1 i

 

SOP2 – Contents

Page

Revision History Log............................................................................................................................iii

Acknowledgements...............................................................................................................................iii

2.0 Introduction......................................................................................................................................1

2.1 Pre-Season Classroom Training.......................................................................................................1

2.2 Hands-On Training ..........................................................................................................................3

2.3 Safety Procedures.............................................................................................................................5

2.4 Literature Cited ..............................................................................................................................15

Appendix 1. Emergency Contact and Medical Form...........................................................................17

SOP2 – Tables

Page

Table 1. General safety equipment for field work...............................................................................10

Table 2. Personal protective equipment for laboratory and field work...............................................11

Table 3. Checklists for vehicles and vehicular laboratories................................................................12

Table 4. Checklists for the use of watercraft.......................................................................................13

Standard Operating Procedure #2: Training and Safety, Version 1.1 September 2015

Water Quality Monitoring Protocol for Inland Lakes, Version 1.1 iii

 

Revision History Log

The following table lists all edits and amendments to this document since the original publication 

date. Information entered in the log must be complete and concise. Users of this standard operating 

procedure will promptly notify the project manager and/or the Great Lakes Network (GLKN) data 

manager about recommended and required changes. The project manager must review and 

incorporate all changes, complete the revision history log, and change the date and version number 

on the title page and in the header of the document file. For complete instructions, please refer to 

Revising the Protocol, SOP #13.

Revision History Log:

Previous 

Version 

#

Revision 

Date

Author (with 

title and 

affiliation)

Location in Document 

and Concise 

Description of Revision Reason for Change

New 

Version 

#

1.0 5/01/2015 David 

VanderMeulen, 

GLKN

Updated the NPS contact 

author, added a number 

of sections taken directly 

from the Great Lakes 

Network Health and 

Safety Plan, included use 

of a stadia rod and hand 

level to measure water 

level, fixed a handful of 

grammatical errors 

throughout

To clarify and update 

SOP based on changes 

that have occurred 

since Version 1.0 was 

published in 2008

1.1

Add rows as needed for each change or set of changes tied to an updated version number

Acknowledgements

The safety related portions of this standard operating procedure were adapted from the Great Lakes 

Network Health and Safety plan (Route et al. 2013) and the Greater Yellowstone Network’s SOP on 

safety (O’Ney 2005), with heavy reliance on the U.S. Geological Survey’s manual for collecting 

water quality data (Lane and Fay 1997).

Standard Operating Procedure #2: Training and Safety, Version 1.1 September 2015

Water Quality Monitoring Protocol for Inland Lakes, Version 1.1 1

2.0 Introduction

Prior to collecting data and water samples in the field, the field crew members must be trained in the 

techniques and procedures that will be used throughout the season. Familiarity with the protocol and 

standard operating procedures (SOPs), as well as with boats, equipment, and basic safety standards, 

are critical to the success of the water quality monitoring program. This SOP includes procedures for 

training in the specific water quality related skills and knowledge necessary for collecting good data 

and understanding those data. The crew must be also trained in specific safety procedures to ensure 

their safety and that of others.

The project manager will conduct or arrange for all training needed prior to the field season.

2.1 Pre-Season Classroom Training

Periodically read through the entire protocol, including all standard operating procedures (SOPs). Be 

sure to understand the purpose for which the various types of data will be collected and review the 

SOPs for the types of measurements and samples needed. Be alert for portions of the protocol or 

SOPs that may be in need of revision, and bring these sections to the attention of the appropriate 

supervisor.

It is desirable to begin training well before the field season begins to allow adequate time for 

thorough understanding of field and laboratory procedures and to obtain certification in boat use. 

Field crew leaders must undergo all of the following training. Training in boat use is highly 

recommended for other field crew members, and training in the remaining areas is desirable.

2.1.1 Limnological Concepts

An understanding of basic limnological concepts is useful for recognizing bad or illogical data in the 

field. For example, a dissolved oxygen reading of 30 mg/L may indicate a malfunction of the 

multiparameter sensor, or something as simple as fouling of the probe. Recognition of the problem at 

the time it occurs allows for immediate adjustment in the field, for example cleaning the membrane 

on the probe or changing the batteries, so that good data can still be collected.

The field crew leaders, and if possible, other crew members, will study select modules of the Water 

on the Web (2004) curricula (http://waterontheweb.org/curricula). The modules will be selected by 

the project manager and will include those on lake surveys (e.g., field profiles, sample collection, 

laboratory methods). Individual study will be followed with group discussion and/or individual 

discussion with the project manager or a limnologist.

2.1.2 Understanding the Protocol and Standard Operating Procedures

Reading and understanding the entire protocol and all SOPs are crucial prior to initiating field work. 

The project manager will allow adequate time for all field crew members to complete this step to 

ensure success of the project. Field and laboratory related SOPs will also be covered as part of the 

hands-on training, described below.
Standard Operating Procedure #2: Training and Safety, Version 1.1 September 2015

Water Quality Monitoring Protocol for Inland Lakes, Version 1.1 2

 

2.1.3 First Aid and Cardiopulmonary Resuscitation (CPR)

Training in the basic medic/first aid and Heartsaver AED, which includes CPR and use of an 

automated external defibrillator (AED), is required for all crew members (Route et al. 2013) and will 

be paid for by the Network. Acceptable training should be through the American Red Cross or 

American Heart Association. Certification is valid for two years. Training and certification should be 

acquired prior to the field season.
Standard Operating Procedure #2: Training and Safety, Version 1.1 September 2015

Water Quality Monitoring Protocol for Inland Lakes, Version 1.1 3

2.2 Hands-On Training

In addition to the classroom training described above, a variety of hands-on training and practice 

prior to the first sampling period will help ensure high quality data collection. Familiarity with the 

use and maintenance of equipment, procedures for collecting and processing water samples, 

techniques for cleaning field and laboratory equipment, and safe use of watercraft are essential to the 

success of the water quality monitoring project. Field crew leaders are required to complete all of the 

following training; other field crew members should also complete the training, if possible, although 

it is not required.

2.2.1 Use of a Multisensor Water Quality Instrument

Each type of multisensor instrument comes with specific instructions on use and care. Guidelines for 

calibration and use of multisensor instruments are included in SOP #6, however it is important to use 

the instruction manual specific to each instrument. Check the manufacturers’ websites for updates or 

changes to instructions. 

Training in the use of a multisensor instrument will include the following:

 calibration procedures and acceptance criteria

 keeping a calibration log

 maintenance, including replacing fluids and membranes

 creating files on the data logger

 storing data on the data logger

 downloading data to a laptop computer

 use of the instrument in a field setting, including depth profiles and equilibration

 troubleshooting

Crew members will have the opportunity to practice the skills learned prior to the actual sampling 

until they are comfortable with the use of the instrument.

2.2.2 Use of a Global Positioning System (GPS)

Location information must be gathered via GPS for each site during each visit. Training in the use of 

a GPS will include navigation to a known location, acquiring location information, storing data, and 

downloading data. Details on the use of a GPS can be found in SOP #3.

2.2.3 Field Methods

In addition to collecting data with the multisensor instrument, a field data sheet must be completed, a 

water sample must be collected, and the water level must be determined at each site. Prior to the field 

season, the field crew will receive training in and have the opportunity to practice the following:

 completing the field data sheet

 using an integrated sampling tube

 using a Van Dorn sampler
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 measuring water level by reading a staff gage or through use of a stadia rod and hand level 

(SOP #4)

 decontaminating equipment between lakes to avoid transfer of species from one lake to 

another, and determining when decontamination is necessary

 following QA/QC procedures

2.2.4 Processing Water Samples

Whether the water samples are processed for further analytical laboratory analysis in the field or back 

at the office or lab, strict procedures must be adhered to (see SOP #7). Crew members will be trained 

in, and will have the opportunity to practice the following techniques:

 handling water samples so as to avoid contamination

 rinsing and filling bottles from the analytical laboratory

 preserving samples for various chemical analyses

 filtering samples for various analyses

 packing samples for shipment to analytical laboratory

 filling out chain of custody forms

 following QA/QC procedures

2.2.5 Cleaning Field and Laboratory Equipment

Field and laboratory equipment must be cleaned between lakes or samples to avoid contamination 

with water from the previous sampling site. Training in proper techniques will include:

 cleaning equipment with P-free detergent

 setting up an acid bath

 cleaning equipment with an acid bath

 rinsing with distilled or de-ionized water

2.2.6 Boat Training

Prior to operating a NPS boat or canoe, training and certification are required (Route et al. 2013).

The crew leader must receive the training and obtain certification, and it is highly desirable for the 

remaining crew members to do so as well. The project manager will arrange for training prior to the 

field season through one of the several GLKN parks that offer it. Arrangements should be made well 

in advance of the field season.
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2.3 Safety Procedures

Safety of personnel should always be the first concern in conducting a monitoring program and in the 

selection of sampling sites. General safety considerations for work in the office, field, and laboratory, 

as well as a discussion of other issues such as prevention of accidents and injuries and 

communication procedures are discussed in the Great Lakes Network Health and Safety Plan (Route 

et al. 2013) and GLKN’s Laboratory Safety Plan. 

Numerous safety issues and concerns are associated with implementing a water quality monitoring 

program that includes extensive field work and sampling. Field personnel routinely come into direct 

and indirect contact with waterborne pathogens, chemicals, and potentially hazardous plants and 

animals. Field work requires an awareness of potential hazards (i.e., situational awareness) and 

knowledge of basic safety procedures. Advanced planning can reduce or eliminate many safety 

hazards. 

2.3.1 USGS Field Manual

This SOP is meant to be used in conjunction with Chapter A9 of the USGS National Field Manual 

(Lane and Fay 1997), which contains more complete information about potential hazards that water 

quality monitoring field personnel may encounter during field work and the procedures that, when 

implemented properly, will help ensure the safety and health of field crew members. A copy of this 

manual is provided to the field crew and may be downloaded from 

http://water.usgs.gov/owq/FieldManual/Chap9/content.html. Topics addressed in the USGS 

document include: 

 general references for federal policies and Department of Interior (DOI) safety guidelines 

 safety policies you are required to know and follow under the Occupational Safety and 

Health Act (OSHA), Environmental Protection Agency (EPA), and Department of 

Transportation (DOT);

 understanding and implementing a job hazard analysis (JHA);

 requirements related to use of personal protective equipment (PPE) on the job

 safety training and certification requirements; safety issues associated with transportation and 

operation of vehicles (road vehicles and trailers, watercraft, aircraft etc.) used to reach 

sampling sites

 surface water activities (e.g., wading, working from bridges, boats and cableways, etc.)

 working around machinery, pumps, and other equipment

 proper use, handling, transport, storage, and disposal of chemicals 

 handling of contaminated water and limiting exposure to yourself and others

 environmental conditions caused by extremes in temperature; sun exposure; threats posed by 

storms, floods, fire, snow, ice, and various animals and plants

In addition to consulting the USGS manual, the field crew should contact individual park’s safety 

officers or resource managers for information on park safety plans, radio safety procedures, and local 
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problems and issues, such as dangerous or nuisance animals (e.g., black bears at VOYA, red fox at 

ISRO), insect-and tick-borne diseases (e.g., Lyme disease, encephalitis, West Nile disease), and other 

issues specific to each park. 

2.3.2 Basic Fieldwork Safety Preparation 

2.3.2.1 Crew Size

Basic preparations for fieldwork should become routine before every sampling activity. The 

minimum recommended crew size for field projects is two people. Working alone in the field may be 

allowed if authorized in advance by your supervisor. For example, it may be necessary for boat 

operators to travel alone and complete field tasks between pickups and drop offs of other crews. If it 

is absolutely necessary for a person to work in the field alone, this person must:

 Have verbal authorization from your supervisor

 Carry two forms of reliable communication (e.g. radio and cell phone)

 Communicate periodically with co-workers or radio dispatch about planned travel routes, and 

times of departure and return to key locations.

2.3.2.2 Safety Gear and Information

Carry basic safety equipment, including first aid kit, flashlight, boots, rain gear, antibacterial soap or 

hand cleaner, matches or lighter, etc. Be aware of changing weather conditions and the potential for 

storms. Be aware of potential hazards at a monitoring site. Carry general safety information in each 

vehicle or boat, including: 

 safety data sheets (formerly referred to as material safety data sheets) for preservatives 

 basic first aid protocols 

 emergency phone numbers 

 locations of emergency facilities (hospitals, police and fire departments, U.S. Coast Guard) 

 maps of the park, surrounding area, and nearest city

Job hazard analyses (JHAs), prepared by the aquatic ecologist, will be discussed with field personnel 

prior to the field season. The JHAs will cover such topics as hiking and portaging, boating and 

sampling from a boat/canoe, lab safety, driving vehicles, and stinging insects and poisonous plants.

The next two topics, Trip Plans and Methods of Communication, cover many aspects of fieldwork 

preparation, and are nearly verbatim from the Great Lakes Network Health and Safety Plan (Route et 

al. 2013).

2.3.2.3 Trip Plans

For safety purposes, it is critical that certain park staff be aware of fieldwork being conducted in their 

park by the Network. Network employees are required to set up a chain of communication and 

provide the park with essential information regarding Network activities––herein referred to as a 

“Trip Plan.” For front-country fieldwork this can be as simple as an informal email to the host park’s 

primary contact and cc’d to your supervisor. It can also be a radio message to park dispatch 
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following a park’s procedures for boat operations. All trip plans must include who will be involved 

in the fieldwork, when the fieldwork will take place, what mode of transportation you have, where

the work will be performed, and how you can be communicated with. For example an informal 

email:

To: Park Contact

cc: Joe Supervisor. 

I and Jane Doe will be in your park tomorrow, 6/15/2013, to conduct water quality 

monitoring at Pristine Lake from approximately 10:00 AM until 2:00 PM. We will park our 

NPS vehicle at the boat ramp for Big Lake, boat to the dock at Grassy Campground, and 

portage a canoe to Pristine Lake using Rocky Portage Trail. I will have a cell phone (###-

###-####) and a park radio, but the radio will be off unless I have an emergency.

Such an email is not only a good way of providing essential safety information, it is good policy for 

keeping the park informed of our activities.

For all backcountry trips, or for fieldwork spread over several days, a more formal trip plan should be 

filed. The Network program manager is responsible for ensuring the trip plan meets the host park’s 

need for detail and flow of communication. Refer to Appendix H of the Great Lakes Network Health 

and Safety Plan (Route et al. 2013) or the Network SharePoint site under the Safety folder for an 

example template of a trip plan. 

All trip plans should consider the following guidelines and standards: 

 A trip leader must be identified when more than one person is involved. 

 The trip leader must file a trip plan with the host park and his/her supervisor or delegate. 

 The supervisor is responsible for the flow of communication internally within the Network. 

 A primary contact will be established with the host park through the park’s chief ranger or 

superintendent. This is the responsibility of the project supervisor, but may be coordinated 

more broadly by the Network program manager. The chief ranger or superintendent may 

delegate a primary contact.

 The park’s primary contact is responsible for establishing the park’s internal 

communications, ensuring Network trip plans are available to park staff, and if necessary, 

initiating an emergency response according to park policy. In parks where there is a 

dispatcher, it is the responsibility of the park’s primary contact to see that all dispatchers are 

aware of Network activities.

 The park resource manager/biologist will be informed of Network activities and is often 

delegated as the primary contact.

 For backcountry trips, the trip leader will post the trip plan on the Network SharePoint site 

under the Safety folder (http://imnetsharepoint/glkn/safety/default.aspx). Depending on the 
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complexity and inherent dangers of the fieldwork, supplemental information like GPS 

coordinates for sites or maps of survey areas will also be posted to the SharePoint. 

 Check-ins may be required by the park. If required, the timing and frequency should be 

documented in the trip plan. 

 One trip plan can cover an entire field season, but the plan should clearly outline the 

inclusive dates of discrete field efforts. 

 If plans change to such a degree that someone would be unable to easily locate the crew, the 

trip leader should inform the park as soon as practicable. 

2.3.2.4 Methods of Communication

Field crews must have at least two methods of communication and should determine the most 

effective methods in consultation with their supervisor and the park prior to the trip. The methods 

will vary by park and situation, but the most common will be a portable two-way park radio (for 

parks using radio systems) and either a cell phone or a satellite phone. For urban parks, this can be 

two cell phones (best if they have different carriers to increase the chance of reception), or a cell 

phone and a satellite phone. Park staff should be consulted regarding ‘dead zones’ in radio and cell 

coverage. All GLKN vessels on the Great Lakes will have a park radio and a marine-band radio 

mounted in the cabin. 

For remote situations on land, crew leaders will also carry a Spot Locator. In the event a radio is not 

working properly it can be used to send an email to select individuals and/or request immediate 

emergency response. For boating on the Great Lakes, all GLKN vessels over 18 feet will be equipped 

with an emergency position-indicating radio beacon (EPIRB). The EPIRB is preprogrammed to send 

an emergency message to the U.S. Coast Guard. 

SOPs for contacts, using portable radios, Spot locator devices, and satellite phones are available 

within the Great Lakes Network Health and Safety Plan (Route et al. 2013). Supervisors are required 

to provide hands-on training with crew members on use of devices that will be used during their field 

work. 

2.3.3 Emergency Medical Forms and Information

In a true emergency, get the patient to medical care immediately and worry about forms, payments, 

and other procedures after the situation has been stabilized. For all non-emergency medical 

treatments, you must have your supervisor authorize medical treatment and complete a CA-16 form 

(Authorization for Exam/Treatment) and submit this form to the medical provider. If your supervisor 

is unavailable and you cannot wait for the treatment, call the Network office or the park and someone 

should be able to authorize treatment.

Accidents and/or injuries that occur on the job must be reported on either a CA-1 (Federal 

Employee's Notice of Traumatic Injury and Claim for Continuation of Pay/Compensation) or CA-2 

(Federal Employee's Notice of Occupational Disease and Claim for Compensation) filled out on the 

Safety Management Information System (SMIS) website: https:/www.smis.doi.gov. The injured 

employee fills out the form online and the supervisor is notified by email that his/her portion of the 
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claim is ready to be filled out. Once completed by the supervisor, the claim is forwarded to the 

Midwest Region claims coordinator who reviews and forwards the claim to the Office of Worker’s 

Compensation Program (OWCP). 

The following paper forms can aid in gathering information for reporting an accident and/or injury 

that occurred on the job and can be obtained from the U.S. Office of Personnel Management (OPM) 

website (http://www.opm.gov/). 

 You may need to provide OWCP1500 “Health Insurance Claim Form” to your provider. 

 If you require time off work you must complete form CA-17. Your supervisor must fill out 

the first portion describing your work duties. The treating physician should then complete the 

second portion of the CA-17, stating what tasks you cannot perform.

 For reference see CA-10 “What a Federal Employee Should Do When Injured At Work.”

Employees have a reasonable expectation of privacy; however, the NPS is responsible for assisting 

employees in the event of a medical emergency. To do so, we must be aware of allergies, 

prescription medications, or other medical conditions that would help emergency medical technicians 

and physicians perform their duties. All Network employees have the option to complete a Medical 

Information Form (Appendix 1) that informs their supervisor of medical conditions that could affect 

their health and well-being. Employees who prefer not to share this information must still sign and 

submit a Medical Information Form to their supervisor, indicating their preference. The original copy 

will be placed in a sealed blue envelope by the employee and kept in a locked drawer in the Network 

administrative office. For employees who are in the field, a copy of this form will be kept by the 

supervisor or crew leader in a sealed blue envelope. These sealed envelopes will be opened only in 

an emergency. They will be shredded by the employee at the end of employment.

2.3.4 Safety Equipment Checklists

Checklists are helpful for ensuring that personnel have the appropriate safety equipment available 

during field trips. Items shown in Tables 1 through 4 are the basic necessities for field work. Field 

crew members should consider their specific needs and should customize the checklists as necessary. 

The field crew and project manager will discuss the checklists and determine which items are 

necessary.

Personal Protective Equipment (PPE) (Table 2) must be selected based on the hazards likely to be 

encountered. The Great Lakes Network is required to supply appropriate PPE, and field personnel are 

required to use it. 
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Table 1. General safety equipment for field work.

 Basic Safety Equipment Checklist

Waders, hip boots, rubber knee boots 

Personal floatation device (PFD) 

First aid kit 

Fire extinguisher 

Flashlight and spare batteries 

Communication devices (Park radio, cellular or satellite phone, SPOT locator)

Rain gear 

Hat, sun screen, and sunglasses 

Drinking water or sports drinks 

Safety cones, orange safety vest (working on bridges) 

Tool box with basic tools 

Antibacterial soap or hand cleaner 

Spill kits (for preservatives) 

Material safety data sheets (MSDS) for preservatives 

Hand-held eye wash 

Protective safety glasses or goggles 

Container to carry preservatives 

List of emergency phone numbers and office contacts 
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Table 2. Personal protective equipment for laboratory and field work.

 Chemical and disease protection

Aprons 

Eye/Face splash guards 

Gloves (vinyl and/or latex or nitrile) 

Protective suits 

Respirators (certification required for use) 

 Weather and UV protection

Boots 

Fluids (e.g., water, sports drinks) 

Hat with a brim

Insect repellent 

Rain gear 

Sunglasses 

Sunscreen 

Temperature-modifying clothing 

Work gloves

 Flotation and reflective protection

Orange flotation vests and jackets 

Safety harness 

 Protection for working around boat motors

Hearing protection
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Table 3. Checklists for vehicles and vehicular laboratories.

 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

Bungie cords (to secure loose articles) 

District flood plan (most current version) 

Flagging 

Duct tape

Knife or multi-tool 

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. 
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Table 4. Checklists for the use of watercraft.

 Instructions and navigation

Field folder, with sampling plans 

Charts and maps 

Compass 

Depth finder 

Dead-man’s switch 

Navigation lights 

Ring buoy with line 

 Distress and external communication

Radio (VHF, AM, FM, and WEATHER) 

Special lighting/flagging (if boat activities might pose a hazard to the public, such as tag line measurements) 

Visual distress signals (Coast Guard approved) 

Whistles or horns 

Type IV throwable rescue device 

Personal flotation devices for each passenger (Coast Guard approved) 

Anchor and lines (spare) 

Bucket for use as a bailer (sponge for use in canoes)

Paddle (extra paddle for each canoe or rowboat) 

First aid kit (Coast Guard approved) 

Flashlights and batteries 

Fire extinguishers 

Spare parts (anchor, fuel, propeller, extra lines, cotter pin) 

Tool and repair kits 

Extra clothes (hat, foul-weather gear) 

Food and water 

Sunscreen 

Conversion factors and abbreviations 

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2.4 Literature Cited

Lane, S. L., and R. G. Fay. 1997. Ch A9: Safety in field activities. In National field manual for the 

collection of water-quality data: U.S. Geological Survey techniques of water-resources 

investigations, Book 9. Available at http://pubs.water.usgs.gov/twri9A9. 

O’Ney, S. E. 2005. Standard operating procedure #3: Safety and health, Version 1.0. In Regulatory 

water quality monitoring protocol, Version 1.0, Appendix E. Bozeman (MT): National Park 

Service, Greater Yellowstone Network. 

Route, B., C. Chapin, T. Gostomski, and I. Messerly. 2013. Great Lakes Network health and safety 

plan, version 1.0. Unpublished document. National Park Service, Great Lakes Network Office, 

Ashland, Wisconsin.

Water on the Web (WOW). 2004. Monitoring Minnesota lakes on the internet and training water 

science technicians for the future––A national online curriculum using advanced technologies 

and real-time data. University of Minnesota–Duluth, Duluth, Minnesota. 

(http://waterontheweb.org/curricula).

Standard Operating Procedure #2: Training and Safety, Version 1.1 September 2015

Water Quality Monitoring Protocol for Inland Lakes, Version 1.1 17

Appendix 1. Emergency Contact and Medical Form
Standard Operating Procedure #2: Training and Safety, Version 1.1 September 2015
Standard Operating Procedure #3: Using the Global 

Positioning System (GPS)

Version 1.1

In Water Quality Monitoring Protocol for Inland Lakes

Prepared by

David VanderMeulen* and Mark Hart

National Park Service

Great Lakes Inventory and Monitoring Network 

2800 Lake Shore Drive East

Ashland, Wisconsin 54806

* Contact author: david_vandermeulen@nps.gov

September 2015

Suggested citation: 

VanderMeulen, D., and M. Hart. 2015. Standard operating procedure #3: Using the global 

positioning system . In J. E. Elias, R. Axler, E. Ruzycki, and D. VanderMeulen. 2015. Water quality 

monitoring protocol for inland lakes: Great Lakes Inventory and Monitoring Network, version 1.1. 

Natural Resource Report NPS/GLKN/NRR—2015/1027. National Park Service, Fort Collins, 

Colorado.

Standard Operating Procedure #3: Using the Global Positioning System (GPS), Version 1.1 September 2015

Water Quality Monitoring Protocol for Inland Lakes, Version 1.1 i

SOP3 – Contents

Page

Revision History Log............................................................................................................................iii

Acknowledgements...............................................................................................................................iii

3.0 Introduction......................................................................................................................................1

3.1 Role of GPS in Water Quality Monitoring on Inland Lakes............................................................3

3.2 Using Mapping-Grade GPS Units....................................................................................................5

3.3 Using Recreational-Grade GPS Units............................................................................................13

3.4 Metadata.........................................................................................................................................15

3.5 GPS and NPSTORET ....................................................................................................................15

3.6 QA/QC...........................................................................................................................................17

3.7 Literature Cited ..............................................................................................................................19

Appendix A..........................................................................................................................................21

SOP3 – Tables

Page

Table 1. GPS receiver settings, definitions, and standards for use at GLKN parks..............................6

Table A1. Map scales and allowable error..........................................................................................22

SOP3 – Figures

Page

Figure 1. Examples of GPS point and line features data collection......................................................9

Figure A1. Differences between different grades of GPS units..........................................................22

Standard Operating Procedure #3: Using the Global Positioning System (GPS), Version 1.1 September 2015

Water Quality Monitoring Protocol for Inland Lakes, Version 1.1 iii

Revision History Log

The following table lists all edits and amendments to this document since the original publication 

date. Information entered in the log must be complete and concise. Users of this standard operating 

procedure will promptly notify the project manager and/or the Great Lakes Network (GLKN) data 

manager about recommended and required changes. The project manager must review and 

incorporate all changes, complete the revision history log, and change the date and version number 

on the title page and in the header of the document file. For complete instructions, please refer to 

Revising the Protocol, SOP #13.

Revision History Log:

Previous 

Version 

#

Revision 

Date

Author (with 

title and 

affiliation)

Location in Document 

and Concise 

Description of Revision Reason for Change

New 

Version 

#

1.0 5/01/2015 David 

VanderMeulen, 

GLKN

Updated the NPS contact 

author, removed 

references to specific 

versions of software, 

fixed a handful of 

grammatical errors 

throughout.

To clarify and update 

SOP based on changes 

that have occurred 

since Version 1.0 was 

published in 2008

1.1

Add rows as needed for each change or set of changes tied to an updated version number

Acknowledgements

Major portions of this SOP have been adopted from the GLKN GPS Field Data Collection Guide. 

The guide was originally published as Appendix K to the Great Lakes Inventory and Monitoring 

Data Management Plan (Hart and Gafvert 2005). Appendix A of this SOP was also adopted from that 

document and contains a summary discussion of the general types of GPS units available, as well as 

definitions of terms commonly associated with use of GPS units.

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Water Quality Monitoring Protocol for Inland Lakes, Version 1.1 1

3.0 Introduction

This Standard Operating Procedure (SOP) provides guidance on some of the more common 

operations associated with global positioning system (GPS) units. Although most GPS units are 

capable of multiple functions, only those operations relevant to the protocol established to monitor 

water quality on inland lakes (Elias et al. 2007) are discussed. 

Water quality monitoring staff utilize both mapping and recreational-grade GPS units. The Trimble 

GeoXT is an example of a mapping-grade GPS unit, while the Garmin 76S is an example of a 

recreational-grade unit. Mapping-grade units record data with location accuracy ranging from submeter to less than five meters. Recreational-grade units generally are not as accurate, with spatial 

accuracy less than 15 meters. Mapping-grade units have greater ability to capture spatially referenced 

metadata (i.e., attributes) than recreational-grade GPS. A detailed discussion of these types of GPS 

can be found in Appendix A.

Software pertinent to the use of these GPS units includes:

 Trimble TerraSync mapping-grade GPS unit software

 Trimble GPS Pathfinder Office desktop GPS processing software

 ESRI ArcGIS desktop GIS software

 Minnesota Department of Natural Resources DNRGPS Application – desktop application to 

transfer data between recreational-grade GPS units and GIS software 

 NPSTORET software, NPS database for water quality data (refer to SOP #8, Data Entry and 

Management).

Due to the rapid development of commercial software and hardware capabilities, it is likely that other 

GPS units or software will be utilized in the future. Therefore, this SOP is meant to act as a working 

document that is updated periodically as new hard-software becomes available. Although 

nomenclature may differ depending on what hard-software is utilized, this document should provide 

sufficient guidance on the general process of data collection using GPS tools until the SOP is revised. 

It is strongly recommended that water quality monitoring staff obtain unit-specific GPS training prior 

to deploying in the field. The training should include hands-on use, and should be designed to test all 

appropriate functions and operations prior to going out into the field.

Additionally, this SOP is not intended to be exhaustive or simply a regurgitation of operating 

manuals, but a document that might be carried into the field or periodically reviewed by field 

technicians and project leaders. Although some of the information in this SOP is specific to the water 

quality monitoring effort by GLKN, much of the text contained herein is applicable to other data 

collection efforts by GLKN staff. The objective of this document is to summarize GPS use guidelines 

applicable to the water quality monitoring efforts for inland lakes at GLKN parks.

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Water Quality Monitoring Protocol for Inland Lakes, Version 1.1 3

3.1 Role of GPS in Water Quality Monitoring on Inland Lakes

GPS units are primarily used in the following ways to support water quality monitoring on inland 

lakes:

1. Permanent markers on the shore are installed in order to measure water level relative to the 

marker. GPS units are used to record the location of each marker and the bearing and 

distance between the marker and a known landmark (e.g., fire-ring at a campsite). A detailed 

discussion of how reference markers are installed and water level is measured is found in 

SOP #4, Measuring Water Level. It is recommended that a mapping-grade GPS unit be used 

to obtain a higher precision location during installation of reference markers. These 

coordinates, along with detailed descriptions, should be used relocate the marker.

2. For water quality monitoring on inland lakes, navigating to and sampling at the position 

locations of monitoring stations is accomplished through a combination of:

 Using GPS units to navigate to previously established GPS point locations

 Using hardcopy topographic maps and written notes with site descriptions

 Using a depth sounder to verify site is at the deepest location

 Comparing digital photos taken during site establishment with observer ocular 

estimates

 Field experience of NPS staff conducting the monitoring

3. Accurate station location descriptions must be recorded and carefully followed by sampling 

personnel on subsequent field visits for water quality monitoring. Therefore, once on station, 

GPS equipment is used to obtain the station’s coordinates, which allows the user to spatially 

reference water quality monitoring data to specific geo-referenced locations for each 

sampling event. 

Additional uses of the GPS units may develop over time if protocols change or other needs are 

identified. For example, the Great Lakes Network currently promotes the use of electronic data 

logging equipment to enhance data quality and simplify data management. Many water quality 

parameters (e.g., pH) are now primarily recorded with electronic data logging equipment, while 

others (Secchi disk depth, names of observers, etc.) are logged on hardcopy only. Therefore, GPS 

units capable of logging more information other than just waypoints (e.g., Trimble GeoXT) could be 

programmed to allow for electronic recording of these parameters. The next two sections of this SOP 

will outline some of the more common and pertinent functions associated with mapping and 

recreational-grade GPS units, which are the types of units currently used by GLKN staff for water 

quality monitoring.

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Water Quality Monitoring Protocol for Inland Lakes, Version 1.1 5

3.2 Using Mapping-Grade GPS Units

All mapping-grade GPS users should become familiar with GLKN GPS collection procedures and 

relevant manufacturer’s user guides and operating manuals before GPS operation. For example, prior 

to using a Trimble GeoXT (mapping-grade) GPS unit, the following documents should be reviewed:

 Appendix A of this SOP

 GeoExplorer CE Series: Getting Started Guide

 GPS Mapping for GIS with TerraSync and GeoExplorer CE Series or TerraSync Operation 

Guide v2.4x

 Basic GPS Data Capture Using TerraSync: A Quick Start Guide

Mapping-grade GPS units provide the user with a variety of tools for field data collection. GLKN 

encourages the use of these units for most projects. These units can be used to acquire spatial data 

related to points, lines, and polygons along with associated, user defined, tabular attributes. Careful 

forethought and advanced planning are required to take advantage of these capabilities long before 

data collection begins.

3.2.1 Data Dictionaries

TerraSync software on mapping-grade GPS units is capable of using data dictionaries. Data 

dictionaries define the structure and rules to store attribute information about the feature being 

mapped and are customized for each project. GLKN data management personnel should be directly 

involved in the creation of data dictionaries. Basic steps include:

1. Identify the features to be mapped. These features are real world physical locations of objects 

(e.g., a water quality monitoring station) that are categorized as point, line, or polygon 

features.

2. Identify the attributes to be collected for each feature while in the field and create a data 

dictionary. Part of this process is assigning a unique identifier to each feature. (For example, 

if a survey plot is mapped as both a point and a polygon, one feature should be named 

plotname_poly and the other plotname_pt.).

3. Implement and test the data dictionary. Field staff should conduct a complete trial run for 

newly-created data dictionaries before beginning field work. Corrections and refinements are 

inevitable after such a trial.

Because most of the data for water quality monitoring on inland lakes are recorded by electronic 

sampling equipment, there has not been much incentive to utilize data dictionaries. However, as 

discussed earlier, it is possible that the few parameters not currently logged electronically could be 

incorporated into a data dictionary and recorded. As stated above, it is highly recommended that 

GLKN data management personnel be involved in this process, and that once created, the data 

dictionary only be altered with permission from data management personnel. This will reduce the 

potential for confusion and mistakes when data are processed at the end of the field season.
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3.2.2 GPS Settings

Positional accuracy of GPS data can be affected by several factors that can be monitored and 

recorded with mapping-grade GPS units. Table 1 lists these factors, their definitions, and the standard 

settings for GLKN field work. All spatial data collected shall be analyzed for spatial accuracy and 

shall meet or exceed the National Map Accuracy Standards (Table 1 in Appendix A, and 

http://mapping.usgs.gov/standards/). Table 2 indicates the coordinate system settings for data 

collection in GLKN parks.

Table 1. GPS receiver settings, definitions, and standards for use at GLKN parks.

Setting Name Definition GLKN Setting Standard 

Almanac

File containing estimated position of 

satellites, time corrections, and 

atmospheric delay parameters

Acquired automatically by GPS unit 

or from online sources within 10 

days prior to GPS field work

Altitude reference Ellipsoid model

Height above Ellipsoid (HAE) 

(preferred) or Mean Sea Level: if 

MSL is used, indicate Geoid Model

Antenna height GPS antenna height above the 

ground

Variable, usually 1.0 meters for 

handheld and 1.5 m for backpack

Datum

Geodetic model designed to fit a 

point on the earth’s surface to an 

ellipsoid

NAD 83 (CONUS) [preferred]

WGS 84 [GPS default, as fallback]

NAD 83 (CONUS) (CORS 96) [for 

H-Star use with GeoXH Trimble 

GPS Unit]

Elevation mask

The minimum angle above the 

horizon at which a GPS receiver will 

track a satellite

15 degrees

Feature types Geometry of spatial data GIS native formats; point, line and 

polygon are preferred

Logging interval Time interval between the recording 

of individual GPS fixes

Points: 1 second

Lines and Polygons: 5 seconds, but 

1 second in some circumstances

Minimum fixes for point 

positions

Number of GPS fixes that are used 

to calculate a single position for a 

point feature

50 fixes (120 points in the case of 

GeoXH)

Mode 

2 dimensional for horizontal 

positions and 3 dimension with an 

elevation position

3-dimensional (4 satellite minimum)

PDOP mask

Positional Dilution of Precision, a 

GPS quality estimate based on 

satellite geometry

6.0 or less

Real-time settings

GPS unit may be capable of 

performing differential correction of 

data during collection

Select Integrated WAAS (unless 

using H-star, e.g., XH unit); setting 

will be ‘auto’ or ‘on’ 
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Table 1 (continued). GPS receiver settings, definitions, and standards for use at GLKN parks.

Setting Name Definition GLKN Setting Standard 

Satellite vehicles Number of satellites used for 

position fixes 4 minimum

SNR mask

Signal-to-Noise ratio is a measure of 

the satellite signal relative to 

background noise

4.0 minimum, 6.0 or greater 

preferred

Unit of measure Linear unit of measure Meter (metric)

GPS signals are received in the WGS84 datum. Processing and transformation of the positional 

information to other datums can take place internally in the GPS unit or in software, either the GPS 

data processing software (see below) or in GIS software. GPS data that will receive no postprocessing differential correction, unlikely with a mapping grade receiver, can be collected in native 

WGS84 or NAD83 (CONUS), and ensuring that the datum used is recorded in the metadata. More 

likely with a mapping grade receiver, the GPS data will be differentially corrected after collection 

using data from one or more reference base stations. Data on the GPS unit should be collected in the 

same datum as the data are output from the reference base stations. The majority of public base 

stations in the US are part of the National Geodetic Survey's Continuously Operating Reference 

Station (CORS) network; and output information in the NAD83 (CONUS) CORS datum. Setting the 

GPS unit to record data in NAD83 (CONUS) CORS datum will result in the most accurate spatial 

information when differentially corrected against a CORS base station. A very high precision 

mapping grade unit may use H-Star technology, which requires post collection differential 

correction; using the NAD83 (CONUS) CORS datum and no real-time correction (WAAS) on the 

GPS unit, and correcting against a group of CORS base stations is necessary to realize the maximum 

accuracy from an H-Star receiver.

Table 2. Coordinate system settings for Great Lakes 

Network parks. Bold font indicates parks where water 

quality monitoring on inland lakes will take place.

Park UTM Zone Datum

APIS 15 NAD 1983 (Conus) 

GRPO 16 NAD 1983 (Conus) 

INDU 16 NAD 1983 (Conus) 

ISRO 16 NAD 1983 (Conus) 

MISS 15 NAD 1983 (Conus) 

PIRO 16 NAD 1983 (Conus) 

SACN 15 NAD 1983 (Conus) 

SLBE 16 NAD 1983 (Conus) 

VOYA 15 NAD 1983 (Conus) 

Before beginning data collection, the GLKN data management staff or the GPS user should complete 

some mission planning tasks. If high accuracy fixes are desired and there is some flexibility in 

scheduling of a field data collection mission, the user should complete a satellite survey to determine 

the best timing of the mission, usually when the most satellites are visible and in the best geometry. 
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Software, such as Trimble’s Quick Plan (also included in Pathfinder Office) can be used to look for 

time windows that should offer the lowest PDOP readings, and thus the highest positional accuracy.

If a project requires navigation to preset locations or waypoints, this information must be pre-loaded 

onto the GPS hardware before starting a field data collection mission, unless the locations have been 

previously stored on the GPS. Having printed copies of bathymetric maps with sampling sites 

marked is a good backup and can maximize field time and efficiency. Some of the sampling stations 

on inland lakes are located relative to unique shoreline features (e.g., rock outcrop, island, bay), 

which are annotated on topographic maps. Detailed descriptions and photographs of the shoreline are 

also used to navigate to designated sampling sites.

Many mapping-grade GPS units have the capability of storing and displaying background maps or 

GIS layers, which can be helpful when navigating in the field. For example, topographic maps of Isle 

Royale National Park can be used with GPS units to find lakes that are off-trail. The GLKN data 

management staff can support preparation of these background layers and, if necessary, assist in 

loading them onto the GPS hardware.

GPS units create files to store data during a field session using a prefix and date-time stamp as file 

names. For example:

RMMDDHHx

R – Unit Prefix

MM – Month 

DD – Day 

HH – Hour 

X – a, b, c, etc., the order files are created within an hour

If multiple GPS units are used for a project, a unique prefix (letter) should be assigned to each unit, 

which will ensure that downloaded files for each unit contain a unique identifier within the filename. 

For example, with three GPS units, the unique letters for the units could be N, G, and A. Those 

letters would serve as a prefix for the file n (e.g., N102715A, G102715A, and A102715A would 

indicate units N, G, and A, October 27, 15 hour, A first in hour). In addition, if a data dictionary is 

used, and entry of the observer’s name or initials is not an option in the dictionary, then the 

observer’s name or initials should be included in the file name.

Each user should be familiar with the capabilities of the GPS hardware and field computers. If 

possible, water quality monitoring staff should receive hands-on instruction from someone familiar 

with the equipment. At a minimum, the equipment user guides and operator’s manuals should be 

reviewed, and the operator should test the functions s/he intends to use. 

It is extremely important that each user become familiar with the battery power and memory 

capabilities of the GPS units. All units have limited battery and memory resources; these features 

should be thoroughly tested to gain an understanding of the power and memory limitations of the 
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GPS units before being deployed in the field. It is possible to power or recharge these units from a 

DC power source, such as a vehicle power outlet.

3.2.3 Data Collection

Data collection should be performed using an approved data dictionary or database for the protocol, 

if applicable. Moreover, users should be mindful of the following concepts:

 If using a GPS unit that gives an approximate 5m horizontal accuracy, the user cannot map 

anything as a polygon that is less than 4 to 6m in width or diameter. Such objects must be 

captured as point features.

 If a GPS user is collecting a line or polygon feature and then stops moving, the GPS unit will 

continue to collect data (Figure 1, examples 1 and 2). Users need to be familiar with the 

Pause/Resume toggle key and use it liberally. This technique greatly improves subsequent 

data quality and reduces the need for time-consuming spatial editing.

 Another way to avoid errors is to collect point features that represent the beginning and end 

points of a line transect (Figure 1, examples 3 and 4). Having these reference point locations 

will mean easier editing of any zig-zagging line features.

Figure 1. Examples of GPS point and line features data collection.
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Mapping-grade GPS units have additional features that aid in data collection. These include: 

 Nested Features––Allows user to collect a point while collecting a line or polygon feature. 

For example, while surveying potential amphibian habitat along a stream (line feature), the 

user can pause the line feature, take a point for a specific observation, then resume the line 

feature collection.

 Offset Feature––Allows user to collect a feature when topography is such that getting next to 

or over the feature is impossible. For example, a GPS line could be collected while taking a 

horizontal zooplankton tow off the side of a boat.

 Between-feature Positions––the GPS unit collects positions without any feature or attribute 

data. This feature is useful for tracking areas traveled during a day. For example, while 

surveying for presence or absence of invasive plants, a user could collect data on the area 

surveyed in addition to locations of specific plants found.

3.2.4 Data Processing

When data collection is complete for the day or round of sampling, data are downloaded from the 

GPS unit to a computer. For Trimble GPS units, the proprietary software Pathfinder Office (or the 

GPS Analyst extension) is used to download, differentially correct, and then export the data to a GIS 

format. [Note: Trimble Pathfinder Office and GPS Analyst are relatively expensive. However, 

Trimble also offers a free data transfer utility to download data from the GPS units to a Windowsbased PC]. Differential correction is a post-processing procedure to improve upon raw GPS positions 

using base station data. Base stations consist of a GPS antenna and receiver positioned at a known 

location specifically to collect data from satellites. The distance between the base station(s) and the 

remote GPS receiver should be kept to a minimum. 

Differential correction should be conducted on all GPS data collected, even if data were collected 

using the real-time collection feature. Once the data are differentially corrected, they can be verified 

and edited. Unintentional features can be deleted and attributes can be reviewed. 

The last step in processing data is exporting the data set to GIS (ArcGIS or ArcView). Depending on

the software used for this process, newly created files generated when exporting data are often 

assigned generic names. For example, if Pathfinder Office is used to export a file named 

‘VOYA2007.cor’ (.cor denotes that the file has already been differentially corrected) that only 

contains point features, the exported file will be named ‘point_ge.shp’. Great care should be taken to 

not overwrite this file when exporting other data, as the software will continue to use this generic 

naming convention the next time it is used. In addition, during the export process, the coordinate 

system to which the data will be exported to should be verified (Table 2).

Additional data attributes can be included in the data exports. Data attributes recommended by 

GLKN are listed in Table 3. 
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Table 3. Recommended fields to be exported in addition to GPS features.

All Features Point Features Line Features Area Features 

PDOP Height Length (2D) Area (2D) 

Correction status Position Length (3D) Perimeter (2D) 

Receiver type Perimeter (3D) 

Date recorded 

Data file name 

Total positions 

Data dictionary name 

Managing the incoming GPS data can be a challenge, especially if there are multiple units per 

project. Common practices used by GLKN include: 

 Download all data to a computer or network drive that is regularly backed up.

 Keep GPS data and GIS data separate through electronic file management.

 Directories and files names should not contain non-alpha-numeric characters and/or spaces 

(except underscores).

 Keep GPS data in well-organized directories (see Hart and Gafvert (2005), GLKN Data 

Management Plan, for more details). 

At the end of a project, all data and background files should be removed from the GPS unit to free 

available memory. Data files should not be left on a unit if they have been properly downloaded and 

verified. In addition, some GPS units require their batteries to be re-charged periodically. Failure to 

do so can cause the GPS unit batteries to discharge completely, and may cause some files and 

software to be deleted.

Additional information can be found at www.nps.gov/gis/gps/gps4gis/, which describes the steps 

outlined here in greater detail.

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3.3 Using Recreational-Grade GPS Units

Recreational-grade GPS units can be used to acquire location information (generally points) when 

spatial accuracy is not paramount to the project. Recreational GPS units do not have data dictionaries 

for storing attribute information with the point location. However, using a recreational-grade unit to 

capture a waypoint at each sampling site is a reliable means to verify the correct sampling site has 

been reached, even if a GPS location is not needed.

As with mapping-grade GPS units, personnel that employ recreational-grade GPS units should 

become familiar with GLKN GPS collection procedures and relevant manufacturer’s user guides and 

operating manuals before GPS operation. For example, prior to using a Garmin 76S (recreationalgrade) GPS unit, the following documents should be reviewed:

 Appendix A of this SOP

 GPSMAP 76S Quick Start Guide

 GPSMAP 76S Owner’s Manual and Reference Guide

 Garmin MapSourceTM User’s Manual and Reference Guide

3.3.1 Planning

If a recreational-grade GPS meets the criteria of the project, the unit chosen must have the capability 

of downloading collected data to a personal computer. Downloading data is usually accomplished 

with a parallel or USB cable connection. 

Much of the data collected by GPS will eventually reside in a relational database. Each GPS feature 

collected should contain a unique identifier that relates the feature to an associated record in a 

database. For water quality monitoring on inland lakes, the records associated with each GPS feature 

will consist primarily of water quality parameters. Since recreational GPS units have only one text 

field for input, careful consideration should be given to the use of this field and the design of unique 

identifiers. GLKN data management and GIS staff can assist in creating unique IDs on a project-byproject basis.

3.3.2 Data Collection

Location data are captured by recreational-grade GPS units as waypoints. When taking a waypoint, 

enter the site ID or site designation in the text field provided. It is also good practice to collect 

reference points at regular intervals. These reference point positions should be taken at known 

locations (e.g., trailheads, parking lots, stream confluences) which can later be used in GIS to check 

the accuracy of waypoint data. 

If navigation to preset waypoints is applicable to a project, the waypoints must be loaded onto the 

GPS unit before departure to the field. Some recreational grade GPS units have the ability to store 

and display topographic maps, which can aid in navigation. Printed topographic maps of the 
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waypoint locations can also be used to maximize field time and efficiently navigate between 

waypoints.

3.3.3 Data Processing

Data should be downloaded from GPS units once a day or after each field session. The DNR Garmin

freeware product (www.dnr.state.mn.us/mis/gis/tools/arcview/index.html) can be used to download 

data from Garmin GPS units. Data should be downloaded both as a text file and a shapefile. Each file 

name should include the download date. Points should be checked for reasonable spatial accuracy 

and errors. Subsequent downloads should be error-checked in the same manner. When data collection 

is finished, all files should be compiled into one spatial file, and along with the raw downloads, 

should be saved to the appropriate location on Great Lakes Network servers (refer to SOP #8, Data 

Entry and Management for more detail).
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3.4 Metadata

Regardless of the type of GPS unit used to collect data, all resulting GIS datasets need to have 

information documenting how the GPS data were collected. NPS requires that FGDC (Federal 

Geographic Data Committee, www.fgdc.gov/index.html) compliant metadata be written for all 

geospatial layers created (Executive Order 12906). 

Until final FGDC metadata is written, the data collection and management process is incomplete. 

Tracking GPS projects depends on the complexity of the project, how many participants, length of 

project etc. Documentation can be a simple ‘readme’ text file, or a detailed daily log. 

The Great Lakes Network recommends formal metadata be written by the data collectors, as they are 

the ones familiar with the project and resulting data. However, Network data management and GIS 

staff usually end up documenting someone else’s work. Chapter 7 of the GLKN Data Management 

Plan (Hart and Gafvert 2005) includes a detailed discussion of metadata procedures. At a minimum, 

the following details should be documented to facilitate final FGDC metadata: 

 Name of project

 Name(s) of data collectors

 EHE/EPE or maximum PDOP (using 4 satellites)

 Coordinate system (projection, datum, and zone)

 Type (or types) of GPS units used

 The range of field collection dates

 Name of base station(s) used for differential correction

 Name and version of software used for downloading

 Any major editing performed on the raw data (e.g., moving of points)

 All versions of data dictionaries used

3.5 GPS and NPSTORET

Water quality data, including chemical, physical, and biological data, are managed according to 

guidelines from the NPS Water Resources Division. These guidelines include using the NPSTORET 

desktop database application to help manage data entry, documentation, and transfer. The Network 

oversees the use of NPSTORET according to the Network’s water quality monitoring protocols and 

ensures the content is transferred at least annually to NPS Water Resource Division for upload to the 

EPA STORET (STOrage and RETrieval) database. 
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NPSTORET requires that every water quality monitoring station location must have an assigned 

latitude and longitude coordinate. Also, the horizontal datum to which these coordinates are 

referenced (typically North American Datum 1983 or World Geodetic System 1984) and the method 

by which they were obtained (GPS, map interpolation, etc.) must be provided. Therefore, the GLKN 

project leader for monitoring water quality on inland lakes and the GLKN data manager collaborate 

in organizing monitoring station coordinates in an acceptable format (e.g., Excel spreadsheet or 

Access database) to be imported to the NPSTORET database. A detailed discussion on using the 

NPSTORET database is found in SOP #8, Data Entry and Management.
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3.6 QA/QC

Long-term monitoring is only useful if stakeholders have confidence in the data. Efforts to detect 

trends and patterns in ecosystem processes require high-quality, well-documented data that minimize 

error and bias. Data of inconsistent or poor quality can result in loss of sensitivity and lead to 

incorrect interpretations and conclusions.

NPS Director’s Order #11B: Ensuring Quality of Information Disseminated by the National Park 

Service (www.nps.gov/policy/DOrders/11B-final.htm) specifies that information produced by the 

NPS must be of the highest quality and based on reliable data sources that are accurate, timely, and 

representative of the most current information available. Therefore, GLKN will establish and 

document procedures for quality assurance (QA) and quality control (QC) to identify and reduce the 

frequency and significance of errors at all stages in the data life cycle (see SOPs #8 and #12 for 

details on data management and QA/QC, respectively). Under these procedures, the progression from 

raw data to verified data to validated data implies increasing confidence in the quality of those data. 

Quality assurance and quality control procedures will document internal and external review 

processes and include guidance for addressing problems with data quality.

Examples of general of QA/QC practices include:

 Standardized field data collection forms

 Use of field computers and automated data loggers

 Proper calibration and maintenance of equipment

 Training of field crew and data technicians

 Database features such as built-in pick lists and range limits to reduce data entry errors

 Automated error-checking routines

Many of the standard operating procedures associated with the protocol for monitoring water quality 

in inland lakes include a discussion of QA/QC as it relates to the protocol. Examples of QA/QC 

practices pertaining to use of GPS include:

 Ensure that GPS-related software is periodically updated as it becomes available and has 

been tested. 

 Record location positions on field data forms as well as with the GPS unit.

 For each monitoring station, compare location positions for different sampling events, 

including the position recorded during establishment of the monitoring station. This will 

allow for an assessment of position accuracy over time.
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 If data dictionaries are used with mapping-grade GPS units, ensure that the coordinates for 

the monitoring station match the other attributes recorded on the GPS unit for that monitoring 

station.

 Check to see if the accuracy of the GPS unit meets or exceeds the National Map Accuracy 

Standards shown in Table 1 of Appendix A.

 Ensure that the appropriate coordinate system is used when collecting and exporting data.

 Use mapping software (e.g., Pathfinder Office or ArcGIS 9.x) to view waypoints (or features) 

overlaid on a geo-referenced air photo or topographical map to check for accuracy.

 If applicable, check the accuracy of the attribute(s) recorded on a GPS unit by using mapping 

software (see bullet above) and look-up tables or in spreadsheets generated after postprocessing is complete. 

A final report on data quality, including data collected by GPS, will be incorporated into the 

documentation for this project. Such documentation will include a listing of the specific methods 

used to assess data quality and an assessment of overall data quality prepared by the project manager. 

This is a necessary part of the data quality elements of the metadata file.
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3.7 Literature Cited

Hart, M., and U. Gafvert (editors). 2005. Data management plan: Great Lakes Inventory and 

Monitoring Network. National Park Service Great Lakes Inventory and Monitoring Network 

Report GLKN/2005/20. National Park Service, Ashland, Wisconsin.

Elias, J. E., R. Axler, and E. Ruzycki. 2008. Water quality monitoring protocol for inland lakes, 

Version 1.0. National Park Service, Great Lakes Network, Ashland, Wisconsin. 

NPS/MWR/GLKN/NRTR—2008/109. National Park Service, Fort Collins, Colorado.

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Appendix A

This appendix discusses the role of GPS in GLKN data management and provides an explanation of 

the types of GPS units that are available. The text is taken directly from the GLKN GPS Field 

Collection Guide, which can be found in its entirety in Appendix K of the Great Lakes Inventory and 

Monitoring Data Management Plan (Hart and Gafvert 2005).

Introduction 

Over the past decade new tools have been developed to help researchers collect and manipulate data 

while in the field. Global Positioning System (GPS) is one such tool. GPS is currently a constellation 

of 28 US Department of Defense satellites (as of 2006) orbiting 11,000 miles above the Earth, 

making a complete orbit approximately every 12 hours, and transmitting signals to Earth at precisely 

the same time. The position and time information transmitted by these satellites is used by a GPS 

receiver to triangulate a location coordinate on the earth using three or more satellites. 

Role of GPS in GLKN Data Management

Data collected using GPS-enabled equipment represents all or part of the acquisition stage of an 

information resources lifecycle that includes several other stages (see Section 5.4 in GLKN Data 

Management Plan). The process and methodology used for acquisition, planning, data collecting, and 

post-processing incorporate several aspects of data management, including quality assurance, data 

storage and organization, and data stewardship. To promote data quality and simplify data 

management, the Great Lakes Network expects to use electronic data logging equipment for some 

data acquisition. However, parallel or complementary use of hand written data sheets and field notes 

will remain important for data collection activities. 

Types of GPS Units 

At the most basic level GPS equipment can just consist of a GPS antenna and the associated signal 

processing circuitry. The antenna can be a standalone device, be incorporated in to a handheld unit, 

or be integrated into a larger electronic device, such as a personal data assistant (PDA), data logger, 

or portable computer. As technology evolves, the Great Lakes Network will continually try to use 

equipment which maximizes spatial accuracy; reduces hardware weight and user fatigue; and reduces 

database development, data manipulation, and transformation.

There are three major types of GPS units that are based on the level of accuracy to which spatial data 

can be collected. Survey-grade GPS units are used for surveying tasks that require very high 

accuracy (1 cm or less). Mapping-grade units can map features from sub-meter to less than 5m 

accuracy, employing differential correction. Recreational-grade GPS units are sold primarily for 

outdoor sports and recreational activities. Accuracy using recreational GPS units ranges from 5 to 

30m. Most natural resource-related data collection requirements correspond to either the recreationalgrade or mapping-grade. Figure 1 shows some of the major differences between these two types. 

Deciding which type of unit to use is an essential part of project planning, and depends on the end 

product needed. Mapping-grade GPS units are recommended for most GLKN field work; however, 

for some projects recreational-grade units can meet a project’s accuracy requirements and reduce the 
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cost of field operations. The choice of GPS unit should be made by the project manager after 

consulting with the GLKN data management and GIS staff.

Figure A1. Differences between different grades of GPS units.

All resulting GIS data layers need to meet or exceed the National Map Accuracy Standards for a 

1:24,000 product (NPS GIS Data Standards, 2002, www.nps.gov/gis/data_info/standards.html). 

Table A1 provides the allowable horizontal accuracy for some common scales.

Table A1. Map scales and allowable error. 

Scale Allowable Error 

1:40,000 33.8 meters (111 feet) 

1:31,680 16.1 meters (53 feet) 

1:24,000 12.2 meters (40 feet) 

1:20,000 10.1 meters (33 feet) 

1:12,000 6.1 meters (20 feet)

1:9,600 4.9 meters (16 feet) 

1:4,800 2.4 meters (8 feet) 

1:2,400 1.2 meters (4 feet) 

1:1,200 0.6 meters (2 feet) 
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Definitions 

Accuracy: The degree of conformance between the estimated or measured position, time, and/or 

velocity of a GPS receiver and its true time, position, and/or velocity as compared with a constant 

standard. 

Almanac: Data transmitted by a GPS satellite, which include orbit information on all the satellites, 

clock correction, and atmospheric delay parameters. The almanac is used to facilitate rapid satellite 

vehicle (SV) acquisition. The orbit information is a subset of the ephemeris data with reduced 

precision. 

Attribute: Tabular information about a specific feature. 

Base Station: GPS files collected continuously from community base stations, local base stations, or 

Continually Operating Reference Stations (CORS). Gathering base files will require an internet 

connection and software that dials into a server that houses the base station data collected at the same 

time of the rover. Data stored on these servers will not be available in real-time - hence this step is 

conducted after field collection. Trimble users would use the Differential Correction utility supplied 

in Pathfinder Office. 

Differential Correction: The merging of rover file data with base map data to correct position errors 

due to atmospheric interference. Autonomous data (rover) are collected in the field while base data 

are stored at the stationary base station. The two datasets are loaded into a post-processing software 

package where corrections are applied. This process will reduce errors in the field collected data (the 

rover) by correlating and correcting for known errors recorded in the base file that has the same time 

tag. As distance between the rover and base file increase, there is degradation in post-processed 

accuracy. In general, a degradation of one part per million (1ppm) occurs as the distance between the 

base station and rover increases. For example, one millimeter of degradation occurs for every 

kilometer between base and rover. 

Datum (geodetic datum): A mathematical model that is designed to fit a point on the earth’s surface 

to an ellipsoid. Commonly used datums are North American Datum (NAD) 1927, and NAD 1983, 

modeled to represent the North American continent. 

Feature: A feature is the spatial location of a physical object, or some event or phenomenon. 

Features are often referred to as graphic data in a GIS. Examples include a tree (point), road (line), or 

land parcel (polygon). 

FGDC: The Federal Geographic Data Committee is a 19 member interagency committee composed 

of representatives from the Executive Office of the President, Cabinet-level and independent 

agencies who develop policies, standards, and procedures for organizations to cooperatively produce 

and share geographic data. (www.fgdc.gov/index.html). 

Global Positioning Systems (GPS): A constellation of a minimum of twenty-four satellite vehicles 

orbiting the earth approximately every twelve hours at an approximate pacing of sixty degrees, 

between 11,000 – 12,000 miles above the surface of the Earth 
Standard Operating Procedure #3: Pre-Season Preparation, Version 1.1 September 2015

Water Quality Monitoring Protocol for Inland Lakes, Version 1.1 24

Lines: Geographic term related to the scale that describe how a feature is drawn. Lines are linear 

measures of a feature (such as a line representing a trail) 

Mapping Grade: GPS receivers capable of attaining five meters of accuracy or better using 

differential correction. 

Metadata: Data about the data. Usually comes in the form of a text or html document with 

information on the dataset's quality, current projection, attributes, distribution and citation. In the 

National Park Service, this generally implies a file compliant to the FGDC Content Standard for 

Digital Geospatial Metadata. 

Multipath: Error which occurs when a GPS signal sent from a satellite vehicle is bounced or 

redirected by an object, prior to reaching a GPS receiver. Multipath will cause the time it takes a GPS 

signal sent by a satellite vehicle to reach a GPS receiver to be inflated. This will cause inaccuracies in 

positions collected. 

Points: Geographic term related to the scale that describe how a feature is drawn. Points are single 

dimensional features (such as a point representing a spring). 

Polygons: Geographic term related to the scale that describe how a feature is drawn. Polygons have 

area associated with the feature (such as a circle representing a parking lot). 

Projection: A method of representing the earth's three-dimensional surface as a flat two-dimensional 

surface. This normally involves a mathematical model that transforms the locations of features on the 

earth's surface to locations on a two-dimensional surface. 

Post Processing: Utilizing base station data, GPS software, and data acquired by a GPS receiver in 

the field to gain an accurate fixed position. 

Triangulation: The process of determining the distance between points on the earth’s surface by 

dividing up a large area into a series of connected triangles, measuring a base line between two 

points, and then locating a third point by computing both the size of the angles made by lines from 

this point to each end of the base line and the lengths of these lines. 

Waypoint: A named three-dimensional position on the earth’s surface, that is, having both a latitude 

and longitude. Waypoints are assigned to a fixed location in the field so it can be navigated to 

consistently and accurately through time.
Standard Operating Procedure #4: Measuring Water 

Level 

Version 1.1

In Water Quality Monitoring Protocol for Inland Lakes

Prepared by

Joan Elias, Ray Wise, and David VanderMeulen*

National Park Service

Great Lakes Inventory and Monitoring Network 

2800 Lake Shore Drive East

Ashland, Wisconsin 54806

* Contact author: david_vandermeulen@nps.gov

September 2015

Suggested citation: 

Elias, J., R. Wise, and D. VanderMeulen. 2015. Standard operating procedure #4: Measuring water 

level. In J. E. Elias, R. Axler, E. Ruzycki, and D. VanderMeulen. 2015. Water quality monitoring 

protocol for inland lakes: Great Lakes Inventory and Monitoring Network, version 1.1. Natural 

Resource Report NPS/GLKN/NRR—2015/1027. National Park Service, Fort Collins, Colorado.

Standard Operating Procedure #4: Measuring Water Level, Version 1.1 September 2015

Water Quality Monitoring Protocol for Inland Lakes, Version 1.1 i

SOP4 – Contents

Page

Revision History Log............................................................................................................................iii

Acknowledgements...............................................................................................................................iii

4.0 Introduction......................................................................................................................................1

4.1 Installing Reference Marks..............................................................................................................1

4.2 Measuring Water Level....................................................................................................................3

4.3 Equipment List.................................................................................................................................7

SOP4 – Figures

Page

Figure 1. Clockwise from upper left: drilling a hole into the bedrock, using canned air to 

blow dust from hole, reference mark in bedrock next to GPS unit, applying epoxy to 

reference mark. ......................................................................................................................................2

Figure 2. Example of notes on location and photos of reference marker..............................................3

Figure 3. Holding stadia rod at water’s edge (left), viewing stadia rod through hand-held 

eye level. ................................................................................................................................................5

Figure 4. View through hand-held eye level.........................................................................................5

Figure 5. The second method of measuring water level employs the use of a tightly held 

line stretched from the reference marker to the stadia rod.....................................................................6

Figure 6. To measure water level from in the water, a stadia rod is held on the reference 

marker to read water level above marker...............................................................................................7

Standard Operating Procedure #3: Pre-Season Preparation, Version 1.1 September 2015

Water Quality Monitoring Protocol for Inland Lakes, Version 1.1 iii

Revision History Log

The following table lists all edits and amendments to this document since the original publication 

date. Information entered in the log must be complete and concise. Users of this standard operating 

procedure will promptly notify the project manager and/or the Great Lakes Network (GLKN) data 

manager about recommended and required changes. The project manager must review and 

incorporate all changes, complete the revision history log, and change the date and version number 

on the title page and in the header of the document file. For complete instructions, please refer to 

Revising the Protocol, SOP #13.

Revision History Log:

Previous 

Version 

#

Revision 

Date

Author (with 

title and 

affiliation)

Location in Document 

and Concise 

Description of Revision Reason for Change

New 

Version 

#

1.0 5/01/2015 David 

VanderMeulen, 

GLKN

Updated the NPS contact 

author, deleted a few 

obsolete references, 

fixed a handful of 

grammatical errors 

throughout

To clarify and update 

SOP based on changes 

that have occurred 

since Version 1.0 was 

published in 2008

1.1

Add rows as needed for each change or set of changes tied to an updated version number

Acknowledgements

Many thanks to Pete Penoyer, NPS-WRD, for informational material and feedback on this SOP. We 

appreciate the brainstorming with Larry Kallemeyn, USGS, and Chris Holbeck, VOYA, which led to 

the procedures we are now using in remote areas.

Standard Operating Procedure #3: Pre-Season Preparation, Version 1.1 September 2015

Water Quality Monitoring Protocol for Inland Lakes, Version 1.1 1

4.0 Introduction

An estimate or measurement of flow or water level is highly recommended by the National Park 

Service (NPS) Water Resources Division (WRD) (National Park Service 2002) for water quality 

monitoring programs. Water level data are important in understanding overall lake processes. These 

data help define the spatial extent of littoral zones, which are critical habitat for many aquatic 

organisms. Accurate volumetric estimates, hydrologic budgets, heat budgets, and mass balance 

budgets for chemical compounds and oxygen also require lake level data. Changes in 

bioaccumulation of mercury in aquatic organisms may be explained in part by lake level, as 

methylation rates are correlated with water level fluctuations (Sorensen et al. 2005). In reservoirs and 

other systems where lake level is controlled, such as Lake Kabetogema in Voyageurs National Park 

and Glen Lake adjacent to Sleeping Bear Dunes National Lakeshore, lake levels and discharge from 

the lake are controversial management issues (Kallemeyn et al. 2003, Vana-Miller 2002). 

Fluctuations in lake level also have importance in terms of lakeshore development and wetland 

conservation and function (Mitsch and Gosselink 2000).

In inland lakes, estimates or measurements of water level can be acquired through the use of a staff 

gage or reference mark and level. A staff gage is a ruler, usually made of enameled steel, placed in a 

stream or lake, and is used to measure the water level. Staff gages are usually mounted on permanent 

structures, such as a bridge piling, but may also be sunk into a stable bottom substrate or anchored to 

bedrock. 

A reference mark is a permanent marking (e.g., an ‘X’ etched into concrete or a bolt drilled into a 

structure), the elevation of which is considered to be gage zero 

(www.srh.noaa.gov/ohx/dad/hydro/Doingasurvey.html). If the elevation of the reference mark is 

established it is called a bench mark.

If staff gages or bench marks are not already installed and maintained by another agency, the Great 

Lakes Network will install reference marks for measuring water level of inland lakes.

4.1 Installing Reference Marks

Prior to installing reference marks, complete and submit a minimum tools analysis, if required by the 

park, and ensure that the park grants permission.

4.1.1 Site Selection

Choose a site for the reference mark that is not obtrusive from a visitor’s viewpoint, yet is easy to 

access and relocate. The site should be above current water level by at least 1 m to accommodate a 

large rise in level, and relatively near the water’s edge to allow viewing a stadia rod from the 

reference mark. Past reported water level fluctuations should be reviewed to determine an 

appropriate site and the maximum water level range that may be expected. 
Standard Operating Procedure #4: Measuring Water Level, Version 1.1 September 2015

Water Quality Monitoring Protocol for Inland Lakes, Version 1.1 2

4.1.2 Installation Procedures

At lakes where large pieces of bedrock are exposed, such as at Voyageurs National Park, secure an 

aluminum dome-top concrete reference mark (2” top diameter, 5/8” stem diameter, 2.5” stem length, 

3 oz. weight) in the bedrock using the following steps. Drill a hole 2.5” deep into the bedrock using a 

rock hammer and a 5/8” drill bit. Remove the rock dust from the hole with canned air. Apply the 

appropriate kind of epoxy to the reference mark. Insert the reference mark into the drilled hole, and 

ensure proper seating by pounding it briefly with a rock or stepping on it.

Figure 1. Clockwise from upper left: drilling a hole into the bedrock, using canned air to blow dust from 

hole, reference mark in bedrock next to GPS unit, applying epoxy to reference mark.

At lakes where bedrock is not exposed, one of the following alternatives may be used: 1) A nail in a 

large, long-lived tree, with known height above ground; 2) a long iron rod (approx. 1.5 to 2 m) sunk 

into the ground until nearly flush with ground level, with a reference marker cemented in the top with 

concrete; 3) a mark on a nearby structure, such as a building, bridge, or observation deck. Installing a 

back-up marker will ensure a continuous data record should one marker be dislodged (e.g., frost 

heave or tampering).
Standard Operating Procedure #4: Measuring Water Level, Version 1.1 September 2015

Water Quality Monitoring Protocol for Inland Lakes, Version 1.1 3

4.1.3 Record Location of Reference Mark

Record the location of the marker with a GPS unit. Use the GPS to also record the distance to and 

location of a nearby landmark, such as a fire ring at a campsite. Record detailed notes in the field 

notebook on directions to the reference mark location so that a different field crew will be able to 

find the marker in the future. Take a compass bearing and photo of the reference mark site from at 

least one landmark, and a compass bearing and photo of the landmark(s) from the reference mark. 

Ensure the compass has been set to the proper magnetic declination to get the true compass bearing.

Reference Mark Notes – Agnes Lake

6-10-06 water level = - 1.20m UTM: 5368392N 513742E

Reference mark is on the northwest side of the lake northeast of the campsite at a straight line 

distance of 34.5 m. It is below a large rock wall about 1.5 m away from the water’s edge beneath a 

10” dbh jack pine. Hike along the shoreline to the large jack pine. Reference mark is at a 40o bearing 

from the fire ring.

Pictures are from the campsite toward marker and marker toward the campsite. 

8-2-06 water level = - 1.305 m

Picture of reference mark from campsite Picture of campsite from reference mark

Figure 2. Example of notes on location and photos of reference marker.

4.2 Measuring Water Level

The Network will always install reference markers well above current water level. The markers may 

become submerged, however, after extreme flooding events. For example, water levels at some lakes 

Agnes Lake Reference Mark

reference mark under jack pine

campsite
Standard Operating Procedure #4: Measuring Water Level, Version 1.1 September 2015

Water Quality Monitoring Protocol for Inland Lakes, Version 1.1 4

in Voyageurs National Park have fluctuated by over 1 m from one year to the next due to the 

transience of beaver impoundments (Kallemeyn, personal communication).

In some cases, the reference marker may have been installed by another agency and may be located 

below the current water level. 

Instructions for measuring water level above and below reference markers are included below. 

Because many of our lakes are in remote locations, we will use one of the following procedures that 

require a minimum of equipment. Procedures differ only in the detail; the concept is the same in all.

Water-level measurements at a given lake will always be based on the same reference marker. If a 

new reference marker has to be used, a new water level data set will be created using this new 

reference mark as the standard. The use of a new reference mark for measuring water level will be 

clearly noted in the field notebook and NPSTORET database. Water levels using different reference 

markers cannot be compared because the markers will likely be located at different elevations above 

the land-water interface.

4.2.1 Reference Marker Above Water Level

Method 1: One person stands at the water’s edge and holds the base of the stadia rod at current water 

level while a second person at the reference marker uses an eye level to view the rod held vertically 

(Figure 3). If the reference marker is glued to the bedrock, the second person will need to get his/her 

eye above the rock in a stable position. A second stadia rod or metric ruler will work for this purpose. 

The second person looks through the eye level, first focusing the cross-hairs, then focusing on the rod 

held at water level. When the bubble inside the eye level is centered vertically, the instrument is 

being held on level (Figure 4). Read the height on the stadia rod. The person holding the rod can 

assist by sliding a finger or pencil up and down the rod until the person with the eye level sees it in 

the cross-hair. Record this level to the nearest 0.1 cm, then measure and record the height of the 

second person’s eye level above the reference marker. Subtract this height from the reading of the 

level on the rod to get water level relative to the reference marker. The resulting number will be 

negative to indicate water level below reference marker.

Example: 

 Eye level reads 174.3 cm on the stadia rod

 Height of eye level above reference marker = 15.4 cm

 Subtract height of eye level from level on stadia rod: 174.3-15.4 = 158.9

 Water level relative to reference marker = -158.9 cm or -1.589 m.
Standard Operating Procedure #4: Measuring Water Level, Version 1.1 September 2015

Water Quality Monitoring Protocol for Inland Lakes, Version 1.1 5

Figure 3. Holding stadia rod at water’s edge (left), viewing stadia rod through hand-held eye level.

Figure 4. View through hand-held eye level.

175___

__

__

__

__

__

____

__

raise & lower level 

until bubble is 

between lines

stadia rod in back

correct reading = 

174.3 cm
Standard Operating Procedure #4: Measuring Water Level, Version 1.1 September 2015

Water Quality Monitoring Protocol for Inland Lakes, Version 1.1 6

Method 2: One person stands at the water’s edge and holds the base of the stadia rod vertically at 

current water level and one end of a line or cord (Figure 5). A second person at the reference marker 

holds the other end of the line on the marker and stretches it taut. Using a line level, the person 

holding the stadia rod adjusts the level of the line on the rod until the line is level. The reading to the 

nearest 0.1 cm is taken directly on the rod when the line is level and will be a negative number to 

indicate water level below reference marker.

Example:

 Line is level on stadia rod at 158.9 cm

 Water level relative to reference marker = -158.9 cm or -1.589 m

Figure 5. The second method of measuring water level employs the use of a tightly held line stretched 

from the reference marker to the stadia rod.

4.2.2 Reference Marker Below Water Level

From a boat or while wading, use a stadia rod held on the reference marker to read water level above 

marker (Figure 6). The reading, to the nearest 0.1 cm, will be a positive number.

Example:

 Water level on stadia rod measures 63.4 cm

 Water level relative to reference mark is 63.4 cm or 0.634 m

reference marker

line level

stadia rod

water level

reading = 

158.9 cm

line held 

tightly
Standard Operating Procedure #4: Measuring Water Level, Version 1.1 September 2015

Water Quality Monitoring Protocol for Inland Lakes, Version 1.1 7

Figure 6. To measure water level from in the water, a stadia rod is held on the reference marker to read 

water level above marker.

4.2.3 QA/QC

For quality assurance, each measurement should be repeated, with the field personnel switching 

roles. For example, one person will hold the stadia rod while the other will measure the water level 

through the eye level, then the people will change roles. Both readings should be recorded on the 

field data sheet, along with the average. If the repeated measurements differ by 10 cm or more, both 

readings should be repeated.

To minimize sources of error, use a firm surface on which to set the surveyors rod (e.g., a rock or a 

Secchi disk) and a firm surface on which to place the eye level (e.g., a piece of 2 × 4 lumber or the 

clipboard).

4.3 Equipment List

The following equipment and supplies are required for installing reference marks in bedrock and 

measuring water level.

Installation

aluminum dome cap markers

battery-powered hammer drill and spare battery

drill bit

canned air

reference marker (ground 

water well)

stadia rod

read measurement at 

water level
Standard Operating Procedure #4: Measuring Water Level, Version 1.1 September 2015

Water Quality Monitoring Protocol for Inland Lakes, Version 1.1 8

epoxy

hard surface for mixing epoxy (e.g., piece of cardboard or rigid plastic)

small plastic bag for garbage

GPS unit and spare batteries

compass

field notebook

Measuring Water Level

stadia rod

eye level or line and line level

GPS unit and spare batteries

compass

field notebook

photos and description of location

data sheets

firm surfaces for placing stadia rod and eye level

If installing a reference mark using a method other than gluing it in bedrock, substitute appropriate 

installation materials for those listed above. For example, if pounding in an iron rod and cementing a 

surveyors marker to the top, the following will be needed: sledge hammer, quick-crete, water for 

mixing, stir-stick, bucket for mixing, iron rod, and aluminum dome cap marker.

4.4 Literature Cited

Kallemeyn, L. W., K. Holmberg, J. Perry, and B. Odde. 2003. Aquatic synthesis for Voyageurs 

National Park. USGS Information and Technology Report USGS/BRD/ITR-2003-0001.

Lipe, J. Step-by-step instructions for leveling a staff gage. Available at 

http://www.srh.noaa.gov/ohx/dad/hydro/Doingasurvey.html (accessed 9 December 2005).

Mitsch, W. J., and J. G. Gosselink. 2000. Wetlands, third edition. John Wiley and Sons, Inc. New 

York.

National Park Service. 2002. Recommendations for core water quality monitoring parameters: Final 

report from the freshwater workgroup subcommittee. National Park Service, Ft. Collins, 

Colorado.

Sorensen, J. A., L. W. Kallemeyn, and M. Sydor. 2005. Relationship between mercury accumulation 

in young-of-the-year yellow perch and water-level fluctuations. Environmental Science and 

Technology 39:9237–9243.

Vana-Miller, D. 2002. Water resources management plan for Sleeping Bear Dunes National 

Lakeshore. National Park Service, Water Resources Division, Fort Collins, Colorado.
Standard Operating Procedure #5: Decontamination 

of Equipment to Remove Exotic Species 

Version 1.2

In Water Quality Monitoring Protocol for Inland Lakes

Prepared by

Joan Elias and David VanderMeulen*

National Park Service

Great Lakes Inventory and Monitoring Network 

2800 Lake Shore Drive East

Ashland, Wisconsin 54806

* Contact author: david_vandermeulen@nps.gov

September 2015

Suggested citation: 

Elias, J., R., and D. VanderMeulen. 2015. Standard operating procedure #5: Decontamination of 

equipment to remove exotic species, Version 1.2. In J. E. Elias, R. Axler, E. Ruzycki, and D. 

VanderMeulen. 2015. Water quality monitoring protocol for inland lakes: Great Lakes Inventory and 

Monitoring Network, version 1.1. Natural Resource Report NPS/GLKN/NRR—2015/1027. National 

Park Service, Fort Collins, Colorado.

Standard Operating Procedure #5: Decontamination of Equipment, Version 1.1 September 2015

Water Quality Monitoring Protocol for Inland Lakes, Version 1.1 i

SOP5 – Contents

Page

Revision History Log............................................................................................................................iii

Acknowledgements...............................................................................................................................iii

5.0 Introduction......................................................................................................................................1

5.1 Equipment and Supplies ..................................................................................................................1

5.2 Decontamination Procedures ..........................................................................................................3

5.3 Documentation.................................................................................................................................5

5.4 Literature Cited ...............................................................................................................................5

Appendix A. Instructions for completing a Hazard Analysis and Critical Control Point 

Plan. .......................................................................................................................................................7

Appendix B. Aquatic Invasive Species Hazard Analysis and Critical Control Point Plan 

for water quality monitoring of inland lakes at Isle Royale National Park (version 1.1). ...................11

SOP5 – Figures

Page

Figure 1. An example of a propane burner and pot used to heat water to 140° F (60° C) 

for decontaminating non-electronic equipment .....................................................................................2

Standard Operating Procedure #5: Decontamination of Equipment, Version 1.1 September 2015

Water Quality Monitoring Protocol for Inland Lakes, Version 1.1 iii

Revision History Log

The following table lists all edits and amendments to this document since the original publication 

date. Information entered in the log must be complete and concise. Users of this standard operating 

procedure will promptly notify the project manager and/or the Great Lakes Network (GLKN) data 

manager about recommended and required changes. The project manager must review and 

incorporate all changes, complete the revision history log, and change the date and version number 

on the title page and in the header of the document file. For complete instructions, please refer to 

Revising the Protocol, SOP #13.

Revision History Log:

Previous 

Version 

#

Revision 

Date

Author (with 

title and 

affiliation)

Location in Document 

and Concise 

Description of Revision Reason for Change

New 

Version 

#

1.0 3/1/2010 Richard 

Damstra, Joan 

Elias GLKN 

Aquatic 

Ecologists

 Minor clarifications 

throughout; section 

5.2.2, Procedures for 

Decontamination 

updated such that a 

single procedure is 

outlined regardless of 

remoteness of site; 

Appendix B, HACCP 

updated to include VHS 

and zebra mussels

To clarify protocol and 

bring field procedures 

and protocol into 

agreement, based on 

staff field experience.

1.1

1.1 5/1/2015 David 

VanderMeulen, 

GLKN

Updated the NPS contact 

author and fixed a few 

grammatical errors

To update contact 

author since Version 

1.1 was published in 

2010

1.2

Add rows as needed for each change or set of changes tied to an updated version number

Acknowledgements

I wish to thank Jeff Gunderson and Doug Jensen, of the Minnesota Sea Grant Program, Phil Moy, of 

the Wisconsin Sea Grant Program, and Mike Klepinger, of the Michigan Sea Grant Program, for 

their willingness to discuss exotic species issues in national parks and for providing information on 

the Hazard Analysis Critical Control Point (HACCP) method. Valena Hofman, National Park 

Service, Great Lakes Inventory and Monitoring Network prepared the HACCP plan.

Standard Operating Procedure #5: Decontamination of Equipment, Version 1.1 September 2015

Water Quality Monitoring Protocol for Inland Lakes, Version 1.1 1

5.0 Introduction

Aquatic invasive species (AIS) are an issue of increasing concern nationwide. In the Great Lakes, for 

example, approximately 140 exotic species have invaded since the late 1800s (Great Lakes 

Information Network 2005) and have had enormous ecosystem effects (e.g., Dermott and Kerec 

1997, Barnhisel and Kerfoot 2004, Hoff 2004, Great Lakes Commission 2005). Some of these 

species have invaded inland water bodies, where disruptions to native species are also documented 

(e.g., Jack and Thorp 2000, Indrisi et al. 2001, Compton and Kerfoot 2004). Zebra mussels 

(Dreissena polymorpha) now occur in several lakes at Sleeping Bear Dunes National Lakeshore, and 

the spiny waterflea (Bythotrephes cederstroemi) has been found in Grand Sable Lake, Pictured Rocks 

National Lakeshore. Invasive plants associated with waterbodies, such as hybrid cattails (Typha

glauca x Typha angustifolia), are found at many network parks, including Isle Royale. When the 

parks and Great Lakes Network conduct routine water quality monitoring, it is important to ensure 

these aquatic exotics or other emerging threats are not transferred from contaminated water bodies to 

uncontaminated water bodies.

As we conduct water quality monitoring on inland lakes, we are concerned with the limited suite of 

AIS that can adhere to, or passively catch on, sampling equipment (including waders, boats and 

trailers). In this standard operating procedure (SOP) we will focus on aquatic plants, zooplankton, 

and mussels.

At each park, we will use the Hazard Analysis Critical Control Point (HACCP) method (Gunderson 

and Kinuunen 2004) to identify water bodies at risk and locations where control of AIS is imperative. 

It is critical to integrate this SOP with monitoring for the occurrence of AIS in inland lakes.

5.1 Equipment and Supplies

The sampling equipment used in monitoring inland lakes is detailed in SOP #6. We designed the 

decontamination process to be simple, straight-forward, and consistent with NPS wilderness 

considerations. Specifically, no toxic chemicals are required for decontamination. 

The supplies and equipment required for decontamination of sampling equipment between lakes 

consists of:

 tap water

 hose and sprayer nozzle

 large pot

 portable propane burner (sold as a turkey deep fryer) or other means of heating water in a 

large pot (Figure 1)

 thermometer for measuring temperature of heated water

 scrub brushes
Standard Operating Procedure #5: Decontamination of Equipment, Version 1.1 September 2015

Water Quality Monitoring Protocol for Inland Lakes, Version 1.1 2

Figure 1. An example of a propane burner and pot used to heat water to 140° F (60° C) for 

decontaminating non-electronic equipment. Any large pot and heat source is acceptable, however a 

thermometer should be used to verify that sufficient temperatures have been achieved.
Standard Operating Procedure #5: Decontamination of Equipment, Version 1.1 September 2015

Water Quality Monitoring Protocol for Inland Lakes, Version 1.1 3

5.2 Decontamination Procedures

5.2.1 Aquatic Invasive Species Procedure Plan and Hazard Analysis Worksheet

The aquatic invasive species hazard analysis and critical control point (HACCP) worksheet is used in 

describing the sampling project, including types of gear, methods of transportation, steps involved in 

the procedure; and analyzing the potential risk of AIS transport from one water body to another, or 

one section of a stream to another section. Details on completing the worksheet are described in the 

AIS-HACCP manual (Gunderson and Kinuunen 2004), and are included in Appendix A. The 

example worksheet included in Appendix B is for Isle Royale National Park. The Network has 

modified the worksheet slightly to suit our needs. Worksheets will be completed for each park unit, 

and will be updated annually prior to the sampling season. Worksheets will also be updated in the 

following circumstances:

 change in sampling equipment or techniques 

 addition of a new water body or to the sampling regime 

 change in the order of sampling water bodies

 detection of a new AIS in a water body

 change in scientific knowledge regarding life history, potential hazard, or control of an AIS.

5.2.2 Procedures for Decontamination

Many AIS, especially plants can be controlled by simply being vigilant and periodically examining 

equipment, clothing, and boots and removing materials suspected to be an AIS species (cattail “fluff” 

or other seeds, viable plant materials, animal “hitchhikers” such as spiny water flea stuck or other 

invertebrates stuck on equipment). 

When the hazard analysis worksheet identifies a significant AIS risk and adequate drying or freezing 

of equipment is not feasible (five days in the sun for boats and trailers, 10 days for other equipment, 

or two days of freezing; Gunderson and Kinuunen 2004), the procedures below will be followed. The 

decontamination procedure assumes tap water is available.

Basic guidelines:

 Be vigilant about periodically checking equipment, clothing, and boots during portages and 

especially upon arrival and departure from sampling sites. Look for signs of AIS, especially 

plant materials.

 When possible, avoid using equipment on both infested and uninfested waters. Designate a 

set of equipment for both types of waters.

 Always begin sampling with sites not known to harbor exotic species; sample sites known or 

suspected to contain exotic species last.

 Thoroughly clean or disinfect all equipment between uses in all inland waters.

 When possible, allow sampling equipment, to dry for 10 days after sampling a water body 

known to be infested with AIS.
Standard Operating Procedure #5: Decontamination of Equipment, Version 1.1 September 2015

Water Quality Monitoring Protocol for Inland Lakes, Version 1.1 4

 Due to emerging science on the transport of AIS in felt soles of wading boots, lug soles 

constructed of a non-porous material, such as rubber, should be utilized for ease of 

decontamination (Gates 2007, Bothwell et al. 2009).

Step-by-Step Procedure:

When finished at a sampling site and before sampling the next site:

 Remove or rinse mud, plant material, invertebrates, and other visible organic material from 

boots, nets, and all sampling equipment with a hose and high pressure nozzle. 

 Non-electronic gear, such as lines, tapes, dipnets, wading boots, should be exposed to water 

heated to 140°F (60°C) and held at this temperature for at least 1 minute. Portable turkey 

fryers are ideal for this, although a large pot on a stove will work. Rags and brushes used in 

decontamination procedures should be heat treated as well. Electronic equipment such as 

flow meters, depth probes, temperature probes, data collection sondes, and associated cables 

should be rinsed with copious amounts of tap water and cleaned with brushes and/or clean 

rags. 

 Pay particular attention to lines, cracks, and crevices in equipment, and rinse well.

 Visually inspect all gear to verify that all equipment and gear has been cleaned and rinsed.

 Take measures to allow equipment to dry out as completely as possible.
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Water Quality Monitoring Protocol for Inland Lakes, Version 1.1 5

5.3 Documentation

The original AIS-HACCP worksheet and all updates will be maintained at each park and copies will 

be kept at the Network office. Documents used to complete each worksheet will also be kept on file 

at the parks and at the Network. Examples of such supporting documentation include information 

used in analyzing the hazards of contamination and determining adequate prevention of AIS spread, 

and the most current geographic range of AIS.

5.4 Literature Cited 

Barnhisel, D. R., and C. Kerfoot. 2004. Fitting into food webs: Behavioral and functional response of 

young lake trout (Salvelinus namaycush) to an introduced prey, the spiny cladoceran 

(Bythotrephes cederstroemi). Journal of Great Lakes Research 30:300–314. 

Bothwell, M. L., D. R. Lynch, H. W. Wright, and J. Deniseger. 2009. On the boots of fisherman: 

The history of didymo blooms on Vancouver Island, British Columbia. Fisheries 34:382–388.

Compton, J. A., and C. Kerfoot. 2004. Colonizing inland lakes: Consequences of YOY fish ingesting 

the spiny cladoceran (Bythotrephes cederstroemi). Journal of Great Lakes Research 30:315–326.

Dermott, R., and D. Kerec. 1997. Changes to the deepwater benthos of eastern Lake Erie since the 

invasions of Dreissena: 1979–1993. Canadian Journal of Fisheries and Aquatic Science 54:922–

930.

Gates, K. K. 2007. Myxospore detection in soil and angler movement in southwestern Montana: 

Implications for whirling disease transport. Thesis, Montana State University, Bozeman, 

Montana. 

Gunderson, J. L., and R. Kinnunen. 2004. AIS-HACCP: Aquatic nuisance species––hazard analysis 

and critical control point training curriculum, second edition. Minnesota Sea Grant Publication 

MN SG-F11.

Great Lakes Information Network. 2005. www.great-lakes.net/envt/florafauna/invasive/invasive.html (accessed 7 June 2005).

Great Lakes Commission. 2005. Great Lakes Panel on Aquatic Nuisance Species. Counterattack: 

Great Lakes Panel Targets Aquatic Nuisance Species. Available at 

www.glc.org/ans/counterattack.html (accessed 7 June 2005).

Hoff, M. H. 2004. Biotic and abiotic factors related to rainbow smelt recruitment in the Wisconsin 

waters of Lake Superior, 1978–1997. Journal of Great Lakes Research 30:414–422. 

Indrisi, N., E. L. Mills, L. G. Rudstam, and D. J. Stewart. 2001. Impact of zebra mussels (Dreissena 

polymorpha) on the pelagic lower trophic levels of Oneida Lake, New York. Canadian Journal of 

Fisheries and Aquatic Science 58:1430–1441.
Standard Operating Procedure #5: Decontamination of Equipment, Version 1.1 September 2015

Water Quality Monitoring Protocol for Inland Lakes, Version 1.1 6

Jack, J. D., and J. H. Thorp. 2000. Effects of the benthic suspension feeder Dreissena polymorpha on 

zooplankton in a large river. Freshwater Biology 44:569–580.
Standard Operating Procedure #5: Decontamination of Equipment, Version 1.1 September 2015

Water Quality Monitoring Protocol for Inland Lakes, Version 1.1 7

Appendix A. Instructions for completing a Hazard Analysis 

and Critical Control Point Plan.

The following instructions for completing HACCP Procedure Form, Potential Hazards Worksheet, 

Hazard Analysis Worksheet, and Plan are taken directly from the AIS-HACCP manual (Gunderson 

and Kinuunen 2004). Not all steps will apply to the Great Lakes Inventory and Monitoring 

Network’s protocol for decontamination of water quality monitoring field equipment and gear.

Preliminary Steps

1: Document general information.

Record the name and address of your facility or agency in the spaces provided on the first page of the 

Hazard Analysis Worksheet and the AISHACCP Plan Form (Appendix 9).

2: Describe the cultured or wild harvested fish (if applicable).

Identify the market name or Latin name (species) of the fish. Examples:

 Fathead minnows (Pimephales promelas)

 Golden shiners (Notemigonus crysoleucas)

 White sucker (Catostomus commersoni)

 Walleye (Sander vitreus)

Fully describe the product. Examples:

 Fathead minnows graded on 16 grader

 Golden shiners graded on 21 grader

 White suckers ungraded

 Rosy red minnows from Arkansas, held in ponds until distribution

 White suckers graded on a 23 grader

 Walleye fingerlings 5–8 inches

 Yellow perch fingerlings 2.5–3 inches

For management, research, and enforcement activities:

 Completely describe research or management activities

 Describe all equipment and gear that will be used

 Identify when and how activities will be conducted

Record this information in the spaces provided on the first page of the Hazard Analysis Worksheet 

and the AIS-HACCP Plan Form.
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3: Describe the harvest, production, management, research, or enforcement activity.

Identify how the product or the samples are collected, stored, and distributed. Identify whether any 

special shipping or handling methods are used. Examples:

 Wild harvested with seines, held in tanks, graded, then trucked to retail stores

 Pond-raised, seined, then held in different ponds over the winter, trucked to retail stores

 Pond-raised, trapped from ponds, then transferred directly to lakes for stocking

 Anglers on three lakes are checked for violations each day for a given period of time

 Electroshocking and seining are conducted on 10 lakes to assess year class strength

Record this information in the spaces provided on the first page of the Hazard Analysis Worksheet 

and the AIS-HACCP Plan Form.

4: Identify the intended use and customer (if applicable).

Identify how the product will be used. Examples:

 Live fishing bait

 Feeder fish (feeding pond or aquarium fish)

 Stocking into public waters

 Stocking into private waters

 Stocking into aquaculture production facility (indoor or outdoor)

 Scale and stomach samples will be brought back to the office for analysis

 Fish will be brought back for captive brood stock

Identify your intended customer or user of the product. Examples:

 General public

 A wholesaler

 A retail store

 Fish farmer

 State agency

Record this information in the spaces provided on the first page of the Hazard Analysis Worksheet 

and the AIS-HACCP Plan Form.

5: Develop a flow diagram.

The purpose of the flow diagram is to provide a clear, simple description of the steps involved in 

producing your fishery products or conducting your management, research, and enforcement 

activities. The flow diagram should cover all of the steps in the process that your firm or agency 

performs. The flow diagram should be verified on-site for accuracy. Examples of flow diagrams can 

be found in appendices 3–8.
Standard Operating Procedure #5: Decontamination of Equipment, Version 1.1 September 2015

Water Quality Monitoring Protocol for Inland Lakes, Version 1.1 9

Hazard Analysis Worksheet

6: Set up the Hazard Analysis Worksheet.

Record each of the steps from the flow diagram in column 1 of the Hazard Analysis Worksheet.

7: Identify the potential AIS-related hazards.

Record the AIS-related hazards for each step. Use your own expertise and that of others to identify 

AIS hazards related to your fish production, or management, research, or enforcement practices. 

Check with appropriate agencies to determine if the waters in which you conduct activities are 

infested with invasive species.

Even if you think you have effective hazard controls in place, record the hazard. For example, your 

equipment might be free of AIS plant material because of the: 1) absence of AIS in the area of 

harvest or sampling in an infested water body; or 2) existence of inadvertent hazard controls 

(procedures you typically use in the course of your activities that may remove AIS).

8: Complete the Hazard Analysis Worksheet.

Completing the Hazard Analysis Worksheet requires understanding potential hazards, determining if 

each potential hazard is significant, and identifying critical control points for each significant hazard 

associated with your product or activities.

AIS –HACCP Plan Form

9: Complete the AIS-HACCP Plan Form.

Copy the Critical Control Points from column 6 of the Hazard Analysis Worksheet to column 1 of 

the AIS-HACCP Plan Form. Enter the associated hazard(s) from column 2 of the worksheet to 

column 2 of the plan form. If you did not identify significant hazards and CCPs, you do not need to 

complete an AIS-HACCP plan.

Complete the AIS-HACCP Plan Form by designing techniques, methods, and treatments to deal with 

each significant hazard in column 2. For each significant hazard:

 set critical limits

 establish monitoring procedures

 establish corrective action procedures

 establish a record keeping system

 establish verification procedures

After you completed these steps for each hazard, the AIS-HACCP plan form is finished.

To signify that the AIS-HACCP plan has been accepted for implementation, the responsible 

individual on-site or a higher level official should sign and date the first page of the plan form.

Standard Operating Procedure #5: Decontamination of Equipment, Version 1.1 September 2015

Water Quality Monitoring Protocol for Inland Lakes, Version 1.1 11

Appendix B. Aquatic Invasive Species Hazard Analysis and 

Critical Control Point Plan for water quality monitoring of 

inland lakes at Isle Royale National Park (version 1.1).

Prepared by Valena Hofman, Great Lakes Network Office

March 25, 2009

Revision History Log

The following table lists all edits and amendments to this document since the original publication 

date.

Previous 

Version 

#

Revision

Date

Author (with 

title and 

affiliation)

Location in 

Document and 

Concise Description 

of Revision

Reason for 

Change

New 

Version #

1.0 02/25/2010 Richard 

Damstra

Aquatic 

Ecologist, GLKN

Added zebra mussel 

(Dreissena 

polymorpha) to all 

sections concerned 

with AIS 

invertebrates; added 

Viral Hemorrhagic 

Septicemia virus 

(VHSv) to sections on 

AIS pathogens

Zebra mussel 

documented in 

Lake Superior 

waters at ISRO in 

September 2009; 

Viral Hemorrhagic 

Septicemia virus 

(VHSv) 

documented in 

Lake Superior in 

2009.

1.1
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AIS-HACCP PLAN

Aquatic Invasive Species-Hazard Analysis and Critical Control Point Procedure Form 

Procedure Description

Park info: Park name: Isle Royale National Park (ISRO)

Address: 800 Lakeshore Drive East, Houghton, MI 49931

(if applicable): Fish species: NA

Management, 

research, or 

monitoring 

activity:

Activity: Water Quality (WQ) Monitoring of Inland Lakes by the Great Lakes Network Office 

(GLKN)

Method of 

transportation, 

distribution, 

and storage of 

boats, gear, etc.

Methods: Travel on Lake Superior waters with NPS boats to transport personnel, sampling 

equipment, and canoe to trailheads/portages to inland lakes. Sampling equipment and canoe are 

carried to inland lakes; sample site is accessed via canoe which is stabilized at site with anchor 

bags and lines. Profiles of water temperature, dissolved oxygen, specific conductance, and pH are 

collected with multi-probe sonde; field and water conditions are recorded; secchi depth is 

measured. Water is collected with an integrated sampler for lab analyses. Sometimes more than 

one lake is sampled per day.

Procedure 

Flow

List the steps 

involved in the 

management, 

research, or 

monitoring 

activity.

(1) NPS staff operates NPS boat around Isle Royale to transport personnel, equipment and canoe 

to shore or dock to access inland lakes. At times the boat is anchored out or a drop-off & pickup is required and the canoe is used on Lake Superior to paddle to shore.

(2) Equipment and canoe are portaged to inland sampling lake, on and off trail. At times 

additional lakes need to be paddled across to access sample lakes.

(3) Equipment and canoe are portaged to inland sampling lake, on and off trail. At times 

additional lakes need to be paddled across to access sample lakes.

(4) Sampling equipment, canoe and water samples are portaged to Lake Superior and the NPS 

boat. At times the canoe is used to paddle from shore to the NPS boat.

(5) Optional: If sampling is not done and an additional lake is to be sampled at this time, return to 

step 1 AND a new set of sampling equipment is obtained and/or used equipment is 

decontaminated prior to reuse. OR If sampling is done for the day, proceed to step 6.

(6) NPS motorboat is used to return to park headquarters or campsite.

(7) At the end of each sampling trip (single or multi-day), water samples are processed back at the 

park lab. Some samples may be processed in the field.

(8) At the end of each sampling trip (single or multi-day), all equipment coming in contact with any 

lake water is decontaminated; methods vary with type of equipment and use.

Upon 

completion of 

the AISHACCP plan, 

sign here to 

accept plan for 

implementation.

Name:

Signature: Date:
Standard Operating Procedure #5: Decontamination of Equipment, Version 1.1 September 2015

Water Quality Monitoring Protocol for Inland Lakes, Version 1.1 15

AIS-HACCP PLAN

Aquatic Invasive Species-Hazard Analysis and Critical Control Point Potential Hazards Worksheet 

Potential AIS Hazards

List all relevant species

AIS Fish and Other Vertebrates

Examples: round goby, ruffe, carp, 

etc.

Sea lamprey (Petromyzon marinus) and three-spine stickleback 

(Gasterosteus aculeatus) present in Lake Superior waters at Isle 

Royale. No known AIS fish and other vertebrates in inland lakes.

AIS Invertebrates

Examples: zebra mussel, spiny water 

flea, rusty crayfish, etc.

Spiny water flea (Bythotrephes longimanus) present in Lake 

Superior waters at Isle Royale. Zebra mussel (Dreissena 

polymorpha) present at Washington Harbor and Mott Island 

docks. No known AIS invertebrates in inland lakes.

AIS Plants

Examples: curly pondweed, Eurasian 

water-milfoil, etc.

Narrow-leaved and hybrid cattail (Typha angustifolia and T. x

glauca) found along Lake Superior shoreline and numerous 

inland lakes, streams, and wetlands.

AIS Pathogens

Examples: whirling disease,

Heterosporis, etc.

Viral Hemorrhagic Septicemia virus (VHSv) detected in Lake 

Superior; not known in inland lakes.

Next Step:

After identifying the potential hazards, complete a hazard analysis form.
Standard Operating Procedure #5: Decontamination of Equipment, Version 1.1 September 2015

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AIS-HACCP PLAN

Aquatic Invasive Species-Hazard Analysis and Critical Control Point Hazard Analysis Worksheet

(1) (2) (3) (4) (5) (6)

Activity Hazards Significance Justification Control CCP

Activity step from 

flow diagram, page

1

Potential AIS hazards introduced or 

controlled at this step (from potential 

hazards worksheet)

Are AIS

hazards 

significant? 

(Yes/No)

Justify your decisions for column 3.

What control measures will be 

applied to prevent the 

significant hazards?

Is this step a critical 

control point?

(Yes/No)

Work Flow Step (1):

NPS staff operates 

NPS boat around Isle 

Royale to transport 

personnel, 

equipment, and 

canoe to beach or 

dock access to inland 

lakes. At times the 

boat is anchored out 

or a drop-off & pickup is required and 

the canoe is used to 

paddle to shore.

Fish/Other Vertebrates

Sea lamprey (Petromyzon marinus) and 

three-spine stickleback (Gasterosteus 

aculeatus)

No Sea lamprey and three-spine stickleback 

present in Lake Superior waters. Boat and 

equipment used will not capture either.

No

Invertebrate

Spiny water flea (Bythotrephes 

longimanus) and Zebra mussel 

(Dreissena polymorpha)

Yes Spiny water flea and zebra mussel 

documented in Lake Superior waters; no 

documentation of presence in the inland 

lakes. Canoe may be used on Lake 

Superior.

If in contact with Lake Superior 

waters, wipe down paddles, 

entire hull of canoe, and any 

sampling equipment with a cloth 

and inspect for invertebrates. 

Yes

Plant

Cattail species (Typha x glauca & Typha 

angustifolia)

Yes Invasive cattail species documented along 

shorelines of Lake Superior and numerous 

inland lakes.

Hazard controlled simultaneous 

with invertebrate hazard control 

(above).

No

Pathogens

Viral Hemorrhagic Septicemia virus 

(VHSv)

No VHSv documented in Lake Superior. Hazard controlled simultaneous 

with invertebrate hazard control 

(above).

No

Work Flow Step (2): 

Equipment and 

canoe are portaged 

to inland sampling 

lake, on and off trail. 

At times additional 

lakes need to be 

paddled across to 

access sample lakes. 

Fish/Other Vertebrates

N/A

No No AIS fish/vertebrates documented on 

inland lakes.

No

Invertebrate 

N/A

No No documentation of spiny water flea or 

zebra mussel in the inland lakes. 

Routine precautionary wiping 

with a cloth and inspection of 

canoe and paddles if used on 

additional inland lakes.

No

Plant

Cattail species (Typha x glauca & Typha 

angustifolia)

Yes Invasive cattail species are documented 

along shorelines of numerous inland 

lakes, streams, and wetlands. 

Periodically inspect for and 

remove any viable cattail plant 

material from canoe, equipment, 

clothes, and shoes.

Yes
Standard Operating Procedure #5: Decontamination of Equipment, Version 1.1 September 2015

Water Quality Monitoring Protocol for Inland Lakes, Version 1.1 18

AIS-HACCP PLAN

Aquatic Invasive Species-Hazard Analysis and Critical Control Point Hazard Analysis Worksheet (continued)

(1) (2) (3) (4) (5) (6)

Activity Hazards Significance Justification Control CCP

Activity step from 

flow diagram, page

1

Potential AIS hazards introduced or 

controlled at this step (from potential 

hazards worksheet)

Are AIS

hazards

significant? 

(Yes/No)

Justify your decisions for column 3.

What control measures will be 

applied to prevent the 

significant hazards?

Is this step a critical 

control point?

(Yes/No)

Pathogens

N/A

No No AIS Pathogens documented on inland 

lakes.

No

Work Flow Step (3): 

Once at sample lake, 

canoe is used to 

access WQ sample 

site; anchor bags 

(filled with rocks 

from the sample 

lake) and lines 

secure boat at site. 

WQ parameters are 

measured with a 

multi-probe sonde, 

clarity measured 

with a secchi disc 

and field notes are 

recorded; water 

sample is collected 

with an integrated 

sampler for lab 

analysis. 

Fish/Other Vertebrates

N/A

No No AIS fish/ vertebrates in inland lakes. No

Invertebrate

N/A 

No No documentation of spiny water flea or 

zebra mussel in the inland lakes.

No

Plant

Cattail species (Typha x glauca & Typha 

angustifolia)

No Potential to increase spread of invasive 

cattails, but overall, minimal hazard to 

lakes with existing cattail populations.

Avoid cattails and viable cattail 

plant material as a 

precautionary measure.

No

Pathogens

N/A

No No AIS Pathogens documented on inland 

lakes.

No

Work Flow Step (4):

Sampling equipment, 

canoe and water 

samples are portaged 

to Lake Superior and 

the NPS boat. At 

times the canoe is 

used to paddle from 

shore to the NPS 

boat.

Fish/Other Vertebrates

Sea lamprey (Petromyzon marinus) and 

three-spine stickleback (Gasterosteus 

aculeatus)

No No AIS fish/ vertebrates in the inland 

lakes. Equipment and canoe will not catch 

or transport fish or vertebrates on Lake 

Superior.

No

Invertebrate

Spiny water flea (Bythotrephes 

longimanus) and zebra mussel 

(Dreissena polymorpha)

No No documentation of spiny water flea or 

zebra mussel in the inland lakes. Spiny 

water flea and zebra mussel documented 

in Lake Superior waters; at times canoe 

may be paddled on Lake Superior waters 

to access NPS boat. 

If canoe, paddles, and any 

equipment contact Lake 

Superior waters, these hazards 

must be addressed in step 5 

(optional), if sampling an 

additional lake, or in step 8.

No

(see steps 5 or 8)
Standard Operating Procedure #5: Decontamination of Equipment, Version 1.1 September 2015

Water Quality Monitoring Protocol for Inland Lakes, Version 1.1 19

AIS-HACCP PLAN

Aquatic Invasive Species-Hazard Analysis and Critical Control Point Hazard Analysis Worksheet (continued)

(1) (2) (3) (4) (5) (6)

Activity Hazards Significance Justification Control CCP

Activity step from 

flow diagram, page

1

Potential AIS hazards introduced or 

controlled at this step (from potential 

hazards worksheet)

Are AIS

hazards

significant? 

(Yes/No)

Justify your decisions for column 3.

What control measures will be 

applied to prevent the 

significant hazards?

Is this step a critical 

control point?

(Yes/No)

Plant

Cattail species (Typha x glauca & Typha 

angustifolia)

Yes Invasive cattail species are documented 

along shorelines of numerous inland 

lakes, streams, and wetlands, and Lake 

Superior shorelines. Unintentional 

transport could spread populations.

Periodically inspect for and 

remove any viable cattail plant 

material from canoe, equipment, 

clothes, and shoes. 

Yes

Pathogens

Viral Hemorrhagic Septicemia virus 

(VHSv)

No VHSv documented in Lake Superior. If canoe or paddles contact Lake 

Superior waters, these hazards 

must be addressed in step 5 

(optional), if sampling an 

additional lake, or in step 8.

No

Work Flow Step 5 

(optional):

If sampling is not 

done for the day and 

an additional lake is 

to be sampled at this 

time, return to step 1 

AND a new set of 

sampling equipment 

is obtained and/or 

used equipment is 

decontaminated 

prior to reuse. 

OR

If sampling is done

for the day, proceed 

to step (6).

Fish/Other Vertebrates

Sea lamprey (Petromyzon marinus) and 

three-spine stickleback (Gasterosteus 

aculeatus)

No Equipment used and decontamination 

procedures will not capture any fish or 

vertebrates. 

No

Invertebrate

Spiny water flea (Bythotrephes 

longimanus) and zebra mussel 

(Dreissena polymorpha)

Yes Routine decontamination prevents 

potential hazards. 

Canoe, paddles, and equipment may be 

contaminated if canoe was paddled from 

shore to NPS boat in previous step.

Standard sampling protocol: 

For next sample lake, obtain a 

new set of sampling equipment 

(i.e., lines, anchor bags, I-tube) 

or decontaminate (wipe, rinse 

and inspect) used equipment 

(i.e., probe, canoe, paddles, 

secchi disc) before use in second 

lake.

If canoe and paddles are to be 

used on Lake Superior to access 

next sample lake, 

decontamination of these items 

can wait until returning to step 

1. 

Yes

Plant

Cattail species (Typha x glauca & Typha 

angustifolia)

No Routine decontamination addresses 

potential hazards.

The above precautionary control 

measures address this low 

potential hazard.

No
Standard Operating Procedure #5: Decontamination of Equipment, Version 1.1 September 2015

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AIS-HACCP PLAN

Aquatic Invasive Species-Hazard Analysis and Critical Control Point Hazard Analysis Worksheet (continued)

(1) (2) (3) (4) (5) (6)

Activity Hazards Significance Justification Control CCP

Activity step from 

flow diagram, page

1

Potential AIS hazards introduced or 

controlled at this step (from potential 

hazards worksheet)

Are AIS

hazards

significant? 

(Yes/No)

Justify your decisions for column 3.

What control measures will be 

applied to prevent the 

significant hazards?

Is this step a critical 

control point?

(Yes/No)

Pathogens

None known

No No AIS pathogens present. No

Work Flow Step (6):

NPS motorboat is 

used to return to 

headquarters or 

campsite

Fish/Other Vertebrates

Sea lamprey (Petromyzon marinus) and 

three-spine stickleback (Gasterosteus 

aculeatus)

No Sea lamprey and three-spine stickleback 

present in Lake Superior waters. NPS 

boat does not leave Lake Superior waters

and is not a transport vector.

No

Invertebrate

Spiny water flea (Bythotrephes 

longimanus) and zebra mussel 

(Dreissena polymorpha)

No Spiny water flea and zebra mussel 

documented in Lake Superior waters; NPS 

boat does not leave Lake Superior waters 

and is not a transport vector. 

No

Plant

Cattail species (Typha x glauca & Typha 

angustifolia)

No Cattail species documented along 

shorelines of Lake Superior; NPS boat 

does not leave Lake Superior waters and 

is a low-risk transport vector.

No

Pathogens

Viral Hemorrhagic Septicemia virus 

(VHSv)

No VHSv documented in Lake Superior. No

Work Flow Step (7):

Water samples are 

processed back at the 

park lab at the end of 

each sampling trip 

(single or multi-day). 

Some samples may 

be processed in the 

field. 

Fish/Other Vertebrates

N/A

No No AIS fish/ vertebrates in sample water. 

Equipment used will not capture any fish.

No
Standard Operating Procedure #5: Decontamination of Equipment, Version 1.1 September 2015

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AIS-HACCP PLAN

Aquatic Invasive Species-Hazard Analysis and Critical Control Point Hazard Analysis Worksheet (continued)

(1) (2) (3) (4) (5) (6)

Activity Hazards Significance Justification Control CCP

Activity step from 

flow diagram, page

1

Potential AIS hazards introduced or 

controlled at this step (from potential 

hazards worksheet)

Are AIS

hazards

significant? 

(Yes/No)

Justify your decisions for column 3.

What control measures will be 

applied to prevent the 

significant hazards?

Is this step a critical 

control point?

(Yes/No)

Invertebrate 

N/A

No No documentation of AIS invertebrates in 

the inland lakes/ sample water.

No

Plant

Cattail species (Typha x glauca & Typha 

angustifolia)

No Equipment used and processing procedure 

will not capture AIS plants.

No

Pathogens

N/A

No No AIS pathogens in inland lakes/ sample 

water.

No

Work Flow Step (8): 

At the end of each 

sampling trip (single 

or multi-day) all 

equipment coming in 

contact with Lake 

Superior or inland 

lake water is 

decontaminated; 

method depending on 

type of equipment 

and use.

Fish/Other Vertebrates

Sea lamprey (Petromyzon marinus) and 

three-spine stickleback (Gasterosteus 

aculeatus)

No No AIS fish/ vertebrates present in inland 

lakes. Equipment used will not transport 

nor capture any fish.

No

Invertebrate

Spiny water flea (Bythotrephes 

longimanus) and zebra mussel 

(Dreissena polymorpha)

Yes Potential spiny water flea and zebra 

mussel contamination during NPS boat 

ride and canoe use on Lake Superior. 

Routine equipment 

decontamination procedures, 

using combination of heat, 

physical removal and 

desiccation, prevents hazards. 

All sampling equipment, canoe, 

and paddles are 

decontaminated.

Yes

Plant

Cattail species (Typha x glauca & Typha 

angustifolia)

Yes Potential AIS plant contamination during 

canoe use on Lake Superior.

Hazards controlled 

simultaneously with 

decontamination procedures 

listed above.

No

Pathogens

Viral Hemorrhagic Septicemia virus 

(VHSv)

No VHSv documented in Lake Superior. Hazards controlled 

simultaneously with 

decontamination procedures 

listed above.

No
Standard Operating Procedure #5: Decontamination of Equipment, Version 1.1 September 2015

Water Quality Monitoring Protocol for Inland Lakes, Version 1.1 23

AIS-HACCP PLAN

Aquatic Invasive Species-Hazard Analysis and Critical Control Point AIS-HACCP Plan Form 

Critical 

Control Point

Each row answered “yes”

in column 6 of Hazard Analysis 

Form

(1) Work Flow Step (1): NPS staff 

operates NPS boat around Isle Royale to 

transport personnel, equipment, and canoe to 

beach or dock access to inland lakes. At times 

the boat is anchored out or a drop-off & pick-up 

is required and the canoe is used to paddle to 

shore.

(1) Work Flow Step (2): Equipment and canoe 

are portaged to inland sampling lake, on and off trail. 

At times additional lakes need to be paddled across to 

access sample lakes. 

Significant 

Hazards

as determined in column 3

of Hazard Analysis Form

(2) Spiny water flea (Bythotrephes longimanus) 

and zebra mussel (Dreissena polymorpha)

documented in Lake Superior waters. Potential 

introduction of spiny water flea and zebra 

mussel veligers on WQ sampling equipment if 

canoeing on Lake Superior and during NPS boat 

transport (i.e., water in boat, bow spray).

(2) Cattail species (Typha x glauca & Typha 

angustifolia) documented along Lake Superior 

shoreline and shorelines of numerous inland lake, 

streams, and wetlands. 

Limits for Each 

Control Measure

(3) If using canoe on Lake Superior waters, or 

if canoe was splashed during transport, wipe 

down paddles and entire hull of canoe with a 

cloth and inspect for invertebrates. 

(3) Periodically inspect for and remove any viable 

cattail plant material from canoe, equipment, clothes 

and shoes; particularly after passing cattail 

populations and/or wetlands, shorelines or paddling 

across additional lakes. If at the source of cattail 

hazard, leave vegetation there, otherwise pack out 

and throw away in trash.

Monitoring

Describe what is being

monitored

(4) Canoe, paddles, and equipment being 

monitored for presence of spiny water flea, zebra 

mussel veligers, and Lake Superior water 

contamination. 

(4) Presence of viable cattail plant material on 

equipment (including canoe and paddles), clothing, 

and boots/shoes. Ensure that boat and all equipment 

is free of dirt, mud, and viable plant parts. Viable 

cattail plant material includes, fruiting parts, “fluff”, 

and roots/ tubers/ rhizomes. It does not include 

leaves, or stalks. 

Explain how the monitoring

will take place

(5) Visual inspection of equipment, canoe and 

paddles upon reaching shore after paddling on 

Lake Superior or after a NPS boat ride in which 

equipment is wet with Lake Superior water (i.e., 

due to wave spray).

(5) Visual inspection of equipment, clothing, and 

boots/shoes.

Frequency of monitoring (6) Each time, before equipment is used in a 

lake, after equipment, canoe and paddles are 

exposed to Lake Superior waters.

(6) Ongoing during the portage, especially after 

passing cattail populations, wetlands, shorelines or 

after paddling across additional lakes while accessing 

the sample lake.

Person or position

responsible for monitoring

(7) Water quality monitoring staff. (7) Water quality monitoring staff.

Corrective Actions

Actions taken when limits

of control measures are

not met

(8) Cease operation and re-wipe equipment 

with a new clean cloth to dislodge invertebrates, 

rinse with non-Lake Superior water (tap or 

inland lake water sample), or obtain a new set of 

decontaminated equipment.

(8) Clean equipment again with physical removal 

and rinsing with tap water, if needed, and inspect 

again.

Verification

Method of verification

(9) Personal communication among crew. 

Review record.

(9) Personal communication among crew. Review 

record.

Records

List what is recorded at

each critical control point

(10) Check sampling equipment, canoe and 

paddles for Lake Superior water contamination, 

check for viable cattail vegetation. Record Y/N 

to presence of spiny water flea, zebra mussel and 

cattail vegetation; document actions taken if Y 

and final result on record (i.e., wiped and 

inspected, free of invertebrates).

(10) Check sampling equipment, canoe/paddles, 

clothing, and boots/shoes for viable cattail plant 

material. Record Y/N to presence of cattail 

vegetation; document actions taken if Y and final 

result on record (i.e., removed cattail fluff from 

backpack, backpack clean).
Standard Operating Procedure #5: Decontamination of Equipment, Version 1.1 September 2015

Water Quality Monitoring Protocol for Inland Lakes, Version 1.1 24

AIS-HACCP PLAN

Aquatic Invasive Species-Hazard Analysis and Critical Control Point AIS-HACCP Plan Form (continued) 

Critical 

Control Point

Each row answered “yes”

in column 6 of Hazard Analysis 

Form

(1) Work Flow Step (4): Sampling 

equipment, canoe and water samples are 

portaged to Lake Superior and the NPS boat. At 

times the canoe is used to paddle from shore to 

the NPS boat. 

(1) Work Flow Step (5 optional): 

 If sampling is not done for the day and an 

additional lake is to be sampled at this time, 

return to step 1 AND a new set of sampling 

equipment is obtained and/or used equipment is 

decontaminated prior to reuse. 

 NOTE: If sampling is done for the day, 

proceed to step 6; this critical control point does 

not apply.

Significant 

Hazards

as determined in column 3

of Hazard Analysis Form

(2) Spiny water flea (Bythotrephes longimanus)

and zebra mussel (Dreissena polymorpha) 

documented in Lake Superior waters. Potential 

introduction of spiny water flea on WQ sampling 

equipment if canoeing on Lake Superior.

(2) Spiny water flea (Bythotrephes longimanus) 

and zebra mussel (Dreissena polymorpha) 

documented in Lake Superior waters. Potential 

introduction of spiny water flea and zebra mussel 

veligers on WQ sampling equipment if canoeing 

on Lake Superior.

Limits for Each 

Control Measure

(3) If using canoe on Lake Superior waters, or 

if canoe was splashed during transport, wipe 

down paddles and entire hull of canoe with a 

cloth and inspect for invertebrates. 

(3) If canoe was used to paddle on Lake 

Superior from shore to NPS boat, the canoe, 

paddles, and equipment may be contaminated 

with invertebrates. If sampling is not done for the 

day and an additional lake is to be sampled at 

this time, obtain a new set of sampling equipment 

(i.e., lines, anchor bags, I-tube) or decontaminate 

(wipe, rinse and inspect) used equipment (i.e., 

probe, canoe, paddles, secchi disc) before use in 

second lake. 

 If canoe and paddles are to be used on 

Lake Superior to access next sample lake, 

decontamination of these items can wait (they 

will be addressed again in step 1, after being reused). 

 NOTE: If sampling is done for the day, 

this critical control point does not apply.

Monitoring

Describe what is being

monitored

(4) Canoe, paddles, and equipment being 

monitored for presence of spiny water flea, zebra 

mussel veligers, and Lake Superior water 

contamination. 

(4) Canoe, paddles, and equipment being 

monitored for presence of spiny water flea, zebra 

mussel veligers, and Lake Superior water 

contamination. 

Explain how the monitoring

will take place

(5) Visual inspection of equipment, canoe and 

paddles upon reaching shore after paddling on 

Lake Superior or after a NPS boat ride in which 

equipment is wet with Lake Superior water (i.e., 

due to wave spray).

(5) Visual inspection of equipment, canoe, and 

paddles upon reaching NPS boat after paddling 

on Lake Superior from shore.

Frequency of monitoring (6) Each time, before equipment is used in a 

lake, after equipment, canoe and paddles are 

exposed to Lake Superior waters.

(6) Upon reaching the NPS boat or at the 

latest, prior to portaging to next sample lake.

Person or position

responsible for monitoring

(7) Water quality monitoring staff. (7) Water quality monitoring staff.

Corrective Actions

Actions taken when limits

of control measures are

not met

(8) Cease operation and re-wipe equipment 

with a new clean cloth to dislodge invertebrates, 

rinse with non-Lake Superior water (tap or 

inland sample lake water), or obtain a new set of 

decontaminated equipment.

(8) Cease operation and repeat 

decontamination procedures as required based 

on type of equipment and use; obtain new, 

decontaminated set of sampling equipment prior 

to accessing sample lake.

Verification

Method of verification

(9) Personal communication among crew. 

Review record.

(9) Personal communication among crew. 

Review record.
Standard Operating Procedure #5: Decontamination of Equipment, Version 1.1 September 2015

Water Quality Monitoring Protocol for Inland Lakes, Version 1.1 25

AIS-HACCP PLAN

Aquatic Invasive Species-Hazard Analysis and Critical Control Point AIS-HACCP Plan Form (continued) 

Records

List what is recorded at

each critical control point

(10) Check sampling equipment, 

canoe/paddles, clothing, and boots/shoes for 

viable cattail plant material. Record Y/N to 

presence of cattail vegetation; document actions 

taken if Y and final result on record (i.e., 

removed cattail fluff from backpack, backpack 

clean).

(10) Document if only lake or second (other) 

lake sampled today; record Y/N that all 

equipment for second (other) lake has either been 

decontaminated and/or is a new clean set prior 

to sampling. 

Critical 

Control Point

Each row answered “yes”

in column 6 of Hazard Analysis 

Form

(1) Work Flow Step (8): At the end of 

each sampling trip (single or multi-day) all 

equipment coming in contact with Lake Superior 

or inland lake water is decontaminated; method 

depending on type of equipment and use.

(1) 

Significant 

Hazards

as determined in column 3

of Hazard Analysis Form

(2) Bythotrephes longimanus and Dreissena 

polymorpha documented in Lake Superior 

waters. Potential introduction of invertebrates 

on WQ sampling equipment if canoeing on Lake 

Superior and during NPS boat transport (i.e., 

water in boat, bow spray).

(2) 

Limits for Each 

Control Measure

(3) Routine decontamination procedures for all 

sampling equipment coming into contact with 

any lake water. Methods as of 2008:

- soft equipment and some hard equipment 

(anchor bags, lines, and secchi disc) are soaked 

in hot water (140°F) for 1 minute.

- hard equipment (multi-probe, secchi disc, Itube, paddles) are wiped down, rinsed with tap 

water and visually inspected

OR

- all equipment is allowed to dry thoroughly and 

remain dry for at least 5 days.

(3) 

Monitoring

Describe what is being

monitored

(4) Water quality sampling equipment, 

everything that comes in contact with any lake 

(large or inland sample). 

(4) 

Explain how the monitoring

will take place

(5) Visual inspection during and post routine 

decontamination.

(5) 

Frequency of monitoring (6) At least once at end of decontamination. (6) 

Person or position

responsible for monitoring

(7) Water quality monitoring staff. (7) 

Corrective Actions

Actions taken when limits

of control measures are

not met

(8) If dirty used equipment or presence of 

invertebrates is found; cease operation and 

repeat decontamination procedures as specified; 

change method if necessary. Re-inspect to ensure 

equipment is clean. 

(8) 

Verification

Method of verification

(9) Personal communication among crew. 

Review record.

(9) 
Standard Operating Procedure #5: Decontamination of Equipment, Version 1.1 September 2015

Water Quality Monitoring Protocol for Inland Lakes, Version 1.1 26

AIS-HACCP PLAN

Aquatic Invasive Species-Hazard Analysis and Critical Control Point AIS-HACCP Plan Form (continued) 

Records

List what is recorded at

each critical control point

(10) Record the equipment receiving 

decontamination and the method(s) used. Check 

for and mark Y/N for presence of invertebrates 

and/or cattail, and action taken if Y.

(10) 

This form accommodates two Critical Control points. Attach additional pages of this form as 

necessary.

Final Step: 

Once the HACCP plan is completed, attach it to the signed procedure form with the hazard analysis 

worksheets.
Standard Operating Procedure #6: Field 

Measurements and Water Sample Collection

Version 1.2

In Water Quality Monitoring Protocol for Inland Lakes

Prepared by

Richard Axler and Elaine Ruzycki

Center for Water and the Environment

Natural Resources Research Institute

University of Minnesota–Duluth

5013 Miller Trunk Highway

Duluth, Minnesota 55811

and

Joan Elias and David VanderMeulen*

National Park Service

Great Lakes Inventory and Monitoring Network 

2800 Lake Shore Drive East

Ashland, Wisconsin 54806

* Contact author: david_vandermeulen@nps.gov

September 2015

Suggested citation: 

Axler, R., E. Ruzycki, J. E. Elias, and D. VanderMeulen. 2015. Standard operating procedure #6: 

Field measurements and water sample collection, version 1.2. In J. E. Elias, R. Axler, E. Ruzycki, 

and D. VanderMeulen. 2015. Water quality monitoring protocol for inland lakes: Great Lakes 

Inventory and Monitoring Network, version 1.1. Natural Resource Report NPS/GLKN/NRR—

2015/1027. National Park Service, Fort Collins, Colorado.

Standard Operating Procedure #6: Field Measurements and Water Sample Collection, Version 1.2 September 2015

Water Quality Monitoring Protocol for Inland Lakes, Version 1.1 i

SOP6 – Contents

Page

Revision History Log............................................................................................................................iii

Acknowledgements...............................................................................................................................iii

6.0 Introduction......................................................................................................................................1

6.1 Equipment and Supplies ..................................................................................................................2

6.2 Overview of Field Work ..................................................................................................................4

6.3 Field Measurement Procedures........................................................................................................8

6.4 Water Sample Collection ...............................................................................................................16

6.5 Departing From the Monitoring Site..............................................................................................18

6.6 Quality Assurance/Quality Control (QA/QC)................................................................................19

6.7 Data and Records Management .....................................................................................................29

6.8 Literature Cited ..............................................................................................................................30

Attachments .........................................................................................................................................32

SOP6 – Tables

Page

Table 1. Typical sensor performance specificationsafor field instruments (Penoyer 

2003). .....................................................................................................................................................2

Table 2. Checklist of field equipment and supplies required for monitoring water quality..................3

Table 3. Recommended instrument stabilization criteria for recording field 

measurements.........................................................................................................................................9

Table 4. Ideal calibration frequency and acceptance criteria. .............................................................19

Table 5. Post-calibration check error limits. .......................................................................................24

Table 6. Frequency, acceptable range, and corrective actions for duplicate samples. ........................27

Table 7. Summary of QA/QC documentation and sampling methods................................................28

Standard Operating Procedure #6: Field Measurements and Water Sample Collection, Version 1.2 September 2015

Water Quality Monitoring Protocol for Inland Lakes, Version 1.1 iii

Revision History Log

The following table lists all edits and amendments to this document since the original publication 

date. Information entered in the log must be complete and concise. Users of this standard operating 

procedure will promptly notify the project manager and/or the Great Lakes Network (GLKN) data 

manager about recommended and required changes. The project manager must review and 

incorporate all changes, complete the revision history log, and change the date and version number 

on the title page and in the header of the document file. For complete instructions, please refer to 

Revising the Protocol, SOP #13.

Revision History Log:

Previous 

Version 

#

Revision 

Date

Author (with 

title and 

affiliation)

Location in Document and 

Concise Description of 

Revision Reason for Change

New 

Version 

#

1.0 2/18/2010 Richard 

Damstra, David 

VanderMeulen, 

Joan Elias, 

GLKN 

Clarified some verbiage 

throughout, made changes to 

field sequence, field gear 

checklist, added optical DO 

probe info, equipment blank 

procedures, and data backup 

procedures.

To clarify protocol and 

bring field procedures 

and protocol into 

agreement, based on 

new equipment and 

staff field experience. 

1.1

1.1 5/01/2015 David 

VanderMeulen, 

GLKN

Updated the NPS contact author, 

added information about 

continuous monitoring, added 

information about thermal 

arrays, referenced the Aquarius

database, fixed a handful of 

grammatical errors throughout

To clarify and update 

SOP based on changes 

that have occurred 

since Version 1.1 was 

published in 2010

1.2

Add rows as needed for each change or set of changes tied to an updated version number

Acknowledgements

Combinations of existing protocols were used to develop this standard operating procedure for 

measuring the required water quality field parameters for the Great Lakes Network (GLKN). We 

consulted protocols written for the EPA, USGS, an online curriculum for monitoring water quality, 

this and other NPS networks, NPS internal documents, and the NPS–WRD website. We wish to 

acknowledge these sources and thank them for the valuable contribution that they have made to this 

document.

Standard Operating Procedure #6: Field Measurements and Water Sample Collection, Version 1.2 September 2015

Water Quality Monitoring Protocol for Inland Lakes, Version 1.1 1

6.0 Introduction

Field measurements should represent, as closely as possible, the natural condition of the surface 

water at the time of sampling. Experience with and knowledge of the sampling equipment and the 

collection, storage, and processing of water samples for subsequent laboratory analyses are critical

for collecting data of high quality. To ensure consistent, high-quality data, always:

 Make field measurements only with calibrated instruments that have been error-checked. 

 Maintain a permanent log book for each field instrument for recording calibrations and 

repairs. Review the log book before leaving for the field. This book should also be used for 

recording results of pre-and post-calibration checks as well as housing copies of results from 

alternate measurement sensitivity (AMS) checks, if applicable. 

 Test each instrument (meters and sensors) before leaving for the field. Become familiar with 

new instruments and new measurement techniques before collecting data. 

 Have backup instruments readily available and in good working condition, whenever 

possible. 

 Follow quality assurance/quality control procedures in SOP #12. Such 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 to minimize 

artifacts that can bias the result. Check field-measurement precision and accuracy (variability 

and bias). 

6.0.1 Core Suite of Water Quality Variables

The core field variables are temperature, specific conductance, pH, water level, and dissolved

oxygen, all of which are mandated by the National Park Service Water Resources Division (NPSWRD). To this mandated suite, GLKN has added a measure of water clarity. Depth profiles of 

temperature, specific conductance, pH, and dissolved oxygen will be measured at each sampling 

station using a multiparameter instrument (multiprobe). Continuous water temperature profile data 

will be collected from a subset of inland lakes across four parks (Isle Royale and Voyageurs national 

parks, and Pictured Rocks and Sleeping Bear Dunes national lakeshores) that contain a significant 

number of inland lakes. Water level will be measured at benchmark stations with an eye or laser 

level and a surveyor’s rod (described in detail in SOP #4). Water clarity will be measured with a 

transparency tube or Secchi disk. The expected ranges and resolutions required of multiprobes are 

listed in Table 1, and the methods for taking field measurements are described in Section 6.4.

6.0.2 Advanced Suite of Water Quality Variables

The advanced suite variables consist of total phosphorus, total nitrogen, nitrate+nitrite-nitrogen, 

ammonia-nitrogen, sulfate, chloride, magnesium, calcium, potassium, sodium, dissolved silica, 

dissolved organic carbon, alkalinity, and total chlorophyll-a. The methods for collecting water 

samples for these variables are described in Section 6.5. These water quality variables were chosen to 

monitor effects of the likely stressors on the resource, including land use change and atmospheric

deposition. Other variables symptomatic of contamination (e.g., DDT and PCBs) are addressed in 

GLKN’s protocol for monitoring bioaccumulative contaminants (Route et al. 2009).
Standard Operating Procedure #6: Field Measurements and Water Sample Collection, Version 1.2 September 2015

Water Quality Monitoring Protocol for Inland Lakes, Version 1.1 2

6.1 Equipment and Supplies 

6.1.1 Instrument Specifications

Toward low bias and high precision of water quality data for this protocol, Table 1 lists typical field 

sensor performance specifications that should be expected from monitoring equipment for this 

protocol. Multiparameter sensor instruments (or multiprobes), while expensive, are convenient and 

commonly used in water quality monitoring. A multiprobe instrument should be selected based on 

the observable range for each variable. However, an additional investment in a back-up set of less 

expensive individual sensors will help ensure the development of a long-term data set, should the 

multiprobe not be working properly.

Table 1. Typical sensor performance specificationsafor field instruments (Penoyer 2003).

Sensor

Expected 

Range

Reporting 

ResolutionbEstimated Biasc

Temperature -5°C to 45°C 0.01°C ±0.15°C

Specific Conductivity 

(SC25)

0 to 2000 

μS/cm

1 μS/cm 

(range 

dependent)

±0.5% of reading + 1 μS/cm

pH 1 to 14 units 0.01 unit ±0.2 units

Dissolved Oxygen

(Concentration) 0 to 50 mg/L 0.01 mg/L 0 to 20 mg/L ±0.2 mg/L;20 to 50 mg/L ±0.6 mg/L

Dissolved Oxygen

(% saturation) 0%–200% 0.1% ca. ±2 %

Turbidity --- --- ---

Depth - Z

(pressure sensor) 0–>100 m 0.1 m ca. 0.1 m

a

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 Irwin 2004 for more details). 

b 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 Irwin (2004). 

c Estimated bias specifications reflect the uncertainty in measurement of the instrument and sensor in 

combination only, and not other factors that can affect accuracy, such as environmental variables or the ability of 

field personnel to calibrate and operate the instrument using proper protocols.

Instrument-specific estimations of the range of uncertainty for each variable must be calculated for 

use in the interpretation of data. Therefore documentation will be maintained regarding the ability of 

each multiprobe to meet the data quality objectives of this project; blank forms are included in SOP 

#12. The completed forms for each multiprobe will be maintained along with the calibration and 

maintenance logs for the multiprobe.
Standard Operating Procedure #6: Field Measurements and Water Sample Collection, Version 1.2 September 2015

Water Quality Monitoring Protocol for Inland Lakes, Version 1.1 3

Details on estimating instrument sensitivity are included in SOP #12, Quality Assurance/Quality 

Control. Because field equipment is likely to change during the course of this long-term monitoring 

project, QA/QC procedures must be followed on documenting cumulative bias (SOP #12).

6.1.2 Additional Equipment, Supplies, Forms, etc.

Refer to the checklist of supplies and equipment needed for field sampling (Table 2) prior to each 

sampling trip. Keep on hand all necessary forms, calibration logbooks, field logbooks, field data 

sheets, procedural manuals, and equipment instructional manuals.

Table 2. Checklist of field equipment and supplies required for monitoring water quality.

√ Equipment and Supplies

Field notebook, pencils, and pen (waterproof ink) 

New field forms on waterproof paper 

Up-to-date field folders containing recent data sheets for field comparison (copies only; never take 

originals in the field)

Multiparameter instrument (calibrated), calibration standards, check solutions, data logger 

Long and short cables for multiprobe instrument(s)

Equipment for thermal arrays (temperature sensors, lines, buoys, anchor, data logger, etc.)

Calibration logbook for each instrument 

All maintenance parts and calibration standards for field instruments 

Backup instruments in case of electronic failure of multiprobe (for example: YSI 85 [T-DO-SC25] or 

equivalent, YSI 200 [T-DO], Hannah Dist3 [SC25], armored NIST certified thermometer [°C], portable 

pH meter)

Transparency tube

Secchi disk and metered line (marked at 0.5 m intervals) 

Sounding weight(s)

Surveyor’s rod and level

Water samplers: Integrating tube, Van Dorn type sampler 

Compositing jug and other bottles, including brown or amber bottles for chlorophyll-a

Sonde with barometric pressure sensor, weather radio barometer, or other way to obtain barometric 

pressure

Pocket calculator (waterproof, if possible) 

Extra batteries for all field equipment (multiparameter probe, calculator, GPS, etc.) 

Rain gear 

First aid kit

Personal flotation device(s)

Field trip itinerary 

Cellular phone and/or park radio 

Digital camera with extra flash cards and battery

Map(s) of station location, preferably at different scales

Global positioning system (GPS) with extra batteries

Deionized or distilled water for field rinsing 

Copy field data sheets on waterproof paper. See the attachments for blank data sheets. The 

instruction manuals for each instrument should be copied and the originals placed in a secure file and 
Standard Operating Procedure #6: Field Measurements and Water Sample Collection, Version 1.2 September 2015

Water Quality Monitoring Protocol for Inland Lakes, Version 1.1 4

kept in the office. Specific sections of the manual that might be important to have in the field should 

be copied onto waterproof paper and remain in the field kit. Include copies of a datalogger software 

manual.

6.2 Overview of Field Work

6.2.1 Sequence of Activities During Field Work Day

1. Review field gear checklist.

2. Create a new field form for each monitoring station, printed on waterproof paper.

3. Prepare sample bottles and labels in advance and place in a cooler.

4. Conduct daily calibration of appropriate meters and probes.

5. Inspect vehicles at the beginning of every field day, including all safety and directional lights, 

oil, gasoline, tire air pressure levels.

6. Inspect boat; ensure all safety gear is on board.

7. Drive to boat landing or portage boat into lake to be sampled. Load boat with sampling gear, 

launch boat, and navigate to monitoring site. Set up a clean work space on the boat for 

sampling.

8. Refer to description of monitoring station location, directions, maps, and photo to verify 

correct location. Verify coordinates on GPS unit.

9. Measure field water quality variables per Section 6.4 and collect samples per Section 6.5. 

10. Be sure that all samples are correctly labeled and preserved on ice. 

11. Locate benchmark and record measurements of water level as detailed in SOP #4.

12. Verify that field form is completely filled out, and initial the form.

13. If sampling from more than one monitoring station in a day, follow procedures for 

decontamination of equipment per SOP #5, and go back to step 6, above.

14. Upon return to shore, inspect boat, trailer, and all equipment that has come into contact with 

the water for invasive species. 

15. Return to office or field station.

16. Process samples according to SOP #7. Refrigerate or freeze samples, as required and package 

samples for sending to contract analytical laboratory.
Standard Operating Procedure #6: Field Measurements and Water Sample Collection, Version 1.2 September 2015

Water Quality Monitoring Protocol for Inland Lakes, Version 1.1 5

17. Clean sampling equipment per SOP #7. Rinse sensors with deionized water and perform 

calibration re-checks, as detailed in SOP #12. This can be done upon returning to home base. 

Perform decontamination of the probe or other instruments as detailed in SOP #5.

18. As soon as possible after returning from the field, review both hardcopy and electronic data; 

offload electronic data onto computer; review laboratory data as it is received.

19. At the end of the field season, enter or import all field and laboratory data into NPSTORET 

or Aquarius databases.

6.2.2 Recording Field Information Upon Arrival at Monitoring Site

Consistent methods are important to long-term data quality. In actuality, the ideal conditions are not 

always met in the field or in the lab and changes in staff occur. Therefore, documentation of 

procedures, site conditions, laboratory analysis, and reasons for deviations of any kind is important. 

Personnel are encouraged to write down more than they feel may be necessary in the moment, as the 

future interpretation of their data will depend on the written record and not the memory of an 

individual. Waterproof field forms (copy available in the attachments) should be prepared ahead of 

time labeled with the project and station IDs. Sampling stations will be identified by park and water 

body name according to GLKN guidance. Information on the sampling station and park will comply 

with NPSTORET and Aquarius database requirements. Field sampling forms are used to record the 

physical and chemical water quality variables measured at the time of sample collection. In addition 

to recording the field variables, any samples collected for laboratory analyses must be so indicated. 

Documentation should include calibration data for each instrument, field conditions at the time of 

sample collection, visual observations, and other information that might prove useful in interpreting 

these data in the future. 

While at each monitoring site, the information recorded on field sampling forms should include:

 Date

 Time of arrival

 Names of field team members

 GPS coordinates, to verify location

 Current weather (air temperature and wind speed) and relevant notes about recent weather 

(storms or drought), including days since last significant precipitation

 Observations of water quality conditions (see below)

 Multiparameter meter (model/serial no.), calibration date, and field measurements of core 

suite variables

 List of sample IDs and collection times for advanced suite variables or quality assurance 

samples

 Whether any samples were not collected, and reason

 Quality assurance/quality control procedures followed

 Water level measurement

 Any other required metadata for NPSTORET data entry
Standard Operating Procedure #6: Field Measurements and Water Sample Collection, Version 1.2 September 2015

Water Quality Monitoring Protocol for Inland Lakes, Version 1.1 6

 Any additional non-routine monitoring (e.g., collection of dragonfly larvae for mercury 

analysis) by GLKN or park staff, or park partners

 Time of departure

All entries should be made clearly. If an incorrect entry is made, a single heavy line should be drawn 

through the incorrect entry and the correction made. All corrections should be initialed and dated. 

The completed field forms will be maintained in chronological order by station, copied into project 

binders and the originals maintained on file indefinitely. Field data are reviewed annually by GLKN 

personnel (see SOP #8, Data Entry and Management, for details).

Upon arrival at the monitoring station, record visual observations of water quality conditions that will 

be useful in interpreting water quality data.

 Water appearance—General observations on water may include color, unusual amount of 

suspended matter, debris, or foam.

 Biological activity—Excessive macrophyte, phytoplankton, or periphyton growth. The 

observation of water color and excessive algal growth is important in explaining high 

chlorophyll-a values. Other observations to note include types of fish, birds, or spawning 

fish.

 Unusual odors—Examples include hydrogen sulfide, mustiness, sewage, petroleum, 

chemicals, or chlorine.

 Watershed activities—Activities or events that are impacting water quality; for example, 

forest fires, road construction, timber harvest, shoreline mowing, beaver activity, or livestock 

watering.

6.2.3 Preventing Contamination 

Field technicians should be aware of and record potential sources of contamination at each field site. 

Decontaminate field sampling equipment according to SOP #5 for minimizing the risk of spreading 

invasive species. Clean field and laboratory equipment according to SOP #7 to avoid contamination 

of analytes to be measured. Do not allow sample water to touch hands; do not touch insides of 

sampling equipment, containers, or laboratory bottles.

6.2.4 Using Disposable Gloves 

Wearing disposable gloves is strongly recommended when handling acid preservatives. Check 

manufacturer’s chemical resistance information to be sure gloves are appropriate for compounds to 

which they will be exposed. Common glove types include those made of vinyl, latex, and nitrile; 

nitrile is in standard use for USGS sampling work because of its resistance to most of the chemicals 

to which it typically will be exposed for the length of exposure (usually < 15 minutes). Field 

personnel are cautioned that direct contact with materials such as latex or nitrile can cause severe 

allergic reactions in some individuals and should be monitored. 
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Physical properties to consider when selecting disposable gloves are glove length, slip protection, 

puncture resistance, heat and flame resistance, cold protection and comfort. These factors can vary 

between manufacturers. Gloves should be inspected visually for defects. Check for tears, punctures 

and other flaws that can prevent the glove from being an effective shield. After putting the gloves on, 

rinse them with water while gently rubbing hands together to remove any surface residue before 

handling sampling equipment. 

6.2.5 Bottle Preparation – Types and Sizes of Bottles

For each monitoring station, select the bottles appropriate for each analyte and label them with 

Station ID, sample date, and analyte code according to the requirements of the contact analytical 

laboratory. Store pre-labeled bottles in a dry box or in separate bags for each station.
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6.3 Field Measurement Procedures 

6.3.1 Where and When to Measure Field Variables

The deepest part of the lake is the preferred sampling site for both discrete and continuous 

(temperature array) monitoring. If the morphometry is not known, sample at the estimated 

geographic center unless there is another basis for selecting the site. Upon visiting a site that has 

been visited before, a GPS should be used to locate the sample site. If a GPS is not available, use a 

compass and known landmarks to triangulate the sample site. A depth finder can also be used to 

verify that the deepest part of the lake is being sampled. 

Discrete routine monitoring will occur three times throughout the open-water season, typically from 

May through October, with more narrowly-defined sampling windows depending on a park’s 

latitude. All three sampling periods should occur when lakes are stratified. It is extremely difficult to 

predict either spring or fall turnover, although the spring period immediately follows ice-out. Fall 

turnover, in the sense of a period when the temperature is uniform, and more importantly, when DO 

is uniformly 100% saturated, is much less predictable. It also occurs at a more dangerous time of year 

to be on the water (November to December). May through October will provide ample sampling 

dates to be able to fully characterize the major period of plant growth, oxygen depletion, water 

clarity, temperature change, maximum public use, and the variable periods of algal nuisance blooms.

Sampling should be conducted during mid-day, from 10:00 AM to 3:00 PM, when possible. Water 

samples and Secchi depth readings are typically collected during mid-day to reduce variability in the 

data due to the differences in daylight, and to a lesser extent, temperature (Carlson and Simpson 

1996). Mid-day is usually the peak period of algal photosynthesis, which can have dramatic effects 

on DO, transparency, and dissolved inorganic phosphorus (phosphate) and dissolved inorganic 

nitrogen (nitrite+nitrate+ammonium) throughout a 24 hr cycle.

Continuous water temperature profile data will be collected from a subset of inland lakes, at the same 

location where discrete routine monitoring takes place. At these lakes sensors will record water 

temperature at 1-hour intervals, year round, from the surface to bottom at 1-meter intervals. In a 

typical season the thermal arrays are serviced and data are downloaded during the first and last 

rounds of planned discrete monitoring. In some cases field logistics (e.g., timing) might dictate that 

arrays are serviced outside of discrete routine monitoring events. 

For all sampling, it is critical to avoid sampling water showing evidence of oil, gasoline or anything 

else from the boat motor. It is best to turn off the engine and set the anchor, although this may not be 

possible or advisable in bad weather or with a balky engine. The engine is commonly located in the 

stern of the boat; therefore, the anchor should be secured near the prow of the boat, such that strong 

winds will rotate the stern to the downwind. After setting anchor, allow surface water to clear of 

disturbances. Collect samples on the upwind side of the boat, to minimize contamination and 

disturbance. Avoid surfactants, floating debris, and turbid aeration during sample collection. Discard 

rinse water or excess sampling water on the downwind side of the boat. 
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6.3.2 Stabilization of Sensor Probe Readings

Before making field measurements, properly-calibrated sensors must be allowed to equilibrate to the 

condition of the water being monitored. Sensors have equilibrated adequately when instrument 

readings have stabilized, that is, when the variability among measurements does not exceed an 

established criterion. The criteria for stabilized field readings were defined by O’Ney (2005) for a set 

of three or more sequential measurements (Table 3). Although the criteria used by the Greater 

Yellowstone Network (O’Ney 2005) differ from those used in the upper Midwest by the NRRI-UMD 

group (WOW 2004), the differences are small in comparison to the true range of variability one 

might expect in the field and with aging instrument sensors. The natural variability inherent in 

surface water or ground water at the time of sampling generally falls within these stability criteria 

and reflects the accuracy that should be attainable with a calibrated instrument. 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 Irwin 2006, 2004 for more details).

Dissolved oxygen typically requires the greatest amount of time to stabilize. For dissolved oxygen 

sensors that utilize a membrane, differences in polarigraphic sensor membrane thicknesses, age, and 

rates of oxygen consumption increase the variability of the equilibration time. The longest 

equilibration times will typically occur where dissolved oxygen exhibits a steep gradient (change in 

DO concentration >5 mg/L) or very low oxic levels (DO concentration <3 mg/L). Depending on the

site characteristics and the specific oxygen sensor, 3 to 5 minutes may be required for complete 

equilibration. This time far exceeds what is needed for the other variables, which typically stabilize 

in less than 60 seconds. Observers should only note instrument DO readings after the stabilization 

criteria in Table 3 are met, and then record readings for all variables at once.

Table 3. Recommended instrument stabilization criteria for recording field 

measurements.

Standard Direct

Field Measurement

Stabilization Criteria

(O’Ney 2005)

Stabilization Criteria

In situ Multisensors

(WOW 2005)

Temperature: 

Thermistor Thermometer 

Liquid-in-glass Thermometer 

± 0.2°C

± 0.5°C

± 0.2°C

(5%)

Specific Conductivity (SC25)

When ≤100 μS/cm 

When >100 μS/cm 

± 5%

± 3%

< 5 uS/cm

(10%)

pH: Meter displays to 0.01 ± 0.1 unit ± 0.2 unit

(10%)

Dissolved oxygen: 

Amperometric (same as 

polarigraphic) method 

± 0.3 mg/L

± 2%

± 0.5 mg/L

(10%)
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6.3.3 Outline of Discrete Water Profile Measurements 

Acquiring high quality results requires the use of consistent measurement methods. Adhere to the 

following guidelines:

1. Depths <20 m: Measure T, DO, pH, and SC25 surface to bottom at 1 m intervals.

2. Depths >20 m: Decrease measurements to 2 m intervals down to 30 m and to as much as 5 m 

increments for greater depths.

3. Wait for the DO value to stabilize first, record the value, then read the other parameters. 

Because DO takes the longest to stabilize this assures all parameters have equilibrated. See 

section 6.4.4 for further details. Stabilization of the DO value will typically take anywhere 

from 30 seconds to several minutes, depending on the gradient from the previous depth and 

the age and type of oxygen sensor. Extra time should be allowed for equilibration when 

values are below approximately 3 mg/L. If the sonde does not have a stirring mechanism, 

jiggle the cable gently approximately once per second.

4. Enter all data on field forms. 

5. Quality Assurance (QA): At a minimum, replicate one of every 10 sets of measurements 

(e.g., at 1 m, 10 m, etc.). The replicate should be taken immediately following the original 

reading. Values should agree within + 10% or the detection limits listed in Table 3, 

whichever is larger. 

6. Additional QA: At least once per field day, when a multiprobe is used to record water 

quality parameters, record 7 sets of measurements at the same depth after all parameters have 

stabilized. The readings should be taken immediately after one another in quick succession. 

These readings will be used to calculate the alternative measurement sensitivity (AMS) of 

each sensor on the multiprobe, which provides a way to track long-term sensor accuracy. 

Instrument problems or failure

 If water quality sensor measurements are not representative of field conditions based on 

previous data or limnological knowledge, re-calibrate and try again. 

 If readings seem reasonable, proceed. If not, first check the troubleshooting guide in the 

instrument manual. If problem persists, collect as much data as possible using back-up hand 

held instruments, if available. Using the Van Dorn bottle, collect a sample from 2.5, 5, 7.5, 

and 10 m, and then at 5 m intervals to the bottom, and record values obtained by dipping the 

sensors into the top of the sampler. In the case of measuring DO, jiggle the probe without 

causing bubbles to form in low DO hypolimnetic samples. If, after approximately 2 min, the 

value continues to decrease, increase the rate of swirling or jiggling to see if it will stabilize; 

if it is increasing after 2 minutes, you may be agitating the water enough to be causing an 

aeration artifact near the surface. If too much time elapses and the temperature of the water 

sample has increased by more than 1oC, collect a fresh sample.
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6.3.4 Detailed Description and Troubleshooting Hints for Field Variables

Because temperature, DO, and other water quality variables are important determinants of biotic 

habitats, it is important that observers write down values on field forms and think about their 

ecological meaning, even if a data logger is recording the measurements. The hard copy also serves 

as backup in case there is an electronic failure.

6.3.4.1 Temperature

Temperature (T) is measured in units of degrees Celsius (°C) and recorded to the nearest degree or 

tenth of a degree as warranted by instrument. 

1. If a cabled thermistor is not available, the high specific heat of water allows a temperature 

profile to be obtained by bringing deep samples to the surface with a water sampler and 

immediately measuring temperature with a hand-held thermometer or thermistor. Anything 

immersed into the water sampler potentially contaminates that particular sample; a separate 

sample must be collected for water chemistry.

2. The upper few centimeters of soft sediments are often several tenths of a degree warmer than 

the overlying water. The rise in temperature can be an indication that the probe is submersed 

into the sediments. If this happens, be sure to vigorously shake the instrument in shallow 

water with high DO to clean it before re-taking measurements. Check intermediate depth 

values, and if these values do not meet QA criteria, pull the instrument to the surface and 

clean it.

6.3.4.2 Specific Conductivity

Specific conductivity (SC) is the ability of water to conduct an electrical current for a unit length and 

unit cross-section at a certain temperature, measured in units of microsiemens per centimeter 

(μS/cm), and recorded to the nearest μS/cm. Commonly used in water quality monitoring, SC is a 

general measure of the number of ions dissolved in the water. It is important to be aware of the 

difference between SC (specific conductivity at the ambient temperature of the sensor) and SC25 (an 

abbreviation for specific conductivity temperature compensated to 25°C). This difference becomes 

very important in profiling stratified lakes where the hypolimnion is cold with respect to the 

epilimnion. In such cases, the typical increase in ions with depth, as estimated by SC25, would be 

substantially offset by the corresponding decrease in SC due to decreasing temperature. The 

difference between SC and SC25 can confound analyses of seasonal patterns of dissolved ions since 

water temperatures vary throughout the year. The SC25 can be used to monitor seasonal changes in 

total dissolved salts (TDS) such as a spring flush of road salt, which is why the temperature 

compensation is so important. Many instruments will display SC in addition to SC25. In the event 

that an uncompensated sensor must be used (older instruments and most pocket conductivity meters 

are not temperature-compensated), the value of SC25 can be calculated from SC and temperature 

values (see # 3 below). The value of SC should be recorded on the field form even when SC25 will 

be calculated.

1. A common physical problem in using a specific conductance probe (or meter) is entrapment 

of air in the conductivity probe chambers. Its presence is indicated by unstable specific 
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conductance values fluctuating up to +100 μS/cm. This problem is much more prevalent in 

turbulent stream waters and can be minimized by slowly and carefully placing the probe 

vertically into the water and when completely submerged, quickly moving it back and forth 

through the water to release any air bubbles. An SC probe with an open flow design does not 

trap air.

2. Is the value real or is the instrument out of calibration? Having specific conductance 

standards in the field can help verify values that fall outside the expected range. For example, 

the expected specific conductivity 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 

is out of calibration. 

3. SC25 values can be calculated from uncompensated SC values via a temperaturecompensation formula. For example, for YSI probes, use:

SC25 =

SCm

1 + 0.0191(tm − 25)

Where, SC25 = corrected conductivity value adjusted to 25oC,

SCm = measured conductivity before correction, and

tm = water temperature at time of SCm measurement.

Contact the instrument vendor for the appropriate formula.

6.3.4.3 Hydrogen Ion Activity (pH)

Commonly used in water quality monitoring, pH is a measure of the acidity of water, measured in 

standard pH units (SU), and recorded to the nearest 0.1 pH unit. The pH scale is from 1 to 14: neutral 

water is pH 7, acidic waters have pH <7, and alkaline waters have pH >7.

 Is the value real or is the instrument out of calibration? Having pH standards in the field can 

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. 

 As with dissolved oxygen, a pH probe can take longer to equilibrate when the gradient from 

the previous measurement is large (>1.0 pH SU).

 Low ionic strength waters with SC25 <50 μS/cm can cause pH measurement stability 

problems with some probes, necessitating use of low ionic strength probes. Probes will often 

calibrate fine in strong ionic strength buffers but will not read accurately in lower ionic 

strength surface waters. If you suspect this is the case, use a sensor that is designed for low 

ionic strength waters. 

 Because the pH scale is logarithmic, field values may first have to be converted to hydrogen 

ion activity (i.e., concentration) values, averaged, and re-transformed to pH standard units 

prior to conducting statistical analysis. To compute a mean pH for a group of data:
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o Convert each pH value to hydrogen-ion activity, using the equation: Hydrogen 

Activity = 10-pH. 

o Calculate the mean of the activity values by adding the values and dividing the sum 

by the total number of values. 

o Convert the calculated mean activity back to pH units, using the equation, pH = -log10

(mean hydrogen activity).

6.3.4.4 Dissolved Oxygen

Dissolved oxygen (DO): units of mg/L record value to nearest 0.1 mg/L unless otherwise justified; 

percent saturation (% DO) record value to nearest %; also temperature compensated to 25°C.

 Be aware that if a water sample has a strong rotten egg smell (H2S gas) it must have a DO of 

zero. This is one way to check your meter. You can use the measured offset value to correct 

your higher DO values. Do not report negative DO values in the final database although it is 

important to report them on the field data sheet. Do the correction afterwards but note on the 

field sheet the depth at which you could smell sulfide gas. Avoid touching the bottom, if 

possible, as the membrane may become fouled.

 Equilibration time is critical; the steeper the DO gradient, the longer the equilibration time. It 

may take >5 minutes when DO drops abruptly to near zero.

 The DO probes with membranes (Clark cell) actually consume oxygen in the immediate 

vicinity around the membrane as they work; measurements therefore require moving water 

using either a built-in stirrer (typical in multiparameter sondes and BOD probes) or moving 

the cable up and down (e.g., 6” each side of the desired depth) during the measurement. 

Optical sensors do not consume oxygen and hence do not require moving water.\

 Accuracy of an optical DO probe can be compromised if it is covered with a residue that 

inhibits or increases oxygen reaching the sensor surface. Algae on the sensor surface may 

increase DO measurements, while oils or sediments may lower them. If measurements seem 

suspect, or if the instrument was used in contaminated water, the sensing surface should be 

cleaned with a soft brush and a mild detergent.

 If the electronic DO meter is not functioning properly, DO can be measured by Winkler 

titration (Clesceri et al. 1998). A variety of field kits are convenient and cost effective, 

including Lamotte, Hach, and others.

6.3.4.5 Clarity

Measurement of Secchi disk transparency has historically been the most common means of 

measuring water clarity due to its simplicity. It is a qualitative evaluation of the transparency of water 

to light based on the reflection of light from the surface of the Secchi disk and is a function of the 

absorption characteristics both of the water and its dissolved and particulate matter. To get an 

accurate measure of Secchi depth, the disk must hang vertically from the side of the boat. The 

transparency tube, which uses the same principle as a Secchi disk, is recommended when the Secchi 

disk can be seen on the lake bottom or when the disk does not hang vertically due to a current or an 

unstable boat.
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6.3.4.5.1 Secchi Depth:

1. Measure Secchi depth using a 20 cm (8 in diameter) black and white Secchi disk from the 

shaded side of the boat. Do not wear sunglasses while viewing the Secchi disk. 

2. Measurements should be made as near to midday as possible (10 AM to 3 PM; sunny and 

calm is optimal). Visit each lake as close to the same time of day as previous visits in order to 

minimize diurnal variation.

3. Try to lower the disk in the shade of the boat and make sure that the line is hanging 

vertically. In strong currents or choppy waves, it may be helpful to tape a rock or weight to 

the bottom of the disk.

4. Slowly lower the disk into the water until it disappears and note the depth.

5. Lower the disk a little farther, then slowly raise it until the disk reappears and note the depth 

again.

6. Average the two readings and record the value. Record the Secchi observer on the data sheet 

(see #8 below).

7. Record the conditions present when the Secchi measurement was made, with 1 being 

excellent (sunny clear skies, calm water), 2 being moderate (some clouds, small waves), or 3 

being poor (dark skies, very choppy water, or currents that make it extremely difficult to 

read).

8. Quality Assurance (QA): At a minimum, replicate Secchi readings at every tenth site. 

Because of the apparent ease of this measurement yet its potential difficulty in less than ideal 

conditions, all field crew members should take this measurement at each site for at least the 

first round of sampling The crew should not reveal their value until all are finished and then 

all values should be recorded and compared. Values should agree within +10% for Secchi 

measurements <5 m and +0.5 m for greater values.

6.3.4.5.2 Transparency Tube:

1. Measure transparency tube clarity using a 120 cm tube if the Secchi is visible on the bottom 

of a lake or wetland pond. For all shallow (<2 m) lakes and ponds, measure clarity with a 

transparency tube even if Secchi measurements can be made on occasion because clear water 

times can occur, when Secchi depth cannot be measured.

2. The tube should be set on a white towel background, shaded by your body, and read without 

sunglasses.

3. Water should be dispensed from a carboy that was used for integrating water samples (see 

below) rather than dipped from the water body. The carboy must be well shaken prior to 

filling the tube to minimize artifacts due to settling of sand and larger silt particles. Allow air 

bubbles to disappear before making the final measurement. 
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4. While slowly releasing water from the bottom of the tube via its valve, note and record the 

depth at which the mini-Secchi first becomes visible. Discard the remaining water and repeat 

the measurement with a second subsample from the carboy. 

5. Several attempts to read the clarity may be necessary because of overshooting the endpoint, 

so collect plenty of water for this analysis. A standard 120 cm × 4.5 cm outside diameter tube 

requires approximately1.5 L to fill it, so dedicate at least 4 L of water for this measurement. 

6. During clear water periods, the tube may not be long enough for a measurement. In such 

cases, the value should be recorded as >120 cm. If it appears to be barely visible, this fact 

should be recorded to distinguish it from a measurement where it is clearly visible.

7. Quality Assurance (QA): At a minimum, replicate transparency tube readings at every tenth 

site. As for the Secchi reading, because of the apparent ease of this measurement yet its 

potential difficulty in less than ideal conditions, all field crew members should take this 

measurement at each site for at least the first round of sampling. Crew members should not 

reveal their values until all are finished and then all values should be recorded and compared. 

Values should agree within 10%. This acceptance criterion is subject to change as more data 

from various volunteer monitoring programs become available (such as the Minnesota 

Citizen Stream Monitoring Program (http://www.pca.state.mn.us/water/csmp.html).

Maintenance notes and other precautions:

1. The rubber stopper (with attached Secchi) can be dislodged easily. Tape the stopper with 

black vinyl electricians tape and carry an extra stopper-Secchi.

2. Clean the transparency tube periodically with mild dish soap and a soft cloth.

3. Although water from the tube may be saved for turbidity and TSS measurements, do not save 

it for nutrient or other pollutant analyses because the tubes are not cleaned according to 

certified protocols.

4. Subsampling and settling issues are important, as particles settle quickly. A stopper for the 

top of the tube is useful to allow for resuspension during the measurement if rapid settling 

occurs. 

5. Dissolved color due to organic matter (humic and fulvic acids, usually from bogs and conifer 

needles) can confound comparisons of transparency tube data between lakes. Also, lakes with 

similar concentrations of suspended sediments can have different transparency because 

smaller particles scatter more light. 

6. A transparency reading taken from one tube cannot be compared with a reading taken from 

another tube made by a different manufacturer if the dimensions are different.

6.3.5 Measuring Water Level

Water level will be measured relative to a benchmark or reference mark. GLKN will always install 

markers above water level, but extreme water level fluctuations could submerge a marker that was 
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originally well above the ordinary high water mark. In some cases, benchmarks may have been 

installed by other agencies, and may not be above current water level. Water levels that are below the 

reference marker will be recorded as negative numbers; levels above the marker will be positive.

A single person can measure water level above a reference mark by placing a measuring device, such 

as a meter stick, on the marker and reading the water level directly on the device. Two people are 

required to measure water level when the reference marker is above the current water level. One 

person holds a stadia rod at the water’s edge, while the second person uses an eye level or laser level 

at the benchmark to view the stadia rod.

Detailed instructions for installing reference markers and measuring water levels can be found in 

SOP #4, Measuring Water Level.

6.4 Water Sample Collection 

A tube sampler collects and integrates a column of water into a single sample. If the top end is 

capped, all or most of the water will remain in the tube as it is raised. The main advantage over using 

a surface dip (often called a grab sample), is that a larger stratum of water in the epilimnion is 

represented by the sample, reducing the effect of high chlorophyll concentrations from concentrated 

scums on the seasonal mean. Bottom water, and on occasion other depths, will be sampled using a 

Van Dorn or Niskin type remote-closing water bottle. Although less durable, a transparent acrylic 

bottle allows the crew to ensure that near bottom water samples do not contain suspended bottom 

sediment before pouring the (contaminated) water into the sample bottles. Precautions will be taken 

to check with the manufacturer regarding the potential for nutrient or other contamination from the 

sampler. Before its first use, the sampler will be cleaned thoroughly by rinsing three times with hot 

tap water, rinsing three times with 0.1 N HCl, and finally, rinsing three times with deionized water.

6.4.1 Integrated Sampling Tube

1. Rinse compositing jug 3 times before sampling. Increase surface water flushing to 6 rinses if 

the compositing jug previously contained water that was contaminated with sediment or 

water deemed to have much higher nutrient levels.

2. Remove both stoppers from integrated sampler. Rinse the integrated sampler in lake water 3 

times (lower to 2 m, raise, lower again, etc. for 3 rinses). 

3. Collect sample by lowering sampler into water column (if water depth will allow it). If the 

site is too shallow for the 2 m sampler, then use one of the following methods:

a. collect sample by using the integrated sampler on an angle instead of vertically,

b. fill jug with 0.5 m deep water using the Van Dorn sampler, 

c. or fill jug via surface grab.
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Secure the top stopper, raise the sampler vertically, and immediately drain it into the rinsed 

compositing jug. The sampler will start releasing its water as soon as it clears the water 

surface. Two or three integrated samplers of water will be needed to fill a 6 L jug. Fill the jug 

at least 75% full to ensure adequate water for all analyses; if a transparency tube 

measurement will be done, an entire jug is needed. Extra water simply reduces variance 

associated with the site.

4. Once water is collected, immediately begin dispensing it into appropriate analyte bottles or 

keep jug cold and dark until processing in the park lab or home base at the end of the day 

(details below).

6.4.2 Discrete Depth Sampling 

During the mid-summer sampling when the lake is thermally stratified, (defined as a gradient of 

≥1°C/m or DO levels ≤2 mgO2/L), collect two separate samples. 

Collect surface water with the 0–2 m integrated tube sampler as above; collect bottom water with 

Van Dorn sampler from approximately 0.5 to 1 m above the lake bottom. Because the hypolimnetic 

water will be used for nutrient analyses only, a smaller container (1 or 2 L) may be used for storage 

and transport to the sample processing site. Do not collect bottom water from lakes that are not 

thermally stratified, as evidenced by temperature (and oxygen) profile data recorded with a 

multiprobe.

6.4.3 Distributing Sample Water from the Compositing Jugs 

 Always ensure composite water is well mixed prior to dispensing it to any other containers. 

 Rinse bottles and caps for chlorophyll-a with lake water three times, prior to filling. Uncap 

and re-cap bottles below water surface to avoid surface scum or debris.

 Fill dark plastic bottle for chlorophyll-a (at least 1 L); keep cold and dark until filtering at the 

end of the day.

If the water sample is processed on-site, follow the instructions below, in addition to those in SOP 

#7.

Integrated 0–2 m Water 

1. Rinse caps and bottles with composite water three times, using approximately 50 mL for each 

rinse, prior to filling. Shake out excess water.

2. Cap and re-agitate composite jug and then dispense water into previously labeled appropriate 

bottles. Be careful not to overfill bottles pre-loaded with acid. Fill nutrient bottle to the 

bottom of the neck of the bottle – this will prevent the bottle from breaking when the water 

expands as it freezes.

3. Use remaining water for transparency tube measurement if specified. If insufficient water is 

left, collect additional water until there is enough for replicate measurements. 
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Bottom Water

 From compositing jug––Rinse the bottle caps and bottles in composite water as for surface 

water. 

 From Van Dorn––Carefully stand the Van Dorn bottle on the side of the boat or on a seat, 

crack the top slightly to start the flow, rinse and dump 3 aliquots before filling the bottles to 

their necks. If there is not enough water in the Van Dorn to fill all the bottles, start over and 

either be more cautious with draining the sampler or use the compositing jug after rinsing, as 

above. Two Van Dorn samples may be pooled. Cap loosely and agitate the jug before 

dispensing water into the plastic bottles for raw and filtered nutrients (probably the only 

analyses to be done for bottom water). 

Pay special attention to the appearance (visual color and turbidity) and smell (rotten egg gas, 

H2S) of the water. If there is any evidence suggesting that bottom sediments were stirred up 

and captured by the sampler, re-do the collection taking care to vigorously clean the sampler 

and compositing carboy with surface water. 

6.4.4 Sample Handling While in the Field

Store water samples in cooler with ice until return to home base for further processing.

In bad weather on lakes with a single sampling station or with a small boat it will be more convenient 

and safer to sample the bottom water first, collect the surface sample after the profiling is done, and 

then return to shore to pour the subsamples from a full compositing jug. 

6.4.5 Quality Assurance of Field Duplicates

Collect a field duplicate every 10 samples. Label the duplicate analysis bottles with the code 

appropriate for the duplicate, using the same date and time of sampling. Indicate on the data field 

form which site or lake is the duplicate. Treat the duplicate as a regular sample for all phases of 

collection, processing, and analysis. The duplicate should be a split sample, taken from the same 

composite jug. See section 6.6.3.2, below, for more details.

6.5 Departing From the Monitoring Site

Before leaving the monitoring site, all field forms and sample labels must be reviewed for legibility, 

accuracy, and completeness. Any changes in procedure due to field condition must be explained in 

the comments section. Make sure the information is complete on all forms. Record the departure time 

on the field form. After reviewing each form, initial the upper right corner of each page of the form. 

Document any photos taken by including the photo number and roll number or digital camera photo 

number on the field form.
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6.6 Quality Assurance/Quality Control (QA/QC)

QA/QC basically refers to all those things good investigators do to make sure their measurements are 

right-on (accurate; the absolute true value), reproducible (precise; consistent), and include good 

estimates of uncertainty. It specifically involves following established rules in the field and lab to 

assure everyone that the sample is representative of the site; free from outside contamination by the 

sample collector, and that it has been analyzed following standard QA/QC methods. See SOP #12, 

Quality Assurance/Quality Control, for more details.

6.6.1 Calibration of Field Instrument Sensors

Calibration schedules overlap but differ from sampling schedules, so calibration methods are listed 

here as a separate procedural step. Instrument calibration is an essential part of quality assurance. 

Table 4 summarizes the ideal calibration frequency and minimum acceptance criteria for some of the 

most commonly collected water quality parameters. The reality of logistical constraints at back 

country sites may preclude calibration and checks of calibration at the ideal frequency. This SOP 

provides only generic guidelines for equipment use and maintenance. A wide variety of field 

instruments is available; such instruments are continuously being updated or replaced using newer 

technology. Keep equipment manufacturers' maintenance and calibration instructions for all 

instruments for reference purposes. Field personnel must be familiar with the instructions provided 

by manufacturers. Contact manufacturers for answers to technical questions.

Table 4. Ideal calibration frequency and acceptance criteria.

Parameter USEPA Method

Minimum 

Calibration 

Frequency and QC 

Checks Acceptance Criteria Corrective Actions

Temperature 170.1

Annually, 2-point 

check with NIST 

thermometer

±1.0 oC

Re-test with a 

different 

thermometer; repeat 

measurement.

Specific 

conductance (SC25) 120.1

Daily, prior to field 

mobilization; 

calibration check 

prior to each round 

of sampling; 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
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Table 4 (continued). Ideal calibration frequency and acceptance criteria.

Parameter USEPA Method

Minimum 

Calibration 

Frequency and QC 

Checks Acceptance Criteria Corrective Actions

pH 150.1

Daily, prior to field 

mobilization (two 

buffers should be 

selected that bracket 

the anticipated pH of 

the water body to be 

sampled)

±0.05 pH unit

Re-test; check low 

battery indicator; use 

different standards; 

repeat 

measurement; don’t 

move cords or cause 

friction/static

Calibration check w/ 

third buffer prior to 

each round of 

sampling; check with 

low ionic strength 

buffer in addition, if 

conductivity is <50 

μS/cm 

±0.1 pH unit

10% of the readings 

taken each day must 

be duplicated or a 

minimum of 1 

reading if fewer than 

10 samples are read.

RPD 10%

Dissolved oxygen 360.1

Daily, prior to field 

mobilization; check 

at the field site if 

elevation or 

barometric pressure 

changed since 

calibration

0.2 mg/L 

concentration or

±10%

saturation

Re-enter altitude; retest; check low 

battery indicator; 

check membrane for 

wrinkles, tears or air 

bubbles; replace 

membrane; use a 

different meter; 

repeat 

measurement; allow 

more time for 

stabilization

Depth --

Daily, prior to field 

mobilization, check 

at the field site. 

Check annually 

against commercially 

purchased brass 

sash chain labeled 

every 0.5 m to 

ensure that it reads 

zero at the surface 

and varies <0.3 m for 

depths <10 m and no 

more than 2% for 

greater depths.

±0.1 m

Retest, check low 

battery indicator; 

repeat 

measurement; use 

with accurately 

calibrated line
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Table 4 (continued). Ideal calibration frequency and acceptance criteria.

Parameter USEPA Method

Minimum 

Calibration 

Frequency and QC 

Checks Acceptance Criteria Corrective Actions

Transparency tube --

Transparency tubes 

have a 100 or 120 

cm scale; ensure 

tube is clean

±1.0 cm for 

transparency tube

Marked lines (e.g., 

Secchi, Van Dorn) --

Check markings 

annually against 

brass sash chain. If 

lines are heated (for 

decontamination) 

check prior to each 

round of sampling.

±1%, 0–10 m

±2%, >10 m Re-mark line.

6.6.1.1 Instrument Calibration and Maintenance Logbooks

Calibration and maintenance logs for multi-parameter sondes and all back-up sensor probes will be 

maintained and will document the frequency of calibration, maintenance, and calibration checks. See 

the attachments for a blank calibration log form. Keep calibration logs with each instrument during 

the sampling season. Logs will later be archived at the Network office in Ashland, Wisconsin. A new 

log will be started for each field season. Each instrument will have a logbook for recording all 

maintenance and calibration information, including:

 serial number, date received, manufacturer’s contact information, especially technical service 

representatives

 service records, dates of probe replacements

 maintenance records, for example, whenever the following general maintenance occurs: DO 

membrane replacement, pH reference probe junction and filling solution, probe cleanings, 

sonde (the sensor housing) replacement, impellor replacement or cleaning, etc. 

 calibration dates and calibration data

 any problems with sensors

 pre-mobilization, post-calibration checks performed on individual sensor probes

6.6.1.2 Handling of Calibration Standard Solutions

Store all calibration standards in a temperature-controlled environment. Standards should be dated 

upon receipt and upon opening. Commercially-purchased calibration standards come with an 

expiration date that must be observed. Ensure that calibration standards are not used beyond 

expiration dates.

Properly dispose of all waste materials. Used calibration solutions, in general, may be rinsed down a 

sink with water after consideration of the wastewater treatment system available to that sink. Material 

safety data sheets (MSDS) that are sent with manufacturer purchased calibration solutions should be 

kept on file. These documents describe the flammability, toxicity, and other safety hazards of 

reagents. Some reagents may include constituents that are toxic to aquatic life. These should not be 

rinsed down a sink in any large quantities in primitive areas where the ultimate destination of 
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wastewater is the aquatic environment. Instead, these reagents should be collected in a properlymarked leak-proof container for disposal in an adequate treatment system.

6.6.1.3 Temperature

Temperature is typically not adjustable on an electronic sensor but should be cross-compared to a 

National Institute of Standards and Technology (NIST) traceable thermometer at the beginning of 

each field season, as follows: 

 Compare against a NIST-certified or NIST-traceable thermometer at a broad range of 

temperatures, for example 0oC to 40oC; 

 The sensor should read within ±1.0oC of the NIST thermometer; 

 Typically you cannot adjust the instrument to calibrate it but check the manual. It is a good 

idea to check the instrument at 0oC in slurry of ice-water if a calibrated (NIST) thermometer 

is not available since electronic and non-electronic temperature sensors are typically linear 

over the likely range of field temperatures. 

An armored glass thermometer that has been referenced to the NIST standard should be taken into 

the field for air temperature and surface water temperature measurements and for checks of the 

electronic sensor. 

6.6.1.4 Specific Conductivity

Specific conductivity (SC25) will be calibrated using a KCl solution as specified by the instrument

manual. Stock calibration solutions can be purchased commercially, prepared by a water quality 

contract lab, or made in an academic or agency lab. If the KCl solution is prepared by an academic or 

agency lab, it should be cross checked by an external certified lab. Set the instrument to record 

temperature-compensated SC (SC25) rather than SC. 

Because the typical modern SC25 sensor is linear to <3% over the range from approximately 20 to 

10,000 μS/cm, a single point calibration is typically sufficient. A typical standard is 1000 or 1413 

μS/cm. Pre-mobilization error checks of this sensor using 10, 100, 1413, and 10,000 uS/cm standards 

may be used to establish sensor error over the range of most interest in freshwater work.

6.6.1.5 pH

The pH is calibrated using the standard two buffer technique, using either pH 4 and pH 7, or pH 7 

and pH 10, depending on the expected field values. Calibrate the probe according to the 

manufacturer’s recommendations, usually starting with pH 7 buffer followed by the second buffer. If 

a water body is classified as low acid neutralizing capacity (ANC) acid-sensitive (i.e., ANC 

approximately 100 ueq/L or lower), it should also be checked against a low ionic strength buffer 

(LISB) with pH approximately 4, as per protocols from the National Acid Precipitation Assessment 

Program (NAPAP 1990). A low ionic strength pH combination electrode may be necessary to 

acquire this extra level of sensitivity if stabilized pH measurements are not achieved with standard 

pH sensors. Prior to each round of sampling, check the calibration with a third standard with a pH 

value between those used for calibration.
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6.6.1.6 Dissolved Oxygen

Two types of dissolved oxygen (DO) sensors are typically utilized: Clark cell and optical. A Clark 

cell (membrane) sensor is air-calibrated, while an optical DO sensor is calibrated in 100% saturated 

tap water. For a Clark cell, it is assumed that the dry sensor will read 100% saturation in an enclosed 

airspace with enough water in the bottom of the container to saturate the air with water vapor. For 

optical DO sensors, the sensor window must be submerged in 100% DO saturated water, which is 

obtained by agitating tap water in a container for one minute and then decanting it into the calibration 

chamber until the DO sensor is completely covered with water. 

A Clark cell should be checked for bubbles under the surface of the membrane. If bubbles are 

observed, change the electrolyte solution and replace the membrane. An optical DO sensor’s surface 

should be observed to make certain that no air bubbles are clinging to it. The calibration chamber can 

be tapped gently to dislodge any bubbles. 

Temperature affects DO saturation, as does the air pressure, which varies with elevation and ambient 

weather. Both sensors require a known barometric pressure (BP), obtained by the multiprobe itself (if 

equipped with a BP sensor) or from another source. Acceptable sources for BP are from another 

instrument, such as a calibrated barometer, or a third-party source, such as the local weather bureau 

or airport. Typically, one can assume the barometric pressure to vary with elevation. As a result, the 

instrument should be re-calibrated at each site if the elevation has changed more than 50 feet.

6.6.1.7 Depth

The length measurement of brass Secchi chains, transparency tubes, and depth sounders usually 

require little calibration after purchase and an initial check for accuracy. Compare all depth cables to 

each other and ensure they are synchronized. A brass Secchi chain can be used to calibrate other 

cables and lines. The use of a brass chain is particularly important because this single tool is likely to 

provide consistent long-term data. Nylon and certain braided weave ropes and cords can stretch as 

much as 20% and may vary depending upon wetness, load, and age. Lines may also shrink, as when 

they are soaked in hot water to avoid spread of exotic species.

Electronic depth sensors, or pressure transducers, are based on pressure differences and need to be set 

to zero at the water surface initially. Perform this zero check at every station; however, verify the 

depth measurement with labels on the actual instrument cable. 

A useful and widely-used labeling system for coding depths is:

1. 5 m increments: Wrap vinyl tape of a specified color at 5 m increments and add an extra wrap 

every 5 m. Therefore, there is a single wrap at 5 m: two wraps at 10 m separated by approx.. 

0.5 cm with 10 m lying exactly between the wraps; three wraps at 15 m with the 15 m depth 

located at the middle of the second wrap, and so on. A permanent marking pen should be 

used to write the actual depth on the tape.

2. 0–10 m depth: Use a second color to make wraps at 1 m intervals to best define shallow 

water columns.
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3. 10–20 m depth: Use the second color, or new third color, to wrap at 2 m intervals.

4. >20 m: Mark the line at 2.5 m intervals or continue with 2 m intervals.

6.6.1.8 Post-Field Calibration Checks

Post-field 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 postcalibration should be no more than 24 hours apart. When sampling daily, the second day’s calibration

can serve as the first day’s post-field calibration check. Take the same care used in performing the 

initial calibration by rinsing the sensors and waiting for sensors 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 postfield calibration values in the calibration logbook (generally on the same page with the initial 

calibration for that sampling trip). Deviation beyond the manufacturer’s specifications is cause for 

concern and should be addressed before the next sampling date.

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. This 

will ensure that 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. 

If post-calibration values (Table 5) fall outside the error limits for DO, pH, and specific conductance, 

data collected do not meet quality assurance (QA) standards and should be flagged appropriately (see 

SOP #12 for more details on QA/QC). Measurements may be repeated with a different or back-up 

instrument. If post-calibration measurements do not consistently fall within the error limits after inhouse trouble shooting, the instrument should be returned to the manufacturer for maintenance.

Table 5. Post-calibration check error limits.

Parameter Value 

Temperature ±1°C, annual calibration check 

Specific Conductance ±5% 

pH ±0.1 standard units 

Dissolved Oxygen ±0.2 mg/L, ± 10% saturation 

Do not adjust the instrument (using calibration 

controls) during the post-calibration check.
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6.6.1.9 Sensor Maintenance and Storage

Most multiparameter sondes should be stored with a small amount of water in the storage cup. Refer 

to the manufacturer’s manual for tips on cleaning the probes and housing, routine maintenance 

procedures, and proper storage procedures.

6.6.2 Calculation of Field Instrument Performance Criteria

Performance of field instruments must be checked in several ways, as detailed in the QA/QC 

procedures of SOP #12. Formulae for calculating instrument sensitivity, instrument precision, 

instrument bias, and cumulative bias are found in SOP #12.

Documentation of these performance criteria include estimation of the limits of detection of the 

multiprobe, the relative percent difference of duplicates, measurement of reference solutions, and 

estimates of change due to change in methods or instrumentation. 

6.6.3 Quality Assurance/Quality Control Samples

Quality control samples are commonly used in documenting quality control associated with the 

collection of samples in the field. Field blanks and duplicates are routinely incorporated into a 

monitoring program without a good understanding of their function. The purpose of these samples is 

to validate the precision and accuracy of laboratory data, and to determine the adequacy of 

preservation techniques, equipment cleaning and preparation, and sampling procedures. Field blanks 

are used to measure and quantify the amount of contamination from extraneous sources 

(preservatives, sample bottles, sample handling, automatic samplers, etc.) that might compromise the 

integrity of a sample (alter its true value or concentration). 

6.6.3.1 Equipment Blanks

Blanks are an integral part of quality control (QC) and are required for all sampling activities. Their 

creation should be noted in the field log book. Blanks establish that there is no sample contamination 

from the containers during custody, transportation, and or pre-analysis preparation either in the field 

or in the laboratory. Blanks establish the level of constituents introduced into a sample by the 

equipment used for sampling, preservatives, and/or containers. We will conduct equipment blanks 

prior to each field season and occasionally during the field season between field sites to ensure field 

rinsing is adequate.

Collect an equipment blank prior to the field season as follows:

1. Clean all equipment used to collect, store, and process water samples (e.g., integrating 

sampler, compositing jug, filtering apparatus) according to SOP #7.

2. Rinse the equipment used to collect and store water samples (integrating sampler and 

compositing jug) with laboratory reagent grade water three times and discard. 

3. Fill the integrating sampler with a fourth aliquot of laboratory reagent grade water and handle 

and process this aliquot as if it were a lake sample to be analyzed. 
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Another source of systematic error is sample cross contamination from field sampling equipment 

used to handle a multiple number of samples. The integrated sampler and compositing jugs are to be 

rinsed in the field three times at each site prior to taking a sample. Either piece of equipment may be 

a source of cross contamination. Collect periodic equipment blanks as follows: 

1. In between sample sites, rinse the equipment used to transfer water samples (integrating 

sampler and compositing jug) with laboratory reagent grade water three times and discard. 

2. Fill the integrating sampler with a fourth aliquot of laboratory reagent grade water and handle 

and process this aliquot as if it were a lake sample to be analyzed. 

This sample is labeled as an equipment blank and information kept on a datasheet describing the 

source of the blank. Results for all parameters should be non-detect. This type of blank is a check for 

cross contamination between sampling sites and control for bias introduced by cross contamination.

Other types of blanks will be used as needed: field sampling conditions or ambient blanks, if there is 

any reason to suspect that ambient air pollution has the potential to contaminate water quality 

samples; preservative blanks, if there is any reason to suspect that a preservative may be 

contaminated; or bottle blanks, any time sample collection bottles are of uncertain quality or 

cleanliness or from a source not previously used.

6.6.3.2 Sampling Duplicates

The purpose of a duplicate sample is to estimate the inherent variability of a procedure, technique, 

characteristic or contaminant. Duplicate samples are collected and duplicate analyses may be made in 

the field: 1) as a form of field quality control; 2) to measure or quantify the homogeneity of the 

sample, the stability and representativeness of a sample site, the sample collection method(s) and/or 

the technician’s technique. 

Duplicates are analyzed in the laboratory for the same parameters as the monitoring sample to which 

they apply. Laboratory duplicates which exceed QA/QC standards for the parameter are retested. 

Analytical results of duplicate samples will, theoretically, be the same. Realistically, results may 

differ due to the non-homogeneity of the sample source, and sampling and analytical errors. 

Duplicate samples also document the technique and ability of the technician and analyst to produce 

representative water quality data. 

The laboratory analytical report must show test results for the duplicates, blanks and spikes, the 

method and the results for summary quality control statistics calculations. Copies of these reports are 

a permanent part of the site file.

Duplicates will ideally be splits of homogeneous samples to estimate measurement precision in the 

context of repeatability unless otherwise documented and justified. If enough sample water cannot be 

collected in the compositing container to facilitate a split sample, then duplicate samples will be colocated. 
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Duplicate field samples must be collected every sampling trip for each type of sample collected and 

the results must have a Relative Percent Difference (RPD) less than or equal to the guidelines in 

Table 6. Required field parameter measurements can be duplicated to estimate the precision of the 

equipment. Every tenth measurement may be duplicated, and the results of both measurements 

recorded and evaluated as RPD. The result can be compared with the stated precision of the 

instrument.

Table 6. Frequency, acceptable range, and corrective actions for duplicate samples.

Type of 

Duplicate Frequency

Acceptable Range for 

Precision Corrective Action

Field 

duplicates 

(samples) 

Minimum of 1 per trip 

per parameter or 

10% of all samples 

per parameter per 

day 

Chlorophyll-a, TSS and 

nutrients ±30% RPD; all 

other parameters ±15% 

RPD 

Audit field personnel and verify sample 

collection procedure; resample; 

reanalyze; revise SOP; audit and train 

field personnel; project manager 

determines whether associated data is 

usable 

Field 

duplicates 

(multiprobes) 

Minimum of 1 per trip 

per parameter or 

10% of all samples 

per parameter per 

day 

All parameters ±10% 

RPD

Re-calibrate instrument; replace batteries; 

perform instrument field check with 

different standards; repair or replace 

instrument; notify management; audit and 

train field personnel; project manager 

determines whether associated data is 

usable

6.6.4 Summary of Quality Assurance/Quality Control Field Procedures 

Quality assurance protocols are means to ensure data collected are as representative of the natural 

environment as possible. Quality assurance procedures are required in all data collection efforts as 

part of this monitoring protocol. Many of the key elements of quality assurance have been included 

in the SOPs where appropriate, as well as detailed in SOP #12. A summary of important QA/QC 

procedures follows. Table 7 lists additional requirements for QA/QC methods and documentation.

 Field staff must be trained by personnel experienced in the protocol. Training will include 

classroom time as well as field and lab components. Details of the training are given in the 

Standard Operating Procedure #2: Training and Safety.

 Use calibrated instruments for all field measurements. Test and/or calibrate the instruments 

before leaving for the field. Each field instrument must have a permanent log book for 

recording calibrations and repairs. Review the log book before leaving for the field.

 All manually recorded field measurement data will be collected on field forms; data that are 

automatically recorded will be captured electronically and the equipment used will be 

documented on field forms. Hard and electronic copies will be made as soon as possible after 

surveys and kept at a separate location as backup.
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Table 7. Summary of QA/QC documentation and sampling methods.

Procedure Description/reason

Instrument calibration logs Each instrument must have a log in the form of a permanently bound 

logbook. Calibration schedule must be observed, using fresh 

calibration standards.

Project binder Containing: checklist of QA/QC reminders, copies of 

decontamination, sample collection and processing SOPs, copies of 

equipment calibration and troubleshooting instructions, ASR and 

COC forms, blank field forms.

Site binders Containing: GPS coordinates for verification of correct sampling 

location, table of previous field measurements to compare with new 

measurements

Field forms Field forms are the only written record of field measurements, so 

copies are placed in site binders and originals must be kept on file 

indefinitely. 

Field instrument methods Require consistent measurement methods and detection limits 

Sample preservation and 

minimum holding time

Water quality variable concentrations are maintained as close to 

sampling conditions as possible.

Chain-of-custody A chain-of-custody includes not only the form, but all references to 

the sample in any form, document or log book which allow tracing the 

sample back to its collection, and documents the possession of the 

samples from the time they were collected until the sample analytical 

results are received. 

Laboratory methods Require consistent analytical methods and detection limits

 Complete records will be maintained for each sampling station and all supporting metadata 

will be recorded appropriately (field forms or electronically). 

 Make field measurements in a manner that minimizes bias of results. 

 Check field-measurement precision and accuracy. Follow the procedures in SOP #12.

 Collect 10% duplicate water samples; conduct duplicate measurements of field parameters at 

approximately 10%.

 Create field blanks prior to the beginning of each field season and periodically throughout the 

season.

6.6.5 Corrective Responsive Action

The project manager, in consultation with experienced professionals, will be responsible for taking 

corrective responsive action in the case in which QA/QC is not followed or in the case of an 

unexpected event. Responsive action is often needed in the event of broken sample bottles, missing 
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data, errors on field sheets, changes due to field conditions, problematic analyses and other events 

that do not fall within the standard operating procedures. A “Memo-to-file” will be used to document 

any decisions or corrections that are made. This memo will include the date, name of author, site or 

sample referred to, a description of the problem or error and a statement describing the decision made 

or action taken. The memo will be archived with the appropriate site data and files.

6.7 Data and Records Management

 Hand-written field sheets with core suite profiles should be reviewed for completeness 

immediately upon returning to the shore. Make photocopies as soon possible and file them 

appropriately. Download and back up data from data loggers as soon as possible. 

 Ensure that field forms, field notebooks, and other hardcopy records are secure, organized, and 

available for viewing, reproduction, or transfer upon request and/or at the end of each field 

season.

 Schedule and perform regular data transfer and backup. Data will be protected from loss or 

damage by daily backup, when possible, or on a feasible schedule approved by the project leader 

and the data manager. Ideally, raw data are backed up off-site as soon as a sampling trip is 

completed. Electronic data will be backed up from field sites using the GLKN FTP site 

following each sample round.

 Record and verify observed or measured data values. Complete paper forms and enter or import 

data into NPSTORET and/or other electronic databases. 

 A ‘Memo-to-file’ will be used to document any decisions or corrections that are made. This 

memo will include the date, name of author, site or sample referred to, a description of the 

problem or error, and a statement describing the decision made or action taken. The memo will 

be archived with the appropriate site data and files. 

 Data validation, the process by which data are proven or disproved to be accurate, involves the 

review of the results of all measurements, samples, and QC samples. Sample data should be 

flagged if the analyte was detected in a blank at a concentration similar to that in the sample; 

flagged data contain much more uncertainty than unflagged data. Some investigation into the 

sampling method may be needed if flagged data are a continual occurrence.

 Refer to SOP #8 for more details regarding data entry and management.
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6.8 Literature Cited

Baker, J. R., D. V. Peck, and D. W. Sutton (editors). 1997. Environmental monitoring and 

assessment program (EMAP) surface waters: Field operations manual for lakes. EPA/620/R97/001. U.S. Environmental Protection Agency, Washington D.C. Available at 

www.epa.gov/emap/html/pubs/docs/groupdocs/surfwatr/field/97fopsman.html.

Carlson, R. E., and J. Simpson. 1996. A coordinator’s guide to volunteer lake monitoring methods. 

North American Lake Management Society (www.nalms.org). Available at 

http://dipin.kent.edu/Sampling_Procedures.htm.

Clesceri, L. S., A. E. Greenberg, and A. D. Eaton (editors). 1998. Standard methods for the 

examination of water and wastewater (20th edition). American Public Health Association, 

Washington, D.C. 

Hoffman, R. L., T. J. Tyler, G. L. Larson, M. J. Adams, W.Wente, and S. Galvan. 2005. Sampling 

protocol for monitoring abiotic and biotic characteristics of mountain ponds and lakes. Chapter 2 

in Book 2, Collection of Environmental Data, Section A, Water Analysis Techniques and 

Methods 2-A2. U.S. Department of the Interior, U.S. Geological Survey, Reston, Virginia.

Irwin, R. 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. Available at 

www.nature.nps.gov/water/Vital_Signs_Guidance/Guidance_Documents/part_b_lite_05_2005.p

df.

Irwin, R. 2004. Vital signs long-term aquatic monitoring projects, planning process steps: Part B, 

issues to consider and then document in a detailed study plan that includes a quality assurance 

project plan (QAPP) and monitoring “protocols” (including standard operating procedures), 

January 2004 draft. Available at 

http://science.nature.nps.gov/im/monitor/protocols/wqPartB.doc. 

Magdalene, S., D. R. Engstrom, and J. Elias. 2007. Standard operating procedure #6: Field 

measurements and water sample collection. In S. Magdalene, D. R. Engstrom, and J. Elias. 2008. 

Large rivers water quality monitoring protocol, version 1.0. Great Lakes Inventory and 

Monitoring Network. Natural Resource Report NPS/GLKN/NRR—2008/060. National Park 

Service, Fort Collins, Colorado.

NAPAP (National Acid Precipitation Assessment Program). 1990. Acid deposition: State of science 

and technology, Volume II aquatic processes and effects. National Acid Precipitation Assessment 

Program, Office of the Director, Washington, DC.

O’Ney, S. E. 2005. Standard operating procedure #5: Procedure for collection of required field 

parameters, version 1.0. Appendix E in Regulatory water quality monitoring protocol, version 

1.0. National Park Service, Greater Yellowstone Network, Bozeman, Montana. 
Standard Operating Procedure #6: Field Measurements and Water Sample Collection, Version 1.2 September 2015

Water Quality Monitoring Protocol for Inland Lakes, Version 1.1 31

Penoyer, P. 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. Aug. 6, 2003. Draft. Available at 

http://science.nature.nps.gov/im/monitor/protocols/wqPartC.doc. 

Route, B., W. Bowerman, and K. Kozie. 2009. Protocol for monitoring environmental contaminants 

in bald eagles, version 1.2: Great Lakes Inventory and Monitoring Network. Natural Resource 

Report NPS/GLKN/NRR—2009/092. National Park Service, Fort Collins, Colorado.

USGS (U.S. Geological Survey). 2005. National field manual for the collection of water-quality data. 

Chapters A1–A9 in U.S. Geological Survey Techniques of Water-Resources Investigations, book 

9. Available at http://pubs.water.usgs.gov/twri9A.

WOW (Water on the Web). 2004. Water on the Web––Monitoring Minnesota lakes on the internet 

and training water science technicians for the future: A national on-line curriculum using 

advanced technologies and real-time data. University of Minnesota–Duluth, Duluth, Minnesota. 

Available at http://waterontheweb.org.
Standard Operating Procedure #6: Field Measurements and Water Sample Collection, Version 1.2 September 2015

Water Quality Monitoring Protocol for Inland Lakes, Version 1.1 32

Attachments

 Field Data Sheet

 Multiprobe Calibration Log

 Eureka Manta Maintenance Log

 Multiprobe Calibration/Maintenance Log
Standard Operating Procedure #6: Field Measurements and Water Sample Collection, Version 1.2 September 2015

Water Quality Monitoring Protocol for Inland Lakes, Version 1.1 33

Figure A1. The water quality monitoring field data sheet (front).

Park______________________ Site Code__________________________ Date____________________ Start time__________ End time__________

Location Name____________________________________________ Secchi (m) 1st___________ 2nd ____________ Ave._________________ 

UTM/LatLong_________________________________________________ Secchi reading cond.: excellent 1 moderate 2 poor 3 on bottom 4

NAD______ Zone*: 15N 16N WP#_____________________________ Transparency Tube (cm) 1st__________ 2nd __________ Ave.__________

Personnel______________________________________________________ Water color (visual, in composite jug) ______________________________

Instrument(s)_______________________Cal Date_______________ Water sample type: I-tube Grab Van Dorn Other___________

Model/Model#___________________________________________________ VanDorn depth (m) _______________Wave Height (cm) _______________

Elevation (MSL, ft or m?)___________________ Zmax (m)___________ probe____________other________________________

Barometric Pressure (_________in Hg) (25.4mm/in) = _________mm Hg DO Cal (% sat.) Start____________Finish___________

B= Bottom, Q=QA/QC

Initials Observer 1: Benchmark Nail

Initials Observer 2: Benchmark Nail

Chl a ______________________TSS ________________________

TP/TN, NOx/NH4

Chl-a

Alk, Cl, SO4

DOC

SiO2

Ca, Mg, Na, K

TSS

Other (diatoms, Hg, contaminants, etc.) Weather Observations - fill in blanks or circle code Current Past 48 hours Wind Dir. (as °) _________ Wind Condition Code Rainfall & Wind

Air Temp (°C)________ Smoke rises vertically 0

Sky Cover Code Smoke drifts, leaves rustle 1 Clear: < 10% 0 Wind felt on face 2

Scattered: 10% to 50% 1 Flag extended, leaves move 3

Broken: 51% to 90% 2 Dust, sm. branches move 4 Overcast: > 90% 3 Small trees begin to sway 5 Obscure: precip or obstruction 4 Large branches move, wires 6

Fog 5 whistle, umbrellas hard to control

Light Mist 6 Beyond 6, you shouldn't be out in a boat

Any Info on Back?

Y N

Water Sample Collected for (check off):

Water Sample Info

Correction 

(+/-)

Water 

Level 2

Avg WL 1 & 2

EC 

(μS/cm) Depth (m) Temp (C)

DO 

(mg/L) pH DO (% sat)

(SACN only)

(SACN only)

Water Level Measurement 

Sample Volume Filtered (ml)

Stadia Meas.

Correction 

(+/-)

Water 

Level 1

Stadia Meas.
Standard Operating Procedure #6: Field Measurements and Water Sample Collection, Version 1.2 September 2015

Water Quality Monitoring Protocol for Inland Lakes, Version 1.1 34

Figure A2. The water quality monitoring field data sheet (back).

B= Bottom, Q=QA/QC

NOTES: DO (% sat) EC 

(μS/cm)

Azimuth (0-360°) Description

Landmark Information (for site establishment or re-establishment)

Picture Filename

Depth (m) Temp 

(C) pH DO (mg/L)
Standard Operating Procedure #6: Field Measurements and Water Sample Collection, Version 1.2 September 2015

Water Quality Monitoring Protocol for Inland Lakes, Version 1.1 35

Eureka Manta Multiprobe Calibration 

Personnel Date

Multiprobe

DO Membrane Changed

Date

Time

pH Reference Electrolyte Changed 

Date

Calibration 

Standard 

(True Value)

PreCalibration 

Reading

Calibration 

Reading

Calibration 

Check

Pre- or PostField?

Battery 

Voltage

Depth 0

SpCond 

(μS/cm) Air (0)

SpCond 

(μS/cm)

value 

Lot#

SpCond 

(μS/cm)

value 

Lot#

SpCond 

(μS/cm)

value 

Lot#

Temperature

pH 

7 

Lot#

pH 

10 

Lot#

pH

4 

Lot#

pH

 

Lot#

Baro Pressure

DO% 

Saturation

DO (mg/L)

Standard Operating Procedure #6: Field Measurements and Water Sample Collection, Version 1.2 September 2015

Water Quality Monitoring Protocol for Inland Lakes, Version 1.1 37

Eureka Manta Maintenance Log

Record maintenance performed, date, and person conducting maintenance

Date & Personnel DO Probe pH probe EC25 probe Temperature

Depth 

Sensor

Standard Operating Procedure #6: Field Measurements and Water Sample Collection, Version 1.2 September 2015

Water Quality Monitoring Protocol for Inland Lakes, Version 1.1 39

MULTIPROBE CALIBRATION/MAINTENANCE LOG 

PRE FIELD CALIBRATION 

Calibration _______ Initials:_________ Sonde ID:________ Date:______ Time: _______Instrument:________ Battery 

Voltage:___________ 

Function Temp. of 

Standard 

Value of 

Standard 

Initial 

Reading 

Calibrated 

to Comments 

Specific conductance 

pH calibrated (~7) 

pH secondary standard 

(4 or 10) 

Dissolved oxygen 

DATA NEEDED FOR DISSOLVED OXYGEN CALIBRATION 

Altitude (A )=______________feet above msl Barometric pressure _________ inches 

Barometric Pressure (BP) Options Barometric Pressure Formulas 

Barometer Barometric pressure (inches) ________ x 25.4 = BP ________mm 

From local source after correction (CBP) BP _________ mm = CBP _______mm - 2.5 (altitude ____/100) 

Estimated from altitude only BP _________ mm= 760 mm - 2.5 (altitude _____/100) 

For older Hydrolabs: Table DO value______ x ALTCORR______ x BAROCORR ______= DO standard _______ 

POST FIELD CALIBRATION CHECK Post Calibration Initials: Date: Time: Instrument: Battery Voltage: date of original calibration 

______ 

Function Temp. of 

Standard 

Value of 

Standard 

Initial 

Reading 

Calibrated 

to Comments 

Specific conductance 

pH 7 

pH secondary standard 

(4 or 10) 

Dissolved oxygen 

Check previous maintenance and use; do the following before calibration: 

Polish conductivity electrodes. Must be polished within 

the last two months or once every 15 field trips 

Date: Name/comments: 

Change pH reference probe solution. Must be renewed 

within last two months or once every 15 field trips. 

Date: Name/comments: 

Inspect DO membrane for nicks or bubbles. Must be 

changed within last six months or once every 15 field 

trips. 

Date: Name/comments: 

Change battery. Change once a year. Change internal 

batteries for newer generation products according to 

guidelines in product manual. 

Date: Name/comments: 

[TCEQ] Texas Commission on Environmental Quality, Monitoring Operations Division. 2003. Surface water quality monitoring 

procedures, Volume 1: Physical and chemical monitoring methods for water, sediment and tissue. Publication nr RG-415 

(formerly GI-252). Available from www.tceq.state.tx.us/comm_exec/forms_pubs/pubs/rg/rg-415/index.html.

Standard Operating Procedure #7: Samples and 

Analytical Laboratory Requirements

Version 1.2

In Water Quality Monitoring Protocol for Inland Lakes

Prepared by

Richard Axler and Elaine Ruzycki

Center for Water and the Environment

Natural Resources Research Institute

University of Minnesota–Duluth

5013 Miller Trunk Highway

Duluth, Minnesota 55811

and

Joan Elias and David VanderMeulen*

National Park Service

Great Lakes Inventory and Monitoring Network 

2800 Lake Shore Drive East

Ashland, Wisconsin 54806

* Contact author: david_vandermeulen@nps.gov

September 2015

Suggested citation: 

Axler, R., E. Ruzycki, J. E. Elias, and D. VanderMeulen. 2015. Standard operating procedure #7: 

Samples and analytical laboratory requirements, version 1.2. In J. E. Elias, R. Axler, E. Ruzycki, and 

D. VanderMeulen. 2015. Water quality monitoring protocol for inland lakes: Great Lakes Inventory 

and Monitoring Network, version 1.1. Natural Resource Report NPS/GLKN/NRR—2015/1027. 

National Park Service, Fort Collins, Colorado.

Standard Operating Procedure #7: Samples and Analytical Laboratory Requirements, Version 1.2 September 2015

Water Quality Monitoring Protocol for Inland Lakes, Version 1.1 i

SOP7 – Contents

Page

Revision History Log............................................................................................................................iii

Acknowledgements...............................................................................................................................iii

7.0 Introduction......................................................................................................................................1

7.1 Summary of Analytical Methods.....................................................................................................1

7.2 Sample Handling and Processing Procedures..................................................................................5

7.3 Shipping Procedures ........................................................................................................................8

7.4 Quality Assurance/Quality Control..................................................................................................9

7.5 Data and Records Management .......................................................................................................9

7.6 Literature Cited ..............................................................................................................................11

Attachment A. Example of a chain of custody and analysis request form. .........................................13

SOP7 – Tables

Page

Table 1. Examples of analytical methods, method detection limits (MDLs), containers, 

and holding times...................................................................................................................................2

Table 2. Frequency of analyses of water samples and depths at which samples will be 

collected. ................................................................................................................................................4

Table 3. Laboratory equipment and supplies list. .................................................................................6

Standard Operating Procedure #7: Samples and Analytical Laboratory Requirements, Version 1.2 September 2015

Water Quality Monitoring Protocol for Inland Lakes, Version 1.1 iii

Revision History Log

The following table lists all edits and amendments to this document since the original publication 

date. Information entered in the log must be complete and concise. Users of this standard operating 

procedure will promptly notify the project manager and/or the Great Lakes Network (GLKN) data 

manager about recommended and required changes. The project manager must review and 

incorporate all changes, complete the revision history log, and change the date and version number 

on the title page and in the header of the document file. For complete instructions, please refer to 

Revising the Protocol, SOP #13.

Revision History Log:

Previous 

Version 

#

Revision 

Date

Author (with 

title and 

affiliation)

Location in Document and 

Concise Description of 

Revision Reason for Change

New 

Version 

#

1.0 2/25/2010 Rick Damstra, 

David 

VanderMeulen, 

Joan Elias, 

GLKN 

7.2 Sample Handling and 

Processing – clarification; 7.3 

Shipping Procedures –

clarification; 7.4 Quality 

Assurance/Quality Control -

clarification

To bring SOP into 

alignment with

procedures practiced

1.1

1.1 5/01/2015 David 

VanderMeulen, 

GLKN

Updated the NPS contact author, 

added that field samples might 

be collected as elbow deep grab 

samples, included information 

about acid-washing bottles, fixed 

a handful of grammatical errors

throughout

To clarify and update 

SOP based on changes 

that have occurred 

since Version 1.1 was 

published in 2010

1.2

Add rows as needed for each change or set of changes tied to an updated version number

Acknowledgements

Combinations of existing protocols were used to develop this standard operating procedure for 

handling and processing water samples prior to sending them to an analytical laboratory. The authors 

wish to acknowledge these sources (Hoffman et al. 2005, O’Ney 2005, USGS 2005, WOW 2004, 

Penoyer 2003, EPA 2001, and Baker et al. 1997) for the guidance they provided. Thanks also go to 

White Water Associates for providing examples of forms for analytical requests and chain of 

custody.

Standard Operating Procedure #7: Samples and Analytical Laboratory Requirements, Version 1.2 September 2015

Water Quality Monitoring Protocol for Inland Lakes, Version 1.1 1

7.0 Introduction

As part of our water quality monitoring program, we will collect water samples for analysis of basic 

limnological parameters that may respond to stressors such as atmospheric deposition, land use 

change, and recreational pressures. Because neither the GLKN nor the individual park units currently 

have certified laboratories and instrumentation for performing these analyses, water samples will 

need to be processed soon after collection for transport to a suitable laboratory. This will require 

filtering and preserving subsamples of water and filters according to methods specific to the analyte. 

This standard operating procedure (SOP) is designed to provide detailed instructions on the handling 

and processing of water samples prior to analysis by an analytical laboratory. 

We will collect water in the field (SOP #6) for the analysis of the following parameters:

 Nutrients: total phosphorus (TP), total nitrogen (TN), nitrate+nitrite-N (NO3+NO2-N ), and 

ammonium-N (NH4-N)

 Total chlorophyll-a 

 Major anions (SO4

-2

and Cl-);

 Alkalinity

 Major cations (Mg+2, Ca+2, Na+, K+)

 Dissolved silica (SiO2)

 Dissolved organic carbon (DOC)

Water chemistry will be performed by one or more analytical laboratories that have demonstrated the 

ability to measure analytes at detection levels adequate to meet our needs. Preferably, the laboratories 

will be state- or federally-certified for performing the above water chemistry analyses in natural 

waters, or an academic research laboratory that can demonstrate quality assurance and quality control 

(QA/QC) procedures consistent with SOP #12 and current EPA procedures used as the basis for state 

certification of commercial environmental laboratories. The GLKN’s preference is for laboratories to 

provide clean sample bottles and preservatives, where appropriate, as well as chain of custody 

documentation and sample logging.

7.1 Summary of Analytical Methods 

Analytical methods, method detection limits, and procedures related to handling samples change over 

time as the science progresses. Table 1 summarizes examples of the variety of methods, detection 

limits, preservation techniques, and holding times for water samples addressed in this protocol. Table 

2 summarizes the frequency at which water samples will be collected for analysis.
Standard Operating Procedure #7: Samples and Analytical Laboratory Requirements, Version 1.2 September 2015

Water Quality Monitoring Protocol for Inland Lakes, Version 1.1 2

Table 1. Examples of analytical methods, method detection limits (MDLs), containers, and holding times.

Analyte

Analytical

Note 1 Method # Det. Limit

Vol. 

(ml) Filter Preservation

Sample 

Bottle

Note 2

Hold 

Time

Alkalinity

Titrimetry 310.1 EPA-NERL 10 mg/L 4oC 14 d

Spec. auto. 310.2 EPA-NERL 10 mg/L 4oC 14 d

Titrimetry NFM USGS-OWQ 0.01 meg/L Note 4 None none

Calcium

ICP 3120B APHA 10 ug/L Note 3 pH<2 HNO3 P or G 6 mo

Titrimetry 215.2 EPA-NERL 0.5 mg/L Note 3 4oC 6 mo

FAA I-3152 USGS-NWQL 0.1 mg/L 250 

mL Note 3 pH<2 HNO3 P 180 d

Chloride

IC 300.0 EPA-NERL 0.02 mg/L 4oC P or G 28 d

Colorimetry 325.2 EPA-NERL 1 mg/L 4oC 28 d

Titrimetry 4500-Cl APHA 0.15 mg/L 100 

mL 4oC P or G 28 d

Chlorophyll-a Spect. 10200 APHA 2 ug/L ≤1 L Note 4 Freeze filter P 30 d

Color

Spect. 110.2 EPA-NERL 5 Pt units Note 5 4oC G 48 hr

Vis. Comp. I-1250 USGS-NWQL 1 Pt-co 

250 

mL Note 5 4 oC P 30 d

DOC

Spect. 415.3 EPA 0.018 mg/L 125 Note 3 pH<4 H2SO4 G 28 d

Spect. 0-1122-92 USGS 0.1 mg/L 4oC AG

K

ICP 3120B APHA 0.3 mg/L Note 3 pH<2 HNO3 P or G 6 mo

FAA 3111B APHA 5 ug/L Note 3 pH<2 HNO3 P or G 6 mo

Mg

ICP 3120B APHA 20 ug/L Note 3 pH<2 HNO3 P or G 6 mo

FAA 3111B APHA 0.5 ug/L Note 3 pH<2 HNO3 P or G 6 mo

Na

ICP 3120B APHA 30 ug/L Note 3 pH<2 HNO3 P or G 6 mo

FAA 3111B APHA 2 ug/L Note 3 pH<2 HNO3 P or G 6 mo

NH4-N

Selective elec. 4500-NH3E 0.08 mg/L 4oC/pH2,0oC 24 hr /

28 d

Colorimetry 350.2 EPA-NERL 0.08 mg/L pH<4 H2SO4 28 d

Titrimetry 4500-NH3 APHA 5 mg/L 4oC / pH2,0oC

24 hr /

28 d

SiO2

ICP 3120B APHA 20 ug/L Note 3 pH<2 HNO3 P or G 6 mo

Spect. 4500- SiO2 D APHA 0.04 mg/L Note 3 No, 4oC P 28 d

FIA-Spect. 4500- SiO2 F APHA 0.78 ug/L Note 3 No, 4oC P 28 d

TSS Gravimetric I-3765 USGS-NWQL 1 mg/L 250–

500 Note 4 4oC filter P NA

SO4 IC 4110C APHA 75 ug/L Note 3 pH<4 H2SO4 P or G
Standard Operating Procedure #7: Samples and Analytical Laboratory Requirements, Version 1.2 September 2015

Water Quality Monitoring Protocol for Inland Lakes, Version 1.1 3

Table 1 (continued). Examples of analytical methods, method detection limits (MDLs), containers, and 

holding times.

Analyte

Analytical

Note 1 Method # Det. Limit

Vol. 

(ml) Filter Preservation

Sample 

Bottle

Note 2

Hold 

Time

SO4

(continued)

CIE-UV D6508 ASTM 0.1 mg/L Note 3 pH<4 H2SO4 ASAP

Spect. 37512 EPA-NERL 0.5 mg/L Note 3 pH<4 H2SO4 P or G 28 d

TP

Spect. I-2606 USGS-NWQL 0.001 mg/L 125 

mL MgCl 4oC BrownP 30 d

Alkaline P USGS 2003 0.01 mg/L 120 ml Note 6 4oC / H2SO4

48 hr /

30 d

ICP 200.7 EPA-NERL 60 ug/L pH<2 HNO3 P 6 mo

TN

Alkaline P USGS 2003 0.03 mg/L 120 ml Note 6 4oC / H2SO4

48 hr /

30 d

Titrimetry 4500-N 0–100 mg/L 4oC AG 7 d

Combustion 440.0 EPA-NERL 0.1 mg/L Filter 100 d

Source: National Environmental Methods Inventory website (NEMI 2006)

This list is not an endorsement of any particular method or laboratory for any particular analyte. Rather it is to be used as a 

reference for the range of analytical methods available for each analyte. There are surface water conditions (pH, turbidity, other 

elements) that make a particular method unsuitable for a particular situation. As GLKN is monitoring surface water, the methods 

listed were chosen as representative of the lower range of detection limits.

Note 1. CIE-UV= capillary ion electrophoresis with UV detection, FAA = flame atomic absorption, FIA = flow injection analysis, IC= 

ion chromatography, ICP = inductively coupled plasma, Spec. auto = spectroscopy with autoanalyzer

Note 2. P = plastic (polypropylene), G=glass, AG=amber glass

Note 3. 0.45μm membrane filter. Pre-filter for dissolved portion analysis.

Note 4. 0.45μm glass fiber filter.

Note 5. 0.45μm membrane filter or centrifuge is recommended to remove suspended solids that affect color; however some color 

will also be removed.

Note 6. USGS 2003. Evaluation of Alkaline Persulfate Digestion as an Alternative to Kjeldahl Digestion for Determination of Total 

and Dissolved Nitrogen and Phosphorus in Water By Charles J. Patton and Jennifer R. Kryskalla. U.S. Geological Survey WaterResources Investigations Report 03-4174.
Standard Operating Procedure #7: Samples and Analytical Laboratory Requirements, Version 1.2 September 2015

Water Quality Monitoring Protocol for Inland Lakes, Version 1.1 4

Table 2. Frequency of analyses of water samples and depths at 

which samples will be collected. Surface samples will be a 0–2 m 

integrated sample or an elbow-deep (ca. 0.3 m) grab sample. 

Bottom samples will be collected during mid-summer if a lake is 

stratified. 

Water Quality Variables

Monitoring 

Frequency

Total phosphorus (TP) 3x/yr, surface

1x/yr, bottom

Total Nitrogen (TN) 3x/yr, surface

Nitrate + Nitrite-Nitrogen (NO3+NO2-N) 3x/yr, surface

Ammonium-Nitrogen (NH4-N) 3x/yr, surface

Major Anions (SO4

-2

, Cl-) 1x/yr; surface

Alkalinity 1x/yr; surface

Major Cations (Mg+2, Ca+2, Na+, K+) 1x/yr; surface

Dissolved silica (SiO2) 1-2x/yr; surface

Dissolved organic carbon (DOC) 1x/yr; surface

Total chlorophyll-a 3x/yr; surface
Standard Operating Procedure #7: Samples and Analytical Laboratory Requirements, Version 1.2 September 2015

Water Quality Monitoring Protocol for Inland Lakes, Version 1.1 5

7.2 Sample Handling and Processing Procedures

The following general techniques will be observed throughout the procedures detailed in 7.2.1 

through 7.2.4.

1. Keep all water samples cool and dark until processing is complete and samples are shipped to 

the analytical laboratory.

2. Use only new, clean sample bottles supplied by the analytical laboratory, purchased precleaned from a supplier, or those cleaned and acid-washed with 0.1N HCl by GLKN staff. 

3. Rinse filtration equipment with deionized water (DIW) three times between samples.

4. Avoid touching the inside of sample bottles and filtering apparatus, tips of forceps, and filters 

to prevent contamination of the samples.

5. When filtering samples in the field, use an enclosed filtering apparatus to minimize 

contamination from airborne sources.

6. Wear disposable, powderless gloves when working with acids and other preservatives.

7. Filter samples in the order of anticipated phosphorus concentrations, from low to high. After 

filtering a water sample that is expected to contain high nutrient concentrations, rinse the 

apparatus three times with 0.1N HCl followed by three times with DIW water before 

processing the next sample.

8. Prepare QA/QC samples in the same manner as regular samples, using water from the same 

sample collection container.

9. Rinse all reusable equipment with DIW immediately, before equipment dries.

10. Ensure all sample bottles are labeled correctly, completely, and legibly.

11. Check laboratory equipment and supplies list (Table 3) and ensure equipment is clean and 

ready for use and supplies are adequate.

12. Prepare a temperature check bottle for each anticipated cooler, if recommended by the 

contract analytical laboratory. Use tap water to fill an extra bottle of the same size used for 

one of the analytes and label as “Temperature Check.” Store this check bottle in refrigerator 

with other samples; package and send to the analytical laboratory with the other samples.
Standard Operating Procedure #7: Samples and Analytical Laboratory Requirements, Version 1.2 September 2015

Water Quality Monitoring Protocol for Inland Lakes, Version 1.1 6

Table 3. Laboratory equipment and supplies list.

 Filtration towers and manifold (4.7 mm) plastic

 Vacuum pump with pressure gauge and extra filtering flask as a water trap to 

protect the pump in case of overflow

 Graduated cylinders, plastic 250, 500 and 1000 mL

 Whatman GF/C filters (4.7 cm diameter)

 0.45 μm Millipore membrane filters (4.7 cm diameter)

 Filter forceps with broad tips

 Aluminum foil

 Labeling tape, permanent markers

 Deionized water (ASTM grade 1 or 2; 1–10 megohm)

 Acid for preservation (according to contract laboratory specifications)

 Freezer

 Plastic storage bags

 Sample bottles (provided by analytical laboratory)

 Insulated ice chest, ice, and ice packs

 Saturated MgCO3 solution (for chlorophyll-a), depending on laboratory method

 Adjustable automatic pipettes: 1–5 mL ; 0.2–1 mL; 0.02–0.1 mL

 Paraffin paper roll 

 Wash (squirt) bottles – 500 mL

 Kim wipes

The following sections detail the procedures to be followed when processing water samples for 

particular analysis.

7.2.1 Total Chlorophyll-a

1. Fit rinsed filtering device with a Whatman GF/C glass fiber filter using forceps, smooth side 

down (curl is up). 

2. Agitate water sample (always shake well to minimize subsampling error for solids).

3. Set pump vacuum to ≤0.5 atmospheres (7.5 PSI or 380 mm Hg). If using a hand pump, 

maintain pressure at or below 10 PSI.

4. Use a glass or plastic graduated cylinder to measure 100–1000 mL of water sample. Filter 

sample. If water is very turbid, filter small aliquots (100 mL) to avoid clogging the filter. 

Sufficient volume has been filtered when a green, brown, or tan color is clearly visible on the 

filter and the flow decreases to a few drops/second.

5. Add 0.15 mL (approx. 3 drops) of saturated MgCO3 during the last 30 mL of filtering to 

buffer the filter, if required by the method used by the contract analytical laboratory. 

6. Rinse graduated cylinder and filtering apparatus with DIW and pass through filter to include 

any algae that may have adhered to the sides of the cylinder.
Standard Operating Procedure #7: Samples and Analytical Laboratory Requirements, Version 1.2 September 2015

Water Quality Monitoring Protocol for Inland Lakes, Version 1.1 7

7. Record volume filtered on data sheet (excluding DIW rinse).

8. Use forceps to fold filter into quarters with sample on the inside; do not touch filter with 

fingers.

9. Wrap filter in foil; label foil with sample location, date, and time sample was collected, and 

volume filtered. Place foil in small, sealable baggie with standard laboratory label. 

10. Refrigerate immediately and freeze as soon as possible. Place small baggies with foils 

together in a large, sealable freezer bag. A third watertight container may be used for 

shipping to ensure that melt water in transport will not corrupt the samples.

7.2.2 Unfiltered (Raw) Samples

1. Rinse sample bottle provided by analytical laboratory 1x with sample water.

2. Fill sample bottle with sample water (fill to neck if sample will be frozen).

3. Refrigerate or freeze, as per laboratory instructions, until packaging for transport to analytical 

laboratory.

7.2.3 Filtered Samples

1. Using clean forceps, place a 0.45μm Millipore cellulose membrane filter in the filtration 

apparatus. Rinse with 100 mL DIW into a cleaned (0.1N HCl and DIW rinsed as per sample 

bottle cleaning) filtering flask (glass or plastic). Rinse flask with filtrate and discard filtrate. 

2. Filter a small amount (approx. 50 mL) of sample water; rinse filtering flask with filtrate and 

discard filtrate.

3. Filter enough of the sample to produce the required amount of filtrate to be tested.

4. Dispense the filtrate into separate bottles provided by the analytical laboratory as follows:

 Unpreserved constituents––rinse bottle with small amount of filtrate (approx.. 10 mL) 

and discard; fill bottle to neck, refrigerate or freeze as per laboratory instructions.

 Preserved constituents––if pre-loaded with preservative by the analytical laboratory, fill 

bottle, and store at room temperature or refrigerate. If bottle does not come pre-loaded 

with preservative, rinse bottle with small of amount of filtrate (approx. 10 mL) and 

discard, fill bottle approximately 3⁄4 full, add the preservative (ampule provided by 

laboratory) and continue to fill bottle until full. Gently roll bottle to mix. Store at room 

temperature or refrigerate.
Standard Operating Procedure #7: Samples and Analytical Laboratory Requirements, Version 1.2 September 2015

Water Quality Monitoring Protocol for Inland Lakes, Version 1.1 8

7.3 Shipping Procedures

1. Call FedEx or other courier service ahead of time to arrange pick-up. 

2. Make large quantities of ice cubes and ice blocks (or buy ice) ahead of time.

3. Line cooler with large plastic garbage bag.

4. Place all total chlorophyll-a baggies containing aluminum foil wrappers in one large sealable 

plastic bag. Place this baggie between 2 ice packs or bags of ice. It is critical that melt water 

does not soak the filters, so you may want to place large sealed bag of foil wrappers in a 

sealed plastic jar before surrounding with ice.

5. Use ice cubes, doubly bagged in plastic bags, to pack around samples; use other ice blocks 

(water bottles, soda bottles, etc.) as they will fit.

6. Include a temperature check bottle with the sample bottles in each cooler, if used by the 

contract analytical laboratory. 

7. Complete the chain of custody (COC) form, keeping the “client copy” for the project files. 

Seal the laboratory’s copies in a one-gallon plastic sealable bag and tape to the inside cover 

of the cooler. Prepare separate COC forms for each cooler. An example COC form is 

provided in Attachment B.

8. If the refrigerated samples are sent in the same insulated cooler with the frozen samples, 

protect them from freezing by wrapping them in newspaper, bubble wrap, or something 

similar.

9. Ship samples overnight so they are received the following day during a work-week, 

whenever possible. Contact the laboratory about Saturday shipment receipt availability 

before shipping samples on a Friday. Many laboratories do not have sample receipt staff on 

Saturday or charge extra for staff time. 

10. Alert the contract laboratory when samples have been shipped via phone or e-mail. Be sure to 

get acknowledgement from the lab that they know the samples are en route. Ask the lab to let 

you know when the samples are received.
Standard Operating Procedure #7: Samples and Analytical Laboratory Requirements, Version 1.2 September 2015

Water Quality Monitoring Protocol for Inland Lakes, Version 1.1 9

7.4 Quality Assurance/Quality Control 

Quality assurance/quality control refers to all those things good investigators do to ensure their 

measurements are accurate (the absolute true value) and precise (reproducible, consistent), and that 

they include a good estimate of their uncertainty. It specifically involves following established rules 

in the field and laboratory to assure everyone that the sample is representative of the site, free from 

outside contamination, and that it has been analyzed following standard QA/QC methods. These 

methods typically involve comparing the sample to a set of known samples for estimating accuracy 

and replicating the measurement to estimate its precision.

In the context of field sampling and processing, quality assurance protocols are meant to ensure that 

data collected are as representative of the lake or stream site as possible. Such procedures include 

implementing good field procedures and quality-control checks, careful post-collection processing of 

water samples to minimize artifacts due to contamination or mislabeling, proper storage and 

preservation techniques while in transit to a laboratory, and proper QA/QC by the laboratory itself. 

See SOP #12, Quality Assurance/Quality Control, for more details.

Quality assurance at the batch level (within the laboratory) is accomplished by using proper 

techniques and replicating 10% of the field samples. 

The most important aspects of quality control in the collection of water quality samples are: 1) 

samples collected should represent the lake site at the time the samples are collected, such that the 

samples produce the quality of information necessary to meet the objectives of the survey; and 2) the 

integrity of the samples collected is not compromised by contamination, misidentification, or 

improper sample handling or preservation. 

To help meet these quality control aspects, the transport and tracking of the samples from the field to 

the analytical laboratory that performs the chemistry analyses is critical. Each set of samples should 

include a Chain of Custody Form (COC), and if the lab uses it, an Analytical Services Request (ASR) 

(see Appendix B for an example). To ensure correct processing of samples, the information recorded 

on the COC and ASR forms must correspond to each sample in the shipment. Check with individual 

analytical laboratory requirements for correct labeling codes and procedures. To prevent water 

damage to paperwork accompanying samples to the laboratory, place all paperwork inside a sealable 

plastic bag and tape the bag to the underside of the cooler lid. Keep a copy of the completed COC 

and ASR forms in the office binder.

7.5 Data and Records Management 

Complete and accurate record keeping of field-derived data is an essential component of monitoring 

water quality. Field technicians, crew leaders, and project leaders share responsibility for collecting, 

verifying, and documenting data according to the guidelines in this monitoring protocol and all 

applicable standard operating procedures. Data and records management include the following 

responsibilities: 
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Water Quality Monitoring Protocol for Inland Lakes, Version 1.1 10

1. Refer to the GLKN Data Management Plan (Hart and Gafvert 2006) for overall guidance. 

2. Follow the QA/QC procedures in SOP #8 for specific instructions on data entry, 

management, verification, and validation. 

3. Record and verify observed or measured data values, including completing paper forms and 

entering data into NPSTORET and/or other electronic databases. NPSTORET maintains the 

necessary relationships between data values, equipment configuration and calibration, 

procedures, methods, and metadata. 

4. Schedule and perform regular data transfer and backup. Data will be protected from loss or 

damage by daily backup when possible, or on a feasible schedule approved by the project 

leader and the data manager. 

5. Review, verify, and correct field data and sample processing information as soon as possible 

after the actual survey (see SOP #8 for more details). 

6. Prepare data and procedural documentation, especially deviations from the protocol or study 

plan, including metadata forms in NPSTORET and additional documentation requested by 

the project manager or data manager. 

7. Ensure that field forms, field notebooks, and other hardcopy records are secure, organized, 

and available for viewing, reproduction, or transfer upon request.
Standard Operating Procedure #7: Samples and Analytical Laboratory Requirements, Version 1.2 September 2015

Water Quality Monitoring Protocol for Inland Lakes, Version 1.1 11

7.6 Literature Cited

APHA (American Public Health Association). 1998. Standard methods for the examination of water 

and wastewater, 20th edition. American Public Health Association, Washington, D.C.

Baker, J. R., D. V. Peck, and D. W. Sutton (editors). 1997. Environmental monitoring and 

assessment program (EMAP) surface waters: Field operations manual for lakes. EPA/620/R97/001. U.S. Environmental Protection Agency, Washington D.C. Available at 

www.epa.gov/emap/html/pubs/docs/groupdocs/surfwatr/field/97fopsman.html.

EPA (US Environmental Protection Agency). 2001. Guidance for preparing standard operating 

procedures (SOPs): EPA QA/G-6. Report nr EPA/240/B-01/004. U.S. Environmental Protection 

Agency, Washington, DC. Available at: www.epa.gov/quality/qs-docs/g6-final.pdf. 

Hart, M., and U. Gafvert (editors). 2006. Data management plan: Great Lakes Inventory and 

Monitoring Network. Great Lakes Inventory and Monitoring Network Report GLKN/2006/20. 

National Park Service, Ashland, Wisconsin. Available at 

http://science.nature.nps.gov/im/units/glkn/assets/docs/GLKN_SD8_Data_Management_Plan.pdf

Hoffman, R. L., T. J. Tyler, G. L. Larson, M. J. Adams, W.Wente, and S. Galvan. 2005. Sampling 

protocol for monitoring abiotic and biotic characteristics of mountain ponds and lakes. Chapter 2 

in Book 2, Collection of Environmental Data, Section A, Water Analysis Techniques and 

Methods 2-A2. U.S. Department of the Interior, U.S. Geological Survey, Reston, Virginia.

O’Ney, S. E. 2005. Standard operating procedure #5: Procedure for collection of required field 

parameters, version 1.0. Appendix E in Regulatory water quality monitoring protocol, version 

1.0. National Park Service, Greater Yellowstone Network, Bozeman, Montana. 

Penoyer, P. 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. Aug. 6, 2003. Draft. Available at 

http://science.nature.nps.gov/im/monitor/protocols/wqPartC.doc. 

USGS (US Geological Survey). 2003. Evaluation of alkaline persulfate digestion as an alternative to 

Kjeldahl digestion for determination of total and dissolved nitrogen and phosphorus in water. 

U.S. Geological Survey Water-Resources Investigations Report 03-4174.

USGS (US Geological Survey). 2005. National field manual for the collection of water-quality data: 

U.S. Geological Survey Techniques of Water-Resources Investigations, book 9, chaps. A1–A9, 

http://pubs.water.usgs.gov/twri9A.

WOW (Water on the Web). 2004. Water on the Web––Monitoring Minnesota lakes on the internet 

and training water science technicians for the future: A national on-line curriculum using 

advanced technologies and real-time data. University of Minnesota–Duluth, Duluth, Minnesota. 

Available at http://waterontheweb.org.

Standard Operating Procedure #7: Samples and Analytical Laboratory Requirements, Version 1.2 September 2015

Water Quality Monitoring Protocol for Inland Lakes, Version 1.1 13

Attachment A. Example of a chain of custody and analysis request form.

Standard Operating Procedure #8: Data Entry and 

Management

Version 1.2

In Water Quality Monitoring Protocol for Inland Lakes

Prepared by

Mark Hart, Joan Elias, Rick Damstra, and David VanderMeulen*

National Park Service

Great Lakes Inventory and Monitoring Network 

2800 Lake Shore Drive East

Ashland, Wisconsin 54806

* Contact author: david_vandermeulen@nps.gov

September 2015

Suggested citation: 

Hart, M., J. E. Elias, R. Damstra, and D. VanderMeulen. 2015. Standard operating procedure #8: 

Data entry and management, version 1.2. In J. E. Elias, R. Axler, E. Ruzycki, and D. VanderMeulen. 

2015. Water quality monitoring protocol for inland lakes: Great Lakes Inventory and Monitoring 

Network, version 1.1. Natural Resource Report NPS/GLKN/NRR—2015/1027. National Park 

Service, Fort Collins, Colorado.

Standard Operating Procedure #8: Data Entry and Management, Version 1.2 September 2015

Water Quality Monitoring Protocol for Inland Lakes, Version 1.1 i

SOP8 – Contents

Page

Revision History Log............................................................................................................................iii

Acknowledgements...............................................................................................................................iv

8.0 Introduction......................................................................................................................................1

8.1 Data Stewardship Roles and Responsibilities..................................................................................1

8.2 NPSTORET Database......................................................................................................................3

8.3 Aquarius Database ...........................................................................................................................5

8.4 Data Management Procedures .........................................................................................................5

8.5 Literature Cited ..............................................................................................................................13

SOP8 – Tables

Page

Table 1. Data stewardship responsibilities of water quality monitoring personnel. .............................2

SOP8 – Figures

Page

Figure 1. Schematic of data flow to the STORET database: water quality data are 

transferred from the Network to the national master database and ultimately to the master 

database..................................................................................................................................................3

Figure 2. Schematic of data flow to the Aquarius database: water quality data from data 

loggers are transferred from the Network to the WRD-hosted version of Aquarius.............................5

Figure 3. Great Lakes Network folder structure for information related to the protocol for 

monitoring water quality of inland lakes .............................................................................................10

Standard Operating Procedure #8: Data Entry and Management, Version 1.2 September 2015

Water Quality Monitoring Protocol for Inland Lakes, Version 1.1 iii

Revision History Log

The following table lists all edits and amendments to this document since the original publication 

date. Information entered in the log must be complete and concise. Users of this standard operating 

procedure will promptly notify the project manager and/or the Great Lakes Network (GLKN) data 

manager about recommended and required changes. The project manager must review and 

incorporate all changes, complete the revision history log, and change the date and version number 

on the title page and in the header of the document file. For complete instructions, please refer to 

Revising the Protocol, SOP #13. 

Revision History Log:

Previous 

Version 

#

Revision 

Date

Author (with 

title and 

affiliation)

Location in Document and 

Concise Description of 

Revision Reason for Change

New 

Version 

#

1.0 2/25/2010 Richard 

Damstra and 

David 

VanderMeulen, 

GLKN 

8.3.2 Data Entry, Verification, 

and Documentation – update 

data checking procedures

To bring SOP into 

alignment with 

practices

1.1

1.1 5/1/2015 David 

VanderMeulen, 

GLKN

Updated the NPS contact author, 

distinguished discrete from 

continuous data, noted that 

EQuIS database is used to load 

data into the National STORET 

Data Warehouse, deleted 

outdated information related to 

data distribution and interaction 

with data, added a schematic to 

show data flow for continuous 

data, added information about 

use of thermal arrays to collect 

water temperature data, added 

basic information about 

Aquarius summary statistics, 

data archival, and data 

availability and distribution, 

added information about the 

Integrated Resource 

Management Applications 

(IRMA) web portal, fixed a 

handful of grammatical errors 

throughout.

To clarify and update 

SOP based on changes 

that have occurred 

since Version 1.1 was 

published in 2010

1.2

Add rows as needed for each change or set of changes tied to an updated version number
Standard Operating Procedure #8: Data Entry and Management, Version 1.2 September 2015

Water Quality Monitoring Protocol for Inland Lakes, Version 1.1 iv

Acknowledgements

Primarily, we relied on the Great Lakes Network’s data management plan (Hart and Gafvert 2005) in 

writing this document. Standard operating procedures for the entry and management of data written 

by other networks also provided guidance.
Standard Operating Procedure #8: Data Entry and Management, Version 1.2 September 2015

Water Quality Monitoring Protocol for Inland Lakes, Version 1.1 1

8.0 Introduction

Water quality data collected under the inland lakes water quality monitoring protocol (Elias et al. 

2008) must be entered, quality-checked, documented, managed, and made available to others for a 

variety of purposes, such as management decision-making, research, and education. The National 

Park Service (NPS) Water Resources Division (WRD) developed a database application called the 

Water Quality Database Template, or NPSTORET, to facilitate management of water quality data. 

NPSTORET facilitates the importing of water quality data into a copy of Earthsoft’s EQuIS database 

maintained by WRD. From the EQuIS water quality data is imported into the National STORET 

(STOrage and RETrieval) Data Warehouse administered by EPA, as required by the water quality 

component of the Natural Resource Challenge (NPS 1999), NPS-75, and NPS Reference Manual 77. 

NPSTORET is best suited for water quality data that comes from discrete sampling during individual 

site visits.

To better accommodate continuous or time-series data that are generated from automated data 

loggers, WRD adopted Aquatic Informatics’ Aquarius system for storage and visualization of 

continuously monitored water quality data. The Network will utilize a version of Aquarius hosted by 

WRD for remote data entry, analysis and visualization.

This standard operating procedure outlines data stewardship roles and responsibilities, and provides 

specific instructions and references for entering, quality checking, and managing water quality data.

8.1 Data Stewardship Roles and Responsibilities 

Data stewardship is for the process of managing data and information resources that are organized, 

useful, compliant, available, and safe. The demand for detailed, high quality data and information 

about water quality requires a group of people working together to ensure that data are collected 

using appropriate methods, and that resulting datasets, reports, maps, and other derived products are 

well-managed. 

The Great Lakes Network (GLKN) aquatic ecologist serves as project manager for water quality 

monitoring. The project manager will supervise data collection, provide project oversight, direct onthe-ground data collections, and provide cohesive links among data collection, synthesis, 

interpretation, and reporting. 

While the project manager must act as the steward for water quality monitoring data for the Network, 

other project and GLKN personnel are also accountable for specific data management tasks. Table 1 

lists stewardship responsibilities of personnel involved in the management of water quality data. To 

ensure that all project data are managed properly, individuals must understand their responsibilities, 

communicate with one another, and assist one another as needed.
Standard Operating Procedure #8: Data Entry and Management, Version 1.2 September 2015

Water Quality Monitoring Protocol for Inland Lakes, Version 1.1 2

Table 1. Data stewardship responsibilities of water quality monitoring personnel.

Personnel Role Data management responsibilities related to water quality monitoring 

Project Crew 

Member 

Crew members collect and manage data with direction and guidance from the crew leader 

and/or project manager. Data collection includes calibrating and operating sampling 

equipment, collecting water samples, and recording measurements and observations. Crew 

members are responsible for quality control by following data collection and recording 

instructions and by promptly verifying recorded data. Crew members may also perform data 

entry and verification. 

Project Crew 

Leader 

The crew leader normally performs the same duties as the other crew members and ensures 

adherence to data collection and processing protocols, including data verification and 

documentation. The crew leader also works with the project manager and data manager on 

water quality data management in the office. 

Project Manager 

(Network Aquatic 

Ecologist)

The project manager is responsible for all project operations and results, and may also

participate in field operations. The project manager ensures that data management activities 

are conducted according to established procedures and is responsible for data validation and 

certification: approving the data content, quality, and documentation, as well as making 

decisions about data sensitivity and distribution. The project manager is responsible for 

evaluating project data at specified intervals, analyzing data for trends, and following reporting 

requirements.

Resource 

Specialist 

The water resource specialist, who may also serve as a crew leader, works closely with the 

project manager in all aspects of data management. The water resource specialist collects field 

data, enters field and laboratory data, verifies data, and validates data.

Network Data 

Manager 

The network data manager, together with the project manager, ensures that water quality 

monitoring data are organized, useful, compliant, available, and safe. The network data 

manager provides the most current version of NPSTORET and works with project personnel to 

ensure Network water quality data are received by WRD. The network data manager oversees

activities related to training, user support, quality assurance, documentation, backups, 

archiving, and data maintenance and distribution. 
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Water Quality Monitoring Protocol for Inland Lakes, Version 1.1 3

8.2 NPSTORET Database

Water quality data are managed according to guidelines from the NPS Water Resources Division. In 

accordance with these guidelines, the desktop database application NPSTORET will be used to enter, 

store, document, and transfer discrete (or snapshot) water quality data. The GLKN oversees the use 

of NPSTORET per the Network’s water quality monitoring protocols and ensures that data are 

transferred at least annually to the NPS Water Resource Division for upload to the EPA STORET 

database/Water Quality Exchange (WQX) (Figure 1).

STORET is an interagency water quality database developed and supported by the Environmental 

Protection Agency (EPA) to house local, state, and federal water quality data collected in support of 

managing the nation’s water resources under the Clean Water Act. NPS Director’s Order 77 indicates 

that the NPS should archive water quality data in STORET, and the NPS WRD mandates that any 

data collected as part of a WRD-funded project get archived in STORET. The NPS uses STORET as 

a repository of physical, chemical, biological, and other monitoring data collected in and around 

national park units by park staff, contractors, and cooperators. The NPS operates its own Servicewide copy of STORET and makes periodic uploads to the EPA STORET National Data Warehouse 

so that data collected by and for parks will be accessible to the public.

Figure 1. Schematic of data flow to the STORET database: water quality data are transferred from the 

Network to the national master database and ultimately to the master database. Public access to 

STORET is available via an online clearinghouse.

8.2.1 Database Design

The database design for NPSTORET is described in its associated documentation. Maintenance and 

documentation of NPStoret is performed by NPS WRD. Because it must be compatible with the 

Oracle-based EPA STORET, NPSTORET is a complex MS Access implementation. The latest 

version of NPSTORET can be found at: http://nrdata.nps.gov/programs/water/npstoret/. 

The Great Lakes Network will maintain one master copy of NPSTORET for each park at the 

Ashland office on a central server. This is the only copy of NPSTORET that can be used to export 

data to other locations (i.e., WRD and GLKN’s SQL Server). Additional copies of NPSTORET can 

be used by GLKN personnel stationed at parks, but they can only be used as a conduit for data entry 

and the importation of data to GLKN’s master version of NPSTORET. For analysis, the data from 

the master copy of NPSTORET, that has passed all QA/QC procedures, must be used.

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Water Quality Monitoring Protocol for Inland Lakes, Version 1.1 5

8.3 Aquarius Database 

Guidelines for managing time series data are being developed by NPS Water Resources and

Inventory and Monitoring (IMD) divisions. For water quality monitoring personnel, data collection, 

management, and stewardship responsibilities for time series data are the same as those for discrete 

or snapshot data (Table 1). At the time of this latest SOP revision (Version 1.2), WRD and IMD are 

in the process of creating SOPs to use Aquarius tools to import, QA/QC, and validate and certify 

continuous data. A general data flow schematic for continuously collected data is shown in Figure 2.

Figure 2. Schematic of data flow to the Aquarius database: water quality data from data loggers are 

transferred from the Network to the WRD-hosted version of Aquarius. Public access to this data is 

provided through the Aquarius WebPortal.

8.4 Data Management Procedures

8.4.1 Data Collection

Data values are measured, observed, or estimated according the GLKN inland lakes water quality 

monitoring protocol at various monitoring locations (sample sites) and recorded on field forms (see 

SOP #6, Field Measurements and Water Sample Collection). Crew members are responsible for 

legible, accurate entries on field forms and in log books, including the calibration log. As a first step 

to verify data, crew members will check and double-check the recorded values on the day of data 

collection. 

Discrete data collected with a multiparameter sonde are stored directly on a datalogger attached to 

the sonde and recorded on the field sheets at the time of sampling. The hard copy of the data serves 

as a back-up should something happen to the electronic data. 

Continuous data collected by temperature sensors through use of thermal arrays are stored directly on 

the sensors, downloaded to a data transfer device (e.g., a Hobo Shuttle), and transferred to a 

computer. Hard copies of continuous temperature data do not exist, although electronic data are 

stored in multiple locations and backed-up daily.
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Water Quality Monitoring Protocol for Inland Lakes, Version 1.1 6

Digital images of sample sites are acquired during site establishment and periodically as sites change 

(SOP #6). Crew members are responsible for proper settings and use of digital camera equipment and 

should refer to the user manual for details specific to the camera. 

GPS coordinates are stored as waypoints if using a recreational GPS unit, or as features if using a 

mapping-grade unit with a data dictionary, and recorded on the field sheets. When possible, the GPS 

data will be differentially corrected to improve the accuracy of location coordinates. See SOP #3 for 

more information on using a GPS unit.

Water samples are collected, labeled, and packaged for laboratory analysis according to SOPs #6 and 

#7. Identification numbers on sample containers, chain of custody forms, laboratory reports, and on 

the field data collection form facilitate management of laboratory results.

8.4.2 Data Entry, Verification, and Documentation

Requirements for data entry into NPSTORET are detailed in the documentation for users. We present 

a summary of data entry below, and refer staff to the most recent NPSTORET documentation for the 

specifics.

On a regular schedule approved by the project manager and data manager, the crew leader gathers the 

field data collection forms and verifies the completeness, accuracy, and legibility of each form. 

Following each round of sampling, the crew leader will make a photocopy of each field form and 

ensure each copy is legible; the copy will be placed in the office binder kept at the park, and the 

original will be sent to the project manager for archival in the GLKN office. Additional photocopies 

will be made as needed. Upon receiving the original data sheets, the project manager will proofread 

the datasheets, making sure that they have been filled out completely. All data sheets should have 

been reviewed for completeness while in the field, however some deficiencies in data recording may 

not be identified until all data sheets have been reviewed as a group. 

Project staff enters site establishment data in the NPSTORET Station Entry Template as soon as 

possible following the initial site visit to each sample location. This prompt action is a good data 

management practice and an NPSTORET requirement that enables parameter data entry. Linking 

digital images of sample sites to stations in NPSTORET is required as part of this data entry process.

File size for digital images linked to stations in NPSTORET should normally be at least 100kb and 

less than 300kb. Project staff will reduce the size of image files larger than 300kb and copy images to 

a file folder named “images” for the appropriate park. Original ‘raw’ images can be stored in the 

Images folder (see Folder and File Organization below) if project staff determine it is important to 

keep higher resolution images.

Electronic data from the multiparameter sonde are downloaded from the datalogger to a computer in 

an MS Excel spreadsheet or text file at the end of each sampling day or as soon as feasible after 

sampling, and verified for accuracy. Likewise, at the end of each sampling day or as soon as feasible 

after sampling, all digital images will be downloaded to a computer and labeled with date, location, 

and subject matter. Import data from the MS Excel spreadsheet into NPSTORET following the 

guidelines.
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Water Quality Monitoring Protocol for Inland Lakes, Version 1.1 7

Any notes taken in the field regarding collection of data with the sonde are transcribed to 

NPSTORET in a field for comments and notes. Results of laboratory analyses typically are sent to 

the project manager in a MS Excel spreadsheet and on hard copy forms. The project manager will 

verify both sets of data and follow-up with the contract laboratory if any discrepancies are noted or 

any questionable results are reported (see SOP #12 on QA/QC for more details). Project staff will 

import the verified data into NPSTORET. 

Non-electronic field data recorded on hard copy data sheets are manually-entered into a MS Excel 

spreadsheet. At the end of the season when all data are entered, the project leader will perform or 

coordinate a check of 100% of this manually-entered data prior to import into NPSTORET.

A random check of 3% of all electronically transferred data (GPS, multiprobe, and laboratory data) is 

also performed after it is imported into NPSTORET, to ensure no problems occurred during data 

transfer. For electronically transferred or manually-entered data, the project leader resolves errors 

according to established procedures. See SOP #12 for additional QA/QC details.

Data verification starts with the QA/QC steps that are detailed in SOP #12. As data are entered into 

NPSTORET, either by keyboard or using an import routine, a suite of QA/QC procedures exist that 

compare the entered data with expected formats and accepted data value ranges or domains. If the 

entered data do not pass a form-based QA/QC test, NPSTORET prompts the user to make 

corrections and re-enter the data. For most of the form-based tests, the NPSTORET database will not 

accept out-of-bounds data, and correction is mandatory; for some range tests, out-of bounds data are 

accepted after a user prompt, but are flagged accordingly. The QA/QC procedures on imported data 

perform similar tests, but exceptions that do not pass QA/QC are presented to the user and must be 

reconciled before the record or dataset can be accepted by NPSTORET.

Additional comparison tests will be run on data in NPSTORET to flag records that are outside the 

expected rate of change for a parameter based on previous records for that parameter. These suspect 

data points are reviewed by an expert user and can be corrected, flagged, or excluded from the 

dataset.

As mentioned above, NPSTORET performs numerous QA/QC checks on the data as they are entered 

and stored. Additionally, once the data are transferred to WRD, more QA/QC procedures are 

performed. The Network’s water quality data records are regarded as being in provisional status until 

they are returned to GLKN from WRD, or are accepted by WRD without changes after the final 

QA/QC steps. Each individual record in the water quality dataset always has one, and only one, 

status flag indicating its status as provisional or final. Finalized data can still be edited and changed if 

errors are discovered after review in reporting and analysis, but the status of those records reverts to 

provisional and they must be resubmitted to the master STORET version at WRD and returned 

before they can be reassigned as finalized data records.

A user’s identification is assigned to each aspect of data handling, from collection through the final 

steps of QA/QC. On data sheets, the identity of the data collector(s) is recorded and is transcribed 

into the data entry forms in NPSTORET. Additionally, NPSTORET records the user name (login) for 
Standard Operating Procedure #8: Data Entry and Management, Version 1.2 September 2015

Water Quality Monitoring Protocol for Inland Lakes, Version 1.1 8

every table entry or modification. Only qualified users who have been trained and given edit 

permissions are allowed to edit data in NPSTORET. These procedures protect the integrity of the 

data and allow the history of each data record to be traced.

The Aquarius database software used for continuous water quality data has built-in QA/QC tools 

specifically tailored for time series data. These features tools are particularly useful for dealing with 

data gaps, overlaps and out of range values, and will be utilized as part of the QA/QC process used 

for continuous data imported into Aquarius. At the time of this SOP development WRD and IMD are 

working cooperatively to create SOPs for QA/QC and data certification (see next section) for the 

Aquarius tool. GLKN will adopt the SOP’s for these tasks when they are completed.

Executive Order 12906, mandates federal agencies to “...document all new geospatial data it collects 

or produces, either directly or indirectly...” using the Federal Geographic Data Committee Content 

Standard for Digital Geospatial Metadata. Water quality monitoring meets the definition of 

geospatial data and, thus, GLKN is responsible for documenting all public datasets using metadata 

that meets that standard. NPSTORET and Aquarius require and store a great deal of metadata at the 

record and project level. Metadata will be developed, using NPSTORET and Aquarius as primary 

sources that meet the federal standard. Consult the GLKN Data Management plan (Hart and Gafvert 

2005) for additional details about metadata procedures and requirements.

8.4.3 Data Validation and Certification

Prior to distributing the data for any type of use, the project manager or other appropriate water 

resource specialist validates the NPSTORET database content in the master water quality data file 

according to procedures in the Quality Control and Quality Assurance SOP. The integrity of each 

master data file must be preserved during the validation process in cases where the person 

performing data validation does not have direct access to the master water quality data file. 

Validation is performed at least once each year after data collection and entry are complete and 

before data are submitted to the NPS Water Resource Division, usually by the end of each calendar 

year. If this annual validation does not meet scheduled reporting requirements of the Network, then 

the project manager may coordinate more frequent validation to meet needs, or reports can include a 

statement explaining that results are based on data that have not been validated. The statement should 

include an explanation of what significance this has for using preliminary data. 

Laboratory results must be imported and validated in NPSTORET as soon as possible following 

receipt of the results. The project manager coordinates receiving and entering data with project staff 

and then performs or coordinates the validation of lab results.

Data certification will be performed annually according to policies in the Network Data Management 

Plan, Hart and Gafvert (2005). The certification process will take place before the finalization of the 

annual NPStoret submission to WRD, and the release of data in Aquarius for public viewing.

8.4.4 Data Analysis and Reporting 

Project staff will follow the procedures for data analysis in SOP #9 and data reporting in SOP #10. 

Data summary statistics will typically include, but not be limited to: 
Standard Operating Procedure #8: Data Entry and Management, Version 1.2 September 2015

Water Quality Monitoring Protocol for Inland Lakes, Version 1.1 9

 Mean 

 Median 

 Standard deviation 

 Minimum 

 Maximum 

 Count 

 Percentiles (10, 25, 75, and 90th percentiles) 

 Standard error 

 Variance 

 Range 

 Mode 

 Sum 

 Kurtosis 

 Skew 

Some of these statistics are available through NPSTORET’s query function and others can be derived 

from NPSTORET outputs. NPSTORET provides an export for any portion of the data in tabular 

format for use with the Data Analysis Toolpak. 

Aquarius has primarily been a tool used by hydrologists to compile stage and discharge data for 

flowing waters. It can generate the same data summary statistics as NPSTORET as well as a few 

others, such as reports by location showing minimum, maximum, mean, and count number of data 

points per time series. Aquarius can also be used to calculate means over several time scales 

(monthly, daily, or hourly) and to generate time series graphs. In addition to these and other analysis 

procedures, data can also be exported from Aquarius to flat file formats for use by other graphing or 

statistical software, such as R or SigmaPlot.

8.4.5 Data Folder and File Organization

All data from this water quality protocol should be stored, at the earliest possibility, on the GLKN 

central server. A diagram showing the folder structure is shown in Figure 3.

Files should be named in accordance with the file-naming standards in the GLKN Data Management 

plan (see section 6.4 of Hart and Gafvert 2005). Files have a ‘GLKN’ prefix, a descriptive element, 

and finish with a date element. For example, ‘GLKN_ISRO_Field_Data_20070605.doc’ contains 

field data from Isle Royale National Park on June 5, 2007. Do not use spaces in file names.

8.4.6 Data Archival and Distribution Procedures

Data archiving serves two primary functions: it provides a source to retrieve a copy of any data set 

when the primary dataset is lost or destroyed, and it provides a data record that is an essential part of 

the QA/QC process. Original data will be archived at the Network office. Original data for printed 

forms are either the physical datasheets or exact and complete digital copies of the forms that capture 

all entries and notations. The unedited files are the original data for digital data.
Standard Operating Procedure #8: Data Entry and Management, Version 1.2 September 2015

Water Quality Monitoring Protocol for Inland Lakes, Version 1.1 10

Figure 3. Great Lakes Network folder structure for information related to the protocol for monitoring water 

quality of inland lakes. The Images, Lab_Data, and Maps folders also have subfolders for each park. Data 

are organized in subfolders by year within each park folder.

All digital data have a duplicate file created at the earliest opportunity. At least two complete copies 

of any water quality dataset are required by WRD, including digital replicas (scanned versions), if 

they are created, of hard copy data sheets. Digital field data that are entered directly into a field 

computer or collected from a data logger must be backed up to a second medium at the earliest 
Standard Operating Procedure #8: Data Entry and Management, Version 1.2 September 2015

Water Quality Monitoring Protocol for Inland Lakes, Version 1.1 11

possibility. The data files on field computers and loggers must not be erased until the integrity of 

these data files are verified on the duplicate storage medium. The removal of original data files from 

a field computer or logger must be a balance of keeping memory available for new data collection 

and a need to keep data in their most original form for as long as possible. Field files should only be 

deleted when memory space is needed for new data collection.

The Network’s master version of NPSTORET and the SQL Server geodatabase are maintained on a 

central server in the Ashland Office that is backed up daily, and backed up off-site weekly. Complete 

details of the GLKN Server archiving procedure are found the Infrastructure chapter of GLKN’s 

Data Management Plan (Hart and Gafvert 2005); the general strategy for data archiving is also 

described in this plan and its appendices. 

Raw time series data (.hobo files and flat files created from the .hobo files) are stored on the central 

server at GLKN, which is backed up daily, and backed up off-site weekly. The version of Aquarius 

that GLKN uses is housed on a server at WRD in Ft. Collins, Colorado. For the time series data to be 

stored and used in Aquarius, the flat file versions are uploaded to the SQL server using the Aquarius 

Springboard. All Aquarius data is uploaded to this server at least annually by GLKN staff or 

cooperators. WRD is currently working on a public-facing web application where this time series 

data will be available, once the data is officially certified.

GLKN has a number of different avenues for data distribution depending on the audience served and 

the degree of analysis and customization needed by the end-user (see GLKN’s data management 

plan, Hart and Gafvert [2005], for more details). The NPS IMD Integrated Resource Management 

Applications (IRMA) web portal is the primary tool that provides interactive access to GLKN data. 

Some GLKN water quality datasets are available through links to the IRMA portal on the GLKN 

webpages. However, due to the complexity of the NPSTORET database, providing the data in that 

format will not meet the needs of those users unfamiliar with that application. Network (GLKN) 

versions of NPSTORET are used to update a master version of STORET maintained by NPS WRD. 

The WRD master copy of STORET data is used to regularly update the EPA database that provides 

on-line access to GLKN water quality data through the EPA WQX and forthcoming Water Quality 

Portal. NPS IMD is also developing a web map portal to monitoring data tentatively called the NPS 

Data Visualizer. This will allow a user to spatial query data, including monitoring data, and retrieve

the scope of interest. The pathway for this tool is via a Common View Data Template that will allow 

data in NPStoret to be read by the database server supplying the Data Visualizer.

Data distribution will primarily occur through the EPA STORET portal, the NPS Data Store, 

Aquarius WebPortal and the NPS Data Visualizer. These tools are described previously in this 

document. The USGS and EPA are developing the Water Quality Portal (www.waterqualitydata.us). 

This will probably become the primary tool for reaching data stored in EPA STORET/WQX. For 

many users, the EPA tools will be the easiest way to retrieve subsets of GLKN inland lakes water 

quality data.

In cases where specific data are requested that are unavailable through the public distribution 

methods outlined above, the project manager or appropriate water resource specialist will respond 
Standard Operating Procedure #8: Data Entry and Management, Version 1.2 September 2015

Water Quality Monitoring Protocol for Inland Lakes, Version 1.1 12

based on the nature of each request and the state of the data, for example, whether or not the data are 

fully qualified and documented to meet the needs of the requestor.
Standard Operating Procedure #8: Data Entry and Management, Version 1.2 September 2015

Water Quality Monitoring Protocol for Inland Lakes, Version 1.1 13

8.5 Literature Cited

Elias, J. E., R. Axler, and E. Ruzycki. 2008. Water quality monitoring protocol for inland lakes, 

version 1.0. National Park Service, Great Lakes Network, Ashland, Wisconsin. Natural Resource 

Technical Report NPS/MWR/GLKN/NRTR—2008/109. National Park Service, Fort Collins, 

Colorado.

Hart, M., and U. Gafvert (editors). 2006. Data management plan: Great Lakes Inventory and 

Monitoring Network. Great Lakes Inventory and Monitoring Network Report GLKN/2006/20. 

National Park Service, Ashland, Wisconsin. Available at 

http://science.nature.nps.gov/im/units/glkn/assets/docs/GLKN_SD8_Data_Management_Plan.pdf

NPS (National Park Service). 1999. Natural Resource Challenge. Available at

www.nature.nps.gov/challenge/index.cfm (accessed 26 January 2007).

Standard Operating Procedure #9: Data Analysis

Version 1.1

In Water Quality Monitoring Protocol for Inland Lakes

Prepared by

Joan Elias and David VanderMeulen*

National Park Service

Great Lakes Inventory and Monitoring Network 

2800 Lake Shore Drive East

Ashland, Wisconsin 54806

* Contact author: david_vandermeulen@nps.gov

September 2015

Suggested citation: 

Elias, J. E., and D. VanderMeulen. 2015. Standard operating procedure #9: Data analysis, version 

1.1. In J. E. Elias, R. Axler, E. Ruzycki, and D. VanderMeulen. 2015. Water quality monitoring 

protocol for inland lakes: Great Lakes Inventory and Monitoring Network, version 1.1. Natural 

Resource Report NPS/GLKN/NRR—2015/1027. National Park Service, Fort Collins, Colorado.

Standard Operating Procedure #9: Data Analysis, Version 1.1 September 2015

Water Quality Monitoring Protocol for Inland Lakes, Version 1.1 i

SOP9 – Contents

Page

Revision History Log............................................................................................................................iii

Acknowledgements...............................................................................................................................iii

9.0 Introduction......................................................................................................................................1

9.1 Temporal and Spatial Domains........................................................................................................1

9.2 Initial QA/QC Checks for Outliers in Data......................................................................................3

9.3 Annual Data Summaries..................................................................................................................3

9.4 Analyses of Long-Term Trends.......................................................................................................3

9.5 Literature Cited ................................................................................................................................7

Standard Operating Procedure #9: Data Analysis, Version 1.1 September 2015

Water Quality Monitoring Protocol for Inland Lakes, Version 1.1 iii

Revision History Log

The following table lists all edits and amendments to this document since the original publication 

date. Information entered in the log must be complete and concise. Users of this standard operating 

procedure will promptly notify the project manager and/or the Great Lakes Network (GLKN) data 

manager about recommended and required changes. The project manager must review and 

incorporate all changes, complete the revision history log, and change the date and version number 

on the title page and in the header of the document file. For complete instructions, please refer to 

SOP #13: Revising the Protocol. 

Revision History Log:

Previous 

Version 

#

Revision 

Date

Author (with 

title and 

affiliation)

Location in Document and 

Concise Description of 

Revision Reason for Change

New 

Version 

#

1.0 5/01/2015 David 

VanderMeulen, 

GLKN

Updated the NPS contact author, 

distinguished discrete from 

continuous data, fixed a handful 

of grammatical errors throughout

To clarify and update 

SOP based on changes 

that have occurred 

since Version 1.0 was 

published in 2008

1.1

Add rows as needed for each change or set of changes tied to an updated version number

Acknowledgements

I would like to acknowledge Brenda Moraska Lafrancois and Richard Axler for helpful input and 

discussions relative to analysis of water quality data and general limnological principles. Thanks also 

to Sue Magdalene and Erik Beever for providing verbiage in earlier drafts of this document.

Standard Operating Procedure #9: Data Analysis, Version 1.1 September 2015

Water Quality Monitoring Protocol for Inland Lakes, Version 1.1 1

9.0 Introduction

Data analysis is the process by which measurements of the environment are interpreted meaningfully. 

It begins with evaluations of data after the data have been collected and entered into an electronic file 

or database, and have undergone a check of the data entry to ensure quality. Data analysis includes 

quality assurance/quality control (QA/QC) checks for statistical outliers prior to data summarization, 

may include exploratory data analysis, and concludes with analyses that lead to summary and 

interpretations of the data. 

Well-conceived and -developed monitoring strategies have clear connections between questions of 

interest, appropriate sampling designs, and resulting analytical approaches (Noon 2003).

Accordingly, the utility and robustness of the Great Lakes Network’s (GLKN) analyses for 

monitoring water quality are based on ecologically meaningful questions and relationships, which 

prescribe the monitoring design, which in turn prescribes an analytical approach. Increasingly, 

biometricians are advocating that ecologists seek to elucidate and quantify ecologically important 

phenomena, rather than exclusively pursue statistical significance (Yoccoz 1991, Johnson 1999, 

Anderson et al. 2001). Efforts of GLKN to monitor water quality seek to provide a quantitative 

understanding of the effect size (e.g., temporal trend, difference in indicator values among predefined strata) as well as the repeatability of that result (i.e., a measure of precision or uncertainty 

associated with the estimate). We are striving to address directed monitoring questions that reflect 

our prior knowledge of the system and may provide useful information for management decisions, 

rather than test myriad hypotheses about ecosystem change. 

In addition to quantitatively describing the status and temporal trends of water quality indicators, a 

secondary goal is to begin to understand the dynamics and drivers of our indicators, following our 

conceptual models (Gucciardo et al. 2004). Although not every trend is a product of local 

management action, tests of association that address the underlying ‘why’ questions behind the 

‘what’ questions in trend analysis will be explored for at least a subset of our metrics of water 

quality. Although the validity of these associations can be strengthened with focused research, these 

types of questions increase the likelihood that our monitoring can lead to an early correction of trend 

before the cascading ramifications become irreversible.

9.1 Temporal and Spatial Domains 

As described in the protocol narrative for monitoring water quality in GLKN inland lakes (Elias et al. 

2008), we have defined our temporal domain for discretely collected data as daytime periods during 

the ice-free months, ideally, when lakes are thermally stratified. Selected lakes will be sampled three 

times annually, at the same location within each lake. We selected lakes using several criteria, 

including lake type based on ordinations of past chemistry data to determine groupings of similar 

lakes within a given park, amount of past data, spatial balance within each park, and particular 

interest by park staff. We also selected lakes to span various gradients within a park, such as 
Standard Operating Procedure #9: Data Analysis, Version 1.1 September 2015

Water Quality Monitoring Protocol for Inland Lakes, Version 1.1 2

gradients across intensity of visitor use, surface area, maximum depth, and watershed area. 

Continuous water temperature data will be collected from a subset of inland lakes at Isle Royale and 

Voyageurs National Parks, and Pictured Rocks and Sleeping Bear Dunes National Lakeshores, which 

are the four parks in the Great Lakes I&M Network that contain a significant number of inland lakes.

Both discrete and continuous monitoring of lakes will take place at the deepest location of a given 

lake unless a question specific to the littoral zone is being addressed. It has been shown that spatial 

variation within a basin is small relative to temporal variation (Hanna and Peters 1991, Marshall and 

Peters 1989) for highly variable parameters such as chlorophyll and phosphorus. Therefore, for 

discrete monitoring we will maximize the number of sampling visits per lake, within budget 

constraints, and sample at a single location (the deepest part of the basin). For continuous 

monitoring, autonomous temperature sensors record water temperature from a lake’s surface to the 

bottom at discrete intervals, once per hour, year round, with site visits typically coincident with 

discrete monitoring visits at the beginning and end of a field season. 
Standard Operating Procedure #9: Data Analysis, Version 1.1 September 2015

Water Quality Monitoring Protocol for Inland Lakes, Version 1.1 3

9.2 Initial QA/QC Checks for Outliers in Data 

All water quality data undergo several quality assurance/quality control (QA/QC) procedures (e.g., 

duplicate sampling, data-entry filters, removal of logically inconsistent entries; see SOP #8 for data 

management details) to ensure that the data accurately represent the natural environment at the time 

of sampling. In addition to these procedures, several analytical and data sorting techniques (e.g., 

scatter plots, box-and-whisker plots, stem-and-leaf plots, sorting values of a given indicator in 

ascending or descending order, “COUNTIF” statements in Excel) are available to identify potentially 

erroneous values and statistical outliers. During this process, data points that do not meet limitations 

for precision or bias may be flagged or eliminated from the database. Some statistical measures, such 

as population mean, are sensitive to extreme atypical values, or outliers. Therefore, to reveal the 

central tendency of the population, the project manager may elect to remove outliers from the data 

pool. Such removals should be performed with great caution, and only when it is clear that the outlier 

truly did not reflect system properties (e.g., the outlier resulted from instrument error, transcriptional 

error, contamination of the sample). 

9.3 Annual Data Summaries 

Brief characterizations of the data from each lake, each park, and the Network as a whole will be 

performed each year, after all QA/QC procedures have been completed. For each lake sampled, and 

for each parameter measured, descriptive statistics may include mean, median, maximum and 

minimum values, as well as skew, kurtosis, and measures of variability, when appropriate (e.g., 

coefficient of variation, standard error, variance), and provided as hard copy or web based summary 

reports, with the primary audience being the parks

Given the relevant legislation (e.g., Clean Water Act of 1972), it may be of interest to individual NPS 

units and to other entities to assess the proportion of measurements during a time period or across a 

domain (at a single point in time) that exceed pre-determined thresholds, such as State water quality 

standards or ecoregional nutrient criteria. As with nearly all percentage data, arcsine transformations 

must be performed on those data before statistical analyses can be conducted (Sokal and Rohlf 1995).

9.4 Analyses of Long-Term Trends 

In addition to these descriptive statistics, analytical approaches may also include estimation of 

interannual change, graphic approaches (e.g., comparison of mean and variability of a parameter in 

the current year versus during past years), and occasionally qualitative analysis (Guthery et al. 2001), 

as well as modeling, correlational analyses, and various parametric and nonparametric analyses. 

Results of such analyses will be distributed via synthesis reports and/or articles in peer-reviewed 

journals. 
Standard Operating Procedure #9: Data Analysis, Version 1.1 September 2015

Water Quality Monitoring Protocol for Inland Lakes, Version 1.1 4

Because lakes were not selected randomly, we will not make inferences about trends in lakes other 

than those we sample. We will analyze data from each lake independently of all other lakes. All lakes 

sampled within a park may be grouped for analytical comparison with lakes sampled in another park. 

Whenever lakes are pooled for analysis, we will ensure inferences are not made beyond those lakes 

that were sampled. Characteristics of the lakes that are known or suspected to affect water quality 

(e.g., lake size, maximum depth, underlying geology, watershed characteristics) can be included as 

covariates.

9.4.1 Recommended Methods for Long-Term Trend Analysis

Synthesis reports will include more intensive analyses of change after at least three years of sampling 

in a given lake has occurred. In addition to repeated-measures, time-series, regression, and nonparametric equivalents of various methods (such as regression, paired-t tests, and ANOVA), 

monitoring data may also be evaluated through nonparametric trend tests (e.g., Mann-Kendall or 

Seasonal Kendall), Monte Carlo simulation analyses, Bayesian analyses, and comparisons of period 

means. For the latter-most approach, one is often interested in comparing values before and after an 

important event (e.g., change in management policy, remarkable anthropogenic disturbance, natural 

catastrophe, drought), and considers years within each of the two periods as replicates. We may also 

examine trends for breakpoints, or changes in slope, which may indicate the timing of an important 

event, and hence a potential cause. Trends in parameters that are analyzed with respect to biotic and 

abiotic covariates will be included in the synthesis reports, although cause-effect relationships may 

be investigated more thoroughly by NPS partners and collaborators. 

In addition to analyzing each variable separately, water quality variables could be analyzed 

collectively through multivariate ordinations (e.g., nonmetric multi-dimensional scaling) of resource 

conditions through time, following West and Yorks (2002). This approach effectively integrates 

information across many indicators, and can suggest whether individual stations are all moving in the 

same direction in multidimensional ordination space. Furthermore, joint plots can be overlaid on the 

ordination, and can suggest which variables correlate most strongly to the direction of changes. 

Similarly, if specific comparisons are desired across a suite of uncorrelated variables, two or more 

pre-defined groups of samples could be compared using MANOVA or NPMANOVA, depending on 

whether parametric assumptions are met.

9.4.2 Approaches to Analyze Frequently-Collected Data

In contrast to many other parameters that the Network is monitoring, discrete water quality 

measurements are collected several times per year. Not only does the long-term nature of this data set 

allow for robust retrospective analyses of trend, but the multiple sampling sessions within each year 

allow for various analytical approaches to analyze long-term trends. For example, if the goal is to 

monitor trend in the average value of a particular water-quality parameter, then all measurements 

collected within the year (or during the ice-free season) at each sampling location would be 

considered temporal subsamples and averaged. Trend analysis (using repeated-measures, time-series, 

or other regression analyses) would thus be performed simply on the annual means at each sampling 

location. This approach seems particularly viable for parameters that do not exhibit strong intraannual variability (e.g., pH). However, this approach may be vulnerable to imprecision or bias if a 
Standard Operating Procedure #9: Data Analysis, Version 1.1 September 2015

Water Quality Monitoring Protocol for Inland Lakes, Version 1.1 5

parameter exhibits significant, predictable variability in its value throughout the year and data are not 

collected (due to equipment failure or logistical constraint) at a high number of intended sampling 

occasions.

Alternatively, if a particular parameter is known to exhibit significant intra-annual variability (e.g., 

chlorophyll-a), samples within the year can be partitioned into one of several periods (ideally, 

defined by relevant phenological or biological phenomena). Thus, for example, if interannual trends 

in nutrient concentrations during algal blooms are of interest, the temporal domain can be 

accordingly defined, and all samples within that window averaged within each year and the means

analyzed for trend across years. Finally, if there is a strong desire to incorporate intra-annual 

variability into interannual trend analyses, data within each year can be analyzed through a 

smoothing algorithm, and interannual variability is thus analyzed on the smoothed data. However, it 

may be the case that process variation is larger than the sampling variability (Burnham et al. 1987). 

9.4.3 Duplicate Sampling

To ensure that understanding of water quality trends within lakes of the GLKN is not confounded by 

biased results, for discrete monitoring we will collect duplicate samples and field measurements at 

the rate of approximately once every 10 samples. We will assess the relative percent difference 

between duplicate samples or measurements and flag data that do not meet the QA/QC guidelines 

detailed in SOP #12. Those data that do not meet the QA/QC stipulations may or may not be used in 

analyses, on a case by case basis. For example, parameters measured at low concentrations (e.g., less 

than five times the method detection limit) may be accepted, and both duplicates used in analysis. If 

duplicate samples meet the QA/QC guidelines, we will use the mean value of the duplicate 

measurements in data analyses. Explanations of how duplicates are handled in data analyses will be 

included in reports. 

9.4.4 Other Analytical Considerations

For trend analyses performed using regression, trend will be investigated using a linear relationship. 

If analyses suggest a non-linear temporal pattern, serial autocorrelation, or lagged response to 

stressors, appropriate analytical modifications will occur. When discussing the desire to be able to 

detect a trend of 20%, for example, it must be stated during what time period that level of change is 

to be detected. This allows one to calculate the minimum level of change that is important to detect 

between successive sampling periods. A 20% change occurring over 1 year is obviously much 

different than that same level of change (20%) occurring over 10 years (i.e., an average change of 

1.84% per year).

Adopting the philosophies of the precautionary principle (United Nations 1992) and the safe 

minimum standard of conservation (Ciriacy-Wantrup 1952, Berrens et al. 1998), the GLKN 

monitoring program seeks to identify potential natural resource problems early, before deleterious or 

irreversible ecosystem changes occur (e.g., crossing of ecological thresholds; Laycock 1991, van de 

Koppel et al. 1997, Laurance and Williamson 2001). Consequently, for most analyses that use the 

null hypothesis of no change through time, we will adopt α = 0.10. Furthermore, for parameters that 

exhibit particularly high variability, magnitudes of change that seem biologically meaningful 
Standard Operating Procedure #9: Data Analysis, Version 1.1 September 2015

Water Quality Monitoring Protocol for Inland Lakes, Version 1.1 6

(Johnson 1999) yet have 0.10 < α < 0.20 may merit more intensive or extensive monitoring or 

experimental study.

If water quality monitoring tracks a relatively large suite of variables, Bonferroni or modified 

Bonferroni corrections (e.g., Hohm’s method) may be performed, to maintain the ‘family-wise’ alpha 

at 0.10. Roback and Askins (2005) argue that if the main goal is simply initial screening for 

conservation problems or generation of hypotheses to be tested further, but not detection of real 

differences or trends, then alpha can be left at its standard comparison-wise significance level, to 

avoid Type II errors.

When the dataset contains non-detects, we will follow Helsel (2005) in conducting statistical 

analyses. Several methods exist for handling non-detects, each with advantages and drawbacks. Early 

in our program we will likely use a substitution method, where a value between zero and the 

detection limit will be substituted for the non-detect. The main drawback of this method is that 

estimates of the true variability are not possible. When the program is more mature and we have 

adequate data to determine the distribution of data, we will likely use maximum likelihood 

estimation, which works well for large sample sizes. Other methods, such as “regression on order 

statistics” and the non-parametric Kaplan-Meier method will be considered, and in consultation with 

a statistician, the most appropriate method for the data will be employed.
Standard Operating Procedure #9: Data Analysis, Version 1.1 September 2015

Water Quality Monitoring Protocol for Inland Lakes, Version 1.1 7

9.5 Literature Cited

Anderson, D. R., K. P. Burnham, W. R. Gould, and S. Cherry. 2001. Concerns about finding effects 

that are actually spurious. Wildlife Society Bulletin 29:311–316. 

Berrens R. P., D. S. Brookshire, M. McKee, and C. Schmidt. 1998. Implementing the safe minimum 

standard approach: Two case studies from the U.S. Endangered Species Act. Land Economics 

74:147–161.

Burnham, K. P., D. R. Anderson, G. C. White, C. Brownie, and K. H. Pollock. 1987. Design and 

analysis methods for fish survival experiments based on release-recapture. American Fisheries 

Society Monograph 5:1–437.

Ciriacy-Wantrup S. V. 1952. Resource Conservation: Economics and Policies. University of 

California Press, Berkeley, California. 

Elias, J. E, R. Axler, and E. Ruzycki. 2008. Water quality monitoring protocol narrative for inland 

lakes, version 1.0. National Park Service, Great Lakes Inventory and Monitoring Network.

Natural Resource Technical Report NPS/MWR/GLKN/NRTR—2008/109. National Park 

Service, Fort Collins, Colorado.

Gucciardo, S., B. Route, and J. Elias (editors). 2004. Conceptual ecosystem models for long-term 

monitoring in the Great Lakes Network. Great Lakes Network Technical Report GLKN/2004/04.

National Park Service, Ashland, Wisconsin.

Guthery, F. S., J. J. Lusk, and M. J. Peterson. 2001. The fall of the null hypothesis: Liabilities and 

opportunities. Journal of Wildlife Management 65:379–384.

Hanna, M., and R. H. Peters. 1991. Effect of sampling protocol on estimates of phosphorus and 

chlorophyll concentrations in lakes of low to moderate trophic status. Canadian Journal of 

Fisheries and Aquatic Science 48:1979–1986.

Helsel, D. R. 2005. Nondetects and Data Analysis: Statistics for Censored Environmental Data. John 

Wiley and Sons, Inc., New York.

Johnson, D. H. 1999. The insignificance of significance testing. Journal of Wildlife Management 

63:763–772.

Laurance, W. F., and G. B. Williamson. 2001. Positive feedbacks among forest fragmentation, 

drought, and climate change in the Amazon. Conservation Biology 15:1529–1535. 

Laycock, W. A. 1991. Stable states and thresholds of range condition on North American rangelands: 

A viewpoint. Journal of Range Management 44:427–433.

Marshall, C. T., and R. H. Peters. 1989. General patterns in the seasonal development of chlorophylla for temperate lakes. Limnology and Oceanography 34:856–867.
Standard Operating Procedure #9: Data Analysis, Version 1.1 September 2015

Water Quality Monitoring Protocol for Inland Lakes, Version 1.1 8

Noon, B. R. 2003. Conceptual issues in monitoring ecological resources. Pages 27–72 in D. E. 

Busch, and J.C. Trexler, editors. Monitoring Ecosystems: Interdisciplinary Approaches for 

Evaluating Ecoregional Initiatives. Island Press, Covelo, California.

Roback, P. L., and R. A. Askins. 2005. Judicious use of multiple hypothesis tests. Conservation 

Biology 19:261–267.

Sokal, R. R., and F. J. Rohlf. 1995. Biometry: The Principles and Practice of Statistics in Biological 

Research, third edition. W. H. Freeman and Company, New York.

United Nations. 1992. Agenda 21. Chapter 17 in Report of the United Nations conference on 

environment and development. United Nations, New York.

van de Koppel, J., M. Reitkerk, and F. J. Weissing. 1997. Catastrophic vegetation shifts and soil 

degradation in terrestrial grazing systems. Trends in Ecology and Evolution 12:352–356.

West, N. E., and T. P. Yorks. 2002. Vegetation responses following wildfire on grazed and ungrazed 

sagebrush semi-desert. Journal of Range Management 55:171–181.

Yoccoz, N. G. 1991. Use, overuse, and misuse of significance tests in evolutionary biology and 

ecology. Bulletin of the Ecological Society of America 72:106–111.
Standard Operating Procedure #10: Reporting

Version 1.1

In Water Quality Monitoring Protocol for Inland Lakes

Prepared by

Suzanne Sanders, Joan Elias and David VanderMeulen*

National Park Service

Great Lakes Inventory and Monitoring Network 

2800 Lake Shore Drive East

Ashland, Wisconsin 54806

* Contact author: david_vandermeulen@nps.gov

September 2015

Suggested citation: 

Sanders, S., J. E. Elias, and D. VanderMeulen. 2015. Standard operating procedure #10: Reporting, 

version 1.1. In J. E. Elias, R. Axler, E. Ruzycki, and D. VanderMeulen. 2015. Water quality 

monitoring protocol for inland lakes: Great Lakes Inventory and Monitoring Network, version 1.1. 

Natural Resource Report NPS/GLKN/NRR—2015/1027. National Park Service, Fort Collins, 

Colorado.

Standard Operating Procedure #10: Reporting, Version 1.1 September 2015

Water Quality Monitoring Protocol for Inland Lakes, Version 1.1 i

SOP9 – Contents

Page

Revision History Log............................................................................................................................iii

10.0 Introduction....................................................................................................................................1

10.1 Summary Reports...........................................................................................................................1

10.2 Analysis and Synthesis Reports.....................................................................................................3

10.3 Scientific Journal Articles..............................................................................................................3

10.4 Other Communications..................................................................................................................5

Standard Operating Procedure #10: Reporting, Version 1.1 September 2015

Water Quality Monitoring Protocol for Inland Lakes, Version 1.1 iii

Revision History Log

The following table lists all edits and amendments to this document since the original publication 

date. Information entered in the log must be complete and concise. Users of this standard operating 

procedure will promptly notify the project manager and/or the Great Lakes Network (GLKN) data 

manager about recommended and required changes. The project manager must review and 

incorporate all changes, complete the revision history log, and change the date and version number 

on the title page and in the header of the document file. For complete instructions, please refer to 

Revising the Protocol, SOP #13. 

Revision History Log:

Previous 

Version 

#

Revision 

Date

Author (with 

title and 

affiliation)

Location in Document and 

Concise Description of 

Revision Reason for Change

New 

Version 

#

1.0 5/01/2015 David 

VanderMeulen, 

GLKN

Updated the NPS contact author, 

distinguished between routine 

data summaries and periodic 

summary reports, added 

language about the use of webbased visualization and data 

summary tools, added resource 

briefs and newsletters as 

subsections under 10.4 Other 

Communications, fixed a handful

of grammatical errors throughout

To clarify and update 

SOP based on changes 

that have occurred 

since Version 1.0 was 

published in 2008

1.1

Add rows as needed for each change or set of changes tied to an updated version number

Standard Operating Procedure #10: Reporting, Version 1.1 September 2015

Water Quality Monitoring Protocol for Inland Lakes, Version 1.1 1

10.0 Introduction

A primary goal of the NPS Servicewide I&M Program is to ensure that the results and knowledge 

gleaned from monitoring are shared with all appropriate parties, especially the parks and their natural 

resource managers. Because the Network’s main focus is to assist parks with monitoring needs, we 

will strive to provide park managers with clear, meaningful products to convey our findings.

While the Network primarily addresses concerns of the parks, its monitoring program has the 

potential to serve a much broader community. For example, monitoring projects can provide a 

starting point for external scientific research (especially to establish cause-effect relationships), and 

can provide insights for adaptive management on other public lands. The Network is also 

accountable to multiple organizations within the federal government, including the NPS I&M 

Program and the U.S. Congress. To ensure accountability and to meet the requests of all parties, we 

will provide the types of reports and communications detailed below.

10.1 Summary Reports

Routine data summaries will be completed annually for lakes and parks that are sampled within that 

year. The summaries will be compiled from data that has been uploaded to the EPA’s STORET 

database and Aquatic Informatics Aquarius database. Hard copy or web-based summary reports will 

be produced periodically, with the primary audience being park resource managers. 

Web-based summaries will primarily be in the form of visualization tools that allow the user to query 

data to create customized water quality summaries, which are currently under development. Hard 

copy summary reports will document our efforts and convey the findings of previous field seasons. 

At a minimum they will provide:

 a brief introduction that describes why that Vital Sign is being monitored;

 an outline of the sampling strategy, including the number of sites sampled, parameters 

measured, and analyses performed;

 data summaries, including tables and figures to enhance visual presentation, as well as a text 

explanation of the findings;

 any other relevant or significant findings; and

 a limited discussion section in which important results are interpreted.

The project manager (aquatic ecologist) will take the lead in writing the report, coordinate an internal 

review, and take responsibility for providing the report to parks.

Standard Operating Procedure #10: Reporting, Version 1.1 September 2015

Water Quality Monitoring Protocol for Inland Lakes, Version 1.1 3

10.2 Analysis and Synthesis Reports

Detailed reports in which data are analyzed and synthesized will be produced on a periodic basis, 

with the frequency depending on the given Vital Sign. The first analysis and synthesis reports will be 

written after at least three years of water quality data have been collected at a given park. The 

frequency of subsequent detailed reports will depend on the data and whether or not trends seem to 

be occurring. As lakes at the parks are monitored repeatedly, in-depth analyses will be conducted for 

each park as well as across parks.

The reports will be written in the format of a scientific journal article (abstract, introduction, 

methods, results, discussion, literature cited) and will contain in-depth analyses as outlined in the 

protocol narrative and SOP #9, Data Analysis. Further, these comprehensive reports will:

 place the observed results in both a regional and historical context by relating them to other 

published literature;

 discuss the significance of the results in terms of environmental change; and

 provide management recommendations based on the findings.

The project manager will take the lead in writing the analysis and synthesis reports, and will 

coordinate an internal review. The target audience of these reports will be the parks (primarily the 

natural resource managers), the Network, and both regional and Servicewide I&M. Outside of the 

park service, the target audience includes the four state departments of natural resources (Indiana, 

Michigan, Minnesota, Wisconsin), the Minnesota Pollution Control Agency, the St. Croix River 

Interagency Basin Team, and the broader scientific community. 

Drafts of analysis and synthesis reports will be reviewed internally and possibly sent to outside 

sources for further review, depending on how analytically complicated the methods are and on the 

gravity of the implications and recommendations.

10.3 Scientific Journal Articles

Because the inland lakes protocol has been designed with rigorous standards for sampling design and 

analysis, monitoring results are expected to be highly defensible and meet the standards of the peerreview process. The publication of monitoring results in scientific journals will allow the Network to 

reach the scientific community in a way that internal NPS reports cannot. Further, peer-reviewed 

publications can promote collaborative investigation by members of the scientific community, either 

independently or in cooperation with the Network. Ultimately, this process should foster a greater 

understanding of ecosystem components and processes. 

For these reasons, the Great Lakes I&M Network will strive to publish analysis and synthesis reports 

in peer-reviewed scientific journals. We will encourage the preparation of manuscripts by having 

reviewers of analysis and syntheses reports recommend whether publication is warranted and suggest 

appropriate journals. The aquatic ecologist and Network coordinator will track these 

recommendations and encourage and provide work time, respectively.

10.4 Other Communications

While reports are a definitive method of documenting the progress of each program, other means of 

communication can further disseminate information to a broader audience. To this end, we will 

provide the following additional types of communications:

Presentations to Park Natural Resource Managers

The project manager will periodically present the findings from the water quality monitoring 

program from previous years to the natural resource managers from the parks where monitoring took 

place. These presentations, which will likely occur at the annual technical committee meeting in 

March, will provide a concise synopsis of monitoring results as well as management considerations.

Conference Presentations

When possible, the project manager will present monitoring results at regional and national scientific 

conferences. Such presentations will allow the Network to reach the broader scientific community, as 

well as land managers and conservation practitioners. Potential conferences include those sponsored 

by the Ecological Society of America, Society for Conservation Biology, The Wildlife Society, the 

Natural Areas Association, the NPS Water Professionals Meeting, and the George Wright Society. At 

a more local scale, the Western Great Lakes Research Conference, which is sponsored in part by the 

Network, is a valuable venue for information exchange.

Resource Briefs

The project manager and assistant project managers will periodically publish short (typically one 

double-sided page) resource briefs (i.e., fact sheets) related to the GLKN aquatics program. These 

briefs, which are written for a lay audience, will convey key findings without using overly technical 

terminology or jargon. The briefs can be specific to a park (i.e., “Water Quality Monitoring at Inland 

Lakes at Pictured Rocks National Lakeshore”) or topical (i.e., “Monitoring North Manitou Island”). 

Hard copies of resource briefs are disseminated to parks, park partners, and other collaborators, and 

provided electronically on GLKN’s website.

Newsletter Articles

GLKN publishes a newsletter titled The Current in the spring and fall, in which the project manager 

provides plans for water quality monitoring and field season summaries, respectively. The project 

manager will also occasionally write water quality related feature articles for the newsletter. Hard 

copies of the newsletter are disseminated to parks, park partners, and other collaborators, and 

provided electronically on GLKN’s website. 

Standard Operating Procedure #11: Post-Season 

Procedures

Version 1.1

In Water Quality Monitoring Protocol for Inland Lakes

Prepared by

Richard Axler and Elaine Ruzycki 

Center for Water and the Environment

Natural Resources Research Institute

University of Minnesota-Duluth

5013 Miller Trunk Highway

Duluth, Minnesota 55811

and

Joan Elias and David VanderMeulen*

National Park Service

Great Lakes Inventory and Monitoring Network 

2800 Lake Shore Drive East

Ashland, Wisconsin 54806

* Contact author: david_vandermeulen@nps.gov

September 2015

Suggested citation: 

Axler, R., E. Ruzycki, J. E. Elias, and D. VanderMeulen. 2015. Standard operating procedure #11: 

Post-season procedures, version 1.1. In J. E. Elias, R. Axler, E. Ruzycki, and D. VanderMeulen.

2015. Water quality monitoring protocol for inland lakes: Great Lakes Inventory and Monitoring 

Network, version 1.1. Natural Resource Report NPS/GLKN/NRR—2015/1027. National Park 

Service, Fort Collins, Colorado.

Standard Operating Procedure #11: Post-Season Procedures, Version 1.1 September 2015

Water Quality Monitoring Protocol for Inland Lakes, Version 1.1 i

SOP11 – Contents

Page

Revision History Log............................................................................................................................iii

11.0 Introduction....................................................................................................................................1

11.1 End of Season Procedures..............................................................................................................1

11.2 Data Management ..........................................................................................................................2

11.3 Quality Assurance/Quality Control................................................................................................2

11.4 Literature Cited ..............................................................................................................................2

Standard Operating Procedure #11: Post-Season Procedures, Version 1.1 September 2015

Water Quality Monitoring Protocol for Inland Lakes, Version 1.1 iii

Revision History Log

The following table lists all edits and amendments to this document since the original publication 

date. Information entered in the log must be complete and concise. Users of this standard operating 

procedure will promptly notify the project manager and/or the Great Lakes Network (GLKN) data 

manager about recommended and required changes. The project manager must review and 

incorporate all changes, complete the revision history log, and change the date and version number 

on the title page and in the header of the document file. For complete instructions, please refer to

Revising the Protocol, SOP #13. 

Revision History Log:

Previous 

Version 

#

Revision 

Date

Author (with 

title and 

affiliation)

Location in Document and 

Concise Description of

Revision Reason for Change

New 

Version 

#

1.0 5/01/2015 David 

VanderMeulen, 

GLKN

Updated the NPS contact author, 

added language about long-term 

storage of multiprobes, noted 

that equipment must be checked 

to ensure that it is clearly 

marked, added language about 

storing and inventorying 

equipment with GLKN and/or 

NPS property numbers, 

referenced chemical inventory 

records, replaced “Material 

Safety Data Sheets” with “safety 

data sheets”, fixed a handful of 

grammatical errors throughout

To clarify and update 

SOP based on changes 

that have occurred 

since Version 1.0 was 

published in 2008

1.1

Add rows as needed for each change or set of changes tied to an updated version number

Standard Operating Procedure #11: Post-Season Procedures, Version 1.1 September 2015

Water Quality Monitoring Protocol for Inland Lakes, Version 1.1 1

11.0 Introduction

The proper maintenance and storage of field and laboratory equipment will prolong the life of the 

gear as well as simplify start-up procedures for the next field sampling season.

11.1 End of Season Procedures

11.1.1 Field Instrumentation and Equipment

When multisensor water quality probes are to be stored for extended periods of time, make the 

following preparations: 

 Thoroughly clean the sensors. 

 Remove installed batteries. 

 Fill the storage cap approximately one-fourth full of tap water or pH 4.0 calibration solution. 

Store in a temperature-controlled environment. Do not expose sensors to freezing 

temperatures. Store away from direct sunlight. Although the instrument should be able to be 

reliably reactivated for field use with a minimum of effort before field use, it should be 

checked out well in advance of scheduled surveys to allow time for repair or replacement. 

Refer to equipment manuals for more detailed instructions regarding maintenance of multiprobe 

sondes or individual sensors like those used in thermal arrays.

End-of-season care of other equipment includes the following:

 Inspect and clean all equipment following the procedures detailed in SOP #5, 

Decontamination of Equipment to Remove Exotic Species. This effort minimizes the 

potential for transferring nuisance species from contaminated lakes to uncontaminated lakes. 

 Lay out all ropes and sampling lines to dry completely, then coil or roll back into their 

holders.

 Store field equipment in protective storage cases to avoid damage.

 Clean all sample collection and storage containers in a 0.1N HCl acid bath followed by 

deionized water rinses as per SOPs #6 and #7.

 Ensure that all equipment is clearly marked (e.g., GLKN WQ).

 Return all of the equipment and supplies to the proper storage area. Keep them organized so 

they can be inventoried using the equipment and supply checklists, and for annual property 

inventories for equipment assigned a GLKN or NPS property number.

 Store calibration standards and electrolyte solutions in a temperature-controlled environment.

 Properly dispose of all chemical waste material.

11.1.2 Laboratory Equipment and Supplies

 Clean all lab ware in a 0.1N HCl acid bath followed by deionized water rinses as per SOP #7. 
Standard Operating Procedure #11: Post-Season Procedures, Version 1.1 September 2015

Water Quality Monitoring Protocol for Inland Lakes, Version 1.1 2

 Inventory all supplies, including chemical inventory records, and if necessary replace 

chemical and non-chemical supplies as soon as possible. 

 Ensure that safety data sheets (formerly known as material safety data sheets) are up-to-date, 

complete, and readily accessible.

11.2 Data Management

There is no substitute for complete and accurate record keeping of field-derived data. Field 

technicians, crew leaders, and project leaders share responsibility for collecting, verifying, and 

documenting data according to the guidelines in this monitoring protocol and all applicable standard 

operating procedures. Refer to the GLKN Data and Information Management Plan (Hart and Gafvert 

2005) for overall guidance and follow SOP #8, Data Entry and Management and SOP #10, 

Reporting, for additional details.

11.3 Quality Assurance/Quality Control

Taking proper care of all field and lab instrumentation and sampling gear is a fundamental part of 

any QA/QC program. Sensors that are properly cared for will likely be less variable, equilibrate more 

quickly in the field, and less prone to malfunction or failure. See SOP #12 for additional details on 

QA/QC procedures.

11.4 Literature Cited

Hart, M., and U. Gafvert (editors). 2006. Data management plan: Great Lakes Inventory and 

Monitoring Network. Great Lakes Inventory and Monitoring Network Report GLKN/2006/20. 

National Park Service, Ashland, Wisconsin. Available at 

http://science.nature.nps.gov/im/units/glkn/assets/docs/GLKN_SD8_Data_Management_Plan.pdf
Standard Operating Procedure #12: Quality 

Assurance/Quality Control

Version 1.2

In Water Quality Monitoring Protocol for Inland Lakes

Prepared by

Tracey Ledder, Joan Elias, and David VanderMeulen*

National Park Service

Great Lakes Inventory and Monitoring Network 

2800 Lake Shore Drive East

Ashland, Wisconsin 54806

* Contact author: david_vandermeulen@nps.gov

September 2015

Suggested citation: 

Ledder, T., J. E. Elias, and D. VanderMeulen. 2015. Standard operating procedure #12: Quality 

assurance/quality control, version 1.2. In J. E. Elias, R. Axler, E. Ruzycki, and D. VanderMeulen. 

2015. Water quality monitoring protocol for inland lakes: Great Lakes Inventory and Monitoring 

Network, version 1.1. Natural Resource Report NPS/GLKN/NRR—2015/1027. National Park 

Service, Fort Collins, Colorado.

Standard Operating Procedure #12: Quality Assurance/Quality Control, Version 1.2 September 2015

Water Quality Monitoring Protocol for Inland Lakes, Version 1.1 i

SOP12 – Contents

Page

SOP12 – Tables.....................................................................................................................................iii

Revision History Log.............................................................................................................................v

Acknowledgements..............................................................................................................................vii

12.0 Purpose...........................................................................................................................................1

12.1 Applicability ..................................................................................................................................1

12.2 Summary........................................................................................................................................1

12.3 Definitions and Abbreviations.......................................................................................................3

12.4 Personnel Responsibilities.............................................................................................................5

12.5 Sampling Process and Design ........................................................................................................7

12.5.1 Site Selection.......................................................................................................................8

12.5.2 Field Collection Parameters ................................................................................................8

12.5.3 Field Analysis......................................................................................................................9

12.5.4 Laboratory Analysis ..........................................................................................................10

12.6 Sampling Methods.......................................................................................................................13

12.6.1 Site Locations....................................................................................................................13

12.6.2 Field Water Measurements................................................................................................13

12.6.3 Samples for Laboratory Analysis......................................................................................15

12.6.4 Sampling Forms.................................................................................................................18

12.7 Handling and Custody..................................................................................................................19

12.7.1 Field Data ..........................................................................................................................19

12.7.2 Site/Sample Identity Codes ...............................................................................................19

12.7.3 Data Transfer.....................................................................................................................19

12.7.4 Sample Transfer.................................................................................................................21

12.8 Analytical Methods......................................................................................................................21

12.8.1 Field Methods....................................................................................................................21

12.8.2 Field Equipment Performance Criteria..............................................................................23

12.8.3 Laboratory .........................................................................................................................25

12.8.4 Laboratory Performance Criteria.......................................................................................25
Standard Operating Procedure #12: Quality Assurance/Quality Control, Version 1.2 September 2015

Water Quality Monitoring Protocol for Inland Lakes, Version 1.1 ii

SOP12 – Contents (continued)

Page

12.8.5 Changing Methods and Documenting Cumulative Bias ...................................................28

12.9 Instrument Calibration Frequency, Inspection, and Maintenance ...............................................29

12.9.1 Field Instruments...............................................................................................................29

12.9.2 Laboratory Instruments .....................................................................................................29

12.10 Inspection and Acceptance of Supplies and Consumables........................................................31

12.11 Records Management.................................................................................................................31

12.12 Assessment and Oversight .........................................................................................................33

12.12.1 Corrective Responsive Actions .......................................................................................33

12.13 Reports to Management .............................................................................................................33

12.14 Data Validation, Certification, and Usability.............................................................................33

12.15 Reconciliation with Data Quality Objectives.............................................................................35

12.16 Literature Cited ..........................................................................................................................35

Attachment A. Checklists for Selection of Multiprobe and Selection of Laboratory..........................37

Multiprobe Checklist....................................................................................................................39

Contract Laboratory Checklist .....................................................................................................41

Attachment B. Checklists for data validation. .....................................................................................43

Field Measurement Validation Checklist .....................................................................................45

Laboratory Data Validation Checklist..........................................................................................47
Standard Operating Procedure #12: Quality Assurance/Quality Control, Version 1.2 September 2015

Water Quality Monitoring Protocol for Inland Lakes, Version 1.1 iii

SOP12 – Tables

Page

Table 1. Number of lakes selected for long-term monitoring of water quality in each 

GLKN park unit. ....................................................................................................................................7

Table 2. Core suite of field variables and required in situ measurement method. ................................9

Table 3. Typical sensor performance specifications for multiprobe field instruments. ......................10

Table 4. Analytical detection levels required for GLKN water quality monitoring. ..........................11

Table 5. Recommended instrument stabilization criteria for recording field 

measurementsa,b....................................................................................................................................14

Table 6. Example range of analytical methods, method detection limits (MDLs), 

containers, and holding times...............................................................................................................16

Table 7. STORET-supported laboratory remark codes.......................................................................20

Table 8. STORET detection descriptors..............................................................................................21

Table 9. Ideal calibration frequencies and acceptance criteria for field instruments. .........................22

Table 10. Frequency, acceptable range, and corrective actions for quality control (QC) 

samples.................................................................................................................................................24

Table 11. Checklists of equipment and supplies for monitoring water quality of inland 

lakes. ....................................................................................................................................................31

Table 12. Summary of QA/QC procedures pertaining to data management.......................................31

Standard Operating Procedure #12: Quality Assurance/Quality Control, Version 1.2 September 2015

Water Quality Monitoring Protocol for Inland Lakes, Version 1.1 v

Revision History Log

The following table lists all edits and amendments to this document since the original publication 

date. Information entered in the log must be complete and concise. Users of this standard operating 

procedure will promptly notify the project manager and/or the Great Lakes Network (GLKN) data 

manager about recommended and required changes. The project manager must review and 

incorporate all changes, complete the revision history log, and change the date and version number 

on the title page and in the header of the document file. For complete instructions, please refer to 

Revising the Protocol, SOP #13. 

Revision History Log:

Previous 

Version 

#

Revision 

Date

Author (with 

title and 

affiliation)

Location in Document and 

Concise Description of 

Revision Reason for Change

New 

Version 

#

1.0 2/25/2010 David 

VanderMeulen, 

Joan Elias, Rick 

Damstra, 

GLKN

Table 4 – update detection levels 

required; info on optical DO 

probes added; Table 9 – clarify 

& update calibration frequency

To bring SOP into 

alignment with 

procedures practiced

1.1

1.1 5/01/2015 David 

VanderMeulen, 

GLKN

Updated the NPS contact 

author, added language 

about the use of web-based 

visualization and data 

summary tools, continuous 

monitoring with thermal 

arrays, data certification, and 

Aquarius database, updated 

the number of index lakes in 

Table 1, added Attachment 

C, Sample Data Certification 

Form, fixed a handful of 

grammatical errors 

throughout.

To clarify and update 

SOP based on changes 

that have occurred 

since Version 1.1 was 

published in 2010

1.2

Add rows as needed for each change or set of changes tied to an updated version number

Standard Operating Procedure #12: Quality Assurance/Quality Control, Version 1.2 September 2015

Water Quality Monitoring Protocol for Inland Lakes, Version 1.1 vii

Acknowledgements

This document was prepared largely through the use of available National Park Service guidance and 

documents prepared for the Great Lakes Network Inventory and Monitoring program. The authors 

wish to acknowledge these sources and thank them for the valuable contribution that they have made 

to this document. Some verbiage contained within this standard operating procedure (SOP) was first 

written in the protocol narrative and other SOPs, and we wish to thank the authors of those sections.

Standard Operating Procedure #12: Quality Assurance/Quality Control, Version 1.2 September 2015

Water Quality Monitoring Protocol for Inland Lakes, Version 1.1 1

12.0 Purpose

This standard operating procedure (SOP) defines procedures for quality assurance and quality control 

to be used with the Great Lakes Network protocol for monitoring water quality in inland lakes. 

Quality assurance is the planned and systematic pattern of all actions necessary to provide adequate 

confidence, or assurance, that a project outcome optimally fulfills expectations. Quality control is the 

systematic evaluation of the various aspects of a project to ensure, or control, that the standards of 

quality are being met. Quality control involves specific tasks undertaken to determine the reliability 

of field and laboratory data. Together, quality assurance/quality control (QA/QC) is a substantial part 

of any monitoring program. The objective of QA/QC is to ensure that the data generated by a project 

are meaningful, representative, complete, precise, comparable, scientifically defensible, and 

reasonably free from bias (Irwin 2006).

12.1 Applicability

Procedures in this SOP will be implemented during all work pertaining to monitoring water quality in 

inland lakes as described in the protocol narrative. This SOP is designed to assure that all data 

obtained will contribute quality information to an understanding of the ecological integrity of park 

units of the Great Lakes Network. 

The rationale for dividing a sampling protocol into a protocol narrative with supporting SOPs is 

based on the following: 

 The protocol narrative is a general overview of the protocol that gives the history and 

justification for doing the work and an overview of the sampling methods, but does not 

provide all methodological details. The protocol narrative will only be revised if major 

changes are made, such as changes in sampling design. 

 The SOPs are specific step-by-step instructions for performing a given task. They are 

expected to be revised more frequently than the protocol narrative. 

 Usually, when a SOP is revised, it is not necessary to revise the protocol narrative to reflect 

the specific changes made to the SOP. All versions of the protocol narrative and SOPs will be 

archived. 

The steps for changing the protocol (either the protocol narrative or the SOPs) are outlined in 

Procedures for Revising the Protocol (SOP #13).

12.2 Summary

Inland lakes are important and valuable resources at six of the parks of the Great Lakes Network 

(APIS, INDU, ISRO, PIRO, SLBE and VOYA). Lakes at these parks are used extensively by visitors 
Standard Operating Procedure #12: Quality Assurance/Quality Control, Version 1.2 September 2015

Water Quality Monitoring Protocol for Inland Lakes, Version 1.1 2

for fishing, boating, swimming, and other recreational activities. The preservation of lake water 

quality and quantity is of utmost importance to park managers, researchers, and the general public. 

Monitoring basic water quality ranked among the highest of the Network’s vital signs (Route 2004).

A national review panel assembled by the NPS Water Resources Division (WRD) recommended a 

suite of five parameters be measured across all NPS monitoring networks (NPS 2002). In addition to 

these five mandated parameters (temperature, pH, specific conductance, dissolved oxygen, and 

flow/water level) we added a measure of clarity (secchi depth or transparency depth) to our core 

suite. The core suite was ranked highest among potential vital signs for aquatic systems of GLKN 

parks, although it was recognized that these measurements were less diagnostic of water quality 

degradation than biotic communities and other water quality variables, such as nutrient 

concentrations.

Inputs of excess nutrients, invasion and spread of exotic species, and contaminants from atmospheric 

fallout and surface runoff, and how these stressors affect the chemical and biological functions of 

lakes are key issues of concern. By monitoring an advanced suite of parameters (nitrogen and 

phosphorus species, dissolved organic carbon, major ions, alkalinity, dissolved silica, and 

chlorophyll-a), we will provide data for a thorough understanding of changes in lakes over time.

Our overall goal is to develop a program for monitoring water quality in inland lakes that will 

contribute to an understanding of the health of ecosystems in park units of the Great Lakes Network. 

The monitoring protocol is intended to document water quality status and trends for individual lakes 

and provide an indication of status and trends on a park-wide and network-wide basis. The protocol 

includes analysis of historical data, sample design, field and laboratory methods, data analysis and 

reporting, and training and operational requirements.
Standard Operating Procedure #12: Quality Assurance/Quality Control, Version 1.2 September 2015

Water Quality Monitoring Protocol for Inland Lakes, Version 1.1 3

12.3 Definitions and Abbreviations

APIS Apostle Islands National Lakeshore (Wisconsin)

INDU Indiana Dunes National Lakeshore (Indiana)

ISRO Isle Royale National Park (Michigan)

PIRO Pictured Rocks National Lakeshore (Michigan)

SLBE Sleeping Bear Dunes National Lakeshore (Michigan)

VOYA Voyageurs National Park (Minnesota)

Blanks Analytical quality control samples analyzed in the same 

manner as site samples.

Equipment blank Also known as field blank. A sample of distilled, 

deionized water taken to the field, opened, and used as 

sample water would be (i.e., poured through equipment 

used to handle samples).

Trip blank Used to indicate potential contamination due to 

migration of volatile organic chemicals (VOCs) from 

the air on the site or shipment into the sample vial. 

Consists of laboratory distilled, deionized water in a 40

mL glass vial sealed with a Teflon septum and is 

unopened in the field.

Laboratory calibration blank Distilled, deionized water injected directly into an 

instrument; indicates contamination in instrument or 

source of water.

Laboratory reagent blank Also known as method blank. Distilled, deionized water 

manipulated as if it were a sample (digestions, 

extractions, etc.).

CCV Continuing Calibration Verification

EPA Environmental Protection Agency

EMAP Environmental Monitoring and Assessment Program

GLKN Great Lakes Inventory and Monitoring Network
Standard Operating Procedure #12: Quality Assurance/Quality Control, Version 1.2 September 2015

Water Quality Monitoring Protocol for Inland Lakes, Version 1.1 4

m Meter

MDL Method Detection Limit

mg/L Milligrams per liter

ML Method Limit of quantitation

MQO Measurement Quality Objective

NAWQA National Water Quality Assessment Program

NPS National Park Service

NPSTORET National Park Service Storage and Retrieval Database

QA/QC Quality Assurance/Quality Control

QAPP Quality Assurance Project Plan

Reference standard Independently created solution of known concentration.

RPD Relative Percent Difference

SDS Safety Data Sheet

SOP Standard Operating Procedure

STORET Storage and Retrieval Database

USGS United States Geological Survey

μg/L Micrograms per liter

WRD Water Resources Division of the National Park Service
Standard Operating Procedure #12: Quality Assurance/Quality Control, Version 1.2 September 2015

Water Quality Monitoring Protocol for Inland Lakes, Version 1.1 5

12.4 Personnel Responsibilities

Personnel will study this SOP prior to beginning work on the project and follow its procedures in 

order to conduct the project according to outlined QA/QC procedures. This will ensure consistency 

and comparability when changes in personnel occur.

The role of the project manager is to serve as a liaison among other related water quality monitoring 

projects conducted by partners (e.g., state monitoring programs), park staff, other Network staff 

(field personnel, data manager), contracted analytical laboratories, and other GLKN monitoring 

project managers. The individual will coordinate with resource management staff at the parks to 

ensure parks are informed of monitoring activities. Specific responsibilities of the project manager 

include the following:

 Coordinate field schedules and availability of supplies with field personnel

 Develop a training program for field personnel

 Develop, document, and oversee the implementation of standard procedures for field data 

collection and data handling

 Coordinate logistics with park staff

 Develop quality assurance and quality control measures for the project, supervise staff 

training and conduct quality assurance checks of field sampling techniques at least once, midseason, with each field crew 

 Contract with an analytical laboratory for analysis of water samples, ensure lab results meet 

program needs (e.g., QA/QC procedures, meaningful minimum detection limits for low level 

strength waters, adequate reproducibility of replicate samples)

 Supervise or perform data entry, verification, and validation

 Summarize and analyze data, prepare reports

 Serve as the main point of contact concerning data content

The project manager will also work closely with the data manager in the following capacities:

 Complete project documentation in NPSTORET and Aquarius (describing who, what, where, 

when, why and how of a project)

 Develop data verification, validation, and certification measures for quality assurance

 Ensure staff are trained in the use of database software and quality assurance procedures

 Coordinate changes to the field data forms and the user interface for project databases

 Identify sensitive information that requires special consideration prior to distribution

 Manage the archival process to ensure regular archival of project documentation, original 

field data, databases, reports and summaries, and other products from the project

 Define how project data will be transformed from raw data into meaningful information and 

create or oversee data summary procedures to automate and standardize this process

 Establish meaningful liaisons with state counterparts to promote sharing of data on a timely 

basis
Standard Operating Procedure #12: Quality Assurance/Quality Control, Version 1.2 September 2015

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The field crew leader will be responsible for preparing supplies and equipment for field season; 

ordering needed supplies; making travel arrangements; maintaining sampling equipment; maintaining 

field vehicles; ensuring field personnel follow sampling protocols; preparing field data forms, chain 

of custody forms, and analytical service request forms for each site; notifying contract laboratory of 

planned sample shipment date; and providing project manager with field trip and check-in schedule.

Field personnel should be adequately experienced and/or trained in using field and water quality 

sampling equipment. This experience is best obtained through a combination of classroom and 

hands-on training, including pilot-testing equipment at a nearby water body. Personnel should be 

familiar with the instruction manuals for all equipment, particularly with regard to calibration and 

maintenance procedures. See SOP #2, Training and Safety, for more details on training.

Field personnel will be responsible for following protocols and standard operating procedures during 

field activities and the handling of samples.

Roles of staff are explained in more depth in section 5 of the inland lakes protocol narrative, along 

with training and requirements.
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12.5 Sampling Process and Design

The process of developing the sampling for this project included consideration of random versus 

nonrandom selection of lakes, and the sampling designs of Minnesota, Wisconsin, and Michigan. 

These three states have the greatest number of lakes of the lower 48 states, have active water quality 

monitoring programs and contain several of the Network parks. Consistency of the Network’s 

monitoring design and protocol with neighboring state programs is desirable to facilitate data 

comparisons and allow statistical inferences using regional data. See the Inland Lakes Protocol 

Narrative for more information on these considerations.

Answering questions about all lakes within a park or all lakes across the network requires either a 

complete census of lakes or a random selection of lakes, which allows inference to the population of 

lakes as a whole. A complete census of lakes is not feasible, as the Network contains well over 1,000 

lakes. A random selection of lakes is not desirable because many lakes are inaccessible and would 

require more than a day of off-trail, backcountry travel to reach. We selected lakes, called index 

lakes, at six park units within the Network to span gradients of chemical and physical parameters, 

visitor use, watershed size, and spatial distribution within each park. The number of lakes selected at 

each park unit varies from one to nine (Table 1). We will analyze data separately for individual lakes 

and address questions at broader spatial extents through comparisons of trends across lakes. (See 

section 4 of the protocol narrative and SOP #9, Data Analysis, for more details).

Table 1. Number of lakes selected for long-term monitoring of water 

quality in each GLKN park unit.

Park Unit Number of Lakes

Apostle Islands National Lakeshore 1

Indiana Dunes National Lakeshore 1

Isle Royale National Park 9

Pictured Rocks National Lakeshore 6

Sleeping Bear Dunes National Lakeshore 6

Voyageurs National Park 8

The information goals and statistical requirements determine the sampling frequency. To identify the 

long-term trends in a waterbody, the sampling frequency should be sufficient to identify a statistical 

trend beyond the background variability. Therefore, it is essential to evaluate existing data prior to 

establishing 1) the number of sites and 2) the frequency of sampling. Statistical power analysis based 

on the power to detect change guided the selection of these two parameters, using calculations of 

statistical sample size and analysis of sensitivity to sampling frequency, respectively. The goal is to 

be able to detect 20% change at 80% power and 5% significance. (See the inland lakes protocol 

narrative for more details on this power analysis.)

Sampling frequency, therefore, requires a pragmatic compromise among statistical rigor, logistics, 

and cost. For discrete monitoring the Network will visit each selected lake three times, annually, 
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during the open water season. Analyses of existing data, such as described in the protocol narrative, 

help us understand the limitations of our sampling design. We do not expect to be able to detect 

changes in most variables after only a few sampling years, and realize that it may take many years to 

detect changes in some highly variable parameters. Given our sampling frequency, we expect even 

the least variable parameter to require more than 10 years of monitoring data before we will be able 

to detect a 20% change with 80% power.

12.5.1 Site Selection

The lakes selected for sampling are listed in section 2 of the inland lakes protocol narrative. A single 

sampling site, typically located in the deepest part of the lake, will be the routine location for 

measuring all water quality variables. Sampling the deepest part of the lake allows sampling every 

possible depth to the bottom, and has a long history in limnology.

For discrete monitoring the Network will use a 0–2 m integrating tube sampler, following the 

protocol used by Wisconsin and Minnesota and many other states. A near-bottom sample 

(approximately 1 meter from bottom) will be collected via Van Dorn sampler during mid-summer, 

when lakes are stratified, for analysis of TP. Continuous water temperature profile data will be 

collected from a subset of index lakes across four parks, and co-located with discrete water quality 

monitoring locations.

12.5.2 Field Collection Parameters

Core field parameters will be measured with multiprobes or individual sensors (Table 2). Samples 

will be taken for shipment to a contract laboratory for nutrients (TP, TN, NO3+NO2-N, NH4-N) and 

chlorophyll-a each sampling visit, or three times annually, and the remaining parameters (alkalinity, 

major ions (Cl, SO4, Ca, Na, K, and Mg), DOC, and SiO2) once annually. In addition, a near-bottom 

sample for TP will be collected once annually from thermally stratified lakes.

Collect water sample(s) with an integrated sampling tube or Van Dorn and process as per SOP #7. In 

the field log book and on the field data sheet, record information related to the sample collection, 

including:

1. Lake name and site identification code

2. Sample date, time, and depth.

3. The amount of water collected.

4. Whether duplicate samples for quality control were collected at this site.

5. Any additional notes or observations pertinent to this sample or location for this sampling 

period.

Additionally, always keep in mind the following:

 Sample containers should be labeled in indelible ink with, at a minimum, the station name, 

date and time of collection, and preservation method, if applicable.

 Follow all SOPs for sample collection and preservation.
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 To ensure the integrity of the sample, be aware of possible sources of contamination. 

Contamination introduced during each phase of sample collection and processing is additive 

and usually is substantially greater than contamination introduced elsewhere in the sample 

handling and analysis process.

 Use appropriate procedures and quality-assurance measures that ensure sample 

representativeness and integrity and that meet study criteria. The degree to which a sample 

can be considered representative of a water body depends on many interrelated factors 

including temporal and spatial homogeneity of the water body, sample size, and the method 

and manner of sample collection.

12.5.3 Field Analysis

For discrete monitoring dissolved oxygen, temperature, specific conductance, and pH will be 

measured in the field using a multiprobe and following the methods listed in Table 2. Multiprobes 

typically perform within the specifications detailed in Table 3. Continuous temperature monitoring 

will also be conducted at select lakes, with the temperature sensors also in accordance with methods 

and specifications in Tables 2 and 3, respectively. Other parameters may be analyzed at the field 

station by field personnel in the future.

Table 2. Core suite of field variables and required in situ 

measurement method.

Field Variable Method

Temperature (°C) EPA 170.1

pH EPA 150.1

Specific conductivity (μS/cm) EPA 120.1

Dissolved oxygen (mg/L) EPA 360.1

Clarity (cm) Transparency tube

Specification of quantification ability for field multiprobes and sensors is not a straightforward data 

quality objective exercise. Most field parameters tend to be those that characterize the waterbody and 

are not usually based on a criterion limit as would be used for a toxic pollutant. Therefore, instrument 

selection should be based on the parameters and ranges they can measure, but instrument-specific 

estimations of the range of uncertainty for each parameter will have to be made when interpreting 

data. Details on estimating instrument sensitivity are included below in section 12.8.2.
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Table 3. Typical sensor performance specifications for multiprobe field instruments.

Sensor

Expected 

Range

Reporting 

Resolution* Estimated Bias Stabilization Criteria

Temperature -5°C to 45°C 0.01°C ±0.15°C Thermistor: ±0.2°C

Glass: ±0.5°C

Specific 

Conductivity (SC25)

0 to 2000

μS/cm

μS/cm

(range 

dependent)

±0.5% of 

reading +1 

μS/cm

≤100 μS/cm: ±5%

>100 μS/cm: ±3%

pH 1 to 14 units 0.01 unit ±0.2 units ±0.1 standard unit

Dissolved Oxygen 

(Conc.) 0 to 50 mg/L 0.01 mg/L

0 to 20 mg/L:

±0.2 mg/L

20 to 50 mg/L: 

±0.6 mg/L

±0.3 mg/L

Dissolved Oxygen 

(% sat.) 0%–200% 0.1% ca. ±2% ±2%

Depth – Z (pressure 

sensor) 0–>100 m 0.1 m ca. 0.1 m 0.1 m

* Resolution specifications are supplied by the manufacturers of the measuring meters. They are not necessarily closely related to 

real-world (outdoor) precision or bias, and are sometimes more related to the number of significant figures reported rather than 

how accurate the extra significant figures are. This is why we will control measurement sensitivity in the actual outdoor measuring 

environment at least once a year by calculating alternative measurement sensitivity (AMS; see Irwin 2006 for more details on 

AMS).

12.5.4 Laboratory Analysis

Samples will be collected in the field according to SOP #6 for shipment to contract laboratories that 

meet QA/QC requirements outlined in Section 12.8.3 of this SOP. Samples will be analyzed for 

nutrients (TP, TN, NO3/NO2-N, NH4-N) and total chlorophyll-a, each sampling period, while 

alkalinity, major ions (Cl, SO4, Ca, Na, K, and Mg), DOC, and SiO2, which tend to be less variable, 

will be monitored annually.

Methods chosen will meet quantification limits according to the criteria tabulated below (Table 4). 

The method limit of quantitation (ML) of the chosen method should be two to ten times lower than 

the typical expected low value. The ML is the lowest value that can be quantified with certainty. The 

value in the “ML needed” column of Table 4 is two to ten times lower than the lowest value found in 

the pilot year of sampling water quality for each analyte. This estimation is used as guide to the 

selection of the method that will be needed for this project.

The majority of the parameters listed in Table 4 are used in waterbody characterization and do not 

have criterion lower limits as would a toxic pollutant. Some of the criteria available are listed as 

maximums not to be exceeded and, as such, do not guide the selection of a method by ML. 

Guidelines to be used, therefore, include relevant state water quality standards, EPA eco-regional 

nutrient recommendations (USEPA 2000), state nutrient criteria as they are developed, data results 

for these parameters from the pilot studies carried out by GLKN, lowest values for the parameter 
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found in relevant Horizon reports (NPS 1995a, 1995b, 1995c, and 1999), and/or values based on the 

best professional judgment of GLKN staff.

Table 4. Analytical detection levels required for GLKN water quality monitoring.

Analyte

Typical Low 

Value Found Criteria Sourcea, b Comment

ML

Needed

Alkalinity (mg/L)c ND (<1) Lowest value

pilot year MDL unknown

DOC (mg/L) c3

Lowest value

pilot year Lab MDL 0.1 0.3 mg/L

Ca2+ (mg/L) c2.4 Horizon report MDL unknown 0.24 mg/L

Cl-(mg/L) c0.273 Lowest value

pilot year Lab MDL 0.025 0.02 mg/L

Chl-a (μg/L) 0.63 EPA Lower of VII and VIII 0.06 μg/L

Mg2+ (mg/L) c0.47 Horizon report MDL unknown 0.04 mg/L

K

+

(mg/L) c0.24 Lowest value

pilot year Lab MDL 0.06 0.02 mg/L

Na+(mg/L) c0.5 Horizon report MDL unknown 0.05 mg/L

SO4

2-

(mg/L) c0.625 Lowest value

pilot year Lab MDL 0.025 0.06 mg/L

TP (μg/L) 10 EPA Lower of VII and VIII 1.0 μg/L

TN (μg/L) 0.38 EPA Lower of VII and VIII 0.03 mg/L

NH4-N (μg/L ) c5.0 Horizon report MDL unknown 1.0 μg/L

NO3+NO2-N (μg/L )

c

2.0 Horizon report MDL unknown 1.0 μg/L

Si02 (mg/L) ND (<0.1) Lowest value

pilot year Lab MDL 0.2 0.1 mg/L

NOTES: 

a: EPA = EPA Ecoregional nutrient criteria recommendations, lower value recommended for aggregate 

ecoregions VII and VIII (USEPA 2000).

b: WQS = criteria value listed in Ledder (2003) state water quality standards

c: parameter has no official criterion for any of the states, the value reported in the analytical requirement 

column is the lowest value determined in the pilot year for rivers or lakes or the lowest value found in a spot 

check of Horizon reports for each park.

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12.6 Sampling Methods

Consistent methods are important to long-term quality data. In actuality, the ideal conditions are not 

always met in the field or in the lab and changes in staff do occur. Therefore, documentation of 

procedures, site conditions, laboratory analysis, and reasons for deviations of any kind is important in 

and of itself for long-term projects. Personnel will be encouraged to write down more than they feel 

may be necessary in the moment as the future interpretation of their data will depend on the written 

record and not the memory of an individual.

12.6.1 Site Locations

Refer to description of monitoring station location, directions, and photos to verify correct location. 

Verify coordinates with a GPS unit. Document this verification. This information will be contained 

in a site binder along with a table of previous field measurements to compare with new 

measurements.

A single sampling site, typically located in the deepest part of the lake, will be the routine location 

for measuring all water quality variables. Sampling the deepest part of the lake allows sampling 

every possible depth to the bottom, and has a long history in limnology. Except for shallow lakes, 

this type of sampling ignores the littoral zone and always avoids the nearshore zone, as well as 

embayments and other features related to morphometry.

12.6.2 Field Water Measurements

Before making field measurements during discrete monitoring, properly-calibrated sensors (see SOP 

#6) must be allowed to equilibrate to the condition of the water being monitored. Sensors have 

equilibrated adequately when instrument readings have stabilized, that is, when the variability among 

measurements does not exceed an established criterion. The criteria for stabilized field readings were 

defined operationally by O’Ney (2005) for a set of three or more sequential measurements (Table 5). 

The natural variability inherent in surface water or ground water at the time of sampling generally 

can be compared with these stability criteria and indirectly relates to the short term bias or the long 

term accuracy that should be attainable with a calibrated instrument. Dissolved oxygen sensors that 

utilize a Clark cell membrane may require up to five minutes to stabilize, while optical dissolved 

oxygen sensors and sensors for the other parameters typically require less than 60 seconds to 

stabilize. Observers should only note instrument readings after the stabilization criteria in Table 5 are 

met for all the sensors, and then record readings for all parameters at once.

Measure field water quality variables and conduct sampling according to SOP #6, field 

measurements and water sample collection. Quality results require consistent measurement methods 

and detection limits.

Depth profiles of temperature, specific conductance, pH, and dissolved oxygen will be measured at 

each sampling station using a multiparameter instrument (multiprobe). Lake level will be determined 

at benchmark stations on a regular basis. Details of methods for measuring lake levels are included in 

SOP #4. Clarity will be measured using a Secchi disk or transparency tube. These core parameters 

will be measured when water samples for analysis of the advanced parameters are collected.
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Begin just below the water’s surface (ca. 0.3 m depth) and take readings after stabilization of the 

multiprobe. Lower the sensors to collect a vertical profile of field parameters at 1m intervals until 20 

m depth, and then every 2–5 m depending on overall depth and gradients. Replicate 10% of the

readings (e.g., at 1 m, 10 m, etc.); take the replicate readings immediately following the original 

readings. Values should agree within 10% or the acceptance criteria in Table 5, whichever is larger.

Sensors that record water temperatures at 1-hour intervals year round from the surface to bottom at 1-

meter intervals will be deployed in a subset of index lakes. Since the sensors are simply deployed 

with no connection to a data logger, assessment of sensor stabilization occurs after data are 

downloaded. 

At all sites, record visual observation information required on the data sheet. Such observational data 

can provide important information to the interpretation of field measurements.

Table 5. Recommended instrument stabilization criteria for recording field

measurementsa,b.

Standard Direct

Field Measurement

Stabilization Criteria

(O’Ney 2005)

Stabilization Criteria

In situ Multisensors

(WOW 2005)

Temperaturec: 

Thermistor Thermometer 

Liquid-in-glass Thermometer 

± 0.2°C

± 0.5°C

± 0.2°C (5%)

Specific Conductivity (SC25)d

When ≤ 100 μS/cm 

When > 100 μS/cm 

± 5%

± 3%

<5 μS/cm (10%)

pHe: Meter displays to 0.01 ± 0.1 unit ± 0.2 unit (10%)

Dissolved oxygene: 

Amperometric (same as 

polarigraphic) method 

± 0.3 mg/L ± 0.5 mg/L (10%)

Notes:

a: 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 

Irwin (2004). 

b: In the case of field probes, bias 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, and is hard to 

quantify with the small sample sizes used to control bias and precision in typical field 

measurements (see Irwin 2004 for more details). 

c: Recommended sensor calibration is quarterly. 

d: Recommended sensor calibration is daily. 

e: Recommended sensor calibration is at beginning of sampling day with a calibration check at 

the end of the day.
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If any analyses are to be done in-house, conduct these analyses as soon as possible upon return from 

the field. A clean analytical station should be prepared in which to work, free of food items, mud, 

lubricants, or lab chemicals. Hands should be thoroughly washed.

12.6.3 Samples for Laboratory Analysis 

Prepare bottles and labels prior to field sampling as per SOP# 6. Collect samples using a 0–2 m 

integrating tube sampler as per SOP #6. For all sampling, it is critical to avoid sampling water 

showing evidence of oil, gasoline or anything else from the boat. It is best to kill the engine and set 

the anchor, if possible, although this may not be possible or advisable in bad weather or with a balky

engine.

Prior to filling sample bottles sent by the laboratory, first rinse the bottle once with sample water, if 

the bottle is not pre-preserved. Some analyses require preservation of the sample with acid, which 

may be added to the bottle by the contract laboratory; in these cases do not rinse the bottle first. Take 

care not to overfill the bottle if the bottle is pre-acidified, as overfilling will flood the acid out of the 

bottle. If the samples requiring acid preservation are not pre-preserved, use caution to add the ampule 

of preservative supplied by the lab and immediately rinse hands in water if acid is spilled. Protective 

gloves are recommended.

Table 6 summarizes the variety of methods, detection limits, preservation techniques, and holding 

times for water samples addressed by this protocol. These methods conform to those used by 
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Table 6. Example range of analytical methods, method detection limits (MDLs), containers, and holding times.

Analyte

Analytical

Note 1 Method # Det. Limit

Vol. 

(ml) Filter Preservation

Sample Bottle

Note 2 Hold Time

Alkalinity Titrimetry 310.1 EPA-NERL 10 mg/L 4

oC 14 d

Spec. auto. 310.2 EPA-NERL 10 mg/L 4

oC 14 d

Titrimetry NFM USGS-OWQ 0.01 meg/L Note 4 None None

Calcium

ICP 3120B APHA 10 ug/L Note 3 pH<2 HNO3 P or G 6 mo

Titrimetry 215.2 EPA-NERL 0.5 mg/L Note 3 4

oC 6 mo

FAA I-3152 USGS-NWQL 0.1 mg/L 250 mL Note 3 pH<2 HNO3 P 180 d

Chloride

IC 300.0 EPA-NERL 0.02 mg/L 4

oC P or G 28 d

Colorimetry 325.2 EPA-NERL 1 mg/L 4

oC 28 d

Titrimetry 4500-Cl APHA 0.15 mg/L 100 mL 4

oC P or G 28 d

Chlorophyll-a Spect. 10200 APHA 2 ug/L <1 L Note 4 Freeze filter P 30 d

Color Spect. 110.2 EPA-NERL 5 Pt units Note 5 4

oC G 48 hr

Vis. Comp. I-1250 USGS-NWQL 1 Pt-co 250 mL Note 5 4

oC P 30 d

DOC Spect. 415.3 EPA 0.018 mg/L 125 Note 3 pH<4 H2SO4 G 28 d

Spect. 0-1122-92 USGS 0.1 mg/L 4

oC AG

K

ICP 3120B APHA 0.3 mg/L Note 3 pH<2 HNO3 P or G 6 mo

FAA 3111B APHA 5 ug/L Note 3 pH<2 HNO3 P or G 6 mo

Mg

ICP 3120B APHA 20 ug/L Note 3 pH<2 HNO3 P or G 6 mo

FAA 3111B APHA 0.5 ug/L Note 3 pH<2 HNO3 P or G 6 mo

Na

ICP 3120B APHA 30 ug/L Note 3 pH<2 HNO3 P or G 6 mo

FAA 3111B APHA 2 ug/L Note 3 pH<2 HNO3 P or G 6 mo

NH4-N

Selective elec. 4500-NH3E 0.08 mg/L 4

oC/pH2,

0

oC

24hr / 28d

Colorimetry 350.2 EPA-NERL 0.08 mg/L pH<4 H2SO4 28 d

Titrimetry 4500-NH3 APHA 5 mg/L 4

oC/pH2,

0

oC

24 hr / 28 d

SiO2

ICP 3120B APHA 20 ug/L Note 3 pH<2 HNO3 P or G 6 mo

Spect. 4500- SiO2 D APHA 0.04 mg/L Note 3 No, 4oC P 28 d

FIA-Spect. 4500- SiO2 F APHA 0.78 ug/L Note 3 No, 4oC P 28 d

TSS Gravimetric I-3765 USGS-NWQL 1 mg/L 250–500 Note 4 4

oC filter P NA

SO4

IC 4110C APHA 75 ug/L Note 3 pH<4 H2SO4 P or G

CIE-UV D6508 ASTM 0.1 mg/L Note 3 pH<4 H2SO4 ASAP

Spect. 37512 EPA-NERL 0.5 mg/L Note 3 pH<4 H2SO4 P or G 28 d
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Table 6 (continued). Example range of analytical methods, method detection limits (MDLs), containers, and holding times.

Analyte

Analytical

Note 1 Method # Det. Limit

Vol. 

(ml) Filter Preservation

Sample Bottle

Note 2 Hold Time

TP

Spect. I-2606 USGS-NWQL 0.001 mg/L 125 mL MgCl 4oC BrownP 30 d

Alkaline P USGS 2003 0.01 mg/L 120 ml Note 6 4

oC /H2SO4 48 hr / 30 d

ICP 200.7 EPA-NERL 60 ug/L pH<2 HNO3 P 6 mo

TN

Alkaline P USGS 2003 0.03 mg/L 120 ml Note 6 4

oC /H2SO4 48 hr / 30 d

Titrimetry 4500-N 0–100 mg/L 4

oC AG 7 d

Combustion 440.0 EPA-NERL 0.1 mg/L Filter 100 d

Source: National Environmental Methods Inventory website (NEMI 2006)

This list is not an endorsement of any particular method or laboratory for any particular analyte. Rather it is to be used as a reference for the range of analytical 

methods available for each analyte. There are surface water conditions (pH, turbidity, other elements) that make a particular method unsuitable for a particular 

situation. As GLKN is monitoring surface water, the methods listed were chosen as representative of the lower range of detection limits.

Note 1. CIE-UV= capillary ion electrophoresis with UV detection, FAA = flame atomic absorption, FIA = flow injection analysis, IC= ion chromatography, ICP = 

inductively coupled plasma, Spec. auto = spectroscopy with autoanalyzer

Note 2. P = plastic (polypropylene), G=glass, AG=amber glass

Note 3. 0.45μm membrane filter. Pre-filter for dissolved portion analysis.

Note 4. 0.45μm glass fiber filter.

Note 5. 0.45μm membrane filter or centrifuge is recommended to remove suspended solids that affect color, however some color will also be removed.

Note 6. USGS 2003. Evaluation of Alkaline Persulfate Digestion as an Alternative to Kjeldahl Digestion for Determination of Total and Dissolved Nitrogen and 

Phosphorus in Water By Charles J. Patton and Jennifer R. Kryskalla. U.S. Geological Survey Water-Resources Investigations Report 03-4174.
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Minnesota, Wisconsin, and Michigan for state certification of environmental laboratories involved in 

Clean Water Act or drinking water sample analysis (MDH 2005, WSLH 2003, MDEQ 2005). They 

are also used by EPA-funded research projects of natural waters in the upper Midwestern U.S. 

Holding times shall in no case be less stringent than those recommended by EPA in 40 CFR Part 136 

to 136.3 and appendices. Refer to SOP #6 for additional details regarding sample collection and 

preservation.

Samples are stored in a cooler with ice packs during field sampling. Prepare samples for shipment 

according to the contract laboratory’s protocols. These protocols will be provided to the field 

sampling personnel for each sampling round so that the proper procedures are accessible in the event 

of contract laboratory changes. In general, samples are shipped on ice to maintain a temperature of 

approximately 4°C. A plastic bag is placed in the cooler first. Sample bottles are packed among zip 

lock bags of ice and/or ice packs to prevent water leakage into the sample bottle during shipment. 

Prepare a temperature check bottle for each anticipated cooler, if recommended by the contract 

analytical laboratory. Use tap water to fill an extra bottle of the same size used for one of the analytes 

and label as “Temperature Check.” Store this check bottle in refrigerator with other samples; package 

and send to the analytical laboratory with the other samples. Some analyses require the sample to be 

frozen for shipment; such frozen samples are likewise packed among ice packs for shipment to the 

contract laboratory. 

Follow the shipping company’s requirements in preparation of the cooler of samples for shipment. 

Packaging problems may cause delays in shipment, which can mean that samples do not arrive at the 

laboratory at the proper temperature or past holding time, compromising data quality. In general, the 

ice and samples should be contained within a sealed plastic bag within the cooler so that the cooler 

does not leak. Packing tape should be wrapped around the cooler vertically and around the lid seam 

horizontally to ensure it remains closed. A note on the cooler that it contains water samples is helpful 

as well so that if leakage occurs, carriers will know the contents are not hazardous.

12.6.4 Sampling Forms

Before leaving the monitoring site, all field forms and sample labels must be reviewed for legibility, 

accuracy, and completeness. Any changes in procedure due to field condition must be explained in 

the comments section. Make sure the information is complete on all forms. Record the departure time 

on the field form. After reviewing each form, initial the upper right corner of each page of the form. 

Document any photos taken by including the photo number and roll number or digital camera photo 

number on the field form.
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12.7 Handling and Custody

One part of proper data and sample handling procedures is to provide a complete record of the 

methods and procedures followed. Complete records are important to long-term monitoring so that 

anyone using the data may trace the sampling history.

12.7.1 Field Data

Field data will be collected on forms printed on waterproof paper. While at each monitoring site, the 

information recorded on the forms should include:

 Date and day of week

 Time of arrival

 Names of field team members

 GPS coordinates, to verify location

 Current weather (air temperature and wind speed) and relevant notes about recent weather 

(storms or drought)

 Observations of water quality conditions

 Description of any photographs taken

 Multiparameter sonde (model), calibration date, and field measurements of core suite 

variables

 Sample identification numbers and collection times for advanced suite variables or quality 

assurance samples

 Samples taken for laboratory analysis

 Whether any samples were not collected, and reason

 Water level

 Any other required metadata for NPSTORET or Aquarius data entry

 Time of departure

All entries should be made clearly. If an incorrect entry is made, a single heavy line should be drawn 

through the incorrect entry and the correction made. All corrections should be initialed and dated. 

The completed field forms will be maintained in chronological order by station, copied into site 

binders and the originals maintained on file indefinitely. Field data are reviewed annually by network 

personnel (see SOP #8, Data Entry and Management, for details).

12.7.2 Site/Sample Identity Codes

Sampling stations will be identified by park and water body according to Network guidance. 

Information on the sampling station and park will comply with NPSTORET and Aquarius 

requirements.

12.7.3 Data Transfer

Import field and laboratory data into NPSTORET or Aquarius as soon as possible after receiving the 

data, according to SOP #8. Field forms are the only written records of field measurements; place 

copies in office binders and keep originals on file indefinitely. Program sampling data and associated 
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records are archived and stored in the GLKN Ashland Office. Boxes are numbered consecutively by 

year, project, and station number.

Personnel importing data into the database should take care to ensure that units are consistent for 

laboratory data. Different laboratories may report analytical results in different units (mg/L vs. μg/L) 

for the same analyte. Follow SOP #8, Data Entry and Management, when importing data.

Contract laboratories should use the STORET-supported laboratory remark codes (Table 7) or 

provide a map relating their remark codes to these. Unlisted remark codes should be discussed for 

possible addition by the USEPA to the STORET codes. The detection descriptors to be used in data 

entry to STORET are listed in Table 8.

Table 7. STORET-supported laboratory remark codes.

AL Aldol condensation present. Analyte may not be present.

CNT Non-acceptable colony counts.

EHT Sample or extract held beyond acceptable holding time.

FBK Analyte found in blank. Sample contamination indicated.

FDB Failed. Dry blank not acceptable.

FDC Failed. Drift check not acceptable.

FIS Failed. Internal standard not acceptable.

FLD Failed. Lab duplicate not acceptable.

FFD Failed. Field duplicate not acceptable.

FFB Failed. Field blank not acceptable.

FFS Failed. Field spike not acceptable.

FFT Failed. Trip blank not acceptable.

FLC Failed. Linearity check did not meet quality criterion.

FLS Failed. Lab spike recovery not acceptable.

FMS Failed. Matrix spike recovery not acceptable.

FPC Failed. Lab performance check not acceptable.

FQC Failed. Quality control criteria exceeded during analysis.

FRS Failed. Internal reference sample not acceptable.

FSP Failed. Surrogate spike recovery not acceptable.

FSB Failed. Spiked field blank recovery not acceptable.

FSL Failed. Spiked lab blank recovery not acceptable.

INT Interference suspected. Analyte may not be present.

ISP Improper sample preservation noted. Analysis performed.

LIS Lab internal standard(s) added to sample.

LLS Value less than lower quality control standard.

PRE Presumptive evidence that analyte is present.

NJ TIC, Tentatively Identified Compound, result is approximate

N TIC, Tentatively Identified Compound, presumptive id only

OUT Result value is defined as an outlier by data owner

SUS Result value is defined as suspect by data owner
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Table 8. STORET detection descriptors.

Detected and Quantified

*Non-detect

*Present >QL

*Present <QL

*Not Reported

*Present

12.7.4 Sample Transfer

Conduct sample processing per SOP #7. Refrigerate or freeze samples, as required. Conduct in-house 

laboratory work and package samples for sending to contract analytical laboratory. Sample 

preservation and conditions for shipment will differ for each parameter; these needs should be 

discussed ahead of time with the contract laboratory and documented. Fill out the analytical request 

form and chain-of-custody (COC) form provided by the laboratory (examples are included in SOP 

#7). The COC form is used to document the taking, shipment, and receipt of samples. The laboratory 

will use the COC to check samples into the analytical process. Clean all transfer bottles and 

equipment according to SOP #7. Water samples are maintained as close to sampling conditions as 

possible by shipping on ice. Chain-of-custody documentation will be maintained. A chain-of-custody 

includes not only the form, but all references to the sample in any form, document, or log book that 

allow tracing the sample back to its collection, and documents the possession of the samples from the 

time they were collected until the sample analytical results are received.

12.8 Analytical Methods 

Field equipment and contract laboratories are likely to change during the course of this long-term 

monitoring project. Documentation will be maintained, therefore, as regards each multiprobe and 

contract laboratory’s ability to meet the data quality objectives of this project. Forms for this purpose 

are included in Attachment A. These completed forms for each multiprobe and contract laboratory 

will be maintained along with the maintenance logs for the multiprobe and QAPPs for each analytical 

laboratory.

12.8.1 Field Methods

One important aspect in the low uncertainty/bias and high precision of a water quality monitoring 

program is the correct selection of probes for measuring field variable and their subsequent 

calibration and maintenance. Table 3 lists typical field sensor performance specifications that should 

be expected from monitoring equipment for this protocol. Table 9 summarizes the ideal calibration 

frequency and minimum acceptance criteria for these sensor probes. The reality of logistical 

constraints at back country sites may preclude calibration and checks of calibration at the ideal 

frequency. 
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Table 9. Ideal calibration frequencies and acceptance criteria for field instruments.

Parameter

USEPA 

Method

Minimum Calibration Frequency 

and QC checks

Acceptance 

Criteria Corrective Actions

Temperature 170.1 Annually, 2-point check with NIST 

thermometer ±1.0oC

Re-test with a different 

thermometer; repeat 

measurement 

Specific 

Conductance 

(SC25)

120.1

Daily, prior to field mobilization; 

calibration check prior to each 

round of sampling; 10% of the 

readings taken each day must be 

duplicated or a minimum of 1 

reading if fewer than 10 samples 

are read. 

±5%

RPD 10%

Re-test; check low battery 

indicator; use a different meter; 

use different standards; repeat 

measurement 

pH 150.1

Daily, prior to field mobilization (two 

buffers should be selected that 

bracket the anticipated pH of the 

water body to be sampled)

±0.05 pH unit

Re-test; check low battery 

indicator; use different 

standards; repeat 

measurement; don’t move cords 

or cause friction/static 

Calibration check w/ third buffer 

prior to each round of sampling; 

check with low ionic strength buffer 

in addition, if conductivity is <50 

μS/cm 

±0.1 pH unit

10% of the readings taken each 

day must be duplicated or a 

minimum of 1 reading if fewer than 

10 samples are read.

RPD 10%

Dissolved 

Oxygen 360.1

Daily, prior to field mobilization; 

check at the field site if elevation or 

barometric pressure changed since 

calibration 

0.2 mg/L 

concentration or

±10%

saturation

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; allow more time 

for stabilization 

Depth --

Daily, prior to field mobilization, 

check at the field site. Check 

annually against commercially 

purchased brass sash chain 

labeled every 0.5 m to ensure that 

it reads zero at the surface and 

varies <0.3 m for depths <10 m 

and no more than 2% for greater 

depths. 

±0.1 m

Retest, check low battery

indicator; repeat measurement; 

use with accurately calibrated 

line

Transparency 

tube --

Transparency tubes have a 100 or 

120 cm scale; ensure tube is clean

±1.0 cm for 

transparency 

tube

Marked lines 

(e.g., Secchi, 

Van Dorn)

--

Check markings annually against 

brass sash chain. If lines are 

heated (for decontamination) check 

prior to each round of sampling.

±1%, 0–10 m

±2%, >10 m Re-mark line.
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Ensure calibration standards are not used beyond expiration dates. Refer to SOP #6 for an 

explanation of each parameter measured, guidelines on potential field measurement problems, and 

other details on performing calibration checks. Keep the manufacturer’s manual with each instrument 

for aid in troubleshooting.

Used calibration solutions, in general, may be rinsed down a sink with water after consideration of 

the wastewater treatment system available to that sink. Safety data sheets (SDS) which are sent with 

manufacturer purchased calibration solutions should be kept on file. These documents describe the 

flammability, toxicity, and other safety hazards of reagents. Some reagents may include constituents 

toxic to aquatic life. These should not be rinsed down a sink in any large quantities in primitive areas 

where the ultimate destination of wastewater is the aquatic environment. These reagents should be 

collected in a leak-proof container that is properly marked, and disposed of in an adequate treatment 

system.

Calibration logs for multi-parameter sondes will be maintained and will document the frequency of 

calibration and calibration checks. Data reporting units will be standardized by using the data sheet. 

Keep calibration and maintenance logs for multiparameter sondes with the sonde during the sampling 

season. Logs will later be archived at the Network office in Ashland, Wisconsin. A new log will be 

started for each field season.

12.8.2 Field Equipment Performance Criteria

Estimates of the completeness, representativeness, precision, comparability, and systematic error of 

data generated by the use of a multiprobe will be estimated and documented according to this SOP. 

Data will be considered representative of the lake when procedures detailed in the inland lakes 

protocol narrative and associated SOPs are followed. Actual sampling location and changes due to 

field conditions will be documented on the field forms. Data will be comparable year-to-year as 

objectives and methods chosen are consistent within documented NPS GLKN sampling procedures.

12.8.2.1 Field Data Completeness

The completeness of data collected, or percentage of intended field measurements that were actually 

made, will be calculated at year’s end according to the formula below.

Percent_completeness= (

# samples_collected

# samples_planned ) × 100

12.8.2.2 Instrument Sensitivity

Sensitivity of the multiprobe will be documented through an estimation of the limits of detection 

known as alternative measurement sensitivity (AMS). The AMS for each multiprobe will be 

estimated annually, and for any new multiprobes, by taking multiple (at least seven) measurements in 

a field simulation for each parameter. Alternative Measurement Sensitivity (AMS) is a two-sided 
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estimation based on the 99% confidence interval for sample size seven. Of interest is the size of the 

difference between two individual values that can be considered to actually be a true difference. This 

calculation differs from the MDL, which is a one-sided true difference from zero. The standard 

deviation will then be calculated and used in the estimation of AMS (3.708 x SD). This estimation 

will be carried out and documentation kept for a new probe and annually thereafter (Attachment A). 

Documentation will be kept in the project files.

12.8.2.3 Instrument Precision

The precision of the multiprobe will be estimated through the use of duplicates. Duplicates will be 

measured each day in the field at a rate of 10% (or 1 per park sampled if fewer than 10 sites are 

sampled). A reading will be considered a duplicate when it is repeated at a particular sampling site 

immediately after it is initially taken. Only the surface reading need be replicated. This will reduce 

the contribution of variability from the variability of the lake itself. Precision calculations are made 

by way of a Relative Percent Difference (RPD). Measurement Quality Objective (MQO) for 

precision: The RPD should be less than or equal to 10%; details and corrective actions are listed in 

Table 10. Calculate precision as follows:

Precision = (

A − B

(A + B) ∕ 2

) × 100

Where A is the firest reading, and B is the second reading taken immediately after the first.

Table 10. Frequency, acceptable range, and corrective actions for quality control (QC) samples.

Type of QC 

Sample Frequency

Acceptable Range for 

MQOs Corrective Action

Field 

Duplicates 

(samples) 

Minimum of 1 per trip 

per parameter or 10% 

of all samples per 

parameter per day 

All parameters ±15% 

RPD, chlorophyll-a, TSS 

and nutrients ±30% 

Audit field personnel and verify sample 

collection procedure; resample; 

reanalyze; revise SOP; audit and train 

field personnel; project manager 

determines whether associated data is 

usable 

Field 

Duplicates 

(multi-probes) 

Minimum of 1 per trip 

per parameter or 10% 

of all samples per 

parameter per day 

All parameters ±10% RPD

Re-calibrate instrument; replace batteries; 

perform instrument field check with 

different standards; repair or replace 

instrument; notify management; audit and 

train field personnel; project manager 

determines whether 

Laboratory 

Control QC 

(bias)

One each per 

analytical batch, 

minimum 1 per 20 

samples

All parameters ±15% RPD

According to laboratory QAPP, ensure recalibration, re-analysis, and 

documentation.
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12.8.2.4 Instrument Bias

The systematic error/bias of the multiprobe will be estimated through the use of reference solutions. 

Reference solutions will be measured prior to each round of sampling, in the lab or field. The results 

will be documented and used as a calibration check according to Table 9 as well as for a long-term 

estimate of systematic error/bias. Bias calculations are made by way of a Percent Difference (PD). 

Calculate bias as follows:

Bias = (

Y − X

X

) × 100

Where X is the known (or expected) amount, and Y is the measured concentration.

12.8.3 Laboratory

The ability to use environmental data to reveal long-term trends requires consistent analytical 

methods and detection limits. The NPS recommendation is to use only laboratories with NELAC 

certification or at least certification by the state programs that also use the laboratory. The chosen 

contract laboratories must prove their capability annually through participation in blind quality 

control checks and other methods prescribed by the states in which they receive certification and/or 

federal programs in which they participate. Copies of certifications for each analyte and/or method 

will be kept on file along with Quality Assurance Project Plans (QAPPs) for each laboratory 

contracted for the duration of this monitoring effort. 

The method used in calculating method detection limits (MDLs) and method limit of quantitation 

(ML) or laboratory reporting limits (Lt-RL for USGS labs) may differ for each contract laboratory. 

Most laboratories routinely recalculate MDLs, MLs, and QC sample control limits using repeated 

measurement of standard samples or multiple percent recoveries on a quarterly or annual basis. The 

GLKN will request and maintain copies of this information as most recently calculated for the 

relevant analytical methods to assist in the selection of contract laboratories, data validation, and 

AMS calculations. 

A checklist to be used in selecting contract laboratories and documenting their compliance with 

GLKN QA/QC expectations is included in Attachment A. 

Great Lakes Network staff validating laboratory data for database entry should take care to ensure 

that data are entered in consistent units, as different laboratories may report results in different units 

(mg/L or μg/L) for the same analytes. A checklist to be used in data validation is included in 

Attachment B.

12.8.4 Laboratory Performance Criteria

Comparability, representativeness, precision, systematic error, and completeness of data generated by 

contract laboratories will be estimated and documented according to this SOP during data validation. 

Table 10 can be used as a guide. Unless otherwise justified (for example, to be consistent with State 

requirements), in no case will Measurement Quality Objectives less stringent than the following be 

accepted: 
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 Precision––A maximum of 10% RPD for all lab parameters except chlorophyll-a and 

nutrients, for which the maximum RPD is 30%.

 Bias––A maximum of 15% PD for all parameters, or State credible data defaults, whichever 

is more stringent.

All MQOs will be used as data rejection criteria.

The data delivery package must contain QC sample results and an explanation of new STORET and 

NPSTORET compatible laboratory flags. A checklist to be used for documenting this procedure is 

included in Attachment B.

Data generated will be considered representative of the particular site when samples are taken 

according to the sampling protocol for each sampling objective. Actual sampling location and 

changes due to field conditions will be documented on the field forms. Data will be comparable yearto-year as objectives and methods chosen are consistent within documented sampling procedures.

12.8.4.1 Laboratory Data Completeness

The completeness of data analyzed, or the percentage of intended sample measurements that were 

actually made, will be calculated at year’s end according to the formula below. Data points may be 

missed due to site conditions, sample container breakage, or disqualified analyses due to control limit 

exceedances in the laboratory. The reasons for missing data should be documented.

Percent_completness = (

#samples_analyzed

#samples_planned ) × 100

Determining required sample sizes and attendant completeness goals was done in a stepwise manner, 

considering desired statistical power and minimum detectable differences (see discussions in the 

protocol narrative). Should percent completeness ever fall below sample sizes needed for analysis of 

trends, adaptive changes will be made to ensure it does not happen again.

12.8.4.2 Laboratory Sensitivity

Measurement sensitivity is estimated in laboratory analysis through the use of signal to noise ratios 

or the standard deviation of repeat measurements of a low level reference standard. The method each 

laboratory uses to calculate MDLs and MLs will be documented using the data validation check list. 

This information will be reviewed during data validation and kept along with other QA/QC 

information for each laboratory.

12.8.4.3 Laboratory Precision

Measurement precision and bias are estimated using a number of QC samples during a round of 

sample analysis for each method. A reference standard of a certified known concentration is analyzed 

along with samples at a rate specified by the laboratory’s QA/QC program. The results of these 

samples are reported and the percent difference calculated. Laboratory duplicates of field samples are 

also analyzed. This is a field sample that is split or subject to repeat analysis within the laboratory to 

estimate and control precision repeatability. Relative percent differences are calculated for laboratory 
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duplicates. The percent difference and RPD of these QC samples should fall within the control limits 

specified by the laboratory (usually 10% to 20% depending on the type of analysis made).

Field duplicates are to be sent to the analytical laboratory at a rate of at least one in every 10 samples. 

A field duplicate is a split sample, or at minimum, a sample co-located in time and space. The 

duplicate is usually given a separate sample identity on the sample label and forms, and it is noted on 

the field form for which sample this is a duplicate. This is a separate check on precision and 

repeatability of the laboratory analysis. The precision measurement is calculated using the Relative 

Percent Difference (RPD) between duplicate sample results per analyte. Precision estimates should 

be performed within seven days of receipt of laboratory results as part of data validation. Acceptance 

criteria and corrective actions are summarized in Table 10.

12.8.4.4 Laboratory Bias

Systematic error/bias (formerly referred to as percent recovery) is estimated for each laboratory 

method through the analysis of spiked samples and/or certified reference materials. Spiked sample 

analyses are conducted by the contract laboratory to ensure the reported data are accurate, or 

compare favorably to the true values. A spiked sample consists of a sample with a known 

concentration of analyte added before any sample preparation procedures are carried out. Sample and 

spiked sample are analyzed using normal procedures and the percent spike difference is calculated. 

Percent difference is calculated as bias (equation 3, above).

Other sources of systematic error in monitoring programs include sample cross contamination from 

field sampling equipment used to handle a multiple number of samples. Equipment blanks are used 

to estimate whether systematic error is added to sample data during sample handling. The integrated 

sampler is to be rinsed in the field three times at each site prior to taking samples. Compositing jugs 

that are not site-dedicated may also be a source of cross contamination. Collect an equipment blank 

periodically, as follows: 

1. In between sample sites, rinse the equipment used to transfer water samples (integrating 

sampler or compositing jug) with laboratory reagent-grade water three times and discard.

2. Rinse with a fourth aliquot and save this aliquot to lab bottles as if it were a lake sample to be 

analyzed.

This sample is labeled equipment blank and information kept on a datasheet describing the source of 

the blank. Results for all parameters should be non-detect. This type of blank is a check for cross 

contamination between sampling sites and control for bias introduced by cross contamination.

The laboratory QAPP should define control limits to be used during analysis of samples. If the 

analysis QC samples are not meeting the control limits, the analysis is usually repeated after recalibration. This protocol should be documented in the lab’s QAPP. During data validation GLKN 

will ensure that the laboratory performance meets the precision and bias MQOs tabulated in Table 

10.
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12.8.5 Changing Methods and Documenting Cumulative Bias

When a field method is changed, the cumulative bias, or change in sampling results due to the 

method change alone, should be estimated. Cumulative bias can become significant over time even 

though changes in methods are small. When change occurs due to a scheduled change in staff, both 

the new staff member and old staff member should perform side-by-side field measurements several 

times (minimum of seven) during training when possible. The results for both will be compared as 

below.

When purchasing a new probe, it should be used for a minimum of seven measurements side-by-side 

with the existing probe when possible.

When a change in laboratory methods is made by the laboratory, the laboratory will be responsible 

for estimating any bias introduced by the change. When a laboratory contract is changed to a 

different laboratory, a minimum of seven samples will be split for analysis in both labs. Data from 

these comparisons will be used to calculate a percent difference (PD) and fraction of change:

PD = (

new − old

old ) × 100

Fraction_of_change = (

old

new)

Where old = data from the older or original method and new = data from the new or 

replacement method. 

Ideally, the average PD (two-sided 95% t-distribution confidence interval) will be within 20% of the 

mean of the old or the new method measurements. If this is not the case, the number of overlapping 

measures should be increased until this criterion is met (Irwin 2006). New values can then be 

normalized to the old method value by multiplying them by the fraction of change.

Any bias should be stated clearly and documented. Documentation will be stored within each site file 

and should also include:

 all raw data pairs for future use

 standard deviation

 the MDL or AMS of the method

 number of paired samples

 95% t-distribution confidence interval for the measurement difference

 dates between which overlapping measurements were made

 date documentation calculation was made

These comparison of methods will be carried out, when possible, in order to document any bias that 

is introduced into the long-term data by a change in methodology and not in the actual environment. 
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Due to the logistical realities imposed by sampling in remote locations and the reality of equipment 

loss or damage and abrupt changes in staff, this type of comparison may not always be possible.

12.9 Instrument Calibration Frequency, Inspection, and 

Maintenance

Instruments used in field measurement or laboratory analysis often require frequent inspection and 

maintenance to ensure they are in good working order. Calibration frequencies differ by instrument 

and should be spelled out in SOPs for both field and laboratory work to ensure consistency.

12.9.1 Field Instruments

Each instrument must have a logbook. The calibration schedule must be observed, using fresh 

calibration standards. Calibration solutions may be disposed of by rinsing down the work space sink 

if the contents do not include constituents which would harm the pipes or aquatic life on the 

receiving end of the available wastewater treatment (see relevant SDS sheets). Calibration checks 

must be documented.

When sensor probes are to be stored for extended periods of time, thoroughly clean sensors, remove 

batteries, and store sonde according to specific instructions in SOP #11 and manufacturer’s manual. 

Store calibration standards and electrolyte solutions in a temperature-controlled environment. 

12.9.2 Laboratory Instruments

Instrument calibration and verification is performed at least once a day for each analytical method 

prior to the analysis of samples. Each laboratory specifies its own procedure, which should include 

multiple point calibrations plus a blank, continuing calibration verification, and final calibration 

verification at the end of an analytical run. Each laboratory should define the procedures in a QAPP. 

Review of these procedures will be documented using the laboratory checklist in Attachment B.

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12.10 Inspection and Acceptance of Supplies and 

Consumables

Monitoring water quality requires many pieces of equipment and a large amount of supplies. Table 

11 lists the SOPs that include checklists of supplies and equipment. When new equipment is received 

or equipment is returned after repair, inspect it for flaws and test it to ensure proper functioning. 

When supplies are received, inspect them to ensure containers are properly sealed. Ensure reagent 

containers are dated upon receipt and upon opening. Commercially purchased calibration standards 

come with an expiration date that must be observed. 

Table 11. Checklists of equipment and supplies for 

monitoring water quality of inland lakes.

Checklist Location

Safety equipment and supplies SOP #2

Decontamination equipment and supplies SOP #5

Field equipment and supplies SOP #6

Laboratory equipment and supplies SOP #7

12.11 Records Management 

All records must be kept, from field activity through sample results. Required metadata will be 

complete. Table 12 summarizes the QA/QC procedures related to data management. For more details 

on the Great Lakes Network’s overall strategy for metadata generation, management, and distribution 

see chapter 8, Data Documentation, of GLKN’s Data Management Plan (Hart and Gafvert 2005) and 

the appendices of that document.

Table 12. Summary of QA/QC procedures pertaining to data management.

Procedure Description

Instrument calibration logs Each instrument must have a logbook.

Field forms Field forms are the only written record of field measurements. Place 

copies in site binders and keep originals on file indefinitely. 

Estimating precision The precision measurement is calculated using the Relative Percent 

Difference (RPD) between duplicate sample results per analyte. 

Precision estimates should be performed within 7 days of receipt of 

laboratory results. 

Electronic data entry Approximately 10% of electronic data entries should be spot checked 

for errors on a random basis. If errors are found, another 10% are 

spot checked. 

Data archiving Sampling data and associated records are archived in boxes and 

stored at the GLKN Ashland office. Boxes are numbered 

consecutively by year, project, and station number. 
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Table 12 (continued). Summary of QA/QC procedures pertaining to data management.

Procedure Description

Data validation Data validation is the process that determines whether quality control 

objectives for data collection were met. 

Data validation reports Data validation reports provide a narrative that discusses any 

deviations from QA/QC procedures and the impacts of those 

deviations. 

Data verification Data verification demonstrates that a data set will qualify as credible 

data. 

Data verification reports Data verification reports document the results of the data verification 

procedure. 

Data qualification codes Data must be fully qualified before uploading to the Water Resources 

Division’s NPSTORET 

Data will be archived according to SOP #8 (Data Entry and Management) for digital data, paper 

copies, and field forms. Field forms are maintained indefinitely. Brief characterizations of the data 

from each NPS unit that was sampled and the Network as a whole will be performed each year, after 

all QA/QC procedures have been completed. For each station sampled, these descriptive statistics 

will include mean, median, maximum and minimum values, skew, kurtosis, and measures of 

variability (e.g., CV, standard error, variance) for each water quality variable. Understanding of 

landscape-scale dynamics will be provided by analyses of variability among stations within the 

domain of interest (e.g., park unit), following one of several approaches described in SOP #9, Data 

Analysis. 

A ‘Memo-to-file’ will be used to document any decisions or corrections that are made. This memo 

will include the date, name of author, site or sample referred to, a description of the problem or error 

and a statement describing the decision made or action taken. The memo will be archived with the 

appropriate site data and files.
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12.12 Assessment and Oversight

It is the project manager’s responsibility to make sure each component of this and other SOPs are 

followed.

12.12.1 Corrective Responsive Actions

The project manager, in consultation with experienced professionals, will be responsible for taking 

corrective responsive action in the case in which QA/QC is not followed or in the case of an 

unexpected event. Responsive action is often needed in the event of broken sample bottles, missing 

data, errors on field sheets, changes due to field conditions, problematic analyses, and other events 

that do not fall within the standard operating procedures. A “Memo-to-file” will be used to document 

any decisions or corrections that are made. This memo will include the date, name of author, site or 

sample referred to, a description of the problem or error and a statement describing the decision made 

or action taken. The memo will be archived with the appropriate site data and files. 

12.13 Reports to Management

Routine data summaries will occur annually for lakes. Summary reports will be produced 

periodically. Web-based visualization and data summary tools for inland lake water quality data are 

under development. These tools and summary reports will be provided to park resource managers, 

park partners, and the public.

More comprehensive analyses of trends will occur for most parameters after three or more years of 

sampling. For stations that are located where no previous monitoring has occurred, this period of 

time tends to be the minimum needed to establish a time series sufficiently powerful to detect 

meaningful levels of change (e.g., 20%) through time. The target audience of the analysis and 

synthesis reports will be the parks, the Network, both regional and Service-wide I&M, and the 

broader scientific community. Drafts will be reviewed internally and sent to the parks, and possibly 

outside sources, for further review. The extent of review will depend on how analytically 

complicated the methods are and the gravity of inference and recommendations.

12.14 Data Validation, Certification, and Usability

Data validation is the method in which data are proven or disproved to be accurate. This process 

involves the review of the results of all measurements, samples, and QC samples. Field data sheets 

and laboratory data are reviewed for transcription errors, completeness, verification of calibration 

and quality control check samples or standards.

A checklist for use in data validation is presented in Attachment B. Data are validated by comparing 

the actual estimates for MDL and ML, precision, bias/uncertainty for each analytical run to the 
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expected quality of results. Once this information is documented, the decision is made by the project 

manager on the usability of the data. Data may be flagged as between MDL and ML and therefore 

highly uncertain (J). Data may be flagged (B) if the analyte was detected in the blank at a 

concentration similar to that in the sample (laboratory flagging rules may differ slightly). These types 

of flagged data contain much more uncertainty than unflagged data. The decision must be made 

whether or not to add them to the database or merely maintain them in files for future reference. 

Some investigation into the sampling method or laboratory method may be needed if ‘B’ flagged data 

are a continual occurrence or if the required MLs are repeatedly unmet.

NPSTORET itself includes some form-based QA/QC tests on data entry. The system does not allow 

entry of results below the ML but will flag the data as “present, not quantified”. The project manager, 

in consultation with other NPS or outside experts, will flag data when they fall outside of expected 

limits. Laboratory results below detection limits (ND) will be kept in the archives as ‘ND’ and will 

be handled statistically according to recent literature (e.g., Helsel 2005) in summary and analysis 

reports. Aquarius provides QAQC tools to check for single value or rate of change data outliers, for 

example.

Once returned to GLKN by WRD, and after appropriate documentation is completed, the 

NPSTORET datasets are officially considered certified. A process for certifying data imported into 

Aquarius is being developed by WRD. Data certification is a benchmark in the project information 

management process that indicates that: 1) the data are complete for the period of record; 2) they 

have undergone and passed the quality assurance checks; and 3) that they are appropriately 

documented and in a condition for archiving, posting and distribution as appropriate.

Certification is not intended to imply that the data are completely free of errors or inconsistencies, 

which may or may not have been detected during quality assurance reviews. Only qualified users 

who have been trained and given edit permissions are allowed to edit data in NPSTORET or 

Aquarius. These procedures protect the integrity of the data and allow the history of each data record 

to be traced.
Standard Operating Procedure #12: Quality Assurance/Quality Control, Version 1.2 September 2015

Water Quality Monitoring Protocol for Inland Lakes, Version 1.1 35

12.15 Reconciliation with Data Quality Objectives

Once data validation is complete, the project manager then calculates percent completeness, 

compares the results to the data quality objectives, and determines whether or not the data meet the 

objectives for both the field and laboratory components of the project.

12.16 Literature Cited

Hart, M., and U. Gafvert (editors). 2006. Data management plan: Great Lakes Inventory and 

Monitoring Network. Great Lakes Inventory and Monitoring Network Report GLKN/2006/20. 

National Park Service, Ashland, Wisconsin. Available at 

http://science.nature.nps.gov/im/units/glkn/assets/docs/GLKN_SD8_Data_Management_Plan.pdf

Helsel, D. R. 2005. Nondetects and Data Analysis: Statistics for Censored Environmental Data 

(Statistics in Practice). John Wiley and Sons, New York.

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. Available at 

www.nature.nps.gov/water/Vital_Signs_Guidance/Guidance_Documents/part_b_lite_05_2005.p

df. 

Irwin, R. 2004. 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, Ft. Collins, Colorado. Available at 

http://science.nature.nps.gov/im/monitor/protocols/wqPartB.doc. 

Ledder, T. 2003. Water resource information and assessment report for the Great Lakes Inventory 

and Monitoring Network. National Park Service, Great Lakes Inventory and Monitoring 

Network, Ashland, Wisconsin. Great Lakes Network Technical Report: GLKN/2003/05. National 

Park Service, Ashland, Wisconsin.

MDEQ (Michigan Department of Environmental Quality). 2005. Environmental and drinking water 

testing labs directory. Available at http://www.michigan.gov/deq/0,1607,7-135-6132_6828-

18205--,00.html. 

MDH (Minnesota Department of Environmental Health). 2005. Laboratory certification program. 

Available at http://www.health.state.mn.us/divs/phl/cert/index.html.

NEMI (National Environmental Methods Index). 2006. National Environmental Methods Index

website, http://www.nemi.gov (accessed July 2006).
Standard Operating Procedure #12: Quality Assurance/Quality Control, Version 1.2 September 2015

Water Quality Monitoring Protocol for Inland Lakes, Version 1.1 36

NPS (National Park Service). 1999. Baseline water quality data inventory and analysis: Apostle 

Islands National Lakeshore. Technical Report NPS/NRWRD/NRTR-98/188. National Park 

Service, Water Resources Division, Fort Collins, Colorado.

NPS (National Park Service). 1995a. Baseline water quality data inventory and analysis: Isle Royale 

National Park. Technical Report NPS/NRWRD/NRTR-95/41. National Park Service, Water 

Resources Division, Fort Collins, Colorado.

NPS (National Park Service). 1995b. Baseline water quality data inventory and analysis: Mississippi 

River National River and Recreation Area. Technical Report NPS/NRWRD/NRTR-95/61.

National Park Service, Water Resources Division, Fort Collins, Colorado.

NPS (National Park Service). 1995c. Baseline water quality data inventory and analysis: Saint Croix 

National Scenic Riverway. Technical Report NPS/NRWRD/NRTR-95/69. National Park Service, 

Water Resources Division, Fort Collins, Colorado.

O’Ney, S. E. 2005. Regulatory water quality monitoring protocol, version 1.0. National Park Service, 

Greater Yellowstone Network, Bozeman, Montana. Available at 

http://science.nature.nps.gov/im/monitor/protocoldb.cfm. 

Route, B. 2004. Process and results of choosing and prioritizing vital signs for the Great Lakes 

Inventory and Monitoring Network. National Park Service, Great Lakes Inventory and 

Monitoring Network, Ashland, WI. Great Lakes Network Technical Report: GLKN/2004/05.

National Park Service, Ashland, Wisconsin.

USEPA (U.S. Environmental Protection Agency). 2000. Ecoregional nutrient criteria. Available at 

www.epa.gov/waterscience/criteria/nutrients/ecoregion/sumtable.pdf (accessed 2 June 2006).

WOW (Water on the Web). 2005. Monitoring Minnesota lakes on the internet and training water 

science technicians for the future––A national online curriculum using advanced technologies 

and real-time data. Available at http://waterontheweb.org.

WSLH (Wisconsin State Laboratory of Hygiene). 2003. Environmental Health Division analytical 

services and methods. University of Wisconsin, Madison, Wisconsin. Available at 

www.slh.wisc.edu/services/index.php. 
Standard Operating Procedure #12: Quality Assurance/Quality Control, Version 1.2 September 2015

Water Quality Monitoring Protocol for Inland Lakes, Version 1.1 37

Attachment A. Checklists for Selection of Multiprobe and 

Selection of Laboratory.

Standard Operating Procedure #12: Quality Assurance/Quality Control, Version 1.2 September 2015

Water Quality Monitoring Protocol for Inland Lakes, Version 1.1 39

Multiprobe Checklist

Probe ____________________________ Purchased __________________________

Serial Number_____________________ Location used _______________________

Manufacturer’s Stated Limits

Sensor Range

Reporting 

Resolution Bias Stabilization Criteria

Temperature

Sp. Cond. (SC25)

pH

DO (Conc.)

DO (% sat.)

Depth – Z 

(pressure sensor)

Alternative measurement sensitivity by multiple field readings 

Location ______________________ Performed by_____________________

Date _______________ Began calibration log _____

Sensor 1 2 3 4 5 6 7

Temperature

Specific 

Conductivity 

(SC25)

pH

(sensor units)

DO (Conc.)

DO (% sat.)

Depth – Z 

(pressure sensor)
Standard Operating Procedure #12: Quality Assurance/Quality Control, Version 1.2 September 2015

Water Quality Monitoring Protocol for Inland Lakes, Version 1.1 40

Calculations

For each parameter calculate the standard deviation of the 7 readings.

Sensor

Standard 

deviation

AMS

3.708x sd

Temperature

Specific 

Conductivity 

(SC25)

pH

(sensor units)

DO (Conc.)

DO (% sat.)

Depth – Z 

(pressure sensor)

Alternate Measurement Sensitivity is a two-sided estimation based on the 99% confidence interval for 

sample size 7. Of interest is the size of the difference between two individual values that can be 

considered to actually be a true difference. The MDL is a one-sided true difference from zero.
Standard Operating Procedure #12: Quality Assurance/Quality Control, Version 1.2 September 2015

Water Quality Monitoring Protocol for Inland Lakes, Version 1.1 41

Contract Laboratory Checklist

Laboratory:

Address: 

Contact person: 

_____ Received QAPP

_____ Received copy of certifications

_____ Received a list of analytical methods used

_____ Define the limits of detection and limit of quantitation calculation method

(can lab report as MDL and ML if currently calculated as LOD and LOQ?)

_____ Received a copy of latest MDL/ML/control limits calculations for relevant methods

_____ MDL/ML as listed meet project needs

(list any analyte for which the ML requirement is not met – discuss options with lab)

_____ Received successful interlaboratory participation documentation

_____ Sample handling log in and COC are documented in the QAPP

_____ Equipment maintenance and calibration procedures are documented in the QAPP

_____ Internal QA/QC documented in QAPP

Control limits calculations are made by what method

(QC includes blanks, duplicates, spikes, reference standards and LCS)

Calibration curves cover level of analytical interest

(QC includes ICV and ICB, and CCV and CCB)

Reporting data flags used include

Attach all copies

Reviewed by ________________________________________ Date _____________

Standard Operating Procedure #12: Quality Assurance/Quality Control, Version 1.2 September 2015

Water Quality Monitoring Protocol for Inland Lakes, Version 1.1 43

Attachment B. Checklists for data validation.

Standard Operating Procedure #12: Quality Assurance/Quality Control, Version 1.2 September 2015

Water Quality Monitoring Protocol for Inland Lakes, Version 1.1 45

Field Measurement Validation Checklist

(one sheet per Park sampled)

Sampling Unit _________________

Date Sampled __________________

Date Reviewed _________________

Reviewed by ___________________

_________ All field forms have been received (data sheet, flow, etc.)

_________ Multiprobe was calibrated correctly 

_________ Multiprobe post-calibration checks were successful

_________ Field duplicates were within range

_________ Multiprobe end of use calibration checks were successful

_________ There were no obvious trends in data taken from any sensor during the sampling day

_________ Equipment blanks sent to lab included

Standard Operating Procedure #12: Post-Season Procedures, Version 1.1 September 2015

Water Quality Monitoring Protocol for Inland Lakes, Version 1.1 47

Laboratory Data Validation Checklist

Sample set from_____________

Date taken ________________

Received data ______________

Reviewed by _______________

Review date _________________

_____ Samples received by lab at proper temperature (look at COC copy from lab)

_____ Holding time limits met

_____ Analytical methods used in analyses were those agreed upon

_____ Useable MDL and ML achieved in this analytical run

_____ Calibration procedures were followed

QC samples control limits applicable to this analytical batch

Lab blank _____

Lab dup _____

Lab LCS _____

Lab spikes _____

Field dup _____

Eq blank _____

CCVs _____

QC samples within range expected

Lab blank _____

Lab dup _____

Lab LCS _____

Lab spikes _____

Field dup _____

Eq blank _____

CCVs _____

Lab notes or flags

Samples rejected

Signature of Reviewer ______________________________________________

Standard Operating Procedure #13: Procedure for 

Revising the Protocol

Version 1.1

In Water Quality Monitoring Protocol for Inland Lakes

Prepared by

Suzanne Sanders, Joan Elias, and David VanderMeulen*

National Park Service

Great Lakes Inventory and Monitoring Network 

2800 Lake Shore Drive East

Ashland, Wisconsin 54806

* Contact author: david_vandermeulen@nps.gov

September 2015

Suggested citation: 

Sanders, S., J. E. Elias, and D. VanderMeulen. 2015. Standard operating procedure #13: Procedure 

for revising the protocol, version 1.1. In J. E. Elias, R. Axler, E. Ruzycki, and D. VanderMeulen. 

2015. Water quality monitoring protocol for inland lakes: Great Lakes Inventory and Monitoring 

Network, version 1.1. Natural Resource Report NPS/GLKN/NRR—2015/1027. National Park 

Service, Fort Collins, Colorado.

Standard Operating Procedure #13: Procedure for Revising the Protocol, Version 1.1 September 2015

Water Quality Monitoring Protocol for Inland Lakes, Version 1.1 i

SOP13 – Contents

Page

Revision History Log............................................................................................................................iii

13.0 Introduction....................................................................................................................................1

13.1 Steps for Revising the Protocol......................................................................................................1

Standard Operating Procedure #13: Procedure for Revising the Protocol, Version 1.1 September 2015

Water Quality Monitoring Protocol for Inland Lakes, Version 1.1 iii

Revision History Log

The following table lists all edits and amendments to this document since the original publication 

date. Information entered in the log must be complete and concise. Users of this standard operating 

procedure will promptly notify the project manager and/or the Great Lakes Network (GLKN) data 

manager about recommended and required changes. The project manager must review and 

incorporate all changes, complete the revision history log, and change the date and version number 

on the title page and in the header of the document file. For complete instructions, please refer to the 

information in this protocol, below. 

Revision History Log:

Previous 

Version 

#

Revision 

Date

Author (with 

title and 

affiliation)

Location in Document and 

Concise Description of 

Revision Reason for Change

New 

Version 

#

1.0 5/01/2015 David 

VanderMeulen, 

GLKN

Updated the NPS contact author, 

added information about 

obtaining a new document 

number, noted that data manager 

will repost new version of 

narrative to IRMA if major 

changes are made, fixed a 

handful of grammatical errors 

throughout

To clarify and update 

SOP based on changes 

that have occurred 

since Version 1.0 was 

published in 2008

1.1

Add rows as needed for each change or set of changes tied to an updated version number

Standard Operating Procedure #13: Procedure for Revising the Protocol, Version 1.1 September 2015

Water Quality Monitoring Protocol for Inland Lakes, Version 1.1 1

13.0 Introduction

Because of the long-term nature of the National Park Service’s (NPS) monitoring program, the 

projects must necessarily accommodate change. Refined field methods, advances in analysis 

techniques, and feedback from field crews and project managers can all contribute to improving the 

monitoring protocol. The purpose of the current SOP is to define a systematic and routine process for 

incorporating these changes into the protocol.

13.1 Steps for Revising the Protocol

1. Attempt to incorporate the changes by first modifying only the SOP(s), without making changes 

to the protocol narrative. However, if it is clear that changes will also be needed on the narrative, 

then revise it as well. 

2. Make all revisions using the Track Changes feature of Microsoft Word. For minor changes, at 

least one other person must review the revision. If the change is more extensive, a discussion of 

the changes by Network staff is warranted before acceptance of the revision. For major changes, 

review from outside of the Network should be sought. Examples of major changes include 

modifications of the sampling design, significantly altered field methods, and revised analysis 

techniques.

3. Record the changes in the revision history log of the SOP and/or in the narrative, as appropriate. 

Include the date of revision, full name(s) and affiliation(s) of author(s), description of and 

reasons for the changes, and section of SOP or narrative where changes were made. 

4. Rename the version of the SOP and/or narrative. For minor changes, only revise the version 

number after the decimal point (e.g., change V. 1.1 to V. 1.2). For major changes, revise the 

number before the decimal point (e.g., V. 2.3 to 3.0) and obtain a new Natural Resources Report 

number. Also change the version number of the SOP or protocol in the header or footer, as 

appropriate.

5. Notify the data manager of the change(s) so that the metadata of the project database will be 

updated. If major changes are made to the protocol narrative the data manager will also repost 

the updated narrative to the NPS Integration of Natural Resource Applications website.

6. Distribute the revised version to all appropriate parties, including the members of the field crew 

and appropriate GLKN staff. The revised version must also be posted on the Network’s website.

7. Maintain a library of previous versions. Such historical information may be crucial for 

understanding, interpreting, and analyzing data.

The Department of the Interior protects and manages the nation’s natural resources and cultural heritage; provides scientific 

and other information about those resources; and honors its special responsibilities to American Indians, Alaska Natives, and 

affiliated Island Communities.

NPS 920/129697, September 2015
National Park Service

U.S. Department of the Interior

Natural Resource Stewardship and Science

1201 Oakridge Drive, Suite 150

Fort Collins, CO 80525

www.nature.nps.gov

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