Relation of Lake-Floor Characteristics to 

the Distribution of Variable Leaf WaterMilfoil in Moultonborough Bay, Lake 

Winnipesaukee, New Hampshire, 2005

By Denise M. Argue, Richard G. Kiah, Jane F. Denny, Jeffrey R. Deacon, 

William W. Danforth, Craig M. Johnston, and Amy P. Smagula

Prepared in cooperation with the 

New Hampshire Department of Environmental Services

Scientific Investigations Report 2007–5125

U.S. Department of the Interior

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

DIRK KEMPTHORNE, Secretary

U.S. Geological Survey

Mark D. Myers, Director

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

For product and ordering information:

World Wide Web: http://www.usgs.gov/pubprod

Telephone: 1-888-ASK-USGS

For more information on the USGS--the Federal source for science about the Earth, its natural and living resources, 

natural hazards, and the environment:

World Wide Web: http://www.usgs.gov

Telephone: 1-888-ASK-USGS

Any use of trade, product, or firm names is for descriptive purposes only and does not imply endorsement by the 

U.S. Government.

Although this report is in the public domain, permission must be secured from the individual copyright owners to 

reproduce any copyrighted materials contained within this report.

Suggested citation:

Argue, D.M., Kiah, R.G., Denny, J.F., Deacon, J.R., Danforth, W.W., Johnston, C.M., and Smagula, A.P., 2007, 

Relation of lake-floor characteristics to the distribution of variable leaf water-milfoil in Moultonborough Bay, Lake 

Winnepesaukee, New Hampshire, 2005: U.S. Geological Survey Scientific-Investigations Report 2007–5125, 38 p.
iii

Acknowledgments

The authors acknowledge the New Hampshire Department of Environmental Services for their 

assistance in project development and support. Thanks are extended to Barry Irwin and Charles 

Worley, U.S. Geological Survey, for their assistance in the collection of geophysical data. Thanks 

also are extended to Jeffrey Schloss, University of New Hampshire, and Walter Barnhardt and 

James F. Coles, U.S. Geological Survey, for their critical review of this report. Appreciation is 

extended to Mary Ashman for the editorial report review, Patricia Lee for manuscript and layout, 

and Susan L. Bergin for graphics.

v

Contents

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

Introduction ....................................................................................................................................................2

Purpose and Scope ..............................................................................................................................4

Previous Studies ...................................................................................................................................4

Methods of Data Collection and Analysis .................................................................................................5

Geophysical Mapping of the Lake Floor ...........................................................................................5

Acoustic Ground Discrimination System Survey ............................................................................9

Water Column, Interstitial Pore Water, and Surficial-Sediment Sampling .................................9

Quality Assurance and Quality Control ...........................................................................................10

Statistical Methods.............................................................................................................................10

Characterization of the Lake Environment .............................................................................................10

Lake Floor.............................................................................................................................................11

Submerged Aquatic Vegetation .......................................................................................................18

Water Quality of the Water Column and of Interstitial Pore Water ...........................................18

Chemical Characteristics of the Surficial Sediment on the Lake Floor.....................................18

Characterization of the Distribution of Variable Leaf Water-Milfoil ...................................................18

Summary and Conclusions.........................................................................................................................33

References Cited..........................................................................................................................................34

Appendix 1. Site Names, Locations, Water Depths, Textural Compositions, Median 

Surficial-Sediment Grain Sizes, Standard Deviations, Skewness, Kurtosis, and 

“Verbal Equivalents” (Shepard, 1954) for Sediment Samples Collected in 

Moultonborough Bay, Lake Winnipesaukee, New Hampshire, July 2005 ...............38

Figures

1. Photograph showing variable leaf water-milfoil .....................................................................2

2–3. Maps showing—

2. Study area for Moultonborough Bay, Lake Winnipesaukee, New Hampshire .........3

3. Water- and sediment-sampling sites in Moultonborough Bay, 

Lake Winnipesaukee, New Hampshire............................................................................6

4. Schematic diagram showing geophysical and sampling tools used to map 

lake-floor environments...............................................................................................................7

5. Map showing sidescan-sonar imagery from Moultonborough Bay, Lake 

Winnipesaukee, New Hampshire, and the locations and names of the sites 

where samples were taken to provide ground truth for sonar data....................................8

6. Graph showing measures chosen to describe the grain-size distribution of 

sediment samples include the 16th (d16: fine fraction), 50th (d50: median grain 

size), and 84th (d84: coarse fraction) percentiles of the cumulative-frequency 

distribution curves .....................................................................................................................11

7. Map showing bathymetry for Moultonborough Bay, Lake Winnipesaukee, 

New Hampshire ..........................................................................................................................12
vi

8. Graphs showing seismic-reflection profile in Moultonborough Bay, Lake 

Winnipesaukee, New Hampshire: (A) original image and (B) interpreted profile 

showing bedrock, glaciolacustrine sediments, and lacustrine sediments.......................14

9–12. Maps showing—

9. Depth to bedrock as measured from the lake surface in Moultonborough 

Bay, Lake Winnipesaukee, New Hampshire, determined through the use of 

seismic-reflection data.....................................................................................................15

10. Total sediment thickness in Moultonborough Bay, Lake Winnipesaukee, 

New Hampshire, determined through the use of seismic-reflection data...............16

11. Three lake-floor environments in Moultonborough Bay, Lake Winnipesaukee, 

New Hampshire, as interpreted from geophysical and sediment-sample data ....17

12. Distribution and percentage of the lake floor covered by submerged aquatic 

vegetation in Moultonborough Bay, Lake Winnipesaukee, New Hampshire..........19

13. Graphs showing a comparison of data from the acoustic ground-discrimination 

system survey reports for (A) vegetative cover, (B) reflected acoustic intensity of 

the sediments and vegetation, and (C) fractal dimension among variable leaf watermilfoil sites, other-SAV sites, and no-SAV sites in Moultonborough Bay, 

Lake Winnipesaukee, New Hampshire...................................................................................26

14. Map showing distribution and percentage of the lake floor covered by variable 

leaf water-milfoil and areas susceptible to variable leaf water-milfoil growth in 

Moultonborough Bay, Lake Winnipesaukee, New Hampshire...........................................28

15–19. Graphs showing—

15. A comparison of water depth among the variable leaf water-milfoil sites, 

other-SAV sites, and no-SAV sites in Moultonborough Bay, Lake 

Winnipesaukee, New Hampshire ...................................................................................29

16. A comparison of iron concentrations in water-column samples among the 

variable leaf water-milfoil sites, other-SAV sites, and no-SAV sites in 

Moultonborough Bay, Lake Winnipesaukee, New Hampshire..................................29

17. A comparison of surficial-sediment grain size for (A) the fine fraction, 

16th percentile (d16), (B) the median grain size, 50th percentile (d50), and 

(C) the coarse fraction, 84th percentile (d84) among variable leaf water-milfoil 

sites, other-SAV sites, and no-SAV sites in Moultonborough Bay, 

Lake Winnipesaukee, New Hampshire..........................................................................30

18. Water depth and the median (d50) surficial-sediment grain size for all study 

sites in Moultonborough Bay, Lake Winnipesaukee, New Hampshire ....................31

19. Concentrations of total ammonia plus organic nitrogen from interstitial 

pore-water samples and the median (d50) surficial-sediment grain 

size for all study sites in Moultonborough Bay, Lake Winnipesaukee, 

New Hampshire .................................................................................................................32
vii

Tables

1. Family, genus, species, and common name of the most common submerged 

aquatic plants in Moultonborough Bay, Lake Winnipesaukee, New Hampshire ..............4

2. Lake-floor environments, sidescan-sonar backscatter patterns, descriptions, 

sediment textures, and water depths in Moultonborough Bay, Lake 

Winnipesaukee, New Hampshire ............................................................................................13

3. Site numbers, site names, locations, water depths, selected field parameters, 

median surficial-sediment grain sizes, and percentages of vegetative bottom 

cover for sampling sites in Moultonborough Bay, Lake Winnipesaukee, 

New Hampshire ..........................................................................................................................20

4. Concentrations of potassium, dissolved nitrite plus nitrate, ammonium nitrogen, 

total ammonia plus organic nitrogen, total phosphorus, dissolved ortho-phosphorus, 

iron, and total organic carbon measured in water samples from sampling sites in 

Moultonborough Bay, Lake Winnipesaukee, New Hampshire...........................................21

5. pH (ratio); concentrations of potassium, total nitrate, total nitrite, ammonia plus 

ammonium, total ammonia plus organic nitrogen, phosphorus (strong acid digest), 

phosphorus (Olsen method), loosely sorbed phosphorus, iron-bound phosphorus, 

and iron; percent total organic carbon; and percent moisture measured in 

sediment samples from sampling sites in Moultonborough Bay, Lake 

Winnipesaukee, New Hampshire ............................................................................................22

6. Percentage of the total sediment samples that were finer than the sieve diameter 

from sampling sites in Moultonborough Bay, Lake Winnipesaukee, New Hampshire...24

7. Sediment composition of variable leaf water-milfoil and other-SAV sampling sites 

in Moultonborough Bay, Lake Winnipesaukee, New Hampshire.......................................31
viii

Conversion Factors, Water-Quality Units, and Datums

Multiply By To obtain

Length

meter (m) 3.281 foot (ft)

centimeter (cm) 0.3937 inch (in.)

millimeter (mm) 0.03937 inch (in.)

Area

square kilometer (km2

) 0.3861 square mile (mi2)

Temperature: Temperature is given in degrees Celsius (°C) and may be converted to degrees 

Fahrenheit (°F) as follows: 

 °F=(1.8×°C)+32

Abbreviated water- and sediment-quality units used in this report: Chemical concentrations in 

water and sediment samples are reported in milligrams per liter (mg/L), milligrams per kilogram 

(mg/kg), and percent (%). Milligrams per liter is a unit expressing the concentration of chemical 

constituents as mass (milligrams) of chemical per unit volume (liter) of water. Milligrams per 

kilogram is a unit expressing the concentration of chemical constituents as mass (milligrams) of 

chemical per unit mass (kilogram) of sediment. Percent is the fraction of a sample divided by the 

whole sample and multiplied by 100.

Abbreviated energy and time units used in this report: Energy is reported in decibels (dB) 

and kilohertz (kHz), and time is reported in milliseconds (ms) and seconds (s). Boat velocity is 

reported in knots. Underwater sound velocity is reported in meters per second (m/s).

Specific conductance is given in microsiemens per centimeter at 25 degrees Celsius 

(μS/cm at 25°C).

Vertical coordinate information is referenced to the National Geodetic Vertical Datum of 1929 

(NGVD 29).

Horizontal coordinate information is referenced to the North American Datum of 1983 (NAD 83).
Relation of Lake-Floor Characteristics to the Distribution 

of Variable Leaf Water-Milfoil in Moultonborough Bay, 

Lake Winnipesaukee, New Hampshire, 2005

By Denise M. Argue1, Richard G. Kiah1, Jane F. Denny2, Jeffrey R. Deacon1, William W. Danforth2, 

Craig M. Johnston1

, and Amy P. Smagula3

Abstract

Geophysical, water, and sediment surveys were done 

to characterize the effects of surficial geology, water and 

sediment chemistry, and surficial-sediment composition on the 

distribution of variable leaf water-milfoil in Moultonborough 

Bay, Lake Winnipesaukee, New Hampshire. Geophysical 

surveys were conducted in a 180-square-kilometer area, and 

water-quality and sediment samples were collected from 

24 sites in the survey area during July 2005. 

Swath-bathymetric data revealed that Moultonborough 

Bay ranged in depth from less than 1 meter (m) to about 15 m 

and contained three embayments. Seismic-reflection profiles 

revealed erosion of the underlying bedrock and subsequent 

deposition of glaciolacustrine and Holocene lacustrine 

sediments within the survey area. Sediment thickness ranged 

from 5 m along the shoreward margins to more than 15 m in 

the embayments. Data from sidescan sonar, surficial-sediment 

samples, bottom photographs, and video revealed three distinct 

lake-floor environments: rocky nearshore, mixed nearshore, 

and muddy basin. Rocky nearshore environments were found 

in shallow water (less than 5 m deep) and contained sediments 

ranging from coarse silt to very coarse sand. Mixed nearshore 

environments also were found in shallow water and contained 

sediments ranging from silt to coarse sand with different 

densities of aquatic vegetation. Muddy basin environments 

contained the finest-grained sediments, ranging from fine to 

medium silt, and were in the deepest waters of the bay. 

Acoustic Ground Discrimination Systems (AGDS) survey 

data revealed that 86 percent of the littoral zone (the area along 

the margins of the bay and islands that extends from 0 to 4.3 m 

in water depth) contained submerged aquatic vegetation (SAV) 

in varying densities: approximately 36 percent contained SAV 

bottom cover of 25 percent or less, 43 percent contained SAV 

bottom cover of more than 25 and less than 75 percent, and 

approximately 7 percent contained SAV bottom cover of more 

than 75 percent. SAV included variable leaf water-milfoil, 

native milfoil, bassweed, pipewort, and other species, which 

were predominantly found near shoreward margins and at 

depths ranging from less than 1 to 4 m. 

AGDS data were used in a Geographic Information 

System to generate an interpolated map that distinguished 

variable leaf water-milfoil from other SAV. Furthermore, 

these data were used to isolate areas susceptible to variable 

leaf water-milfoil growth. Approximately 21 percent of the 

littoral zone contained dense beds (more than 59 percent 

bottom cover) of variable leaf water-milfoil, and an additional 

44 percent was determined to be susceptible to variable leaf 

water-milfoil infestation. 

Depths differed significantly between sites with variable 

leaf water-milfoil and sites with other SAV (p = 0.04). 

Variable leaf water-milfoil was found at depths that ranged 

from 1 to 4 m, and other SAV had a depth range of 1 to 2 m. 

Although variable leaf water-milfoil was observed at greater 

depths than other SAV, it was not observed below the 

photic zone. 

Analysis of constituent concentrations from the water 

column, interstitial pore water, and sediment showed little 

correlation with the presence of variable leaf water-milfoil, 

with two exceptions. Iron concentrations were significantly 

lower at variable leaf water-milfoil sites than at other sampling 

sites (p = 0.04). Similarly, the percentage of total organic 

carbon also was significantly lower at the variable leaf 

water-milfoil sites than at other sampling sites (p = 0.04). 

Surficial-sediment-grain size had the greatest correlation 

to the presence of variable leaf water-milfoil. Variable leaf 

water-milfoil was predominantly growing in areas of coarse 

sand (median grain-size 0.62 millimeters). Surficial-sedimentgrain size was also correlated with total ammonia plus organic 

nitrogen (Rho = 0.47; p = 0.02) and with total phosphorus 

(Rho = 0.44; p = 0.05) concentrations in interstitial 

pore-water samples. 

1

U.S. Geological Survey, New Hampshire/Vermont Water Science Center, 

Pembroke, New Hampshire.

2

U.S. Geological Survey, Coastal and Marine Geology, Woods Hole Science 

Center, Woods Hole, Massachusetts.

3

New Hampshire Department of Environmental Services, Concord, 

New Hampshire.
2 Relation of Lake-Floor Characteristics to the Distribution of Variable Leaf Water-Milfoil, New Hampshire, 2005

Introduction 

In freshwater bodies of New Hampshire, the most 

problematic aquatic invasive plant species is Myriophyllum 

heterophyllum or variable leaf water-milfoil (fig. 1) 

(A.P. Smagula, New Hampshire Department of Environmental Services, written commun., 2006). Once established, 

variable leaf water-milfoil forms dense beds that can alter the 

limnologic characteristics of a waterbody. The dense beds 

commonly clog the water and reduce circulation in shallow 

areas; as a result, temperatures increase throughout the water 

column in summer, which may lower dissolved oxygen 

concentrations (Smith and Barko, 1990; Keast, 1983). These 

types of changes may decrease the habitat quality for fish. In 

addition to the effect on natural lacustrine communities and 

their habitats, variable leaf water-milfoil infestations disrupt 

recreational uses of waterbodies. The lakes and ponds of 

New Hampshire are an important economic resource and are 

highly regarded for their inherent beauty and recreational 

uses. Invasive aquatic plants such as variable leaf watermilfoil have negatively affected swimming, boating, fishing, 

and property values in and around several lakes and ponds 

in New Hampshire (Crow and others, 2000; Halstead and 

others, 2003). 

Lake Winnipesaukee, the subject of this study, is in the 

east-central part of New Hampshire (fig. 2). Moultonborough 

Bay is in the northern section of Lake Winnipesaukee (fig. 2).

Despite its oligotrophic status, Moultonborough Bay 

supports the most extensive rooted aquatic plant growth 

in Lake Winnipesaukee (A.P. Smagula, New Hampshire 

Department of Environmental Services, written commun., 

2006). Several species of aquatic plants native to New 

Hampshire waterbodies live in Moultonborough Bay; a native 

species of water milfoil, bassweed, pipewort, and at least eight 

additional native submerged aquatic plants (which are present 

at low densities and occurrences) have been documented in 

the bay (table 1) (A.P. Smagula, New Hampshire Department 

of Environmental Services, written commun., 2006). In 1965, 

Moultonborough Bay became the first waterbody in New 

Hampshire where variable leaf water-milfoil (Myriophyllum 

heterophyllum) was observed (A.P. Smagula, New Hampshire 

Department of Environmental Services, written commun., 

2006). Variable leaf water-milfoil is native to the Southeastern 

and Midwestern areas of the United States. In its native range, 

the more alkaline waters appear to limit the growth of this 

plant. Outside its native range, however, it adapts well to the 

relatively acidic, low-alkalinity, and nutrient-poor conditions 

of oligotrophic lakes and bays (Crow and others, 2000; 

Kimball and Baker, 1983) similar to Moultonborough Bay.

Since the first documented case of variable leaf watermilfoil infestation in Moultonborough Bay, the plant has 

been observed in 56 other waterbodies in New Hampshire 

(New Hampshire Department of Environmental Services, 

2006). Once the plant is well established, eradication becomes 

complicated and expensive. Studies of Eurasian watermilfoil 

have noted that eradication attempts in areas where this plant 

is detected early have the highest rates of success (Eichler and 

others, 2001). These results emphasize the importance of early 

detection in the prevention of further infestation of invasive 

aquatic plants. 

Figure 1. Variable leaf water-milfoil. (Photograph courtesy of A.P. Smagula, New Hampshire 

Department of Environmental Services.)
Introduction 3

Figure 2. Study area for Moultonborough Bay, Lake Winnipesaukee, New Hampshire.

£¤3

UV171

UV11

UV28

UV25

UV109

UV16

UV113

UV107

UV106

UV41

UV25

UV28

71°30' 71°20' 71°10'

43°30'

43°40'

Lake

Winnipesaukee

Lake

Wentworth

Winnisquam

Lake

Squam

Lake

Laconia

Meredith

Center Harbor

Wolfeboro

Moultonborough

Alton

Gilford

Tuftonboro

Lake 

Winnipesaukee

New

Hampshire

Belknap Mountains

Ossipee

Mountains

Study Area

0 2 4 1 MILES

0 2 4 1 KILOMETERS Shaded relief from U.S. Geological Survey 

30-meter National Elevation Dataset, 1999;

developed land from U.S. Geological Survey

National Landcover Dataset, 1992 

Developed land

Moultonborough Bay study area

EXPLANATION

North
4 Relation of Lake-Floor Characteristics to the Distribution of Variable Leaf Water-Milfoil, New Hampshire, 2005

Effective management strategies for invasive aquatic 

plants are continually being investigated and developed by 

federal, state, and local agencies, as well as private volunteer 

organizations. A priority of the U.S. Geological Survey 

(USGS) Invasive Species Program (Lovich and others, 2003) 

and the 1999 Federal Executive Order on Invasive Species is 

to document and monitor invasions and develop methods that 

resource managers can use to evaluate management strategies. 

In 2005, the New Hampshire Department of Environmental 

Services (NHDES) cooperated with five research entities 

to develop six projects that focused on characterizing the 

habitats of variable leaf water-milfoil, methods of long-term 

control, and methods of eradication. For one of these projects, 

the USGS cooperated with the NHDES to investigate the 

distribution (presence and density) of variable leaf watermilfoil in Moultonborough Bay, Lake Winnipesaukee, New 

Hampshire, in May through July of 2005. This study utilized 

geophysical and conventional water-quality measurements to 

identify lake environments that may provide suitable habitat 

for the establishment and growth of variable leaf watermilfoil. The results of the study are intended to assist resource 

managers in federal and state agencies by providing methods 

for detecting variable leaf water-milfoil and for identifying 

areas susceptible to infestation. Ultimately, this information 

may lead to early detection, prevention, and more effective 

mitigation strategies. 

Purpose and Scope

This report (1) describes geophysical methods used to 

assess limnological characteristics; (2) describes the lakefloor environment and the distribution of submerged aquatic 

vegetation (SAV); and (3) correlates lake-floor environments, 

and water and sediment chemistry with the presence and 

density of variable leaf water-milfoil.

This report describes the suite of geophysical 

surveys done in a 180-km2

 area to characterize lake-floor 

environments, the surficial-sediment distribution, and the 

underlying geology. Acoustic ground discrimination systems 

(AGDS) surveys were conducted to assess the spatial 

distribution of SAV and to determine surficial-sediment 

characteristics. The results of water and sediment samples 

collected from 24 sites are described in this report. Three 

categories were used to differentiate the 24 sampling sites for 

analysis: variable leaf water-milfoil (sampling sites where 

all SAV present was variable leaf water-milfoil), other SAV 

(sampling sites where little to none of the SAV present was 

variable leaf water-milfoil), and no SAV (sampling sites where 

there was no SAV present). 

Previous Studies

High-resolution geophysical systems are routinely used 

in the geologic mapping of sea- and lake-floor environments; 

this mapping is effective in the management of lacustrine and 

marine resources, habitat and environmental monitoring, and 

in providing baseline information for long-term limnologic 

and oceanographic research (Shaw and others, 1997; Butman 

and others, 2000; Gardner and others, 2000; Schwab and 

others, 2000; Twichell and others, 2000; Denny and Colman, 

2003; Baldwin and others, 2004; Collier and Brown, 2005; 

Colman, 2005; Barnhardt and others, 2006). Technological 

advances in surficial (sidescan-sonar and swath bathymetry) 

and sub-bottom (seismic) systems now enable detailed (meter 

to submeter) mapping of sea- and lake-floor environments. 

When these data are integrated with physical sampling, the 

morphology, surficial-sediment distribution, and subsurface 

geology of the lake floor can be defined at fine scales. 

Many studies have compared the use of surficial 

geophysical-mapping systems such as sidescan-sonar and 

swath bathymetric systems (Brown and others, 2002; Kenny 

and others, 2003; Brown and others, 2004) to narrow-swath 

or single-beam systems used in AGDS, to define benthic 

environments (Foster-Smith and Sotheran, 2003; Brown 

and others, 2005). Kenny and others (2003) recognized the 

effectiveness of AGDS in demarcating changes in bottom 

characteristics when accompanied by sufficient ground-truth 

data and in defining small-scale habitats (smaller than 1 km2

). 

Brown and others (2005) suggest the complementary use of 

sidescan-sonar and AGDS data to provide a robust approach 

that uses the strength of each system for benthic mapping. 

Sidescan-sonar surveys provide complete imagery of the 

sea or lake floor and can be used to broadly define benthic 

environments and boundaries, and high-resolution point 

data from the AGDS can be used to characterize these 

environments further. 

Table 1. Family, genus, species, and common name of the most common submerged aquatic plants 

in Moultonborough Bay, Lake Winnipesaukee, New Hampshire. 

Family Genus and species Common name

Haloragaceae Myriophyllum heterophyllum Variable leaf water-milfoil

Haloragaceae Myriophyllum humile Native milfoil

Potamogetonaceae Potamogeton amplifolius Bassweed

Eriocaulaceae Eriocaulon septangulare Pipewort
Methods of Data Collection and Analysis 5

Other investigations have used AGDS survey data to 

describe the distribution and density of SAV (Maceina and 

Shireman, 1980; Duarte, 1987; Thomas and others, 1990; 

Valley and Drake, 2005). Valley and others (2004) used AGDS 

data to measure the accuracy and precision of SAV estimates 

of percent bottom coverage and percent biovolume. Because 

results of ground-truth surveys did not differ significantly from 

estimates determined from AGDS, AGDS vegetation surveys 

were considered effective. Lubniewski and Stepnowski (1997) 

reported that they successfully used AGDS data to characterize 

sea-bottom sediment characteristics and composition. 

Currently (2007), limited research has been done on 

the effects of water and sediment quality on the distribution 

of variable leaf water-milfoil. A detailed study of selected 

mineral concentrations measured in the submersed apical 

shoots of variable leaf water-milfoil in Lake Winnipesaukee 

and Lee’s Pond, New Hampshire, related these concentrations 

to site and season (Kimball and Baker, 1982) and to temporal 

and morphological factors (Kimball and Baker, 1983). Kimball 

and Baker (1982) compared the changes in magnitudes 

of variation in apical mineral concentrations at a site for 

each season and determined that these variations did not 

significantly differ in magnitude from the variations among 

different sites during the same season. Kimball and Baker 

(1983) reported that variable leaf water-milfoil is a perennial 

submerged aquatic plant, that it maintains a considerable 

amount of green biomass through the winter season, and that 

plant structure and season influence the mineral concentrations 

in its apical shoots. 

Much work has been documented on Eurasian 

watermilfoil, another problematic invasive species in the 

Myriophyllum genus. Nichols (1994) reported that Eurasian 

watermilfoil was growing at greater depths and in areas with 

less organic matter than other SAV in a lake in Wisconsin. 

Smith and Barko (1990) summarized literature describing 

Eurasian watermilfoil and reported general characteristics 

about its habitats: it grows in depths that range from 1 to 4 m; 

plants are essentially evergreen; photosynthesis occurs 

in cool (15oC) waters; and it grows best in fine-textured 

inorganic sediments. In addition, they reported that uptake 

through the roots is the primary source of phosphorus and 

that ammonium is preferred over nitrate as a nitrogen source. 

Keast (1983) investigated the introduction of Eurasian 

watermilfoil as habitat for fish in a lake in Canada. Keast 

observed Eurasian watermilfoil growing at depths that ranged 

from 2 to 3.5 m in previously open water and concluded that 

Eurasian watermilfoil was not replacing native species but 

occupying another niche in the environment. Madsen (1998) 

indicated that the best predictors of Eurasian watermilfoil 

were water-column total phosphorus and Carlson’s Trophic 

State Index, which is a method for characterizing a lake’s 

trophic state.

Barko and others (1986) investigated a variety of 

environmental factors affecting the distribution and 

species composition of SAV and reported that light, water 

temperature, sediment composition, and inorganic carbon 

availability were the most important. Barko and Smart (2006) 

investigated the effects of sediment-related mechanisms on the 

growth of SAV and determined that correlations between SAV 

growth and nutrient concentrations in the interstitial water or 

total sediment were weak; moreover, correlations between 

SAV growth and total or extractable sediment nutrients were 

generally unsuccessful. Loeb and Hackley (1988) studied 

the sparse occurrence of macrophytes in oligotrophic lakes 

and examined the potential growth-regulating factors among 

supporting and nonsupporting habitats for macrophytes. 

They concluded that ground-water inflows may affect the 

distribution of SAV. Results from Lodge and others (1989) 

indicated a positive correlation between ground-water inflows 

and SAV. Lodge and others (1989) suggested that groundwater inflow may contribute to SAV growth by contributing an 

additional source of nutrients and maintaining higher winter 

temperatures in sediments, thus enhancing winter survival of 

perennial SAV.

Methods of Data Collection 

and Analysis

Geophysical and sediment-sampling surveys were used 

to characterize the surficial lake-floor environment [lakefloor morphology (depth), surficial-sediment distribution, 

and the underlying geology] and the presence and density 

of SAV. Water-column, interstitial pore-water, and sediment 

sampling were designed to determine the concentrations of 

nutrients and inorganic constituents and the characteristics of 

surficial sediments. 

A preliminary AGDS survey was conducted in May 

2005 to collect data on the distribution of SAV and surficial 

sediment. Ground-truth data were collected to provide visual 

confirmation of variable leaf water-milfoil presence, sediment 

type, and depth. On the basis of these data, 24 sites for water 

and sediment sampling were selected (fig. 3). These sites were 

spatially distributed throughout the study area and represent a 

wide range of habitat conditions. 

Geophysical Mapping of the Lake Floor

The characteristics of the surficial sediments on the lake 

floor, the underlying sediments, and the bedrock surface were 

mapped using the following suite of geophysical instruments: 

interferometric sonar (swath bathymetry), sidescan sonar, and 

seismic-reflection profiler (fig. 4). Sediment samples, bottom 

photographs, and video also were obtained (fig. 4). For all 

surveys, the ship’s position was determined through the use 

of differential global positioning system (DGPS) navigation. 

Surveyed depths within Moultonborough Bay ranged from 

approximately 1.5 to 15 m. Water depths less than 1.5 m were 

not accessible because of the limited draft of the vessel.
6 Relation of Lake-Floor Characteristics to the Distribution of Variable Leaf Water-Milfoil, New Hampshire, 2005

Figure 3. Water- and sediment-sampling sites in Moultonborough Bay, Lake Winnipesaukee, New Hampshire. (SAV, submerged 

aquatic vegetation.)

QW5

QW9

QW7

QW6 QW3

QW4 QW1

QW8

QW19

QW16

QW14

QW25

QW23

QW21

QW15

QW10

QW27

QW26

QW22

QW20

QW18

QW17

QW12

QW11

QW19

Variable leaf water-milfoil site and identifier

Other-SAV site and identifier

QW23 No-SAV site and identifier

QW22

71°23'30" 71°23' 71°22'30" 71°22' 71°21'30"

43°42'30"

43°43'

43°43'30"

43°44'

EXPLANATION 0 1,000 2,000 FEET 500

Base from 2003 National Agricultural

Imagery Program (NAIP), 2005 0 250 500 METERS 125

Gansy

Island

Birch Hill

Island

Whaleback

Island

Smith

Point

Lees

Mill

Moultonborough, NH
Methods of Data Collection and Analysis 7

Swath-bathymetric systems acquire depth information 

in a swath to either side of the survey vessel and provide 

continuous coverage of the lake floor (fig. 4). These data 

were acquired with an SEA Ltd. Submetrix 2000 series 

interferometric sonar (234 kiloHertz (kHz)). Swath width was 

a function of depth, but was generally 7 to 10 times the water 

depth, yielding a 7 to 100-m swath. A motion reference unit 

mounted directly above the sonar head recorded vessel motion 

(heave, pitch, roll, and yaw); this attitude information was 

used to rectify bathymetric measurements. A sound-velocity 

profiler was used to determine the sound-velocity structure 

of the water column to correct for variations in the speed of 

sound. The vertical resolution of the depth measurements was 

approximately 1 percent of the water depth. The processed 

bathymetric grid was mapped at a 1 m/pixel resolution and 

incorporated into a geographic information system (GIS). 

Sidescan-sonar systems record the intensity of sound 

reflected from the lake floor (fig. 4). This backscatter reveals 

information about the physical characteristics of the lakefloor sediments. These data were acquired with a Klein 3000 

dual-frequency (100/500 kHz) sidescan-sonar system. Data 

were digitally recorded at a 2-kHz sampling rate, yielding 

approximately a 0.2-m pixel resolution by following the 

methodology of Danforth and others (1991). A 50-m trackline 

spacing was used to ensure complete sidescan-sonar coverage 

of the lake floor. Data were processed and used to create a 

composite image of the lake floor at a 1 m/pixel resolution 

(Danforth and others 1991; Paskevich, 1992; Danforth, 1997). 

This imagery was then incorporated into a GIS. 

Seismic-reflection systems are used to map the 

subsurface geology, such as the thickness and geometry 

of the underlying strata (fig. 4). These data were acquired 

with an Edgetech SB-424 chirp sub-bottom profiler. Data 

were recorded at a 75-millisecond (ms) record length and a 

4-24 kHz sweep and were logged by using Triton-Elics Delph 

seismic acquisition software. Seismic-reflection data were 

converted to single-channel SEG-Y by using the Scripps 

Institution of Oceanography’s SIOSEIS seismic-processing 

software (Henkart, 2005). Automatic gains were applied to the 

data through the use of the Colorado School of Mines’ Seismic 

Unix seismic-processing software (Cohen and Stockwell, 

2001). The processed SEG-Y and navigation data were then 

imported into Seisworks (Landmark Graphics Corporation, 

Inc.), an integrated seismic-interpretation package, for digital 

interpretation. Selected horizons were digitized to calculate 

the depths to reflectors. An average sound velocity of 

1,500 meters per second (m/s) was used to determine the depth 

to bedrock and sediment thickness. 

On the basis of variations in the backscatter patterns 

observed in the sidescan-sonar data, 40 locations on the lake 

floor were selected for the collection of sediment samples 

and for bottom photography and video. The sediment samples 

were collected with a mini-SeaBOSS (SeaBed Observation 

and Sampling System), from the upper 10 cm and were used 

to provide ground truth for the sidescan-sonar and seismicreflection data (figs. 4 and 5). Grain-size analyses were done 

by the USGS by following the methodology of Poppe and 

others (1985) and Poppe and Polloni (2000). 

Swath

bathymetry

Research vessel

Seismic

source

Hydrophone

Differential

Global

Positioning 

System 

Sidescan sonar

Echosounder

Sampling 

device

Figure 4. Geophysical and sampling tools used to map lake-floor environments.
8 Relation of Lake-Floor Characteristics to the Distribution of Variable Leaf Water-Milfoil, New Hampshire, 2005

Figure 5. Sidescan-sonar imagery from Moultonborough Bay, Lake Winnipesaukee, New Hampshire, and the locations and 

names of the sites where samples were taken to provide ground truth for sonar data. (Light tones represent high backscatter and 

dark tones represent low backscatter within the image. See appendix 1 for sediment-texture data.) 

71°23'30" 71°23' 71°22'30" 71°22' 71°21'30"

43°42'30"

43°43'

43°43'30"

43°44'

EXPLANATION

0 1,000 2,000 FEET 500

Base from 2003 National Agricultural

Imagery Program (NAIP), 2005 0 250 500 METERS 125

Lees

Mill

Gansy

Island

Birch Hill

Island

Whaleback

Island

Smith

Point

sta1A

sta11 sta12

sta13

sta14

sta15

sta16

sta18

sta19

sta20

sta25

sta26

sta24

sta22

sta23

sta21

sta17

sta27

sta37

sta36

sta35

sta34

sta33

sta32

sta31

sta29

sta38

sta39 sta40

sta28

sta30

sta1B

sta2

sta3

sta4

sta8

sta6 sta5

sta9

sta10

sta7A/B

Sample site

and identifier

Backscatter

High

Low

sta30

No data

Moultonborough, NH
Methods of Data Collection and Analysis 9

Acoustic Ground Discrimination System Survey

A dual-frequency digital echosounder system (by 

Biosonics) with two 6o

 single-beam transducers (120 and 

420 kHz) was used to map the SAV and characterize surficial 

sediments (Burczynski and others, 2005a). The AGDS data 

were acquired in a linear pattern throughout the study area 

and in three concentric transects that follow the margin of the 

shoreline. The concentric transects were spaced approximately 

10 m, 20 m, and 30 m from the shoreline. Boat speed was 

maintained at approximately 2.5 knots to maintain a horizontal 

resolution of approximately 2 m (Valley and Drake, 2005). 

AGDS data at the 24 sampling sites were collected from 

stationary vessel positions. 

Geographic location was determined with a Trimble 

AgGPS 124/132 receiver and integrated with the AGDS data. 

The 120-kHz transducer was configured to send five pings at 

a pulse duration of 0.4 ms and to collect the reflected signal at 

a threshold of -60 decibels (dB). The 420-kHz transducer was 

configured to send five pings at a pulse duration of 0.1 ms and 

to collect the reflected signal at a threshold of -130 dB. 

The 120-kHz echosounder data were processed by 

using Visual Bottom Typer (VBT) software developed by 

Biosonics (Burczynski and others, 2005b). Every group of 20 

consecutive data points was summarized by VBT software 

into a single report representing approximately 5 m of the lake 

floor. These bottom-type data included the DGPS location, 

bottom depth, energy levels from different sections of the 

acoustic echo envelope (E0

), and the fractal dimension (FD), 

which is a measure of the roughness of the bottom sediment 

(Lubniewski and Stepnowski, 1997). Fractal dimension 

classifies the bottom type by characterizing the shape of the 

bottom echo (Burczynski and others, 2005a). The median 

number of reports generated during stationary-boat positioning 

for each of the 24 sampling sites was 15. Information from 

each of the reports was evaluated to determine bottom-type 

information for the 24 sampling sites.

The 420-kHz echosounder data were processed by 

using EcoSAV software developed by Biosonics (Burczynski 

and others, 2005a). Every group of eight consecutive data 

points was summarized by EcoSAV software into a single 

report representing approximately 2 m of the lake floor. The 

processed vegetation data included a DGPS location, binary 

information on plant presence or absence, the average plant 

height, and bottom depth. The percentage of vegetative cover 

was calculated by using plant presence and plant absence 

information for each AGDS data point along the linear and 

concentric transects as well as at each of the 24 sampling sites. 

The median number of reports generated during stationaryboat positioning for each of the 24 sampling sites was 32. 

Information from the reports was averaged to determine the 

percentage of vegetative cover, average plant height, and 

bottom depth at each of the sampling sites. 

The percentages of vegetative bottom cover from the 

transects were used to create an interpolated vegetation map. 

A natural-neighbor technique was used to interpolate between 

measured points for the percentage of vegetative cover. This 

interpolator technique is a hybrid between inverse distanceweighted (IDW) and Euclidean allocation (Environmental 

Systems Research Institute, 2002; 2004). The interpolated 

data values were derived by a weighted average of the 

percentage of bottom cover from the nearest measured points 

as determined by their Euclidean allocation areas. To eliminate 

false vegetation detections, information about plant presences 

recorded at depths greater than 4.3 m were set to zero. This 

helped to prevent false positives below the photic zone, the 

bottom of which is estimated to be at 1.7 times the Secchi-disc 

depth (Wetzel, 1983). 

Water Column, Interstitial Pore Water, and 

Surficial-Sediment Sampling

Water-column samples were collected by using 

a peristaltic pump and polyethylene tubing placed 

approximately 2 ft from the bottom of the lake. All samples 

were handled and processed according to standard USGS 

surface-water protocols (Wilde and Radtke, 1998a; 1998b). 

Interstitial pore-water samples were collected by using 

two methods. When bottom sediments allowed for sufficient 

yield, a pushpoint sampler was used to collect the interstitial 

pore water (Zimmerman and others, 2005). When bottom 

sediments did not yield sufficient water to maintain continuous 

low-flow pumping, a piezometer was installed. Piezometers 

were constructed of polyvinyl chloride (PVC) material with 

a 6-in. slotted-screen interval. Once the piezometer was 

installed, it was allowed to equilibrate for approximately one 

hour prior to pumping. The water level in the piezometer, 

specific conductance, pH, and temperature were monitored 

prior to sample collection. A sample was collected when 

all field parameters had been stable for three consecutive 

independent readings (Wilde and Radtke, 1998a). 

Water-column and interstitial pore-water samples were 

analyzed for concentrations of potassium, dissolved nitrite 

plus nitrate, ammonium nitrogen, total ammonia plus organic 

nitrogen, total phosphorus, dissolved orthophosphate, iron, 

and organic carbon at the New Hampshire Department 

of Environmental Services Laboratory in Concord, New 

Hampshire. Field measurements for specific conductance, pH, 

temperature, dissolved oxygen, and Secchi-disk depth also 

were made.

Sediment samples were collected for chemical and 

grain-size analysis from the upper 0 to 10 cm of the lake 

sediment at 24 sites according to standard USGS protocols 

(Sheldon and Capel, 1994). A small polyethylene scoop 

was used to collect sediment at sites where the water depth 

was less than 1.5 m. A hand-held coring device was used to 

collect sediment at sites where the water depth was greater 

than 1.5 m. All sediment samples were analyzed at SGS 

Environmental Services Laboratory in Lakefield, Ontario for 

concentrations of potassium, dissolved nitrite plus nitrate, 

ammonium nitrogen, total ammonia plus organic nitrogen, 
10 Relation of Lake-Floor Characteristics to the Distribution of Variable Leaf Water-Milfoil, New Hampshire, 2005

total phosphorus (determined by using a strong-acid digest), 

soluble phosphorus (determined by using the Olsen method), 

loosely sorbed phosphorus, iron-bound phosphorus, and iron; 

percentage total organic carbon; percentage moisture; and 

grain-size composition.

Quality Assurance and Quality Control

Quality assurance and quality-control procedures for 

water- and sediment-chemistry data included analyses of 

field blanks and replicate samples. Field blanks provide 

information on bias or potential for contamination of samples 

by collection, processing, and analysis (Spahr and Boulger, 

1997). Concentrations for constituents discussed in this report 

were below the detection limits for the field-blank samples. 

Replicate samples provide information on the variability of 

analytical results caused by sample collection, processing, 

and analysis (Spahr and Boulger, 1997). In this report, the 

constituent concentrations in environmental and replicate 

samples from the water column had a median absolute 

difference of 0.004 mg/L; the absolute differences between 

replicate pairs ranged from 0 to 0.2 mg/L. The constituent 

concentrations in environmental and replicate samples of 

interstitial pore water had a median absolute difference of 

0.05 mg/L; the absolute differences between replicate pairs 

ranged from 0.007 to 0.4 mg/L. The differences in sediment 

grain-size composition between environmental and replicate 

samples were within 3 percent. In summary, these results 

indicate that sample processing and analysis did not introduce 

enough variation in the environmental data to affect the 

interpretation of results.

Quality assurance of the accuracy of the interpolated 

maps was accomplished by two methods. Fifty-five randomly 

selected locations representing variable leaf water-milfoil, 

other SAV, no SAV, or transition points where the interpolated 

map shows changes in the vegetation density were verified 

against video data from the ADGS survey. This comparison 

demonstrated that interpolation of AGDS data in areas 

where the percentage of vegetative bottom cover changes 

substantially over a short distance may affect the accuracy 

of estimated vegetation densities. The smoothing effect of 

interpolation techniques may not accurately portray abrupt 

changes in vegetation density.

The percentage of vegetative bottom cover at each of the 

24 sampling sites was compared to the interpolated values 

for the percentage of bottom cover from the interpolated 

map. Nine of the interpolated values were within 5 percent, 

and 13 of the interpolated values were within 20 percent of 

the percentage of bottom cover measured at the 24 sampling 

sites. The difference in values for two sites in areas with large 

boulders was greater than 20 percent (28 and 43 percent). 

The AGDS data indicated plant material at site QW4 

(37.9 percent), but ground-truth information revealed no SAV. 

Underwater video showed less transparent water and increased 

amounts of flocculent matter on the sediment surface at this 

site, whereas flocculent matter was absent at all other sites. 

The presence of flocculent matter on the lake floor and in the 

water column may yield false identification of SAV by AGDS 

methods (Burczynski and others, 2005a). 

Statistical Methods

The Wilcoxon and Kruskal-Wallis group-comparison 

tests (nonparametric) were used to determine significant 

statistical differences in the ranks of the median concentrations 

of the constituent values (Helsel and Hirsch, 1992). If the 

Kruskal-Wallis test indicated significant differences, the Tukey 

multiple-comparison test was applied to rank-transformed 

data to determine which site types (variable leaf water-milfoil 

sites, other-SAV sites, and no-SAV sites) differed significantly 

(Helsel and Hirsch, 1992). The Spearman rank-correlation 

test was used to determine the strength of association between 

two variables (Helsel and Hirsch, 1992). Water-quality and 

sediment-constituent concentrations compared between and 

among site types were considered statistically different if the 

probability was less than or equal to 5 percent (p < = 0.05). 

Measures chosen to describe the grain-size distribution of 

the sediment samples were the 16th (d16: fine fraction), 

50th (d50: median fraction), and 84th (d84: coarse fraction) 

percentiles of the cumulative-frequency distribution curves 

(Inman, 1952). Figure 6 shows how the d16, d50, and d84 

are determined from two representative curves. In this 

example, 16 percent of the sediment sample from one of the 

other-SAV sites (QW7) is smaller than 0.15 mm, whereas 

16 percent of the sediment sample from one of the variable 

leaf water-milfoil sites (QW12) is smaller than 0.32 mm 

(fig. 6). Statistical differences between site types were 

determined on the basis of these three measures. All statistics 

were analyzed by using SAS software (Statistical Analysis 

Software Institute, 1999, 2002). 

Characterization of the Lake 

Environment 

Swath bathymetry, sidescan-sonar, seismic-reflection 

and sediment-grain-size analysis were used to define the 

lake-floor environment in terms of depth, surficial-sediment 

distribution, and underlying geology. AGDS survey data were 

used to characterize the spatial distribution of SAV and bottom 

types. Water and sediment were sampled to determine selected 

constituent concentrations in the water column, interstitial 

pore water, and the top 10 cm of sediment. Additionally, grain 

size was analyzed in the surficial-sediment samples. Data were 

used to determine whether there were correlations between 

the presence of variable leaf water-milfoil and measures of the 

lake-floor environment, including water and sediment quality, 

and surficial sediments. 
Characterization of the Lake Environment 11

Lake Floor

Moultonborough Bay ranged in depth from less than 1 m 

(within 100 m of the shore) to about 15 m in the deepest parts 

of the localized embayments. The deepest areas within the bay 

were northwest of Smith Point and north of Gansy Island, with 

water depths of 13 and 15 m, respectively (fig. 7). The shallow 

margins of the bay ranged from steep-sided to gently sloping 

with depths increasing toward the centers of the embayments. 

Slopes were steepest along the western and southern margins 

of the southern embayment and along the shoreline north of 

Gansy Island. 

Sidescan-sonar data revealed three distinct patterns 

of acoustic backscatter from the lacustrine sediments of 

Moultonborough Bay: high backscatter, mottled backscatter, 

and low backscatter (fig. 5) (table 2). High-backscatter areas 

were generally along bay margins in water depths less than 

5 m. Exceptions occurred along Gansy Island and in the 

southern embayment where high backscatter was observed 

at 7.5–8 m water depth. High-backscatter areas contained 

sediments that ranged from silt to very coarse sand (median 

grain sizes 0.07 to 1.2 mm, respectively). Isolated pockets 

of high backscatter were detected throughout the bay center 

and along the shoreward margin and were associated with 

boulders or exposed bedrock. Mottled-backscatter areas 

were predominantly along the northwest, north, and eastern 

margins of the bay where water depths were less than 5 m. 

Mottled backscatter was characterized by a diffuse mixture of 

low and high backscatter (fig. 5), with surface sediments that 

ranged in grain size from silt to coarse sand (median grain size 

0.01–0.74 mm). Isolated pockets of gravel and boulders also 

were observed within these regions. Low-backscatter areas 

were found in the deeper waters of the bay (5–15 m water 

depth) and were characterized by fine-grained sediments (silt 

with median grain size less than 0.06 mm), with the finest 

grain sizes collected in the deepest waters. 

The subsurface geology of Moultonborough Bay 

exhibited four distinct acoustic units: bedrock (preglacial), 

glaciolacustrine (glacial), lacustrine (postglacial), and gas 

(fig. 8). Bedrock in this region consists of metamorphic 

and igneous rocks ranging in age from 380 million years 

(Lower Devonian) to 180 (Triassic) million years (Quinn, 

1941; Goldthwait, 1968; Van Diver, 1987; Lyons and others, 

1997). The more easily erodible igneous rocks, such as the 

Winnipesaukee Tonalite (Lyons and others, 1997), were 

deeply scoured by glaciers to form the present bays and 

lakes (Goldthwait, 1968). Seismic-reflection profiles show 

glacial scour of the underlying bedrock. Depth to bedrock 

(as measured from the lake surface) ranged from 2.5 m along 

the bay margins to 27 m in the center embayments (fig. 9). 

Bedrock is commonly exposed along the bay margins and 

less commonly in the central areas as isolated topographic 

Figure 6. Measures chosen to describe the grain-size distribution of sediment 

samples include the 16th (d16: fine fraction), 50th (d50: median grain size), and 

84th (d84: coarse fraction) percentiles of the cumulative-frequency distribution 

curves (using the method of Inman, 1952). (SAV, submerged aquatic vegetation; 

see figure 3 for site locations QW7 and QW12.)

0

20

40

60

80

100

Other-SAV site (QW7)

Variable leaf water-milfoil site (QW12)

GRAIN SIZE, IN MILLIMETERS

0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8

CUMULATIVE DISTRIBUTION OF 

GRAIN SIZE , IN PERCENT

d16

d50

d84

X

X

X

X

X X
12 Relation of Lake-Floor Characteristics to the Distribution of Variable Leaf Water-Milfoil, New Hampshire, 2005

Figure 7. Bathymetry for Moultonborough Bay, Lake Winnipesaukee, New Hampshire. Red line indicates location of seismicreflection profile in figure 8.

-4

-4

-6

-7

-5

-4

-6

-4

-12

-13

-9

-8

-6

-8

-10

-3

-6

-8

-12

-10

-9

-7

-6

-8

-6

-5

-7

Gansy

Island

Birch Hill

Island

Whaleback

Island

Smith

Point

Lees

Mill

71°23'30" 71°23' 71°22'30" 71°22' 71°21'30"

43°42'30"

43°43'

43°43'30"

EXPLANATION 0 1,000 2,000 FEET 500

Base from 2003 National Agricultural

Imagery Program (NAIP), 2005 0 250 500 METERS 125

Depth, in meters

Contour interval is 1 meter

-13 to -16

-10 to -12

-7 to -9

-4 to -6

-1 to -3

No data

Depth contour, in meters

Depth contours are referenced to 

Mean Pool Level, which is defined

to be 504.32 meters above Mean Sea Level 

(NGVD29).

43°44'

Line of seismic-reflection profile (see figure 8)

Moultonborough, NH
Characterization of the Lake Environment 13

highs that form small islands. Bedrock was obscured by gas 

in the overlying sediments (figs. 8 and 9) in some parts of the 

seismic records. 

Sediment accumulations up to approximately 15 m thick 

overlie high-relief bedrock within Moultonborough Bay, 

with the greatest accumulation in the central areas of the 

embayments and thinner layers (less than 1 m thick) along the 

bay margins (fig. 10). Three acoustic signatures were detected 

in the sediments (fig. 8). The first unit was well laminated and 

draped conformably over bedrock, and most likely represents 

glaciolacustrine sediments deposited during the retreat of the 

Laurentide ice sheet. These deposits are probably composed 

of glacial till and outwash, and contain a mixture of rock, 

sand, silt, and clay, which is characteristic of glaciolacustrine 

deposits (Goldthwait, 1968; Van Diver, 1987; Benn and Evans, 

1998). Along the bay margins, this unit was truncated by a 

strong, flat reflector that may represent an erosional surface 

formed during periods of lower lake level. The second unit 

was generally acoustically transparent, with the exception of 

closely spaced internal reflectors in small-scale topographic 

lows (fig. 8), and is thought to represent modern (Holocene) 

lacustrine deposits. Internal reflectors present within the 

topographic lows may represent cyclic deposition within the 

lake. A third unit is characterized by gas in the sediments 

(fig. 8). Gas was found within the central portions of the 

embayments and obscures parts of the seismic record in these 

areas. The gas was probably generated by decomposition of 

organic matter in the Holocene (post-glacial) lake sediments. 

Moultonborough Bay was characterized by three 

lake-floor environments: rocky nearshore, mixed nearshore, 

and muddy basin (fig. 11). Rocky nearshore environments 

were mapped in water shallower than 5 m and consisted 

of high-backscatter coarse-grained sediments, boulders, 

and bedrock outcrop. Seismic-reflection profiles show thin 

accumulations of glaciolacustrine and modern (Holocene) 

sediments and underlying bedrock close to or at the lake 

floor in these areas. Mixed nearshore environments were 

also mapped in water shallower than 5 m; these areas 

are characterized by mottled backscatter and sediments 

ranging from silt to coarse sand. Data collected with bottom 

photographs and video revealed differing densities of aquatic 

vegetation in these areas. Seismic-reflection profiles show 

an accumulation of glaciolacustrine and modern (Holocene) 

sediment from less than 1 to 5 m thick and exposures of 

bedrock in isolated areas along the bay margin. Muddy basin 

environments were mapped in water deeper than 5 m and 

were characterized by low-backscatter fine-grained sediments 

(silt). This low-backscatter sediment represents modern 

deposition within the bay and most likely corresponds to 

the upper acoustically transparent unit interpreted from the 

seismic-reflection profiles.

Table 2. Lake-floor environments, sidescan-sonar backscatter patterns, descriptions, sediment textures, and water depths in 

Moultonborough Bay, Lake Winnipesaukee, New Hampshire. 

[m, meters; mm, millimeters; <, less than]

Lake-floor 

environment

Backscatter 

pattern Description Sediment texture

Water depth 

(meters)

Rocky nearshore High Primarily along bay 

margin; bedrock outcrop 

and boulders; thin 

accumulation of sediment; 

high-relief

Silt to very coarse sand, 

(median grain size 

0.07 to 1.2 mm); 

boulders and exposure 

of bedrock

< 5

Mixed nearshore Mottled Primarily along bay margin; 

diffuse mixture of low 

and high backscatter; 

isolated pockets of highbackscatter associated 

with gravel and boulders; 

thickness of sediment 

ranges from < 1 to 5 m; 

moderate to high-relief

Silt to coarse sand, 

(median grain size 

0.01–0.74 mm); 

isolated gravel, 

boulders

< 5

Muddy basin Low Located in deep waters of 

the bay; uniform lowbackscatter pattern; 

thickest accumulation of 

sediment (1 to 15 m); 

low relief 

Silt, (median grain size 

< 0.06 mm)

5–15
14 Relation of Lake-Floor Characteristics to the Distribution of Variable Leaf Water-Milfoil, New Hampshire, 2005

Figure 8. Seismic-reflection profile in Moultonborough Bay, Lake Winnipesaukee, New Hampshire: (

A) original image and (

B) interpreted profile 

showing bedrock, glaciolacustrine sediments, and lacustrine sediments. Gas is present in the glaciolacustrine and lacustrine sediments. (See figure 6 for location; multiples are “echos“ of the seismic signal.) 

TWO-WAY TRAVELTIME (MS)

0

10203040

Multiple

Gas

Lake floor

APPROXIMATE DEPTH, IN METERS

A

B

Lake floor

TWO-WAY TRAVELTIME (MS)

0

10203040

APPROXIMATE DEPTH, IN METERSMultiple Gas

0

1020

30

0

1020

30

Vertical Exaggeration: ~30:1

0 500 FEET

0 250 METERS

250

E W

E W

EXPLANATION

Gas

BedrockGlaciolacustrine 

Lacustrine (Holocene)
Characterization of the Lake Environment 15

Figure 9. Depth to bedrock as measured from the lake surface in Moultonborough Bay, Lake Winnipesaukee, New Hampshire, 

determined through the use of seismic-reflection data.

71°23'30" 71°23' 71°22'30" 71°22' 71°21'30"

43°42'30"

43°43'

43°43'30"

43°44'

Gansy

Island Birch Hill

Island

Whaleback

Island

Gas

Gas

Gas

Gas

Lees

Mill

Smith

Point

EXPLANATION

Base from 2003 National Agricultural

Imagery Program (NAIP), 2005

Depth to bedrock

from lake surface, 

in meters

Gas in sediment

(depth unknown)

No data

2

27

0 1,000 2,000 FEET 500

0 250 500 METERS 125

Moultonborough, NH
16 Relation of Lake-Floor Characteristics to the Distribution of Variable Leaf Water-Milfoil, New Hampshire, 2005

Figure 10. Total sediment thickness in Moultonborough Bay, Lake Winnipesaukee, New Hampshire, determined through the use 

of seismic-reflection data.

71°23'30" 71°23' 71°22'30" 71°22' 71°21'30"

43°42'30"

43°43'

43°43'30"

43°44'

Gansy

Island Birch Hill

Island

Whaleback

Island

Gas

Gas

Gas

Gas

Lees

Mill

Smith

Point

EXPLANATION

Base from 2003 National Agricultural

Imagery Program (NAIP), 2005

Total sediment

thickness, in meters

Gas in sediment,

(depth unknown)

No data

less than 3

greater than 9

0 1,000 2,000 FEET 500

0 250 500 METERS 125

Moultonborough, NH
Characterization of the Lake Environment 17

Figure 11. Three lake-floor environments in Moultonborough Bay, Lake Winnipesaukee, New Hampshire, as interpreted from 

geophysical and sediment-sample data.

71°23'30" 71°23' 71°22'30" 71°22' 71°21'30"

43°42'30"

43°43'

43°43'30"

43°44'

EXPLANATION

Base from 2003 National Agricultural

Imagery Program (NAIP), 2005

Lake-floor environments

Mixed nearshore No data

Rocky nearshore Muddy basin

Gansy

Island

Birch Hill

Island

Whaleback

Island

Moultonborough, NH

Lees

Mill

Smith

Point

0 1,000 2,000 FEET 500

0 250 500 METERS 125
18 Relation of Lake-Floor Characteristics to the Distribution of Variable Leaf Water-Milfoil, New Hampshire, 2005

Submerged Aquatic Vegetation

AGDS data were used to generate an interpolated map 

showing the percentage of SAV, including variable leaf watermilfoil, native milfoil, bassweed, pipewort, and other species 

(table 1). SAV was predominantly found near shoreward 

margins and at depths ranging from less than 1 m to about 

4 m. Overall, 86 percent of the littoral zone (the area along the 

margins of the bay and islands that extends from 0 to 4.3 m 

in water depth) had some SAV (fig. 12). AGDS data also 

indicated that approximately 36 percent of the littoral-zone 

area had SAV bottom cover of 25 percent or less; 43 percent 

had moderate SAV bottom cover of greater than 25 percent 

and less than 75 percent; and 7 percent had heavy SAV bottom 

cover of 75 percent or greater. 

Water Quality of the Water Column and of 

Interstitial Pore Water 

Summary statistics were determined for selected field 

parameters (specific conductance, pH, and temperature). The 

specific conductance ranged from 63 to 67 μs/cm for watercolumn samples and from 61 to 207 μs/cm for interstitial porewater samples (table 3). The ranges of specific conductance 

for water-column and interstitial pore-water samples were 

significantly different (p < 0.0001). Similarly, pH values of the 

interstitial pore-water samples had a significantly greater range 

(p < 0.0001) than pH values of the water-column samples 

(5.9 to 7.0 and 6.6 to 7.2 standard units, respectively) (table 3). 

Temperatures measured in the water-column samples were 

significantly higher (p < 0.0001) than temperatures measured 

in the interstitial pore-water samples, (25.3 to 29.5oC and 

22.4 to 25.6oC, respectively) (table 3). 

Most water-column constituent concentrations were 

similar among sampling sites. An exception was iron 

concentrations, which ranged from 0.07 to 0.39 mg/L 

(table 4). An exceptionally high total ammonia plus organic 

nitrogen value of 6 mg/L was recorded at site QW4. An 

excessive amount of flocculent matter was observed at this 

site; although the sample was filtered, the flocculent matter 

may have affected the concentration measured. 

Constituent concentrations in interstitial pore-water 

samples had a greater range and were generally higher than 

concentrations measured in the water-column samples for 

the same constituent (table 4). Total ammonia plus organic 

nitrogen concentrations in interstitial pore-water samples 

ranged from less than 0.25 to 3.6 mg/L. The three highest 

concentrations were measured in samples collected at sites 

QW1 (3.6 mg/L); QW3 (3.4 mg/L), in the northwestern part 

of the bay near Lees Mill; and at QW20 (3.0 mg/L), in the 

southeastern part of the bay across from Smith Point (fig. 3). 

Total phosphorus concentrations generally were low and 

ranged from 0.01 to 1.01 mg/L (table 4).

Chemical Characteristics of the Surficial 

Sediment on the Lake Floor

Concentrations of potassium and iron in the surficialsediment samples ranged widely among sampling sites 

(8,300 to 29,000 mg/kg and 9,400 to 30,000 mg/kg, 

respectively) (table 5). Total nitrite, total nitrate, ammonia plus 

ammonium, and phosphorus measured by the Olsen method 

were rarely detected. Concentrations of total ammonia plus 

organic nitrogen were generally low and similar in the samples 

collected from all of the sites. A strong acid digest method 

was used to measure the concentrations of all recoverable 

phosphorus in the sediment samples; these concentrations 

ranged from 210 to 1,100 mg/kg. Concentrations of 

loosely sorbed phosphorus ranged from 2.0 to 11 mg/L 

and concentrations of iron-bound phosphorus ranged from 

1.4 to 3.1 mg/L. The percentage of total organic carbon 

(TOC) measured in the sediment samples ranged from 0.19 to 

8.13 percent (table 5). The three highest percentages of TOC 

were measured in samples from sites QW3 (3.46 percent), 

QW6 (6.67 percent), and QW21 (8.13 percent). Samples 

collected at these three sites also had the highest percentage of 

fine sediment grains (silt) (table 6).

Characterization of the Distribution of 

Variable Leaf Water-Milfoil 

Results of the EcoSAV and VBT analysis from the 

24 sampling sites (fig. 3) were used to differentiate variable 

leaf water-milfoil from other SAV in Moultonborough 

Bay. About 24 reports containing the summary data for 

approximately 20 consecutive points were generated and 

evaluated at each sampling site. To determine bottom-typing 

characteristics, 116 reports were used for the 9 variable leaf 

water-milfoil sites, 107 reports were used for the 7 other-SAV 

sites, and 88 reports were used for the 8 no-SAV sites. 

Significant differences were determined in the percentage 

of vegetative bottom cover (p < 0.0001), echo energy level 

for the segment directly above the first bottom echo (E0

) 

(p < 0.0001), and FD of the bottom sediments (p < 0.0001) 

between the variable leaf water-milfoil and other-SAV sites 

(fig. 13). The percentage of bottom cover at the 24 sampling 

sites ranged from 59 to 95 percent for the variable leaf watermilfoil sites and from 1 to 95 percent for the other-SAV sites 

(fig. 13A). E0

 is a measure of the reflected-energy level from 

material, including plants, directly above the lake bottom 

and ranged from 0.000005 to 0.00002 dB for variable leaf 

water-milfoil and from 0.0000015 to 0.000005 dB for the 

other-SAV sites (fig. 13B). FD ranged from 1.03 to 1.06 for 

variable leaf water-milfoil and from 0.92 to 1.05 for the otherSAV sites (fig. 13C). For this study, an SAV site was labeled 

variable leaf water-milfoil if the percentage of vegetative 
Characterization of the Distribution of Variable Leaf Water-Milfoil 19

Figure 12. Distribution and percentage of the lake floor covered by submerged aquatic vegetation in Moultonborough Bay, 

Lake Winnipesaukee, New Hampshire.

Lees

Mill

Smith

Point

71°23'30" 71°23' 71°22'30" 71°22' 71°21'30"

43°42'30"

43°43'

43°43'30"

43°44'

EXPLANATION

Percentage of the lake floor covered 

by submerged aquatic vegetation

0

1 to 15

31 to 45

46 to 60

61 to 80

81 to 100

no data

16 to 30

Base from 2003 National Agricultural

Imagery Program (NAIP), 2005

Gansy

Island

Birch Hill

Island

Whaleback

Island

Moultonborough, NH

0 1,000 2,000 FEET 500

0 250 500 METERS 125
20 Relation of Lake-Floor Characteristics to the Distribution of Variable Leaf Water-Milfoil, New Hampshire, 2005 Table 3. Site numbers, site names, locations, water depths, selected field parameters, median surficial-sediment grain sizes, and percentages of vegetative bottom cover for sampling sites in Moultonborough Bay, Lake Winnipesaukee, New Hampshire. [SAV, submerged aquatic vegetation; WC, water column; IW, interstitial pore water; μS/cm, microsiemens per centimeter; °C, degrees Celsius; --, not applicable] U.S. Geological Survey site number Site name Latitude (decimal degrees) Longitude (decimal degrees) Water depth (meters) Specific conductance (μS/cm) pH Temperature (oC) Median grain size (milli- meters) Percentage of vegetative bottom cover WC IW WC IW WC IW Variable leaf water-milfoil sites 434326071232801 QW8 43.72576 71.39118 1.27 63 88 6.8 6.5 28.0 24.8 0.71 76.0 434321071230601 QW11 43.72240 71.38515 2.06 65 97 7.0 5.9 28.1 24.8 0.61 59.2 434326071230101 QW12 43.72402 71.38366 3.19 64 105 7.0 6.1 28.1 24.8 0.60 72.8 434328071223401 QW17 43.72457 71.37616 2.45 65 132 7.1 6.6 28.3 24.9 0.70 63.0 434305071222301 QW18 43.71819 71.37305 2.89 65 122 7.0 6.4 28.2 25.2 0.66 80.2 434244071213401 QW20 43.71214 71.35958 3.85 66 67 7.0 7.0 26.2 24.9 0.81 64.9 434242071213101 QW22 43.71178 71.35872 2.18 65 83 7.1 6.6 27.1 25.2 0.60 94.6 434306071214201 QW26 43.71833 71.36139 3.41 66 141 7.1 6.8 27.8 22.4 0.62 67.0 434311071221401 QW27 43.71972 71.37056 2.86 66 140 7.0 6.3 28.0 24.8 0.62 75.0 Median -- -- 2.86 65 105 7.0 6.5 28.0 24.8 0.62 72.8 Other-SAV sites 434339071230501 QW3 43.72755 71.38481 1.94 65 207 6.8 6.3 28.6 22.9 0.52 95.0 434337071232401 QW5 43.72680 71.39007 1.33 63 62 6.9 6.5 28.0 25.0 0.58 15.9 434335071232801 QW7 43.72637 71.39064 1.22 63 103 6.8 6.2 28.0 24.0 0.41 70.9 434314071230701 QW9 43.72062 71.38543 1.51 64 122 7.0 6.5 28.2 24.7 0.54 32.5 434341071224301 QW14 43.72799 71.37865 1.27 66 93 6.9 6.3 27.9 24.9 0.28 7.47 434331071222801 QW16 43.72529 71.37446 1.50 65 105 7.1 6.3 28.1 25.6 0.42 15.8 434305071213601 QW19 43.71798 71.35988 1.36 66 114 7.2 5.9 27.8 25.1 0.18 17.5 Median -- -- 1.43 65 105 6.9 6.3 28.0 24.9 0.42 17.5 No-SAV sites 434341071231001 QW1 43.72801 71.38609 3.41 67 67 6.6 6.9 27.5 23.1 0.86 1.23 434341071231501 QW4 43.72806 71.38750 3.89 64 73 6.9 6.1 28.5 25.4 0.91 137.9 434337071231801 QW6 43.72686 71.38813 4.41 64 61 6.7 6.9 25.3 24.1 0.04 0.8 434315071230901 QW10 43.72071 71.38594 1.37 64 110 7.0 6.4 28.2 24.9 0.57 0.33 434335071222701 QW15 43.72645 71.37416 1.38 66 124 7.1 6.4 27.9 24.9 0.47 0.0 434249071213101 QW21 43.71356 71.35853 1.46 66 122 7.0 6.4 28.6 24.6 0.33 0.0

434246071222901 QW23 43.71272 71.37468 1.40 65 129 7.2 6.4 28.9 24.9 0.19 0.0

434307071230301 QW25 43.71853 71.38410 1.38 65 117 7.1 6.3 29.5 24.9 0.24 0.43

Median -- -- 1.43 65 114 7.0 6.4 28.4 24.9 0.40 0.38

 1 False-positive result.
Characterization of the Distribution of Variable Leaf Water-Milfoil 21

Table 4. Concentrations of potassium, dissolved nitrite plus nitrate, ammonium nitrogen, total ammonia plus organic nitrogen, total phosphorus, dissolved orthophosphorus, iron, and total organic carbon measured in water samples from sampling sites in Moultonborough Bay, Lake Winnipesaukee, New Hampshire.[SAV, submerged aquatic vegetation; WC, water column; IW, interstitial water; <, less than; mg/L, milligrams per liter]

Site 

name

Potassium

(mg/L)

Dissolved

nitrite plus 

nitrate

 (mg/L)

Ammonium 

nitrogen

(mg/L)

Total ammonia 

plus organic 

nitrogen

(mg/L)

Total 

phosphorus

(mg/L)

Dissolved 

orthophosphorus

(mg/L)

Iron

(mg/L)

Total 

organic carbon

(mg/L)

WC IW WC IW WC IW WC IW WC IW WC IW WC IW WC IW

Variable leaf water-milfoil sites

QW8 0.6 1 <0.05 <0.05 <0.05 0.3 0.3 1.1 0.01 0.08 <0.01 <0.01 0.14 4.8 5.3 7.2

QW11 0.6 1 <0.05 <0.05 <0.05 <0.05 0.3 <0.25 0.01 0.04 <0.01 0.02 0.11 3.8 4.5 4.8QW12 0.6 1 <0.05 0.07 0.05 0.1 0.3 0.3 0.01 0.07 <0.01 <0.01 0.13 6.6 5.1 4.1QW17 0.6 2 <0.05 <0.05 <0.05 0.9 0.3 1.5 0.01 0.53 <0.01 0.03 0.11 4.1 5.0 5.0QW18 0.6 1 <0.05 <0.05 <0.05 0.5 <0.25 0.7 0.01 0.07 <0.01 <0.01 0.09 6.9 3.9 4.8

QW20 0.6 4 <0.05 <0.05 <0.05 <0.05 0.3 3.0 0.01 0.52 <0.01 <0.01 0.09 20 4.0 5.3QW22 0.6 1 <0.05 <0.05 <0.05 0.3 <0.25 0.6 0.01 0.15 <0.01 <0.01 0.07 1.9 3.8 4.5QW26 0.6 3 <0.05 <0.05 <0.05 0.3 <0.25 1.4 0.01 1.01 <0.01 <0.01 0.09 29 4.7 5.5QW27 0.6 1 <0.05 <0.05 <0.05 0.4 <0.25 0.9 0.01 0.07 <0.01 0.01 0.11 8.7 4.4 7.3Median 0.6 1 <0.05 <0.05 <0.05 0.3 0.3 0.9 0.01 0.08 <0.01 <0.01 0.11 7.0 4.5 5.0

Other-SAV sites

QW3 0.6 2.2 <0.05 <0.05 <0.05 2.1 <0.25 3.4 0.01 0.18 <0.01 0.01 0.21 9.1 5.8 13

QW5 0.6 0.6 <0.05 0.05 <0.05 <0.05 0.3 0.4 0.01 0.01 <0.01 <0.01 0.15 0.2 5.5 5.7

QW7 0.6 0.8 <0.05 <0.05 <0.05 <0.05 0.4 0.5 0.01 0.05 <0.01 <0.01 0.24 4.3 5.5 7.1

QW9 0.6 1.6 <0.05 <0.05 <0.05 0.2 0.3 0.3 0.01 0.07 <0.01 <0.01 0.13 4.8 4.8 3.9QW14 0.6 1.2 <0.05 <0.05 <0.05 0.1 0.3 0.3 0.01 0.02 <0.01 <0.01 0.22 3.8 5.0 5.3QW16 0.6 1.1 <0.05 <0.05 <0.05 0.2 0.3 0.4 0.01 0.02 <0.01 <0.01 0.15 3.2 4.4 4.0QW19 0.6 1.1 <0.05 <0.05 <0.05 0.1 <0.25 0.3 0.01 0.24 <0.01 <0.01 0.08 1.6 3.7 6.3Median 0.6 1.1 <0.05 <0.05 <0.05 0.1 0.3 0.4 0.01 0.05 <0.01 <0.01 0.15 4.0 5.0 5.7

No-SAV sites

QW1 0.6 1.7 <0.05 <0.05 <0.05 0.1 0.3 3.6 0.01 0.40 <0.01 <0.01 0.39 9.8 5.8 7.3QW4 0.5 1.1 <0.05 <0.05 <0.05 <0.05 6.0 0.3 0.20 0.02 <0.01 <0.01 0.18 1.6 5.7 6.3QW6 0.6 0.6 <0.05 <0.05 <0.05 0.2 0.3 0.4 0.01 0.01 <0.01 <0.01 0.23 0.3 5.8 5.5

QW10 0.6 2.9 <0.05 <0.05 <0.05 0.3 0.3 0.5 0.01 0.10 <0.01 <0.01 0.14 3.3 4.5 3.2QW15 0.6 1.3 <0.05 <0.05 <0.05 0.3 0.3 0.5 0.01 0.14 <0.01 0.016 0.14 6.0 4.8 3.9QW21 0.6 1.8 <0.05 <0.05 <0.05 0.4 0.3 0.6 0.01 0.22 <0.01 <0.01 0.08 3.9 4.1 3.3QW23 0.6 2.1 <0.05 <0.05 0.06 <0.05 0.3 <0.25 0.14 0.01 <0.01 <0.01 0.10 2.4 1.0 4.2QW25 0.6 1.7 <0.05 <0.05 <0.05 0.2 <0.25 0.3 0.01 0.11 <0.01 0.013 0.13 6.7 4.5 2.9Median 0.6 1.7 <0.05 <0.05 <0.05 0.2 0.3 0.45 0.01 0.10 <0.01 <0.01 0.14 4.0 4.7 4.1
22 Relation of Lake-Floor Characteristics to the Distribution of Variable Leaf Water-Milfoil, New Hampshire, 2005

Table 5. pH (ratio); concentrations of potassium, total nitrate, total nitrite, ammonia plus ammonium, total ammonia plus organic 

nitrogen, phosphorus (strong acid digest), phosphorus (Olsen method), loosely sorbed phosphorus, iron-bound phosphorus, and iron; 

percent total organic carbon; and percent moisture measured in sediment samples from sampling sites in Moultonborough Bay, 

Lake Winnipesaukee, New Hampshire.

[SAV, submerged aquatic vegetation; <, less than; mg/kg, milligrams per kilogram; mg/L, milligrams per liter; %, percent]

Site 

name

pH 

1

(ratio)

Potassium

(mg/kg)

Total

nitrate

(mg/kg)

Total

nitrite

(mg/kg)

Ammonia plus 

ammonium

(mg/kg)

Total ammonia 

plus organic 

nitrogen

(mg/kg)

Phosphorus

2

(strong acid 

digest)

(mg/kg)

Variable leaf water-milfoil sites

QW8 6.4 19,000 <0.01 <0.01 <0.01 0.02 680

QW11 6.3 10,000 <0.01 <0.01 <0.01 0.03 390

QW12 6.0 8,900 <0.01 <0.01 <0.01 0.04 540

QW17 6.4 16,000 <0.01 <0.01 <0.01 0.02 320

QW18 6.7 8,300 <0.01 <0.01 <0.01 0.02 570

QW20 7.1 10,000 <0.01 <0.01 <0.01 0.03 320

QW22 6.2 12,000 <0.01 <0.01 <0.01 0.02 260

QW26 7.1 16,000 <0.01 <0.01 <0.01 0.01 290

QW27 6.3 14,000 <0.01 <0.01 <0.01 0.02 300

Median 6.4 12,000 <0.01 <0.01 <0.01 0.02 320

Other-SAV sites

QW3 6.3 13,000 <0.01 <0.01 <0.01 0.11 550

QW5 6.5 16,000 <0.01 <0.01 <0.01 0.02 490

QW7 6.2 19,000 <0.01 <0.01 <0.01 0.03 450

QW9 6.3 29,000 <0.01 <0.01 <0.01 0.02 380

QW14 7.4 17,000 <0.01 <0.01 <0.01 0.02 300

QW16 7.2 17,000 <0.01 <0.01 <0.01 0.03 300

QW19 7.2 16,000 <0.01 <0.01 <0.01 0.02 210

Median 6.5 17,000 <0.01 <0.01 <0.01 0.02 380

No-SAV sites

QW1 6.2 13,000 <0.01 <0.01 <0.01 0.02 640

QW4 6.2 12,000 <0.01 <0.01 <0.01 0.02 490

QW6 6.6 14,000 <0.01 <0.01 <0.01 0.14 1,100

QW10 6.4 20,000 <0.01 <0.01 <0.01 0.02 300

QW15 6.4 15,000 <0.01 <0.01 <0.01 0.02 270

QW21 6.8 9,700 <0.01 <0.01 <0.01 0.05 340

QW23 6.3 14,000 <0.01 <0.01 <0.01 0.02 320

QW25 6.8 19,000 <0.01 <0.01 <0.01 0.02 350

Median 6.4 14,000 <0.01 <0.01 <0.01 0.02 345
Characterization of the Distribution of Variable Leaf Water-Milfoil 23

Table 5. pH (ratio); concentrations of potassium, total nitrate, total nitrite, ammonia plus ammonium, total ammonia plus organic 

nitrogen, phosphorus (strong acid digest), phosphorus (Olsen method), loosely sorbed phosphorus, iron-bound phosphorus, and iron; 

percent total organic carbon; and percent moisture measured in sediment samples from sampling sites in Moultonborough Bay, 

Lake Winnipesaukee, New Hampshire.—Continued

[SAV, submerged aquatic vegetation; <, less than; mg/kg, milligrams per kilogram; mg/L, milligrams per liter; %, percent]

Site 

name

Phosphorus 

3

(Olsen method)

(mg/kg)

Loosely sorbed 

phosphorus

(mg/L)

Ironbound

phosphorus

(mg/L)

Iron

(mg/kg)

Total

organic 

carbon 

(%)

Moisture 

(%)

Variable leaf water-milfoil sites

QW8 <10 6.2 2.2 17,000 0.33 0.18

QW11 11 10 3.1 11,000 0.34 0.18

QW12 <10 7.9 2.3 13,000 0.37 0.26

QW17 <10 6.2 1.7 15,000 0.38 0.24

QW18 <10 8.2 2.5 14,000 0.29 0.20

QW20 <10 5.6 2.9 14,000 0.28 0.25

QW22 <10 10 2.2 9,400 0.19 0.20

QW26 <10 6.0 1.9 14,000 0.26 0.23

QW27 <10 8.2 2.0 11,000 0.26 0.19

Median <10 7.9 2.2 14,000 0.26 0.20

Other SAV sites

QW3 <10 3.0 2.6 18,000 3.46 0.28

QW5 <10 9.2 1.5 13,000 0.35 0.19

QW7 <10 6.7 1.4 13,000 0.59 0.18

QW9 <10 7.2 2.5 16,000 0.35 0.17

QW14 <10 8.4 2.1 10,000 0.44 0.18

QW16 <10 5.0 3.1 12,000 0.67 0.17

QW19 <10 8.4 2.1 12,000 0.60 0.23

Median <10 7.2 2.1 13,000 0.59 0.18

No SAV sites

QW1 <10 6.2 2.5 21,000 0.27 0.15

QW4 12 6.8 2.5 13,000 0.45 0.24

QW6 12 2.0 3.1 30,000 6.67 0.25

QW10 <10 8.2 1.8 14,000 0.22 0.19

QW15 <10 3.0 3.1 15,000 0.69 0.23

QW21 <10 3.9 2.4 22,000 8.13 0.23

QW23 <10 11 1.8 12,000 0.20 0.20

QW25 <10 6.8 1.5 16,000 0.32 0.22

Median <10 6.5 2.4 15,500 0.38 0.22

1 Sediment pH (ratio) was determined as a paste of two parts sediment to one part distilled water.

2 Sample is digested by a four-acid mixture of HNO3

, HF, HClO4, and HCL to obtain a near total digest of 30 elements on low mineralized samples.

3 The soil extraction is derived from the Olsen (NaHCO3

) soil test for phosphorus.
24 Relation of Lake-Floor Characteristics to the Distribution of Variable Leaf Water-Milfoil, New Hampshire, 2005 Table 6. Percentage of the total sediment samples that were finer than the sieve diameter from sampling sites in Moultonborough Bay, Lake Winnipesaukee, New Hampshire. [SAV, submerged aquatic vegetation; mm, millimeters; -- not calculated] Site name Sediment, total sieve diameter, percent finer than 0.038 (mm) Sediment, total sieve diameter, percent finer than 0.053 (mm) Sediment, total sieve diameter, percent finer than 0.075 (mm) Sediment, total sieve diameter, percent finer than 0.106 (mm) Sediment, total sieve diameter, percent finer than 0.150 (mm) Sediment, total sieve diameter, percent finer than 0.212 (mm) Sediment, total sieve diameter, percent finer than 0.30 (mm) Sediment, total sieve diameter, percent finer than 0.425 (mm) Sediment, total sieve diameter, percent finer than 0.60 (mm) Variable leaf water-milfoil sites QW8 1 1 1 2 3 4 10 21 39 QW11 0.1 0.2 0.3 0.4 1 4 13 28 49 QW12 1 1 1 2 2 5 13 30 50 QW17 0.1 1 1 2 3 4 8 18 39 QW18 0 0.2 1 1 2 5 12 25 45 QW20 2 0.1 0.2 0.5 1 3 7 17 33 QW22 1 2 2 3 4 8 16 30 51 QW26 2 1 1 2 3 4 11 26 48 QW27 2 2 2 3 5 8 15 29 48 Median percent 1 1 1 2 3 4 12 26 48 Other-SAV sites QW3 16 16 17 19 20 25 31 41 56 QW5 3 3 3 4 5 11 21 36 51 QW7 6 6 8 10 16 24 37 51 65 QW9 1 1 1 3 5 14 22 35 57 QW14 0.1 0.4 2 9 22 35 53 73 90 QW16 9 10 13 16 21 30 39 51 64 QW19 1 2 3 9 19 82 96 99 99 Median percent 3 3 3 9 19 25 37 51 64 No-SAV sites QW1 6 6 6 6 7 9 13 20 33 QW4 2 2 2 3 3 5 8 16 29 QW6 88 92 93 96 98 100 100 100 100 QW10 2 2 4 8 12 16 23 34 53 QW15 5 6 8 9 11 18 28 44 64

QW21 21 23 24 27 31 37 46 61 73

QW23 0.2 0.4 5 7 23 63 91 98 99

QW25 4 5 7 10 17 28 51 69 81

Median percent 4 5 6 9 15 23 37 52 69
Characterization of the Distribution of Variable Leaf Water-Milfoil 25

Table 6. Percentage of the total sediment samples that were finer than the sieve diameter from sampling sites in Moultonborough Bay, Lake Winnipesaukee, 

New Hampshire.—Continued

[SAV, submerged aquatic vegetation; mm, millimeters; --, not calculated]

Site name

Sediment, 

total sieve 

diameter, 

percent finer 

than 0.850

(mm)

Sediment, 

total sieve 

diameter, 

percent finer 

than 1.180

(mm)

Sediment,

 total sieve 

diameter, 

percent finer 

than 1.70

(mm)

Sediment, 

total sieve 

diameter, 

percent finer 

than 2.36

(mm)

Sediment, 

total sieve 

diameter, 

percent finer 

than 3.35

(mm)

Sediment, 

total sieve 

diameter, 

percent finer 

than 4.75

(mm)

Sediment, 

total sieve 

diameter, 

percent finer 

than 6.70

(mm)

Sediment, 

total sieve 

diameter, 

percent finer 

than 9.50

(mm)

Sediment, 

total sieve 

diameter, 

percent finer 

than 12.50

(mm)

Variable leaf water-milfoil sites

QW8 62 79 94 97 98 99 100 100 100

QW11 72 87 97 -- -- -- -- -- --

QW12 72 88 99 -- -- -- -- -- --

QW17 63 81 95 98 100 100 100 100 100

QW18 65 83 98 -- -- -- -- -- --

QW20 53 69 85 89 92 93 94 98 100

QW22 71 85 97 -- -- -- -- -- --

QW26 69 85 98 -- -- -- -- -- --

QW27 69 83 96 -- -- -- -- -- --

Median percent 69 83 97 97 98 99 100 100 100

Other-SAV sites

QW3 74 87 98 -- -- -- -- -- --

QW5 68 80 92 95 97 99 100 100 100

QW7 79 89 97 -- - -- -- -- --

QW9 76 87 96 99 100 100 100 100 100

QW14 97 99 100 -- -- -- -- -- --

QW16 77 86 94 97 99 100 100 100 100

QW19 100 100 100 -- -- -- -- -- --

Median percent 77 87 97 97 99 100 100 100 100

No-SAV sites

QW1 49 66 86 91 94 97 99 100 100

QW4 46 66 91 94 96 97 99 100 100

QW6 100 100 100 -- -- -- -- -- --

QW10 76 90 98 -- -- -- -- -- --

QW15 81 90 97 -- -- -- -- -- --

QW21 85 93 98 -- -- -- -- -- --

QW23 100 100 100 -- -- -- -- -- --

QW25 91 96 100 100 100 100 100 100 100

Median percent 83 91 98 94 96 97 99 100 100
26 Relation of Lake-Floor Characteristics to the Distribution of Variable Leaf Water-Milfoil, New Hampshire, 2005

Figure 13. Comparison of data from the acoustic ground-discrimination system survey reports for (A) vegetative 

cover, (B) reflected acoustic intensity of the sediments and vegetation, and (C) fractal dimension among variable leaf 

water-milfoil sites, other-SAV sites, and no-SAV sites in Moultonborough Bay, Lake Winnipesaukee, New Hampshire. 

[SAV, submerged aquatic vegetation; results of Tukey’s multiple comparison test (Helsel and Hirsch, 1992) among site 

types are presented as letters, and distributions with at least one letter in common do not differ significantly.] REFLECTED ACOUSTIC INTENSITY FROM SEDIMENTS AND VEGETATION, IN DECIBELS

B

A

C

0.0000001

0.000001

0.00001

0.0001

A B

C

0

10

20

30

40

50

60

70

80

90

100

VEGETATIVE COVERAGE, IN PERCENT

0.60

0.65

0.70

0.75

0.80

0.85

0.90

0.95

1.00

1.05

1.10

FRACTAL DIMENSION

A

B

A

B B

(N = 116) (N = 107) (N = 88)

EXPLANATION

75th percentile

10th percentile

90th percentile

50th percentile (Median)

25th percentile

Variable leaf water-milfoil sites

Other-SAV sites

Multiple comparison group - A No-SAV sites

N = Number of samples
Characterization of the Distribution of Variable Leaf Water-Milfoil 27

bottom cover was greater than 59 percent, E0 was greater 

than or equal to 0.000005 dB, and FD was greater than or 

equal to 1.03. Two other-SAV sites (QW3 and QW7, table 3) 

had percentages of vegetative cover that were within the 

range defined for variable leaf water-milfoil (59–95 percent). 

Although the percentage of bottom cover and FD values for 

site QW3 were within the defined ranges for variable leaf 

water-milfoil (95 percent and 1.04 to 1.06, respectively), the 

E0

 values were all equal to 0.0000008, less than the lower E0

limit used to define variable leaf water-milfoil (0.000005). 

Site QW7 met all three criteria for a variable leaf watermilfoil site. Continuous underwater video at this site showed 

that although QW7 was designated as an other-SAV site, 

some variable leaf water-milfoil was present. Therefore, the 

inclusion of the area around site QW7 on the interpolated map 

of the distribution and percentage of bottom cover of variable 

leaf water-milfoil was considered appropriate, although the 

percentage of variable leaf water-milfoil may be overestimated 

in that area. Overall, evaluation of the data indicated that these 

three criteria were useful in minimizing the amount of other 

SAV that may have been erroneously qualified as variable 

leaf water-milfoil on the interpolated map. Acoustic data are 

especially useful in distinguishing variable leaf water-milfoil 

from other types of SAV because variable leaf water-milfoil 

primarily forms dense, homogenous beds.

AGDS data were used as input in GIS to create a 

vegetation map that distinguished variable leaf water-milfoil 

from other types of SAV in Moultonborough Bay (fig. 14). 

This map shows that approximately 21 percent of the littoral 

zone was characterized to be variable leaf water-milfoil 

at 59 percent or greater bottom cover. In addition, depth, 

sediment texture, and percentage of vegetative bottom cover 

were used to define areas that may be susceptible to future 

infestation by variable leaf water-milfoil. When depth was 

less than 4.3 m, the FD was greater than or equal to 1.03, 

and the percentage of vegetative bottom cover was less than 

59 percent, interpolation was used to define areas that may 

be susceptible to variable leaf water-milfoil spread (fig. 14). 

These criteria were used to identify areas that had habitat 

conducive to the growth of variable leaf water-milfoil but, at 

the time of the study (2005), did not have high percentages 

(greater than 59 percent) of variable leaf water-milfoil. 

The total percentage of the littoral-zone area susceptible to 

variable leaf water-milfoil was estimated by this method to be 

44 percent (fig. 14). 

The amount of light reaching the sediment surface is an 

important factor in the distribution and species composition 

of SAV communities. SAV exhibit distinct morphological 

variations in relation to light intensity; specifically, shadeadapted leaves tend to be finely divided (Wetzel, 1983; Barko 

and others, 1981). Variable leaf water-milfoil has finely 

dissected leaves and was found at depths that ranged from 

1 to 4 m. Sites with other types of SAV had depths that ranged 

from 1 to 2 m. The differences in depth between variable 

leaf water-milfoil sites and other-SAV sites were statistically 

significant (p = 0.04) (fig. 15). Although variable leaf watermilfoil was observed at greater depths than other types of SAV, 

it was not observed at depths below 4.3 m, the lower boundary 

of the photic zone. 

Concentrations of iron in the water-column samples were 

significantly different among the three site types (p = 0.04) 

and consistently lowest at the variable leaf water-milfoil 

sites (fig. 16; table 4). The percentage of TOC measured in 

sediment samples also was significantly different among 

the three site types (p = 0.04) and consistently lowest at the 

variable leaf water-milfoil sites (table 5). Most constituent 

concentrations, however, were not correlated with the presence 

of variable leaf water-milfoil. Other studies of SAV also have 

had limited success in relating water-column, interstitial porewater, and sediment-constituent concentrations to the presence 

or density of SAV (Barko and others, 1986; Barko and Smart, 

2006; Kimball and Baker, 1982). 

In this study, differences in surficial-sediment composition among the three site types had the strongest correlation 

with the presence of variable leaf water-milfoil, which was 

growing in areas where the sediments were predominately 

coarse sand. The grain size of the fine fraction (d16) differed 

significantly between the variable leaf water-milfoil sites and 

other-SAV sites and no-SAV sites (p = 0.005). The median 

grain size of the fine fraction (d16) of the variable leaf watermilfoil sites was 0.33 mm but was 0.14 mm and 0.17 mm at 

the other-SAV sites and no-SAV sites, respectively (fig. 17A). 

The median grain size (d50) of the sediment samples from the 

variable leaf water-milfoil sites ranged from 0.60 to 0.81 mm 

with a median of 0.62 mm (coarse sand) (table 3). The median 

grain size of the sediment samples from the other-SAV and noSAV sites ranged from 0.18 mm to 0.58 mm and from 0.04 to 

0.91, with median values of 0.42 mm and 0.40 mm (medium 

sand), respectively (table 3). A significant difference also was 

found in the median grain size (d50) between variable leaf 

water-milfoil sites and other-SAV sites (p = 0.008), but not 

between variable leaf water-milfoil sites and no-SAV sites 

(p > 0.05) (fig. 17B). The coarse fraction (d84) at the variable 

leaf water-milfoil sites was significantly larger in grain size as 

compared to the coarse fraction (d84) from the other-SAV and 

no-SAV sites (p = 0.05) (fig. 17C). These statistical differences 

indicate that the largest percentages of coarse sediment and the 

smallest percentages of fine sediment were at the variable leaf 

water-milfoil sites (table 7) (sediment textures were defined by 

using definitions in Wentworth, 1922). Thus, sediment grain 

size may be one control for SAV community types and their 

distribution in Moultonborough Bay.

The grain size of the median fraction (d50) of the 

sediment samples also correlated (Rho = 0.49) with water 

depth at depths less than 4.3 m (fig. 18). The relation 

between grain size and depth is unimodal, and sidescan-sonar 

interpretations suggested that surficial-sediment grain size 

decreased with increasing depth in areas deeper than 5 m. 

Depth and grain size were correlated in the littoral zone, and 

both habitat characteristics were correlated with the presence 

of variable leaf water-milfoil. These factors may affect the 

distribution of variable leaf water-milfoil. 
28 Relation of Lake-Floor Characteristics to the Distribution of Variable Leaf Water-Milfoil, New Hampshire, 2005

Figure 14. Distribution and percentage of the lake floor covered by variable leaf water-milfoil and areas susceptible to variable leaf 

water-milfoil growth in Moultonborough Bay, Lake Winnipesaukee, New Hampshire.

71°23'30" 71°23' 71°22'30" 71°22' 71°21'30"

43°42'30"

43°43'

43°43'30"

43°44'

EXPLANATION Base from 2003 National Agricultural

Imagery Program (NAIP), 2005

Percentage of lake floor covered 

by variable leaf water-milfoil 

 59 to 70

71 to 80

81 to 100

Areas susceptible

to milfoil growth

Undifferentiated aquatic

vegetation

No aquatic vegetation

No data

Gansy

Island

Birch Hill

Island

Whaleback

Island

Lees

Mill

Smith

Point

Moultonborough, NH

0 1,000 2,000 FEET 500

0 250 500 METERS 125
Characterization of the Distribution of Variable Leaf Water-Milfoil 29

Figure 15. Comparison of water depth among the variable leaf water-milfoil sites, other-SAV sites, and no-SAV sites in 

Moultonborough Bay, Lake Winnipesaukee, New Hampshire. [SAV, submerged aquatic vegetation; results of Tukey’s multiple 

comparison test (Helsel and Hirsch, 1992) among site types are presented as letters, and distributions with at least one letter in 

common do not differ significantly.]

Figure 16. Comparison of iron concentrations in water-column samples among the variable leaf water-milfoil sites, other-SAV sites, 

and no-SAV sites in Moultonborough Bay, Lake Winnipesaukee, New Hampshire. [SAV, submerged aquatic vegetation; results of Tukey’s 

multiple comparison test (Helsel and Hirsch, 1992) among site types are presented as letters, and distributions with at least one letter in 

common do not differ significantly.]

0.05

0.10

0.15

0.20

0.25

0.30

0.35

0.40

(N = 9) (N = 7) (N = 8)

(p = 0.04)

IRON CONCENTRATIONS, 

IN MILLIGRAMS PER LITER

A

B B

75th percentile

10th percentile

90th percentile

50th percentile (Median)

25th percentile

Variable leaf water-milfoil sites

Other-SAV sites

No-SAV sites

Multiple comparison group - A

N = Number of samples

EXPLANATION

0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

4.5

(N = 9) (N = 7) (N = 8)

A

A B

B

(p = 0.04)

WATER DEPTH, IN METERS

75th percentile

10th percentile

90th percentile

50th percentile (Median)

25th percentile

Variable leaf water-milfoil sites

Other-SAV sites

No-SAV sites

Multiple comparison group - A

N = Number of samples

EXPLANATION
30 Relation of Lake-Floor Characteristics to the Distribution of Variable Leaf Water-Milfoil, New Hampshire, 2005

Figure 17. Comparison of surficial-sediment grain size for (A) the fine fraction, 16th 

percentile (d16), (B) the median grain size, 50th percentile (d50), and (C) the coarse 

fraction, 84th percentile (d84) among variable leaf water-milfoil sites, other-SAV sites, 

and no-SAV sites in Moultonborough Bay, Lake Winnipesaukee, New Hampshire. [SAV, 

submerged aquatic vegetation; results of Tukey’s multiple comparison test (Helsel and 

Hirsch, 1992) among site types are presented as letters, and distributions with at least 

one letter in common do not differ significantly.]

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

1.8

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

0.00

0.05

0.10

0.15

0.20

0.25

0.30

0.35

0.40

0.45

A

B

C

A

B

B

A

A

A B

B

B

B

(p = 0.005)

(p = 0.05)

(p = 0.008) (p > 0.05)

SURFICIAL-SEDIMENT GRAIN SIZE, IN MILLIMETERS

(N = 9) (N = 7) (N = 8)

EXPLANATION

75th percentile

10th percentile

90th percentile

50th percentile (Median)

25th percentile N = Number of samples

Variable leaf water-milfoil sites

Other-SAV sites

Multiple comparison group - A No-SAV sites
Characterization of the Distribution of Variable Leaf Water-Milfoil 31

Table 7. Comparison of sediment composition of variable leaf water-milfoil and other-SAV sampling sites in Moultonborough Bay, 

Lake Winnipesaukee, New Hampshire. 

[Sediment textures from Wentworth, 1922; SAV, submerged aquatic vegetation; Boldface indicates that differences are statistically significant (p-value <0.05)]

Site 

type

Number

of 

samples

Gravel

Very 

coarse

sand

Coarse 

sand

Medium

sand

Fine 

sand

Very

fine 

sand

Silt Clay

Variable leaf watermilfoil sites9 2.3 16.0 37.7 32.9 9.2 1.3 0.3 0.9

Other-SAV sites 8 1.4 9.0 20.8 26.2 27.4 8.6 1.3 5.4

Absolute difference 0.9 7.0 16.9 6.65 18.3 7.2 1.0 4.5

Figure 18. Water depth and the median (d50) surficial-sediment grain size for all study sites in 

Moultonborough Bay, Lake Winnipesaukee, New Hampshire. (SAV, submerged aquatic vegetation.)

EXPLANATION

Variable leaf water-milfoil sites

Other-SAV sites

No-SAV sites

1.0

1.5

2.0

2.5

3.0

3.5

4.0

4.5

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1

Rho = 0.49

p = 0.02

Smooth line

WATER DEPTH, IN METERS

MEDIAN GRAIN SIZE (d50), IN MILLIMETERS
32 Relation of Lake-Floor Characteristics to the Distribution of Variable Leaf Water-Milfoil, New Hampshire, 2005

In addition to depth, grain size also was correlated 

with concentrations of total ammonia plus organic nitrogen, 

and total phosphorus from interstitial pore-water samples. 

Concentrations of total ammonia plus organic nitrogen had 

the strongest correlation with median sediment-grain size 

(d50) (Rho = 0.47; p = 0.02) (fig. 19). Total phosphorus 

concentrations in the interstitial pore-water samples also were 

positively correlated to median grain size (d50) (Rho = 0.44; 

p = 0.05). The correlations between total ammonia plus 

organic nitrogen and total phosphorus to median grain 

size (d50) may indicate that nutrients were affecting the 

distribution of variable leaf water-milfoil, although this 

correlation was not directly significant. Other studies (Loeb 

and Hackley, 1988; Lodge and others, 1989) evaluated groundwater inflows as a factor for SAV distribution in oligotrophic 

lakes. Lodge and others (1989) suggested that ground-water 

inflows may be a source of additional nutrients for SAV. The 

apparent relation of nutrients to coarse grain sediments and 

the strong relation of coarse grain sediments to variable leaf 

water-milfoil distribution indicated that ground-water inflows 

in the coarse, sandy areas of Moultonborough Bay may be 

another control on SAV community type and distribution. 

Lodge and others (1989) also suggested that ground-water 

inflows maintain higher winter temperatures in sediments, 

which may enhance winter survival of perennial SAV. Water 

temperature also has been identified as an important influence 

on the photosynthetic rates of aquatic plants (Nichols and 

Shaw, 1986; Smith and Barko, 1990). Kimball and Baker 

(1983) reported that variable leaf water-milfoil maintained 

a considerable amount of green biomass through the winter. 

The ability to maintain green biomass through the winter and 

early spring growth may give variable leaf water-milfoil a 

competitive advantage within the aquatic-plant community 

and enhance its dominance in the littoral zone. In addition 

to variable leaf water-milfoil potentially outcompeting other 

types of SAV with early spring growth, the apparent difference 

in sediment texture and depth ranges between the habitats of 

variable leaf water-milfoil and other-SAV may indicate that 

variable leaf water-milfoil is able to occupy niches that were 

previously open water, further enhancing its dominance in the 

littoral zone. 

Figure 19. Concentrations of total ammonia plus organic nitrogen from interstitial pore-water samples and 

the median (d50) surficial-sediment grain size for all study sites in Moultonborough Bay, Lake Winnipesaukee, 

New Hampshire.

-0.5

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1

Rho = 0.47

p = 0.02

EXPLANATION

Smooth line

Variable leaf water-milfoil sites

Other-SAV sites

No-SAV sites

 TOTAL AMMONIA PLUS

ORGANIC NITROGEN,

IN MILLIGRAMS PER LITER

MEDIAN GRAIN SIZE (d50), IN MILLIMETERS
Summary and Conclusions 33

Summary and Conclusions

Variable leaf water-milfoil is an invasive aquatic plant 

in New Hampshire waterbodies. The number of waterbodies 

affected by variable leaf water-milfoil continues to rise. Its 

growth often leads to reduced quality of habitat for fish and 

other wildlife. In addition, infestations of variable leaf watermilfoil reduce recreational uses of and property values near 

affected waterbodies. The U.S. Geological Survey, in cooperation with the New Hampshire Department of Environmental 

Services, designed an interdisciplinary study to determine 

environmental factors that may affect the spatial distribution 

of variable leaf water-milfoil within Moultonborough Bay of 

Lake Winnipesaukee. Geophysical, water-quality, and surficial-sediment surveys were done to characterize the lake-floor 

environment, water quality, and surficial-sediment composition. Geophysical surveys were done throughout a 180-km2

area, and water-quality and sediment samples were collected 

from 24 sites in the survey area during July 2005. Data from 

this study were evaluated to identify environmental characteristics associated with the presences of variable leaf watermilfoil. A goal of this study was to characterize the distribution of variable leaf water-milfoil in an affected waterbody. 

Moultonborough Bay ranged in depth from less than 

1 m to about 15 m and included three embayments. Three 

lake-floor environments were defined as and characterized by: 

(1) rocky nearshore environments mapped in water less than 

5 m deep and contained high-backscatter coarse sediments and 

bedrock outcrop; (2) mixed nearshore environments mapped 

in shallow water less than 5 m deep and contained varying 

densities of aquatic vegetation. These areas were characterized 

by a mottled backscatter pattern in the sidescan-sonar data, 

silt to coarse sand sediments, and isolated exposures of 

bedrock; and (3) muddy-basin environments mapped in water 

depths greater than 5 m, contain low-backscatter fine-grained 

sediments, and the thickest accumulations of glaciolacustrine 

and Holocene lacustrine sediments.

Acoustic ground discrimination systems survey data 

were used to describe the distribution of submerged aquatic 

vegetation (SAV) in the littoral zone of Moultonborough 

Bay. SAV included variable leaf water-milfoil, native milfoil, 

bassweed, pipewort, and other species growing in water 

ranging from less than 1 to 4 m deep. Overall, 86 percent of 

the littoral zone had some SAV. These data were used to create 

an interpolated map that distinguished variable leaf watermilfoil from other SAV in the bay. Criteria were determined 

for depth, sediment texture, and the percentage of vegetative 

bottom cover, and were used to identify areas in the littoral 

zone where the SAV is likely to be variable leaf water-milfoil. 

In 2005, 21 percent of the littoral zone had variable leaf watermilfoil at a density of 59 percent or greater bottom cover. The 

criteria also were used to define areas in the littoral zone that 

may be susceptible to the spread of variable leaf water-milfoil. 

Approximately 44 percent of the littoral zone was estimated to 

have habitat suitable for variable leaf water-milfoil and would 

likely be susceptible to future growth of the plant.

Difference in depth between variable leaf water-milfoil 

sites and other-SAV sites was significant (p = 0.04). Variable 

leaf water-milfoil was found at depths that ranged from 

1 to 4 m, whereas other SAV was found at depths that ranged 

from 1 to 2 m. Concentrations of iron in water-column 

samples were significantly lower at variable leaf water-milfoil 

sites than at the other-SAV sites and no-SAV sites (p = 0.04). 

The percentage of TOC in the sediment samples also was 

significantly lower at the variable leaf water-milfoil sites than 

at the other-SAV sites and no-SAV sites (p = 0.04). 

Measures of the fine (d16), median (d50), and coarse 

(d84) fractions of the sediment were interpolated to characterize the sediment composition at each site. The presence of 

variable leaf water-milfoil was most strongly correlated with 

differences in surficial-sediment composition. Variable leaf 

water-milfoil was found in areas of coarse sand (with a median 

grain diameter of 0.62 mm). Concentrations of phosphorus and 

total ammonia plus organic nitrogen in interstitial pore water 

were both correlated with the median grain size (d50) (Rho = 

0.44; p < 0.05 and Rho = 0.47; p = 0.02, respectively). 

The use of geophysical surveys provided a comprehensive assessment of the lake-floor environment and SAV 

distribution; these techniques could be used to guide additional 

sampling and monitoring of lake environments, including the 

growth and spread of aquatic vegetation. The techniques made 

it possible to discern the differences in the spatial distributions 

of variable leaf water-milfoil and other types of SAV and to 

identify habitat for potential growth. These tools also may be 

valuable for assessing the susceptibility of lakes to aquatic 

invasive species. Habitat and SAV maps that indicate variable 

leaf water-milfoil distribution and density may be useful in 

identifying areas susceptible to future infestation or may help 

predict the success of eradication efforts to remove the plant. 

Results from this study indicate that variable leaf water-milfoil 

is present at differing densities in most areas where the sediment characteristics are conducive to its growth. The study 

also demonstrated a methodology that integrated geophysical, 

water-quality, and sediment surveys for identifying areas on a 

lake floor susceptible to variable leaf water-milfoil infestation. 

Results from this study may be useful in the management and 

allocation of resources for monitoring and controlling variable 

leaf water-milfoil infestations at similar sites. 
34 Relation of Lake-Floor Characteristics to the Distribution of Variable Leaf Water-Milfoil, New Hampshire, 2005

References Cited

Baldwin, W.E., Morton, R.A., Denny, J.F., Dadisman, S.V., 

Schwab, W.C., Gayes, P.T., and Driscoll, N.W., 2004, Maps 

showing the stratigraphic framework of South Carolina’s 

Long Bay from Little River to Winyah Bay: 

U.S. Geological Survey Open-File Report 2004–1013, 

20 figs.

Barko, J.W., Hardin, D.G., and Matthews, M.S., 1981, Growth 

and morphology of submersed freshwater macrophytes 

in relation to light and temperature: Canada Journal of 

Botany, v. 60, p. 877–887.

Barko, J.W., Adams, M.S., and Clesceri, N.L., 1986, 

Environmental factors and their consideration in the 

management of submersed aquatic vegetation—A review: 

Journal of Aquatic Plant Management, v. 24, p. 1–10.

Barko, J.W., and Smart, M.R., 2006, Sediment-related 

mechanisms of growth limitation in submersed 

macrophytes: Ecology, v. 67, no. 5, p. 1328–1340.

Barnhardt, W.A., Andrews, B.D., and Butman, B., 2006, 

High-resolution geologic mapping of the Inner Continental 

Shelf—Nahant to Gloucester, Massachusetts: U.S. 

Geological Survey Open-File Report 2006–1293 CD-ROM.

Benn, D.I., and Evans, D.J.A., 1998, Glaciers & glaciation: 

Oxford University Press, USA, 734 p. 

Brown, C.J., Cooper, K.M., Meadowns, W.J., Limpenny, D.S., 

and Rees, H.L., 2002, Small-scale mapping of sea-bed 

assemblages in the eastern English Channel using sidescan 

sonar and remote sampling techniques: Estuarine, Coastal 

and Shelf Science, v. 54, p. 263–278.

Brown, C.J., Hewer, A.J., Limpenny, D.S., Cooper, K.M., and 

Rees, H.L., 2004, Mapping seabed biotopes using sidescan 

sonar in regions of heterogeneous substrata—Case study 

east of the Isle of Wight, English Channel: International 

Journal of the Society for Underwater Technology, v. 26, 

no. 1, p. 27–36.

Brown, C.J., Mitchell, A., Limpenny, D.S., Robertson, M.R., 

Service, M., and Golding, N., 2005, Mapping seabed 

habitats in the Firth of Lorn off the west coast of Scotland— 

Evaluation and comparison of habitat maps produced 

using the acoustic ground-discrimination system, RoxAnn, 

and sidescan sonar: Journal of Marine Science, v. 62, 

p. 790–802.

Burczynski, J., Christiaanse, C., Mosynski, M., 2005a, 

BioSonics, EcoSAV 1, User’s Guide: Seattle, WA, 

BioSonics, Inc., p. 47.

Burczynski, J., Christiaanse, C., Mosynski, M., 2005b, 

BioSonics, VBT 1.9b, Visual Bottom Typer User’s Guide: 

Seattle, WA, BioSonics, Inc., p. 103. 

Butman, B., Danforth, W.W., Knowles, S.C., May, B., and 

Serrett, L., 2000, Seafloor topography and backscatter 

intensity of the historic area remediation side (HARS), 

offshore of New York, based on multibeam surveys 

conducted in 1996, 1998, and 2000: U.S. Geological 

Survey Open-File Report 00–503, (DVD-ROM), accessed 

May 17, 2007, at http://pubs.usgs.gov/of/2000/of00–503/

reports/index.html.

Cohen, J.K., and Stockwell, Jr., J.W., 2001, CWP/SU: Seismic 

Unix Release 35—A free package for seismic research and 

processing: Center for Wave Phenomena, Colorado School 

of Mines. 

Collier, J.S., and Brown, C.J., 2005, Correlation of sidescan 

backscatter with grain size distribution of surficial seabed 

sediments: Marine Geology, v. 214, p. 431–449.

Colman, S.M., 2005, Stratigraphy of lacustrine sediments 

cored in 1996, Bear Lake, Utah and Idaho: U.S. Geological 

Survey Open-File Report 2005–1288, 15 p.

Crow, G.E., Hellquist, C.B., 2000, Aquatic and wetland plants 

of northeastern North America—Volume 1. Pteridophytes, 

Gymnosperms, and Angiosperms—Dicotyledons: Madison, 

WI, University of Wisconsin Press, v. 1, 480 p. 

Danforth, W.W., 1997, Xsonar/ShowImage—A complete 

system for rapid sidescan sonar processing and display: 

U.S. Geological Survey Open-File Report 97–686, 77 p.

Danforth, W.W., O’Brien, T.F., and Schwab, W.C., 1991, 

USGS image processing system—Near real-time 

mosaicking of high-resolution sidescan-sonar data: Sea 

Technology, January, p. 54–59.

Denny, J.F., and Colman, S.M., 2003, Geophysical surveys of 

Bear Lake, Utah-Idaho, September 2002: U.S. Geological 

Survey Open-File Report 03–150, (CD-ROM), accessed 

May 17, 2007, at http://pubs.usgs.gov/of/2003/of03–150/

Duarte, C.M., 1987, Use of echosounder tracings to estimate 

the aboveground biomass of submerged plants in lakes: 

Canadian Journal of Fisheries and Aquatic Sciences, v. 44, 

p. 732–735.

Eichler, L.W., Howe, E.A., and Boylen, C.W., 2001, The use 

of stream delta surveillance as a tool for early detection 

of Eurasian Watermilfoil: Journal of Aquatic Plant 

Management, v. 39, p. 79–82. 

Environmental Systems Research Institute, 2002, ArcView 

GIS 3.3 Using ArcView: Redlands, CA.

Environmental Systems Research Institute, 2004, ArcGIS 9 

Using ArcMap: Redlands, CA.
References Cited 35

Foster-Smith, R.L., and Sotheran, I.S., 2003, Mapping marine 

benthic biotopes using acoustic ground discrimination 

systems: International Journal of Remote Sensing, v. 24, 

no. 132, p. 2761–2784.

Gardner, J.W., Mayer, L.A., and Hughes Clarke, J.E., 2000, 

Morphology and processes in Lake Tahoe (CaliforniaNevada): GSA Bulletin, v. 112, no. 5, p. 736–746.

Goldthwait, R.P., 1968, Surficial Geology of the WolfeboroWinnipesaukee area, New Hampshire: Concord, NH, State 

of New Hampshire Department of Resources and Economic 

Development.

Halstead, J.M., Michaud J., Hallas-Burt, S., and Gibbs, J.P., 

2003, An hedonic analysis of effects of a nonnative invader 

(Myriophyllum heterophyllum) on New Hampshire (USA) 

lakefront properties: Environmental Management, 

v. 32 (3): p. 391–398. 

Helsel, D.R., and Hirsch, R.M., 1992, Statistical methods in 

water resources: New York, Elsevier Science Publishers, 

522 p. 

Henkart, P., 2005, “SIOSEIS, Scripps Institution of 

Oceanography seismic processing software package,” 

http://sioseis.ucsd.edu.

Inman, D.L., 1952, Measures for describing the size 

distribution of sediments: Journal of Sedimentary 

Petrology, v. 22, no. 3, p. 125–145.

Keast, A., 1983, The introduction of aquatic macrophyte, 

Myriollum Spicatum, as habitat for fish and their 

invertebrate prey: Canadian Journal of Zoology, v. 62, 

p. 1289–1303. 

Kenny, A.J., Cato, I., Desprez, M., Fader, G., Schuttenhelm, 

R.T.E., and Side, J., 2003, An overview of seabed-mapping 

technologies in the context of marine habitat classification: 

Journal of Marine Science, v. 60, p. 411–418.

Kimball, K.D., and Baker, A.L., 1982, Variations in the 

mineral content of Myriophyllum Heterophyllum Michx

related to site and season: Aquatic Botany, v. 14, 

p. 139–140.

Kimball, K.D., and Baker, A.L., 1983, Temporal and 

morphological factors related to mineral composition in 

Myriophyllum Heterophyllum Michx: Aquatic Botany, 

v. 16, p. 189–205.

Loeb, S.L., and Hackley, S.H., 1988, The distribution of 

submerged macrophytes in Lake Tahoe, California and 

Nevada, and the possible influence of groundwater seepage: 

International Association of Theoretical and Applied 

Limnology, v. 23, part 4, p. 1927–1933.

Lodge, D.M., Krabbenhoft, D.P., and Striegl, R.G., 1989, 

A positive relationship between groundwater velocity 

and submersed macrophyte biomass in Sparkling Lake, 

Wisconsin: Limnology and Oceanography, v. 34, 

p. 1927–1933.

Lovich, J., Dein, F.J., Grace, J.B., Guptill, S.C., Haag, K.H., 

Larson, D.L., Meyer, D.J., Reheis, M., and Stohlgren, T., 

2003, A strategic science plan for the U.S. Geological 

Survey Research on Invasive Species: U.S. Geological 

Survey, accessed February 18, 2004, at http://internal.usgs.

gov/director/fsd/doc/invasives_draft.doc.

Lubniewski, Z., and Stepnowski, A., 1997, Sea bottom typing 

using fractal dimensions in International Symposium on 

hydroacoustics and ultrasonics, Proceedings, Gdansk-Jurata, 

Poland, May 1997, p. 12–16.

Lyons, J.B., Bothner, W.A., Moench, R.H., and Thompson, 

J.B., Jr., 1997, Bedrock geologic map of New Hampshire: 

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

Interior, 2 sheets.

Maceina, M.J., and Shireman, J.V., 1980, The use of a 

recording fathometer for determination of distribution and 

biomass of Hydrilla: Journal of Aquatic Plant Management, 

v. 18, p. 34–39.

Madsen, J.D., 1998, Predicting invasion success of Eurasian 

watermilfoil: Journal of Aquatic Plant Management, v. 36, 

p. 28–32.

New Hampshire Department of Environmental Services, 2006, 

Watershed Management Bureau, Exotic Species Program: 

(digital) accessed November 2006, at http://www.des.state.

nh.us/wmb/exoticspecies/

Nichols, S.A., 1994, Factors influencing the distribution of 

Eurasian Watermilfoil (Myriophyllum spicatum L) biomass 

in Lake Wingra, Wisconsin: Journal of Freshwater Ecology, 

v. 9, p. 145–151. 

Nichols, S.A., and Shaw, B.H., 1986, Ecological life histories 

of the three aquatic nuisance plants, Myriophyllum 

spicatum, Potamogeton crispus, and Elodea canadensis: 

Hydrobiologia, v. 131, p. 3–21.

Paskevich, V., 1992, Digital mapping of side-scan sonar data 

with the Woods Hole Image Processing System software: 

U.S. Geological Survey Open-File Report 92–536, 

87 p., at http://pubs.usgs.gov/of/of92–536/

Poppe, L.J., Eliason, A.H., and Fredricks, J.J., 1985, 

APASA—An automated particle size analysis system: 

U.S. Geological Survey Circular 963, 7 p. 
36 Relation of Lake-Floor Characteristics to the Distribution of Variable Leaf Water-Milfoil, New Hampshire, 2005

Poppe, L.J., and Polloni, C., eds., 2000, USGS eastcoast sediment analysis; procedures, database, and 

georeferenced displays: U.S. Geological Survey OpenFile Report 00–348, DVD-ROM, (Also available at 

http://pubs.usgs.gov/openfile/of00–358/)

Quinn, A., 1941, The geology of Winnipesaukee quadrangle 

New Hampshire: Concord, NH, State of New Hampshire, 

Department of Resources and Economic Development.

Schwab, W.C., Thieler, E.R., Allen, J.R., Foster, D.S., Swift, 

B.A., and Denny, J.F., 2000, Influence of inner-continental 

shelf geologic framework on the evolution and behavior 

of the barrier-island system between Fire Island Inlet and 

Shinnecock Inlet, Long Island, New York: Journal of 

Coastal Research, v. 16, no. 2, p. 408–422.

Shaw, John, Courtney, R.C., and Currie, J.R., 1997, 

Marine geology of St. George’s Bay, Newfoundland, as 

interpreted from multibeam bathymetry and back-scatter 

data: Geo-Marine Letters, v. 17, p. 188–194.

Sheldon, L.R., and Capel, P.D., 1994, Guidelines for collecting 

and processing samples of streambed sediment for analysis 

of trace elements and organic contaminates for the National 

Water-Quality Assessment Program: U.S. Geological 

Survey Open-File Report 94–458, 20 p. 

Shepard, F.P., 1954, Nomenclature based on sand-silt-clay 

ratios: Journal of Sedimentary Research, v. 24, no. 3, 

p. 151–158.

Smith, C.S., and Barko, J.W., 1990, Ecology of eurasian 

watermilfoil: Journal of Aquatic Plant Management, v. 28, 

p. 55–64.

Spahr, N.E., and Boulger, R.W., 1997, Interim results of 

quality-control sampling of surface water for the upper 

Colorado River National Water-Quality Assessment Study 

Unit, water years 1995–96: U.S. Geological Survey WaterResources Investigations Report 97–4227, 34 p.

Statistical Analysis Software Institute, Inc., 1999, Statview 

user’s guide, version 5: Cary, NC, SAS Institute, Inc.

Statistical Analysis Software Institute, Inc., 2002, SAS/STAT 

user’s guide, version 8.02: Cary, NC, SAS Institute, Inc.

Thomas, G.L., Thiesfeld, S.L., Bonar, S.A., Crittenden, 

R.N., and Pauley, G.B., 1990, Estimates of submergent 

plant bed biovolume using acoustic range information: 

Canadian Journal of Fisheries and Aquatic Sciences, v. 47, 

p. 805–812.

Twichell, D.C., Cross, V.A., Rudin, M., Parolski, K.F., 2000, 

Surficial geology and distribution of post-impoundment 

sediment of the western part of Lake Mead based on a 

sidescan sonar and high-resolution seismic-reflection 

survey: U.S. Geological Survey Open-File Report 99–581.

Valley, R.D., Drake, M.T., and Anderson, C.S., 2004, 

Evaluation of alternative interpolation techniques for 

the mapping of remotely-sensed submersed vegetation 

abundance: Aquatic Botany, v. 81, p. 11.

Valley, R.D., Drake, M.T., 2005, Accuracy and precision 

of hydroacoustic estimates of aquatic vegetation and the 

repeatability of whole-lake surveys—Field tests with 

a commercial echosounder: Minnesota Department of 

Natural Resources Investigative Report 527, p. 13–25.

Van Diver, B.B., 1987, Roadside geology of Vermont and New 

Hampshire: Missoula, MT, Mountain Press Publishing 

Company, 230 p.

Wentworth, C.K., 1922, A scale of grade and class terms 

for clastic sediments: The Journal of Geology, v. 30, 

p. 377–392.

Wetzel, R.G., 1983, Limnology, second edition: Orlando, FL, 

Saunders College Publishing, p. 765.

Wilde, F.D., and Radtke, D.B., 1998a, Collection of water 

samples: U.S. Geological Survey Techniques of WaterResources Investigations, Handbooks for Water-Resources 

Investigations, National field manual for the collection of 

water-quality data, book 9, chap. A4, variously paginated.

Wilde, F.D., and Radtke, D.B., 1998b, Field measurements: 

U.S. Geological Survey Techniques of Water-Resources 

Investigations, Handbooks for Water-Resources 

Investigations, National field manual for the collection of 

water-quality data, book 9, chap. A6, variously paginated.

Zimmerman, M.J., Massey, A.J., Campo, K.W., 2005, 

Pushpoint sampling for defining spatial and temporal 

variations in contaminant concentrations in sediment 

pore water near the ground-water/surface-water interface: 

U.S. Geological Survey Scientific Investigations Report 

2005–5036, 75 p.
Appendix 1
38 Relation of Lake-Floor Characteristics to the Distribution of Variable Leaf Water-Milfoil, New Hampshire, 2005 Appendix 1. Site names, locations, water depths, textural compositions, median surficial-sediment grain sizes, standard deviations, skewness, kurtosis, and “verbal equivalents” (Shepard, 1954) for sediment samples collected in Moultonborough Bay, Lake Winnipesaukee, New Hampshire, July 2005. This information was used to ground-truth sidescan-sonar data. [%, percent; mm, millimeters] Site name Latitude (decimal degrees) Longitude (decimal degrees) Water depth (meters) Clay (%) Silt (%) Sand (%) Gravel (%) Median grain size (mm) Standard deviation Skewness Kurtosis Verbal equivalent (Shepard, 1954) STA1A 43.72825 71.38752 3.0 8.06 31.52 48.69 11.73 0.17 3.33 0.10 -1.03 GRAVEL > 10% STA1B 43.72825 71.38725 3.0 0.61 5.08 55.50 38.81 1.32 2.47 0.43 0.97 GRAVEL > 10% STA2 43.72812 71.38621 4.0 12.87 76.14 10.99 0.00 0.02 1.80 -0.20 0.78 SILT STA3 43.72734 71.38794 4.0 8.38 45.21 45.81 0.60 0.05 2.70 0.03 -0.90 SILTY SAND STA4 43.72665 71.38743 5.0 13.36 69.90 16.74 0.00 0.02 1.92 -0.16 0.10 SANDY SILT STA5 43.72637 71.38824 5.0 24.60 71.90 3.50 0.00 0.01 1.59 -0.08 0.29 CLAYEY SILT STA6 43.72642 71.38937 3.5 19.78 71.76 8.46 0.00 0.01 1.81 -0.22 0.74 CLAYEY SILT STA7A 43.72471 71.38689 5.5 4.57 17.68 75.96 1.78 0.08 1.64 0.53 4.30 SAND STA7B 43.72471 71.38689 5.5 0.95 5.91 88.32 4.82 0.38 1.83 0.61 2.76 SAND STA8 43.72700 71.38854 4.5 16.09 79.50 4.41 0.00 0.01 1.60 0.00 0.64 SILT STA9 43.72643 71.38982 2.5 20.51 68.12 11.37 0.00 0.01 1.91 -0.28 0.42 CLAYEY SILT STA10 43.72584 71.39084 2.0 23.78 68.55 7.67 0.00 0.01 1.86 -0.39 1.19 CLAYEY SILT STA11 43.72408 71.38807 9.5 21.38 77.98 0.64 0.00 0.01 1.47 0.11 -0.04 SILT STA12 43.72367 71.39027 2.5 14.57 75.25 10.18 0.00 0.01 1.80 -0.23 1.09 SILT STA13 43.72298 71.38868 3.0 2.29 13.42 71.82 12.47 0.52 2.53 0.51 0.83 GRAVEL > 10% STA14 43.72314 71.38655 3.5 0.99 4.88 63.33 30.80 0.75 2.29 0.45 1.38 GRAVEL > 10% STA15 43.72205 71.38651 5.0 2.35 16.49 80.72 0.44 0.19 1.96 0.57 1.62 SAND STA16 43.72102 71.38508 4.5 0.47 2.49 93.37 3.67 0.39 1.42 0.61 5.12 SAND STA17 43.71966 71.38200 7.1 5.46 22.87 66.72 4.94 0.24 2.87 0.32 -0.60 SILTY SAND STA18 43.72206 71.38164 7.5 19.97 67.67 12.36 0.00 0.01 2.17 -0.53 1.21 CLAYEY SILT STA19 43.72362 71.38158 5.5 2.66 19.86 76.24 1.24 0.32 2.39 0.49 0.23 SAND

STA20 43.72451 71.38190 5.1 16.35 77.43 6.23 0.00 0.01 1.65 -0.11 0.71 SILT

STA21 43.72673 71.37822 5.0 13.85 68.83 17.32 0.00 0.02 1.79 -0.07 -0.29 SANDY SILT

STA22 43.72702 71.37860 4.1 10.46 55.73 33.62 0.20 0.02 1.94 0.06 -0.50 SANDY SILT
Appendix 39