EPA-600/D-85-043
June 1985
TOTAL ALKALINITY OF SURFACE WATERS: A MAP
OF THE UPPER MIDWEST REGION
by
James M. Omernik
Corvallis Environmental Research Laboratory
U.S. Environmental Protection Agency
200 S.W. 35th Street
Corvallis, Oregon 97333
and
Glenn E. Griffith
Northrop Services, Inc.
200 S.W. 35th Street
Corvallis, Oregon 97333
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Abstract
This map illustrates the regional patterns of mean annual alkalinity of
surface water in the northern portions of Minnesota, Wisconsin, and Michigan.
As such, it provides a qualitative graphic overview of the relative potential
sensitivity of surface waters to acidic input in the upper midwest portions of
the United States. The map is based on data from approximately 14,000 lakes
and streams and the apparent spatial associations between these data and macro-
scale watershed characteristics that are thought to affect alkalinity.
DISCLAIMER
The information in this document has been funded by the United States
Environmental Protection Agency. It has been subjected to Agency
review and approved for publication.
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A major goal specified in the National Acid Precipitation Assessment Plan
(Interagency Task Force on Acid Precipitation, 1982) is the quantification of
the extent of sensitivity of the nation's lakes and streams to acidification.
Most earlier efforts to determine patterns of surface water sensitivity to
acidic deposition have relied on interpretations of bedrock distribution and
chemistry (Galloway and Cowling, 1978; Likens et al., 1979; Hendrey et a!.,
1980; National Atmospheric Deposition Program, 1982). One effort was based on
soil sensitivity (McFee, 1980) and another on surficial geology (Shilts, 1981).
While each of these contributed to the general knowledge of the extent of
surface water sensitivity, they are in sharp disagreement for many portions of
the country. More importantly, there is a lack of spatial correlation between
the patterns drawn by these efforts and the observed patterns of surface water
alkalinity.
Although there is general agreement that surface water alkalinity is
directly related to mineral availability, it is apparent that maps of rock type
or soil type alone are inadequate to express patterns of mineral availability
that are meaningful in terms of surface water sensitivity. For instance,
results from several recent studies of patterns of surface water sensitivity in
different regions of the United States (Eilers et al., 1983; Haines and
Akiela'szek, 1983; Twaroski et al., 1984) indicate that no single factor (e.g.,
bedrock geology) can explain observed patterns of surface water alkalinity.
Rather, these studies indicate that one must consider a variety of driving or
integrating spatial factors that affect alkalinity such as land use, physio-
graphy, and soil type (as well as geology), and that the relative importance of
any one, or a particular combination of those factors, may vary within or among
regions.
A recent report of the National Academy of Sciences (Environmental Studies
Board, 1984) defined several important geochemical and hydrological processes
of watersheds that determine whether waters will acidify and the rate at which
acidification would proceed. These processes are not yet defined on a regional
scale and, therefore, cannot presently be used in a definition of relative
sensitivity of regions to acidic deposition.
In light of the above, it is clear that caution must be used in any effort
to use a single measure such as alkalinity to assess the sensitivity of surface
waters to acidic deposition because the actual response of a given lake or
stream is determined by numerous biogeochemical and hydrological factors of the
watershed plus chemical processes within water bodies. Alkalinity is certainly
the most readily available measure of the acid-neutralizing capacity of surface
waters. Although alkalinity measurements do not completely incorporate the
influences of all factors into a definition of surface water sensitivity, they
do reflect the interactions of biogeochemical and hydrological processes that
ultimately influence sensitivity.
With this rationale, we approached the problem of depicting the likely
patterns of surface water sensitivity in the conterminous United States by
synoptically analyzing spatial patterns of surface water alkalinity as an
integrator of the various factors which determine sensitivity. We accomplished
this by: (1) assembling available alkalinity data on as many representative
surface waters as necessary and/or possible; (2) plotting these data on
1
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large-scale maps; and (3) analyzing the patterns of the values of the plotted
data for spatial correlations with other characteristics such as land use,
geology, and physiography.
A national map compiled earlier (Omernik and Powers, 1983) described the
general patterns of surface water alkalinity in the conterminous United
States. By comparison, the regional map presented here is based on two orders
of magnitude more data (for the Upper Midwest portion of the national map) and
depicts the spatial patterns of surface water alkalinity in greater detail and
at a greater resolution than was possible in the national map.
The alkalinity ranges of the five map units were chosen to reflect
potential sensitivity patterns on a regional scale, as compared with the
broader ranges used for the national map. Although it is not possible to
define exact break points between sensitive, moderately sensitive, and insensi-
tive waters, it is generally agreed that waters of total alkalinity > 200 ueq/1
are relatively insensitive to acidic deposition.
As was the case with the national map, our purpose is to show what range
of alkalinity one might expect to find in most of the surface waters most of
the time. Relative to the national map, the regional map provides more
detailed ancillary information on ranges of conditions, significant apparent
regional and local relationships between alkalinity and macro-scale watershed
characteristics such as land use and physiography, seasonal variations, and
other factors. This information in turn provides a basis for understanding the
confidence with which predictions and estimations of potential surface water
sensitivity might be made for the region, or parts of the region. Me emphasize,
however, that the map and the ancillary information are not intended for making
precise predictions of sensitivity for individual water bodies or specific
locations. Rather, this map and the other regional maps are intended to help
fill the urgent need to understand the relative potential sensitivity of
surface waters in different parts of the country in order to provide a national
perspective of the potential problem, provide rationale for selecting geo-
graphic areas for more detailed studies, and allow more accurate regional
assessments of acid deposition impacts on aquatic resources.
MAP DEVELOPMENT
The methods used to develop this map were similar to those used to prepare
the alkalinity map of the New England and New York Region (Omernik and Kinney,
1985), although the map scales were larger and amount of data used for the
Upper Midwest Region was much greater. The alkalinity data were selected and
mapped according to several categories, with separate designations given for
streams, lakes, and reservoirs, as well as to sites associated with watersheds
of less than 260 sq km (100 sq mi). Each data point was scrutinized for
representativeness by keeping the watershed size consistent with the relative
homogeneity of major watershed features thought to influence surface water
alkalinity such as physiography, vegetation type, and land use. In areas of
relative heterogeneity, most of the data were associated with small watersheds
less than 130 square kilometers. Representative data was imperative for
detecting spatial patterns of alkalinity, possible correlations with patterns
of other characteristics, and, ultimately, extrapolation of the data. To
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include non-representative data from sites having large watersheds of widely
differing characteristics, or data downstream from major industrial waste
discharges, would mask these spatial patterns.
The map of the Upper Midwest Region, similar to the national map and the
New England/New York map, was based on patterns of the actual alkalinity values
and the apparent spatial associations of these values with aerial characteris-
tics that are believed to be driving or integrating factors affecting alkalin-
ity. Driving factors, as used in this paper, refer to those that are generally
believed to directly affect alkalinity (e.g., geology and soils). Integrating
factors, on the other hand, are considered those that tend to reflect combina-
tions of driving factors; for example, land use and potential natural vegeta-
tion reflect regional combinations (or an integration) of driving factors such
as soils, land surface form, climate, and geology. We believe that the
importance of each of these factors, and the hierarchy of importance relative
to the combinations of factors, varies from one region to another and even
within regions. Clarifying these regional factors is a major goal of our
overall synoptic analyses.
We acquired alkalinity data from a variety of sources. As expected,
uniformity of coverage and temporal consistency was lacking. In general, the
amount of data we acquired was a function of its availability and, more impor-
tantly, the apparent complexity of regional patterns of alkalinity. In some
areas, after gathering and plotting a certain amount of data, the spatial
patterns became clear enough so that the addition of more data merely supported
the patterns already set. In other areas, more data, and/or analyses at
increasingly larger scales, were necessary to distinguish the alkalinity
patterns.
The most recent data (1979-1983) for the Upper Midwest Region were
obtained from STORET, an EPA computer-based water quality data storage and
retrieval system. Data collected by the EPA, the University of Minnesota-
Duluth, and the Wisconsin Department of Natural Resources (Glass et al., 1983)
and the Minnesota Pollution Control Agency (Twaroski et al., 1983; Thornton et
al., 1982; Heiskary and Thornton, 1983) from 1978 to 1983, which had not been
entered into STORET at the time of our collection, were also used. These data
were plotted on 1:250,000 or 1:500,000-scale topographic maps, with each site
represented by a small circle color-coded to an alkalinity class value; the
exact value and the water body type were noted beside the circle. From STORET
data for the earlier period, 1960 to 1975, 108 lake and stream points (mostly
from the early 1970s) were determined to be suitable for our mapping purposes
and were plotted on overlays. These three sources yielded approximately 1,648
values (86% from lakes and 14% from streams) in the Upper Midwest Region. Of
these values, 56% represented one sample only, 8% were the mean of two samples,
and 35% were the mean of three or more samples.
For Michigan and Wisconsin, we relied heavily on earlier (1960 to 1975)
data, because of a paucity of more recent data and the relatively complex
alkalinity pattern. In Michigan's Upper Peninsula, in addition to 306 points
from STORET and Glass et al. (1983), small-scale dot maps from Schneider (1975)
showing the distribution of lakes by methyl orange alkalinity class were used
to aid in the determination of the areal extent of our alkalinity classes. The
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patterns of these historical data indicated the location of clusters of lakes
with less than 400 ueq/1 alkalinity. By superimposing these patterns on our
1:500,000-scale maps containing the more recent alkalinity data, and by noting
the apparent relationships of lake type to alkalinity, lake size to alkalinity,
lake vs. stream alkalinity, and relevant macro-scale watershed characteristics,
we were able to interpolate and estimate areas of specific alkalinity classes.
This process was also enhanced by transferring and plotting the data by alka-
linity class on 1:250,000-scale topographic maps.
For Wisconsin, an abundance of historical alkalinity data was available
from that state's Department of Natural Resources (and one of its predecessor
agencies, the Wisconsin Conservation Department) in publications of "Surface
Water Resources" by county (Various Authors, 1960-1980). These included maps
that showed the alkalinity classification for each lake and stream sampled.
For the eighteen-county area delineated in the map inset, alkalinity values
were given for about 10,500 lakes and 2,500 stream sites. On these large-scale
county maps, lake and stream sites were color-coded according to alkalinity
class, and the resultant patterns indicated where boundaries might be drawn.
The delineation of our alkalinity classes on the county maps was made after
noting lake types, lake sizes, stream courses, and physical features from
1:250,000-scale topographic maps as well as consideration of other driving and
integrating factors. In addition, comparisons were made to the spatial patterns
of recent alkalinity data plotted on the 1:500,000-scale Wisconsin map, which
included 537 lake and stream points from STORET and Glass et al. (1983).
The data for Minnesota used in our mapping were primarily of recent
origin. Approximately 805 lake and stream values from STORET and Glass et al.
(1983) were plotted on 1:250,000-scale topographic maps by alkalinity class
(e.g., 1 = < 50 ueq/1, 2 = 50 to 100 ueq/1, 3 = 100 to 200 ueq/1, etc.).
Data listed in Twaroski et al. (1983), Thornton et al. (1982), and Heiskary and
Thornton (1983) were checked for any lakes not previously plotted or listed in
the STORET or Glass et al. (1983) data sets. An interpretive process similar
to that used for Wisconsin and Michigan, considering the relevant driving and
integrating factors, was also used for Minnesota. Since the relationship
between alkalinity and lake type and lake size is quite different in northeast
Minnesota than in other parts of the Upper Midwest Region, the final class
boundaries there were based largely on the spatial pattern of the alkalinity
data itself, but also with some considerations of bedrock type, land surface
form, and land use.
Spatial patterns of the alkalinity values were the most important factor
for delineating alkalinity map units throughout the Upper Midwest Region. Land
use and vegetation information were also useful, but in a more general way of
delineating areas where low alkalinity waters were unlikely. Low alkalinity
waters are generally found only in predominantly forested or wetland areas.
Wherever agriculture (including grazing) occurs, even as a fairly small portion
of the land use mosaic, mean annual alkalinity values are commonly well over
400 ueq/1. Geology maps were used to focus our attention and data collection
efforts on areas of suspected sensitive rock types. However, final map unit
alignments were nearly always based on patterns of alkalinity values or
physiographic features. Locally, physiographic and hydrologic features were
extremely helpful for map unit delineations (e.g., where strong associations
were apparent between lake type and alkalinity or glacial feature and low
alkalinity lake type).
4
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DATA ASSESSMENT
The use of historical alkalinity data raises questions concerning the
comparability of older and newer methods of measuring surface water alkalinity.
Methodologies vary even among recently collected data. For example, of the
recent data (1978-1983) used for the Upper Midwest map, alkalinity values for
approximately 46% of the sites were determined using the titration method of
Gran (1952), 22% were determined by single endpoint titration (potentiometric)
(American Public Health Association, 1980), 11% were determined by double
endpoint titration (potentiometric) (American Public Health Association, 1980),
and 21% were of unknown methodology. While these recent data were of great
importance, especially in Michigan and Minnesota, they only represent about
one-tenth of all the data points used. For the entire Upper Midwest data set,
including the large amount of historical data from Wisconsin, roughly 88% of
the alkalinity values were determined by colorimetric methodologies (usually
methyl orange or methyl purple); only 5% were determined using the method of
Gran (1952), 3% by single endpoint titration (potentiometric) (American Public
Health Association, 1980), 1% by double endpoint titration (potentiometric)
(American Public Health Association, 1980), and 3% unknown.
For low alkalinity waters, the most commonly used fixed endpoint proce-
dures (either potentiometric or colorimetric) often yield overestimates of
alkalinity (Dillon et al., 1978; Zimmerman and Harvey, 1979-1980; Jeffries and
Zimmerman, 1980; National Research Council of Canada, 1981; Henriksen, 1982;
Kramer and Tessier, 1982; Church, 1983). Precision may also be significantly
less with colorimetric procedures because of uncertainty as to the exact
endpoint (Kramer and Tessier, 1982; Church, 1983). In contrast, the double
endpoint procedure and the procedure of Gran are unbiased and more precise for
low alkalinity waters (Gran, 1982; American Public Health Association, 1980;
Church, 1983).
When making our final interpretations of spatial patterns of the data and
subsequent map unit delineations, we attempted to compensate for the probable
bias introduced by selected analytical procedures. If actual endpoint pH
values of the titrations had been known, then quantitative procedures might
have been applied to correct for bias (National Research Council of Canada,
1981; Henriksen, 1982; Kramer and Tessier, 1982; Church, 1983), but because of
the lack of such information, adjustments were not possible. However, a
comparison of values for a large group of lakes in northern Wisconsin where we
obtained recent values determined by Gran's titration, as well as earlier
values determined by colorimetric endpoint, indicated a pattern of overestima-
tion by the colorimetric methods of about 30 or 60 ueq/1, depending on the
particular colorimetric method used (Figure 1). Haines and Akielaszek (1983)
found a similar overestimation (32 ueq/1) in their comparisons of values for a
set of New England lakes. Based on these comparisons, we adjusted the earlier
Wisconsin data by subtracting 30 ueq/1 (if methyl orange) or 60 ueq/1 (if
methyl purple) when we color-coded the county maps. Elsewhere in the Upper
Midwest where representative sites had borderline or slightly above borderline
values between alkalinity classes (e.g., 50, 100, 200, and 400 ueq/1) and where
the alkalinity methods had been other than double endpoint or Gran's titration,
we assigned the respective areas to the lower alkalinity class and drew the map
units accordingly. However, in many cases the compensation may not have been
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700
600
o 500
in „
-'
0,0
400
300
200
100
o..
• . .
..ONEIDA CO
N « 123 ' >
..VtLAS CO-
N = 6« i ~
X = IITY +
t*
93
3*
100
200
300
400
500
600
700
800
WISCONSIN CONSERVATION DEPARTMENT
Vilas Co. -I960 & 61 Methyl orange
Oneida Co. -1966 Methyl purple
Figure 1. Single sample alkalinity values from two time periods for lakes in
Vilas and Oneida counties, Wisconsin. Source: Andrews and
Threinen (1966), Black et al. (1963), Depository of Unpublished Data.
enough to account for the bias due to methodology as suggested in the sources
cited above. Hence, the areas in the lower alkalinity classes may actually be
slightly larger than is shown; e.g., the actual areas shown as map unit #1
(< 50 ueq/1) may include some of the adjacent areas shown as map unit #2 (50 to
100 ueq/1), the areas shown as map unit #2 may include some of the adjacent
areas shown as map unit #3, etc.
Another area of concern is the use of single sample values as representa-
tive data points. Since the alkalinity of surface waters can fluctuate on a
daily, weekly, monthly, and annual basis, a single sample from a water body may
not seem to be representative of that lake or stream's average alkalinity. We
believe, however, that for the purposes of this map, one-sample data points are
sufficiently representative to be used in the assessment of spatial patterns
and delineation of the alkalinity class boundaries. The comparison of alka-
linity values for northern Wisconsin lakes determined using different labora-
tory methods and taken during different time periods (Figure 1) also serves as
an illustration of the usefulness of single sample values for our purposes.
SEASONAL VARIATION
Surface water alkalinity of lakes and streams is subject to seasonal and
annual fluctuations due partially to climatic, meteorologic, and related
hydrologic events. Seasonal variations of alkalinity concentrations in the
Upper Midwest Region appear to have distinct patterns, due especially to runoff
from spring snowmelt.
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Recent data showing complete month by month and seasonal trends for
surface water alkalinity in the Upper Midwest Region are scarce for lakes and
for streams with small watersheds. However, analysis of thirty-one stream
sites across the region with long-term monthly data showed an annual pattern of
higher alkalinity values in winter; a rapid drop in spring, with the lowest
alkalinity values occurring in April; and then another rise with a peak in
August (Figure 2). Although this pattern is based on data from mostly higher
alkalinity streams, some with very large watersheds, a similar seasonal pattern
seemed to occur in most streams throughout the region regardless of alkalinity
level or watershed
difference between
size. For the forty-one year-long data sets, the average
the low value month and the mean annual value of each
sampled stream was 52% (range 14-87%; median 55; standard deviation 14.8%).
Watershed and hydrological characteristics vary greatly from stream to stream,
of course, and have different influences on seasonal alkalinity trends.
Thornton et al. (1982) found that streams in Minnesota which are highly depen-
dent on runoff tend to have greater fluctuations in flow and greater fluctua-
tions in stream chemistry, while streams with large surface water storage areas
will have lesser fluctuations in flow and small fluctuations in stream chemistry,
3000-
2500-
2000-
1500-
1000-
500-
JFMAMJJASOND
Figure 2. Seasonal variations in alkalinity (ueq/1) at thirty-one stream sites
in the Upper Midwest Region (twenty-two in Minnesota, four in
Michigan, and five in Wisconsin). Forty-one year-long data sets are
represented. Source: STORE! 1979-1981.
Declines in alkalinity concentrations during spring snowmelt and in
conjunction with precipitation events can be dramatic for streams, but for
lakes the seasonal fluctuations appear to be less extreme. Low alkalinity
lakes also appear to have lower spring values, but the data are too limited to
adequately assess seasonal fluctuations and trends. Most of the low alkalinity
lakes are represented by only one or a few alkalinity samples pe.r year. A
comparison of spring, summer, and fall alkalinity values for twelve northern
Minnesota lakes revealed that, on the average, the spring alkalinities were
7
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only 14% lower than the mean values (Heiskary and Thornton, 1983). A greater
percentage difference might have resulted had values of the lowest month only
(April or May) been compared to mean annual values that included higher winter
values as well. However, from our synoptic analyses of alkalinity values from
thousands of lakes in the Upper Midwest, seasonal fluctuations do not appear to
vary greatly outside the range of values in the classes designated on our
alkalinity map.
REGIONAL PATTERNS
The Upper Midwest Region exhibits great diversity and spatial hetero-
geneity in its patterns of surface water alkalinity. Several factors contrib-
ute to the complexity of these patterns, especially lake types, sizes, and
their hydrologic characteristics; bedrock geology; land surface forms; and soil
characteristics. The formation of these lakes, surface features, and soils
reflect the region's glacial history. As a result of glacial action, this
region contains one of the densest concentration of lakes in the world.
While nearly all of the streams and a great majority of the lakes in the
Upper Midwest Region have high mean annual alkalinity values (> 400 ueq/1),
there are several areas where a considerable number of lakes have low alkalin-
ity values (< 50 ueq/1). Although relatively large in number, the lakes in the
lowest alkalinity class tend to be small in size and comprise only a small
percent of the region's total surface water area (Table 1). The lakes of
average alkalinity values < 200 ueq/1 comprise only 6.6% of the region's
surface water area. Clusters of lakes with alkalinities < 50 ueq/1 are found
in portions of Vilas, Oneida, Lincoln, and Langlade counties of Wisconsin, as
well as Gogebic, Iron, Alger, and Chippewa counties of Michigan.
The map depicts generalized patterns of surface water alkalinity and is
intended to show the range of values within which one might expect the mean
annual alkalinities for most of the surface waters for each classified area.
Table 1. Area (hectares) in lakes by alkalinity class.*
Alkalinity
Class
< 50 ueq/1
50 - 100
100 - 200
Wisconsin
6,400
5,595
17,843
Minnesota
0
13,982
68,423
Michigan
1,686
1,426
8,948
Total
8,086 (0.4%)
21,003 (1.1%)
95,214 (5.1%)
< 200
29,838
82,405
12,060
124,303 (6.6%)
Total lake area in the Upper Midwest Region (Northern
Wisconsin, Northeastern Minnesota, and Northern Michigan) 1,868,799 hectares
* Lakes > 6 hectares (15 acres). Based on extent of surface water appearing
on 1:250,000-scale USGS topographic maps.
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Although some areas are predominantly of low surface water alkalinity, other
areas are characterized by wide ranges in alkalinity and contain various lake
sizes and lake types that are in close proximity to one another. Thus, care
should be taken in interpreting the mapped patterns. Even in areas classified
as containing waters of predominantly > 400 ueq/1, there may be a few lakes,
but probably no streams, that are of low alkalinity.
Examination of the physical and chemical characteristics of streams and
lakes suggests three loosely delineated subregions within the Upper Midwest
Region. Distinctions can be made between: (1) most of northern Wisconsin and
east central Minnesota; (2) northeast Minnesota comprising Cook, Lake, and
St. Louis counties; and (3) the major portion of Michigan's Upper Peninsula and
the northern portions of Bayfield, Ashland, and Iron counties in Wisconsin
(Figure 3). These subregions, while individually containing variations in
surface water alkalinity, can be broadly differentiated by certain physical
characteristics that influence the alkalinity patterns. Factors that directly
affect alkalinity such as geology, land surface form, and soils, show subtle
variations in the different subregions. Integrating factors such as potential
natural vegetation, or especially land use, which generally correlated with
alkalinity in some other parts of the nation (Omernik and Powers, 1983), were
of less significance for determining alkalinity patterns in the Upper Midwest
Region.
Subregion Boundary
Figure 3. Subregions of the Upper Midwest Region,
Wisconsin-East Central Minnesota
In the northern Wisconsin-east central Minnesota subregion, the differ-
ences in lake types [without inlets or outlets (Type A), with inlets or outlets
(Type B), spring-fed, acid bog, alkaline bog], and the large number of lakes of
each type, contribute to the extreme heterogeneity of surface water alkalinity.
While most of the lakes without inlets or outlets are of low alkalinity, the
streams, spring-fed lakes, and lakes with inlets or outlets are generally of
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high alkalinity. The continental glaciation left a relatively thick layer of
glacial drift over this part of the Upper Midwest, and most of the lakes occur
in pitted outwash and end moraines. These lakes are usually situated well
above bedrock and are relatively shallow. For example, in Oneida County,
Wisconsin, 88% of the lakes are less than 7.6 meters deep (Andrews and
Threinen, 1966). Apparently, for much of this subregion, bedrock has very
little influence on lake chemistry and lake morphology.
The major land forms in this subregion include outwash plains, ground
moraines, end moraines, lacustrine plains, and drumlins. In the Minnesota
portion, in particular Carlton, Crow Wing, and Itasca counties, Twaroski et al.
(1984) concluded that lake forms seem to exert a greater influence on lake
chemistry and lake morphology than does bedrock. They found that, based on
slope and soils, moraine areas are most likely to contain low alkalinity lakes.
These lakes are generally small, with no inlets; are located in interfluvial
areas; are surrounded by steep slopes and soils that create a quick release of
water to the lake; and receive no groundwater inflow (Twaroski et al., 1984).
While they found that lakes tended to have high alkalinities in outwash plains
in east central Minnesota, many of those portions of Wisconsin within our map
unit #1 (< 50 ueq/1) and map unit #2 (50-100 ueq/1) are found in outwash plains
and in end moraines. The general difference between moraines or outwash plains
appears to be of less significance than more specific factors that influence
lake alkalinity in this subregion. Of more importance seem to be groundwater
contact, lake size, watershed size, stream inflow and outflow, as well as the
texture and mineralogy of the soil and the local relief. High alkalinity lakes
tend to be large, with significant inlets and outlets, with large watersheds,
and with substantial groundwater contact. A key factor affecting the alkalin-
ity of lakes in this subregion is hydrology, or the route and residence time of
water in the watershed (Eilers et al., 1983; Twaroski et al., 1984). The
relationship of groundwater to lakes is of major importance and helps to
explain why high alkalinity lakes are found in close proximity to low alkalin-
ity lakes, but it is the least known aspect of lake hydrology (Winters, 1977).
Several areas of surface waters with mean annual alkalinity < 50 ueq/1 are
found in this subregion, centered around Vilas and Oneida counties, Wisconsin.
Including all of the low alkalinity areas in Wisconsin, as well as the area in
southern Gogebic and Iron counties, Michigan, this subregion has roughly 7,250
hectares of lakes (> 6 hectares) that fall within the map unit #1 boundaries.
These areas predominantly contain clusters of low alkalinity lakes without
inlets or outlets (Type A). Although the number of lakes in these areas is
generally large, the total area of surface water is relatively low since Type A
lakes tend to be small in size. For example, of the 1,327 lakes in Vilas
County, Wisconsin, 776 (59%) are Type A lakes of less than eight hectares in
size, but these account for only 4% of the county's lake area (Table 2). On
the other hand, only 88 (7%) of the lakes in the county are Type B lakes or
spring lakes greater than 80 hectares, yet these types comprise 63% of the
county's lake area. Thus, for Vilas County, the greatest extent of lake area
is in the higher alkalinity classes, and the average (uncorrected methyl
orange) alkalinity of 298 ueq/1 (Black et al., 1963) is skewed downward by the
large number of low alkalinity but small Type A lakes.
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Table 2. Characteristics of lakes in Vilas County, Wisconsin. Alkalinity
values were determined by single endpoint titration (colorimetric --
methyl orange) and, although reported in mg/1, have been converted to
ueq/1 in the table. Source: Black et al. (1963).
Size Class
Hectares
0-7
8-23
24-39
40-80
81-201
202-404
405-808
809
Total
Lake Type A
(Without inlets or outlets)
*
776
145
35
32
13
6
1
-
1008
Mean
Size
(ha)
2.0
13.6
31.1
55.2
117.2
285.9
-
-
10.1
Total
Hectares
1554 (4%J
1969 (5%)
1089 (3%)
1767 (5%)
1523 (4%)
1716 (5%)
582 (1%)
-
10,200 (27%)
Samplod lakoi.
Mean
Alk
174
136
172
158
386
332
40
-
170
*
493
145
35
31
12
6
1
-
723
Lake Type B
(With inlets or outlets)
#
31
24
19
27
38
26
9
4
178
Mean
Size
(ha.)
2.3
15.1
30.6
58.3
127 8
286.9
504.4
1299.6
138.5
Total
Hectares
72
362 (1%)
581 (2%)
1574 (4%)
4858 (13%)
7461 (20%)
4540 (12%)
5198 (14%)
24,646(66%)
Sampled lakes
Mean
Alk.
449
546
640
678
756
762
830
700
664
*
23
22
19
27
38
26
9
4
168
Spring Lakes
*
97
13
12
8
9
2
-
-
141
Mean
Size
(ha.)
1.6
15.6
32.3
60.9
108.5
210.6
-
-
18.7
Total
Hectares
158 -
203 -
388 (1%)
487 (1%)
977 (3%)
421 (1%)
-
-
2.634 (7%)
Sampled lakes
Mean
Alk.
693
626
988
772
902
720
-
-
755
*
27
12
8
8
9
2
-
-
66
Streams comprise a very small fraction of the surface water area in much
of this subregion, and stream alkalinity is, on the average, much higher than
that found in lakes. In Vilas County, Wisconsin, streams comprise only 1.4% of
that county's total surface water area, and most streams are small, reflecting
the general headwater location of the county. The mean methyl orange alkalin-
ity (unconnected) for the 151 streams in Vilas County was about 794 ueq/1, with
a range of 130 to 1840 ueq/1 (Black et al., 1963). Only 14 streams (9%) were
determined to have alkalinities < 400 ueq/1, and only 5 streams (3%) had
alkalinity values < 200 ueq/1. For much of this subregion, stream alkalinity
often appears to be twice as high as the mean alkalinity values of nearby
lakes. In general, streams have higher alkalinity than lakes as a result of
having larger drainage areas and greater contact with buffering materials.
The largest area of lakes with alkalinities < 50 ueq/1 is located in
Oneida County, Wisconsin, and contains 109 named Type A lakes ranging from 0.8
hectares to 425 hectares in size. The mean size of these 109 lakes is 27
hectares, ar>d the median size is 12 hectares. Most of this area occurs in a
pitted glacial outwash plain, with sandy acidic soils of low fertility that
typify much of Oneida County. Frequency distributions for recent and histor-
ical data sets of thirty-seven representative lakes in this map unit #1 area
give a general idea of: (1) the proportion of lakes within the lowest map unit
areas of this subregion that have mean annual alkalinity values within the < 50
ueq/1 range; (2) the proportion that have higher values; and (3) some notion of
11
-------
central tendency. These frequency distributions also illustrate the differ-
ences in alkalinity values due to the different methodologies, and support our
adjustment of 60 ueq/1 for the data determined by the colorimetric methyl
purple methodology (Figure 4). In this comparison, 58 ueq/1 was the difference
between the mean of the methyl purple alkalinity data and the mean of the data
determined by Gran's titration.
100
so
60
40
20
N = 37
mean = 63
median = 36
range = -9 - 368
stand, dev. = 75
100-
80-
cfl
O
£ 6°
0 40-
s«
20-
N - 37
mean =121
median = 100
range =* 40 - 420
stand, dev. = 83
<0 50 100 150 200 400
Alkalinity Meq/l
Gran titration
0 50 100 150 200 400 >400
Alkalinity neq/\
Colorimetric — methyl purple
Figure 4. Frequency distributions of thirty-seven representative lakes in an
Oneida County, Wisconsin, map unit #1 area. Source: Glass et al.
(1983), Andrews and Threinen (1966).
Northeast Minnesota
The northeast Minnesota subregion includes Cook, Lake, and northeastern
St. Louis counties, and exhibits considerably more homogeneity in surface water
alkalinity than the other subregions. Lakes of various types and sizes, as
well as streams, tend to have more similar alkalinity values. The processes of
glacial erosion and glacial deposition produced an extremely high density of
lakes and extent of area in lakes in this subregion.
A wide variety of bedrock types is found in this subregion, and because
the soil and glacial till are relatively shallow, bedrock appears to have a
greater influence on lake morphology and lake chemistry. In general, the
gabbros, granites, and iron formations contain lakes with relatively lower mean
alkalinity values, mostly less than 200 ueq/1 (Twaroski et al., 1984). These
formations are non-calcareous and resistant to weathering, with thin overlying
soils that provide little buffering capacity to the lakes. The slates and
greenstone formations contain lakes of higher alkalinity, mostly 400 ueq/1 or
greater, and, although generally non-calcareous, have some veins of calcite
that may greatly influence lake sensitivity (Heiskary and Thornton, 1983).
Some calcareous soils are found in the Ely greenstone northeast of Ely, as well
as in the large area west of St. Louis County that corresponds to deposits from
glacial Lake Agassiz. In addition, the slates and greenstone have faults and
fractures which may supply groundwater to these areas of higher alkalinity
(Twaroski et al., 1984). For most of this subregion, however, groundwater
12
-------
resources are very limited due to the shallow drift and Precambrian crystalline
bedrock types and do not affect alkalinity as in Wisconsin or central
Minnesota.
A considerable extent of map unit #2 alkalinity (50-100 ueq/1) occurs in
the extreme northeastern part of Minnesota. We estimate that approximately
14,000 hectares in lakes fall within the three areas designated as map unit #2
(of lakes greater than 6 hectares). These three areas are based on data from
forty lakes, and were delineated primarily by noting the spatial pattern of
these values as well as surrounding lake alkalinity values. Approximately 70%
of these forty lakes have alkalinity values less than 100 ueq/1 (Figure 5).
100-
80-
60-
tft
a>
N = 40
mean =93
medians 94
-------
bedrock geoprovince. Small amounts of limestone, veins of calcite, or ancient
glacial lake deposits may increase the buffering of otherwise sensitive
bedrock. We found that for most of the Upper Midwest Region, bedrock by itself
was not a good indicator of surface water alkalinity.
Upper Michigan
The third subregion -- most of the Upper Peninsula of Michigan, and the
extreme northwest portion of Wisconsin in Bayfield, Ashland, and Iron counties
-- is physically more heterogeneous, with fewer lakes than the other subregions,
and wide variations in surface water alkalinity. Most of the lakes occur in
glacial outwash plains and moraines, although a few are found on bedrock
outcrops and on ancient lacustrine deposits.
The eastern part of the peninsula varies from smooth plains to irregular
plains with hills. This area is characterized by sandy and silty surficial
features from the predominant ancient glacial lake bed deposits, with a mixture
of alkalinity values. In the southeast part of the peninsula, some lakes are
located on bedrock, but the presence of limestone results in high surface water
alkalinities. The areas of lowest surface water alkalinity appear to be
located in areas of glacial till, and the chemical and physical nature of this
till, along with the amount of groundwater contact, drainage basin size, and
lake type, greatly influence the degree of buffering capacity. The streams and
lakes in these lower alkalinity areas are also located in the uppermost reaches
of tne watersheds, where topographic watersheds are even roughly definable.
[Surface and subsurface watersheds frequently are difficult or impossible to
define, particularly in areas of continental glacial topography (Hughes and
Omernik, 1981)]. Many of the low alkalinity lakes are without outlets. For
the two areas within map unit #1 (< 50 ueq/1) in the eastern portion of the
Upper Peninsula there are recent alkalinity values for four lakes and two
streams (Table 3).
In the western half of the Upper Peninsula, most of the lakes occur in
glacial till, and, as in Wisconsin, alkalinity values appear especially related
to lake and watershed size, lake type, and the amount of groundwater contact.
Table 3. Alkalinity (ueq/1) values in map unit #1 in the Upper Michigan
Subregion. Source: Glass et al. (1983). Methodology: Gran titra-
tion.
Mean: -2.7 ueq/1
Median: -8.0
Range: -36 to 34
Standard Deviation: 29
List of Values: -36, -27, -15, -1, 29, 34
14
-------
A few lakes are located on bedrock in Baraga and Marquette counties, and these
tend to be moderately low in alkalinity (100-200 ueq/1).
Summa ry
Our map of total alkalinity of surface waters in the Upper Midwest Region
of the United States illustrates the general patterns of the relative potential
sensitivity of surface waters to acidic input in that region. The map was
developed through analysis of the spatial patterns of alkalinity values from
over 14,000 representative lakes and streams, as well as through determination
of apparent spatial associations between these data and various watershed
characteristics believed to be causal. We found alkalinity patterns in the
region to be extremely varied and complex. Many lakes in the region have
relatively low alkalinities, but they tend to be small in size, comprise a
small percent of surface water area, and occur in relatively small clusters.
Most streams exhibit high alkalinities. In northeastern Minnesota, however,
there are areas of relatively low alkalinity in which all lakes regardless of
size, and even streams, have similar values.
15
-------
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17
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Haines, T. A., and J. J. Akielaszek. 1983. A regional survey of chemistry of
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18
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Omernik, J. M., and C. F. Powers. 1983. Total alkalinity of surface waters --
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Hydro. Univ. of Toronto.
19
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