Oceanogr., 41(5), 1996, 1124-l 135
0 1996, by the American Society of Limnology and Oceanography, Inc.
Limnol.
Simulated long-term temperature and dissolved oxygen
characteristics of lakes in the north-central
United States and associated fish habitat limits
H. G. Stefan
St. Anthony Falls Laboratory, Department of Civil Engineering, University of Minnesota, Minneapolis 554 14
AI. Hondzo
School of Civil Engineering, Purdue University, W. Lafayette, Indiana 47907
X. Fang
Department of Civil Engineering, Lamar University, Beaumont, Texas 777 10
J. G. Eaton and J. H. McCormick
U.S. Environmental Protection Agency, ERL, Duluth, Minnesota 55804
Abstract
Water temperatures and dissolved oxygen (DO) concentrations in lakes are related to climate. Temperature
and DO in 27 lake classes (3 depth classes x 3 surface area classes x 3 trophic states) were simulated by
numerical models with daily weather data input. The weather data used are from the 25-yr period 19551979. The lakes and the weather are representative of the north-central U.S. Daily profiles ofwater temperature
and DO concentrations were computed and several temperature and DO characteristics extracted from this
information base. Temperature and minimum oxygen requirements for good growth of cold, cool, and warm
water fish were then applied to determine the length of the good-growth periods and the relative lake volumes
available for good growth. All characteristics are presented in graphical form using lake surface area, maximum
lake depth, and Secchi depth as independent variables. The surface area and maximum depth were combined
in a lake geometry ratio which is a relative measure of the susceptibility of a lake to stratification; Secchi
depth was retained as a measure of lake transparency and trophic state. To determine an effect of latitude,
we investigated a southern and northern region separately. The effect of climate change due to a projected
doubling of atmospheric CO, was investigated by applying the output from the GISS 2 x CO, global circulation
model to the lake models.
of projecting characteristics of similar lakes for which
only surface area, maximum depth, and midsummer Secchi depth are known. This procedure permits the comparative study of many lakes over long periods of time.
Parameters characterizing long-term averages of water
temperature, DO, and associated fish habitat in lakes are
presented for climate conditions that existed from 1955
to 1979. The results are from simulations for the openwater season and include the typical summer stratification
of lakes in the north-temperate region. They are presented
in a form that allows interpolation and quantitative comparison among lakes with different morphometries and
trophic levels. For better appreciation of the results, a
brief description of the model formulations, input data
requirements, and accuracy is also provided. The models
have been validated with actual data from a wide range
Acknowledgments
of lakes with different morphometries, trophic levels, and
The investigation described herein was conducted for the U.S.
meteorological conditions.
Environmental Protection Agency/OPPE in cooperation with
The results are for two regions covering latitudes from
the Environmental Research Laboratory, Duluth, as a part of a
46’10’
to 49” (northern region) and 43”30’ to 46’10’
project on climate change effects on fisheries. The Minnesota
(southern
region). The southern region has a mean avSupercomputer Institute, University of Minnesota, provided a
erage annual temperature - 4°C warmer than the northern
resource grant and access to its CRAY2 supercomputer.
region. The effect of a doubling of atmospheric CO2 on
Eville Gorham and Joseph Shapiro provided valuable sugthe simulated lake characteristics was also investigated.
gestions that considerably improved the manuscript.
1124
The following is an analysis of recently completed simulations that project long-term average water temperature
and dissolved oxygen conditions in lakes of the northcentral U.S. and their suitability for fish habitat. Minnesota was selected for this study because it has many
valuable lakes, an extensive lake database, and is located
in the center of the continent. It is also at a latitude where
climate change may have the greatest impact on aquatic
ecosystems. Baseline water-quality simulations were made
with historical records of meteorological parameters
known to influence the temperature and the dissolved
oxygen (DO) of north-temperate lakes. We used processoriented, deterministic numerical modeling which, when
sufficiently calibrated and validated, offers the possibility
Long-term temperature and oxygen
The output of the Goddard Institute for Space Studies
(GISS), Columbia University global circulation model,
was used to specify the future climate scenario. The GISS
2 x CO2 model predicts a 3.8”C air temperature increase
for the northern Minnesota region.
--,
1125
Lake classltication by
- surface area
- maxlmum depth
- Secchi depth
relation
Area - r 0epn-d
I
4il
Simulation methods for water quality and
fish habitat
A deterministic, process-oriented, unsteady, one-dimensional model of lake-water quality was used for these
simulations. This model has been successfully applied to
simulate hydrothermal processesand water quality in lakes
for a variety of meteorological conditions (e.g. Ford and
Stefan 1980a; Riley and Stefan 1987; Hondzo and Stefan
199 1, 1993a). The water-quality model was verified for
16 lakes of different morphometries and trophic levels,
and with different meteorological conditions (Hondzo and
Stefan 19933; Stefan et al. 1993; Stefan and Fang 1993,
1994). The standard error of the water temperature predictions was from 0.5 to 1. 1°C for individual lakes. The
standard error of the predicted DO values was from 0.6
to 2.3 mg liter- l. With these water-quality models, simulations of water temperatures and DO were made for 27
classes of lakes in the southern and northern Minnesota
regions. The 27 lake classes are derived from the product
of 3 depth classes x 3 surface area classes x 3 trophic
classes. The computational sequence is graphically summarized in the flow-chart of Fig. 1. The simulation model
was operated on daily timesteps. Simulated vertical profiles of daily water temperatures and DO concentrations
were obtained for the open-water season, the length of
which was found by the model itself (Hondzo and Stefan
199 1). Southern Minnesota lakes are usually ice free from
April to November and northern Minnesota lakes from
May to October.
The presence of fish in a lake is, in general, related to
accessibility, ecological suitability, human interference,
and resistance to episodic natural events (Fry 1971).
Among the environmental factors limiting survival and
growth of fish, temperature and DO concentrations are
considered the two most significant (Coutant 1987; Christie and Regier 1988; Magnuson et al. 1990). In this study,
the suitability of habitats for cold water, cool water, and
warm water fish was assessedin terms of these two factors
only. The concept is briefly illustrated in Fig. 2. The results indicate which lakes have temperature and DO conditions suitable for survival and good growth of fish. For
this purpose, fish having similar thermal requirements
were grouped as thermal guilds (cold water, cool water,
and warm water). Actual fish observations in 3,002 Minnesota lakes were compared with simulated suitable fish
habitat based on water temperatures and DO concentrations. Good agreement between fish observations and numerical simulations of fish habitat was found (H. G. Stefan et al. UMN-SAFL Proj. Rep. 347).
the lake surface and hydrologic inputs from the lake basin.
Solar radiation and atmospheric longwave radiation heat
the water column; evaporation and back radiation cool
it. Convective heat transfer driven by the temperature
difference between water and air can also warm or cool
a lake. The differential radiative heat absorption throughout the lake depth causes thermal stratification. The
stronger the stratification, the more quiescent the water
body. Wind exerts a drag force on the surface of the lake
which, through a variety of external and internal wave
motions tends to vertically mix the stratified water column (partially or completely). The external mechanical
energy input from the wind is opposed by the potential
(buoyant) energy “locked” in the stratification. The stronger the stratification, the more mechanical energy is needed to mix the water column. The water temperature model simulates these processesby a set of deterministic equations which is described in detail elsewhere (H. G. Stefan
et al. UMN-SAFL Proj. Rep. 347).
Water temperature and thermal stratification simulation -A lake is exposed to meteorological forcing through
Dissolved oxygen concentration simulation -The major
components affecting the DO concentration in the lake
Fig. 1. Schematicillustration of the simulation procedure.
Stefan et al.
1126
a>
B
4d
Mar
b)
Apr
Jun
Jul
Aug
Sep
Ott
Nov
Dee
Ott
Nov
Dee
Dissohred oxygen (mg liter“)
Mar
c>
May
Apr
May
Jun
Jul
Aug
Sep
Fishhabltat quality
Mar
Apr
May
Uninhabttable
Jun
IsI
Jul
Aug
Good
Sep
growth
Ott
Nov
0
Dee
Restricted
growth
Fig. 2. Schematic illustration of the distribution across time
and depth of water temperature isotherms, dissolved oxygen
(DO) isopleths, and those isotherms and DO isopleths which
are considered for the survival and growth of a fish species in
a seasonally stratified lake. LGGT-lower
good-growth temperature limit; UGGT-upper good-growth temperature limit;
LT-lethal temperature.
are plant respiration, photosynthesis, biological and sedimentary oxygen demand (largely microbial respiration
and chemical oxidation), and surface-layer oxygenation.
DO transfer at the water surface and photosynthesis can
increase DO concentrations in the water column. The
sedimentary oxygen demand (SOD), biochemical oxygen
demand (BOD), and plant and microbial respiration (R),
are DO sinks in the water column. The nitrification process is omitted because it makes a minor contribution to
the state of oxygen in the lake as a whole (Stefan and
Fang 1994).
Fish habitat projection - The effects of water temperature on freshwater fish have long been recognized (e.g.
Hokanson 1977; Coutant 1972; Magnuson et al. 1979;
Meisner et al. 1987). An overview of the temperature
effect literature and upper thermal tolerance limits for
cold, cool, and warm water species was given by Eaton
et al. (1995). Similarly, low DO concentrations limit the
survival of fish. Water temperature and DO place severe
physical constraints on fish habitat in freshwater lakes.
Other factors such as food, predation, episodic effects,
and human interference are also important.
Herein, water temperature and DO levels are the only
two parameters used to determine fish habitat. Each parameter value is an average calculated from the simulation of 25 yr of daily water temperature and DO profiles
in a lake. This procedure finds substantial justification in
the extensive and well-documented studies of fish thermal
biology (Eaton et al. 1995).
Temperature criteria for fish habitat were developed
from laboratory and field data as described by Eaton et
al. (1995), and the guild (cold water, cool water, warm
water) designations for various species are as suggested
by Hokanson (1977). Temperature ranges for good growth
of these three thermal guilds, which comprise a total of
28 species were 9.0-18.5”C for cold water, 16.3-28.2”C
for cool water, and 19.7-32.3”C for warm water species.
The upper survival temperature limits used for each of
these guilds were 23.4”C for cold water, 30.4”C for cool
water, and > 30.4”C for warm water species. Fish survival
and good-growth temperature criteria were related to simulated daily water temperatures and DO concentrations
as shown schematically in Fig. 2. Three isotherms were
chosen for each guild; the lethal temperature (LT) threshold, the upper good-growth temperature limit (UGGT),
and the lower good-growth temperature limit (LGGT).
DO limits of 2.5 mg liter-l for warm water fish and
3.0 mg liter-l for cool water and cold water fish were
based on the U.S. Environmental Protection Agency water quality criteria document (U.S. EPA 440/5-86-003).
The isopleth that designates the critical DO survival value
is also shown in Fig. 2. Between the lines in Fig. 2, three
habitat qualities can be identified: uninhabitable space
where the temperature is above or the DO is below the
survival or threshold limit for seven consecutive days;
good-growth habitat if the temperature is between the
upper and lower good-growth limits and the DO is above
survival limit; and restricted-growth habitat if the temperature is above the upper good-growth limit and below
the upper survival limit, or if the temperature is below
the lower good-growth limit (in all casesthe DO must be
above the survival limit).
Databases
Meteorological data- The meteorological database used
as input to the long-term lake simulations consisted of
that for the 25 yr from 1955 to 1979. The meteorological
data file contained average measured daily values for air
temperature, dew point temperature, precipitation, wind
speed, and solar radiation. The period from 1955 to 1979
was chosen because it is long enough to give a representative average and variance on recent conditions in the
chosen study area. Data from the Minneapolis-St. Paul
International Airport (44.5 3”N, 93.13”W) and Duluth
(46. 50°N, 92.1 low) were used for the southern and northern regions. Numerical values for the mean monthly meteorological parameters for these stations are summarized
in Table 1.
1127
Long-term temperature and oxygen
Table 1. Mean monthly meteorological data for Minneapolis-St. Paul and Duluth, Minnesota, 25-yr averages ( 1955-l 979). Air temperature (“C)- AT; dew point temperature (“C)DT; solar radiation (cal cm-2)- SR; wind speed (m s- l)- WS.
Duluth
Mar
Apr
May
Jun
July
Aw
Sep
Ott
Nov
Mean
SD
AT
-4.7
2.9
9.9
15.0
18.4
17.4
12.4
7.1
-2.2
8.5
7.9
DT
-9.8
-3.4
2.6
9.1
12.8
12.5
7.9
2.0
-6.3
3.0
7.7
Minneapolis-St. Paul
SR
WS
344.8
417.2
471.5
504.4
517.0
441.3
317.3
211.5
125.9
372.3
127.1
5.1
5.6
5.3
4.6
4.3
4.2
4.6
4.9
5.2
4.9
0.4
Lake data-The Minnesota Lakes Fisheries Database
(D. Schupp pers. comm.; B. Goodno pers. comm.) contains lake survey data for 3,002 lakes. The database includes 22 physical variables and all common fish species.
Nine primary variables explain 80% of the variability
among lakes. These nine variables include surface area,
volume, maximum depth, alkalinity, Secchi depth, lake
shape, shoreline complexity, percent littoral area, and
length of growing season. Geographic subdivision of the
lakes was approached in a variety of ways. First ecoregions (Omernick 1987) were considered, but found to give
too detailed a picture. An ecoregion is defined as a region
with homogeneous trophic, geologic, vegetative, and landuse features. Then the entire set was considered as a regional entity but that was rejected as too large because of
the diversity of climate. Finally, division of the lakes into
a northern and southern set was considered appropriate
because there is a significant difference in geological, hydrological, climatological, and ecological parameters between the northern and southern half of the state (Baker
et al. 1985; Heiskary et al. 1987; D. Schupp MNDNR
Invest. Rep. 417; Hondzo and Stefan 1993b).
To develop a classification, we selected lake surface
area, maximum depth, and mean Secchi depth as the
AT
-1.3
7.7
14.6
19.9
22.8
21.5
15.8
9.8
0.5
12.4
8.3
DT
-6.9
0.2
6.6
12.8
15.9
15.0
10.0
3.9
-3.5
6.0
7.7
SR
WS
333.6
396.4
477.2
528.3
546.6
469.9
358.4
250.8
139.3
388.9
126.5
4.9
5.4
5.0
4.5
4.1
4.0
4.2
4.5
4.8
4.6
0.4
main independent lake parameters. These three parameters were chosen because the first two have a direct relationship to stratification dynamics of lakes. Secchi depth
was chosen because it is correlated with lake transparency,
trophic state, and biochemical and biological oxygen demand.
Lake surface area (surrogate for wind fetch) and maximum lake depth are used as indicators to differentiate
between seasonally stratified and seasonally polymictic
lakes (Lathrop and Lillie 1980; Niirnberg 1988; Gorham
and Boyce 1989; Demers and Kalff 1993). The criterion
for lake stratification given by Gorham and Boyce (1989),
mainly for the mid-North American continent (for lakes
of surface area <25 km2), is adequately represented by
the regression equation fl,,, = 0.34 As0.25.The same
equation can be rewritten in terms of the lake geometry
ratio (i.e. As0.25: Hmax= 2.9). Values of the geometry ratio
As0*25
: H,, for 27 lake classesused in this study are given
in Table 2. Shallow lakes and lakes with large surface area
and medium depth (Aso. : H,,, > 2.9) are expected to
be seasonally polymictic according to the seasonal stratification criteria given above. The rest of the lakes are
expected to be dimictic.
Solar radiation and wind also play an important role
Table 2. Physical parameters used to define 27 Minnesota lake classes.
Key parameter
Max depth, H,,,,, (m)
Surface area, A, (km2)
Secchi depth, 2, (m)
Descriptive
term
Shallow
Medium
Deep
Small
Medium
Large
Eutrophic
Mesotrophic
Oligotrophic
Lake class
Representative
value used
Range
4.0
13.0
24.0
0.2
1.7
10.0
1.2
2.5
4.5
14.0
4.1-20.0
20.1-45.0
10.4
0.5-5.0
5.1-40.0
51.8
1.9-4.5
4.6-7.0
Cumulative
frequency
Lower 30%
Central 60%
Upper 10%
Lower 30%
Central 60%
Upper 10%
Lower 20-50%
Central 20-50%
Upper 0- 10%
Lake geometry
AS
0.2
0.2
0.2
1.7
1.7
1.7
10.0
10.0
10.0
H max
4.0
13.0
24.0
4.0
13.0
24.0
4.0
13.0
24.0
4 : Kmx
5.3
1.6
0.9
9.0
2.8
1.5
14.1
4.3
2.3
1128
Stefan et al.
OLIGOTROPHIC
20
25
30
MESOTROP”,
40
35
EUTROPHIC
504
45
55
HYPEREUTR0Pf-K
65
60
70
75
60
TROPHIC STATE
INDEX
10
15
87
6
514
3
21
1.5
0.5
1
0.3
TRANSPARENCY
(rn)
21
0.5
CHLOROPHYLL
hwb)
3
4
5
71
10
15
20
30
40
60
60 100
150
a
7
ld
15
40
50
60
80
100
150
TOTAL P
(ppb)
Fig. 3. Carlson’s trophic state index related to several other Minnesota lake parameters
(aftei Heiskary and Wilson 1988).
in lake stratification but are less variable from lake to
lake in a given region than is lake morphometry (Ford
and Stefan 1980a). Secchi depth was chosen as a lake
trophic state indicator (Heiskary and Wilson 1988) because it is a commonly available parameter and can be
related to direct indicators of primary productivity through
Carlson’s trophic state index (Carlson 1977) (Fig. 3). Secchi depth or transparency also affects solar radiation attenuation and oxygen balance.
Combinations of the three values for the three key parameters defined 27 (3 x 3 x 3) lake classes for which simulations were made (Table 2). Representative area-depth
relationships were obtained from 3 5 lakes in a set of 122
lakes. Separate empirical equations were fit to the data
for the three lake sizes and used in the simulations as
representative area-depth relationships.
Results and discussion
Water temperature and thermal stratijkation characteristics-parameters which can be used to characterize
water temperatures and the thermal stratification in a lake
include surface temperature, bottom temperature, volume-weighted (avg) temperature, surface-to-bottom temperature difference, thermocline depth, dynamic stratification stability, linear temperature gradient, seasonal
stratification ratio, and heat content. Values of these parameters were estimated from the daily water temperature
profiles simulated over a 25-yr span. Each parameter is
correlated with lake geometry ratio (Aso.25
: H,,,) and Secchi depth. The results were plotted in a series of graphs
with lake geometry ratio and Secchi depth as axes (H. G.
Stefan et al. UM-SAFL Proj. Rep. 352). Samples of lake
water-quality characteristics with a direct relation to lake
biology are presented herein. The reader is reminded that
all values are 25-yr average values obtained by model
simulations. They cannot be compared to instantaneous
measurements in a lake unless the measurements span
an equally long period and are averaged.
The surface- water temperature isotherms plotted in Fig.
4 represent maximum daily surface-water temperatures
and are obtained by interpolation among 27 simulated
values more or less uniformly distributed over the graph
(Table 2 gives the coordinates). As can be seen, the surface
temperatures are about the same over a wide range of
lake morphometries and Secchi depths, but there is a
noticeable difference between north and south (i.e. regions
with different meteorological conditions). One can conclude that maximum surface-water temperatures are influenced primarily by the meteorological forcing and much
less significantly by lake geometry and trophic state. Daily
average meteorological variables that correlate most significantly with maximum surface-water temperatures and
which are different in the north and the south are air
temperature, dew-point temperature, and solar radiation.
There is a difference of - 1°C between lakes with a permanent seasonal stratification (dimictic lakes) and intermittently stratified lakes (polymictic lakes). The transition from one type of lake to another occurs at As0*25
:
-2.5-5.0 m-o.5 as indicated by Gorham and Boyce
(79%). Surface temperature is given here because it is
important to growth kinetics and survival of plants, fish,
and other organisms in lakes.
The water temperature at the bottom of a lake, unlike
surface-water temperature, is not directly related to the
meteorological forcing, especially in deeper lakes. The
bottom temperature reported is the maximum daily water
temperature 1 m or less above the lake sediments. It is
the temperature that can affect sediment oxygen demand
or fish survival. The simulated daily maximum bottom
temperatures given in Fig. 5 increase strongly when As0.25:
H maxincreases. This increase is related to the gradual
transition from dimictic (seasonally stratified) lakes to
polymictic lakes. The transition occurs when the geometry ratio exceeds a value of -4 (Table 2). The transition
is gradual as the strength of the stratification diminishes
gradually with higher geometry ratio, going from seasonally stratified (dimictic) lakes to polymictic lakes with
shorter and shorter stratification periods. Constant water
Long- term temperature and oxygen
5.0
I
I ,
I
I
0.8 1.0
2.0
4.0
I
I
nor h
’
I ‘III
o
0.6
5.0
I
,
I
(
south
6.0
’
1129
8.010.0
0.6
20.0
5
1’1’1
'i
111,
0.8 1.0
I,',
- south
I
2.0
I
4.0
1
I
I
8
I
I
1'1'1
6.0 8.010.0
20.0
1’1’1
2-
l-
0
0.0
(
0.6
5 , I ,
0.8 1.0
A
I
I
2.0
4.0
S
0.25
’ H
max
0
0.6
1’1’1
6.0
8.010.0
20.0
(m-09
Fig. 4. Maximum daily surface-water temperature (“C) isotherms (simulated 2%yr averages),
temperatures at A,o.25: Hmax > 8 indicate independence
from lake geometry (i.e. daily mixed lakes). There is probably also an asymptotic value of 4°C at As0.25: Hmax< 0.4.
Oligotrophic lakes have higher bottom-water temperatures than eutrophic lakes because of the difference in
solar radiation attenuation. Similar water temperature
trends are evident for northern and southern lakes. In
seasonally stratified lakes, hypolimnetic water temperatures are mainly determined by temperatures at spring
turnover. In summary, the maximum bottom-water temperature is highly correlated with the lake geometry ratio.
The d@erence between surface and bottom temperature
of a lake is an indicator of the strength of stratification
in a lake. Values of maximum daily water temperature
differences between the surface and the bottom are given
elsewhere (H. G. Stefan et al. UMN-SAFL Proj. Rep.
352). This temperature difference increases as the lakes
become more strongly stratified (i.e. as A,o.25: Hmax decreases). The largest difference is estimated for lakes with
the greatest depth and the smallest surface area. These
lakes typically have more wind sheltering. The strength
of the temperature stratification also depends somewhat
on the trophic state of a lake. Eutrophic lakes (with high
solar radiation attenuation with depth) have higher temperature differences than oligotrophic lakes.
,,I,
0.8 1.0
I
2.0
A
0.25 . H
max
s
’
4.0
1’1’1
6.0
8.010.0
20.0
(m-09
Fig. 5. As Fig. 4, but of daily bottom-water temperature.
An average water temperature (weighted by volume) in
the entire lake was also determined from the simulated
water temperature profiles. The maximum of the average
daily water temperatures is lower for stratified (dimictic)
lakes. The volume-averaged lake temperatures are higher,
by &4.0°C, in southern polymictic lakes compared to
northern polymictic lakes (geometry ratio >5). The difference drops to 3°C and 2°C when geometry ratios fall
below 4 and 1, respectively (i.e. stratification diminishes
differences in mean temperatures between lakes in different regions). Deep oligotrophic lakes have a higher
average temperature (i.e. heat content per unit volume)
than do eutrophic lakes of similar depth. This is because
they warm to greater depth than do their less transparent
counterparts.
The thermocline depth is another measure of stratification. It is estimated from the water density gradient
profile (Patterson et al. 1984). In most cases,thermocline
depth corresponds to the position of the maximum density gradient. Values for the maximum daily thermocline
depth relative to maximum lake depth are of interest. A
value of 1.O designates a fully mixed lake. Thermocline
depth decreases with decreasing As0.25: H,,,, and the trophic state of a lake contributes to the thermocline depth.
For the same lake geometry ratio, oligotrophic lakes have
a greater thermocline depth than eutrophic lakes. This is
1130
Stefan et al.
4-
3“m
0
2-
l-
o
I,),
0.6 0.8 1.0
5,
0)
20.0
1
0.6
1 ,I,
5
,I,
0.8 1.0
I/I,
I
I
2.0
4.0
I
I
8
10’1
6.0
1
I’I’I
8.010.0
south
20.0
i
43
N
0
0
:
5
3
CL
g
r
0
0
6
2-
_
-
l0;
0.6
8 ,I,
0.8 1 .O
I
2.0
A S 0.25 : H mc-Jx
I
4.0
~1’1’1
6.0
8.010.0
I
20.0
Cmmo5)
Fig. 6. Length (days) of seasonal stratification (simulated 25yr averages).
because eutrophic lakes attenuate solar radiation more
readily than similar oligotrophic lakes.
Seasonal stratijcation is defined herein as the condition
when the temperature difference between surface and deep
water is > 1°C. Although 1°C is an arbitrary criterion, it
is useful to identify variations of stratification with lake
geometry, trophic state, and geographic location (Fig. 6).
As a result of shorter summers in the north, the length
of the stratification season is also shorter there than it is
in the south. It is also noteworthy that the duration of
stratification in lakes with low geometry ratios is practically independent of Secchi depth. Those lakes with
small surface area and(or) great depth are prone to stratify
regardless of radiation attenuation. Secchi depth has,
however, a strong influence on the length of the stratification periods when lakes are polymictic.
A seasonal stratijkation ratio is defined as the total
number of days when stratification stronger than 1°C exists, divided by the period from the earliest to the latest
date of stratification (length of stratification season). A
seasonal stratification ratio < 1.Oindicates polymictic behavior, and a value of 1.0 indicates a dimictic lake (i.e.
once seasonal stratification is established, it lasts until fall
overturn). Results indicate that lakes with geometry ratios
in the range of 4 to at least 11, and probably more, are
0
0.6
#,I,
0.8 1.0
I
2.0
A 0.25. H
s
’ max
I
4.0
1
1’1’1
6.0 8.010.0
20 .O
(m-0’5>
Fig. 7. Minimum daily dissolved oxygen (mg liter-l)
pleths near lake bottom (simulated 25-yr averages).
iso-
polymictic. In this respect there is no strong distinction
between north and south.
Dissolved oxygen characteristics-parameters that can
be used to characterize DO concentrations in a lake are
surface DO, near-sediment DO, hypolimnetic anoxia duration, and anoxic volume percentage. In this study, these
parameters are again 25-yr averages obtained by model
simulations.
The minimum daily surface layer DO concentrations
are constant to within about +0.3 mg liter-l across a
wide range of lake morphometries and trophic states and
close to saturation (note that this is again a 25-yr average,
not an instantaneous daily observation). The difference
between north and south is primarily due to surface-water
temperature because lake elevations do not vary widely
in Minnesota. Northern lakes have surface-water temperatures lower than those of southern lakes; therefore
oxygen solubility is higher in the northern lakes. Minimum values of daily surface layer DO are 8.0 + 0.3 mg
liter- 1 in the south and 8.5 kO.3 in the north.
Bottom DO concentration is reported as the lowest simulated daily DO concentration above the lake sediments.
Values of this parameter given in Fig. 7 show the effect
1131
Long- term temperature and oxygen
north
01
0.6
0.8 1.0
6.0
4.0
2.0
8.010.0
-
20.0
0.6
5,
south
-11,
0
0.6
0.8 1.0
I
I
2.0
4.0
,@, 0.25 . H
s
-
max
’
8.010.0
1
1.0
,I,
I
I 11’1’1
2.0
4.0
6.0
I
I
’
I
2.0
I
8
4.0
1
8.010.0
20.0
8.010.0
20.0
1’1’1
-
III’1
6.0
0.8
20.0
( m-o.5)
ol
u ,I,
0.6 0.8 1.0
A 0.25. H
s
- ma x
1’1’1
6.0
I
(m-09
Fig. 8. Time (days) between first and last occurrence of hypolimnetic anoxia (simulated 25-yr averages).
Fig. 9. Maximum daily percentage of total lake volume with
anoxia (simulated 25-yr averages).
of lake stratification in the low value on the left side of
the graph. Oligotrophic lakes tend to have higher DO
concentrations in the water near the sediments than do
eutrophic lakes, primarily because of the lower SOD, and
higher photosynthetic rates, especially in shallow lakes.
Hypolimnetic anoxia is defined herein as the condition
when DO concentration at any depth in a lake is -CO.1
mg liter-l. Although 0.1 mg liter-l is an arbitrary criterion, it is useful to identify possible low DO concentrations in lakes with different geometries, trophic state,
and geographic location. For geometry ratios > 5, anoxia
never occurs, regardless of lake trophic state (Fig. 8). These
lakes experience sufficient vertical mixing so that oxygenrich water is frequently in contact with lake sediments,
thus avoiding complete anoxia. For a geometry ratio < 5,
trophic state of the lake affects duration of anoxia besides
the geometry ratio. The longest duration of anoxia is
estimated for eutrophic lakes, which typically have high
SOD and higher water-column stability than oligotrophic
lakes.
Anoxic volume percentage is defined herein as the maximum daily total volume of the lake where DO is ~0.1
mg liter- 1divided by the total lake volume and multiplied
by 100. This parameter gives an estimate of the percentage of the total lake volume with anoxia. Values of anoxic
volume percentage increase substantially as the lake geometry ratio decreases (Fig. 9). The rate of decrease is
faster in eutrophic lakes. The numbers in Fig. 9 indicate
that as much as 60% of a lake’s volume can be anoxic.
The lake volume fraction unsuitable for fish would be
even larger because the DO survival criterion is 2.5-3.0
mg liter- 1 instead of 0.1. Information on hypolimnetic
anoxia has, however, a higher degree of uncertainty because it is directly dependent on the SOD specified in the
model, and SOD is not a very precise value.
Fish habitat characteristics-Fish response to habitat
conditions is evaluated in terms of suitability for survival
(temperature and DO) or for good growth (temperature)
(Stefan et al. 1995). The good-growth season for fish begins when water temperatures exceed the minimum for
good growth and continues as long as it remains below
the upper threshold for good growth and DO remains
adequate for survival. These limits differ by species and
thus by thermal guild.
The length of the good-growth season is given in Fig.
1132
Stefan et al.
Northern
5
Minnesota
Lakes
Southern
Minnesota
Lakes
5
I,I,
I
I
.,.,
8
1’1’1
cold
04
0.6
south
, .(
0.6 1.0
2.0
4.0
6.0
6.010.0
5 1 cool
.(.,
I
20.0
0, . ,.I
0.6
5
I.1
0.6 1.0
2.0
4.0
0.0
I
6.010.0
20.0
.,.,
cool
4
0
111,
0.6
0:.
0.6
_
I.1
0.6 1.0
2.0
4.0
6.0
I
20.0
6.010.0
I
0.8 1 .O
I
’
2.0
A
0.25.
s
1’1’1
6.0
’
8.010.0
20.0
H maio(m-o.5)
Fig. 12. Length (days) of no-survival conditions for cold
water fish in the southern region (simulated 25-yr averages).
‘O,.O
Ap:
.
.
l-i,,,
.
.
“‘$6
‘0:6’1:0
2.0
4.0
Aso.25:
(ml-q
H,,,
6.0
I
6.010.0
20.0
(m-0.5)
Fig. 10. Length (days) of the good-growth season (simulated
25-yr averages).
Southern
5.0-
. I
1
. I
1
Minnesota
Lokes
cold
:
4.0-
so2.01.o0.01
0.6
0.6 1.0
2.0
4.0
6.0
6.0,O.O
20.0
cool
0.0 I
0.6
0.0-l
0.6
1. 1
t.0
0.6
I
,
0.6 I.0
4.0
2.0
2.0
~0.25:
4.0
H,,,
6.0
6.0
(m -0.5)
6.010.0
6.6,0.0
20.0
1
20.0
0.01 . I . ,
0.6 0.6 I.0
0.04
1I
0.6 0.6 1.0
2.0
4.0
2.0
A,0.25:
4.0
H,,,
6.0 6.010.0
6.0 6.010.0
:
1
20.0
1
20.0
(m-0.5)
Fig. 11. Fraction of lake volume available for good growth
(simulated 25-yr averages).
10. The lake geometry ratio, as well as lake trophic state,
have an influence on the cold water fish habitat. The goodgrowth season for cold water fish is given only for northern lakes because in almost all southern Minnesota lakes
cold water fish cannot sustain themselves beyond the
cooler water seasons. For the cold water guild, the goodgrowth season lengthens as the geometry ratio decreases
(i.e. as lakes are more likely to stratify). For cool water
and warm water fish this trend is not apparent. Instead,
contours indicate nearly constant lengths of the good
growth seasons regardless of lake geometry ratio and Secchi depth. In northern Minnesota, the length of the goodgrowth season for warm water fish is - 59d and - 134 d
for cool water fish. In contrast, it is only - 100 d for warm
water fish in southern Minnesota and - 106 d for cool
water species.
Good-growth average volumefraction indicates the fraction of the total lake volume available for good growth.
The highest volume fractions for good growth (Fig. 11)
seem to be available in polymictic lakes and in oligotrophic lakes for all fish guilds. In strongly stratified and
eutrophic lakes, the fraction can be 0.4 or even lower.
The no-survival conditions for cold water fish in the
southern region expressed as the number of days during
which a lake has no habitat for cold water fish are presented in Fig. 12. Because the values are 25-yr averages,
cold water fish may survive in some years in a few lakes,
especially those where the lake geometry ratio is near 2.
Indeed the most tolerant species of the cold water guild
(cisco or lake herring) have been observed in many of
those lakes with only occasional partial fish kills.
Eficts of climate change-Effects of climate change on
the daily water temperature and DO profiles that are the
basis for the foregoing graphical results have also been
investigated. The output from several global circulation
models (GCMs) for a doubling of atmospheric CO2 was
obtained and used to modify the weather database. Simulations of projected water temperature and DO profiles
Long-term temperature and oxygen
MAXIMUM HYPOLlMNETlC
TEMPERATURE
UAXIMUM
DIFFERENCE OF TEMPERATURE
(OC) BETWEEN SURFACE AND BOlTOh
5
-4
E
GISS
MODEL
-
25
Ii
-4
E
zi
3
ES
B
O2
P
2
I
8
WC
zi
El
0
0
GISS -
0.6
1.0
2.0
A&25:H,nox
LO
6.0
(m-0.5)
6.010.0
20.0
0.8 1.0
b&=:Hmox
(,n-0.5)
Fig, 13. Maximum daily hypolimnetic temperature (“C) isotherms and minimum hypolimnetic DO (mg liter-l) isopleths
(simulated 25yr averages) for two northern Minnesota lakes.
Past conditions (top), projected 2 x CO2 GISS climate scenario
(middle), and differences between future and past climate conditions (bottom).
were then made with this modified weather data as input
parameters. The results of these projections cannot be
presented here in their entirety but examples are given
in Figs. 13 and 14. More complete information has been
reported elsewhere (Hondzo and Stefan 199 3b; Stefan and
Fang 1993; Stefan et al. 1993). An example of the projected changes in two water-quality characteristics of
northern Minnesota lakes due to climate change is given
in Fig. 13. The climate parameter changes predicted for
Duluth by the GISS 2 x CO2 model (Table 3) were used
as input to the simulations. Maximum water temperatures and minimum DO concentrations in the hypolimnion of lakes before and after projected climate change
are shown in Fig. 13. Either parameter can become the
controlling factor for the survival of fish. Changes from
past to projected future conditions are plotted at the bottom of Fig. 13.
Two results stand out in Fig. 13: hypolimnetic water
temperatures change less (0-3°C) than air temperatures
(3.8”C average) and water temperature changes depend
on lake geometry (e.g. eutrophic lakes with a geometry
ratio between 2 and 4 and oligotrophic lakes with a geometry ratio between 1 and 2 are projected to have l0°C hypolimnetic temperature changes). Minimum hypolimnetic DO is not affected by climate change if lakes
already experience anoxia under past climate conditions.
Eutrophic and oligotrophic lakes with lake geometry ra-
2.0
hO.25:
4.0
t+mox
8.0
(m-0.5)
8.010.0
20.0
0.8
1.0
2.0
4.0
AsOs25 : Hmax
6.0
8.010.0
PAST.
20.0
(m-O.5)
Fig. 14. Maximum daily difference of temperature between
surface and bottom (simulated 25-yr averages) for southern and
northern Minnesota lakes. Past conditions (top), projected
2 x CO, GISS climate scenario (middle), and differences between
future and past climate conditions (bottom).
tios >4 and 2, respectively, are projected to experience
a drop in minimum hypolimnetic DO. The reduction will
be up to 3 mg liter-‘, resulting in anoxic conditions in
many eutrophic lakes with geometry ratios up to at least
20. This loss of DO, essential for fish survival and well
being, will also be accompanied by a lengthening of the
period of hypolimnetic anoxia, particularly in stratified
lakes. The lengthening of the anoxic period could be as
long as 60 d and is expected to be strongest in lakes with
geometry ratios < 5 for eutrophic lakes and <2 for oligotrophic lakes. The associated increase in lake volumes
affected by anoxia is projected to be as much as 14% of
total lake volume.
Other projected climate change effects on Minnesota
lake-water temperatures, DO and associated fish habitat
have been discussed elsewhere (Hondzo and Stefan 19933;
Stefan and Fang 1993; Stefan et al. 1995). Following are
some of our findings concerning the effects of climate
change on water temperatures, dissolved oxygen, and fish
habitat in Minnesota lakes.
The average (seasonal) epilimnetic water temperature
for the open-water season (not graphed in this paper) is
expected to rise -3OC due to doubling of atmospheric
COZ, regardless of lake morphometry. This value compares to a projected air temperature rise of -4OC. The
largest increases in epilimnetic water temperatures is projected to occur in April (- 7°C) and September (- 5°C).
The minimum is projected to occur in July and Novem-
1134
Stefan et al.
Table 3. GISS- 2 x COZclimate scenario output.
Air
Solar
Wind Rel. hutemp.
rad.
speed midity
(disk
Month
ratio
Precip.
“Cl
Minneapolis-St. Paul (southern Minnesota)
6.20
0.92
0.92
1.16
1.17
Jan
Feb
5.50
1.04
1.12
1.01
1.03
5.20
0.98
Mar
0.47
1.13
1.28
5.05
1.03
1.oo
1.03
0.69
Apr
2.63
1.oo
0.67
1.09
1.12
May
3.71
0.99
0.85
1.01
1.08
Jun
2.15
0.98
0.93
0.93
1.10
Jul
3.79
1.04
1.00
1.02
0.98
A%
7.02
1.04
1.07
1.90
0.70
Sep
Ott
3.73
1.12
2.23
0.95
0.88
Nov
6.14
1.03
5.00
1.oo
0.99
5.85
0.99
0.77
0.98
Dee
1.24
Duluth (northern Minnesota)
5.06
0.87
0.92
0.80
1.09
Jan
6.58
0.78
Feb
2.48
1.02
1.21
1.02
Mar
4.89
1.04
0.82
1.24
4.97
1.oo
1.17
0.85
1.oo
Apr
1.54
1.04
0.57
1.04
0.86
May
3.51
1.oo
0.74
1.15
1.33
Jun
0.97
2.59
0.97
0.75
0.99
Jul
2.80
0.98
0.88
1.04
1.35
Aug
3.96
1.01
0.81
0.94
1.98
Sep
3.89
0.97
Ott
0.73
1.02
1.20
5.93
0.95
Nov
1.06
1.oo
1.16
Dee
5.33
0.80
1.01
0.91
1.39
ber (- 0.5-2°C). Due to climate change, the daily maximum epilimnetic temperature (Fig. 4) is projected to increase over the values in the past by -2OC in the south
and by - 3-3.5”C in the north.
The highest hypolimnetic temperatures were calculated
for large, shallow lakes. Seasonally averaged hypolimnetic
water temperatures after climate change are projected as
follows: shallow lakes- warmer by an average of 3°C;
deep lakes-cooler by an average of 1°C. The cooler temperatures are caused by an earlier onset of seasonal stratification, occurring at lower well-mixed lake-water temperatures. Daily maximum hypolimnetic water temperatures plotted in Fig. 5 are projected to increase by up to
3°C in the southern lakes and < 1°C in the northern lakes.
The strength of vertical stratification of lakes as measured by the maximum difference of temperature between
surface and bottom is projected to increase as much as
4°C in already stratified lakes with geometry ratios <4
(Fig. 14). The increase will be stronger in eutrophic lakes
than in oligotrophic lakes. This increase will be about the
same in the northern and southern lakes. Simulated annual evaporative heat and water losses (not shown) are
projected to increase by - 30% for the 2 x CO2 GISS climate scenario. The annual evaporative water losses may
as a consequence increase by - 300 mm. The total annual
water loss may therefore reach 1,200 mm. Simulated
mixed layer depths are projected to decrease - 1 m in
spring and summer and to increase in fall with the projected climate change. In a warmer climate, the lakes will
stratify earlier and overturn later in the season. The stratification period is projected to increase by 40-60 d.
Epilimnetic DO concentrations are expected to decrease as the climate becomes warmer. The maximum
epilimnetic DO decrease is, however, expected to be <2
mg liter - l, in all types of lakes. The lowest simulated
mean daily DO concentration in the epilimnion is projected to remain > 7 mg liter- I. Therefore the epilimnetic
DO concentrations will only be slightly reduced.
The hypolimnetic DO responsesto climate change show
significant variability. The largest projected hypolimnetic
DO change is on the order of 8 mg liter-l and occurs in
May or October in deep (~20 m) lakes. In shallow (polymictic) lakes, the simulated minimum daily hypolimnetic DO values are from 1 to 7 mg liter-l under past
climate conditions and from 0 to 5 mg liter-l for the
2 x CO2 GISS climate scenario. In deeper lakes with seasonal stratification, the hypolimnetic DO is depleted over
substantial portions of summer. The increase in oxygen
depletion rate of the lake hypolimnia due to climate change
is manifested in lower minimum daily hypolimnetic DO
concentrations (Fig. 13), longer periods of anoxia, and
larger fractions of lake volumes depleted of oxygen. The
dependence of these parameters on lake geometry ratio
was explained earlier.
The losses in cold water fish good-growth potential and
the gains in the cool water fish good-growth potential will
be larger in well-mixed lakes. The gains in warm water
fish good-growth potential will be similar for all lakes.
Good-growth potential is nearly the same in oligotrophic
and eutrophic shallow lakes, both of which tend to be
well mixed. In deep lakes, which have a seasonal stratification and are dimictic, oligotrophy is usually associated
with higher growth potential. This trend will continue
after climate change.
The largest losses in good-growth volume are expected
for cold water fish in eutrophic lakes; the largest gains
(for cool and warm water species) are projected to occur
in oligotrophic lakes. Cold water fish are projected to lose
good-growth habitat, in both area and volume, by the
same percentage. Cold water fish, now rare in the southern
lakes, will virtually disappear. In the north they will experience a habitat reduction of 4 1%. Cool and warm water
species will, however, gain good-growth habitat, in both
area and volume, throughout the state. The increase will
be two-three times higher for the northern lakes than for
the southern lakes.
Conclusions
We have related water-quality characteristics to habitat
requirements for a variety of fish, grouped as guilds, with
similar thermal and DO survival and growth limitations.
The format of the graphical presentation is new and lends
itself well to summarize water-quality characteristics of
a diverse and large set of lakes (e.g. in the north-central
U.S.). Such regional summaries are often sought, but difficult to achieve. We believe that our successful attempt
Long- term temperature and oxygen
to integrate an overwhelming amount of regional information at an appropriate level of scientific sophistication
will be useful. The graphical presentation of the results
allows interpolation and quantitative comparison among
lakes of different morphometries and trophic levels. The
results give an overview of average lake conditions in an
entire region.
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