pH of Water Samples Obtained from the
Milwaukee River Demonstrate Weak Inverse Correlation with Distance Upstream
from Lake Michigan
Tina
Jeselun and Henan Zaal
Abstract
In
this experiment, we hypothesized that water samples obtained from the river at
greater distances upstream from the lake would have an increase in pH. Our hypothesis was based on our understanding
of how photosynthesis affects pH. We
believed that an increase in plant growth would result in a higher reading of
pH. There was not a correlation between
pH of the river and distance upstream from the lake (R2 = 0.1628).
Key words: Milwaukee River, Lake Michigan, pH,
photosynthesis
Introduction
From
previous observations and understanding of lake and river ecosystem’s we
believed that river water samples obtained from further upstream from the lake
would be exposed to more plant life and this would result in a higher pH. We predicted that an increase in plant life,
including algae and phytoplankton, would cause an increase in pH. Upstream, the water is shallower and more
optimal for algae and plant growth. Photosynthesis
increases pH (Carru et al., 1999). This
is because plant life takes up nutrients from the water including carbon and
releases oxygen into the water. Carbon
dioxide content lowers pH and the resulting increase in oxygen in a ratio with
carbon dioxide increases pH. The effects
of the growth on the bottom of the river become more concentrated as the body
of water becomes increasingly shallow.
Upstream from the lake we expected the resulting shallow rivers would produce
an ecosystem with a higher pH. When the
water is shallower the growth on the bottom of the river obtains more sunlight
allowing for the increase in photosynthesis (Anten and Hirose, 2001). We also expect
that the shallow waters at the edge of the river from which we obtained our
samples would be less turbulent, allowing for more plant life to thrive.
Methods
On
October 8, 2011 from 1100 to 2000 and on October 9, 2011 from 1200 to 1500 we
collected 25 different samples of river water from the Milwaukee. To decide where each of the samples would be
taken a map that showed 25 kilometers of the river and its surrounding land was
produced. First the photo of the land
along with street names was obtained from Map
Quest, an online mapping site. The
scale provided by Map Quest allowed
for each kilometer to be marked with the use of Photoshop.
In
Photoshop, the starting point was chosen,
because it was where Lake Michigan becomes the Milwaukee River. On the enlarged photo of this map represented
in figure 1, we marked the starting point with a large red dot. The green letter A represents the first spot
that we would be driving to in order to reach our first sampling area. As seen on our map, this is located near
the Summerfest festival grounds in the city of Milwaukee. At this point, there was a large drop off from
the land to the river and to obtain water sample, one of us had to climb down a
ladder and reach the measurement dropper into the water to obtain 2 mL of
water. We did not test the pH
immediately, because of the difficulty of dipping the pH paper into areas of
waters such as this and reading it correctly in a consistent amount of
time. We believed that collecting all
the samples and then reading them in one place where variables such as light
did not affect our judgment of the color that would determine the reading of
pH. We did not realize that obtaining
the water samples and then testing them later would produce more variables that
we did not consider. This is considered
in the discussion of this paper.
Using
Photoshop, the rest of the river was indicated with a white line and at 1
kilometer intervals each sample area was marked by a smaller red mark. Using the streets provided on the map, we
were able to find each sample site. Due
to the river sometimes being restricted by personal properties and fences, we
were not always able to reach the exact spots indicated by the map. Also, some points marked for obtaining
readings on the map were not very close to roads. They required that we park and hike down to
the river, possible skewing our understanding of where we were located exactly on
our map.
We
continued this process for 25 kilometers, obtaining a two mL sample every
kilometer. Our final sample was obtained
near River Road in the city of Mequon and is indicated as a second large red
dot. An enlarged photo of this area is
provided in figure 2.
After
collecting all of the samples the pH of each was measured with the use of pH
paper. We graphed the data in a scatter
plot with the use of excel. As a
statistical test, we plotted a linear trend line and obtained an R-squared
value.
Fig. 1 (above) the starting point at which the first water
sample was obtained indicated by the large red dot.
Fig. 2 (above) the point of the river at which the last sample was obtained indicated by a large red dot
Results
Fig. 1 pH of water samples shows
very weak inverse correlation with distance obtained upstream from Lake
The
data obtained, as shown in figure 3, shows a very weak inverse correlation between
water sample pH and the distance at which the sample was obtained upstream from
Lake Michigan. The pH of the river,
according to our readings, ranged from 5 to 7 over the 24 kilometer region.
Discussion
The
results do not support our hypothesis.
We believe that this was due to mistakes made in our methods and
multiple outside factors that could have affected the results. First, the pH of each water sample obtained
should have been read immediately. pH
can change over time once removed from its source. One of the reasons for this is that unseen
organisms in the water can continue to grow, expelling oxygen or die and
dissolve into the water, increasing carbon dioxide content. Because some of the samples actually showed a
lower pH, it is possible that dead organisms in the water altered our
measurements.
A
point that was not considered when producing our hypothesis was that
seasonality greatly effects plant growth in water systems. During algae blooms pH rises, because the
algae is removing carbon dioxide from the water, but during seasons of plant
death the dead algae returns to the water along with its nutrients increase the
river’s carbon content and therefore lowering the pH (Carru et al., 1999). Beier et al. (2006) demonstrated in one
ecosystem that there was a change of 22 to 33 percent in ecosystem
respiration. In 0 degree Celsius water,
photosynthesis produced around 5 percent of the respiration while in 20 degree Celsius
up to 35 percent of respiration. They
concluded that season was important to the carbon cycle of an ecosystem. We would expect larger algae blooms in the
spring and more algae death in the fall when the samples were taken.
Also,
we observed that during the time that these samples were obtained, many of the
surrounding trees were losing their leaves.
Often leaves fell directly into the river to die, likely resulting in
their decomposition and an increase in the water’s pH (Abelho et al., 2005).
While lake ecosystems are generally conducted
by biotic factors, rivers are exposed to many more outside factors, such as
land runoff, because there is much less water per land area (Carpenter et al.,
2002). Toxic run off from the land
surrounding the rivers can greatly affect the river ecosystem and cause a
change in pH (Nekola et al., 1999). As
shown in figure 5 some of the river that we measured went through the city,
exposing it to factors not considered.
Because
of the additional information that we have learned related to season and
cellular respiration in ecosystems, we would be interested in performing the
same test again, but at different times of the year. It would also be important that we recorded
the temperature of the water. We would
expect to then be able to see the predicted correlation between distance
upstream from the lake and pH as a result of increased photosynthesis during
the spring and summer months and much less of a correlation during other parts
of the year. We would test the pH of
each sample at the site that it was obtained, to avoid the possible changes in
pH over time once the sample is removed.
When repeating the test we would also record other variables in the
surrounding environment that could affect our results.
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