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A WATER QUALITY STUDY OF
MIDDLE SPRING CREEK AND
BURD RUN, SHIPPENSBURG,
PA An Assessment of In-situ Water Quality-indicator
Parameters
Kelsey Kilhoffer Practical Exam Revision December 12, 2015 Dr. Joseph Zume – Advisor Dr. S.R. Cornell - Reader
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Table of Contents
Abstract………………………………………………………………………………………………………………………..…………………………………………3
Introduction…………………………………………………………………..………………………………………………………………….…………………….3
Literature Review………………………..……………………………………………………………………………………….………..……………………….5
Temperature and Dissolved Oxygen……………………….………………………………………………….………..…………………….7
PH and Oxidation Reduction Potential……..……..………….……………………………………………….…………………………….8
Total Dissolved Solids and Conductivity……………………………………..……..……………………..………..…………………….10
Purpose………………...……………………..……………….……………………………………………………………………….……………………….…….11
Study Area…………………………………..…………………………………………………………………………………………….………….………………11
Methods……………….……………………..…………………………………………………………………………………………………………..…….…….16
Survey Design………………………….…..………..………………………………………………………………………………….…….………16
Data Collection………………………..…..…………..…………………………………………………………………………….…….…………18
Data Analysis………………………….……………………………………………………………………………………………….…….…………19
Results……………………….……………….…………………………….………………………………………………………………………….…….…………20
The Burd Run………………………………………………………..…………………….…………………………………….…….…….………..20
The Upper Middle Spring Creek (upward from confluence with Burd Run)….….……………………….…….………...24
The Entire Middle Spring Creek (down to its mouth at the Conodoguinet)……………………………….…….………..27
Discussion of Results……………………….……………………….………………………………………………………………………….…….…………30
The Burd Run………………………………………………………..………………………………………………………………….…….………..30
The Upper Middle Spring Creek (upward from confluence with Burd Run)….….……………………….…….………...32
The Entire Middle Spring Creek (down to its mouth at the Conodoguinet)……………………………….…….………..33
Summary Water Quality Comparison……………….………………..…………………..……………………………….…….………..34
Conclusion…………………….…………….…………………………….………………………………………………………………………….…….………..35
References…………………….…………….…………………………….………………………………………………………………………….…….………..37
Figures
Figure 1…………………….…………….…………………………….……………………………………..……………………………………………………....10
Figure 2…………………….…………….…………………………….……………………………………..……………………………………………………....13
Figure 3…………………….…………….…………………………….……………………………………..……………………………………………………....15
Figure 4…………………….…………….…………………………….……………………………………..……………………………………………………....17
Figure 5…………………….…………….…………………………….……………………………………..……………………………………………………....18
Figure 6…………………….…………….…………………………….……………………………………..……………………………………………………....21
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Figure 7…………………….…………….…………………………….……………………………………..……………………………………………….……...21
Figure 8…………………….…………….…………………………….……………………………………..………………………………………….…………...22
Figure 9…………………….…………….…………………………….……………………………………..………………………………………….…………...22
Figure 10…………………….…………….………………………….……………………………………..…………………………………………..…………...23
Figure 11…………………….………….…………………………….……………………………………..………………………………………………..……...23
Figure 12…………………….………….…………………………….……………………………………..………………………………………………..……...24
Figure 13…………………….…………….………………………….……………………………………..………………………………………………..……...25
Figure 14…………………….…………….………………………….……………………………………..………………………………………….….………...25
Figure 15…………………….………….…………………………….……………………………………..………………………………………….….………...26
Figure 16…………………….………….…………………………….……………………………………..…………………………………………..…………...26
Figure 17…………………….………….…………………………….……………………………………..…………………………………………….…….…...27
Figure 18…………………….………….…………………………….……………………………………..…………………………………………….…….…...28
Figure 19…………………….………….…………………………….……………………………………..…………………………………………….…….…...29
Figure 20…………………….………….…………………………….……………………………………..…………………………………………….…….…...30
Appendix A: Tables…………..……………...……………………….………………………………………………………………………………………….40
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Abstract
The purpose of this study is to test the following hypotheses: (1) It is possible to detect zones of spring water discharge into the Burd Run channel using variations in specific water quality-indicator parameters. (2) There are noticeable changes in water quality-indicator parameters upstream and downstream from the Shippensburg Wastewater Treatment Plant. Water quality parameters between Middle Spring Creek and Burd Run were also summarized and compared. The methodology consisted of collecting in-situ water quality-indicator parameters including temperature, pH, ORP, DO, conductivity, resistivity, and TDS along the Burd Run and Middle Spring Creeks. Data were analyzed using geospatial techniques and descriptive statistics. The results suggest that the resolution between sample sites along Burd Run is not close enough to accept the first hypothesis. The results also suggest that there is a clear difference in temperature, DO, and TDS between the segments of Middle Spring Creek that are upstream and downstream from the wastewater plant. Overall, Burd Run has better water quality than Middle Spring Creek, however, both streams are considered to be aquatically healthy.
Introduction
The quality of freshwater resources has become a global concern as human population
continues to grow (United Nations, 2014). Polluted water is the biggest health risk that continuously
threatens the condition of human life and aquatic ecosystems. Many surface and groundwater
resources remain vulnerable to pollution regardless of regulations such as the Clean Water Act (National
Resources Defense Council, 2015). Our freshwater systems consist of a complex interconnectedness
between ground and surface water, meaning the potential for contamination rises as complexity
increases. This can present many changing and unpredictable situations for possible contaminants to
enter our water ways. The World Health Organization states that water quality monitoring is essential
for the management of these resources (Bartram and Ballance, 1996). Recent studies such as
Mulamattathil and others, (2015) and Wang and others, (2015) analyze the quality of surface and
ground water and bring to light the importance of regular water quality monitoring in order to assess
the growing concerns over pollution impacts on water resources, as well as treatment and prevention
strategies.
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There are numerous threats to both ground and surface water, but the main concerns center
around urban development and agricultural activities (PASDA, 2013). The increased urbanization of
communities leads to larger areas of impervious surfaces. Runoff from roads and parking lots pose a
threat to receiving streams because they may contain a high concentration of salts, heavy metals, and
other toxic materials (Ellis, 1986). Agricultural runoff is also a concern due to the likelihood of nutrients
such as phosphorous and nitrogen entering waterways. These issues necessitate the periodic collection
of water quality data in areas with potential for water contamination. However, analyzing multiple
samples for water chemistry can be tedious and very expensive. Stone and Clarke (1996) state that in-
situ water quality indicator parameters yield information about the characteristics of water systems. It is
therefore a common practice to collect in-situ data in order to gain preliminary knowledge of stream
conditions.
The negative impacts that pollutants in the form of chemical compounds and suspended
sediments have on humans and aquatic organisms have long been a concern for scientists and
environmentalists (Trombulak and Frissell, 1999). Determining the state of water bodies can be
accomplished through the collection of water quality data. Measuring water quality-indicator
parameters is a technique that has been used to ask and answer many questions about the quality of
streams and rivers (Kose, et al, 2014). The borough of Shippensburg and surrounding areas in the
Cumberland Valley are known for characteristic limestone spring-fed creeks, specifically Middle Spring
Creek and Burd Run. Streams located in areas with limestone bedrock often contain springs that
discharge into the channels along different reaches, contributing to baseflow (Harvey and Skelton,
1968). Discharge points for these springs are generally impossible to determine upon visual inspection,
and often require the measurement of water quality-indicator parameters such as temperature and
conductivity (USGS, 1995). Determining the zones of discharge from these springs could help attribute
sources of stream water quality impairment to factors such as urban and agricultural land uses.
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Point sources, such as industrial and wastewater effluents, also have potential to disrupt the
quality of aquatic environments and ecosystems through the discharge of toxic pollutants into streams.
Monitoring water quality indicator parameters such as temperature, pH, conductivity, etc. can
determine if certain segments of a stream are undergoing a change in water quality. Gathering regular
data, both upstream and downstream from discharge points, is important for the detection of pollution
sources. Understanding these impacts through the collection and analysis of water quality data can help
to implement proper management practices that ensure the well-being of these ecosystems. Examples
of this are the studies on nutrients and sediment conducted by the United States Geological Survey.
These analyses provide implications about the effectiveness of regulations and practices currently in
place (USGS, 2015).
This study focuses on examining two hypotheses. First, whether it is possible to detect zones of
spring water discharge into the Burd Run channel using in-situ measurements of water quality-indicator
parameters. Second whether there is a noticeable change in water quality downstream from the point
where the Shippensburg Wastewater Treatment Plant discharges treated wastewater into Middle Spring
Creek. These hypotheses were tested by analyzing in-situ water quality-indicator parameters along the
two Creeks.
Literature Review
Analyzing water chemistry can be costly and time consuming. Therefore, it is common practice
to conduct in-situ data on streams using water quality-indicator parameters such as temperature, pH,
dissolved oxygen, etc. This allows for a preliminary detection of changes in water quality which can then
determine if a more thorough laboratory analysis is needed. There are many scientific studies that asses
water quality indicator parameters by gathering in-situ data. For example, Topi et al., (2013) used a
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multiparameter portable instrument to analyze parameters including temperature, pH, and dissolved
oxygen of Butrinti lagoon in Albania. Their goal was to determine the overall quality of the lagoon and to
examine its ability to support aquatic life. The results showed that high temperatures and reduced levels
of dissolved oxygen are damaging the rate of growth of mussels in the lagoon. This study resolved that
these parameters should be monitored more closely to protect these aquatic organisms. Other similar
studies include an analysis of dissolved oxygen in Lake Erie by Conroy (2008) and an assessment of
introducing wireless sensors for environmental monitoring in urban areas by Postolache and others
(2014). All of these studies implement the use of a multiparameter probe for monitoring water quality
and validate the use of this instrument for in-situ water quality analysis.
Examining water quality-indicator parameters is an important way to assess the overall health of
a body of water (Muth et al., 1999). There are many different methods that can be used in water quality
analysis including collecting as-needed data to answer a variety of specific questions about water quality
concerns. Some issues may be elevated levels of dissolved solids or depleted concentrations of dissolved
oxygen. Gathering in-situ data allows for the assessment of temperature-dependent parameters.
Measurements that could be taken on site include temperature, dissolved oxygen, pH, oxidation-
reduction potential (ORP), conductivity, resistivity, and total dissolved solids (TDS) (USGS, 2013).
Hatt and colleagues (2004) expresses the importance of using water quality data to assess point
sources of pollution. Their study monitors indicator-parameters such as TDS and DO in order to assess
point source discharge from storm water runoff in fifteen small streams east of Melbourne, Australia.
The analysis determined that the increase in impervious surfaces was responsible for rising stream
temperatures and conductivity. By monitoring water quality-indicator parameters at selected locations
it becomes possible to determine what is causing elevated levels of particular pollutants. Knowing the
cause of these pollutants then allows for proper action to be taken in order to manage them.
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In karst regions such as the Cumberland Valley it is not uncommon for pollutants to enter and
contaminate underground aquifers. The two most common toxins include: (1) fecal matter, which may
enter karst aquifers through leaking septic systems and grazing livestock, and (2) salts, specifically
chloride (Na+), that infiltrate aquifers during snow melt periods (Reischer et al., 2006). A study by Reisch
and Toran (2014) monitored the conductivity of a snowpack that infiltrated into a karst spring in the
Cumberland Valley. They measured this conductivity at the spring’s discharge point to determine the
characteristic transient patterns of the aquifer. Studies such as these highlight the value of determining
zones of spring discharge.
It is important for defining stream sources during periods of drought as well as monitoring water quality
characteristics of the aquifer. Any impairment can then be traced to sources on the surface. The
following are water quality-indicator parameters commonly used in water quality studies.
Temperature and Dissolved Oxygen
One of the most important characteristics of an aquatic system is temperature because it
controls the amount of dissolved oxygen that is present in water and many other chemical reactions.
Increasing water temperature is considered thermal pollution because it decreases the concentration of
dissolved oxygen, therefore, negatively impacting aquatic ecosystems. Often times, anthropogenic
activities are the reason for increases in water temperature. These include, but are not limited to: the
discharge of industrial or wastewater effluents, agricultural practices, and urban development.
Industries that use river water in their processes treat water before it is returned to streams; however, it
is much warmer than it was when extracted. Urban runoff from impervious surfaces such as parking lots
and rooftops may also be significantly warmer than receiving streams. Few factors cause water to be
cooled. A naturally occurring example is the introduction of colder water from springs, although this
decrease in temperature is usually not a concern (Vernier, 2015). Normal temperature range for surface
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water is between 32°F and 86°F (0°C and 30°C) (RAMP, 2015). Temperature above this range can cause
an increase in chemical reaction rates as well as a changes in metabolism, growth, and reproduction in
various aquatic species. This in turn can affect the species composition of an aquatic ecosystem
(Kemker, 2014).
Another important water quality parameter that is affected by temperature is Dissolved Oxygen
(DO). This oxygen comes from the atmosphere via photosynthetic processes performed by aquatic
plants. It is essential for fish and other organisms in order to maintain respiration and metabolic rates.
Temperature and dissolved oxygen have an inverse relationship, meaning as temperatures increase the
solubility of oxygen decreases (Kemker, 2014). Biochemical Oxygen Demand, or BOD, also dictates the
amount of oxygen present in water bodies. BOD is the amount of dissolved oxygen needed by all
organisms in an ecosystem to break down organic matter. Organic wastes from sewage plants, industrial
facilities, and fertilizer runoff can increase the biochemical oxygen demand by introducing organic
material into water systems. This in turn causes the depletion of dissolved oxygen (Qualls et al, 2013).
Eutrophication is a phenomenon that can also be caused by sewage effluent or agricultural runoff.
Increased chemical nutrients promote excessive plant growth and decay. Oxygen is consumed as this
organic matter decomposes, sometimes causing a state of hypoxia or even anoxia. Hypoxia occurs when
the saturation of dissolved oxygen is between 1-30 percent. Anoxia occurs when there is 0% saturation
(Lentz, 2010). The Environmental Protection Agency states a standard minimum amount of DO needed
to support aquatic life is 5ppm, however, a healthy water body should have DO in the range of 10 to 12
ppm (around 80% saturation) (EPA, 2012).
PH and Oxidation-Reduction Potential
Two additional but important parameters to collect on site are pH and oxidation-reduction
potential. pH is a measure of the concentration of hydrogen ions and describes the acid-base (H+ - OH-)
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balance of water. A pH value of 7 represent neutral conditions ([H+] = [OH-]) while pH values less than 7
indicate acidic conditions ([H+] > [OH-]) and pH values above 7 indicate alkaline conditions ([H+] < [OH-]).
The solubility of chemical compounds as well as the form of these compounds are determined by pH.
This in turn can affect reactivity of chemical components, bioavailability of nutrients, and toxicity of a
water body (Kemker, 2014). The acidity or alkalinity of a stream could reflect the characteristics of the
surrounding land and the types of soils drained by surface runoff or via groundwater inputs. Forested
and swampy ecosystems tend to be acidic due to the decay of organic matter, while carbonate and
bicarbonate-rich soils contribute to alkaline aquatic conditions. Bedrock composition also plays an
important role in determining pH. Shale and sandstone bedrocks are associated with low pH values due
to the leaching of calcium (Ca2+) and Magnesium (Mg2+) during precipitation events (USDA, 2003).
Limestone bedrock is associated with high pH values due to the chemical dissolution of carbonate
material (Tutkimuskeskus, 2015). Most healthy neutral waters have a pH ranging from 6.0 to 8.5 (James
et al., 2004).
Oxidation-reduction potential, or ORP, is the degree to which a substance is capable of oxidizing
or reducing another substance. Positive ORP values indicate that a fluid is an oxidizing agent, meaning it
is seeking to gain electrons and in the process can cause oxidation to occur. Negative ORP values are
indicative of reducing agents. These substances have a surplus of electrons that bring about reduction
when those electrons are lost. ORP tends to increase as pH decreases meaning acidic water has a higher
ORP than alkaline water. This is proven by Myron L Company (2012) in a study examining the pH and
ORP of various concentrations of free available chlorine (FAC) (Figure 1). Oxidation-Reduction potential
typically remains positive in most types of fresh water (James et al, 2004). According to Tokatli and
others (2014), high oxygen content with low ORP is an expected situation in alkaline environments.
10
Figure 1: ORP vs pH of various concentrations of Free Available Chlorine
Total Dissolved Solids and Conductivity
The final parameters that are typically collected during in-situ measurements are total dissolved
solids (TDS), conductance/conductivity, and resistance. Total dissolved solids, or TDS, is the
concentration of the amount of dissolved material in water. This can include sodium (Na+), calcium
(Ca2+), magnesium (Mg2+), bicarbonate (HCO3-), chloride (Cl-), and many other substances including
industrial organic acids. Elevated levels of TDS may be caused by minerals in springs and carbonate
deposits which are not a worrisome hazard for aquatic ecosystems. However, high TDS concentrations
may also be caused by urban runoff, agricultural runoff, and wastewater discharges (Webber-Scannell
and Duffy, 2007). This has potential to cause increased salinity in freshwater, causing it to become toxic
for aquatic species. Freshwater has a large range of TDS levels between 0 and 1,000 ppm. Groundwater
TDS levels can range from 100 to over 50,000 ppm. Pristine conditions are TDS concentrations between
10 and 200 ppm while good to fair water quality falls below 500 ppm (CalEPA, 2010).
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Conductivity, is the measure of water’s ability to conduct electrical current. It is sensitive to the
concentration of total dissolved solids and is the reciprocal of resistance. Conductive ions, or
electrolytes, tend to come from dissolved salts, but may also be derived from alkalis (OH-), chlorides (Cl-
), sulfides (S2-), and carbonate (CO32-) compounds. Due to the fact that conductivity is easy to measure, it
is usually used in algorithms to estimate salinity and TDS. This parameter is an important indicator of the
health of freshwater ecosystems because when salinity levels increase, dissolved oxygen concentrations
decrease causing potentially toxic conditions. Healthy freshwater tends to have conductivities ranging
from 10 to 600 µS/cm (RAMP, 2015).
The collection of these water quality-indicator parameters can be used to assess the overall
quality of a stream. They can be used to analyze a change in water quality when comparing different
segments of the same stream along with determining how non-point or point sources are affecting the
aquatic ecosystem.
Purpose
This study focuses on two tributaries of the Conodoguinet Creek; the Middle Spring Creek and
the Burd Run. Wastewater effluent from the Shippensburg Wastewater Treatment Plant (SWTP) enters
Middle Spring Creek approximately 0.8 miles upstream from its confluence with Burd Run. One purpose
of this study is to determine if there is a noticeable change in water quality before and after the point of
treated wastewater discharge. The second focus is on the Burd Run Creek, which consists of an upper
segment that is intermittent and a lower segment that is perennial. The water source for the lower
segment is believed to be groundwater discharge from karst springs that enter the stream channel (Hurd
et al., 2010) although specific points of discharge are not obvious by visual inspection. This study
specifically tests the following hypotheses:
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1. It is possible to detect zones of spring water discharge into the Burd Run channel using
variations in specific water quality-indicator parameters.
2. There are noticeable changes in specific water quality-indicator parameters between the Upper
Middle Spring Creek and its lower segment into which treated wastewater from the
Shippensburg Wastewater Treatment plant is discharged.
Study Area
More broadly, the study area lies within the Cumberland Valley in south-central Pennsylvania.
The study creeks, Middle Spring Creek and Burd Run, depicted in Figure 2, together encapsulate
Shippensburg University Campus and other surrounding areas within Shippensburg Township. This area
has a climate that is humid-continental that is characterized by warm humid summers, cool dry
autumns, cold harsh winters, and warm wet springs. In November, the month the data were collected,
the average daily high for the month is around 53°F, while the average daily low is 35°F, and the overall
average daily temperature is 44°F. Average precipitation for the month of November is about 3.18
inches of rainfall and 2.1 inches of snowfall. The November of 2015 has been warm compared to the
daily averages (Hawkins, 2015).
The study area is primarily underlain by limestone bedrock and contains characteristic karst
features. White (1988) states that karst landforms consist of closed depressions, caves and underground
drainage systems, and areas with disrupted surface drainages. Due to the chemical dissolution of
carbonate rock, much of the water entering the valley is lost to subsurface pathways, eventually leading
to carbonate aquifers. This causes an abundance of groundwater but a significant lack of surface
streams. According to Chichester (1996), the Conodoguinet Creek drains most of the Cumberland Valley
13
(506 mi2) and flows northeastward along the base of Blue Mountain before entering the Susquehanna
River.
Figure 2: Shippensburg University Campus and surrounding areas including Middle Spring Creek and Burd Run.
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Middle Spring Creek is a tributary of the Conodoguinet Creek with headwaters located on South
Mountain. It flows over beds of Cambrian Quartzite that are approximately 75 feet thick. The stream
courses over a thick colluvium wedge at the base of South Mountain eventually flowing over Cambrian
calcareous shale of the Elbrook Formation which consists of 3,000 foot thick layers of siliceous limestone
(PAGEODE, 2015). As distance from South Mountain increases, the colluvium layer thins and limestone
bedrock containing characteristic karst features are exposed (Woltemade, 2015). Middle Spring Creek
continues to flow through the Borough of Shippensburg over Ordovician limestone of the Rockdale Run
Formation. Refer to Figure 3: Underlying bedrock geology of the study area.
Middle Spring Creek meets Burd Run at their confluence which is characterized by a change in
bedrock geology. Ordovician Limestone changes to the St. Paul Group which consists of micro-crystalline
“birdseye” limestone with interbedded dolomite. Finally the Creek flows over Ordovician Shale of the
Martinsburg Formation and into the Conodoguinet Creek (PAGEODE, 2015). The SWTP discharges its
treated wastewater effluent into Middle Spring Creek approximately 0.8 miles upstream from the Burd
Run confluence.
Burd Run is a tributary of the Middle Spring Creek which also has its headwaters located on the
South Mountain. It drains an approximate area of 20.0 square miles (Woltemade, 2015). In general, this
stream flows over nearly the same bedrock formations as the Middle Spring Creek. Burd Run flows over
beds of Cambrian Quartzite, courses over a colluvium wedge at the base of South Mountain, and
continues to flow over Cambrian shale of the Elbrook Formation. It then courses over a layer of
Cambrian Limestone of the Zullinger Formation as it enters the Borough of Shippensburg. This formation
consists of well-bedded limestone and dolomite. The confluence of Burd Run and Middle Spring Creek is
characterized by Ordovician Limestone bedrock of the St. Paul group (PAGEODE, 2015). Karst features in
the limestone bedrock cause Burd Run to contain segments that are influent (losing) and effluent
15
(gaining). When the water table is low, this may cause some sections of the streambed to be dry, while
other sections maintain a baseflow year round as a result of underground springs (Woltemade, 2015).
Figure 3: Underlying bedrock geology of the study area.
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Methods
Survey Design
I selected multiple points of measurement along Middle Spring Creek and Burd Run for this
study (Figure 4). Site selection was based upon the individual characteristics of each body of water along
with the consideration of study objectives. Sample points were also selected based on the in-situ data
type being collected and accessibility to the streams. Six sites, labeled along Middle Spring Creek were
chosen to capture any change in water quality that might occur between the upstream and downstream
segments, where treated waste water from the Shippensburg Wastewater Treatment Plant is
discharged.
Burd Run contains segments that are both influent and effluent. Influent sections occur mainly
just upstream from King Street (Route 11). Therefore, data collection began at the point where there
was adequate flow (near King Street) and continued downstream. Six points of data collection were
selected along Burd Run. An average distance of 1,000 feet separated samples points. These points were
chosen in an attempt to capture any changes in water quality-indicator parameters that may occur along
the stream channel. Sample points were based primarily on access to the stream due to obstacles such
as thick brush, steep slopes, and restricting features such as fences. Sites 2 and 3 are located along the
Burd Run Nature Trail, which contains an 8.5 hectare riparian zone. A known spring (Hawbaker Spring)
discharges into Burd Run between sites 2 and 3 (Woltemade, 2002).
A sample point was also chosen at the confluence of these two streams as well as two points
downstream from this confluence to provide an overall view of the water quality of the Middle Spring
Creek and its tributary Burd Run. In-situ measurements were made in areas that met the criteria set by
the USGS (2006), which includes reaches having uniform flow and a stable bottom contour, in
17
unidirectional flow, upstream from any bridges or structures (unless otherwise unavoidable), and far
enough above and below confluences and point sources to avoid poorly mixed flow.
Figure 4: Site selection for points of measurement along Middle Spring Creek and Burd Run.
18
Data Collection
Data were collected on Tuesday November 17, 2015. The high for this date was 58°F, the low
was 41°F, and the weather was sunny with no precipitation. A Hanna HI9829 multiparameter probe
(Figure 5) was used to gather data. Prior to data collection the probe was calibrated as described in the
instruction manual. The calibration beaker was filled 2/3 of the way full with the provided calibration
solution. The sensors were placed in the beaker, any bubbles that had formed were dislodged, and the
cap was screwed on tight. The “Quick Calibration” setting was selected. Conductivity and pH were
calibrated. The beaker was emptied and any remaining liquid was shaken off of the probe and beaker.
The empty calibration beaker was replaced on the probe body and dissolved oxygen was calibrated.
Figure 5: Hanna HI9829 multiparameter probe used to measure in-situ water quality-indicator parameters.
19
Sites along Burd Run were measured first, starting from the farthest point upstream and ending
at the farthest point downstream. Sites along the Middle Spring Creek were measured next, starting
with the farthest point upstream, continuing downstream to the confluence, and finally gathering
measurements downstream from the confluence of the streams. At each site parameters were
measured according to the guidelines set by the United States Geological Survey (Wilde, 2008). The
probe was placed at mid-depth of each sample site and allowed to equilibrate for 60 seconds.
Temperature, dissolved oxygen, pH, ORP, conductivity, resistivity, and TDS along with the latitude and
longitude of each location (obtained with the in-built GPS unit within the multiparameter probe). The
coordinates of the Shippensburg Wastewater Treatment Plant were also recorded. The data were
logged in a field book and used for analysis.
Data Analysis
An Excel spreadsheet was populated with the data that had been collected in the field including
the parameter measurements for each site along with the latitude and longitude coordinates of each
location. A session of ArcMap 10.2.2 was started and the Excel file was added to ArcCatalog. A feature
class was created from an XY table. The X and Y fields were chosen and the geographic coordinate
system was set to NAD 83. The new shapefile was added to the map. The shapefile was then projected
into NAD_1983_StatePlane_Pennsylvania_South_FIPS_3702_Feet using the ‘project’ tool under the Data
Management section of ArcToolbox. The NetStreams1998 and PaCounty2015_01 shapefiles were
downloaded from the Pennsylvania Spatial Data Access website (PASDA, 2013). The NetStreams1998
shapefile along with the World Imagery basemap were added to the data frame and the extent was set
to 1:45,000. The shapefiles were manipulated to display appropriate symbols and labels. Map elements
including a title, scale bar, north arrow, and legend were added to the data frame. A second and third
data frame were added to create location maps. Finally, the map was exported as an image.
20
A new session of ArcMap 10.2.2 was started. The projected data points shapefile that was
created was added to the data frame. Because certain parameters have direct or inverse relationships,
the water quality-indicator parameters chosen for geospatial analyses included temperature, DO, TDS,
and conductivity. A graduated colors map was created for each parameter. The classification was set to
Natural Breaks with 5 classifications. This was the best way to display ranges in variables. Appropriate
map elements were added and the map was exported as an image.
Scatter plot graphs were created and descriptive statistics including mean, median, standard
deviation, and range were performed for each parameter listed above. Temperature was chosen
because it highly influences the other parameters selected. Temperature is also a good way to
determine zones where spring water discharge is entering a channel. Dissolved oxygen was chosen
because it is a good indicator of whether a stream is healthy enough to support aquatic life. The third
parameter chosen was pH. Measuring this parameter can indicate the sources of influence on a stream.
For example, high pH indicates alkaline conditions which may be the result of carbonate bedrock.
Conductivity was chosen because it indicates the conductivity and thus the amount of material dissolved
in water (Kemker, 2014).
Results
The Burd Run
Table 1 (Appendix A) displays the latitude and longitude of each sample site location. Table 2
(Appendix A) shows the results of in-situ measurements along the Burd Run. However, discussion is
focused only on Temperature, DO, and TDS because the others are somewhat related to these. Springs
discharging into a stream channel have an average temperature of about 52°F year round (NGWA,
2010). If this water is entering the channel, temperature measurements should reflect this, along with
measurements of temperature-dependent parameters such as DO and TDS. Below, Figures 6 through 11
21
depict trends and patterns for temperature, DO and TDS for Burd Run. For each parameter, the trend is
shown as a line graph, while the corresponding pattern is shown on a GIS spatial plot.
Figure 6: Trend in Temperature for Burd Run sample sites 1 through 6.
Figure 7: Temperature Patterns along Burd Run depicted by a graduated colors scheme.
52.5
53
53.5
54
54.5
55
1 2 3 4 5 6
TEM
PER
ATU
RE
(°F)
DATA POINT
BURD RUN TEMPERATURE
22
Figure 8: Trend in Dissolved Oxygen for Burd Run sample sites 1 through 6.
Figure 9: Dissolved Oxygen Patterns along Burd Run depicted by a graduated colors scheme.
10.2
10.4
10.6
10.8
11
11.2
11.4
11.6
1 2 3 4 5 6
TDS
(PP
M)
DATA POINT
BURD RUN DISSOLVED OXYGEN
23
Figure 10: Trend in DO for Burd Run sample sites 1 through 6.
Figure 11: TDS Patterns along Burd Run depicted by a graduated colors scheme.
316
318
320
322
324
326
328
330
332
334
336
1 2 3 4 5 6
TDS
(PP
M)
DATA POINT
BURD RUN TOTAL DISSOLVED SOLIDS
24
Upper Middle Spring Creek (upward from confluence with Burd Run)
Table 3 (Appendix A) displays the results of in-situ measurements along the Middle Spring Creek
upstream from the Burd Run confluence. This discussion again is focused on temperature, DO, and
conductivity, rather than TDS. It must be noted that conductivity and TDS are directly proportional so
they show a similar pattern. Wastewater effluent that discharges into streams is treated, but not to the
condition it was when originally withdrawn. Increased temperatures, lower dissolved oxygen, and high
conductivity are indicators that there is a change in the water quality due to wastewater effluent
entering the stream. Below, Figures 12 through 17 depict trends and patterns for temperature, DO, and
conductivity, presented similarly as for Burd Run above.
Figure 12: Trend in Temperature for Middle Spring Creek sample sites 1 through 6.
53
53.5
54
54.5
55
55.5
56
56.5
57
1 2 3 4 5 6
TEM
PER
ATU
RE
(°F)
DATA POINT
MIDDLE SPRING CREEK TEMPERATURE
25
Figure 13: Temperature Patterns along Middle Spring Creek depicted by a graduated colors scheme.
Figure 14: Trend in Dissolved Oxygen for Middle Spring Creek sample sites 1 through 6.
9
9.2
9.4
9.6
9.8
10
10.2
10.4
1 2 3 4 5 6
DIS
SOLV
ED O
XYG
EN (
PP
M)
DATA POINT
MIDDLE SPRING CREEK DISSOLVED OXYGEN
26
Figure 15: Dissolved Oxygen Patterns along Middle Spring Creek depicted by a graduated colors scheme.
Figure 16: Trend in Conductivity for Middle Spring Creek sample sites 1 through 6.
400
450
500
550
600
650
1 2 3 4 5 6
CO
ND
UC
TIV
ITY
(ΜS/
CM
)
DATA POINT
MIDDLE SPRING CREEK CONDUCTIVITY
27
Figure 17: Conductivity Patterns along Middle Spring Creek depicted by a graduated colors scheme.
The Entire Middle Spring Creek (down to its mouth at the Conodoguinet)
Parameters focused for the analysis of Middle Spring Creek include temperature, DO, and
conductivity. These parameters were chosen to examine broader factors that may be influencing water
quality, such as urban runoff, agricultural development, and influences from Burd Run. Gaining
knowledge of areas larger than just a few small stream segments allows for the determination of
sources of influence from the larger watershed. Figures 18 through 20 illustrate temperature, dissolved
oxygen, and conductivity patterns of Middle Spring Creek both upstream and downstream from its
confluence with Burd Run, toward the Conodoguinet Creek. Only spatial patterns are presented.
28
Figure 18: Temperature Patterns along Middle Spring Creek, continuing downstream from the
confluence, depicted by a graduated colors scheme.
29
Figure 19: Dissolved Oxygen Patterns along Middle Spring Creek, continuing downstream from the
confluence, depicted by a graduated colors scheme.
30
Figure 20: Conductivity Patterns along Middle Spring Creek, continuing downstream from the
confluence, depicted by a graduated colors scheme.
Discussion of Results
The Burd Run
The results for temperature, dissolved oxygen, and TDS for Burd Run yield valuable information
about the characteristics of the stream. Temperature results show a significant variation from data
points 2 through 5. There is a decrease from 53.72°F to 52.7°F between points 1 and 2. The drop in
temperature around station 3 could be due to the influence of spring water entering the stream from
Hawbaker spring around this area. Beyond, the temperature stays fairly consistent until it spikes up to
31
54.68°F at data point 6. This spike could be due to surrounding agricultural practices around the vicinity
of data points 5 to 6.
When examining temperature-dependent parameters we expect to see an inverse relationship
for dissolved oxygen and a direct relationship for total dissolved solids. Looking at the data, however, it
is clear that these patterns do not occur. For example, dissolved oxygen decreases from site 2 to site 3,
and increases fairly steadily form sites 3 to 6. Total dissolved solids concentration steadily increases
form site 1 to site 5 and begins to decrease at site 6. Temperature and dissolved oxygen typically depict
an inverse relationship, while temperature and TDS often have a direct relationship. When comparing
these temperature-dependent parameters to the temperature data collected, it does not follow the
patterns as expected. The reason may be twofold. First, the station spacing may not be close enough to
reveal these relationships. Second, because of the preferential flow pathways of groundwater
contribution to streams in karst terrains, changes in quality indicator parameters may not display the
usually expected patterns.
Because groundwater does not have the opportunity to come in direct contact with atmospheric
oxygen sources, it is typically low in DO concentration (Kemker, 2013). Therefore, discharge from
groundwater springs containing low concentrations of DO could be the cause for the observed decrease
in dissolved oxygen in downstream segments. The abundance of karst features could also be the cause
for the increasing levels of total dissolved solids. The dissolution of limestone adds many carbonate and
bicarbonate ions into solution; their discharge into a stream channel by karst springs may be the cause
for the rise in TDS concentration. The largest increase in TDS occurs from data point 2 to data point 3,
where Hawbaker Spring discharges into the Burd Run channel.
32
Although there is some evidence from the analysis to support the idea that it is possible to
detect zones of spring water discharge, there is not enough data to accept the hypothesis. A survey
design with a higher resolution of sampling stations, say, 1 meter apart, would be ideal for further
examining this hypothesis.
Upper Middle Spring Creek (upward from confluence with Burd Run)
The results for temperature, DO, and conductivity of Middle Spring Creek follow typical patterns
of the other temperature-dependent parameters. The Shippensburg Wastewater Treatment Plant,
located along the Middle Spring Creek, discharges its treated wastewater into the stream between sites
4 and 5. At this point there is a spike in temperature, increasing from 53.36°F to 56.59°F. Dissolved
oxygen concentration drops significantly from 10.25 ppm to 9.15 ppm, following a consistent inverse
pattern with the temperature results. There is also a large jump in conductivity between these points,
474 – 618 µS/cm, indicating a direct relationship with temperature patterns.
These results show a strong evidence to support the hypothesis that there are noticeable
changes in water quality-indicator parameters downstream from the Shippensburg Waste Water
Treatment Plant. It was expected that there would be a large jump in temperature downstream from
the discharge point. Water used in the processes at the wastewater plant are treated before they enter
the stream, but are still much warmer than their receiving stream. It is also expected that dissolved
oxygen levels would deplete significantly because of the introduction of organic material. Biochemical
oxygen demand would rise, therefore, causing concentration of DO in water to decrease. Finally, due to
the large amount of organic material and chemical compounds entering the stream, it is expected that
conductivity would increase. The results depict these patterns from points 4 to 5 where there is
33
significant increases in temperature and conductivity and a clear decrease in dissolved oxygen. The
hypothesis that, there are noticeable changes in water quality-indicator parameters between the upper
Middle Spring Creek Segment and the lower segment, into which treated wastewater form the
Shippensburg wastewater Treatment Plant is discharged, is therefore not rejected.
The Entire Middle Spring Creek (down to its mouth at the Conodoguinet)
Results for temperature, dissolved oxygen, and conductivity of the entire Middle Spring Creek
above and below the confluence with Burd Run are discussed below. Temperature and dissolved oxygen
follow a similar and an inverse pattern throughout the stream. Temperature readings stay moderate
from the uppermost point of measurement, down across King St., and through the urbanized part of
Shippensburg but spikes to its highest measurement directly downstream from the wastewater
treatment plant and steadily grows cooler continuing downstream beyond the point of confluence. The
high temperature just below the point of treated wastewater discharge is expected, and as the water
continues downstream it cools off the rest of the way. This is probably because of the addition of cooler
water at the confluence with Burd Run. Farther downstream it becomes even cooler. This may also be
due to reduced impacts of anthropogenic activity away from the urban area and, therefore, less
potential for thermal pollution. The increase in riparian cover over the stream in this area may also
explain the cooling.
As expected, dissolved Oxygen follows an inverse pattern to temperature along the Middle
Spring Creek. Mid-range DO concentrations are measured upstream from the wastewater treatment
plant. However, concentrations drop to their lowest recorded values immediately downstream from the
wastewater plant. They then continue to rise steadily as the water flows downstream. These results are
34
expected due to the inverse relationship between temperature and dissolved oxygen. Urban runoff and
industrial influences are most likely the cause of low DO concentrations throughout the urbanized
Shippensburg area.
Conductivity, although temperature-dependent, does not follow these same patterns. The
lowest conductivity occurs at the farthest point upstream and steadily increases downstream.
Continuing downstream, it follows a steady increasing pattern. This is most likely due to multiple factors
influencing the stream waters. Runoff from impervious surfaces enters the most upstream portion of
the Middle Spring Creek study area. Father downstream this is mixed with wastewater effluents, which
is the most likely cause for the rise in conductivity just beyond the point of treated wastewater
discharge. Farther downstream nutrients, such as nitrogen and phosphorous may enter the stream
through agricultural practices, causing conductivity to continue to increase. All results along the Middle
Spring Creek are expected considering Shippensburg’s urban and agricultural land use practices. These
parameters all depict clear patterns that are consistent with various anthropogenic influences.
Summary Water Quality Comparison
Table 4 (Appendix A) displays the results of descriptive statistics conducted on in-situ
measurements recorded for this study. By using statistics such as mean, median, standard deviation, and
range, it is possible to compare the overall water quality of Middle Spring Creek with its tributary, the
Burd Run. The focal parameters for comparison are dissolved oxygen, total dissolved solids, and pH.
These are considered sufficient for assessing the overall aquatic health of each stream segment.
Organisms can survive in aquatic habitats with dissolved oxygen concentrations as low as 5 ppm.
However, in order for them to thrive, a concentration of 10 to 12 ppm is desired. Burd Run has mean
and median DO concentrations of roughly 11 ppm, which falls in the desired range. The mean DO
concentration for the upper Segment of the Middle Spring Creek is comparatively lower than that of
35
Burd Run, at 9.9 ppm, but still within the acceptable limit. When taken together, the entire Middle
Spring Creek has acceptable mean and median DO concentrations. Based on the DO parameter the
water quality of both tributaries is good for sustaining aquatic ecosystems.
Distilled water has a pH of 7, but for natural streams, the desirable range for freshwater is 6.0 to
8.5 (James et al., 2004). Burd Run displays a mean and a median value of PH that falls within this range.
The standard deviation is slightly high causing the values to range over 1.42 units. The Upper Segment of
Middle Spring Creek was found to have the same value for mean and median pH. This value falls
between the accepted range and the standard deviation value is low, suggesting lower variability. The
Lower Segment of Middle Spring Creek was found to have the highest pH values with mean and median
values of slightly more than 8. Comparatively, Burd Run pH values are closest to neutral but, overall,
both streams are considered aquatically healthy.
The final parameter analyzed is total dissolved solids. In pristine conditions, TDS ranges from 10
to 200 ppm. Good conditions are considered to be concentrations below 500 ppm (CalEPA, 2010). All
stream segments measured have TDS way within acceptable limits. Thus, when examining the
descriptive statistics of all three parameters, it is arguable that Burd Run has the best water quality. A
nearly neutral pH and high DO concentrations make this stream a healthy environment for aquatic life.
Although the data slightly favors Burd Run for overall aquatic health, TDS concentrations found in this
stream are slightly higher than either segment of Middle Spring Creek. However, this is most likely due
to the dissolution of nonhazardous carbonate minerals entering the channel. Despite the fact that Burd
Run has the best conditions, the data collected suggests that both bodies of water are healthy aquatic
environments.
Conclusion
36
Collecting in-situ water quality data is an important field technique that can be used to evaluate
the quality of surface and groundwater systems very quickly. This study tested two hypotheses
regarding the collection of in-situ water quality-indicator parameters: (1) It is possible to detect zones of
spring water discharge into the Burd Run channel (2) There are noticeable changes in specific water
quality-indicator parameters between the upper and lower segment of Middle Spring Creek.
To determine the best sites for data collection that would optimize the possibility of accepting
or rejecting the hypotheses, a survey design was made. Water quality parameters were recorded along
two tributary streams of the Conodoguinet Creek. The data was consolidated and analyzed using
descriptive statistics along with geospatial techniques.
Based on the analyses described in this report we failed to accept the first hypothesis but failed
to reject the second. The results showed some evidence to support the first hypothesis when analyzing
temperature-dependent parameters such as dissolved oxygen and total dissolved solids. However, there
is not enough data gathered to suggest its validity. Further research using a sampling survey with a finer
resolution is needed to fully assess the hypothesis. The second hypothesis was accepted as a result of a
large amount of supporting evidence. Trends in temperature, dissolved oxygen, and conductivity all
revealed that there are noticeable changes in water quality data on the Middle Spring Creek between
the upper segment and downstream from the Shippensburg Wastewater Treatment Plant. Comparisons
of these data, described statistically, suggest that Burd Run has slightly better water quality than Middle
Spring Creek, however, both streams are within acceptable limits for healthy stream water quality.
It is important to note that these are discrete measurements taken to reflect the water quality
parameters of Middle Spring Creek and Burd Run on one specific day. Further research should include
analyzing continuous measurements over a longer period of time. Long term data collection would
reveal how climate, land use, and geology directly affect the quality of these streams and may reflect
37
any patterns that may occur seasonally and/or annually. On Burd Run particularly, closer spacing of
measurement stations may allow for better detection of specific zones of spring water discharge.
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Appendix A: Tables
Table 1: Geographic location of each point of measurement.
Data Point Latitude (DD) Longitude (DD)
BR 1 40.06175 -77.5151
BR 2 40.06244 -77.5168
BR 3 40.06439 -77.517
BR 4 40.06619 -77.5194
BR 5 40.06817 -77.5221
BR 6 40.07081 -77.5291
MSC 1 40.04719 -77.5209
MSC 2 40.05058 -77.5235
MSC 3 40.05283 -77.525
MSC 4 40.05661 -77.5286
MSC 5 40.06172 -77.5324
MSC 6 40.06727 -77.5318
CONF 40.07074 -77.5351
MSC 7 40.08211 -77.5436
41
MSC 8 40.09781 -77.5615
Table 2: In-situ parameter measurements for Burd Run sample sites 1 through 6.
Data Point pH
ORP (mV)
DO (ppm)
SpC (µS/cm)
Resistivity (MΩ∙cm)
TDS (ppm)
Temp (°F)
1 BR 1 7.81 269.6 11.34 634 1577 318 53.72
2 BR 2 6.86 275.3 11.07 647 1546 323 52.7
3 BR 3 7.67 264.3 10.69 651 1536 326 52.9
4 BR 4 7.85 240.9 10.7 659 1520 329 53.16
5 BR 5 8.09 228.9 11.13 668 1497 334 53.08
6 BR 6 8.28 216 11.35 650 1538 325 54.68
Table 3: In-situ parameter measurements for Middle Spring Creek sample sites 1 through 6.
Data Point pH
ORP (mV)
DO (ppm)
SpC (µS/cm)
Resistivity (MΩ∙cm)
TDS (ppm)
Temp (°F)
1 MSC 1 8.19 204.4 9.95 418 2392 209 54.15
2 MSC 2 8.1 212.6 10.11 437 2288 218 53.61
3 MSC 3 8.08 212.4 9.99 453 2208 227 53.92
4 MSC 4 7.93 218.4 10.25 474 2105 237 53.36
5 MSC 5 7.88 225.5 9.15 618 1618 309 56.59
6 MSC 6 7.98 221.1 10.12 627 1568 317 54.89
Table 4: Water quality-indicator parameter Descriptive Statistics for segments of Middle Spring Creek
and Burd Run.
Burd Run
pH DO (ppm)
Conductivity (µS/cm)
TDS (ppm)
Temperature (°F)
Mean 7.76 11.05 651.5 325.8 53.4
Median 7.83 11.10 650.5 325.5 53.1
Standard Deviation 0.49 0.29 11.5 5.4 0.7
Range 1.42 0.66 34.0 16.0 2.0
Upper Segment MSC
pH DO (ppm)
Conductivity (µS/cm)
TDS (ppm)
Temperature (°F)
Mean 8.03 9.9 504.5 252.8 54.4
Median 8.03 10.1 463.5 232.0 54.0
Standard Deviation 0.12 0.4 93.3 47.6 1.2
Range 0.31 1.1 209.0 108.0 3.2
42
Lower Segment MSC
pH DO (ppm)
Conductivity (µS/cm)
TDS (ppm)
Temperature (°F)
Mean 8.09 10.9 647.0 315.0 53.1
Median 8.03 10.7 656.0 312.0 53.3
Standard Deviation 0.13 0.7 20.1 11.8 1.1
Range 0.23 1.3 37.0 23.0 2.1
