Download An analysis of climate trends in the Susquehanna River basin

An analysis of climate trends
in the Susquehanna River
basin, Pennsylvania
Katherine Smith
Table Of Contents
Abstract ................................................................................................... 1
Introduction ............................................................................................ 2
Purpose & Scope ...................................................................................... 3
Literature Review..................................................................................... 3
What is Global Warming ............................................................................... 3
Trends in Climate over Time ......................................................................... 6
Impacts of Global Warming .......................................................................... 7
Climate Trends and Impacts within Pennsylvania ....................................... 10
Climate Change Analysis ............................................................................ 11
Methods for Analyzing Climate Change ....................................................... 13
Diurnal Temperature Range .................................................................... 13
Precipitation ............................................................................................ 14
Streamflow .............................................................................................. 16
Study Area ............................................................................................. 18
Methods ................................................................................................. 20
Diurnal Temperature Range ....................................................................... 23
Precipitation ............................................................................................... 24
Hydrology ................................................................................................... 25
Graphic Representation .............................................................................. 27
Results................................................................................................... 27
Maximum Temperatures – 1895 to Present ................................................. 27
Maximum Temperatures – 1980 to Present ................................................. 29
Minimum Temperatures – 1895 to Present ................................................. 29
Minimum Temperatures – 1980 to Present ................................................. 31
Diurnal Temperature Range – 1895 to Present............................................ 31
Diurnal Temperature Range – 1980 to Present............................................ 33
Precipitation – 1895 to Present ................................................................... 33
Precipitation – 1980 to Present ................................................................... 35
Comparative Analysis with Elevation, Latitude and Longitude .................... 35
Streamflow ................................................................................................. 38
Conclusions ........................................................................................... 38
References ............................................................................................. 43
List of Figures
Figure 1 ................................................................................................... 2
Figure 2 ................................................................................................. 19
Figure 3 ................................................................................................. 20
Figure 4 ................................................................................................. 26
Figure 5 ................................................................................................. 28
Figure 6 ................................................................................................. 28
Figure 7 ................................................................................................. 30
Figure 8 ................................................................................................. 30
Figure 9 ................................................................................................. 32
Figure 10 ............................................................................................... 32
Figure 11 ............................................................................................... 34
Figure 12 ............................................................................................... 34
Figure 13 ............................................................................................... 39
List of Tables
Table 1 ................................................................................................... 19
Table 2 ................................................................................................... 19
Table 3 ................................................................................................... 22
Table 4 ................................................................................................... 22
Table 5 ................................................................................................... 38
Abstract
Long term climate analyses have shown an increase in global
atmospheric carbon dioxide levels since the Industrial Revolution. This
increase in carbon dioxide not only increases temperatures but also accelerates
the hydrologic cycle. Within the last century, global average temperatures have
increased by nearly 1°C; a majority of this increase seen in the last 50 years.
The impacts vary, but can include an earlier timing of spring, extended growing
seasons, and shifts in water supplies. The Susquehanna River basin provides
approximately 50% of the fresh water for the Chesapeake Bay. Any projected
change in climate within the watershed has the potential to influence
agricultural and recreational activities in the basin, as well as influence
changes in an already stressed Chesapeake Bay. Five aspects of the basin’s
climate were analyzed over two time periods for their trend slope values using
FORTRAN programming; the results were then spatially represented utilizing a
GIS. Results have found that maximum and minimum temperatures are rising
for both time periods. Increases in maximum temperatures are greater than
minimum temperatures, and temperature increases from 1980 – 2008 are
greater than those seen from 1895 – 2008. As a consequence of the changes in
maximum and minimum temperatures, diurnal temperature ranges are
increasing when looking at the 1895 – 2008 period of record, but are
decreasing when looking at 1980 – 2008. Precipitation indicates large
increases over both periods of time studied. Streamflow indicates an overall
increase in drainage, with the exception of spring.
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Introduction
Over the last century, Earth’s climate has been changing due to
anthropogenic actions (IPCC 2007). Precipitation events have become more
erratic, while temperatures across the globe have increased. The subsequent
impacts of global warming are already being felt. Many climate analyses have
been conducted for the Earth as a whole, its continents, and various countries.
Recent climate studies are being performed at finer scales, such as the state
and watershed. This project will analyze any changes in climate that have
occurred in the Susquehanna River basin (Figure 1) over the period of record
(1895 – 2008).
Figure 1: The Susquehanna River basin in relation to the Chesapeake Bay
watershed.
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Purpose and Scope
It is important to understand current regional trends in climate given the
variable nature of climate and the uncertainty that potential future changes
can bring to a region. This study will focus on the Susquehanna River basin
and analyze climate trends across the basin over the period of record (1895 –
2008). The Susquehanna River basin is home to nearly 4 million people, and
its water uses include not only domestic, but also agricultural and industrial.
Specific aspects to be looked and questions to be asked include:

How has the seasonal and annual diurnal temperature range changed
over time?

How have the seasonal and annual maximum and minimum
temperatures changed over time?

How has seasonal and annual precipitation changed over time?

How has seasonal and annual streamflow changed over time?

What are the spatial patterns of the above temporal trends throughout
the basin?
Analysis of these trends and their spatial patterns will lead to a better
understanding of climate variability within the basin.
Literature Review
What is Global Warming?
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The greenhouse effect is essential to life on Earth. Greenhouse gases
(water vapor, carbon dioxide, methane, nitrous oxide, and ground level ozone)
exist naturally within the atmosphere (IPCC 2007; Miller 2008). These gases
trap outgoing terrestrial radiation, which in turn warms the surface of the
Earth through reradiation (Miller 2008). Long term climate analyses show that
recent changes in average climate are due to increases in carbon dioxide levels
within the atmosphere since the Industrial Revolution (Bell and others 2004). A
70% increase in anthropogenic greenhouse gas emissions has occurred
between 1970 and 2004 alone (IPCC 2007, Miller 2008).
Earth responds to this increase in the atmosphere’s capability to trap
more radiation by adjusting the energy balance so a new equilibrium is reached
(Miller 2008). Changes in the mean, or average, climate have profound impacts
on the intensity and frequency of extreme climatic events (Bell and others
2004). The distribution of most precipitation and temperature events follow a
normal curve. Small changes in the mean temperature, for example, have the
potential to shift the normal curve resulting in large changes of event
frequency. This creates an effect of increasing future extreme events at one
end (maximum temperatures) while decreasing the opposite extremes
(minimum temperatures) (Meehl and others 2000; Unkašević and others 2006).
Detecting, and attempting to predict, future temperature change is often what
drives climate change analysis (Boyles and Raman 2003).
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The simple act of measuring temperature can complicate climate
analysis. In the United States, historical temperature records are collected by
the National Weather Service’s Cooperative Station Network, which relies on
volunteers to record the maximum and minimum temperatures as well as
precipitation once within a 24-hour “observational day.” This day is defined by
the convenience of the volunteer. If temperature readings happen to be taken
at different times of the days, error and bias are then introduced into the daily
temperature statistics. Monthly maximum and minimum temperatures are
especially vulnerable to this error (Janis 2002).
Temperature is not the only variable that is going to change as the
climate changes. As temperature increases, the amount of latent heat
increases the atmosphere’s capacity to hold moisture, creating a positive
feedback. Subsequently, the hydrologic cycle is intensified and accelerated
through increasing amounts of evaporation and transpiration. In some
locations, this can create more frequent precipitation events (Hergel and others
2004, Arnell 1999).
This positive feedback amplifies the human – induced warming that is
already taking place due to increased carbon dioxide levels. It is thought that
an accelerated hydrologic cycle may be enough to double the effect seen
through current increases in carbon dioxide alone (Miller 2008). On the other
hand, accelerating the hydrologic cycle also creates a change in the amount of
cloud cover. The increased cloud cover then has a net cooling effect by
reflecting more incoming solar radiation. There is still insufficient evidence to
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determine the exact impact of increased cloud cover on global temperatures
(Miller 2008).
Trends in Climate
Current changes to the mean climate have already been recorded. There
has been an increase in the global mean temperature over the last century of
approximately 0.74C (Miller 2008). The linear trend for temperatures within
the 50 years spanning from 1956 to 2005 are nearly twice the trends of the 100
years that span from 1906 to 2005 (IPCC 2007). Moreover, of the twelve
hottest years on record since 1850, eleven of them occurred between 1995 and
2006 (IPCC 2007; Miller 2008). If these changes were due to natural
variability, the observed trends for air temperature would be similar to
predicted values including only natural variability. This is not the case. The
increase can be connected to human – induced climate change since observed
air temperature is significantly different than estimates that only include
natural variability (Hergel and others 2004).
As the mean temperature continues to rise at locations across the globe,
an increase in the number of extreme hot days and a decrease in the number
of extreme cold days have been observed (Meehl and others 2000). If this
change was due to a shift in the normal distribution of daily observations, then
the increasing trend for both cold and warm extremes would be equal.
However, there have been more increases in the cold extremes than for warm
extremes across the globe. Cold temperatures have shown a stronger increase
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in the Northern Hemisphere than the Southern Hemisphere (Hegerl and others
2004). This is more than likely due to the Northern Hemisphere having more
land coverage and a higher human population concentration than the
Southern Hemisphere, and therefore, the effects of human – induced warming
is greater. The potential for a warmer climate in the future may lead to longer
growing seasons, with hot days becoming a frequent part of prolonged heat
waves. A decrease in the number of cold days leads to a decrease in the
number of frost days (Bell and others 2004).
On the other hand, since 1900, precipitation has declined within the
Mediterranean, southern Africa, and portions of southern Asia. Increases in
precipitation have also been seen in northern Europe, northern and central
Asia, and the eastern portions of North and South America (IPCC 2007; Miller
2008). The intensity and frequency of extreme precipitation has also increased
across the globe (IPCC 2007). This change is due to storms being able to carry
more moisture (Miller 2008).
Impacts of Global Warming
Many of the future impacts of global warming are unavoidable, making
adaptation crucial (UCS 2008). Recent rises in global temperatures will
continue to affect changes in the timing of spring events, including leaf –
unfolding, as well as shifts in plant and animal species distribution. Currently,
agriculture is affected by earlier spring crop plantings, while forests have to
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adapt due to fire and an increase in pests within the higher latitudes of the
Northern Hemisphere (IPCC 2007).
If global average temperatures increase by 1.5C – 2.5C, there is a 50%
to 80% confidence level that around 20 – 30% of currently known plant and
animal species are at an increased risk for extinction. If temperatures exceed
that range, significant changes within the structure and function of ecosystems
would occur. This would result in negative effects on food and water supplies
(IPCC 2007).
Food production in the mid– to high– latitudes, and overall globally, is
likely to increase with a rise in temperature that ranges from 1C – 3C.
Depending on the region, some areas can expect an increase in precipitation
fed crops by approximately 5 – 20%. However, this is not the case for every
region. Lower latitudes have the potential for decreases in productivity with
temperature increases (IPCC 2007). Crops that are currently within the warm
extent of their suitable range are extremely susceptible, especially those that
rely heavily on various water resources. Such crops include cotton, rice, corn,
apples, peppers, potatoes, and watermelons (Draper and Kundell 2007; IPCC
2007).
Accompanying the increase in temperatures, the current projections for
precipitation show a 5% increase in the global land average by the end of the
century. How climate change will affect regional precipitation is still unclear,
even more so than with temperature changes (Miller 2008). Changes in
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temperature and precipitation will naturally lead to changes in runoff, and
subsequently in most areas, water supplies and resources.
Runoff is projected to increase by 10 – 40% in mid– to high– latitudes by
the middle of the 21st century (IPCC 2007; Miller 2008). Runoff changes would
lead to changes in reservoir storage amounts and timing of releases. Many
areas that rely on reservoir storage, like the Southwestern United States, are
already trying to handle the growing demands and associated competitions for
scarce water resource supplies (Miller 2008). This combined with current
projections of earlier snowpack melts and resultant reductions in summer
stream flows would increase competition over already sparse water resources
(IPCC 2007).
Aside from climate variability, water availability is also dependent on
numerous factors, including changes in: population growth, population
concentration, industrial use, agricultural use (irrigation), water use (including
efficiency and management of demands), as well as current environmental
requirements (Arnell 1999). All of these can vary at any given time, making
estimates of the future water use difficult. Future assessments are made
based on assumptions of potential changes within different areas (Arnell 1999).
Within North American metropolitan areas, intense heat waves are
already occurring. These heat waves are projected to increase in intensity,
frequency, and duration (IPCC 2007). Warming within western North America
is expected to decrease snowpacks, increase winter flooding, and reduce
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summer streamflow. This portion of North America will endure harsher effects
of climate change compared to eastern North America (IPCC 2007).
Climate Trends and Impacts within Pennsylvania
Pennsylvania encompasses 76% of the Susquehanna River basin (SRBC
2008). Within Pennsylvania alone, annual temperatures have been rising (USC
2008). Two of the most notable trends are that winter has warmed the most of
all the seasons, and many cities have experienced an increase in the number of
summer days over 32C (UCS 2008). In the northeast region of the state,
changes in the timing of leaf buds as well as insect migration show indications
of the earlier arrival of spring. All of these changes currently being observed
are related to human – accelerated climate change (IPCC 2007; UCS 2008).
Annual precipitation has increased approximately 5 – 20% statewide,
with the exception of south – central Pennsylvania. Since 1970 alone, there
has been an increase in the precipitation that is seen during winter, spring and
fall. Winter snowcover has been decreasing steadily across the state, with a
faster paced decline within the last few decades. Summer is the only season
that has had slightly less rainfall (UCS 2008).
Specific to Pennsylvania, a dramatic increase in the number of summer
days over 32C is expected throughout the state, subsequently increasing the
number of heat waves. This will cause urban air quality to decline and put
vulnerable populations at risk to heat – related health issues, as well as
intensify asthma and other respiratory diseases (UCS 2008). Increases in
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temperatures will stress agriculture. Dairy cattle are thought to reduce milk
production as temperatures rise. Crop yields of grapes, sweet corn, and
various apple varieties could decline due to an increase in the presence of pests
(UCS 2008). A reduction in winter snow packs is expected, along with a
decline in snowmobiling. Ski resorts could remain in operation until about the
middle of the century, when temperatures rise too high to sustain even
artificial snow (UCS 2008). It is expected that there will be a shift in plant
species such that warmer weather species will become more abundant in
Pennsylvania; one example is poison ivy.
Climate Change Analysis
Traditional climate analysis is generally done at specific locations by
analyzing data that are available over the period of record. Trends in
temperature and precipitation from one location can then be easily compared
to another location (Boyles and Raman 2003). Generally, researchers use
observations from one location as indicators for a large surrounding area, if the
region has relatively homogeneous vegetation and topography (Pielke and
others 2000). However, the results at a single location do not necessarily apply
to what is happening throughout a larger region (Boyles and Raman 2003), and
calculating a regional average based on a single point location can be
misleading (Pielke and others 2000).
Local climate analysis can help to precisely reflect the complex climate
that exists. It can also offer a more comprehensive understanding of the
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different patterns occurring within temperature and precipitation data (Boyles
and Raman 2003). If local temperature variability increases, the result will be
larger temperature increases than what is anticipated for the future (Hegerl
and others 2004). In order for there to be effective response and mitigation to
global climate change, local level assessment on the potential changes needs to
be conducted. Since local level climate changes are uncertain at a fine scale,
they cannot be satisfactorily represented through global climate models (Bell
and others 2004). Instead, analyzing a location’s climate trends is what is
customarily used to define the local climate (Boyles and Raman 2003).
Although various models and equations have been used to assess climate
change impacts at the local level, a major complication that arises is whether
or not the region can accurately be represented within those models.
Downscaling, or using regional variables to help define a local climate within a
global climate model, is a method that has been frequently used (Dibike and
Coulibaly 2005; Giorgi 2008; Hayhoe and others 2007; Mareuil and others
2007). However, the ability to accurately downscale predictor variables, such
as precipitation, still needs to be fully assessed with an emphasis on extensive
model experiments (Dibike and Coulibaly, 2005; Mareuil and others 2007).
A more simplistic approach is to analyze the spatial and temporal trends
currently taking place. Linear trends have the ability to be easily compared to
changes not only throughout different regional locations, but also across
various time periods (Boyles and Raman 2003). Spatial analysis also helps to
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alleviate the issue of inferring regional climate trends through a single site
(Pielke and others 2000).
Methods for Analyzing Climate Change
Diurnal Temperature Range
Diurnal temperature ranges (or DTRs) are the mathematical difference
between the daily maximum and minimum temperatures. The DTR is often
used in climate studies since the use of mean temperature alone can hide very
significant temperature change patterns by averaging the trends (Boyles and
Raman 2003; Holder and others 2006). There are also dramatic variations
within daily and weekly trends, along with seasonal variances (Boyles and
Raman 2003; Durre and Wallace 2001; Holder and others 2006). It is rare that
observations will follow a smooth trend over a significant period of time (Holder
and others 2006).
It has also been concluded that for most regions, the DTR will decrease
as mean temperatures increase (Boyles and Raman 2003; Bell and others
2004). This will occur when the increase in minimum temperatures is greater
than the increase in maximum temperatures (Bell and others 2004). As
previously stated, a shift in the mean temperature causes changes in the
frequency of events. The same can be said for the DTR. Any adjustment in the
mean temperature could induce large changes for the DTR (Unkašević and
others 2006).
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Prior studies of the DTR have found that there is variance across the
contiguous United States throughout different geographic regions (Durre and
Wallace 2001). One study has modeled the sensitivity of carbon dioxide within
the atmosphere and addressed the timing and length of the growing season in
relation to the DTR (Bell and others 2004). A study in North Carolina has
focused on separating seasons based on the astronomical definitions, January
– March categorized as winter, April – June categorized as spring, and so on,
and found the same trend of a decreasing DTR (Boyles and Raman 2003).
In North Carolina, studies have shown that minimum temperatures have
increased over time, with the most noticeable increases in the summer and the
fall, while overall maximum temperatures have increased just slightly (Boyles
and Raman 2003). This change in summer minimum temperatures alters the
DTR, creating a much narrower range. Prior studies in the Susquehanna River
basin specific to annual temperature alone utilized data from Philadelphia, PA
and New Haven, CT. The study found that annual average temperatures since
1781 have remained near the long term average of 8.8°C. There have been
three cooling periods throughout this record; however, recent annual
temperatures have risen to the warmest levels on record (Leathers and others
2008).
Precipitation
Although global average precipitation is projected to increase,
precipitation changes will likely not be consistent across the globe in both
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location and timing. Precipitation is dependent on numerous factors including,
but not limited to: season, temperature, and topography. An understanding of
precipitation patterns is important to governments and industries across the
globe (Boyles and Raman 2003). The reliability by which global climate models
create daily precipitation estimates at fine scales is not clear, especially when
precipitation is due to a convective event (Mareuil and others 2007).
Numerous studies indicate that extreme precipitation events will become
more frequent (Boyles and Raman, 2004; Mareuil and others 2007; Miller
2008). Precipitation is likely to become more intense daily, which is well
recognized as an effect of anthropogenic warming (Gutowski and others 2007).
Some predictions indicate that there will be the greatest increase in extreme
precipitation events where greater than two inches fall within a 24 – hour
period (UCS 2008).
With the exception of the southwestern United States, most of the United
States is projected to become wetter (Miller 2008). Previous studies of the
northeast United States indicate that annual precipitation has been increasing
over the last century, with decadal increases specific to the spring, summer
and fall, and decadal decreases in the winter (Hayhoe and others 2007).
Within North Carolina, throughout most of the state, fall and winter had
increased precipitation, summer had decreased precipitation, and spring had
no overall trend throughout the state (Boyles and Raman, 2003). Prior studies
that utilized proxy data within New Haven, CT and Philadelphia, PA determined
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that the Susquehanna River basin had an overall increase in the amount of
annual precipitation since 1829 (Leathers and others 2008). These two
locations were used since there is no data for the Susquehanna River basin
that dates back to the early 1800’s.
Streamflow
Since global climate change and the water cycle are so intricately linked,
it is important to consider other portions of the hydrologic cycle than just
precipitation. Along with precipitation, runoff is expected to change as a
response to climate change. Precipitation change is a crucial component for
changes in runoff, but evaporation changes are equally important since it is
controlled by changes within temperature and humidity (Miller 2008). Soil
moisture will change as a response to changes in precipitation as well. For
example, if soil moisture is low, the amount of runoff will be low as well due to
increased infiltration during precipitation events.
Predictions for changes within runoff indicate an increase for the eastern
portion of North America (Miller 2008). The demands for water are already
high since it is essential to every aspect of the way we live our lives. Not only do
humans rely on water for our own economic growth and food production, but
every level along the food chain requires water (Draper and Kundell 2007;
Miller 2008). Demands for water on a global scale have increased due to rising
populations, while our global supply of water has remained constant.
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By improving the ability to manage effects of current hydrological
impacts such as droughts and floods, future changes may be able to be better
managed as well (Miller 2008). In order to do this, we need to have a better
understanding of the past and current hydrology within a region. Since the
record only extends for a finite interval, it is not an accurate representative of
hydrologic cycles, both wet and dry. Of more concern within the historical
record are manmade structures that have been put in place to manage the
hydrologic flow conditions (Draper and Kundell 2007).
Previous studies have found that with increases in regional
temperatures, snowmelt will accelerate and result in an earlier runoff.
Changes in the resultant flood magnitudes will depend on the combined effect
of changes within the precipitation amounts and the timing of the midwinter to
spring thaw (Mareuil and others 2007). In some portions of the world, the
earlier timing of the spring stream flow will cause problems in the summer
when the peak agriculture demand occurs (Draper and Kundell 2007).
Other studies have found that significant increases in runoff could result
in increases of a return period of specific floods (Mareuli and others 2007).
Within the Susquehanna River basin, reconstructed and historic discharge
across the basin fluctuates. Most notable are different trends including dry
periods (1730s, 1840s, 1960s), as well as shorter moist periods (1810s, 1830s,
and 1970s) (Leathers and others 2008).
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Study Area
The Susquehanna River basin is located in the mid – Atlantic Region of
the United States and is a major contributor of fresh water to the Chesapeake
Bay watershed. The basin covers a drainage area of 71,228 km2; 76% is within
Pennsylvania, 23% within New York, and the remaining 1% in Maryland
(Leathers and others 2008; SRBC 2008).
As of the 2000 census, fewer than 4 million people reside within the
Susquehanna River basin. Current land use varies from agriculture and
forests to urban and mining. It lies across five major physiographic provinces
including the Appalachian Plateaus, the Blue Ridge, the Coastal Plain, the
Piedmont Plateau, and the Ridge and Valley. It consists of six major sub –
basins: Upper, Chemung, Middle, West Branch, Juniata and Lower (Figure 2).
Characteristics for each sub – basin are shown in Table 1. Each of these sub –
basins rely on the river and its numerous tributaries for different water usages
(Table 2, SRBC 2008). If future climate change begins to shift the distribution
of water within the basin, power generation within the West Branch and Lower
sub – basins, for example, may have to be shifted to other areas, such as
domestic uses.
Climate within the basin varies in a north – south gradient. The
northern portion of the basin lies on the Appalachian Plateau, and receives
more overall precipitation than the rest of the basin. This precipitation is in
the form of frequent rainfall events as well as greater snowfalls. The central
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Figure 2: Population centers in relation to the basin.
Table 1: Characteristics of the Susquehanna River sub-basins. Source: SRBC
2008.
Sub-basin Name
Area (km2)
Population
Upper
12,805
488,800
Chemung
6,721
225,350
Middle
9,767
696,800
West Branch
18,073
475,350
Juniata
8,816
312,750
Lower
15,045
1,761,500
Table 2: Water usages within sub – basins of the Susquehanna River.
Source: SRBC 2008.
Power
Sub – basin
Municipal Industrial Agricultural Domestic
Generation
Upper
40.7%
37.6%
15.2%
4.1%
2.4%
Chemung
59.8%
22.4%
9.7%
4.2%
3.9%
Middle
40.7%
37.6%
15.2%
4.1%
2.4%
West Branch
83.0%
8.7%
5.6%
1.5%
1.2%
Juniata
29.1%
23.8%
35.2%
6.4%
5.5%
Lower
89.0%
4.2%
4.8%
1.2%
0.8%
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portion of the basin is within the Ridge and Valley province. This region
experiences the greatest extremes within temperatures and rainfall, and also
receives the heaviest snowfalls. The lower portion of the basin is within the
Piedmont Plateau and Coastal Plain. It has a milder climate, but can
experience longer and hotter summers than the rest of the basin (UCS 2008).
Methods
In order to analyze seasonal and annual changes, monthly temperature
and precipitation data were collected from the United States Historical
Climatology Network (USHCN) for stations that are not only contained within
the basin (Figure 3), but also for stations that are outside of the basin within a
buffer of 25 kilometers. This buffer allowed for an accurate portrayal of climate
Figure 3: The six sub – basins of the Susquehanna River basin, as well as
locations of USHCN stations being used for this analysis.
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trends not only within the river basin, but also at the edges of the basin by
analyzing trends occurring within a region.
USHCN is a source of high quality data that is sponsored by the National
Oceanic Atmospheric Administration (NOAA) and the National Climate Data
Center (NCDC) in North Carolina. The data contained on the website go
through a series of adjustments (SHAP – Station History Adjustment Program)
that account for numerous outliers and inconsistencies within the station data
(Williams and others 2008). These inconsistencies can include random station
relocations as well as other station inconsistencies. Data were acquired at
http://cdiac.ornl.gov/epubs/ndp/ushcn/newushcn.html. Characteristics of
each station within the basin can be found in Table 3. The entire record was
utilized and subsequently broken down into a smaller portion, 1980 – Present.
This allowed a smaller, more significant period of time to be analyzed, which
also allowed for specific trends since the dramatic increase in carbon dioxide
emissions from 1970 to 2004.
Utilizing the mean climate, or 30-year average climate, alone at one
location can hide significant trends throughout time, especially when referring
to annual averages. Analyzing seasons is another way to analyze trends
throughout time, as well as provide insight into which seasons are being
affected the most. Previous studies have calculated seasons as winter being
January through March, spring being April through June, etc. in order to avoid
issues when averaging data from previous years (Boyles and Raman 2003).
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Table 3: Characteristics of USHCN stations within the basin.
Source: http://cdiac.ornl.gov/epubs/ndp/ushcn/ushcn_map_interface.html
Station Location
Station ID
Sub – basin
Beginning Date
Binghamton, NY
300687
Upper
1895
Cooperstown, NY
301752
Upper
1895
Cortland, NY
301799
Upper
1895
Maryland, NY
305133
Upper
1895
Morrisville, NY
305512
Upper
1895
Norwich, NY
306085
Upper
1895
Alfred, NY
300085
Chemung
1895
Elmira, NY
302610
Chemung
1895
Montrose, PA
365915
Middle
1895
Towanda, PA
368905
Middle
1895
State College, PA
368449
West Branch
1895
Wellsboro, PA
369408
West Branch
1895
Williamsport, PA
369728
West Branch
1895
Selinsgrove, PA
367931
Lower
1895
York, PA
369933
Lower
1895
However, in order to maintain the meteorological definitions of the seasons, for
this research seasonal divisions that were used are shown in Table 4. Since
each season is defined by a three month period, an average per season was
determined.
Table 4: Division of seasons throughout the analysis.
Winter
December (previous year), January, February
Spring
March, April, May
Summer
June, July, August
Fall
September, October, November
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Numerous computer codes were written in FORTRAN that helped make
analysis quick and seamless when compared to other methods. FORTRAN was
developed by IBM in the late 1950s with a design that allows mathematical
formulas to easily be translated into code for engineers and scientists. Since
then, it has been modified and updated in order to handle large – scale
programs. Current uses of FORTRAN include numerical weather predictions,
finite element analysis, and computational physics and chemistry. (FORTRAN
1999).
Diurnal Temperature Range
The DTR is the mathematical difference between the maximum and
minimum temperatures. It is used as an indicator of climate change since
using average temperature can hide trends over time. USHCN stations are
adjusted to account for bias that occurs within different observation times. For
each station, the data set contains three different pieces of information for the
monthly temperatures; the average, average daily maximum, and average daily
minimum. For this research, the DTR was calculated for each season utilizing
a code created in FORTRAN which performed the following steps:

Converted temperatures to degrees Celsius

Calculated an average of the seasonal maximum, average, and minimum
temperatures

Calculated the DTR (seasonal average minimum subtracted from the
seasonal average maximum)
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
Performed a standard linear regression on the DTR values, and seasonal
maximum, average and minimum through time to determine the trend
slopes

Utilized the time period from 1980 – present to determine if climate
trends are increasing or decreasing over a more recent time period.
After the trend slopes were calculated, they were compiled and analyzed within
a Geographic Information Systems (GIS) and Excel for graphic representations
across the basin and comparisons within seasons respectively.
Precipitation
USHCN stations contain raw precipitation data, and FILNET precipitation
data. FILNET precipitation utilizes a procedure that is similar to the SHAP
adjustment in order to fill in missing pieces within the original data based on a
network of surrounding stations. FILNET has also completed data sets for
stations that had been moved too often for SHAP to estimate adjustments
(Williams and others 2008). For the purposes of this research, the FILNET
precipitation data was used and analyzed with a FORTRAN code that
performed the following:

Converted all precipitation values from inches to centimeters

Calculated the cumulative seasonal precipitation

Calculated the cumulative precipitation for each water year (October to
September of the following year)
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
Performed a standard linear regression on the seasonal precipitation
values and the cumulative water year values through time to determine
trends

Utilized the time period from 1980 – present to determine if climate
trends are increasing or decreasing over a more recent time period.
It is important to use water years for there to be an easy comparison to water
budgets. After the trend slopes were calculated, they were compiled and
utilized with a GIS and Excel for graphic representations across the basin and
comparisons within seasons respectively.
Streamflow
Hydrologic data were collected from the Susquehanna River Basin
Commission, SRBC. These data have been run through SRBC’s OASIS model,
and are considered naturalized. Naturalized streamflow is a hypothetical view
of what the discharge at specific locations would be if no interferences were in
the way. Interferences include dams, levees, and stream channelization.
Gages were chosen to be within close proximity of the outlet of each sub –
basin, as well as three stations within the basin that correspond to USHCN
data stations. Figure 4 shows the locations of the resulting stations. After
gathering monthly discharge information from these eleven stations, the data
were analyzed based on the following FORTRAN code:

Converted discharge values from cubic feet per second to cubic meters
per day.
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
Divided streamflow by the drainage area to account for compounding
discharge values. Also gave values that are comparable throughout the
basin.

Calculated annual discharge trends (based on water year)

Calculated average seasonal trends (based on the monthly values)

Performed a standard linear regression on the seasonal discharge values
and the water year discharge values through time to determine trends
Again, it is important to use water years for easy comparison. After the trend
slopes were calculated, they were compiled and utilized within a GIS.
Figure 4: Locations of USGS real – time stream flow stations within the
Susquehanna River basin.
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Graphic Representation
After obtaining the linear slopes from the FORTRAN analyses, these
trends were put in to a GIS so the climate trends were spatially represented.
Mapping current trends is an important step in determining specific portions of
the basin may be at greatest risk to future climate changes. Trends from
individual stations will provide a general portrayal of current climate trends
across the basin. It is important to use the USHCN stations within a buffer
from the basin in order for the values not only within the basin, but also the
values at the boundaries to be accurate.
Results
It is worth noting that of all the USHCN stations that data were obtained
for, thirty stations had a significant amount of data spanning since 1895,
which allowed them to be included within the analysis.
Maximum Temperatures – 1895 to Present
Changes in maximum temperature from 1895 to present are shown in
Figure 5. Trends for the basin show an overall increase in maximum
temperatures for all seasons. Winter trends are increasing overall, with most of
the stations with significant increases positioned around the outer edge of the
basin. Spring and summer show a similar increasing pattern, with most of the
significant stations being on the eastern edge of the basin. Fall shows an
increase on the eastern and northern edges of the basin, while the middle and
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western portions show a slight decrease. Annual maximum temperatures show
increasing along the basin’s edge, as well as in the northeastern portion.
Maximum Temperatures – 1980 to Present
Maximum temperature changes from 1980 to 2008 are shown in Figure
6. Overall, each of the seasons shows increases in maximum temperatures.
Winter and spring show overall increases, with increases in winter being
stronger than in spring. Summer increases in maximum temperatures are in
the northern portion of the basin. The eastern portion of the basin shows
significant increases in the fall maximum temperatures. Twelve stations
indicate an increase in annual maximum temperatures; these stations are
towards the western and middle portion of the basin.
Minimum Temperatures – 1895 to Present
Figure 7 shows the changes in minimum temperature from 1895 to
2008. Winter shows slightly increasing trends that appear to be towards the
eastern edge and northern portion of the basin. Spring temperature trends
reveal the stations that have increasing trends are along the outer edges of the
basin with the middle and northwest portions of the basin decreasing. Again, a
majority of the stations for the fall have decreasing temperatures. A few
stations within the southern half of the basin have increasing changes in
temperature. Overall, the annual temperature trends are either slightly
increasing or slightly decreasing temperatures. Stations that were significant
throughout the majority of the seasons (stations that are outlying the
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southeastern and northeastern portions of the basin) have significant annual
changes in temperatures.
Minimum Temperatures – 1980 to Present
Figure 8 shows the changes within minimum temperatures from 1980 to
2008. Minimum temperatures in the winter are increasing overall, while spring
shows decreasing temperature trends. Minimum temperatures in the summer
and fall are increasing over the basin. The annual minimum temperature
trends are increasing across the basin as well.
Diurnal Temperature Range – 1895 to Present
Changes in the DTR from 1895 to 2008 are shown in Figure 9. These
trends appear to be a combination of both maximum and minimum
temperature trends, rather than a being driven by a few select stations. This
makes sense given how the DTR is calculated. It also indicates that the
maximum and minimum temperatures are most likely rising at relatively equal
rates. Winter indicates a slightly increasing DTR throughout most of the basin,
with few stations in the northern portion of the study area having a large
increase (where maximum temperatures are rising faster than minimum
temperatures).
The changes for DTR in the spring show an increase overall in the
northern and middle portion of the basin. Summer DTR trends lie around a
slight change in either direction. Fall shows an overall increase in DTR, with a
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few of the regions of the basin experiencing a strong decrease, while annually
the basin has slight changes in temperature.
Diurnal Temperature Range – 1980 to Present
Changes in the DTR from 1980 to 2008 are shown in Figure 10. Overall,
the seasons are showing a decrease in the DTR. The DTR for winter decreases
overall as you move from the southwestern to the northeastern portions of the
basin. Spring DTR changes are split between increasing and decreasing
trends. Summer shows the strongest decrease in the diurnal temperature
range. Eight of the ten significant stations have decreasing trends; only a few
stations throughout the basin have increases in temperature. Stations for fall
and annual trends both show a split between increasing and decreasing
temperatures.
Precipitation – 1895 to Present
Figure 11 shows the changes in precipitation from 1895 to 2008. Winter
changes in precipitation indicate an overall increase in precipitation, with the
northeastern portion of the basin having the stronger increase. Spring changes
in precipitation show overall increases in precipitation with a few stations
having a slight decrease in precipitation. Summer is split on increasing and
decreasing precipitation trends. Of all the seasons, summer has the greatest
number of stations with decreasing trends. Fall shows the strongest trends of
all the seasons; the vast majority of the stations in the basin have increasing
precipitation trends. The water year also indicates increases in precipitation,
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with the greatest increases occurring in the northern and western portions of
the basin.
Precipitation – 1980 to Present
Figure 12 shows the changes in precipitation from 1980 to 2008. Winter
has an overall increase in precipitation mainly within the northern and eastern
portions of the basin. Spring is split with trends. A slight increase in
precipitation is seen in the northern portion of the basin, while the southern
portion has a slight decrease. Summer trends show increases in precipitation
in the northeastern portion of the basin, and a slight decrease in the western
portion. Fall indicates an increase in precipitation throughout the middle of the
basin. Finally, precipitation over the course of a water year is increasing, with
the northeastern portion of the basin showing the strongest increase.
Comparative Analysis with Elevation, Latitude, and Longitude
After obtaining the trend slope values, it was important to determine if
the observed trends were being influenced by other factors such as elevation,
latitude and longitude. Table 5 shows the results of this analysis.
Precipitation for both time periods analyzed is directly influenced by changes in
elevation. In other words, the greater changes in precipitation are at the higher
elevations. Higher amounts of precipitation would fall at higher elevations as
well due to orographic effects. Temperature trends are indirectly influenced by
elevation for both time periods. That is to say, the higher in elevation a
location is, the trends that should be observed are smaller for changes in
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temperature. This makes sense conceptually since higher elevations usually
have cooler temperatures and less warming overall.
However, when looking at Figures 5 and 6, the trends seen are
contradictory. The majority of the increases in temperatures are seen at the
basin edges. By definition of a watershed, the higher elevations within the
basin are found along the edge of the basin. Elevations within the study area
range from 90m to 1860m. Looking back through the data, some of the
highest elevations have smaller increases in temperatures (e.g. 1770m with a
slope of 0.02 °C/cen) when compared to ever so slightly lower elevations (e.g.
1560m with a slope of 1.7 °C/cen). Given the just these two locations, it is
easy to see how an inverse relationship between station elevation and
temperatures changes would occur, and yet the higher elevations have
increases in elevation.
Overall, latitude has a direct influence on temperature changes within
the basin. That is to say, the further north in the basin the station is, the
greater the changes in temperatures. As the year progresses and the seasons
change, the angle and latitude that the sun’s rays hit the earth at change. This
can cause changes in temperature trends being driven by latitude. Greater
changes in maximum temperatures and diurnal temperature ranges occur at
the higher elevations. Minimum temperatures for 1895, and some a few
seasons within the 1980 analysis show an indirect relationship between
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latitude and temperatures. This is due to the greater changes in minimum
temperatures located in the southern portion of the basin.
Precipitation changes with latitude show an overall direct relationship.
In the winter, most of the precipitation within the basin is in the form of snow,
and most of the snowfall occurs within the northern portion of the basin.
Spring and summer incur the greatest ground warming, which spawns more
localized precipitation. The northern portion of the basin is more
mountainous, and therefore would receive more precipitation in the form of
orographic precipitation. However, one season, fall, shows an inverse
relationship with precipitation; this is most likely due to the sun’s angle in the
sky moving further to the south during this time, and creating less convective
precipitation within the region.
The majority of the temperature trends within the basin show direct
relationships with longitude. Some of the seasons show an inverse relationship
with precipitation. This means that the greater trends in temperature are seen
towards the western portion of the basin, while the greater changes in
precipitation are seen in the eastern portion of the basin. The eastern portion
of the basin is the portion that is the “upwards slope”, or creates the “upwards
lift” that is needed during rain events. This uplift is most likely what causes
more rain to be in this portion of the basin.
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Streamflow
Streamflow changes from 1932 – 2008 are shown in Figure 13. Overall,
the locations that were chosen have streamflows that lie close to a slight
increase in flows. Spring is the only season that shows a decrease in flows,
while winter contains the only location that has a significant change in
streamflow. Overall, the middle portion of the basin has the greatest increase
in streamflows.
Conclusions
Maximum temperatures are rising in both time periods that were
analyzed. Many locations within the basin, especially the northern portions,
are experiencing warmer temperatures. Minimum temperatures since 1895
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show a split between increasing and decreasing trends, while minimum
temperatures since 1980 clearly show an increasing trend as well. Since 1895,
the DTR throughout the basin shows a split in trends, with some areas leaning
towards an increasing DTR. Trends since 1980 show a decrease in DTR.
Finally, there have been significant increases in precipitation throughout the
basin in both time periods that were analyzed.
It was anticipated that winter and summer would have the strongest
decrease in the diurnal temperature range due to minimum temperatures
increasing at a larger rate than maximum temperatures. The majority of the
basin show slightly increasing ranges in maximum temperatures for winter and
summer. However, winter has more stations that have decreasing temperature
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trends due to maximum temperatures increasing basin wide. If this trend
continues, ski resorts in the basin such as Elk Mountain and Sno Mountain
could have to open later and close earlier in the season. On the other hand, it
appears that spring has the greatest increase in diurnal temperature range.
Plant budding and animal migrations will occur earlier in the year. If this
increase continues as well there will ultimately be a shifting in seasons within
the basin.
It was also expected that the southern portion of the basin would have
the faster temperature changes than the northern portion of the basin due to
trends already seen (UCS 2008). While stations in the southern portion of the
study area do have the greatest increase in summer maximum temperatures,
overall the opposite appears to be occurring; the northern portion of the basin
is having a faster rise in temperatures than the southern portion of the basin.
This could be due to the concentration of stations in the northern portion of
the basin compared to the southern portion. More stations within the
southern portion of the basin would be helpful in determining if this is the
case. With the increases in temperatures, the timing of crop planting,
flowering, and harvest may be affected, as well as yields of not only harvests,
but also milk from dairy cattle.
As natural cycles become more exaggerated, it was expected that spring
would have the greatest increase in precipitation and summer was expected to
have the greatest decrease (Hayhoe and others 2007). Summer does appear to
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have the greatest decline in precipitation. However, fall clearly has the greatest
increase in precipitation of all the seasons. It was also expected that the
northern portion of the basin would have the greatest decline in precipitation.
Again, this doesn’t appear to be the case. The northern portion of the basin
shows increases in precipitation. This could also be due to the larger number
of stations in the northern portion of the basin.
With an increase in precipitation, it was expected that there would be an
overall increase in streamflow as well. While that is seen, the majority of the
results are not statistically significant. It is important to note that spring
shows an overall decrease in streamflow, which is odd considering the
precipitation shows increasing trends in the northeastern and southern
portions of the basin. Also, the station towards the mouth of the West Branch
sub – basin shows the strongest change, whether it is an increase or decrease.
Since the USHCN stations in this portion of the basin are sparse, it is hard to
determine what would be causing this. With an increase in water leaving the
basin, it could cause problems in the variety of water uses throughout the
basin.
While climate has been changing over the last 100 years, within the last
50 years there has been a dramatic change to the mean climate due to
numerous anthropogenic actions. Changes projected in Pennsylvania include
an earlier timing of spring, increased heat waves, and decreased snowfall
totals. Local climate analysis throughout the Susquehanna River basin show
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that maximum and minimum temperatures are increasing, as well as
precipitation. Knowing and understanding these current changes lend insight
to what aspects of climate may have greater change in the future that have the
potential to affect agriculture and recreation industries within the basin, but
also anticipate changes that may occur within the Chesapeake Bay. Future
studies could determine if the trends that are currently observed are
continuing as is, worsening, or slowing. Also, a further investigation into why
streamflow throughout the basin is experiencing changes, but not at a
significant rate would be insightful.
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