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

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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 0.74C (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 1.5C – 2.5C, 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 1C – 3C.

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 32C (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 32C 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.

Table 2: Water usages within sub – basins of the Susquehanna River. 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

Sub – basin Power

Generation Municipal Industrial Agricultural Domestic

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

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

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

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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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