SERVICE-LEARNING PROJECT DISTRIBUTION IN THE DOG RIVER
WATERSHED
D. Logan Anderson, Department of Earth Sciences, University of South Alabama, Mobile, AL
36688. E-mail: dla1001@jagmail.southalabama.edu.
Service-learning at the undergraduate level helps to focus on “man-land” interactions and
develop student research interests regarding the quality of watersheds throughout the United
States. Such programs, with the cooperation of watershed maintenance organizations, provide a
database of reports which comment on the health of local watersheds as well as provide support
for communities interested in maintaining the quality of those watersheds. Because most
undergraduate student-led watershed research projects must be completed within a traditional
semester, there may be difficulty in designating a feasible topic due to the ever-increasing
amount of former student projects. Such is the case at the University of South Alabama within
the department of Earth Sciences. Geography students enrolled in their respective fieldwork
course (GEO 480) compete with a variety of former, student-led research topics regarding their
local watershed, the Dog River Watershed, spanning sixteen years. While some projects present
the opportunity for temporal study, most seemingly inhibit the variability of future studies which
can be accomplished within a given time frame. Therefore, the spatial distribution of former
study areas and the frequency of former topics were compiled and mapped for the purpose of
aiding future GEO 480 students to determine problems and potential maintenance goals unique
to previously, less-researched study areas was the objective of this study. It was discovered that
the most-researched topics concerned water quality and little to no research had been
accomplished regarding terrestrial characteristics of the Dog River Watershed.
Keyword: service-learning, undergraduate research, watershed
Introduction
Between eastern Texas and western Florida, coastal watersheds bordering the Gulf of
Mexico provide important support systems for localized wetland areas as well as serve the needs
of industrial transportation networks for inland economies (Zhang et. al., 2011). By
understanding the complexities of watersheds and attributing their health and maintenance to
sustaining the integrity of the environment (Haury, 2000), we can protect such resources as a
means of supporting the future growth of human development. Much pollution on land and in
water is watershed based, caused by numerous direct and indirect factors influenced by
1 interactions between the land and the people who inhabit it (Shepardson et. al., 2007); however,
communities tend to be unknowledgeable of the repercussions of these interactions without the
interests of watershed associations and the goals of service-learning initiatives which inspire the
improvement of water quality and the protection of water resources (Cline et. al., 2003).
Within the past ten years, efforts to reduce the effects urban growth have upon the
ecosystem correlate negatively with provisions of urban ecosystem services (Schmidt et. al,
2012). Education is necessary, and the implementation of service-learning programs at the
undergraduate college level have proven to help focus on “man-land” interactions through
student discovery of potential solutions to issues associated with populated, urban watersheds.
Doing so tends to bridge the gap between academic communities and public communities in
terms of the levels of interest in preserving their local watershed (Elfin et. al., 2007). An example
of such “bridge building” is the Thornton Creek Project near Seattle, Washington; the activities
undertaken by students allowed for educational programs, restoration projects, and workshops to
be administered at the community level after research had been done for course credit and
presented as part of an overall service-learning project. The knowledge they gathered, be it from
personal field observation and measurement or secondary research, helped to blur the lines
between all community divisions and inspire continued monitoring of their local watershed
(Donahue et. al., 1998).
Similar community outreach is apparent in Mobile, AL through a grassroots organization
known as the “Dog River Clearwater Revival” (DRCR), whose bylaws state: “The purpose of
this organization is to improve the water quality in the streams, creeks, rivers and wetlands of the
Dog River Watershed, and to restore and maintain the quality of life and best possible
environment for fish and wildlife, public recreation, and commerce in the watershed. Dog River
2 Clearwater Revival encourages vigilant enforcement of environmental protection laws, the use of
Best Management Practices (BMPs) and Best Available Technologies(BATs) in storm water and
flood plain management, and general public education and outreach regarding responsible land
use practices within the watershed” (Dog River Clearwater Revival, 2013). In addition to the
efforts of the Dog River Clearwater Revival organization, students at the University of South
Alabama, with the guidance of Dr. Miriam Fearn, Chair of the Department of Earth Science,
“…study problems related to water quality in the Dog River Watershed” with the objective of
“… [improving]…students’ research and writing skills, [applying] classroom knowledge to a real
world problem, and [providing] information of value to the community” (Dog River Watershed,
2012). This is primarily done through field work, undertaken by students, and through the
evaluation of student-led projects which ideally identify an issue they see threatening the health
of a particular area of the watershed and potential ways to alleviate such threats.
Studies in the field are excellent modes of integrating classroom content with practical
concepts of research (Kent et. al, 1997). When incorporated as a means of encouraging projects
such as watershed maintenance, a wealth of knowledge can emerge benefiting both the learning
experience and the community, but “[t]he most difficult part of…fieldwork…for many students
is the interpretation of their own results” (Haigh et. al., 1993). Being introduced to an overall
appreciation of the study area and then being left to conduct “option-based” fieldwork can
conflict with particular needs of the project as a whole (Kent et. al, 1997), which can be
summarized as lacking in knowledge of certain areas of the project which have previously been
un-researched yet need to be researched.
In the case of the University of South Alabama, students undertaking personal field
research to identify and offer potential suggestions of improving the Dog River Watershed and
3 its maintenance are faced with a seemingly bourgeoning database of knowledge as previous
studies populate the list of projects. This will hinder further studies of the watershed by students
with a limited time frame for project completion as the daunting task of creating a unique
hypothesis becomes inundated with similar interests having already been researched. Without
the ability to recognize where “holes” exist in the research regarding the maintenance of the Dog
River Watershed, I feel it may become even more difficult to satisfy this lack of research,
ultimately affecting watershed quality maintenance in the form of student involvement. By
presenting an overall distribution of former projects, the areas of the Dog River Watershed which
lack student research are spatially exposed, potentially aiding future fieldwork students with the
ability to provide unique projects beneficial to the maintenance of the watershed.
Research Question
What is the spatial distribution of former study areas and which topics tend to be the most
studied within the Dog River Watershed? Answering such questions concerning student-led
research regarding issues and maintenance of the Dog River Watershed, future fieldwork
students can determine problems and potential maintenance goals unique to previously, lessresearched study areas.
Study Area
The major and minor fluvial systems of Dog River drain a ninety-five square mile basin
located near the northwestern side of Mobile Bay in southwest Alabama (Dog River Watershed,
2013) (Figure 1). The major municipality dependent upon this watershed is the city of Mobile,
which lies approximately 140 miles east of the city of New Orleans, Louisiana, 72 miles west of
4 Pensacola, Florida, and 250 miles south of Birmingham, Alabama along the west bank of Mobile
Bay near the mouth of the Mobile River.
From 1997 to 2012 senior students enrolled in Dr. Miriam Fearn’s Fieldwork course,
Geography 480, have chosen to research issues within, and pertaining to, the Dog River
Watershed. Due to the nature of this study and the goal of determining the frequencies, trends
and distribution of former projects completed by Fieldwork students over the course of sixteen
(16) years, all data collected and analyzed was limited solely within the boundaries of the
watershed.
Figure 1
THE DOG RIVER WATERSHED AND ITS PROXIMITY TO
MOBILE, AL, MOBILE BAY AND THE GULF OF MEXICO.
Sources: ESRI; City of Mobile, AL
5 Methods
Data pertaining to this project was collected and analyzed in three stages. The first of
these being archival research, performed similarly to the method performed by Dr. Carol Sawyer
in her participation of documenting avalanche frequency in Columbia Falls, Montana between
1946 and 2005 (Sawyer et. al., 2006). Information was compiled using research reports collected
by Dr. Fearn in the department of Earth Science detailing former student research conducted in
the Dog River Watershed. To organize student reports for subsequent categorization, the year it
was written, associated key words and titles of each project were hand recorded into a log with a
corresponding number. For example, the key words of the first project, the year it was written, its
author, and its title were given the number (1), and the same criteria for the second project were
given the number (2), and so on and so forth (Appendix A). A total of 191 student reports were
recorded.
Once this had been accomplished, using Microsoft Excel, key words following abstracts
of each student report were entered. Although some reports failed to utilize key words following
an abstract, a majority of projects contributed to the 539 total key words recorded and
alphabetized for further organization. After double checking each key word against their
corresponding abstract, all similar key words were combined into a single Microsoft Excel
column to represent the numerical total of any word used more than once (Appendix B). This
was a necessary step due to a desire to provide initial data for analysis regarding project topics at
their most fundamental level. However, in order for students enrolled in future Fieldwork classes
to benefit from this list of key words, they would need to be able to associate each key word with
a project which they could further, independently investigate. Therefore, using the first data log
of this project, each project report number was recorded next to its respective key word in the
6 combined key word list to show a return of which projects utilized which key word (Appendix
C). As an example, the key word “Awareness” was used twice by projects numbered 5 and 39.
The second stage of data collection and analysis for this project relied on a method of
organizing published research into various categories, completed by Dr. Carol Sawyer in her
unpublished doctoral dissertation wherein patterned ground research was sorted by form
(Sawyer, 2007). Because the majority of student Fieldwork reports deal with the physical
characteristics of a watershed, the U.S. Department of Agriculture’s “Watershed Condition
Indicator Model” was used in an attempt to classify each report (Potyonde et. al., 2011).
Although such a model of classification is used to determine the health of a watershed, in the
case of this project it was accessed as a means of organizing student topics.
The four initial Watershed Condition Indicator categories are “Aquatic Physical,”
“Aquatic Biological,” “Terrestrial Physical,” and “Terrestrial Biological.” Again, because the
purpose of this project is not to determine the health of a watershed, a fifth category was added
to absorb student topics which fall outside of the EPA’s watershed health indicators, and is
simply titled “Other.” Within each of the four initial Condition Indicator Categories and within
the added “Other” category is an additional seventeen (17) Watershed Condition Indicators
suitable for further categorizing student reports: (1) Water Quality, (2) Water Quantity, (3)
Aquatic Habitat, (4) Aquatic Biota, (5) Riparian/Wetland Vegetation, (6) Roads and Trails, (7)
Soils, (8) Fire Regime or Wildlife, (9) Forest Cover, (10) Rangeland Vegetation, (11) Terrestrial
Invasive Species, (12) Forest Health, (13) Public Education, (14) Historical Perceptions, (15)
Social Characteristics, and (17) Atmospheric Characteristics (Table 1).
7 Table 1
WATERSHED CONDITION INDICATOR DESCRIPTIONS.
Aquatic Physical Indicators
1. Water Quality
2. Water Quantity
3. Aquatic Habitat
This indicator addresses the expressed alteration of physical, chemical,
and biological components of water quality.
This indicator addresses changes to the natural flow regime with
respect to the magnitude, duration, or timing of the natural stream flow
hydrograph.
This indicator addresses aquatic habitat condition with respect to
habitat fragmentation, large woody debris, and channel shape and
function.
Aquatic Biological Indicators
4. Aquatic Biota
This indicator addresses the distribution, structure, and density of
native and introduced aquatic fauna.
5. Riparian/Wetland Vegetation
This indicator addresses the function and condition of riparian
vegetation along streams, water bodies, and wetlands.
Terrestrial Physical Indicators
6. Roads and Trails
7. Soils
This indicator addresses changes to the hydrological and sediment
regimes because of the density, location, distribution, and maintenance
of the road and trail network.
This indicator addresses alteration to natural soil condition, including
productivity, erosion, and chemical contamination.
Terrestrial Biological Indicators
8. Fire Regime or Wildlife
9. Forest Cover
10. Rangeland Vegetation
11. Terrestrial Invasive Species
12. Forest Health
This indicator addresses the potential for altered hydrologic and
sediment regimes because of departures from historical ranges of
variability in vegetation, fuel composition, fire frequency, fire severity,
and fire pattern.
This indicator addresses the potential for altered hydrologic and
sediment regimes because of the loss of forest cover on forest lands.
This indicator addresses effects on soil and water because of the
vegetative health of rangelands.
This indicator addresses potential effects on soil, vegetation, and water
resources because of terrestrial invasive species (including vertebrates,
invertebrates, and plants).
This indicator addresses forest mortality effects on hydrologic and soil
function because of major invasive and native forest insect and disease
outbreaks and air pollution.
Other
13. Public Education
Projects related to public awareness and education of local watersheds.
14. Policy
Projects related to laws governing man-land interactions with local
watersheds.
15. Historical Perceptions
Projects related to the history and evolution of local watersheds.
16. Social Characteristics
Projects related to populations which affect local watersheds.
17. Atmospheric Characteristics
Projects related to how atmospheric conditions are within local
watersheds.
8 By examining each report, its topic, and its key word(s), project report numbers were
assigned to each of the Watershed Condition Indicators. Another Microsoft Excel table was
produced to represent the quantities of reports under their respective categories, reflected in the
occurrences of each individual project report number (Table 2).
Table 2
STUDENT REPORTS ORGANIZED WITHIN THE WATERSHED CONDITION INDICATOR CATEGORIES.
Watershed Condition
Indicators
Categories
Corresponding Student Reports
(By Number)
Water Quality
3, 4, 13, 14, 18, 22, 30, 31, 35, 36, 38, 40, 41, 43,
45, 48, 50, 51, 54, 55, 59, 66, 69, 72, 74, 79, 82, 83,
84, 90, 92, 97, 101, 103, 104, 109, 115, 116, 117,
118, 119, 122, 123, 125, 127, 128, 131, 134, 138,
140, 145, 149, 151, 152, 158, 162, 166, 167, 168,
169, 174, 178, 181, 184, 185, 186, 187
Water Quantity
19, 21, 37, 47, 53, 61, 62, 69, 86, 94, 95,
109, 135, 143, 147, 150, 161, 175
Aquatic Habitat
10, 11, 29, 34, 49, 52, 67, 71, 91, 106, 111, 139,
164, 180
Aquatic Biota
28, 63, 73, 110, 170, 171
Riparian/Wetland
Vegetation
2, 24, 32, 42, 56, 78, 80, 88, 89, 98, 144, 154, 142
Aquatic Physical Indicators
Aquatic Biological
Indicators
Terrestrial Physical
Indicators
Terrestrial Biological
Indicators
Roads and Trails
Soils
Fire Regime
or Wildlife
Forest Cover
Rangeland
Vegetation
Terrestrial
Invasive Species
Forest Health
Public Education
Policy
Other
Indicators
156, 159
65, 87, 96, 102, 105, 108, 112, 153, 155, 163, 172,
173, 177, 182
6
5, 15, 22, 25, 39, 60, 64, 75, 77, 121, 124, 129, 141,
146, 126
23, 46, 57, 99, 130
Historical
Perceptions
Social
Characteristics
Atmospheric
Characteristics
9 1, 7, 8, 9, 12, 16, 17, 26, 27,
85, 107, 133, 136, 148, 179, 176, 189
70, 90, 93, 113, 137, 157
44, 165, 191
65, 100, 120, 132, 163, 183, 188, 190
160
The final stage of data collection and analysis dealt solely with the distribution of former
student project study areas. Using ArcMap software, version 10.1, two field maps were created,
similar to Figure 1, of the Dog River Watershed with an added water bodies layer and road
network layer. In re-examining each of the 191 student reports, points were placed, by hand, on a
printed copy of the field maps. Visual approximations of study sites were made with student
reports whose study area descriptions did not give exact locations, exact locations were marked
with student reports whose study area descriptions included geographic coordinates, and any
studies completed of the entire watershed or large sections of the watershed were designated as
“Difficult to Determine.” Student reports which did not specify a study area, such as those
belonging to the “Historical Perceptions” indicator category, or were beyond the boundaries of
the Dog River Watershed were designated as “No Study Site Specified” or “Outside Watershed.”
After all points were recorded on the field maps, methods outlined in Wagner’s article
regarding the spatial distribution of archaeological sites in northern China (Wagner et. al, 2013)
guided the digital input of each study site location into a shape file within ArcMap to show their
spatial distribution throughout the Dog River Watershed (Figure 2). Afterwards, using
ArcToolbox spatial analyst software, each study area was rasterized for the density of student
research completed at that particular location (Figure 3) and a “mask” was created to confine all
raster values within the borders of the Dog River Watershed for visual purposes.
10 Figure 2
FORMER STUDENT RESEARCH REPORT STUDY SITES
WITHIN THE DOG RIVER WATERSHED
Figure 3
INITIAL DESNITY RASTER OF FORMER
STUDENT RESEARCH REPORTS
11 Results
After recording 539 key words from the abstracts of student project reports in Geography
480, Fieldwork, and grouping them based on the frequency of their usage, a “Top Twenty” list
was compiled which displays the greatest occurrences of the following key words: Dog River,
Water Quality, Dog River Watershed, Turbidity, Watershed, Litter, Sedimentation,
Channelization, Mobile, Runoff, Alabama, Sediment, Urbanization, Wetlands, Best Management
Practices (BMPs), Trash, Construction, Dissolved Oxygen, Geographic Information Systems
(GIS), and Spring Creek (Figure 4). Each of these key words occurs five times or greater among
the total amount of key words selected by students. Besides common key words associated with
a majority of reports, such as “Dog River,” or “Dog River Watershed,” all key words are
associated with projects which exhibit the greater frequencies regarding their organization within
the Watershed Indicator Model.
Top Twenty Key Words
40
35
Number of Occurrences
30
25
20
38
15
10
20
19
18
15
5
11
10
8
8
8
7
7
7
7
0
Key Words
Figure 4
KEY WORDS USED FIVE TIMES OR GREATER
12 6
6
5
5
5
5
Regarding the organization of student project reports into categories outlined by the U.S.
Department of Agriculture’s Watershed Condition Indicator Model, as well as the addition of an
“Other Indicators” category, projects concerned with the sub-category “Water Quality” were the
most common with 67 reports (Figure 5). Sub-categories with a number of student reports
greater than 10 but less than 20 were “Water Quantity,” “Roads and Trails,” “Public Education,”
“Aquatic Habitat,” “Rangeland Vegetation,” and “Riparian/Wetland Vegetation.” Sub-categories
with a number of student reports greater than one but less than 10 were “Social Characteristics,”
“Aquatic Biota,” “Soils,” “Policy,” “Historical Perceptions,” “Forest Cover,” “Terrestrial
Invasive Species,” and “Atmospheric Characteristics.” The final two sub-categories had no
comparable student reports and were “Fire Regime or Wildlife,” and “Forest Health.”
Watershed Condition Indicators
80
Number of Corresponding Student Reports
70
60
50
40
67
30
20
10
18
17
15
14
14
13
8
6
6
4
3
2
1
1
0
Condition Indicator Categories
Figure 5
FREQUENCY OF STUDENT REPORTS WITHIN SUB-CATEGORIES OF
THE WATERSHED CONDITION INDICATOR MODEL
13 0
0
The distribution of former student research report study areas within the boundaries of
the Dog River Watershed exhibit high densities in or around areas of the “Halls Mill Creek,”
“Moore Creek,” “Eslava Creek,” and “Rabbit Creek” sub-watersheds. The total number of study
sites, with the exception of those concerning the entire Dog River Watershed, undisclosed or
difficult to determine study sites, or reports not dealing with physical aspects of the watershed,
was 445. Visually these densities are represented with the help of a density raster wherein the
greater the amount of student report study areas within an area, the higher the raster value.
Subsequently, these higher densities appear as a darker color within the map in Figure 6.
Figure 6
FINAL DENSITY RASTER OF FORMER STUDENT REPORTS. NOTE THE DARKER SHADES OF GREEN
REPRESENTATIVE OF THE LOCATION OF GREATER NUMBERS OF FORMER STUDY AREAS.
14 Discussion and Conclusion
In analyzing the extracted data regarding written student reports between the years 1997
and 2012 and distributing them among the four major Watershed Condition Indicators, as
outlined by the U.S. Department of Agriculture, several factors were taken into consideration.
First, with an initial twelve sub-categories within the Watershed Condition Indicators, it was
important to understand how each student project applied to the description of these indicators.
Many projects were difficult to define in terms of an indicator due to the fact that their study
seemingly dealt with more than one issue concerning the Dog River Watershed. It often became
necessary to further interpret the project based on the author’s research questions and objectives
and how they applied to their results. As obvious as such a task may seem, it was not apparent
that this particular way of determining the best category for a project was the most suitable
method until these two aspects of the projects were separated from the rest of the research. After
this was accomplished, an additional issue occurred in the interpretation of reports and their
categorizations, which were those projects that, in little to no way, met the qualifications of the
Watershed Condition Indicator category descriptions. By adding a new category to satisfy such
projects, new sub-categories presented themselves due to the frequency in which the reports
satisfied various other topic descriptions.
Second, with so many topics previously studied, determining the importance of
categorizing them and recognizing their trends and the spatial distribution of each study area was
key to understanding in which ways this data could be presented to provide the best possible
resource for future Fieldwork students trying to develop their own unique research perspective.
Given the results it is apparent that a majority of students have always been concerned with the
quality of water within the Dog River Watershed, which is in and of itself a great resource for
15 those interested in the maintenance of the watershed. However, what we see as a result of this
study is the need for greater interest in other areas of the conditions of the Dog River Watershed,
particularly those of a terrestrial nature. This is also evident in the highest densities of study
areas being centered on the aforementioned sub-watersheds and the lowest densities spread out
among the non-fluvial regions of the watershed.
Finally, we have been made aware through these student reports the condition of the
water itself, but what about some of the many factors influencing those conditions? Of course
studies have been performed regarding the effects of impermeable surfaces, and the effects of
urbanization, etc., but perhaps a new perspective on not just what negatively affects the water
quality can be adopted. Some of the more creative topics dealt primarily with the habitat the
Dog River Watershed provides; not just for plants and animals, but for humans as well. The
social characteristics of what impacts the maintenance of watershed quality is of particular
importance when we take into consideration the daily interaction humans have with the
watershed that supports them.
Overall, many of the reports generated by previous students in Dr. Fearn’s Geography
480, Fieldwork course provided generous insight into the workings of the Dog River Watershed,
and on various levels. While this study aimed to provide a foundation for future Fieldwork
students to recognize where more investigation is needed to understand and implement research
concerning the quality of the watershed, it also provides an opportunity for further interpretation
of its results. We know where the “holes” in student research topics exist, it is now important to
understand why and any particular events or attitudes which may have influenced such trends.
16 Works Cited
Cline, Sarah A., and Alan R. Collins, (2003). Watershed associations in West Virginia: their
impact on environmental protection. Journal of Environmental Management. 67, pp. 373383.
Dog River Clearwater Revival [online]. (2013). Available from: <http://dogriver.org/our-urbanwatershed>. [Accessed 25 February 2013].
Dog River Watershed [online]. (2012). Available from: <http://dogriver.southalabama.edu>.
[Accessed 03 February 2013].
Donahue, Timothy P., Lisa Bryce Lewis, Lawrence F. Price, and David C Schmidt, (1998).
Bringing science to life through community-based watershed education. Journal of
Science Education and Technology. 7, pp. 15-23.
Elfin, James, and Amy L. Sheaffer, (2007). Service-learning in watershed-based initiatives: keys
to education for sustainability in geography? Journal of Geography. 105, pp. 33-44.
Haury, D.L., (2000). Watersheds: a confluence of important ideas. Columbus, OH: ERIC
Clearinghouse for Science Mathematics and Environmental Education.
Kent, Martin, David D. Gilbertson, and Chris O. Hunt, (1997). Fieldwork in geography teaching:
a critical review of the literature and approaches. Journal of Geography in Higher
Education. 21, pp. 313-332.
Sawyer, Carol F. (2007). Frost heaving and surface clast movement in turf-banked terraces,
Eastern Glacier National Park, Montana. ETD Collection for Texas State University.
https://digital.library.txstate.edu/handle/10877/4295.
Sawyer, Carol F., and David R. Butler, (2006). A chronology of high-magnitude snow
avalanches reconstructed from archived newspapers. Disaster Prevention and
Management. 15, pp. 313-324.
Schmidt, P., and T.H. Morrison, (2012). Watershed management in an urban setting: process,
scale and administration. Land Use Policy. 29, pp. 45-52.
Shepardson, Daniel P., Bryan Wee, Michelle Priddy, Lauren Schellenberger, Jon Harbor, (2007).
What is a watershed? Implications of student conceptions for environmental science
education and the national science education standards. Science Education. 91, pp. 554578.
Potyonde, John P. and Theodore W. Geier (2011). Watershed condition classification technical
guide. Washington, D.C.: U.S. Department of Agriculture. pp. 5-6.
17 Wagner, Mayke, Pavel Tarasov, Dominic Hosner, Andreas Fleck, Richard Ehrich, Xiaocheng
Chen, Christian Leipe, (2013). Mapping of the spatial and temporal distributon of
archaeological sites of northern China during the neolithic and bronze age. Quaternary
International. 290-291, pp. 344-357.
Zhang, N., Z.C. Zheng, and Saikiran Yadagiri, (2011). A hydrodynamic simulation for the
circulation and transport in coastal watersheds. Computers and Fluids. 47, pp. 178-188.
18