© 2015 charles patrick nealis
TRANSCRIPT
MANAGING EXPECTATIONS: CREATING A COMMUNITY BASED STORMWATER POND NUTRIENT MANAGEMENT PROGRAM
By
CHARLES PATRICK NEALIS
A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT
OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY
UNIVERSITY OF FLORIDA
2015
© 2015 Charles Patrick Nealis
To Mr. Larry McFall; for inspiring my passion for science, love of teaching, and appreciation of Fleetwood Mac and B&B, and to my daughter, Evelyn, whom I hope to
inspire the same appreciation of science
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ACKNOWLEDGMENTS
This research was made possible through essential funding from the Tampa Bay
Environmental Fund and the University of Florida Water Institute. Additional support
was provided from Lakewood Ranch and the University of Florida Soil and Water
Science Department. The financial, physical and technical contributions were essential
for the success of this research project.
I would like to thank the community of Lakewood Ranch, Florida, for allowing me
to conduct my research in their back yards. Additionally, I’d like to thank Ryan Heise for
his continued support and guidance working in Lakewood Ranch and his willingness to
explore new options for creating a more environmentally friendly development. I had
additional incredible support from interested community members, Mike, Tracy, and
Emily Ott and I am extremely grateful for your contributions. I’d also like to thank those
who helped me sample in the field. It was an arduous task, but without the help of
Jackson Nealis, Katie Nealis, Kaylie Nealis, Adrian Hughes, Shannon Duffy, Ben
Hughes, Grant Weinkam, Wesley Henson, Mary Beth Litrico, and Brenhan Street, I
would have been stuck rowing circles a stormwater pond and talking to myself for days.
I also would like to thank my advisors and committee members, Dr. Mark Clark,
Dr. Paul Monaghan, Dr. George Hochmuth, and Dr. Kathryn Frank. Dr. Clark has been
a pillar of support through my academic journey, providing knowledge, technical advice
and enjoyable conversation ever since he took a chance on me and offered me an
opportunity to work on my PhD at the University of Florida. I’m eternally thankful for the
mentor he became. Additionally, Dr. Monaghan has been a constant presence and
beacon of insight into the social needs of physical science. His work inspired this project
and his continuing support has been irreplaceable. Dr. Hochmuth and Dr. Frank have
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provided outstanding support and knowledge throughout my studies, and their classes
have served as inspirations for a true interdisciplinary research project. Thank you all.
I would also like to acknowledge the tremendous help provided by Mike Sisk and
James Coley. Mike continuously provided support and advice from day one and was an
incredible help through any challenge. James provided irreplaceable help with statistical
analysis and review. This work would not have been completed if not for both of their
assistance.
Finally, I would like offer my greatest thanks to my friends and family. Without the
inspirational support, love and encouragement from my wife, daughter, brothers,
parents, extended family and friends I wouldn’t be have made it through with my sanity
intact. My wife, Jennifer, has been my inspiration of strength, positivity and
perseverance, no matter what I face. Thank you Jenn, Evelyn, Mom, Dad, Jackson,
Jake, Rose, Ben, Nick, Kiley, Grant, Brian, Dennis, Mary Beth, Soko, Chris and Dom for
everything.
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TABLE OF CONTENTS page
ACKNOWLEDGMENTS .................................................................................................. 4
LIST OF TABLES ............................................................................................................ 8
LIST OF FIGURES .......................................................................................................... 9
WORKING DEFINITIONS ............................................................................................. 11
ABSTRACT ................................................................................................................... 12
CHAPTER
1 WATERFRONT WARS AND THE NEED FOR INTERVENTION ........................... 14
The Growing Conflict .............................................................................................. 14 The Impact of Nutrients on Surface Water Resources ............................................ 16
Increase of Nutrients in Surface Waters and Urban Land Use ......................... 17 Role of Nutrients in Surface Water Impairment ................................................ 20
Algae .......................................................................................................... 20 Nutrients..................................................................................................... 22 Urban surface waters ................................................................................. 25
Regulatory Framework Protecting Water Resources .............................................. 26 Clean Water Act ............................................................................................... 27 Florida’s Stormwater Management ................................................................... 28 Water Quality Standards .................................................................................. 30 Local Ordinances and Restrictions ................................................................... 33
Reducing Non-Point Source Nutrient Pollution Using Stormwater Ponds ............... 35 Regulatory Requirements ................................................................................. 36 Social Expectations .......................................................................................... 41
Location Description ............................................................................................... 42 Research Objectives and Hypotheses .................................................................... 44
2 NUTRIENT-ALGAL RESPONSE RELATIONSHIPS IN STORMWATER PONDS . 50
Introduction ............................................................................................................. 50 Methods .................................................................................................................. 52 Results and Discussion........................................................................................... 54 Conclusion .............................................................................................................. 58
3 IDENTIFYING SIGNIFICANT FACTORS INFLUENCING STORMWATER POND NUTRIENT AND ALGAE CONCENTRATIONS .......................................... 68
Introduction ............................................................................................................. 68 Methods .................................................................................................................. 72
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Results and Discussion........................................................................................... 74 Conclusion .............................................................................................................. 82
4 CREATING A COMMUNITY-BASED CHLOROPHYLL-A THRESHOLD FOR STORMWATER PONDS ........................................................................................ 89
Introduction ............................................................................................................. 89 Methods .................................................................................................................. 91 Results and Discussion........................................................................................... 94
Identified Mean Treatment Thresholds ............................................................. 94 Impact of Pond Use on Mean Treatment Threshold ......................................... 96 Knowledge and Educational Influence on Mean Treatment Threshold ............ 99 Demographic Drivers of Mean Treatment Threshold ...................................... 103
Conclusion ............................................................................................................ 105
5 METHODS FOR IDENTIFYING AND QUANTIFYING IMPACT OF NUMERIC THRESHOLD IN STORMWATER PONDS ........................................................... 115
Introduction ........................................................................................................... 115 Methods ................................................................................................................ 117
Nutrient Management Threshold .................................................................... 117 Nutrient Assimilation Potential ........................................................................ 118
Results and Discussion......................................................................................... 119 Nutrient Management Threshold .................................................................... 119 Nutrient Assimilation Potential ........................................................................ 121
Conclusion ............................................................................................................ 122
6 CONCLUSION ...................................................................................................... 130
Findings ................................................................................................................ 130 Future Research Implications ............................................................................... 135
APPENDIX: COMMUNITY-BASED STORMWATER POND MANAGEMENT SURVEY ............................................................................................................... 139
LIST OF REFERENCES ............................................................................................. 161
BIOGRAPHICAL SKETCH .......................................................................................... 180
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LIST OF TABLES
Table page 1-1 EPA Approved Numeric Criteria for Florida’s Lakes ........................................... 49
2-1 Mean, median, standard error, and minimum and maximum values for total phosphorus, total nitrogen and chlorophyll-a concentrations in stormwater ponds compared to Numeric Nutrient Criteria..................................................... 60
2-2 Empirical models and summary statistics describing the association of monthly average nutrient and chlorophyll concentrations using data from stormwater ponds in a southwest Florida community and Florida Lakes ............ 61
3-1 Management and landscaping variables evaluated for significance as predictors of total phosphorus, total nitrogen and chlorophyll-a concentrations in stormwater ponds. .......................................................................................... 83
3-2 Empirical models and summary statistics describing the association of nutrient and chlorophyll concentrations using significant management and landscaping predictors from stormwater ponds in southwest Florida ................. 85
3-3 Summary statistics for significant predictor variables of total phosphorus, total nitrogen and chlorophyll-a stormwater pond models in southwest Florida .. 86
4-1 Demographic survey questions and responses with no significant difference in mean treatment threshold between responses ............................................. 107
5-1 Empirical models and summary statistics describing the association of monthly average nutrient and chlorophyll concentrations and median percent algal assimilated phosphorus or nitrogen using data from stormwater ponds .. 124
5-2 Quadratic models and summary statistics describing the association of monthly average nutrient and chlorophyll concentrations and algal assimilated phosphorus or nitrogen associated with the identified threshold ... 124
5-3 Florida’s Numeric Nutrient Criteria and the stormwater pond nutrient management criteria established for a residential community in southwest Florida. ............................................................................................................. 125
5-4 Summary statistics describing the estimated assimilated algal phosphorus (AAP) and assimilated algal nitrogen (AAN) for clear and colored stormwater ponds for a residential community in southwest Florida. .................................. 125
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LIST OF FIGURES
Figure page 1-1 Stormwater pond interactions and drivers .......................................................... 49
2-1 Location of 36 stormwater ponds sampled ......................................................... 62
2-2 Regression analysis between annual geometric mean chlorophyll-a concentration and annual geometric TP concentration in clear Florida lakes clear stormwater ponds in southwest Florida...................................................... 63
2-3 Regression analysis between annual geometric mean chlorophyll-a concentration and annual geometric TP concentration in colored Florida lakes compared to colored stormwater ponds in southwest FL ......................... 64
2-4 Regression analysis between annual geometric mean chlorophyll-a concentration and annual geometric TP concentration in West Central Peninsular Region colored, Florida lakes compared to colored stormwater ponds located in the same region ....................................................................... 65
2-5 Regression analysis between annual geometric mean chlorophyll-a concentration and annual geometric TN concentration in clear Florida lakes compared to clear stormwater ponds in southwest FL ....................................... 66
2-6 Regression analysis between annual geometric mean chlorophyll-a concentration and annual geometric TN concentration in colored Florida lakes compared to colored stormwater ponds in southwest FL .......................... 67
3-1 Variables identified as significant predictors of phosphorus, nitrogen and chlorophyll-a concentrations in stormwater ponds .............................................. 88
4-1 Series of ten photos depicting water column chlorophyll-a concentrations increasing in increments of five from 5 µg·L-1 to 50 µg·L-1 over a sandy bottom including submerged aquatic vegetation............................................... 108
4-2 Series of ten photos depicting water column chlorophyll-a concentrations increasing in increments of five from 5 µg·L-1 to 50 µg·L-1 over a sandy bottom. ............................................................................................................. 108
4-3 Comparison of mean chlorophyll-a concentration (µg·L-1) response of four survey treatments ............................................................................................. 109
4-4 Comparison of mean treatment threshold based on pond use ......................... 110
4-5 Comparison of mean treatment threshold associated with knowledge of stormwater pond origin ..................................................................................... 111
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4-6 Comparison of mean treatment threshold associated with stormwater pond education and awareness ................................................................................. 112
4-7 Mean treatment threshold associated with resident perceptions of algae function in stormwater ponds ............................................................................ 113
4-8 Comparison of mean treatment threshold associated with demographic information ........................................................................................................ 114
5-1 Models displaying treatment threshold and numeric phosphorus values with associated algal phosphorus assimilation values. ............................................ 126
5-2 Models displaying treatment threshold and numeric nitrogen values with associated algal nitrogen assimilation values. .................................................. 127
5-3 Estimated algal assimilated phosphorus (AAP g·m-3) in stormwater ponds at chlorophyll-a concentrations from 5 to 30 µg·L-1............................................... 128
5-4 Estimated algal assimilated nitrogen (AAN, g·m-3) in stormwater ponds at chlorophyll-a concentrations from 5 to 30 µg·L-1............................................... 129
6-1 Variables identified as significant predictors of phosphorus, nitrogen and chlorophyll-a concentrations in stormwater ponds ............................................ 138
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WORKING DEFINITIONS
Designated Use
State of Florida policy defined uses of a water body with specific protective criteria for water quality.
Impaired Waters that do not meet protective water quality standards for the designated use (United States Environmental Protection Agency, 2013).
Non-point source
Any source of water pollution not legally defined as point source in the Clean Water Act, including-but not limited to- runoff from land caused by precipitation and/or irrigation, atmospheric deposition, drainage, and seepage (Davis & McCuen, 2005; United States Environmental Protection Agency, 2012).
Point source “Any discernible, confined and discrete conveyance, including but not limited to any pipe, ditch, channel, tunnel, conduit, well, discrete fissure, container, rolling stock, concentrated animal feeding operation, or vessel or other floating craft, from which pollutants are or may be discharged. This term does not include agricultural stormwater discharges and return flows from irrigated agriculture.” (33 U.S.C. 1251 et seq., p. 214)
Stormwater Storm water, snow melt, and surface water runoff and drainage (40 C.F.R. § 122.26(b)(13)).
Total Maximum Daily Load (TMDL)
The Total Maximum Daily Load (TMDL) Program, instituted by the United States Environmental Protection Agency (EPA), requires a state to identify its impaired water bodies, develop a total maximum daily load necessary to eliminate the impairment in each water body, and then enact each plan throughout the state (United States Environmental Protection Agency, 2013)
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Abstract of Dissertation Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy
MANAGING EXPECTATIONS: CREATING A COMMUNITY BASED STORMWATER
POND NUTRIENT MANAGEMENT PROGRAM
By
Charles Patrick Nealis
December 2015
Chair: Mark Clark Major: Soil and Water Science
Degradation of surface waters is a critical concern in the state of Florida.
Regulatory frameworks and best management practices (BMPs) exist to protect the
designated uses of natural surface waters and reduce the impact of runoff from
upstream activity. Stormwater ponds (SWPs) are an increasingly popular BMP in
residential developments and are assumed to remove at least 80% of the nutrient load
from the contributing watershed to meet regulatory requirements. Residential SWPs
also generate a property value premium by creating “waterfront” property with social
expectations related to aesthetics and recreational value. The management of SWPs to
meet social expectations often includes the removal of biological responses to
increased nutrient concentrations, resulting in a reduction of the nutrient removal
efficiencies and failure to meet regulatory requirements. In this study, a method was
developed to quantify social expectations of SWPs and define numeric nutrient criteria
required to meet social demands and regulatory criteria. Nutrient and chlorophyll-a
water column concentrations in SWPs within a southwest Florida community were
sampled and significant nutrient-response relationships were established for clear and
colored systems. The SWP nutrient-response relationships were compared to those
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established for Florida’s numeric nutrient criteria for natural lakes and found to be
weaker but significantly different. To quantify social expectation criteria, a web-based
survey was created to identify thresholds of impairment based on water column
chlorophyll-a concentrations. Results indicated mean community-based thresholds
range from 20-30 µg·l-1. Preferred thresholds were found to increase with frequency of
use for recreational activities and respondents who correctly identified the role of algae
in SWPs had significantly greater thresholds than those who did not. Age, seasonality of
residence, sex and presence of children in the household were also found to have a
significant impact on preferred thresholds. Based on the identified community-based
thresholds and nutrient-response relationships, SWP numeric nutrient criteria were
established and the potential impacts were estimated. The findings and methods
identified in this study indicate the significant potential to effectively meet regulatory
requirements and social expectations of SWPs, improving management practices and
reducing downstream impacts of runoff from residential development.
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CHAPTER 1 WATERFRONT WARS AND THE NEED FOR INTERVENTION
The Growing Conflict
Florida’s climate, location and natural attractions have long been a powerful draw
for visitors and transplant residents. The attraction has led to Florida recently becoming
the third most populous state in the United States with a population of 19.9 million
people, increasing at over 800 new residents per day (United States Census Bureau,
2014). Florida continues to be a popular tourist destination as well, hosting a record
high 94.7 million visitors in 2013 (Jackovics, 2014). Growth has come with a cost,
greatly straining the state’s natural resources as an estimated 10,000 acres per year are
converted to residential, industrial, commercial and infrastructural development to meet
the demands of an increasing population (Francesconi & Stein, 2008). Accordingly,
overall freshwater use has increased and public water use has become the largest
consumer, surpassing agriculture in 2010 and demanding 2.3 billion gallons per day and
expected to escalate significantly with increased population growth and demand (Florida
Department of Environmental Protection, 2014).
As water use and land development have increased, an increasing number of
Florida’s fresh and salt water resources have been negatively impacted by nutrient
runoff from activities in the watershed. Identifying and preventing pollution from the
many nonpoint sources has been extremely difficult and protective policies and
practices have been implemented on a variety of scales and with varying success.
National, state and local regulatory programs attempt to identify and control polluted
runoff while new practices are implemented in design and management of current and
future development, creating an amalgam of protective policies in an attempt to ensure
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environmental integrity and prevent further degradation. Urban stormwater runoff is a
major source of nutrient pollutants to surface water bodies in Florida (Livingston &
McCarron, 1992; Roach, et al., 2008) and stormwater management provides one
promising avenue for effectively addressing nonpoint source pollution (Roy, et al.,
2008).
Unfortunately, numerous gaps often exist between policy planning,
understanding and management when individuals and communities make decisions
regarding nutrient reduction, resulting in conflict between individual expectations,
regulatory requirements and environmental protection. The dispute between the
protection of Florida’s surface water quality and the protection of individuals’ property
values, aesthetics and expectations has created a “Waterfront War” between residents
and often unintentional environmental impacts. Stormwater ponds represent the
epicenter of the struggle to balance development and the environment. The interactions
and drivers of stormwater pond function are summarized in Figure 1-1 and described in
the following sections of this chapter.
Originally, stormwater ponds were utilized as a regulated stormwater
management strategy designed and assumed to protect natural ecosystems by
mitigating the impact of activities within the watershed on downstream water quantity
and quality (Anderson, Watt, & Marsalek, 2002; Roy, et al., 2008). Currently, however,
stormwater ponds are increasingly integrated into low-relief areas of developments as
landscape features (Collins, et al., 2010; Schueler T. , 1997) and maintained for their
aesthetic, recreational and economic value to community stakeholders (DeLorenzo,
Thompson, Cooper, Moore, & Fulton, 2012; Serrano & DeLorenzo, 2008). The intended
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design and function of stormwater ponds to protect downstream, natural systems by
reducing runoff pollution rarely coincide with stakeholder expectations as communities
manage the stormwater ponds for aesthetic values. In addition, evaluation of
conventional stormwater pond design criteria indicate that nutrient load reduction
expectations are not being met and that source controls, pretreatment strategies and
alternative pond management strategies are needed (Harper & Baker, 2007). As more
natural surface water bodies are impaired by nutrients, identifying opportunities to
improve effectiveness of existing infrastructure and adoption of new practices will be
required. Creating a management regime to better address the dual function of
stormwater ponds as a nutrient reduction strategy and aesthetic, community asset is
essential to identifying compatible practices and ensuring the adoption and
effectiveness of more environmentally friendly and sustainable ideals.
The Impact of Nutrients on Surface Water Resources
Freshwater resource degraded by human-induced eutrophication in the United
States has led to annual economic losses in recreational water use, property value,
endangered and threatened species recovery and drinking water estimated at more
than 2.2 billion dollars (Dodds, et al., 2009). Nutrient loss from anthropogenic activities
contribute greatly to freshwater resource degradation as 90% of the rivers in 12 of the
14 ecoregions in the United States contain excess phosphorous (3 times higher) and
nitrogen (5.5 times higher) compared to established reference levels (Dodds, et al.,
2009). Florida, a state long known for and dependent upon its water resources,
currently faces severe resource degradation due to water scarcity, water quality
degradation and natural ecosystem loss (Mustafa, Smucker, Ginn, Johns, & Connely,
2010).
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Florida’s natural resources have long been affected by the growing demand of
anthropogenic activity within the state. Florida has experienced substantial losses of
natural habitat to human activity and development since 1935, losing 22% of the natural
forest cover and 51% of the natural marsh area while increasing agricultural areas 60%
and urban areas 632% (Mustafa, Smucker, Ginn, Johns, & Connely, 2010). Florida’s
remaining natural areas, including hundreds of miles of coastline and rivers, continue to
be increasingly impacted by nutrient loading from further population growth and
development.
Increase of Nutrients in Surface Waters and Urban Land Use
Development in urban and suburban areas of Florida has led to increased
nonpoint source runoff and nutrient loading to surface water resources (Dauer,
Weosnerg, & Rannasinghe, 2000; Osborne & Wiley, 1988). Development and
conversion of lands to urban and residential areas reduces infiltration and increases the
overland transport of nitrogen and phosphorus to surface waters (Paul & Meyer, 2001;
Walsh, Fletcher, & Ladson, 2005). These nutrients are the primary cause of water
quality impairment in Florida (United States Environmental Protection Agency, 2014)
and upland, nonpoint sources representing the primary contributor of phosphorus to
freshwater systems (Sharpley, et al., 1994; Daniel, Sharpley, Edwards, Wedepohl, &
Lemunyon, 1994).
The process of converting natural and agricultural landscapes to urban and
residential areas has had a significant impact on nutrient loading to downstream
environments. Construction and runoff associated with development can produce high
sediment loads in urban watersheds, carrying a multitude of potential pollutants into
surface water bodies (Schueler & Simpson, 2004). Runoff and sediment nutrient
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concentrations are closely related to land use and management (Graves, Wan, & Fike,
2004) and conversion of agricultural land to residential land use can result in the
mobilization of large amounts of legacy soil phosphorus (Daniel, Sharpley, Edwards,
Wedepohl, & Lemunyon, 1994; Sharpley, et al., 1994).
Following the conversion into residential land use, the application of additional
landscape fertilizer can further increases the potential phosphorus runoff to aquatic
systems like ponds, streams and lakes (Fluck, Fonyo, & Flaig, 1992; United States
Environmental Protection Agency, 1996). In addition to applied nutrient loss, dissolved
losses of soil phosphorus can be extremely high once the soil phosphorus absorption
capacity is exceeded (Sims, Simard, & Joern, 1998). Unfortunately for reasons of
awareness, negative environmental impacts resulting from phosphorus application and
accumulation in soils may not be expressed in downstream freshwater systems for
many years (Reed-Anderson, Carpenter, & Lathrop, 2000). Water quality problems and
changes in aquatic ecosystem productivity may appear abruptly once an assimilation
threshold in the system is surpassed (Heckrath, Brookes, Poulton, & Goulding, 1995).
Conversely, soil phosphorus accumulation and subsequent release can also cause lags
between management actions to control resulting water quality issues and achieving
desired results (Stigliani, et al., 1991).
Residential landscape preferences and management further increase nonpoint
source pollution to downstream water bodies once the landscape has been converted.
Intensely managed turfgrass lawns are a dominating feature in residential landscapes
and have been promoted and perceived as a source of individual and social good for
nearly 200 years (Downing A. , 1844; Fein, 1972; Schroeder F. , 1993) as the present
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idea of a perfect, ordered, and monoculture lawn is constantly marketed through
numerous media imagery outlets (Bormann & Balmori, 1993). Although turfgrass has
been criticized by many for its negative environmental impact, the management
decisions and resident actions associated with turfrass, not the turfgrass itself, may be
the defining culprit of downstream degradation.
Mismanagement of turfgrass can have tremendous negative impacts on the
environment. Studies have shown between 50 and 75% of households apply fertilizer to
their lawn (Carrico, Fraser, & Bazuin, 2013; Fissore, et al., 2011; Law, Band, & Grove,
2004; Robbins, Polderman, & Birkenholtz, 2001; United States Environmental
Protection Agency, 2004) and the high density and frequency of fertilizer applications by
individuals within an urban watershed will collectively contribute to increased nutrient
concentrations in urban surface water bodies (Serrano & DeLorenzo, 2008). Residents
personally caring for their lawn rarely receive training regarding application, storage,
handling and disposal of turfgrass chemicals, or education on the environmental
impacts of their use and decisions (Carrico, Fraser, & Bazuin, 2013). Fertilizing
turfgrass lawns at rates exceeding plant and soil requirements can lead to greater
nutrient loss and negative downstream environmental impacts (Fissore, et al., 2011;
Law, Band, & Grove, 2004; Trenholm, Unruh, & Sartain, 2012; Soldat & Petrovic, 2008).
Additionally, improper use of turfgrass fertilizer can lead to further loss of soil nutrients,
acidification of soils and surface water, accelerated loss of biodiversity, contaminated
resources and the release of nitrous oxide (Vitousek, et al., 1997).
Improper irrigation compounds nutrient runoff in residential areas, carrying nutrients
and other pollutants to downstream water bodies (Kjelgren, Farag, Neale, Endter-Wada,
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& Kurtzman, 2002) and stressing water resources through consumption and pollution
(Martin C. , 2001; Baker, Wilson, Fulton, & Horgan, 2008; Yabiku, Casagrande, &
Farley-Metzger, 2008; Milesi, et al., 2005). Typically, runoff from turfgrass landscaping
contains approximately 0.5-2.0 mg phosphorous and 3.0-5.0 mg nitrogen per liter
(Barten & Jahnke, 1997; Easton & Petrovic, 2004; Shuman, 2004; Waschbusch, Selbig,
& Bannerman, 1999) and is often distributed to stormwater ponds or natural
waterbodies via stormwater conveyance structures included during development. A
large volume of runoff containing nutrient concentrations of this level is capable of
causing eutrophication in any receiving water body, natural or created (Baker, Wilson,
Fulton, & Horgan, 2008).
Role of Nutrients in Surface Water Impairment
Excess enrichment of phosphorus and nitrogen in surface waters leads to
degradation through eutrophication, or the increasing supply of organic matter to the
system (Carpenter, et al., 1998). Degradation, identified as a change in integrity of the
natural system, species or use (Postel & Carpenter, 1997), leads to impairment of the
water body if it is found to be unsuitable for the assigned designated use (Florida
Administrative Code). Changes in benthic invertebrates, vascular plants, fish,
periphyton, and phytoplankton biomass/community structure are indicators of ecological
imbalance or impairment caused by increases in nutrient concentrations (Havens &
Schelske, 2001; Livingston R. , 2001; Kennish, 1999).
Algae
Increased algal growth is one of the most recognizable and adverse effects of
eutrophication in Florida surface waters. Phytoplankton communities may shift to bloom-
forming nuisance algae when water bodies are enriched with a limiting nutrient (Smith,
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1990) and the decomposition of the algae can cause oxygen depletion in the water
column, resulting in fish kills and nuisance complaints regarding aesthetics and odor
(Carpenter, et al., 1998; Smith, 1998). Some algal blooms can also produce toxins
(Lawton & Codd, 1991), eliminate native plants, and drastically diminish the biodiversity
of an aquatic ecosystem (Smith, 1998).
Chlorophyll-a is often used as a measure of the algal standing crop (Dillon &
Rigler, 1974) and is one of the most visible indicators of eutrophication in a surface
water body (Havens, 2003). In Florida, an algal bloom refers to chlorophyll a
concentrations greater than 40 µg·L-1 (Walker & Havens, 1995; Havens & Walker,
2002), a level also identified as a “severe nuisance” in other states (McGhee, 1983).
Concentrations of chlorophyll-a do not have to reach algal bloom levels to be
considered problematic as chlorophyll-a concentrations greater than 20 µg·L-1 have
been associated with nuisance or unwanted conditions (Heiskary & Walker, 1988;
Florida Department of Environmental Protection , 2012).
Managing and controlling algal blooms can be difficult as a lag often exists
between nutrient dose and algal response in aquatic systems, both in the near and long
term. Algal mass within an aquatic system is not immediately respondent to nutrient
enrichment as the algae requires time to uptake and incorporate nutrients into additional
biomass under influence of other environmental conditions (United States
Environmental Protection Agency, 2010). It is also extremely difficult to predict the
immediate and prolonged impact of management decisions reducing loads of nitrogen
and phosphorus to an aquatic ecosystem in an attempt to control eutrophication
(Jacoby & Frazer, 2009). Noticeable impairment of aquatic systems may appear long
22
after phosphorous accumulation in upstream soils, sediments and aquatic systems are
elevated enough to continue contributing phosphorus to the system for an extended
future amount of time (Bennett, Carpenter, & Caraco, 2001).
Nutrient runoff into lakes is highly influenced by climate (Florida Department of
Environmental Protection , 2012), but there are no consistent seasonal or wet and dry
period patterns in algal and chlorophyll a response to total nitrogen (TN) and total
phosphorous (TP) in Florida (United States Environmental Protection Agency, 2010).
Increasing trends of nutrient and chlorophyll a concentrations within the system are the
result of increasing external and/or internal loads of nutrients to the surface water body,
turnover time, and temperature and are exacerbated when loading exceeds internal,
biological assimilation processes and downstream export (Florida Department of
Environmental Protection , 2012).
Nutrients
The major nutrients required by aquatic organisms include carbon, oxygen,
hydrogen, nitrogen and phosphorus (Wetzel, 2001). Nitrogen and phosphorus most
often affect the primary productivity in freshwater systems, with one nutrient in excess
and the other considered limiting since its lack of availability inhibits increased growth
(Suplee, Watson, Varghese, & Cleland, 2008). The relationship of nitrogen to
phosphorus, or N:P ratio, most often determines the limiting nutrient controlling algal
growth in in freshwater lakes. Systems with an N:P ratio less than 7:1 are considered
nitrogen limited, systems with an N:P ratio greater than 20:1 are considered phosphorus
limited and systems with an N:P ration between 7:1 and 20:1 are considered co-limited
(Guildford & Hecky, 2000). Excess supply of limiting nutrients can cause increased algal
and/or macrophyte growth beyond the capacity of natural grazer control, leading to
23
undesirable and detrimental water quality including decreased water clarity and
dissolved oxygen levels (Florida Department of Environmental Protection , 2012).
Controlling or preventing eutrophication in freshwater systems usually focuses on
decreasing phosphorus inputs as it is often considered the limiting nutrient, but several
studies suggest nitrogen must be controlled as well (Schindler, et al., 2008; Conley, et
al., 2009), especially when considering downstream impacts of freshwater to saltwater
systems (Paerl, 2009). Algal response to increased phosphorus concentrations can be
reduced by alternative nutrient limitation (Canfield, 1983) and an over-abundance of
available phosphorus can lead to nitrogen limitation in freshwater systems (Schindler,
1971). The constraint on algal production by the synergistic interaction between
nitrogen and phosphorus, known as co-limitation, occurs often in freshwater lakes
(Harpole, et al., 2011; Maberly, King, Dent, Jones, & Gibson, 2002) so it is important to
reduce both nitrogen and phosphorus runoff to prevent eutrophication unless there is a
clear driver and defined limiting nutrient (Conley, et al., 2009).
The role of nitrogen in freshwater systems is often overlooked. Sole focus on
reducing nitrogen input to a water body does not reduce algal biomass within the water
body (Smith & Schindler, 2009; Schindler, et al., 2008), but nitrogen concentration in
runoff from residential land uses is a significant concern. Reducing nitrogen runoff is
important as nitrogen control within lakes can be expensive and unnecessary due to the
presence of nitrogen fixing cyanobacteria (Schindler & Hecky, 2009) that can bloom
when phosphorus is abundant and nitrogen becomes the limiting nutrient (Conley, et al.,
2009). Additionally, results from a study by Paerl et al (2004), suggest both nitrogen and
phosphorus reductions may be needed in freshwater systems when the freshwater
24
system is connected to estuarine/marine systems where nitrogen is the limiting nutrient.
Nitrogen in the inorganic form is the most soluble and readily assimilated form of
nitrogen and runoff from residential land use has a greater fraction of inorganic nitrogen
(18%) than runoff from other urban land uses (11%) (Graves, Wan, & Fike, 2004).
Nitrogen has a positive, predictive relationship with chlorophyll-a in freshwater lakes and
protective criteria have been established for nitrogen concentrations (Florida
Department of Environmental Protection , 2012).
Algal production in most freshwater ponds and lakes, however, depends on
phosphorus input as phosphorus is usually the limiting nutrient (Schindler, 1977;
Schindler, 1974). Total phosphorus (TP) concentration is an indicator of trophic state in
natural, freshwater lake systems (Dillon, 1975) and can be used as an indicator of algal
population densities measured by the chlorophyll-a concentration (Jones & Bachmann,
1976). The relationship between chlorophyll a and TP is significantly positive in Florida
(Canfield, 1983; Mazumder & Havens, 1998), but caution must be practiced in
predicting algal response as chlorophyll-a per unit TP can be reduced by zooplankton
grazing (Mazumder, 1994), abiotic turbidity (Phlips, et al., 1997) and nitrogen limitation
(Canfield, 1983). Water color may also suppress the TP/chlorophyll a relationship as
color reduces light penetration in the water column (Havens, 2003). Additionally, not all
phosphorus in a freshwater system is available to contribute to algal growth. Only
dissolved inorganic phosphorus is considered immediately bioavailable while organic
and particulate forms must usually undergo transformations to inorganic forms before
becoming bioavailable (Reddy, Kadlec, Flaig, & Gale, 1999). Available phosphorus can
also become unavailable in aquatic systems through complexation with dissolved
25
organic material (Jackson & Hecky, 1980), precipitation and assimilation into particulate
matter by plants (Reddy & DeLaune, 2008).
Urban surface waters
Lakes in urban and developed residential settings tend to receive higher nutrient
loads from stormwater runoff than lakes in non-urban settings (Schueler & Simpson,
2004). Upland residential fertilizer application, activity and erosion can be considerable
contributors of phosphorus and nitrogen to lake systems (Carpenter, et al., 1998; Law,
Band, & Grove, 2004; Gaddis, Vladich, & Voinov, 2007; Groffman, Law, Belt, Band, &
Fisher, 2004; Strynchuk, Royal, & England, 1999). Soil particles eroded into lakes or
ponds are also an important contributor of phosphorus (Daniel, Sharpley, Edwards,
Wedepohl, & Lemunyon, 1994; Sharpley, et al., 1994), especially during large rain
events (Pionke, Gburek, Sharpley, & Zollweg, 1997). Overall surface water runoff from
all activities in residential land use areas has been reported to have a typical TP
concentration ranging from 0.22 to 0.52 mg·L-1 and total nitrogen (TN) concentrations
ranging from 1.61 to 2.32 mg·L-1 (Graves, Wan, & Fike, 2004; Harper & Baker, 2007).
External nutrient loading is not the only source of phosphorus within lakes and ponds;
however, when reducing external phosphorus loading does not reduce eutrophication it
is often due to internal loading from sediments in the lake or pond (Schindler & Hecky,
2009). In addition to release from the sediment, urban lakes have several other unique
internal phosphorus sources, including waterfowl and recreation activity (Schueler &
Simpson, 2004).
Many of the current nutrient reduction strategies and regulations focus on
reducing nonpoint source pollution, or stormwater runoff, from urban sources through
design and assumed compliance. The inclusion of stormwater ponds and other nutrient
26
sinks in the landscape design can help reduce nutrient runoff from reaching natural
aquatic systems (Novotny & Olem, 1994; Soranno, Hubler, Carpenter, & Lathrop, 1996)
but the actual nutrient removal efficiencies do not currently meet regulatory
requirements (Harper & Baker, 2007). Incorporating more efficient nutrient application
and better landscape management practices in upland systems can reduce downstream
eutrophication (Bennett, Carpenter, & Caraco, 2001) and may also help improve design
removal efficiencies. New strategies incorporating both source control and treatment
practices must be researched, developed and implemented to better meet regulatory
requirements and downstream protection.
Regulatory Framework Protecting Water Resources
Improving water quality protective practices requires a clear understanding of the
current regulatory framework protecting water resources. Water resource management
in the United States is often handled independently by different agencies and
stakeholders in response to a problematic pollutant, polluter or sensitive landscape
feature following public outcry stemming from the failure of a water resource to meet a
certain perceived societal need or expectation that has never been fully vetted with a
comprehensive set of social values (Sabatier, et al., 2005). The resulting strategies are
often controversial, limited in scope and focused on physical manipulation as a solution
to water resource problems as opposed to source control and preventative strategies
(Gleick, 2000). Over time, policy and associated regulations have integrated more
collaborative approaches to address water resources issues and engage stakeholders
to improve program success. The scale of regulation and management, from federal law
to community codes and covenants, are all important in establishing an effective
foundation protecting water resources.
27
Clean Water Act
The Federal Clean Water Act, established in 1972, is the foundation for
supporting the protection of water quality in Florida. The Federal Clean Water Act
requires states adopt water quality criteria to protect the designated uses of surface
waters based on sound scientific rationale and federal, state, municipal and industrial
entities to investigate, develop and enact programs protecting water bodies and
preventing, reducing or eliminating pollution (33 U.S.C. 1251 et seq.). The Clean Water
Act provided greater clarity and enforcement than prior regulations by requiring permits
for point sources discharging pollutants into water bodies through the National Pollutant
Discharge Elimination System (NPDES), protecting water quality, wildlife and
recreational use of navigable waters (33 U.S.C. 1251 et seq.; Davis & McCuen, 2005).
Runoff from activities within urban areas, including nutrients and contaminants from
landscaping and impervious surfaces, is considered non-point source pollution and is
not as easily identified or controlled as point sources.
Multiple phases of the NPDES have been implemented to reduce stormwater
impact on natural water bodies. Phase I of the NPDES required stormwater permits for
ten categories of industrial activities, construction discharge on five or more acres of
land, and municipal separate storm sewers (MS4s) discharge in medium and large
urban areas of 100,000 or more individuals (United States Environmental Protection
Agency, 2014b). Phase II expanded the stormwater permit requirement to smaller
construction site operators, MS4s in smaller urban areas, and MS4s outside of urban
areas designated by the permitting authority to obtain NPDES coverage (United States
Environmental Protection Agency, 2014b). Under Phase II of the NPDES and section
402(p)(3)B) of the Clean Water Act, stormwater pollutants must be reduced to the
28
maximum extent possible (33 U.S.C. 1251 et seq.). A Stormwater Management Plan
including six minimum control measures is required by Phase II applicants, identifying
public education and outreach, public participation and involvement, illicit discharge
detection and elimination, construction site runoff control, post-construction runoff
control and pollution prevention procedures (United States Environmental Protection
Agency, 2014b).
Florida’s Stormwater Management
In conjunction with the Clean Water Act and efforts to manage flooding, Florida
has implemented numerous measures to better manage and protect water quality.
Regulatory requirements and roles have evolved over several decades to improve the
management of stormwater runoff and implementation of protective practices in the
watershed.
The Water Resources Act of 1972 established a plan for regulating Florida’s
water resources and created five regional water management districts drawn on
hydrologic boundaries, localizing water management (Christaldi, 1996). The act directed
the Florida Department of Environmental Protection (FDEP) to delegate much of its
authority to the water management districts, giving them the power to manage regional
water resources and develop rules, procedures and policy for water resources within the
district (Christaldi, 1996). The Water Resources Act allowed for local administration of
state rules and regulations, creating state-level and regionally specific implementation of
planning and policy decisions (Christaldi, 1996).
Florida statute also required FDEP to protect water quality and FDEP delegated
the authority to do so to the five Florida water management districts (WMDs) (§373.403-
.469). The WMDs utilize environmental resource permits protective of Florida’s water
29
quality standards to exercise their authority. New and existing developments
contributing to violations of the water quality standards must provide reasonable,
documented assurance discharges will not violate state water quality standards to be
issued a permit (Rupert & Ankerson, 2008). No additional permits causing or
contributing to a water quality violation can be approved by the WMD if a waterbody is
currently in violation of state water quality standards (Rupert & Ankerson, 2008). WMDs
and FDEP also have the responsibility to manage and assign nutrient loads to sources
as part of the Total Maximum Daily Load (TMDL) process. FDEP has authority over the
TMDL program following the 1999 passage of the Florida Water Restoration Act
(Hueber, 2010) and is able to establish Basin Management Action Plans (BMAPs), or
basin specific strategies for reducing waterborne pollutants. Planning and
implementation of these plans are shared by FDEP and the water management districts
(Hueber, 2010).
The enforceable regulatory scheme of BMAP obligations of nonpoint sources
was important as it created an enforcement mechanism where no prior option existed,
but could be strengthened in respect to identifying violators and ensuring compliance.
BMAP program success and pollutant reduction can be improved through involvement
and cooperation of stakeholders in the development and implementation of the program
(Hueber, 2010). Specifically including BMPs in Conditions, Covenants and Restrictions
of homeowners associations (HOAs) and delegating enforcement rights to local
governments and WMDs could improve compliance and enforcement (Rupert &
Ankerson, 2008).
30
Water Quality Standards
Florida was the first state in the country to adopt a rule dictating a specified level
of stormwater pollutant load reduction. Florida’s performance standard required all new
developments following the 1972 Water Resources Act to reduce post-development
stormwater pollutant loading of total suspended solids (TSS) by at least 80% (Florida
Department of Environmental Protection, 2011). The 80% level of treatment was chosen
to create equal treatment requirements for point and nonpoint sources and set a
realistic goal as the cost of stormwater treatment increases tremendously with additional
treatment above 80% (Florida Department of Environmental Protection, 2011). The
State Water Resource Implementation Rule amended the expectation of stormwater
treatment in 1990 beyond TSS to include removal of 80% of all post-development
stormwater pollutants causing or contributing to water quality standard violations,
including nitrogen and phosphorus (Florida Department of Environmental Protection,
2011). Stormwater infrastructure design criteria and WMD permitting rules necessary to
meet the updated treatment requirement, however, have never been revised
accordingly despite the updated state and federal water quality regulation.
The stormwater rule relies upon a minimum level of treatment goal, a design
criteria for achieving established goals, a rebuttable presumption stormwater systems
following the design criteria will not harm water resources, and a periodic review and
update of the design criteria to ensure continual improvement and success (Florida
Department of Environmental Protection, 2011). The goal of resource preservation,
stormwater treatment, and pollution load reduction is established and legitimized in the
Water Resource Implementation Rule, chapter 62-40 of the Florida Administrative Code
(Harper & Baker, 2007; Florida Administrative Code ).
31
The Surface Water Quality Standards and minimum water quality levels
necessary to protect present and future most beneficial uses of waters are defined and
surface waters are classified in section 62-302 of the Florida Administrative Code
(Harper & Baker, 2007; Florida Administrative Code ). Water quality classifications are
listed in decreasing order of required protection from Class I to Class V, with Class I, II
and III surface waters including water quality criteria with recreational use considered
(Florida Administrative Code). Recreational use includes any activities providing value
as a resource for outdoor recreational activities, including fishing, boating and nature
observation (Florida Administrative Code). The designated uses of Florida’s surface
waters are:
• Class I Potable Water Supplies
• Class II Shellfish Propagation or Harvesting
• Class III Fish Consumption; Recreation, Propagation and Maintenance of a Healthy, Well-Balanced Population of Fish and Wildlife
• Class III-Limited Fish Consumption; Recreation or Limited Recreation; and/or Propagation and Maintenance of a Limited Population of Fish and Wildlife
• Class IV Agricultural Water Supplies
• Class V Navigation, Utility and Industrial Use (Florida Administrative Code)
Florida established a Narrative Nutrient Criteria in 1974 to protect the designated
uses of Class I and III surface waters (Obreza, et al., 2011; Florida Department of
Environmental Protection, 2015). The Narrative Nutrient Criteria identified impaired
surface waters, or those waters not providing their designated use, based on changes in
aquatic species compositions due to increased nutrients (Florida Administrative Code).
Surface waters would be identified as impaired if there was a detectable change in the
composition of aquatic species populations due to increased nutrients.
32
Recently, however, the United States Environmental Protection Agency (EPA)
determined Florida’s narrative criteria was not protective of water quality and numeric
standards were necessary to meet Clean Water Act requirements (Obreza, et al., 2011).
The EPA published numeric nutrient criteria (NNC) establishing numeric water quality
criteria for nutrients and response variables, including chlorophyll-a, interpreting
narrative criteria for Class I and III surface waters based upon FDEP research and
recommendations (Florida Department of Environmental Protection , 2012). The EPA
defined the NNC (Table 1-1) for an individual system based on several variables
influencing the relationship between chlorophyll-a concentration and the TP or TN
concentration. Chlorophyll-a values of 6 µg·L-1 for clear (≤40 Platinum Cobalt Units,
PCU), low alkalinity lakes and 20 µg·L-1 for colored (>40 PCU) and clear (≤40 PCU),
high alkalinity lakes were chosen as thresholds protective of designated uses based on
EPA guidance and the Impaired Waters Rule Technical Advisory Committee’s review
and revision of the Trophic State Index used in 1998 303(b) report (Florida Department
of Environmental Protection , 2012).
The NNC was designed to protect aquatic life, water quality, public health and
recreational uses of Florida waters from wastewater, urban stormwater runoff, and
excess fertilizer pollution from anthropogenic activities within the watershed (Florida
Department of Environmental Protection , 2012). Additionally, maintaining the numeric
criteria for an individual water body ensures attainment and maintenance of water
quality standards for downstream waters (Obreza, et al., 2011). Consistent with their
development, Florida’s numeric nutrient standards are expressed as annual geometric
33
means based on regular monitoring and cannot be exceeded more than once in a three
year period.
Even though the NNC established statewide standards, nutrient-response
concentrations and relationships in Florida are regionally diverse. Lakes located in the
West Central Peninsula Nutrient Watershed Region (WCPNWR) have been identified
as being potentially impacted by natural sources of phosphorous and variations in the
stressor-response variables have been noted. Colored lake systems in this region have
a region specific maximum TP limit of 0.49 mg·L-1 to protect downstream flowing waters
(United States Environmental Protection Agency, 2010). The increased TP threshold is
due to the lack of a strong relationship between TP and chlorophyll-a (r2=0.028;
p=0.315), as evaluated through a least squares regression analysis. Clear lake systems
in the WCPNWR, however, showed a strong and statistically significant relationship
between chlorophyll-a and TP (r2=0.45; p<0.001) as well as TN (r2=0.66; p<0.001), and
do not have a region specific limit (United States Environmental Protection Agency,
2010).
Local Ordinances and Restrictions
Ordinances, restrictions and policies implemented at the local level can also
contribute to water quality protection and maintenance of regional or statewide
requirements. Local Florida governments can regulate stormwater as long as the
regulatory program is not in conflict with state or federal laws (Rupert & Ankerson,
2008). Local stormwater regulations, monitoring and control can provide an avenue for
improving stormwater management by implementing zoning and planning initiatives
protective of water resources and providing infrastructure and community services to
reduce runoff pollution (Livingston E. , 1995).
34
For source control, county-wide fertilizer ordinances restricting residential
fertilizer use during the rainy season are common practice in several Florida counties
(Hochmuth, Nell, Unruh, Trenholm, & Sartain, 2012). Most county fertilizer ordinances
restrict application of nitrogen and phosphorus between June 1st and September 30th,
with additional restrictions of application during a severe weather warning or watch
(Manatee County, 2011; Hochmuth, Nell, Unruh, Trenholm, & Sartain, 2012).
Additionally, fertilizer ordinances can suggest nutrient application rates, identify areas
where fertilizer application is restricted, and recommend low maintenance or buffer
zones to aid in reducing nutrient runoff (Manatee County, 2011; Hochmuth, Nell, Unruh,
Trenholm, & Sartain, 2012).
Homeowners associations (HOAs) and Community Development Districts
(CDDs) also represent local entities capable of regulating stormwater management.
HOAs are generally responsible for operating and maintaining the stormwater
management system as they usually own and maintain the infrastructure and common
areas within a development or community (Rupert & Ankerson, 2008). Additionally,
HOAs often are the operation and maintenance permit holder for the stormwater system
in new residential developments and incorporate covenants, conditions and restrictions
(CCRs) to ensure the financial, legal and administrative capability of the HOA to
maintain the stormwater system in perpetuity (Rupert & Ankerson, 2008). Local
governments can enforce CCRs only if it properly imposes the related CCRs on a
development upon approval of a local stormwater permit, development of regional
impact or planned unit development proposal and cannot enforce private CCRs
unrelated to the local government’s regulatory authority (Rupert & Ankerson, 2008).
35
Either way, HOAs are often depended upon to monitor and enforce CCRs because local
governments commonly lack the resources to do so, but the local government can serve
as an important backstop should the HOA fail in their duties to enforce operation and
management conditions (Rupert & Ankerson, 2008).
CDDs represent another important organization with many of the same powers
as a local government, including the ability to levy and assess taxes and special
assessments within the district (Rupert & Ankerson, 2008). Unlike HOAs, they lack the
statutory authority to enforce CCRs unless the CDD holds the rights to easements
containing stormwater elements and language preventing adjacent property owners
from damaging or interfering with stormwater control elements within the easement
(Rupert & Ankerson, 2008). The CDDs assessment and taxing power can provide
incentive to better manage current stormwater issues as well as the means to collect
money necessary to maintain the operations and management of the stormwater
structures (Rupert & Ankerson, 2008).
Reducing Non-Point Source Nutrient Pollution Using Stormwater Ponds
Stormwater management is an important component of water quality protection
in Florida, especially with the recent and projected growth of urban and residential
areas. Effective stormwater management can serve several functions, from pollution
reduction, erosion control, and water storage to aesthetic and recreational enhancement
(Livingston & McCarron, 1992). Stormwater runoff flows and nutrient concentrations are
highly variable and difficult to predict (Davis & McCuen, 2005) and it is challenging to
effectively design and implement a stormwater management system fitting of the social
and regulatory needs (Schueler T. , 1995). Stormwater pollution management can
include structural or nonstructural controls managed and maintained at the state or local
36
level. Structural controls are physical practices employed to manage water volume and
peak discharge rate or contain or restrict stormwater flow to allow for treatment through
settling, filtration, chemical treatment or biological uptake (Livingston & McCarron,
1992). Nonstructural controls include land use planning, resource protection, education,
restrictions and/or practices implemented to prevent runoff pollution (Livingston &
McCarron, 1992).
The primary goal of urban stormwater management and stormwater pond
construction has historically been water volume control and flood prevention (Davis &
McCuen, 2005; Livingston & McCarron, 1992) but stormwater ponds are also
recognized for their benefit in protecting downstream ecosystems by mitigating the
impact of activities within the watershed on water quality and quantity (Anderson, Watt,
& Marsalek, 2002; Roy, et al., 2008). Stormwater ponds have been increasingly
integrated into developments and community design as landscape features (Collins, et
al., 2010), especially in low-relief areas like Florida where it is difficult to separate the
high groundwater table from the stormwater (Schueler T. , 1997). Managing ponds to
meet regulatory requirements and social expectations has led to difficulty in adequately
maintaining and enhancing stormwater pond performance, but a paradigm shift focused
on meeting requirements and expectations simultaneously may offer a sensible and
effective solution.
Regulatory Requirements
Although regulatory enforcement of the Stormwater Rule requirements has been
lax, the EPA’s TMDL program and Phase II of the Municipal Stormwater Sewer System
Program and NPDES permit for stormwater discharge have heightened recent focus on
non-point source runoff quality from urban landscapes (Baker, Wilson, Fulton, &
37
Horgan, 2008). A renewed focus on identifying, quantifying and reducing nutrient loads
from residential communities is imminent with the increasing quantity and severity of
impaired natural water bodies. The design and management of stormwater ponds
should be conducive of nutrient removal processes through physical (sedimentation),
chemical (precipitation and adsorption), and biological (uptake) mechanisms, and
stormwater ponds built to the state criteria are assumed to meet the required nutrient
removal efficiencies (Harper & Baker, 2007). As designed and managed, however, the
efficiency of stormwater ponds in reducing stormwater flow and retaining nutrients may
be less than what is expected by permit (Harper & Baker, 2007).
The nature of the techniques used for treating stormwater and the internal design
geometry of a stormwater pond are two very important factors influencing stormwater
pond performance (Scheuler, 1994). Stormwater ponds are generally categorized as
detention or retention ponds. Retention ponds discharge through infiltration and
groundwater transport and drain completely within twenty-four to seventy-two hours
(Vandiver & Hernandez, 2009; Livingston & McCarron, 1992). Infiltration utilizes the
natural nutrient removal capacities of soil and vegetation as water moves through the
soil profile, before it reaches groundwater or surface water (Ferguson, 1990). As
stormwater moves through the soil profile phosphorus and other contaminants tend to
accumulate in the upper soil layers, depending on organic matter content and soil
particle size, while nitrogen is reduced to N2 gas in the anaerobic soil layers (Brady &
Weil, 2008).
Detention ponds, or “wet” stormwater ponds, with a permanent volume of water
gradually discharge downstream through a designated overflow structure (Vandiver &
38
Hernandez, 2009; Livingston & McCarron, 1992). Stormwater detention pond
performance is usually assessed through total suspended solids levels and removal
(Olding, Steele, & Nemeth, 2004; Gharabaghi, et al., 2006), neglecting the role of
biogeochemical processes and fate of dissolved contaminants including nutrients
(Anderson, Watt, & Marsalek, 2002; Olding, Steele, & Nemeth, 2004; Collins, et al.,
2010; Downing J. , 2010). Stormwater pond biogeochemical characteristics are
relatively unknown, but they appear to be extremely productive and able to support
complex microbial communities and food webs (Chiandet & Xenopoulos, 2010;
Sommaruga, 1995; Sanchez, et al., 2011). Williams et al. (2013) report water chemistry
and phytoplankton biomass in stormwater ponds tend to be more variable than natural,
unimpacted systems (Chiandet & Xenopoulos, 2010), and more closely resemble
eutrophic lakes (Sommaruga, 1995; Sanchez, et al., 2011) and restored and natural
wetlands in anthropogenically impacted watersheds (Stewart & Downing, 2008; Hossler,
et al., 2011).
The existing microbial food webs and biogeochemical cycles are dependent on
water residence time within the stormwater pond and the external chemical input
quantity and quality (Sommaruga, 1995; Van Meter, Swan, & Snodgrass, 2011). Internal
cycling drives processes within the stormwater pond during dry periods while rainfall
can provide external inputs of nutrients from the watershed, influencing the water
column characteristics and turnover time within the pond (Olding, Steele, & Nemeth,
2004; Chiandet & Xenopoulos, 2010). Terrestrial connections to stormwater ponds may
be best reflected during periods of high rainfall and associated runoff (Williams, Frost, &
Xenopoulos, 2013).
39
Stormwater ponds are required by permit to mitigate for increased rates of runoff
volume and elevated pollutants associated with development. Structurally, wet
stormwater ponds must detain water for a minimum of 14 days, contain a littoral zone of
at least 30% of the pond area, and be no deeper than 10 feet below the control
elevation (Livingston E. , McCarron, Cox, & Sanzone, 1988). Stormwater ponds are
typically built to provide a 24-48 hour lag phase during a rain event, allowing total
suspended solids to settle before entering downstream water bodies (Olding, Steele, &
Nemeth, 2004; Gharabaghi, et al., 2006). Sediment accumulation can be rapid
(Downing, et al., 2008) and must be mitigated through periodic dredging to maintain
permitted storage capacity (Anderson, Watt, & Marsalek, 2002).
Pollutants in the stormwater pond system are removed from the water column
through biological uptake and/or sediment deposition (Novotny, 1995). The state
Stormwater Rule, Chapter 17-25 Florida Administrative Code, requires stormwater
systems to treat the first flush of stormwater and remove at least 80% of the annual
average pollutant load, with an increased treatment to 95% of the load if water is being
discharged to Outstanding Florida Waters (Livingston & McCarron, 1992). A study by
Harper and Baker (2007), however, demonstrated stormwater ponds are not meeting
the required removal efficiencies for TN and TP as currently designed and fail to meet
the 80% to 95% removal efficiencies required by the Florida Administrative Code. To
meet the required removal efficiencies, Harper and Baker (2007) suggest increasing
retention time and adding upstream mitigation to stormwater management plans to form
a treatment train reducing the overall load reaching natural water bodies.
40
Stormwater ponds that receive excess loading of nitrogen and phosphorus can
become eutrophic and experience algal blooms and excessive aquatic vegetation
growth. Vegetation type and coverage can increase the nutrient removal efficacy of
stormwater ponds (Mallin, Ensign, Wheeler, & Mayes, 2002) and represent an important
nutrient removal pathway within the pond (Harper & Baker, 2007). Littoral and pond
bank vegetation can also increase soil stabilization on the slopes around stormwater
ponds and decreases overland runoff velocity and associated soil erosion (Livingston &
McCarron, 1992; Arendt, 1996) and improve soil development and infiltration rates while
utilizing nutrients moving through the soil (Brady & Weil, 2008). Additionally, extensive
aquatic plant coverage may reduce the potential of undesirable phytoplankton blooms
(Richard & Small, 1984). Unfortunately, eutrophication can also impair the aesthetic
value and recreational use of the stormwater pond. Eutrophication results in decreased
water clarity, altered water column color, unwanted odor, and changes in ecological
community composition (Vitousek, et al., 1997; Xavier, Vale, & Vasconcelos, 2007;
Dokulil, Martin, & Teubner, 2003).
Eutrophication occurs naturally in lake systems and is often noted as a
consequence of the aging of a lake basin as they become less deep and more
biologically productive over time (Rodhe, 1969). Urban stormwater ponds can have
extremely high rates of internal nutrient processing (Downing, et al., 2008; Tranvik, et
al., 2009; Downing J. , 2010; Williams, Frost, & Xenopoulos, 2013) and may be subject
to accelerated eutrophication and aging due to the increased supply of nutrients and
sediments from the surrounding watershed and anthropogenic activities. Increased
plant and algae biomass within the stormwater pond leads to increased organic
41
sediment production, decreased storage volume and decreased dissolved oxygen from
the increased microbial degradation of organic matter (Wetzel, 2001). To maintain
volume requirements, stormwater ponds may need to be dredged periodically.
Social Expectations
Stormwater ponds in urban and residential settings are often marketed to meet
aesthetic and recreational expectations in addition to regulatory requirements.
Stormwater ponds are prominent landscape features in many communities and offer
aesthetic, recreational and economic value similar to natural lakes (DeLorenzo,
Thompson, Cooper, Moore, & Fulton, 2012; Serrano & DeLorenzo, 2008). Unlike
natural lakes, however, there are no water quality standards established for pond uses
and expectations are highly variable between homeowners. Often, maintaining the
social expectations of stormwater ponds is implemented by suppressing the biological
responses to increased nutrient loads instead of managing excess nutrients in the
watershed. Killing algae growth in the pond may achieve homeowner expectations of
the pond aesthetics but may compound the stormwater pond’s ability to meet the
required TN and TP removal efficiencies by eliminating an important biological nutrient
removal mechanism within the pond (Harper & Baker, 2007).
Stormwater ponds in residential and urban developments are often used for
recreational activities like fishing and boating by residents in the community (Serrano &
DeLorenzo, 2008). In natural lake systems, user water quality preference varies based
on their use of the system (Ditton & Goodale, 1973; Parsons & Kealy, 1992) and users
are willing to pay for management strategies protective of their desired use (Bockstael,
McConnell, & Strand, 1989). Residents in communities with stormwater ponds mirror
this willingness to pay and often employ lake management companies to chemically
42
treat algal blooms and remove nuisance vegetation resulting from nutrient loading and
eutrophic conditions.
Eutrophication causes unwanted changes that negatively affect aesthetic and
recreational uses of surface water bodies (Vitousek, et al., 1997; Xavier, Vale, &
Vasconcelos, 2007; Dokulil, Martin, & Teubner, 2003) and reduce the property value of
waterfront homes (Steinnes, 1992). Nutrient loading to aquatic systems has an
enormous economic price and includes declines in lakefront property value, fishing and
recreation loss, cost of biodiversity loss, and cost of water purification (Dodds, et al.,
2009). Stormwater ponds are designed and regulated to be nutrient sinks reducing the
impact of nutrient loading on downstream systems, but maintaining social expectations
of stormwater ponds shifts the concerns and costs of nutrient loading in natural systems
upstream to the stormwater pond. Unfortunately, chemical interventions eliminating
biological responses to increased nutrients artificially maintains stormwater pond
expectations and allows nutrients to bypass removal mechanisms in the stormwater
pond and enter downstream systems. To maintain regulatory nutrient reduction
requirements and social expectations of stormwater ponds, better management criteria
must be developed to identify thresholds of impairment and reduce upstream nutrient
loads.
Location Description
The Tampa Bay area is one of the fastest growing coastal urban centers in
Florida and population growth is leading to increased fresh water demand, development
and sprawl (Dorsey, 2010). Urban land use in the Tampa Bay watershed has more than
tripled since 1991 and accounts for approximately 27% of the total land area as more
than two million people now reside within the watershed (Xiang, Crane, & Su, 2007).
43
Coastal states are dramatically impacted by nonpoint source pollution from stormwater
runoff with more than sixty percent of rivers, estuaries and bays moderately to severely
degraded (National Research Council, 2000). Urban areas are significant contributors to
non-point source pollution (United States Environmental Protection Agency, 2009) and
residential areas within the Tampa Bay watershed are the primary source of nitrogen
pollution reaching Tampa Bay (Tampa Bay Estuary Program, 2006). Elevated nitrogen
levels in Tampa Bay, along with other nutrients and pollutants, can lead to loss of
seagrass beds, algal blooms and other negative environmental impacts (Tampa Bay
Estuary Program, 2006).
Landscaping practices and decisions have led to many of the nutrient loading
and water supply issues the Tampa Bay watershed experiences. Irrigation of lawns and
gardens accounts for more than 80% of the domestic water use in Florida (Johns, et al.,
2007) and lawns are maintained through extensive labor and chemical inputs. Turfgrass
lawns are extremely popular in the Tampa Bay watershed as a recent study indicated
nearly 70% of residents reported 25% or more of their property is completely covered in
turfgrass (Mustafa, Smucker, Ginn, Johns, & Connely, 2010). Despite the environmental
concerns present in the watershed, residents tend to be largely unaware of the impact
their landscaping decisions and runoff have on natural systems (Nielson & Smith,
2005). Piped water, specifically in the form of irrigation and stormwater management,
causes disconnect between people and the local environment (Malone, 1999; Hillman,
Brierley, & Fryirs, 2008).
This study was conducted in a large residential community within the Tampa Bay
watershed and West Central Peninsula Nutrient Watershed Region (Florida
44
Administrative Code, 2013). The community covers over 8,500 acres and has a growing
population of over 15,000 residents. The demographics of the community vary greatly
and range from working class, young families to affluent, retired, part-time residents.
Formerly a cattle ranch, the community now includes thousands of homes, over 300
stormwater ponds, multiple parks, several natural areas, and two golf courses.
Stormwater ponds are an important component of the community beyond water storage
and treatment capacities as they provide aesthetic, recreational and economic value to
residents and homeowners. Although many homeowners paid premiums to have
waterfront property on these stormwater ponds, many were unaware they were not
natural water bodies and do not understand their role in treating non-point source
nutrient runoff. Landscaping in the community is done by contracted lawn maintenance
companies or homeowners and there are strong expectations for lawns and
landscaping to be regularly maintained to meet aesthetic standards. Stormwater ponds
and common areas are managed by a single director of operations.
Runoff from the community eventually deposits into the Braden River which
contributes to the Manatee River and, ultimately, Tampa Bay. The Braden River
designated use is potable water supply and it is impaired for fecal coliforms, chlorophyll-
A, and dissolved oxygen (United States Environmental Protection Agency, 2013). A
TMDL for fecal coliforms was established in 2009 and the Braden River was impaired
for nutrients, fecal coliform, total suspended solids and dissolved oxygen in the
reporting year 2002.
Research Objectives and Hypotheses
Perceived value and community ownership of stormwater is necessary to identify
solutions to improve water quality (Winz, Brierley, & Trowsdale, 2011), therefore
45
stormwater ponds in residential areas represent an ideal focal point to evaluate
strategies that address both social and regulatory objectives. This research investigated
the use of a community-selected chlorophyll-a nutrient threshold to help align the social
and regulatory expectations of stormwater ponds. Following the FDEP Numeric Nutrient
Criteria model for natural lakes, chlorophyll-a thresholds were established based on
visual preferences deemed protective of desired aesthetic and recreational uses and
then used to identify nutrient criterion to maintain or improve the water condition (Florida
Department of Environmental Protection , 2012). Establishing stormwater pond water
quality goals and numeric nutrient criteria that could be used by community pond
managers would help guide upstream nutrient management programs, maintain the
social and regulatory functions of stormwater ponds, and help protect the designated
uses of natural, downstream waterbodies.
Empowering and entrusting community members to self-regulate landscaping
decisions in accordance with community aesthetic expectations may be the best
opportunity to minimize impact on natural systems. Since residents value stormwater
ponds like natural lake systems, utilizing similar management strategies to protect
designated uses could allow stormwater ponds to better meet regulatory requirements
and aesthetic expectations with minimal use of algaecides and herbicides. Developing
acceptable nutrient criteria for stormwater ponds would provide a framework for better
management of nonpoint source pollution and stormwater while ensuring better
protection for downstream water bodies. Understanding the physicochemical
environmental and biogeochemical mechanisms controlling the quality and clarity of
water within and released from stormwater ponds could improve the management,
46
performance and sustainability of the system (Williams, Frost, & Xenopoulos, 2013).
Additionally, creating a community based nutrient management criteria based on social
expectations could provide site specific goals meeting local, state and federal
regulations strengthened by stakeholder involvement.
To create a community-based stormwater pond management program to meet
regulatory requirements and aesthetic preference, several objectives must be met. The
following chapters present investigations of 1) the nutrient-response relationships in
Florida stormwater ponds, 2) the identification of chlorophyll-a thresholds for stormwater
ponds, 3) the evaluation of significant predictors of nutrient enrichment in stormwater
pond systems and 4) the identification of community-based nutrient management
thresholds and potential impacts.
Establishing the relationships between TN, TP and chlorophyll-a concentration is
essential in defining water column nutrient criteria and the nutrient-response
relationships in stormwater ponds. This part of the investigation is summarized in
Chapter 2. Objectives and hypothesis for Chapter 2 were:
• Objective 2-1: Develop nutrient-response models for stormwater ponds using TP, TN and chlorophyll-a concentrations.
• Hypothesis 2-1: Chlorophyll-a response to nutrients in stormwater ponds are significantly different than the chlorophyll-a response to TN and TP in natural Florida lakes.
Identifying community-based expectations and acceptable thresholds based on
chlorophyll-a concentrations were necessary to identify nutrient concentration criteria
protective of resident preference. Results of this investigation are provided in Chapter 3.
The objectives and hypotheses for Chapter 3 were:
47
• Objective 3-1: Identify community-based expectations and thresholds of impairment in stormwater ponds based on water-column chlorophyll-a concentrations.
• Hypothesis 3-1: Community-based expectations and thresholds of impairment identified for stormwater ponds will be lower than the numeric nutrient criteria established for natural lake systems in Florida (20 µg·L-1 chl-a).
• Objective 3-2: Determine if educational information on the role of algae in stormwater ponds has an effect on community-based expectations and thresholds of impairment chosen in a web-based survey.
• Hypothesis 3-2A: Educational treatment regarding the benefit and role of algae in a stormwater pond will increase community-based treatment thresholds.
• Hypothesis 3-2B: The presence of aquatic vegetation will reduce community-based treatment thresholds.
• Objective 3-3: Determine if pond use, education regarding stormwater ponds and demographic background have significant effects on preferred chlorophyll-a treatment threshold.
• Hypothesis 3-3A: If individuals use ponds frequently for recreational activities, then they will have a higher chlorophyll-a treatment threshold than individuals who do not.
• Hypothesis 3-3B: If residents are educated regarding the benefit and function of water column algae growth, then they will have a higher chlorophyll-a treatment threshold than those who are not.
• Hypothesis 3-3C: There will be a significant difference in chlorophyll-a treatment thresholds according to demographic identity.
In Chapter 4, several management variables were evaluated as predictors of
stormwater pond TN, TP, and chlorophyll-a concentration to identify potential
management targets for reducing undesirable conditions and identifying pond-specific
treatment thresholds. The objective for Chapter 4 was:
• Objective 4-1: Identify potential drivers of stormwater pond nutrient enrichment and develop pond-specific TN, TP and chlorophyll-a concentration models.
After identifying nutrient-response relationships and chlorophyll-a treatment
thresholds, a community-based numeric nutrient criteria can be established to guide
48
management decisions. Chapter 5 utilized nutrient response relationships established in
Chapter 2 and treatment-thresholds identified in Chapter 3 to establish nutrient
thresholds for several potential chlorophyll-a treatment levels. The objectives and
hypotheses for Chapter 5 were:
• Objective 5-1: Establish community-based stormwater pond nutrient criteria for TN and TP in clear and colored stormwater ponds based on community-identified chlorophyll-a treatment thresholds.
• Hypothesis 5-1: Higher chlorophyll-a treatment thresholds will result in increasingly greater nutrient removal potential in stormwater ponds.
In conclusion (Chapter 6), the results are summarized within the context of the
current regulatory requirements and social expectations of stormwater ponds in Florida.
49
Table 1-1. EPA Approved Numeric Criteria for Florida’s Lakes (United States Environmental Protection Agency, 2010).
Lake Type Color/Alkalinity
Response Chl-a µg/L
Stressor Nutrient mg/L
Lower Threshold
Upper Threshold
Clear, Low Alkalinity
6 6
TP TN
.01
.51 .03 .09
Clear, High Alkalinity
20 20
TP TN
.03 1.05
.09 1.93
Colored 20 20
TP TN
.05
.1.27 .16 2.23
Color is distinguished by the amount of dissolved organic matter, free from turbidity, and reported in Platinum Cobalt Units (PCU). Clear lakes have values less than or equal to 40 PCU and colored lakes have values greater than 40 PCU. Alkalinity is determined by concentration of CaCO3. Alkaline lakes have greater than 20mg/L CaCO3 and acid lakes have values less than or equal to 20mg/L CaCO3.
Figure 1-1. Stormwater pond interactions and drivers
50
CHAPTER 2 NUTRIENT-ALGAL RESPONSE RELATIONSHIPS IN STORMWATER PONDS
Introduction
The development of a quantitative and predictive ecological nutrient-response
relationship is essential to establishing adequate watershed management practices
(Dillon & Rigler, 1974). Nutrient-response relationships are commonly used by
regulatory agencies and lake managers to implement eutrophication control measures,
and nitrogen and phosphorus are widely recognized predictive drivers of chlorophyll-a
response in freshwater lake systems (Sakamoto, 1966; Dillon & Rigler, 1974; Brown,
Hoyer, Bachmann, & Canfield, 2000; Florida Department of Environmental Protection ,
2012). To establish the relationships, lake water column nutrient concentrations are
measured directly or estimated with nutrient loading models and then compared in an
associated regression models to relate to algae chlorophyll-a concentrations (Hoyer,
Frazer, Notestein, & Canfield, 2002). Chlorophyll-a concentrations can, in turn, be used
to determine how much the nutrient of concern needs to be controlled to achieve or
maintain a desired algal concentration (Hoyer, Frazer, Notestein, & Canfield, 2002;
Florida Department of Environmental Protection , 2012). This nutrient-response
approach to address eutrophication in freshwater lake systems has been successfully
implemented in several locations, including Florida (Cooke, Welch, Peterson, &
Newroth, 1993; Hoyer, Frazer, Notestein, & Canfield, 2002; Florida Department of
Environmental Protection , 2012), but no similar relationship has ever been established
or applied to stormwater pond systems.
Eutrophication in stormwater pond systems is a recent problem that has arisen
with the increased implementation of wet stormwater ponds as landscape features and
51
recreational amenities in residential communities (DeLorenzo, Thompson, Cooper,
Moore, & Fulton, 2012; Serrano & DeLorenzo, 2008). In Florida, stormwater pond
systems are regulated stormwater management features expected to treat nutrient
runoff and protect natural downstream systems by removing at least 80% of the annual
average pollutant load (Livingston & McCarron, 1992). Stormwater pond design and
management supports nutrient removal through physical (sedimentation), chemical
(precipitation and adsorption), and biological (uptake) mechanisms, and stormwater
ponds built to the state criteria are assumed to meet the required nutrient removal
efficiencies (Harper & Baker, 2007). However, a recent study by Harper and Baker
(2007) revealed stormwater ponds built and managed to state standards failed to meet
the required total nitrogen (TN) and total phosphorus (TP) removal efficiencies.
The principal role of stormwater ponds for quantity and quality mitigation systems
of runoff from urban development has become secondary to aesthetic and recreational
expectations of water quality standards and management decisions to use herbicides
and algaecides to achieve expectations further compounds the inefficiencies of nutrient
removal. To meet nutrient removal efficiencies, Harper and Baker (2007) suggest
adding upstream source control and mitigation to stormwater management plans
forming a treatment train to help reduce the overall load reaching natural water bodies.
Establishing the nutrient-response relationships between TN, TP and chlorophyll-a in
stormwater ponds would allow managers to establish quantitative relationships between
nutrients and algal response and more effectively identify water quality goals, including
acceptable nutrient concentration targets and specific upstream nutrient reduction
strategies.
52
Nutrient-response relationships are well established for natural Florida lakes, but
applying those relationships to stormwater ponds may not be appropriate. Prior studies
demonstrated empirical models developed from natural lakes were not applicable for
built aquatic systems (Smith, 1990; Gloss, Reynolds, Mayer, & Kidd, 1981; Higgins,
Poppe, & Iwanski, 1981) and primary productivity appeared lower in artificial systems
than in natural lakes (Soballe, Kimmel, Kennedy, & Gaugush, 1992; Cooke & Carlson,
1989; Jones & Bachmann, 1976). The major objective of this work was to develop
nutrient-response models for TP, TN and chlorophyll-a concentrations in Florida
stormwater ponds. Additionally, the established stormwater pond models was compared
to the Florida lake nutrient-response models used to develop the Numeric Nutrient
Criteria in the state of Florida.
Methods
Urban development in the Tampa Bay watershed, Florida, currently accounts for
at least 27% of the total land area (Xiang, Crane, & Su, 2007) and is considered a
significant contributor to non-point source pollution reaching Tampa Bay (Tampa Bay
Estuary Program, 2006; United States Environmental Protection Agency, 2009). This
study was conducted in a large, residential community located within the Tampa Bay
watershed that covers approximately 8,500 acres with a population of more than 15,000
residents. Wet stormwater ponds are an important feature in the community as over 300
ponds provide water storage, water treatment, aesthetic, recreational and economic
value to residents and homeowners. Stormwater pond management decisions are
made by a single community pond manager based on resident preferences and
algaecide and herbicide applications to control algal growth are applied by a contracted
pond management company.
53
A simple, randomized sample (n=36) of the 307 stormwater ponds in the
residential community located in southwest Florida was selected (Ary, Jacobs, &
Razavieh, 2002) and water column TP concentration, TN concentration, color and
chlorophyll-a concentration were measured at three predetermined locations within
each pond monthly during May, July, August and October, 2013 (Figure 2-1). Water
samples were taken by hand at a depth of 0.60 m and preserved in accordance with
EPA protocol (United States Environmental Protection Agency, 1979) in 20 ml PTFE
acid-washed bottles and stored on wet ice. Water samples collected for TP were
syringe filtered through 0.45µm disk filter and H2SO4 was added to ensure pH below
2.0. Water samples collected for TKN and NOx-N were preserved with H2SO4 to ensure
pH below 2.0. Color and chlorophyll-a concentrations were measured at a depth of 0.60
m using a WET Labs ECO Triplet-w optical instrument. The WET Labs ECO Triplet-w
measured chlorophyll-a concentration (µg·L-1) and color (platinum cobalt units, PCU)
every 30 seconds for 3 minutes and mean values were calculated for each sampling
station. Water samples were analyzed for nutrients by the University of Florida
Analytical Research Lab following EPA Method 365.1 for TP and EPA Methods 351.2
(TKN) and 353.2 (NOx-N) to determine TN.
Following the 4 months of sampling, a representative subset of 12 ponds was
selected from the randomized sample for continued sampling for an additional 8
months. The representative sample consisted of 4 phosphorus limited ponds with
consistently low water column TP concentrations, 4 phosphorus limited ponds with
consistently high water column TP concentrations and 4 nitrogen limited ponds.
Phosphorus limited ponds were defined as ponds with an N:P ratio greater than 20:1
54
and nitrogen limited ponds were defined as ponds with an N:P ratio less than or equal to
20:1 (Guildford & Hecky, 2000). For the study data analysis, mean color, TP, TN and
chlorophyll-a concentrations were determined for each pond by averaging the values
measured at each of the three sites within the pond for each sampling date, similar to
Hoyer et al (2002). Computations and comparisons were performed using the JMP Pro
11 statistical software package (SAS Institute, 2009) and mean values are reported with
the standard error.
For analysis and comparison of nutrient-response relationships, stormwater
ponds were categorized into clear (≤40 PCU) and colored (>40 PCU) systems similar to
state Numeric Nutrient Criteria classification (Florida Department of Environmental
Protection , 2012) to account for the possible influence of color on the chlorophyll-a and
nutrient relationships (Hoyer & Jones, 1983; Brown, Hoyer, Bachmann, & Canfield,
2000). Data for nutrient-response were log-transformed to normalize data and
accommodate heterogeneity of variance (Cleveland, 1984; Ott & Longnecker, 2001;
Snedecor & Cochran, 1967). Stormwater pond nutrient-response linear regressions
were then compared to the established, statewide colored and clear lake nutrient-
response regressions utilizing a fixed-effects test of a least squares model to evaluate
for significant difference between the two indicator-variable models and slopes.
Results and Discussion
The 36 stormwater ponds sampled for this project were distributed throughout
the residential community and ranged in size and surrounding land use. All of the
stormwater ponds were constructed after 1992 and were 5 acres or smaller in size.
Total phosphorus concentrations averaged 0.03 ± 0.003 mg·L-1 for clear stormwater
ponds and 0.05 ± 0.005 mg·L-1 for colored stormwater ponds (Table 2-1). The average
55
TP concentration of colored stormwater ponds was higher than the average of 0.039
mg·L-1 reported for natural Florida lakes (Brown, Hoyer, Bachmann, & Canfield, 2000),
and equal to the lower threshold of 0.05 mg·L-1 identified by the Numeric Nutrient
Criteria for colored Florida lakes (United States Environmental Protection Agency,
2010). The average TP for clear stormwater ponds (0.03 mg·L-1) was equal to the
Numeric Nutrient Criteria lower threshold for clear, high alkalinity lakes (United States
Environmental Protection Agency, 2010).
Total nitrogen concentrations averaged 0.91 ± 0.04 mg·L-1 for clear stormwater
ponds and 1.29 ± 0.04 mg·L-1 for colored stormwater ponds, both higher than the values
reported TN concentration of 0.69 mg·L-1 for all natural Florida lakes (Brown, Hoyer,
Bachmann, & Canfield, 2000). The average TN concentration of colored stormwater
ponds exceeded the Numeric Nutrient Criteria lower threshold for total nitrogen of 1.27
mg·L-1 in natural, colored lakes, but the average TN concentration of clear stormwater
ponds did not exceed the Numeric Nutrient Criteria for clear, high alkalinity lakes of 1.05
mg·L-1 (United States Environmental Protection Agency, 2010).
The average chlorophyll-a concentrations of clear and colored stormwater ponds
were 5.55 ± 0.49 µg·L-1 and 9.12 ± 0.44 µg·L-1, respectively. Neither value exceeded
the 23.0 µg·L-1 average chlorophyll-a concentrations reported for all Florida lakes
(Brown, Hoyer, Bachmann, & Canfield, 2000). The stormwater ponds also did not
exceed the 20 µg·L-1 impairment threshold identified by the Numeric Nutrient Criteria for
colored and clear, high alkalinity lakes with the designated use of fishing, recreation and
maintenance of a healthy fish and wildlife population (United States Environmental
Protection Agency, 2010).
56
The relationship between nutrients and chlorophyll-a concentrations in
stormwater ponds is much weaker than those established in natural Florida lakes (Table
2-2). Total phosphorus alone accounted for 25% of the variance in chlorophyll-a
concentrations in clear stormwater ponds and 27% of the variance in chlorophyll-a
concentrations in colored stormwater ponds, compared to a much more robust 68% in
clear lakes and 58% in colored lakes (Florida Department of Environmental Protection ,
2012). The relationship between TP and chlorophyll-a in clear and colored stormwater
ponds was plotted, respectively, against the TP-chlorophyll-a relationship established in
setting Florida’s Numeric Nutrient Standard (Florida Department of Environmental
Protection , 2012) for clear (Figure 2-2) and colored (Figure 2-3) lakes. The chlorophyll-
a response to increases in TP concentration appears to be greater in clear and colored
lake systems than in clear and colored stormwater ponds and a fixed-effects test
revealed significant difference in the TP-chlorophyll-a interaction and slopes of clear
lakes and clear stormwater ponds (F1,1=7.504, p<0.05) and of colored lakes and colored
stormwater ponds (F1,1=4.763, p<0.05).
Interestingly, the community is also located in a region with noted external
influences on the nutrient-response relationships in natural lakes and streams (Florida
Department of Environmental Protection , 2012). Prior evaluation by the Florida
Department of Environmental Protection (FDEP) of natural lakes in the West Central
Peninsula Region (WCPR) revealed the relationship between TP and chlorophyll-a was
weak (R2=0.028, p=0.315), suggesting other factors influence the nutrient-algal
response relationship in this area (2012). Total phosphorus-chlorophyll-a relationships
for colored lakes in this area were evaluated and an alternative model was developed,
57
leading FDEP to cap the upper TP threshold of the Numeric Nutrient Criteria for colored
lakes at the regional stream threshold of 0.49mg/L. When data collected for colored
stormwater ponds were compared to natural lakes located in the WCPR (Table 2-2), the
TP-chlorophyll-a relationship was found to be stronger in stormwater ponds than in
lakes, with TP accounting for 27% of the variance in chlorophyll-a in stormwater ponds
and only for 3% of the variance in chlorophyll-a in lakes (Florida Department of
Environmental Protection , 2012). The chlorophyll-a response to TP concentrations in
colored stormwater ponds was plotted against the chlorophyll-a response to TP in
colored lakes in the WCPR (Figure 2-4). A fixed effects test of least squares model
revealed the TP-chlorophyll-a interaction and slopes of colored lakes and colored
stormwater ponds were not significantly different (F1,1=0.701, p=0.404), even though
nearly all the stormwater pond data were less than TP concentrations found in the
natural colored lakes in the WCPR. Furthermore, a fixed effects test least squares
model for mean response difference at zero indicates there is no significant difference
(F1,1=0.001, p=0.978) in the intercept between colored stormwater ponds and colored
lakes in this region.
Total nitrogen accounted for 5% of the variance in chlorophyll-a in clear
stormwater ponds and 7% in colored stormwater ponds, much less than the 77% and
65% variance in chlorophyll-a related to TN concentrations in clear and colored lakes,
respectively (Florida Department of Environmental Protection , 2012). Thus, the TN-
chlorophyll-a stormwater pond models (Table 2-2) are much less robust than those for
natural Florida lakes. Additionally, the relationships between TN and chlorophyll-a in
clear and colored stormwater ponds were plotted, respectively, against the TN-
58
chlorophyll-a relationship established in setting Florida’s Numeric Nutrient Standard
(Florida Department of Environmental Protection , 2012) for clear (Figure 2-5) and
colored (Figure 2-6) lakes. As seen in the TP-chlorophyll-a relationships, the
chlorophyll-a response to increases in TN concentration appears to be greater in clear
and colored lake systems than in clear and colored stormwater ponds. A fixed-effects
test revealed significant difference in the TN-chlorophyll-a interaction and slopes of
clear lakes and clear stormwater ponds (F1,1=13.800, p<0.005) and of colored lakes and
colored stormwater ponds (F1,1=11.268, p<0.005).
Conclusion
This study developed nutrient-response models for TP, TN and chlorophyll-a
concentrations in Florida stormwater ponds by sampling a random selection of
stormwater ponds in southwestern Florida for several months. These models may help
guide stormwater pond managers to better design and implement nutrient reduction
strategies preventing unwanted algal responses by identifying target nutrient thresholds.
Phosphorus is normally the primary limiting nutrient in Florida lakes (Canfield, 1983;
Brown, Hoyer, Bachmann, & Canfield, 2000), and the data presented suggest TP often
has a greater influence on the chlorophyll-a concentration within stormwater ponds than
TN and is the primary limiting nutrient. Total phosphorus concentrations account for
25% and 27% of the variance in chlorophyll-a concentrations in clear and colored
stormwater ponds, respectively. Total nitrogen concentrations account for only 5% and
7% of the variance in chlorophyll-a concentrations in clear and colored stormwater
ponds, respectively.
Although the TP-chlorophyll-a relationships in stormwater ponds are not as
robust as those established for natural lake systems, they are more robust than
59
relationships found in a prior study of built reservoirs in the southeastern United States
(Reckhow, 1988; Canfield & Bachmann, 1981). The models developed for TP/TN-
chlorophyll-a relationships in clear and colored stormwater ponds were also found to be
significantly different from those developed for Florida lakes. The chlorophyll-a
responses to increases in TP and TN concentrations are less in stormwater pond
systems than the response occurring in natural lake systems, suggesting the poor
suitability of the Florida lake models for use in stormwater ponds. There is one
exception, however, as the region specific TP model for colored lakes in the WCPR was
not significantly different than the TP model for colored stormwater ponds. This finding
suggests there is an external influence on TP-chlorophyll-a relationships for lake and
stormwater pond surface water bodies in this region that should be further investigated.
The models developed in this investigation provide a more accurate description
of the nutrient-response relationships in stormwater ponds and could be used more
suitably to provide quantitative guidance for managing aesthetic and permitted demands
in stormwater ponds where no such guidance currently exists. The relatively weak
nutrient-chlorophyll-a relationships, however, suggest there are other variables
contributing to the variance of chlorophyll-a concentrations that should be investigated
to improve the eutrophication models for stormwater ponds. Alternative variables
impacting chlorophyll-a concentration in stormwater ponds, including detention time,
pond design and management strategies, should be investigated and considered to
better explain and predict nutrient-response relationships in stormwater ponds.
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Table 2-1. Mean, median, standard error, and minimum and maximum values for total phosphorus, total nitrogen and chlorophyll-a concentrations in stormwater ponds compared to Numeric Nutrient Criteria (NNC) lower threshold values (United States Environmental Protection Agency, 2010) and natural Florida (FL) lake values (Brown, Hoyer, Bachmann, & Canfield, 2000)
Pond Color Variable Mean Median S.E. Min. Max. NNC FL Clear (≤40 PCU) n=87
TP (mg·L-1) 0.03 0.02 0.003 0.01 0.14 0.03 0.04 TN (mg·L-1) 0.91 0.87 0.04 0.4 2.24 1.05 0.69 Chl-a (µg·L-1) 5.55 4.14 0.49 0.18 26.03 20.0 23.0
Colored (>40 PCU) n=120
TP (mg·L-1) 0.05 0.03 0.005 0.01 0.29 0.05 0.04 TN (mg·L-1) 1.29 1.21 0.04 0.66 3.48 1.27 0.69 Chl-a (µg·L-1) 9.12 8.95 0.44 1.41 30.68 20.0 23.0
TP, total phosphorus, TN, total nitrogen, Chl-a, Chlorophyll-a, PCU, platinum cobalt units, S.E., standard error, NNC, Numeric Nutrient Criteria, FL, natural Florida lake values.
61
Table 2-2. Empirical models and summary statistics describing the association of monthly average nutrient and chlorophyll concentrations using data from stormwater ponds in a southwest Florida community and Florida Freshwater Lakes (Florida Department of Environmental Protection , 2012).
Model Color p r2
Southwest FL Stormwater ponds LnCHL = 0.520LnTP + 3.459 Clear <0.001 0.245 LnCHL = 0.423LnTN + 1.528 Clear <0.05 0.051 LnCHL = 0.368LnTP + 3.284 Colored <0.001 0.269 LnCHL = 0.486LnTN + 1.959 Colored <.01 0.066 FDEP (2012) for Florida freshwater lakes LnCHL = 1.136LnTP + 6.370 Clear <0.001 0.677 LnCHL = 1.729LnTN + 2.482 Clear <0.001 0.769 LnCHL = 1.128LnTP + 5.729 Colored <0.001 0.581 LnCHL = 1.965LnTN + 1.995 Colored <0.001 0.645 LnCHL = 0.594LnTP + 3.942 Colored, WCPR =0.351 0.028
CHL, chlorophyll-a (µg·L-1), TP, total phosphorus (mg·L-1), TN, total nitrogen (mg·L-1), clear (≤40 PCU), colored (>40PCU). WCPR, West Central Peninsula Region.
62
Figure 2-1. Location of 36 stormwater ponds sampled between May 2013 and June 2014. The yellow pins indicate the initial 24 stormwater ponds sampled during the first 4 sampling dates and the red pins indicate the subset of ponds sampled all 12 dates.
63
Figure 2-2. Regression analysis between annual geometric mean chlorophyll-a
concentration and annual geometric TP concentration in clear Florida lakes (black data points, upper left equation (Florida Department of Environmental Protection , 2012)) compared to regression analysis between monthly mean pond chlorophyll-a concentration and monthly mean TP concentration in clear stormwater ponds in southwest Florida (blue data points, lower right equation). The two lines represent the linear regressions for each data set. Fixed effects test of least squares model shows significant difference in TP-Chlorophyll-a interaction and slopes of clear lakes and clear stormwater ponds (F1,1=7.504, p<0.05).
64
Figure 2-3. Regression analysis between annual geometric mean chlorophyll-a
concentration and annual geometric TP concentration in colored Florida lakes (black data points, upper left equation (Florida Department of Environmental Protection , 2012)) compared to regression analysis between monthly mean pond chlorophyll-a concentration and monthly mean TP concentration in colored stormwater ponds in southwest FL (blue data points, lower right equation). The two lines represent the linear regressions for each data set. Fixed effects test of least squares model shows significant difference in TP-Chlorophyll-a interaction and slopes of colored lakes and colored stormwater ponds (F1,1=4.763, p<0.05).
65
Figure 2-4. Regression analysis between annual geometric mean chlorophyll-a
concentration and annual geometric TP concentration in West Central Peninsular Region colored, Florida lakes (black data points, upper left equation (Florida Department of Environmental Protection , 2012)) compared to regression analysis between monthly mean pond chlorophyll-a concentration and monthly mean TP concentration in colored stormwater ponds located in the same region (blue data points, lower right equation). The two lines represent the linear regressions for each data set. Fixed effects test of least squares model shows TP-Chlorophyll-a interaction and slope of colored lakes and colored stormwater ponds are not significantly different (F1,1=0.701, p=0.404).
66
Figure 2-5. Regression analysis between annual geometric mean chlorophyll-a
concentration and annual geometric TN concentration in clear Florida lakes (black data points, upper left equation (Florida Department of Environmental Protection , 2012)) compared to regression analysis between monthly mean pond chlorophyll-a concentration and monthly mean TN concentration in clear stormwater ponds in southwest FL (blue data points, lower right equation). The two lines represent the linear regressions for each data set. Fixed effects test of least squares model shows significant difference in TN-Chlorophyll-a interaction and slopes of clear lakes and clear stormwater ponds (F1,1=13.800, p<0.005).
67
Figure 2-6. Regression analysis between annual geometric mean chlorophyll-a
concentration and annual geometric TN concentration in colored Florida lakes (black data points, upper left equation (Florida Department of Environmental Protection , 2012)) compared to regression analysis between monthly mean pond chlorophyll-a concentration and monthly mean TN concentration in colored stormwater ponds in southwest FL (blue data points, lower right equation). The two lines represent the linear regressions for each data set. Fixed effects test of least squares model shows significant difference in TN-Chlorophyll-a interaction and slopes of colored lakes and colored stormwater ponds (F1,1=11.268, p<0.005).
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CHAPTER 3 IDENTIFYING SIGNIFICANT FACTORS INFLUENCING STORMWATER POND
NUTRIENT AND ALGAE CONCENTRATIONS
Introduction
Nutrient-algae response relationships are commonly used to predict unwanted
algal blooms, control eutrophication and manage natural lake systems. Nitrogen and
phosphorus are recognized drivers of algal biomass, as measured by chlorophyll-a
concentration, in freshwater lake systems (Sakamoto, 1966; Dillon & Rigler, 1974;
Brown, Hoyer, Bachmann, & Canfield, 2000; Florida Department of Environmental
Protection , 2012) and the relationships between total phosphorus (TP), total nitrogen
(TN) and chlorophyll-a concentrations can be used to create regression models
approximating algal response concentrations based on quantifiable nutrient
concentrations (Hoyer, Frazer, Notestein, & Canfield, 2002). Nealis et al. (2016),
established nutrient-chlorophyll-a relationships for stormwater ponds, but recognized
the nutrient-response relationships were significantly different from natural lake systems
and additional variables were likely influencing the algal response to increasing nutrient
concentrations.
Water quality expectations of stormwater pond users are similar to natural,
freshwater lakes (Nealis, Monaghan, Clark, Hochmuth, & Frank, 2016), but current
stormwater pond management practices may influence TN, TP and chlorophyll-a
concentrations within ponds and compound pond failure to meet the required nutrient
removal efficiencies (Harper & Baker, 2007). Currently, stormwater pond managers
focus on several variables that may have a significant impact on the nutrient-response
relationships within stormwater ponds.
69
Within the pond, algae, emergent vegetation and submerged aquatic vegetation
are often controlled through various chemical treatments to meet aesthetic preferences.
Application of algaecides and herbicides drastically reduce algal populations, artificially
suppressing chlorophyll-a concentration response to water column nutrient
concentrations. Chemical applications may eliminate important biological nutrient
removal pathways (Harper & Baker, 2007; Brenner, et al., 2006; de-Bashan & Bashan,
2004; Reddy, Kadlec, Flaig, & Gale, 1999; Graves, Wan, & Fike, 2004), specifically the
assimilative capacity of algae in the water column, reducing the overall nutrient removal
efficiencies of the stormwater pond. Algae, specifically, has the ability to assimilate
nitrogen and phosphorus (Wetzel, 2001), store excess, “luxury” phosphorus (Kuhl,
1974; Powell, Shilton, Pratt, & Chisti, 2008), and sequester nutrients as algae particles
settle within the pond.
The management of emergent and submerged vegetation within and surrounding
stormwater ponds is also an important variable to consider. Vegetated wetland areas,
as are found on some littoral shelves or pond edges, can have a high assimilative
capacity for nutrients while the denitrification processes within the wetland area can
reduce nitrate-nitrite N concentrations in runoff (Graves, Wan, & Fike, Water quality
characteristics of storm water from major land uses in South Florida, 2004; Hammer &
Bastian, 1989), but they do not necessarily increase the nutrient removal efficiencies
compared to non-vegetated littoral areas (DB Environmental, Inc., 2005). Vegetated
littoral shelves can contribute nutrients to the water column from decomposing plant
tissue (Graves, Wan, & Fike, Water quality characteristics of storm water from major
land uses in South Florida, 2004), especially when vegetation is managed with
70
herbicidal treatments (DB Environmental, Inc., 2005). Littoral shelf vegetation may,
however, contribute to reducing chlorophyll-a concentrations by outcompeting algae for
light and nutrients (DB Environmental, Inc., 2005; van Donk & van de Bund, 2002),
producing allelopathic substances (Jasser, 1995; Wium-Anderson, Christophersen, &
Houen, 1982), and supporting communities grazing zooplankton communities (van
Donk & van de Bund, 2002).
Stormwater pond structural design may also influence nutrient and chlorophyll-a
concentrations. Littoral shelves are the shallow area at the edge of a stormwater pond,
usually no deeper than approximately 1 meter below the design overflow, where
sunlight may penetrate the water column and reach the soil surface (Southwest Florida
Water Management District, 2010). The shallow areas provided by littoral shelves have
the ability to reduce water column nutrient concentrations by increasing the area of
contact between the water column, soil, and vegetation (Baldwin, Simpson, &
Weammert, 2009; DB Environmental, Inc., 2005) and increase the settling of suspended
particles by decreasing the velocity of incoming runoff (Brix, 1993; Schueler T. , 1992).
Management decisions surrounding stormwater ponds may also impact
stormwater pond nutrient and chlorophyll-a concentrations. Landscaping decisions
(Linde & Watschke, 1997; Easton & Petrovic, 2004; Shuman, 2004) and land use
(Brown & Vivas, 2005; Mallin, Ensign, Wheeler, & Mayes, 2002; Mallin, Johnson, &
Ensign, 2009) adjacent to the stormwater pond may influence nutrient loads to the pond
and reduce water quality. Increased land use intensity and impervious surface cover
have been linked to increases in runoff volume, erosion and nutrient loading (Carey, et
al., 2011; Schiff & Benoit, 2007; Brown & Vivas, 2005). Soil erosion surrounding
71
stormwater ponds is another important variable as shoreline erosion can be prevented
through several design and landscaping practices. Eroded soil particles and organic
matter can be significant contributors of nitrogen and phosphorus to a stormwater pond
(Daniel, Sharpley, Edwards, Wedepohl, & Lemunyon, 1994; Sharpley, et al., 1994;
Quinton, Govers, Van Oost, & Bardgett, 2010) and further increase water column
nutrient concentrations.
Landscape maintenance decisions may also impact nutrient loading to
stormwater ponds. Runoff from managed turfgrass landscaping has been reported to
contain 0.5-2.0 mg phosphorous and 3.0-5.0 mg nitrogen per liter (Barten & Jahnke,
1997; Easton & Petrovic, 2004; Shuman, 2004; Waschbusch, Selbig, & Bannerman,
1999) and runoff containing these nutrient concentrations are capable of causing
eutrophication in surface water bodies receiving the runoff in large volumes (Baker,
Wilson, Fulton, & Horgan, 2008). Local regulations restricting residential fertilizer
application have been implemented in several areas in an attempt to reduce non-point
source nutrient runoff, but the effect of the ordinances on stormwater pond water
column nutrient concentrations is currently unknown.
Grass clippings are an additional byproduct of turfgrass management and, if
mismanaged, can enter a stormwater pond through direct input from maintenance of
adjacent shorelines, overland flow from surrounding areas, or from transport via
impervious surfaces and stormwater systems. Grass clippings contain a 1.5 to 3.5%
nitrogen concentration and a 0.15 to 0.5% phosphorus concentration by dry weight
(Sartain, 2001) and can supply additional nitrogen and phosphorus to the water column
as they decompose (Bedan & Clausen, 2009). Most of the nutrients associated with
72
grass clippings will leach into the water column within 22 days of immersion, with a
majority of the phosphorus and a third of the TKN released within the first day of
immersion (England, 2001; Strynchuk, Royal, & England, 1999). Leached nutrients
enter the water column and can potentially stimulate increased algal growth.
The influence of the aforementioned management variables must be evaluated to
identify other factors potentially influencing the TP, TN and chlorophyll-a concentrations
in stormwater ponds. Identifying and measuring variables that significantly impact
nutrient and algal concentrations within stormwater ponds will provide better guidance
for stormwater pond management criteria. The careful evaluation and consideration of
individual stormwater pond characteristics may provide a more accurate understanding
of nutrient-response relationships (Havens, 2003). Identifying landscaping and
management variables with significant impacts on water column nutrients and algae
could also provide future guidance and recommendations for reducing nutrients and
algae in stormwater ponds.
In this paper, the impact of pond design, management and landscaping decisions
on stormwater pond nutrient and chlorophyll-a concentrations were evaluated to identify
significant predictive variables of TP, TN and chlorophyll-a concentrations within
stormwater ponds. Significant predictor variables were then used to develop pond-
specific TN, TP and chlorophyll-a concentration models for clear and colored
stormwater ponds.
Methods
This study was conducted in a large, residential community located within the
Tampa Bay watershed. Wet stormwater ponds are an important feature in the
community as over 300 ponds provide water storage, water treatment, aesthetic,
73
recreational and economic value to community members. A single community pond
manager is tasked with making all stormwater pond management decisions and a single
pond management company is contracted to implement the community pond manager’s
decisions, including chemical and mechanical interventions applied to the stormwater
ponds. Landscape management surrounding the stormwater ponds may be conducted
by a community contracted company, individual private contractor, or private
homeowner.
Nealis et al. (2016), sampled 36 stormwater ponds in a large, residential
community in southwest Florida and measured water column TP concentration, TN
concentration, color and chlorophyll-a concentration at three predetermined locations
within each pond monthly for 4 months. A representative subsample of 12 ponds was
then selected from the 36 original ponds and sampled for an additional 8 months. This
data were used to establish nutrient-response relationships for TP and TN in clear and
colored stormwater ponds (Nealis, Clark, Monaghan, Hochmuth, & Frank, 2016). The
nutrient-response relationships established for TP and TN in stormwater ponds provide
an estimate for quantifying the nutrient removal capacity within a stormwater pond, but
low coefficients of determination for each model suggest there are other factors
influencing nutrient and response dynamics (Nealis, Clark, Monaghan, Hochmuth, &
Frank, 2016). Concurrent with the previous study, additional variables were measured
at each stormwater pond sample site during each of the 12 sampling events, including
field assessments of landscaping and management decisions. The variables and
methods used to quantify the variables are described in Table 3-1.
74
Visual evaluation of land use adjacent to stormwater ponds was conducted on
site and spatial analysis of land use within 100 meter buffer of the stormwater ponds
was conducted using ArcGIS Desktop (ESRI, 2011) and landscape disturbance
gradients identified in the Landscape Development Intensity index (Brown & Vivas,
2005). These variables were evaluated for their significance as predictors of TP, TN and
chlorophyll-a concentrations in clear and colored storm water ponds reported by Nealis
et al. (2016), using a statistical software (SAS Institute, 2009) stepwise regression fit
model, mixed option, with the probability to enter and leave set at 0.15. Once the
significant variables were identified, a fit least squares model procedure was conducted
to identify variable coefficients and the model equation.
Results and Discussion
The stepwise regression fit model identified significant predictive variables for
TP, TN and chlorophyll-a concentrations in clear and colored ponds and a fit least
squares model was used to determine variable coefficients, model equations and the
coefficient of determination for each model. Predictive models evaluating the impact of
different management and landscaping variables for clear and colored stormwater
ponds are presented in Table 3-2 with summary statistics for each significant variable
presented in Table 3-3.
Residential fertilizer application, chlorophyll-a concentration, subaquatic
vegetation coverage, bank erosion, and the nutrient limitation of the stormwater pond
were found to be significant predictor variables of phosphorus concentrations in clear
stormwater ponds (p<0.001, r2 =0.76). Chlorophyll-a concentration, area of stormwater
pond in proportion to surrounding 100 meters, presence of grass clippings, percent of
pond area in littoral shelf, pond area, and nutrient limitation of the stormwater pond were
75
found to be significant predictor variables of phosphorus concentrations in colored
stormwater ponds (p<0.001, r2 =0.82). Residential fertilizer application, presence of
artificial aeration, percent of surrounding land area in low-intensity transportation and
low intensity commercial use, chlorophyll-a concentration, filamentous algae coverage,
presence of bank erosion, percent of pond area in littoral shelf, and percent of littoral
shelf area planted in emergent aquatic vegetation were found to be significant predictor
variables of nitrogen concentration in clear stormwater ponds (p<0.001, r2 =0.49).
Residential fertilizer application, presence of aeration, percent of surrounding land area
in low intensity transportation and in high-density residential use, percent of surrounding
land area in natural lands or wetlands, presence of grass clippings, percent of pond
area in littoral shelf and percent of adjacent land use in natural areas were found to be
significant predictor variables of nitrogen concentration in colored stormwater ponds
(p<0.001, r2 =0.31). Evidence of chemical treatment, percent of surrounding land area in
low-intensity recreational and low-intensity commercial land use, percent coverage of
submerged aquatic vegetation, presence of grass clippings, percent of pond area in
littoral shelf, percent of adjacent residential land use, nutrient limitation and TP
concentration were found to be significant predictor variables of chlorophyll-a
concentration in clear stormwater ponds (p<0.001, r2 =0.51). Percent of surrounding
land area in high-density residential use, percent of surrounding land in natural lands or
wetlands, percent of pond area in littoral shelf, percent of shoreline with shoreline
plantings, percent of adjacent residential land use, percent of adjacent natural area, and
nutrient limitation were found to be significant predictor variables of chlorophyll-a
concentration in colored stormwater ponds (p<0.001, r2 =0.51).
76
Only two variables, littoral shelf coverage of pond area and the presence of grass
clippings, were identified as significant drivers of TP, TN and chlorophyll-a
concentrations in clear and colored stormwater ponds (Figure 3-1). Ponds in this study
had littoral shelf coverage ranging from 0 to 60%, with a median coverage of 15%.
Littoral shelf coverage was negatively correlated with TP concentration in colored
stormwater ponds, positively correlated with TN concentrations in clear ponds,
negatively correlated with TN concentrations in colored ponds, and positively correlated
with chlorophyll-a concentrations in clear and colored ponds. Grass clippings were
present in 73% of the ponds when sampled and the presence of grass clippings was
inversely correlated with TP and TN concentrations and positively correlated with
chlorophyll-a concentrations within stormwater ponds.
Results suggest littoral shelf coverage is an important driver of nutrient and
chlorophyll concentrations. Littoral shelves may provide some of the nutrient removal
benefits of wetlands as runoff enters a stormwater pond, assimilating nutrients and
leading to low concentrations of TP and inorganic N (Graves, Wan, & Fike, Water
quality characteristics of storm water from major land uses in South Florida, 2004). The
shallow areas in littoral shelves increase the area of contact between the water column,
soil, and vegetation, and increase the potential of nutrient assimilation (Baldwin,
Simpson, & Weammert, 2009; DB Environmental, Inc., 2005). These shallow areas also
reduce the velocity of incoming runoff and may allow suspended particles and the
associated nutrients to settle out of the water column (Brix, 1993; Schueler T. , 1992).
Moreover, denitrification processes within the wetland-like area can lead to additional
nitrogen removal and low nitrate-nitrite N concentrations in wetland runoff (Graves,
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Wan, & Fike, Water quality characteristics of storm water from major land uses in South
Florida, 2004; Hammer & Bastian, 1989). Additional to nutrient mitigation, emergent
littoral shelf vegetation has been found to reduce chlorophyll-a concentrations by
outcompeting algae for light and nutrients (DB Environmental, Inc., 2005; van Donk &
van de Bund, 2002), producing allelopathic substances (Jasser, 1995; Wium-Anderson,
Christophersen, & Houen, 1982), and supporting algae grazing communities (van Donk
& van de Bund, 2002).
Consequently, emergent and vegetative coverage of littoral shelves and pond
shoreline were identified as significant drivers of nutrient and chlorophyll-a
concentrations in stormwater ponds. Planted littoral shelves were found to be a
significant predictor of TN concentration in clear stormwater ponds, with TN
concentrations inversely correlated with plant coverage. Shoreline plantings coverage
was a significant predictor of algae growth and was inversely correlated with
chlorophyll-a concentrations. Submerged aquatic vegetation was found to be a
significant predictor of TP and chlorophyll-a concentrations in clear stormwater ponds,
with TP and chlorophyll-a concentrations inversely correlated with submerged aquatic
vegetation coverage. Prior research indicates increased phosphorus levels in the water
column are not directly linked to the increased growth of submerged aquatic vegetation
as they obtain most of their phosphorus from the sediments (Cooke, Welch, Peterson, &
Newroth, 1993), but submerged aquatic vegetation is able to alter the physicochemical
environment of water, resulting in chemical precipitation (Reddy, Kadlec, Flaig, & Gale,
1999).
78
Results also suggest grass clippings are an important driver of nutrient and
chlorophyll concentrations in stormwater ponds. The presence of grass clippings was a
significant predictor of TP concentration in colored stormwater ponds, TN
concentrations in clear and colored ponds, and chlorophyll-a concentrations in clear
ponds. Although grass clippings provide additional nutrients to the water column as they
decompose (Bedan & Clausen, 2009), the presence of grass clippings was negatively
correlated with TP and TN concentrations but positively correlated with chlorophyll-a
concentrations within stormwater ponds. These correlations could potentially be
explained by the presence and growth of epiphytic or filamentous algae on subsurface
grass clippings, but the presence of grass clippings and water column nutrient
concentrations should be further investigated to identify the dynamics of grass clipping
nutrient fate.
Several other variables were identified as significant drivers of TN, TP and/or
chlorophyll-a concentrations. Residential fertilizer application was a significant predictor
of both TN and TP concentrations in the stormwater ponds. Residential application of
nitrogen and phosphorus fertilizer was assumed to cease during the months of the
Manatee County fertilizer ordinance, from June 1st to September 30th (Manatee County,
2011), and the presence of this fertilizer restriction was inversely correlated with TP
concentrations in clear stormwater ponds and TN concentrations in both clear and
colored ponds. Even though regulatory controls are considered generally ineffective in
managing non-point source pollutants from stormwater with no clear point of origin
(Taylor & Wong, 2002), fertilizer restrictions may have a positive impact on immediately
receiving waters by reducing the nutrient loads to the landscape. Removing or limiting
79
external loading of nutrients to the watershed may thus reduce the runoff into
stormwater ponds.
Chlorophyll-a concentration was a significant predictor of nutrient concentrations,
positively correlated with TP concentrations in clear and colored stormwater ponds and
TN concentration in clear ponds. The modeling results align with previous studies as
nitrogen and phosphorus are recognized as drivers of chlorophyll-a concentrations in
freshwater lake systems (Sakamoto, 1966; Dillon & Rigler, 1974; Brown, Hoyer,
Bachmann, & Canfield, 2000; Florida Department of Environmental Protection , 2012)
and stormwater ponds (Nealis, Clark, Monaghan, Hochmuth, & Frank, 2016).
Interestingly, filamentous algae coverage was identified as a significant predictors of TN
in clear stormwater ponds and was negatively correlated with increases in TN
concentrations. Filamentous algae is a recognized aesthetic concern in stormwater
ponds and its growth, nutrient response and aesthetic impact in stormwater ponds
should be further researched.
The presence of bank erosion surrounding the stormwater pond was also a
significant predictor of TP and TN concentrations in clear stormwater ponds and was
inversely correlated with water column nutrient concentration. The models’ suggested
relationship is contrary to expectations as eroded soil particles and organic matter can
be important contributors of nitrogen and phosphorus to the aquatic system (Daniel,
Sharpley, Edwards, Wedepohl, & Lemunyon, 1994; Sharpley, et al., 1994; Quinton,
Govers, Van Oost, & Bardgett, 2010), especially during large rain events causing major
erosion and runoff (Pionke, Gburek, Sharpley, & Zollweg, 1997). Shoreline erosion may
contribute additional organic matter and soil particles to the stormwater pond littoral
80
areas, supporting denitrification and providing additional sorption sites, but additional
research should be conducted to identify a possible explanation.
The limiting nutrient status of the stormwater pond was a significant predictor of
phosphorus and chlorophyll-a concentrations in clear and colored ponds. Phosphorous
is usually identified as the limiting nutrient in freshwater systems and driver of algal
production (Schindler, 1977; Schindler, 1974; Canfield, 1983; Mazumder & Havens,
1998). Chlorophyll-a response to increasing TP concentrations in freshwater lakes can
be reduced by nutrient limitation (Canfield, 1983), so stormwater ponds in this study
were categorized as nitrogen limited (N:P<7:1), phosphorus limited (N:P>20:1) or co-
limited (7:1<N:P<20:1) (Guildford & Hecky, 2000). Co-limitation, the constraint on algal
production by the synergistic interaction between nitrogen and phosphorus, occurs often
in freshwater lakes (Harpole, et al., 2011; Maberly, King, Dent, Jones, & Gibson, 2002).
Nitrogen limitation in freshwater systems can result from an over-abundance of
available phosphorous (Schindler, 1971) and models for TP in clear and colored
stormwater ponds suggested nitrogen limited ponds were correlated with an increase in
TP concentrations whereas ponds identified as phosphorus or co-limited had a negative
correlation with TP concentrations.
Various surrounding land uses were identified as significant predictors of nitrogen
and chlorophyll-a concentrations in clear and colored stormwater ponds, though the
correlation with nutrient concentrations was not in complete accordance with
established nutrient-development relationships. Previous studies report increased
impervious surface cover and land use intensity will increases nutrient runoff (Carey, et
al., 2011; Schiff & Benoit, 2007; Brown & Vivas, 2005), but the stormwater pond models
81
suggest the opposite, with the exception of low-intensity transportation land use. The
percent land use in natural area/wetland were positively correlated with TN and
chlorophyll-a concentrations in stormwater ponds while the percent land in low-intensity
commercial use and percent land use in high-density residential use were inversely
correlated with TN and chlorophyll-a concentrations. As expected, the percent of the
surrounding 100 meter buffer in low-intensity transportation, or paved roads, was
positively correlated with TN concentrations in clear and colored stormwater ponds.
Since the contributing landscape surrounding the stormwater ponds is designed to
direct runoff flows to specific stormwater ponds, the landscape use in the 100 meters
surrounding the pond may have less impact on the nutrient concentrations within the
pond than the adjacent land use as runoff may be directed to other stormwater ponds.
The percent adjacent natural area was a significant predictor of TN and chlorophyll-a
concentrations in colored stormwater ponds and the inverse correlation suggests the
low impact of this land use.
Evidence of chemical treatment to the pond, either visual or recorded, was a
significant predictor of algal growth, inversely correlated with chlorophyll-a
concentrations in clear stormwater ponds. The negative impact of chemical treatment
on chlorophyll-a concentrations suggests anthropogenic intervention suppresses algal
response to nutrient concentrations within stormwater ponds, supporting claims made
by Nealis et al. (2016). This evidence is important to consider when identifying nutrient-
response relationships and establishing nutrient management thresholds for stormwater
ponds as the actual response in untreated ponds may be different than those without
chemical intervention.
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Several other measured variables were significant predictors of individual algae
and nutrient concentrations and warrant further investigation. Stormwater pond area
and the proportion of the stormwater pond area in relation to the surrounding 100 meter
contributing area were identified as significant predictors of TP in colored systems.
Additionally, the use of artificial aeration was a significant predictors of TN in clear or
colored stormwater ponds, with both positive and negative impact on water column TN
concentration. Aeration can impact nutrient release by increasing the oxidation of
organic sediments and removing anaerobic areas necessary for denitrification, but
further research should be conducted to evaluate the impact of aeration devices on
water column nutrient concentrations.
Further investigation of all the bivariate relationships between identified individual
significant predictor variables and nutrient or chlorophyll concentrations is necessary.
However, recognizing the importance of these identified variables as drivers in
stormwater pond systems offers an improved prediction of TN, TP and chlorophyll-a
concentrations within clear and colored stormwater ponds.
Conclusion
This study evaluated the impact of management and landscaping decisions on
stormwater pond nutrient and chlorophyll-a concentrations to identify significant
predictor variables of TP, TN and chlorophyll-a water column concentrations within clear
and colored stormwater ponds. Using the significant predictor variables, models were
developed to provide more accurate, site specific nutrient and water column algae
predictions to aid and improve management of stormwater pond function, use and
aesthetics.
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Table 3-1. Management and landscaping variables evaluated for significance as predictors of total phosphorus, total nitrogen and chlorophyll-a concentrations in stormwater ponds.
Variable Description Chemical treatment CT Presence of chemical treatment was determined at each site by blue
water column coloring, indicating dye for clarity and/or algae treatment, or if chemical treatment was performed and recorded by the pond management company within 6 weeks prior to the sampling date. Pond management company records were not always consistent with visual evidence of treatment. Presence of treatment was coded with “1” and absence of treatment was coded with “0.”
Residential landscape fertilizer application
RF Residential fertilizer application of fertilizer containing nitrogen and/or phosphorus was assumed to cease during the months of the Manatee County fertilizer ordinance, from June 1st to September 30th (Manatee County, 2011). Sampling events during the ordinance were coded with “1”. Fertilizer application was assumed to occur during the remaining, non-restriction months and sampling events were coded with a “0.”
Aeration AE The presence of aeration devices within the stormwater pond was coded with “1” and absence of aeration was coded with “0.” Aeration devices included subsurface and surface aerators.
Chlorophyll-a concentration
CHL Concentration of chlorophyll-a (µg·L-1) were measured at a depth 0.60 m using the WET Labs ECO Triplet optical instrument. The WET Labs ECO Triplet-w measured chlorophyll-a concentration every 30 seconds for 3 minutes and mean values were calculated for each sampling station This variable was not included in the evaluation of chlorophyll-a concentrations predictor variables.
Natural land/open water land use
NL Percent coverage of land in open water, upland, or wetland with very low manipulations within 100 meters of the stormwater pond (Brown & Vivas, 2005). Land use coverage was evaluated with GIS software.
Recreational/open land- low intensity
RL Percent coverage of land in areas maintained as natural areas and undeveloped land with natural within 100 meters of the stormwater pond (Brown & Vivas, 2005). Land use coverage was evaluated with GIS software.
Recreational/open land- medium intensity
RM Percent coverage of land in areas with grassy lawns, land that has been cleared and prepared for construction, and human-created water bodies (stormwater ponds) within 100 meters of the stormwater pond (Brown & Vivas, 2005). Land use coverage was evaluated with GIS software.
Recreational/open land- high intensity
RH Percent coverage of land used for recreation fields and golf courses within 100 meters of the stormwater pond (Brown & Vivas, 2005). Land use coverage was evaluated with GIS software.
Single family residential- high density
HD Percent coverage of land in areas used for residential units with a density of more than 20 units/ha within 100 meters of the stormwater pond (Brown & Vivas, 2005). Land use coverage was evaluated with GIS software. All residential property in the community was included in this category.
Commercial- low intensity
CL Percent coverage of land in areas used for commercial business within 100 meters of the stormwater pond (Brown & Vivas, 2005). Land use coverage was evaluated with GIS software.
Transportation- low intensity
TL Percent coverage of land in driveways and paved roads with no more than 2 lanes within 100 meters of the stormwater pond (Brown & Vivas, 2005). Land use coverage was evaluated with GIS software.
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Table 3-1. Continued Variable Description Transportation- high intensity
TH Percent coverage of land in paved roads with more than 2 lanes, including the shoulder, within 100 meters of the stormwater pond (Brown & Vivas, 2005). Land use coverage was evaluated with GIS software.
Stormwater pond SW Area of stormwater pond of interest in proportion to surrounding 100 meters. Land use coverage was evaluated with GIS software.
Floating filamentous algae coverage
FA Percent coverage of shoreline water in floating filamentous algae. Shoreline water was defined as the 2 meters extending into the stormwater pond from the water’s edge. Coverage was visually estimated on site.
Submerged aquatic vegetation
SAV Percent coverage of the visible sub-surface sediment by submerged aquatic vegetation. Visible sub-surface sediment was defined as the 3 meters extending into the stormwater pond from the water’s edge. Coverage was visually estimated on site.
Bank erosion BE The presence of surrounding bank erosion was documented and coded with “1” if there was any evidence of soil erosion within five meters of the stormwater pond perimeter. The absence of erosion was coded with “0.”
Grass clippings GC The presence of grass clippings within the stormwater pond was documented and coded with “1” if clippings were identified on the pond surface or settled to the pond sediment. The absence of grass clippings was coded with “0.”
Littoral shelf coverage
LS The percent coverage of total stormwater pond area consisting of littoral shelf. This value was determined using “as built” development documents and on-site visual evaluation.
Littoral shelf plantings LP The percent of the littoral shelf planted in emergent vegetation was visually evaluated during each sampling event.
Shoreline plantings SP The percent of the stormwater pond shoreline edge planted with vegetation other than turfgrass. Shoreline edge was defined as 1 upland meter from the water’s edge. Shoreline plantings were evaluated during each sampling event.
Adjacent homes HO The percent of the area immediately surrounding the stormwater pond in residential homes, lawns and driveways. Evaluated visually on-site.
Adjacent golf course GO The percent of the area immediately surrounding the stormwater pond in use as a golf course. Evaluated visually on-site.
Adjacent natural area NA The percent of the area immediately surrounding the stormwater pond preserved as a natural area. Evaluated visually on-site.
Adjacent roads RO The percent of the area immediately surrounding the stormwater ponds in use as paved roadway. Evaluated visually on-site.
Pond size PS The total area of the pond as defined by community development and pond management documents.
Nutrient Limitation LM Using corresponding TN and TP concentrations (Nealis, Clark, Monaghan, Hochmuth, & Frank, 2016), ponds were categorized as nitrogen limited (N:P<7:1), phosphorus limited (N:P>20:1) and co-limited (7:1<N:P<20:1) (Guildford & Hecky, 2000).
Total nitrogen concentration
TN From Nealis et al. (2016), concentration (mg·L-1) analyzed by the University of Florida Analytical Research Lab following EPA Methods 351.2 (TKN) and 353.2 (NOx-N) to determine TN. Not included as predictor of total nitrogen or total phosphorus.
Total phosphorus concentration
TP From Nealis et al. (2016), concentration (mg·L-1) analyzed by the University of Florida Analytical Research Lab following EPA Method 365.1. Not included as predictor of total nitrogen or total phosphorus.
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Table 3-2. Empirical models and summary statistics describing the association of
monthly average nutrient and chlorophyll concentrations using significant management and landscaping predictors from stormwater ponds in southwest Florida (Nealis, Clark, Monaghan, Hochmuth, & Frank, 2016).
Variable Pond Model n F p > F r2
Phosphorus (mg·L-1)
Clear TP =0.075 -0.005RF +0.001CHL -0.010SAV -0.009BE + LM (0.068 IF N-Limited, -0.021 IF Co-Limited, -0.047 IF P-Limited)
87 42.92 <0.001 0.76
Colored TP =0.109 -0.116SW +0.001CHL -
0.016GC -0.041LS +0.004PS +LM (0.079 IF N-Limited, -0.016 IF Co-Limited, -0.063 IF P-Limited)
120 71.03 <0.001 0.82
Nitrogen (mg·L-1)
Clear TN =1.06 -0.19RF +0.63AE +1.28TL –2.76CL +0.01CHL –2.65FA –0.24BE +0.56LS –0.18LP
87 8.08 <0.001 0.49
Colored TN =1.02 -0.15RF -0.25AE +5.27TL -
1.63HD +2.88NL -0.18GC -0.57LS -1.42NA
120 6.25 <0.001 0.31
Chlorophyll-a (µg·L-1)
Clear CHL =-2.90 -1.62CT +27.41RL -39.24CL -2.62SAV +2.33GC +12.46LS +6.31HO +1.07LM +50.40TP
87 8.87 <0.001 0.51
Colored CHL =10.48 -26.29HD +20.38NL
+7.81LS -4.45SP +6.71HO -8.28NA -2.07LM
120 7.54 <0.001 0.32
Coefficient abbreviations are identified in Table 3-3.
86
Table 3-3. Summary statistics for significant predictor variables of total phosphorus,
total nitrogen and chlorophyll-a stormwater pond models in southwest Florida
Model Variable Estimate SE t-ratio >|t| Phosphorus, Clear Residential Fertilizer RF -0.005 0.003 -1.56 =0.12 (mg·L-1) Chlorophyll-a CHL 0.001 0.001 2.88 <0.01 Sub. Aquatic Veg. SAV -0.010 0.004 -2.81 <0.01 Bank Erosion BE -0.009 0.004 -2.41 <0.05 N-Limited LM 0.068 0.006 11.32 <0.001 Co-Limited LM -0.021 0.004 -5.78 <0.001 P-Limited LM -0.047 -- -- -- Phosphorus, Colored Stormwater Pond SW -0.116 0.043 -2.71 <0.01 (mg·L-1) Chlorophyll-a CHL 0.001 0.001 2.95 <0.01 Grass Clippings GC -0.016 0.005 -3.41 <0.001 Littoral Shelf LS -0.041 0.015 -2.72 <0.01 Pond Size PS 0.004 0.003 1.54 =0.13 N-Limited LM 0.079 0.005 14.46 <0.001 Co-Limited LM -0.016 0.004 -3.81 <0.001 P-Limited LM -0.063 -- -- -- Nitrogen, Clear Residential Fertilizer RF -0.188 0.07 -2.73 <0.01 (mg·L-1) Aeration AE 0.625 0.21 2.97 <0.01 Transportation, L.I. TL 1.278 0.63 2.02 <0.05 Commercial, L.I. CL -2.759 1.09 -2.54 <0.05 Chlorophyll-a CHL 0.014 0.01 2.06 <0.05 Filamentous Algae FA -2.651 0.67 -3.96 <0.001 Bank Erosion BE -0.237 0.09 -2.70 <0.01 Littoral Shelf LS 0.563 0.37 1.53 =0.13 Littoral Shelf Planted LP -0.191 0.83 -2.28 <0.05 Nitrogen, Colored Residential fertilizer RF -0.147 0.08 -1.86 <0.10 (mg·L-1) Aeration AE -0.248 0.12 -2.07 <0.05 Transportation, L.I. TL 5.269 1.16 4.55 <0.001 Residential, H.D. HD -1.625 0.81 -2.02 <0.05 Natural/Wetland NL 2.882 0.78 3.69 <0.001 Grass Clippings GC -0.176 0.10 -1.83 <0.10 Littoral Shelf LS -0.573 0.26 -2.23 <0.05 Adj. Natural Area NA -1.425 0.38 -3.75 <0.001 Chlorophyll-a, Clear Chemical Treatment CT -1.625 0.86 -1.54 =0.13 (µg·L-1) Recreational, L.I. RL 27.405 5.51 4.97 <0.001 Commercial, L.I. CL -39.235 13.80 -2.84 <0.01 Sub. Aquatic Veg. SAV -2.619 1.06 -2.47 <0.05 Grass Clippings GC 2.330 0.89 2.61 <0.05 Littoral Shelf LS 12.464 4.51 2.76 <0.01 Adj. Homes HO 6.312 2.06 3.06 <0.01 Nutrient Limitation LM 1.071 0.63 1.69 <0.10 Total Phosphorus TP 50.400 20.32 2.48 <0.05
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Table 3-3. Continued Model Variable Estimate SE t-ratio >|t| Chlorophyll-a, Residential, H.D. HD -26.295 10.25 -2.57 <0.05 Colored Natural/Wetland NL 20.382 8.66 2.35 <0.05 (µg·L-1) Littoral Shelf LS 7.807 3.14 2.48 <0.05 Shoreline Plantings SP -4.445 1.83 -2.43 <0.05 Adj. Homes HO 6.713 3.39 1.98 <0.10 Adj. Natural Area NA -8.281 4.73 -1.75 <0.10 Nutrient Limitation LM -2.069 0.46 -4.46 <0.001
Descriptions of variables located in Table 3-3.
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Figure 3-1. Variables identified as significant predictors of phosphorus, nitrogen and chlorophyll-a concentrations in stormwater ponds. Arrows indicate positive, negative or both positive and negative variable coefficients.
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CHAPTER 4 CREATING A COMMUNITY-BASED CHLOROPHYLL-A THRESHOLD FOR
STORMWATER PONDS
Introduction
Nutrient-response relationships are commonly utilized by researchers and water
resource managers to develop standards and criteria protecting water quality.
Relationships between water column nutrient concentrations and the response variable
are measured directly or estimated and regression models are established to estimate
response variable concentrations based on quantifiable nutrient concentrations (Hoyer,
Frazer, Notestein, & Canfield, 2002). The desired use of a water body should then be
identified to determine how water quality is defined (Hoyer, Brown, & Canfield, 2004).
Once water quality is defined, a management criteria can be established identifying
nutrient or response variable concentration thresholds protective of desired conditions,
dependent on use or water body type.
Designated uses and nutrient-response relationships were used in this manner to
establish protective criteria for natural, freshwater lakes in Florida. The United States
Environmental Protection Agency (EPA) published numeric nutrient criteria (NNC)
establishing numeric water quality criteria for nutrients and response variables,
specifically chlorophyll-a, interpreting narrative criteria for Class I and III surface waters
based upon Florida Department of Environmental Protection (FDEP) research and
recommendations (Florida Department of Environmental Protection , 2012). The annual
geometric mean chlorophyll-a concentration was chosen by FDEP as the biological
response variable to relate total nitrogen (TN) and total phosphorus (TP) concentration
because of the strong, predictable correlation (Florida Department of Environmental
Protection , 2012). A chlorophyll-a value of 20µg·L-1 was selected for colored (>40
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platinum cobalt units, PCU) and highly alkaline, clear (≤40 PCU) lakes in Florida based
on several lines of evidence, including user perception and protection of designated use
(Florida Department of Environmental Protection , 2012).
Although stormwater ponds are increasingly treated and valued as freshwater
lakes in Florida, they do not fall under the same protective criteria as natural lakes.
Stormwater ponds in Florida are increasingly utilized in developments for purposes
other than their permitted requirement of removing at least 80% of the annual average
pollutant load (Livingston & McCarron, 1992). Residents value stormwater ponds as
landscape features, providing recreational and economic value to their residential
communities (DeLorenzo, Thompson, Cooper, Moore, & Fulton, 2012; Serrano &
DeLorenzo, 2008), but unlike natural lakes, water quality standards and designated
uses within stormwater ponds are not protected or defined. Use and aesthetic
expectations of stormwater ponds appear to be similar to natural, freshwater lakes, but
the maintenance for aesthetic expectations may impact stormwater pond treatment
function and increase the likelihood that these ponds will fail to meet required TN and
TP removal efficiencies (Harper & Baker, 2007).
Currently, aesthetic expectations of stormwater ponds are often maintained
through biological response suppression. Algal blooms in stormwater ponds due to high
water column nutrient concentrations are typically controlled through chemical
treatments to meet aesthetic and recreational demands, temporarily removing the
biological uptake nutrient removal pathway (Harper & Baker, 2007). Identifying a
biological endpoint similar to the NNC would provide clear guidance to improve
management and maintenance of ponds nutrient concentrations to identify quantifiable
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nutrient goals protective of both pond use expectations and downstream, natural water
bodies. The stormwater pond regulatory requirements of nutrient removal and social
expectations of aesthetics and attaining use objectives would no longer have to be
mutually exclusive.
Identifying the designated uses of stormwater ponds and establishing a biological
endpoint protective of those uses and preferences is essential for improving stormwater
pond management and ensuring maintenance of the permitted function. Surveys of lake
users regarding lake use, water quality and water chemistry have been conducted
(Heiskary & Walker, 1988; Smeltzer & Heiskary, 1990; Hoyer, Brown, & Canfield, 2004)
and have contributed to establishing the biological response threshold of impairment for
the NNC protecting natural Florida lakes (Florida Department of Environmental
Protection , 2012). In this study, a survey was conducted to determine a community-
based chlorophyll-a threshold, or biological endpoint, for stormwater ponds in a large,
southwest Florida community. Additionally, the impact of education on chlorophyll-a
threshold and/or the presence of submerged aquatic vegetation on participant identified
thresholds was evaluated. Finally, the influences of pond use, knowledge of stormwater
pond function and demographic background on preferred threshold were determined.
Methods
This study was conducted in a large community within the Tampa Bay
watershed, covering 8,500 acres with a growing population of over 15,000 residents.
The community includes thousands of homes, over 300 stormwater ponds, multiple
parks, several natural areas, and two golf courses. Stormwater ponds are an important
component of the community as they provide aesthetic, recreational and economic
value to residents and homeowners. Many homeowners paid premiums to have
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waterfront property on stormwater ponds, but most ponds in the community are easily
visible and accessible to all residents.
An internet-based (Qualtrics, 2015) survey evaluating stormwater pond use,
knowledge and perceptions was distributed via email to a purposive sample (Ary,
Jacobs, & Razavieh, 2002) of residents on the community email listserv and conducted
between October 23, 2014 and November 7, 2014 in accordance with established
protocol (Dillman, 2007). The survey included questions regarding pond use,
stormwater pond knowledge, demographic information, and one question to identify the
acceptable biological endpoint, or “treatment threshold,” for managing stormwater
ponds.
To identify the acceptable biological endpoint, participants were randomly
assigned one of four treatments examining the impact of pre-question education and
chlorophyll-a concentration presentation. For the pre-question education treatment,
participants were randomly assigned either a question preface providing education
regarding algae and nutrient enrichment or a question preface with no educational
information. The educational statement was:
Algae can be found in most natural lakes and ponds in Florida. Algae blooms can occur when large amounts of nutrients enter a water body. These nutrients come from all parts of the land that drain to the pond, even if the land may be located some distance away. Activities within this area, including fertilizer use, can provide nutrients to the pond if they are not managed appropriately. Algae growth in stormwater ponds, as well as natural lakes, helps to take up nutrients in runoff and protects downstream natural resources by acting as a filter. When the nutrient supply to the pond is reduced, algae blooms can become less frequent and less intense.
The educational component explained the response of algae to water column nutrients,
the natural occurrence of algal blooms in some Florida lakes, and the role of algae and
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submerged aquatic vegetation in reducing water column nutrient concentrations. For the
chlorophyll-a concentration presentation, survey participants were also randomly
assigned one of two series of ten images depicting chlorophyll-a concentrations
increasing in increments of five from 5 µg·L-1 to 50 µg·L-1 in a water column over a
sandy bottom. Participants were asked to identify the chlorophyll-a concentration at
which water quality became unacceptable, or the “treatment threshold.” One of the two
series of images included submerged aquatic vegetation over the sandy bottom to
provide a focal item for clarity perspective (Figure 4-1) and the other series of photos
contained no item atop the sandy bottom (Figure 4-2). To create the series of images, a
0.50 m diameter, 1.00m tall clear, acrylic cylinder with a sand-covered bottom was used
to create a 0.75 m water column of varying chlorophyll-a concentrations, increasing in
increments of five from 5 µg·L-1 to 50 µg·L-1. An initial chlorophyll-a concentration of 50
µg·L-1 was confirmed using the WET Labs ECO Triplet-w optical instrument and a
dilution factor was used to create decreasing chlorophyll-a concentrations. Photographs
were taken of the water column from 0.20 m above the water surface with a digital
camera under similar combined natural and artificial lighting.
Statistical computations were performed using the JMP statistical package (SAS
Institute, 2009) by University of Florida Department of Statistics Statistical Consulting. A
comparison of means was used to examine the difference between the mean identified
threshold for each treatment and that for natural, Florida lakes. Pairwise comparison
and Tukey-Kramer grouping for least square means (α=0.05) were conducted for each
treatment to evaluate differences in mean identified thresholds for each treatment
groups and assess impact of image selection and pre-question education on response.
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Additionally, the GLIMMIX procedure (SAS Institute, 2005) was conducted to fit general
linearized mixed models to the treatment data to compare resident identified
chlorophyll-a thresholds for different pond uses and demographic categories utilizing the
Tukey-Kramer Grouping for Treatment Least Squares Means (α=0.10).
Results and Discussion
The internet-based survey was distributed to 3,848 residents and received 712
responses for a response rate of 18.5%. The low response rate may suggest the
influence of a non-response bias on the resulting data. Of the 712 responses, 578 were
complete for a completion rate of 81%. Data processing refined the raw survey data,
coding and categorizing free response questions and removing unrecognizable
responses.
Identified Mean Treatment Thresholds
One survey item asked the participant, “From completely clear to water colored
green from algae, how green does your pond (or pond in your neighborhood) get before
you think it needs treatment?” The responses were designed to depict a gradient in
water column chlorophyll-a concentrations, from a 5 µg·L-1 to 50 µg·L-1 and determine
the biological endpoint, or treatment threshold, at which conditions became
unacceptable. There were four potential treatments applied at random to the survey
item for each participant; (1) the photos in the item had no submerged aquatic
vegetation in the water column and the question had no educational component (NN),
(2) the photos in the item had no submerged aquatic vegetation in the water column and
the question was prefaced with an algae educational component (NE), (3) the photos in
the item contained submerged aquatic vegetation in the water column and the question
had no educational component (VN), and (4) the photos in the item contained
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submerged aquatic vegetation in the water column and the question was prefaced with
an algae educational component (VE).
A comparison of least squares means (α=0.05) was conducted to determine if
the chlorophyll-a concentration treatment threshold for stormwater ponds was
significantly different than Florida’s numeric nutrient criteria (NNC) threshold of 20 µg·L-1
for natural lakes. A pairwise comparison of least square means using the Tukey-Kramer
HSD, α=0.05, compared the treatment thresholds identified by the different survey
treatment groups (Figure 4-3).
The mean identified treatment thresholds for stormwater ponds are similar to
previous findings establishing chlorophyll-a concentration values protective of
recreational and aesthetic values between 20 and 30 µg·L-1 (Hoyer, Brown, & Canfield,
2004; Glass, 2006) but greater than the 20 µg·L-1 criteria established to protect natural
Florida lakes (United States Environmental Protection Agency, 2010). The community-
based treatment threshold could be coupled with associated nutrient data to develop a
stormwater pond numeric criteria similar to the NNC to create management criteria
protective of the desired water quality.
The comparison of survey treatment groups revealed the impact of presentation
when identifying the treatment threshold. Respondents asked to identify treatment
threshold when provided with no prior education and no aquatic vegetation in the photo
indicated thresholds significantly greater than individuals provided with photos
containing aquatic vegetation, regardless of the inclusion of pre-question algae
educational information. Respondents asked to identify preferred treatment threshold
when provided with education and no aquatic vegetation in the photo indicated a
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significantly higher treatment threshold than individuals provided a photo with aquatic
vegetation and education. Results suggest the presence of aquatic vegetation in the
survey images reduces the preferred treatment threshold. Additionally, pre-question
education regarding algae and nutrients does not have a significant effect on preferred
treatment threshold.
Even though the preference for submerged aquatic vegetation can vary among
lake users (Richardson, 2008), research by Kaplan et al. (1972) suggest more complex
natural scenes presented in images are preferred by individuals. The submerged
aquatic vegetation becomes more difficult to see in the series of images presented in
the survey as the chlorophyll-a concentration increases, whereas no natural item
provides perspective as the chlorophyll-a concentration increases in the other series of
images. An increase in algae and decrease in water clarity have been identified as
indicators of poor water quality (David, 1971; Moser, 1984), especially when the waters
are used for recreational purposes (Hoyer, Brown, & Canfield, 2004), and the increase
may be more evident when submerged aquatic vegetation provides a preferred focal
point for comparison. Additionally, the educational treatment provided pre-question did
not have a significant effect on the treatment threshold and did not change respondent
perspective. The lack of impact is not unexpected, especially considering the question
queried participants regarding personal pond preference and research has
demonstrated individuals are less environmentally conscious concerning issues
immediately related to their personal lives and material ambitions (Rickinson, 2001).
Impact of Pond Use on Mean Treatment Threshold
One survey item asked participants how frequently over the prior year they used
their stormwater pond for several specific uses, including birdwatching, fishing, watching
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the sun set/rise, relaxing, walking and picnicking. Respondents indicated the frequency
on a seven-point scale ranging from never to daily. Stormwater pond use responses
were reduced to three categories for statistical analysis; (1) never, (2) occasional, and
(3) frequent. “Occasional” was defined as less than once a month but not as often as
once a week and “frequent” was defined as at least once a week.
A GLIMMIX procedure (SAS Institute, 2005) was conducted to fit general
linearized mixed models to the four sets of treatment data (NN, NE, VN, VE) associated
with each individual’s response to effectively compare mean resident identified
treatment thresholds for different stormwater pond uses and frequency of use (Figure 4-
4) utilizing the Tukey-Kramer Grouping for Treatment Least Squares Means (α=0.10).
The comparison between use frequency treatment threshold means for “birdwatching”
revealed no significant difference between the use categories of frequent (n=355,
M=24.4µg·L-1, SE=0.65), occasional (n=150, M=23.3µg·L-1, SE=1.00) and never
(n=102, M=21.5µg·L-1, SE=1.35). The comparison between use frequency treatment
threshold means for “fishing” revealed no significant difference between the use
categories of frequent (n=32, M=26.1µg·L-1, SE=2.25), occasional (n=101, M=24.5µg·L-
1, SE=1.20) and never (n=462, M=23.6µg·L-1, SE=0.60). The comparison between use
frequency treatment threshold means for “watching sunset/rise” revealed no significant
difference between the use categories of frequent (n=302, M=24.2µg·L-1, SE=0.70),
occasional (n=144, M=23.6µg·L-1, SE=1.05) and never (n=158, M=23.2µg·L-1,
SE=1.05). The comparison between use frequency treatment threshold means for
“relaxing” revealed frequent users (n=394, M=24.8µg·L-1, SE=0.60) had significantly
higher treatment thresholds than both occasional (t(507)=-2.09, p<0.10; n=99,
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M=22.0µg·L-1, SE=1.25) and non-users (t(507)=-2.51, p<0.05; n=109, M=22.3µg·L-1,
SE=1.30). The comparison between use frequency mean treatment threshold for
“walking” revealed no significant difference between the use categories of frequent
(n=254, M=24.8µg·L-1, SE=0.75), occasional (n=137, M=22.5µg·L-1, SE=1.05), and
never (n=214, M=23.2µg·L-1, SE=0.90). The comparison between use frequency mean
treatment threshold for “picnicking” revealed no significant difference between use
categories of frequent (n=14, M=22.3µg·L-1, SE=3.40), occasional (n=76, M=26.1µg·L-1,
SE=1.35), and never (n=513, M=23.4µg·L-1, SE=0.55). Additionally, a Tukey-Kramer
HSD (α=0.10) was conducted to evaluate the differences between mean treatment
thresholds identified by frequent users for each stormwater pond use category and
found there was no significant difference.
Stormwater ponds in residential and urban developments are valued for their
recreational uses (Serrano & DeLorenzo, 2008). In natural lake systems, user water
quality preference varies based on the use of the system (Ditton & Goodale, 1973;
Parsons & Kealy, 1992), but the data collected suggests there is no significant
difference between water quality preference of different uses when comparing the
treatment thresholds of frequent users. However, frequency of use appears to increase
the tolerance of higher chlorophyll-a concentration values for most uses, significantly so
for the use “relaxing.” Prior research indicates increased frequency of use increases the
tolerance of higher chlorophyll-a concentrations (Smeltzer & Heiskary, 1990; Hoyer,
Brown, & Canfield, 2004) because individuals become accustomed to higher
concentrations of chlorophyll-a. Acceptable water quality for recreation is relative to
users’ experiences (Smeltzer & Heiskary, 1990) and perceptions may be more sensitive
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to changes in water quality parameters from established or expected conditions
(Michael, Boyle, & Bouchard, 2000) than specific levels. The variation of identified
treatment thresholds within each stormwater pond use and frequency of use has been
demonstrated in a similar study on natural Florida lakes (Hoyer, Brown, & Canfield,
2004) and exhibits the variety in individual user preference.
Establishing designated uses for stormwater ponds may provide a strategy for
developing defensible criteria for protecting recreational uses, aesthetic demands and
regulatory nutrient load requirements of stormwater ponds. Results from this study
provide identifiable treatment thresholds dependent on use and frequency of use,
establishing chlorophyll-a concentrations associated with impairment.
Knowledge and Educational Influence on Mean Treatment Threshold
Several survey items asked participants questions evaluating their knowledge of
stormwater ponds. A GLIMMIX procedure (SAS Institute, 2005) was conducted to fit
general linearized mixed models to the four sets of treatment data (NN, NE, VN, VE)
associated with each individual’s response to effectively compare mean resident
identified treatment thresholds for participant responses to the knowledge and
education questions utilizing the Tukey-Kramer Grouping for Treatment Least Squares
Means (α=0.10).
One survey question asked participants (n=518) if the pond or lake in their
community was natural or created (Figure 4-5). All water bodies in the residential
community are created stormwater ponds. No significant difference (α=0.10) was found
between response variables, however respondents who indicated “natural” had a lower
mean treatment threshold (n=30, M=19.8µg·L-1, SE=2.15) than respondents indicating
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“created” (n=380, M=23.6µg·L-1, SE=0.60) and “I do not know” (n=108, 24.7µg·L-1,
SE=1.10).
Three survey questions queried participants regarding prior education or
awareness of stormwater ponds (Figure 4-6). The first question asked participants
(n=524) if they had received any prior education regarding stormwater ponds. No
significant difference (α=0.10) was found between response variables, however
respondents who indicated they had received prior education had slightly higher mean
treatment thresholds (n=210, M=24.2µg·L-1, SE= 0.80) than respondents indicating they
had not received prior education (n=314, M=23.4µg·L-1, SE=0.65). The second question
asked participants (n=522) if they were provided with any stormwater pond information
by the real estate company when looking to buy or rent their home. Respondents who
indicated they had been provided with stormwater pond information by the real estate
company had a significantly higher, t(514)=1.70, p<0.10, mean treatment threshold
(n=27, M=27.5µg·L-1, SE=2.45) than respondents who indicated they had not been
provided with stormwater pond information (n=495, M=23.55µg·L-1, SE=0.50). The third
question asked participants (n=521) if they were provided with any stormwater pond
information or presentation when moving into their community. No significant difference
(α=0.10) was found between variables, however respondents who indicated they had
received stormwater pond information or presentation when moving into the community
had slightly higher mean treatment thresholds (n=80, M=24.6µg·L-1, SE=1.30) than
respondents indicating they had not received stormwater pond information or
presentation (n=441, M=23.6µg·L-1, SE=0.55).
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One survey question asked participants to identify the function of algae in
stormwater ponds (Figure 4-7). Respondents who identified “filter and uptake nutrients
and pollutants” as the function of algae had a mean treatment threshold significantly
higher (n=139, M=27.6µg·L-1, SE=0.96) than respondents who identified algae function
as “grow out of control and look swampy” (t(502)=4.45, p<0.001; n=165, M=21.8µg·L-1,
SE=0.87), , “decrease property value” (t(502)=3.29, p<0.01; n=48, M=21.4µg·L-1,
SE=1.62), , “smell bad” (t(502)=2.03, p<0.05; n=23, M=22.3µg·L-1, SE=2.39), , and “I
don’t know” (t(502)=3.23, p<0.01; n=147, M=23.3µg·L-1, SE=0.92). There were no
significant differences found between any of the other responses.
Establishing treatment thresholds for stormwater ponds would create quantified
management criteria to improve recreation, aesthetic and nutrient removal functions of
stormwater ponds. Currently, qualitative aesthetic and recreational demands drive
stormwater pond management in residential areas. Biological responses, like algal
blooms, are suppressed with chemical treatments whenever there are complaints.
Removing or limiting the biological response eliminates an important removal pathway
for nutrients and jeopardizes the regulated function of stormwater ponds as treatment
basins (Harper & Baker, 2007).
The current management regime and understanding of pond roles must be
altered to improve pond function. Establishing a community identified treatment
threshold may help, but it is widely recognizing changing the knowledge, opinions, and
behaviors of homeowners regarding management decisions is a significant challenge
(Hostetler & Noiseux, 2010; Youngentob & Hostetler, 2005; Askew & McGuirk, 2004;
Dunlap & Jones, 2003). The challenge is compounded by the lack of knowledge
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regarding stormwater pond function. A notable percentage (27%, n=138) of the
participants were unaware the water bodies in their community were built stormwater
ponds. The lack of awareness coincides with the absence of prior education regarding
stormwater ponds as 60% (n=314) of respondents claim they had received no prior
general stormwater pond education and 85% (n=441) claim they had received no
community specific stormwater pond education or information. Prior education regarding
stormwater ponds should provide individuals with better understanding of stormwater
pond function and design and did result in the acceptance of slightly higher mean
treatment thresholds.
Information and education provided by real estate agencies was found to have a
significant impact on resident identified treatment thresholds. Even though only 5%
(n=27) of respondents indicated they were provided with stormwater pond information
by the real estate company when they were purchasing their home, they identified a
significantly higher treatment threshold than the 95% (n=495) of respondents who
indicated they had received no such information. Individuals purchasing homes on or
near stormwater ponds managed for aesthetic and recreational demands may perceive
these as natural systems and fail to understand their role in treating runoff. People
prefer landscapes they perceive as natural (Dearden, 1987; Herzog, 1989; Kaplan &
Kaplan, 1981; Knopf, 1987; Nassauer, 1995), even if they are not. Even though the
biological response to increased nutrients occurs in natural lakes, the desire to manage
and suppress the response is not surprising as the presence of actual natural
ecosystems and processes in urban settings have been linked to perceived lack of care
(Bos & Mol, 1979; Gobster & Hull, 2000; Misgav, 2000; Nassauer, 2004; Nassauer,
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1993; Williams & Cary, 2002). Increasing the awareness and understanding of the
nutrient removal function of algae in stormwater ponds may increase the acceptable
treatment threshold identified by a community. As demonstrated in this study,
respondents who were aware of the function of algae in stormwater ponds had a
significantly higher mean treatment threshold than all other respondents.
Demographic Drivers of Mean Treatment Threshold
Several demographic questions were included in the survey to evaluate
influences on stormwater pond treatment threshold selection. A GLIMMIX procedure
(SAS Institute, 2005) was conducted to fit general linearized mixed models to the four
sets of treatment data (NN, NE, VN, VE) associated with each individual’s response to
effectively compare mean resident identified treatment thresholds for demographic
questions utilizing the Tukey-Kramer Grouping for Treatment Least Squares Means
(α=0.10) to identify significant differences.
Responses revealed several significant differences in mean treatment thresholds
between demographic groups (Figure 4-7). Seasonal resident respondents had a
significantly lower mean treatment threshold (n=123; M=22.1µg·L-1, SE=1.03),
t(510)=1.87, p<0.10, than year-round resident respondents (n=395, M=24.3µg·L-1,
SE=0.57). Male respondents had a significantly lower mean treatment threshold (n=331,
M=22.5µg·L-1, SE=0.62), t(510)=-3.62, p<0.001, than female respondents (n=187, M=
26.2µg·L-1, SE=0.82). Respondents with children younger than 18 years old living in
their residence had a significantly higher mean treatment threshold (n=73, M=26.4µg·L-
1, SE=1.33), t(510)=2.11, p<0.05, than respondents without young children (n=445,
M=23.4µg·L-1, SE=0.54). Respondents who were older than 64 years had a significantly
lower mean treatment threshold (n=278, 21.7µg·L-1, SE=0.67), t(480)=2.98, p<0.01,
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than respondents who were between 54 and 64 years old (n=126, 25.3µg·L-1, SE=1.00)
and significantly lower, t(480)=4.89, p<0.001, than respondents who were younger than
54 years old (n=88, 28.5µg·L-1, SE=1.21). Several additional demographic responses
did not reveal any significant differences in mean treatment threshold (Table 4-1).
Understanding demographic drivers of preferred treatment thresholds provides
additional guidance improving stormwater pond management by identifying specific
populations with significantly different preferences. Traditionally, lake use has defined
water quality criteria in natural systems for users (Ditton & Goodale, 1973; Smeltzer &
Heiskary, 1990; Parsons & Kealy, 1992; Hoyer, Brown, & Canfield, 2004) and regulators
(Florida Department of Environmental Protection , 2012), but identifying populations that
may be unaccepting of management criteria and adopted treatment thresholds provides
opportunity for focused education and outreach to improve acceptance and
implementation of water quality goals.
The influence of gender and parental status demonstrated in this study (Figure 4-
7) is supported by prior environmental studies. Women have been found to be more
concerned about environmental quality issues than men (McStay & Dunlap, 1983;
Zelezny, Chua, & Aldrich, 2000; Hunter, Hatch, & Johnson, 2004; McCright, 2010) and
the significantly greater treatment threshold identified by female participants may reflect
this concern. Additionally, parents of young children have demonstrated greater
environmental concern and commitment to environmental protection than individuals
without young children (Dupont, 2004; Teal & Loomis, 2000; Hamilton, 1985). The
parental effect even influences the male gender effect, increasing environmental
concern and value (Wilson, Daly, Gordon, & Pratt, 1996).
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The influence of age on preferred treatment threshold is significant (Figure 4-7)
and could be the result of several factors that should be further investigated to improve
understanding of this demographic difference. The negative correlation between age
and willingness to contribute to future environmental protection is well supported
(Samdahl & Robertson, 1989; Whitehead, 1991; Carlsson & Johansson-Stenman,
2000) but recent data has revealed age is positively correlated with environmental
concern (Liu, Vedlitz, & Shi, 2014). A large percentage of respondents greater than 64
years in age (24%) are seasonal residents and half (51%) have lived in Florida for 10
years or less, so their prior experiences and reference conditions may be influencing
their current preferred treatment threshold (Hoyer, Brown, & Canfield, 2004). The
impact of participant residence time is further demonstrated in the significant difference
in treatment thresholds identified by all seasonal and year-round residence (Figure 4-7),
supporting the findings of Hoyer, Brown and Canfield (2004) that suggest lake users are
more tolerant of eutrophic conditions if they are consistently exposed to more eutrophic
conditions. Perception of water quality is relative to experience and exposure.
Conclusion
Establishing designated uses and management criteria similar to natural Florida
lakes (Florida Department of Environmental Protection , 2012) could provide a
framework for protecting aesthetic, recreational and permitted treatment functions of
stormwater ponds. This study presented an approach for identifying a treatment
threshold for stormwater ponds at which the stormwater pond is considered unsuitable
for desired uses as defined by the community. Nearly all of the mean treatment
thresholds identified for stormwater ponds in this study were significantly higher than the
20µg·L-1 chlorophyll-a concentration of Florida’s NNC (Florida Department of
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Environmental Protection , 2012) but were similar to prior studies establishing
chlorophyll-a concentration values protective of recreational and aesthetic values
(Hoyer, Brown, & Canfield, 2004; Glass, 2006). Survey image presentation does have
an influence on respondent identified chlorophyll-a treatment threshold as the presence
of submerged aquatic vegetation did significantly reduce the preferred chlorophyll-a
treatment threshold. Pre-question education regarding the role of algae in stormwater
ponds did not have an effect on the participant identified treatment threshold.
This study also identified the impact of designated uses, educational influences,
and demographic drivers of treatment thresholds that must be considered to
successfully implement a management criteria for stormwater ponds. The frequency of
use for the identified stormwater pond recreational uses had some positive correlation
with treatment thresholds, but the treatment threshold identified by frequent users of
ponds for “relaxing” was the only use found to be significantly higher than less frequent
users. Knowledge of the actual function and role of algae in a stormwater ponds, as well
as prior education of the role of stormwater ponds provided by real estate agencies,
resulted in significantly higher chlorophyll-a treatment thresholds. Finally, several
demographic factors were found to be predictors of significant treatment threshold
differences, including year-round residency, gender, parental status, and age.
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Table 4-1. Demographic survey questions and responses with no significant difference in mean treatment threshold between responses (Tukey-Kramer HSD, α=0.10)
Question
Response
Mean Treatment Threshold (µg·L-1)
SE
Is property adjacent to a pond or lake? (n=523) Yes 23.5 0.60 No 24.5 0.92 Years lived in current home? (n=518) ≤1 25.0 1.57 1.1-5 23.5 0.95 5.1-10 24.3 0.89 10.1-15 22.9 1.05 >15 18.6 3.50 How many years lived in Florida? (n=510) ≤1 26.5 2.46 1.1-5 24.2 1.07 5.1-10 24.25 1.06 10.1-15 22.2 1.04 15.1-20 21.9 1.80 >20 24.8 1.34 Education (n=516) Some college 23.9 1.33 4 yr degree 24.0 0.84 Grad. degree 23.7 0.76 Household income (n=427) <50,000 24.6 3.09 50,000-74,999 27.1 1.87 75,000-149,999 24.3 0.92 >150,000 23.6 0.83
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Figure 4-1. Series of ten photos depicting water column chlorophyll-a concentrations increasing in increments of five from 5 µg·L-1 to 50 µg·L-1 over a sandy bottom including submerged aquatic vegetation.
Figure 4-2. Series of ten photos depicting water column chlorophyll-a concentrations increasing in increments of five from 5 µg·L-1 to 50 µg·L-1 over a sandy bottom.
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Figure 4-3. Comparison of mean chlorophyll-a concentration (µg·L-1) response of four survey treatments. The mean treatment threshold for each survey treatment was compared to the Numeric Nutrient Criteria at 20 µg·L-1 (represented by the red line) and found to be significantly greater for treatments NN, NE, and VN (*** = p<0.001, * = p<0.05). A pairwise comparison of least square means using the Tukey-Kramer HSD, α=0.05, revealed significant differences between survey treatment groups indicated by letters A, B and C.
A*** AB
***
BC*
C
15
20
25
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No education, novegetation in photo (NN)
Education, no vegetationin photo (NE)
No education, vegetationin photo (VN)
Education, vegetation inphoto (VE)
Trea
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Treatment
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Figure 4-4. Comparison of mean treatment threshold based on pond use. A Tukey-Kramer HSD (α=0.10) was conducted to compare the mean treatment threshold for “frequent” use of pond for each desired use and no significant difference was found. For each desired use, a Tukey-Kramer Grouping for Treatment Least Squares Means (α=0.10) was conducted to compare mean treatment thresholds and no significant difference was found between use frequencies for birdwatching, fishing, watching sunset/rise, walking or picnic, however, respondents who frequently used the stormwater pond for relaxing had a significantly higher treatment threshold than respondents using the stormwater pond for relaxing occasionally (p<0.05) and never (p<0.05). The Numeric Nutrient Criteria (NNC) chlorophyll-a concentration threshold of 20 µg·L-1 for natural lake systems is included for reference and visual comparison (horizontal red line).
a
ai
aii
aiii aiv
av
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av
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Birdwatching Fishing WatchingSunset/rise
Relaxing Walking Picnic
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Desired use
FrequentlyOccasionallyNever
A
A
AA A A
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Figure 4-5. Comparison of mean treatment threshold associated with knowledge of stormwater pond origin. A Tukey-Kramer HSD (α=0.10) was conducted to compare the mean treatment threshold between each response and no significant difference was found between the three responses to stormwater pond origin. The red horizontal line representing the NNC at 20µg·L-1 is included for visual comparison.
A
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Natural Created I don't know
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Stormwater pond origin
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Figure 4-6. Comparison of mean treatment threshold associated with stormwater pond
education and awareness. A Tukey-Kramer HSD (α=0.10) was conducted to compare the mean treatment threshold between positive and negative responses to receiving each form of stormwater pond education. No significant difference (α=0.10) was found between individuals who did and did not receive education in the form of prior education or a presentation or information provided prior to moving to the community. Individuals who received stormwater pond educational information from the real estate company prior to purchasing or renting their home (M=27.5µg·L-1, SE=2.45) had significantly higher (p<0.10) mean treatment threshold than those who were not provided with information from the real estate company (M=23.55µg·L-1, SE=0.50). The red horizontal line representing the NNC at 20µg·L-1 is included for visual comparison.
AA
Ai
Aii
Aii
15
20
25
30
Yes No Yes No Yes No
Prior education Real estate information Presentation or informationprior to moving
Trea
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)
Survey item
Bi
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Figure 4-7. Mean treatment threshold associated with resident perceptions of algae
function in stormwater ponds. A Tukey-Kramer HSD (α=0.10) was conducted to compare the mean treatment threshold associated with the selected algae functions in stormwater ponds. Participants who identified algae function as “filter and uptake nutrients and pollutants” had treatment threshold (M=27.6µg·L-1, SE=0.96) significantly greater (p<0.001) than participants who identified algae function as “grow out of control and look swampy” (M=21.8µg·L-1, SE=0.87), “decrease property values” (21.4µg·L-1, SE=1.62), “smell bad” (M=22.3µg·L-1, SE=2.39) and “I don’t know” (M=23.3µg·L-1, SE=0.92). The red horizontal line representing the NNC at 20µg·L-1 is included for visual comparison.
A
B B
BB
15
20
25
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Filter and uptakenutrients and
pollutants
Grow out ofcontrol and look
swampy
Decrease propertyvalues
Smell bad I don’t know
Trea
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ldCh
l-a (u
g/L)
Algae function
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Figure 4-8. Comparison of mean treatment threshold associated with demographic
information. A Tukey Kramer (α=0.10) comparison of least square means for each survey item revealed significant differences between mean treatment thresholds associated with demographic information. The red horizontal line representing the NNC at 20µg·L-1 is included for visual comparison.
A
B
Ai
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Aiii
Biii
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Seasonal Year round Male Female Children No children < 54 years 54-64 years > 64 years
Seasonal or year roundresident
Sex Children under 18 Age
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Survey item
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CHAPTER 5 METHODS FOR IDENTIFYING AND QUANTIFYING IMPACT OF NUMERIC
THRESHOLD IN STORMWATER PONDS
Introduction
Nutrient-response relationships are commonly used by lake managers and
regulatory agencies to predict unwanted algal blooms and implement measures to
control eutrophication. Chlorophyll-a concentration is a highly visible indicator of
eutrophication (Havens, 2003) and is often used as a measure of the algal standing
crop (Dillon & Rigler, 1974). Nitrogen and phosphorus are recognized drivers of
chlorophyll-a response in freshwater lake systems (Sakamoto, 1966; Dillon & Rigler,
1974; Brown, Hoyer, Bachmann, & Canfield, 2000; Florida Department of
Environmental Protection , 2012) and the relationships between total phosphorus (TP),
total nitrogen (TN) and chlorophyll-a concentrations can be used to create regression
models approximating algal response concentrations based on quantifiable nutrient
concentrations (Hoyer, Frazer, Notestein, & Canfield, 2002).
The state of Florida adopted numeric nutrient criteria (NNC) to establish
protective numeric water quality criteria for nutrients and chlorophyll-a in Class I and III
surface waters (Florida Department of Environmental Protection , 2012). A chlorophyll-a
value of 20 µg·L-1 was deemed protective of the designated uses of colored (>40
platinum cobalt units, PCU) and highly alkaline, clear (≤40 PCU) lakes in Florida
(Florida Department of Environmental Protection , 2012) and corresponding nutrient
values were established for TP and TN. To establish the NNC values, FDEP decided to
define a range of 50% probability that a given TN or TP level will elicit the chlorophyll-a
response given the regression equations calculated for the clear and colored lake
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systems when establishing the numeric nutrient criteria (Florida Department of
Environmental Protection , 2012).
Stormwater ponds in Florida are increasingly utilized in developments for
aesthetic and recreational purposes (DeLorenzo, Thompson, Cooper, Moore, & Fulton,
2012; Serrano & DeLorenzo, 2008), but their desired uses and water quality thresholds
are not defined or protected by the same regulations and criteria protecting natural
lakes, even though water quality expectations of stormwater pond users are similar to
natural, freshwater lakes (Nealis, Monaghan, Clark, Hochmuth, & Frank, 2016).
Currently, the only regulatory water quality requirement stormwater ponds must meet is
the removal of at least 80% of the annual average pollutant load (Livingston &
McCarron, 1992). Establishing a nutrient management threshold utilizing stormwater
pond user expectations and nutrient-response relationships would provide the
framework for identifying quantifiable watershed nutrient management goals and
strategies to protect stormwater pond uses and expectations. A stormwater pond
nutrient management criteria and successful management regime could increase the
likelihood that stormwater ponds meet regulatory nutrient removal requirements and
minimize the impact of nonpoint source pollution on downstream water bodies.
A survey conducted by Nealis et al. (2016), found mean chlorophyll-a
concentrations thresholds for a variety of stormwater pond uses and aesthetic
preferences ranged from approximately 20 to 25 µg·L-1 chlorophyll-a while a previous
study revealed the actual mean stormwater pond chlorophyll-a concentration in the
same community was 5.55 ± 0.49 µg·L-1 (SE) for clear systems and 9.12 ± 0.44 µg·L-1
for colored systems (Nealis, Clark, Monaghan, Hochmuth, & Frank, 2016). It is believed
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that low algal responses to nutrients within the ponds are a result of algaecide
applications to meet present aesthetic preferences. However, there appears to be a
discrepancy between the community’s acceptable threshold and the threshold at which
pond managers are treating the ponds. Managing stormwater ponds for the increased
chlorophyll-a concentration could potentially increase the stormwater ponds’ biological
nutrient uptake and removal of nitrogen and phosphorus, assuming algal assimilated
nutrients could potentially increase the stormwater ponds’ removal of nitrogen and
phosphorus, algal assimilated nutrients remain within the stormwater pond and
chlorophyll-a concentrations remain constant.
In this paper, a method is proposed for identifying and quantifying threshold
nutrient levels in stormwater ponds. The proposed method used established nutrient-
chlorophyll-a response relationships (Nealis, Clark, Monaghan, Hochmuth, & Frank,
2016) to create stormwater pond nutrient criteria. These values were then used to
determine the maximum assimilative potential of nutrients if chlorophyll-a levels were
allowed to increase above current management levels.
Methods
Nutrient Management Threshold
Nutrient-response relationships in clear and colored stormwater ponds in a
Southwest Florida community were used to identify TP and TN concentrations
associated with chlorophyll-a thresholds identified by residents as protective of aesthetic
and recreational uses (Nealis, Monaghan, Clark, Hochmuth, & Frank, 2016). The
inverse equations of the nutrient-response relationships established by Nealis et al.
(2016), were calculated to determine the nutrient management criteria for TP and TN
(mg·L-1) in clear and colored stormwater ponds based on community defined
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chlorophyll-a concentration thresholds (µg·L-1). Although not as stringent as the range of
values offered by the NNC, this mean intercept of the nutrient-response relationships
was chosen to simplify management strategies and provide a single defensible
management target to improve current management strategies. After establishing
nutrient management threshold values, the estimated percent of TP and TN assimilated
into algal biomass were calculated to quantify the estimated impact different chlorophyll-
a management thresholds would have on algal nutrient assimilation potential within
clear and colored stormwater ponds.
Nutrient Assimilation Potential
To estimate the fraction of TP likely assimilated in algal biomass, TP was divided
by orthophosphate-phosphorus to identify percentage of TP in inorganic form. The
remaining portion of TP was assumed to be in particulate organic form and associated
with assimilated algal phosphorus (AAP). For each sample, the AAP was calculated and
then divided by TP to identify the percentage of TP assimilated into organic form. To
estimate the assimilated nitrogen values, ammonium-nitrogen (NH3-N) and nitrate-
nitrogen (NOx-N) were subtracted from TN to identify the mass of nitrogen assumed to
be in organic form and associated with assimilated algal nitrogen (AAN). For each
sample, the AAN was calculated and then divided by TN to identify the percentage of
TN assimilated into organic form. The median AAP and AAN percentages for clear (≤40
PCU) and colored (>40 PCU) stormwater ponds were calculated because of the non-
normal, skewed distribution of data. Separate values were calculated for clear and
colored stormwater ponds to account for the influence of color on nutrient-response
relationships (Hoyer & Jones, 1983; Brown, Hoyer, Bachmann, & Canfield, 2000). TP
and TN values were multiplied by the median AAP and AAN percentages for each lake
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type to determine the associated absolute AAP and AAN values for clear and colored
stormwater ponds.
AAP and AAN values for potential chlorophyll-a concentration thresholds ranging
from 5-30 µg·L-1 in clear and colored stormwater ponds were determined by multiplying
the associated nutrient management threshold criteria for TP and TN by the
corresponding median percent of the nutrient in organic form. Best fit curves and
equations were then created for the AAP and AAN relationships using statistical
software (SAS Institute, 2009). Individual empirical models were used to calculate TP
and TN values for clear and colored stormwater ponds at chlorophyll-a thresholds
ranging from 5 to 30 µg·L-1. Associated AAP and AAN values for clear and colored
stormwater ponds were calculated from the nutrient-response values using the
associated percent algal assimilated nitrogen and phosphorus.
Results and Discussion
Nutrient Management Threshold
The inverse equations of the nutrient-response relationships established by
Nealis et al. (2016), were calculated to create the empirical nutrient management
criteria models for TP and TN (mg·L-1) (Table 5-1). A least squares regression analysis
revealed statistically significant (p<0.001) yet weak relationships between TP and
chlorophyll-a in clear (r2=0.23) and colored (r2=0.26) stormwater ponds. The regression
analysis revealed statistically significant but even weaker relationships between TN and
chlorophyll-a in clear (p<0.05, r2=0.05) and colored (p<0.01, r2=0.07) stormwater ponds.
Statistically significant (p<0.001) quadratic best fit models for clear and colored
stormwater ponds were calculated for the resulting nutrient management criteria (Tables
5-1 & 5-2).
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The stormwater pond nutrient management criteria for clear and colored systems
established at 20 µg·L-1 chlorophyll-a are much different than the state of Florida’s NNC
for natural lakes (Table 5-3). The acceptable range for TP in natural clear lake systems
is 0.03 to 0.09 mg·L-1 and the clear stormwater pond TP threshold relating to a
chlorophyll-a concentration less than 20 µg·L-1 is 0.41 mg·L-1. The acceptable statewide
range for TP in a natural colored lake system is 0.05 to 0.16, but the limit for lakes in the
West Central Nutrient Watershed Region (WCNWR) is set at 0.49 mg·L-1. The
community in this study is located in the WCNWR and the colored stormwater pond TP
threshold is a comparable 0.46 mg·L-1. The acceptable range for TN in natural clear
lake systems is 1.05 to 1.91 mg·L-1 and the clear stormwater pond TN threshold is 32.1
mg·L-1. The acceptable range for TN in natural colored lake systems is 1.27-2.23 mg·L-1
and the colored stormwater pond TN threshold is 8.45 mg·L-1. (Florida Department of
Environmental Protection , 2012) The TN thresholds for clear and colored stormwater
ponds are much greater than those established for natural lake systems and further
support the importance of investigating the influence of stormwater pond management
and chemical interventions on algal-response relationships to nutrients as reported in
Nealis et al (2016).
Utilizing the more protective NNC for establishing a nutrient management criteria
for nitrogen in stormwater ponds may be suggested to ensure protection of both
stormwater pond aesthetic demands and natural downstream waterbodies. Stormwater
ponds and the contributing watersheds are heavily managed and several other
environmental drivers, including algaecide applications within the stormwater ponds,
may impact nutrient-response relationships (Nealis et al., 2016). Therefore, it is
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recommended the nutrient criteria most protective of natural downstream systems be
selected for managing stormwater ponds. Utilizing the most protective criteria inherently
protects the desired aesthetic and recreational uses of stormwater ponds while ensuring
downstream ecosystems will not be negatively impacted.
Nutrient Assimilation Potential
The median AAP portion of TP was 81% (n=86) in clear stormwater ponds and
76% (n=118) in colored stormwater ponds (Table 5-4). The median AAN portion of TN
was 80% (n=87) in clear stormwater ponds and 85% (n=120) in colored stormwater
ponds.
The estimated AAP and AAN associated with a range of chlorophyll-a thresholds
for clear and colored stormwater ponds were determined using the developed quadratic
models (Figures 5-1 & 5-2). The AAP and AAN values were then converted to g·m-3 to
quantify the potential assimilative capacity of phosphorus (Figure 5-3) and nitrogen
(Figure 5-4) by stormwater ponds at chlorophyll-a thresholds ranging from 5 to 30 µg·L-
1. Utilizing the estimated AAP and AAN, the potential increases in nutrient assimilative
capacity associated with increasing chlorophyll-a treatment thresholds from present
stormwater pond chlorophyll-a concentrations to the community identified treatment
thresholds were evaluated (Figure 5-3 & Figure 5-4). At the current stormwater pond
mean chlorophyll-a concentrations, clear systems maintained at 5 µg·L-1 chlorophyll-a
potentially remove 0.023 g·m-3 phosphorus and 0.970 g·m-3 nitrogen. Colored
stormwater ponds maintained at 10 µg·L-1 chlorophyll-a potentially remove 0.053 g·m-3
phosphorus and1.725 g·m-3 nitrogen. If the chlorophyll-a management threshold were
increased to survey defined acceptable levels of 20 or 25 µg·L-1 for clear and colored
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stormwater ponds, an increased removal of phosphorus and nitrogen in clear and
colored stormwater ponds could be achieved. A 20 µg·L-1 chlorophyll-a threshold
potentially results in the removal of 0.332 g·m-3 phosphorus in clear systems (1,343%
increase), 0.347 g·m-3 phosphorus in colored systems (555% increase), 25.71 g·m-3
nitrogen in clear systems (2,551% increase), and 7.18 g·m-3 nitrogen in colored systems
(316% increase). A 25 µg·L-1 chlorophyll-a threshold potentially results in the removal of
0.510 g·m-3 phosphorus in clear systems (2,117% increase), 0.636 g·m-3 phosphorus in
colored systems (1,100% increase), 43.6 g·m-3 nitrogen in clear systems (4,388%
increase), and 11.4 g·m-3 nitrogen in colored systems (584% increase).
Considering a stormwater pond of average size (0.40 hectares, 2 meter average
depth) contains a volume of 8000 m3 and has several complete volume turnovers per
year, and knowing there are several hundred stormwater ponds within the community,
the effect of increasing community-wide chlorophyll-a thresholds on nutrient removal
and downstream loading could be significant.
Conclusion
This study identified a method for ascertaining and quantifying nutrient
management criteria in clear and colored stormwater ponds using established nutrient-
response relationships and community-based chlorophyll-a tolerance thresholds. The
phosphorus nutrient management criteria values established for clear and colored
stormwater ponds were greater than those for natural lake systems, but were
comparable to the NNC for natural colored lakes in the WCNWR. The nitrogen nutrient
management criteria values established for clear and colored stormwater ponds were
much greater than those established for natural lake systems and suggest the impact of
other management variables on algal responses.
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Furthermore, the potential assimilation of nitrogen and phosphorus at various
nutrient management criteria levels were calculated to estimate the environmental
impact of various community identified management thresholds. Increasing the nutrient
management criteria from current levels to community-identified management
thresholds results in a great increase in the potential assimilation of nitrogen and
phosphorus by stormwater pond algae. An increase in the chlorophyll-a concentrations
in clear and colored stormwater ponds from the current standards to the community
identified acceptable chlorophyll-a concentration of 20 µg·L-1 would result in a 1,343%
increase in the removal phosphorus in clear systems, 555% increase in the removal of
phosphorus in colored systems, 2,551% increase in the removal of nitrogen in clear
systems, and 316% increase in the removal of nitrogen in colored systems, assuming
all algal particles settle within the pond and there is permanent sediment stability. It is
recommended stormwater pond managers select the most conservative nutrient
management criteria when comparing the stormwater pond management criteria to the
NNC in order to protect both stormwater ponds and natural, downstream systems.
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Table 5-1. Empirical models and summary statistics describing the association of monthly average nutrient and chlorophyll concentrations and median percent algal assimilated phosphorus or nitrogen using data from stormwater ponds in southwest Florida (Nealis, Clark, Monaghan, Hochmuth, & Frank, 2016).
Nutrient Pond Model n F p > F r2
Phosphorus Clear LnCHL= 0.520LnTP + 3.459 86 27.19 <0.001 0.25 (mg·L-1) LnTP= 1.923LnCHL - 6.652 86 25.55 <0.001 0.23 Colored LnCHL= 0.368LnTP + 3.284 120 43.32 <0.001 0.27 LnTP= 2.717LnCHL - 8.924 120 40.39 <0.001 0.26 Nitrogen Clear LnCHL= 0.423LnTN + 1.528 86 4.53 <0.05 0.05 (mg·L-1) LnTN= 2.364LnCHL – 3.612 86 4.53 <0.05 0.05 Colored LnCHL= 0.486LnTN + 1.959 120 8.30 <0.01 0.07 LnTN= 2.058LnCHL – 4.031 120 8.30 <0.01 0.07
CHL, chlorophyll-a (µg·L-1), TP, total phosphorus (mg·L-1), TN, total nitrogen (mg·L-1), clear (≤40 PCU), colored (>40PCU). Table 5-2. Quadratic models and summary statistics describing the association of
monthly average nutrient and chlorophyll concentrations and median percent algal assimilated phosphorus or nitrogen associated with the identified threshold using data from stormwater ponds in southwest Florida (Nealis, Clark, Monaghan, Hochmuth, & Frank, 2016).
Model Color p r2
Nutrient Response Relationships TP = 0.0009(CHL-17.625)2 + 0.0348CHL - 0.2913 Clear <0.001 0.99 TN = 0.1221(CHL-17.625)2 + 3.3919CHL - 35.9322 Clear <0.001 0.99 TP = 0.0024(CHL-17.625)2 + 0.0572CHL - 0.6862 Colored <0.001 0.99 TN = 0.0227(CHL–17.625)2 + 0.7667CHL - 6.9959 Colored <0.001 0.99 Estimated Algal Assimilated Nutrient AAP = 0.0007(CHL-17.625)2 + 0.0282CHL - 0.2359 Clear <0.001 0.99 AAN = 0.0977(CHL-17.625)2 + 2.7135CHL – 28.7458 Clear <0.001 0.99 AAP = 0.0018(CHL-17.625)2 + 0.0435CHL - 0.5215 Colored <0.001 0.99 AAN = 0.0193(CHL-17.625) 2 + 0.6517CHL - 5.9465 Colored <0.001 0.99
CHL, chlorophyll-a (µg·L-1), TP, total phosphorus (mg·L-1), TN, total nitrogen (mg·L-1), clear (≤40 PCU), colored (>40PCU), AAP/N, percent algal assimilated phosphorus or nitrogen.
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Table 5-3. Florida’s Numeric Nutrient Criteria and the stormwater pond nutrient management criteria established for a residential community in southwest Florida.
Nutrient Color Statewide Range Stormwater Pond WCNWR Nitrogen Clear 1.05 – 1.91 32.1 (mg·L-1) Colored 1.27 – 2.23 8.45 Phosphorus Clear 0.03 - 0.09 0.41 (mg·L-1) Colored 0.05 - 0.16 0.46 0.49
Clear ≤40 PCU, Colored >40 PCU. NNC values established by Florida Department of Environmental Protection (United States Environmental Protection Agency, 2010). TP, total phosphorus, TN, total nitrogen, Chl-a, Chlorophyll-a, PCU, platinum cobalt units, S.E., standard error, NNC, Numeric Nutrient Criteria, WCNWR, West Central Nutrient Watershed Region.
Table 5-4. Summary statistics describing the estimated assimilated algal phosphorus (AAP) and assimilated algal nitrogen (AAN) for clear and colored stormwater ponds for a residential community in southwest Florida.
Nutrient Color n Median Mean SD Range AAP Clear 86 0.807 0.786 0.193 0.297 – 1.00 Colored 118 0.757 0.714 0.242 0.246 – 1.00 AAN Clear 87 0.799 0.747 0.148 0.158 – 0.944 Colored 120 0.849 0.820 0.112 0.282 – 0.968
Clear ≤40 PCU, Colored >40 PCU.
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Figure 5-1. Models displaying treatment threshold and numeric phosphorus values
based on nutrient response relationships defined in Chapter 2 for clear and colored stormwater ponds with associated algal phosphorus assimilation values.
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Figure 5-2. Models displaying treatment threshold and numeric nitrogen values based
on nutrient response relationships defined in Chapter 2 for clear and colored stormwater ponds with associated algal nitrogen assimilation values.
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Figure 5-3. Estimated algal assimilated phosphorus (AAP g·m-3) in stormwater ponds at
chlorophyll-a concentrations from 5 to 30 µg·L-1.
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Figure 5-4. Estimated algal assimilated nitrogen (AAN, g·m-3) in stormwater ponds at
chlorophyll-a concentrations from 5 to 30 µg·L-1.
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CHAPTER 6 CONCLUSION
Findings
Stormwater ponds are an increasingly important landscape feature in Florida
developments. The original and regulatory intent of including stormwater ponds in
residential developments was to protect surface water quality by mitigating urban or
residential runoff volume and reducing pollutants, including nitrogen and phosphorus
(Livingston & McCarron, 1992; Harper & Baker, 2007). Nutrients are removed through
numerous pathways in stormwater ponds, including biological assimilation by plants and
algae (Harper & Baker, 2007). Stormwater ponds are required to remove 80-95% of the
total nitrogen (TN) and total phosphorus (TP) in runoff, but a study by Harper and Baker
(2007) revealed stormwater ponds fail to meet the permitted removal efficiencies and
recommended increased retention time and upstream pretreatment.
Recently, stormwater ponds have become recognized by communities for their
aesthetic and recreational value. Developers have increasingly incorporated stormwater
ponds into community design to maximize waterfront properties and property value
premiums. As such, water quality within stormwater ponds has become a concern of
residents using the stormwater ponds, but, unlike natural water bodies in Florida, no
water quality criteria exist for stormwater ponds. Managing social expectations of
stormwater ponds does not take into consideration regulatory intent and therefore may
be conducted at the expense of meeting regulatory requirements.
Algal response to increased water column nutrients is common as there is a well-
documented positive relationship between nutrients and algal biomass as measured by
chlorophyll-a concentrations (Dillon & Rigler, 1974; Brown, Hoyer, Bachmann, &
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Canfield, 2000; Hoyer, Frazer, Notestein, & Canfield, 2002; Florida Department of
Environmental Protection , 2012). Nutrient response relationships are helpful in guiding
management practices and were used to establish Florida’s Numeric Nutrient Criteria
(NNC) protecting designated uses of natural lakes. The NNC aids in identifying
management strategies and nutrient loading targets by identifying unacceptable
chlorophyll-a concentrations and associated preventative nutrient thresholds. In
stormwater ponds, nutrient-response relationships, unacceptable chlorophyll-a
concentrations, and preventative nutrient thresholds are all unknown. Instead of
protective criteria, algal blooms and other biological responses triggered by high nutrient
loads in stormwater ponds are often suppressed chemically to maintain resident
expectations. Artificial management of the biological response to increased nutrients
then eliminates an important nutrient removal pathway within the pond and potentially
reduces the required pond nutrient removal efficiency.
This study proposed developing a community based stormwater pond nutrient
criteria to create a stormwater pond management program effectively meeting both
regulatory and community demands. Identifying nutrient concentrations resulting in
problematic algal blooms shifts protective standards reserved for natural systems by the
NNC to the stormwater pond and identifies targets for upland nutrient management and
nutrient runoff reduction. To develop the criteria, nutrient-response relationships in
stormwater ponds were evaluated and compared to the relationships in natural lake
systems. Furthermore, variables significantly predicting TP, TN, and chlorophyll-a
concentrations were identified to isolate targets for reducing stormwater pond nutrient
enrichment and creating a site-specific model of nutrient criteria. Finally, chlorophyll-a
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concentrations associated with impairment were identified by residents and related to
numeric nutrient thresholds to create the stormwater pond nutrient criteria.
The evaluation of nutrient-chlorophyll-a relationships in stormwater ponds
revealed statistically significant positive relationships between TP and chlorophyll-a
concentrations in clear and colored systems and TN and chlorophyll-a concentrations in
clear and colored systems, but the relationships were much weaker the nutrient-
response relationships found in natural lakes. When compared to natural lakes, the
chlorophyll-a response to TP and TN concentrations was greater in natural lakes than
stormwater ponds and there was a significant difference in the nutrient response
interaction and slopes in both clear and colored systems. However, there was no
significant difference in the TP-chlorophyll-a interaction of colored lakes and colored
stormwater ponds in the specific West Central Peninsular Region.
Numerous management and landscaping variables were evaluated for their
significance as predictors of TP, TN and chlorophyll-a concentrations in stormwater
ponds and site-specific models were developed. Significant predictor variables
influencing water column TP, TN and chlorophyll-a concentrations were summarized
and categorized (Figure 6-1) and the presence of grass clippings and littoral shelf
coverage of the stormwater pond area were identified as the two significant predictor
variables influencing all three concentrations. Fertilizer restrictions, chlorophyll-a
concentrations and the presence of bank erosion were the three variables found to be
significant predictors of nutrient concentrations. The TP, TN and chlorophyll-a
concentration models associated with the significant predictors were more robust than
133
the nutrient-response models for TN and TP in stormwater ponds and may offer a better
alternative for establishing stormwater pond nutrient criteria at a site-specific level.
A web-based survey was then used to identify a community-based chlorophyll-a
threshold of impairment, referred to as “treatment threshold,” by having participants
identify the point of impairment in a series of photos with increasing chlorophyll-a water
column concentrations. Each participant was given one of four survey-based treatments
evaluating the impact of pre-question educational information and image presentation
on preferred treatment threshold. Mean thresholds of impairment from the four different
treatments were greater than the NNC of 20 µg·L-1 and ranged from 21 to 26 µg·L-1, but
only three of the treatments were significantly greater than the NNC. Education was
found to have no significant impact on treatment threshold, but inclusion of a visual focal
point in the images did have a significantly negative impact on the identified threshold.
Several additional questions were included in the survey to identify significant
predictors of preferred chlorophyll-a treatment thresholds in stormwater ponds.
Increased frequency of stormwater pond use for different recreational activities had a
positive correlation with identified thresholds of impairment. Additionally, some forms of
prior knowledge of stormwater pond function had a significant effect on the identified
treatment threshold. Participants who identified algae function in stormwater ponds as a
nutrient removal pathway had a significantly greater treatment threshold than
respondents who identified other algal roles and individuals who received stormwater
pond educational information from the real estate company prior to purchasing or
renting their home had a significantly higher mean treatment threshold than those who
were not provided with information from the real estate company. Finally, age, presence
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of children in the household, sex and seasonality of residence were identified as
demographic categories with significant differences in treatment thresholds amongst
groups.
Finally, potential community-based stormwater pond nitrogen and phosphorus
criteria were then identified for clear and colored stormwater ponds based on the
established nutrient-response relationships and survey-identified thresholds of
impairment. The TN and TP concentration thresholds were higher than those identified
for natural Florida lakes, with exception of the NNC established for TP in colored lakes
of the WCPR region which was comparable to the colored stormwater pond TP criteria.
Additionally, algal nitrogen and phosphorus assimilation values were estimated and the
potential algal nutrient removal associated with each treatment threshold was calculated
to reveal the potential environmental impact of varying stormwater nutrient criteria.
Results indicated that managing ponds at the community-identified chlorophyll-a
concentration threshold of 20 µg·L-1 instead of the current concentrations of 5 and 10
µg·L-1 would increase the potential TP and TN removal from stormwater ponds in clear
and colored stormwater ponds significantly.
In conclusion, the integration of a community-based stormwater pond nutrient
management program would facilitate the objectives of both regulatory and social
requirements. As demonstrated in this study, establishing a community-based
chlorophyll-a treatment threshold and the associated protective nutrient concentration
clearly defines the management and intervention criteria necessary to maintain the
desired aesthetic and recreational use of stormwater ponds. Identifying a specific
protective nutrient concentration will identify specific landscape management targets
135
and promote more efficient nutrient management in contributing, upland systems.
Protecting the community-identified designated use of a stormwater pond through
improved nutrient management shifts nutrient removal requirements upstream from
stormwater ponds and inserts another protective standard between the natural
environment and human development. Thus, protecting stormwater ponds as aesthetic
and recreational commodities will inherently protect downstream natural waters and
satisfy the regulatory requirements of these built systems while maintaining social
expectations.
Future Research Implications
Nutrient-response relationships in stormwater ponds and the quantitative
implications of user preferences and management on stormwater pond nutrient removal
performance had not been studied in great detail prior to this investigation. Each
chapter of this study revealed important and pertinent results that could be applied to
current management strategies to improve stormwater pond management, however,
numerous additional opportunities for research arose with each finding.
The nutrient-response relationships identified in Chapter 2 were found to be
significantly different than nutrient-response relationships in natural lake systems, but
the relationship between TN/TP and chlorophyll-a concentrations were much weaker in
stormwater pond systems. Current stormwater pond management strategies may
contribute to the weaker relationship since stormwater pond systems are heavily
managed for aesthetics, and algae concentrations are treated with various chemical
compounds. Additionally, the nutrient-response relationships within the stormwater
ponds were not significantly different than the nutrient-response relationships in natural
lakes located in this region which may indicate the influence of naturally occurring
136
phosphorus deposits. Therefore, the dynamics of nutrient interactions and both internal
and external influences of nutrient-response relationships warrant further investigation
to determine why nutrient-chlorophyll-a response relationships in stormwater ponds
differ from that of natural systems.
Chapter 3 identified significant management variables influencing the nutrient-
response relationships in stormwater ponds and developed models for TN, TP and
chlorophyll-a for clear and colored stormwater ponds. These models should be further
validated in the same community as well as other regional and statewide stormwater
ponds. Additionally, independent management variables influencing nutrient and algal
concentrations should be further tested to better quantify their impact on nutrient
concentrations in stormwater ponds. Validating and improving the understanding of the
impact of various management decisions has great implications in BMP
recommendation and homeowner adoption.
Chapter 4 identified resident preferred chlorophyll-a management thresholds and
provided usable evidence to support management decisions. Although pre-question
education had no effect on preferred chlorophyll-a concentration, another survey item
demonstrated the influence of algae function knowledge on preferred chlorophyll-a
values. There should be a further investigation into effective education regarding the
role of algae in stormwater ponds and the best manner of information delivery.
Additionally, the presence of a focal point (submerged aquatic vegetation) in images
presented regarding water column algae concentration did seem to have an impact on
desired chlorophyll-a concentrations. Additional studies should focus on the impact of
other focal points, both submerged and emergent, on water column algae preference.
137
Finally, water column algae concentration is not the only natural response variable
managed in stormwater ponds so similar studies focusing on identifying thresholds for
filamentous algae, submerged aquatic vegetation, emergent vegetation, water color,
shoreline plantings, etc., should be conducted.
Lastly, in Chapter 5, the community-based chlorophyll-a threshold and nutrient-
response relationships were used to set the stormwater pond nutrient management
values for clear and colored stormwater ponds and the estimated algae assimilated
nutrients were used to predict the impact of increasing management thresholds on
potential nutrient removal. Additional studies should be conducted to identify the actual
nutrient assimilation by the water column algae, algae settling rates, sediment stability,
and overall short-term and long-term retention percentage of nutrients assimilated by
algae within stormwater ponds.
138
Figure 6-1. Variables identified as significant predictors of phosphorus, nitrogen and chlorophyll-a concentrations in stormwater ponds. Arrows indicate positive, negative or both positive and negative variable coefficients
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APPENDIX A COMMUNITY-BASED STORMWATER POND MANAGEMENT SURVEY
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BIOGRAPHICAL SKETCH
Charlie Nealis grew up on a frozen tundra in a house constructed entirely of
dinosaur bones. He attended grade school with various woodland creatures and was
only accepted as one when he defeated a one-eyed grizzly bear named Gerald the
Terrible in hand-to-paw combat. After being crowned king of the wilderness, Charlie
earned his B.S. in food and resource economics at the University of Florida with a minor
in agronomy. Following his bachelor’s, Charlie earned his M.S. in agricultural education
and communication from the University of Florida. After working as a research assistant
in community based social marketing of environmentally friendly landscaping practices
at the University of Florida and a biology teacher at Deltona High School, Charlie
returned to the University of Florida as a Water Institute Graduate Fellow and earned
his PhD in soil and water science.