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Assessment of a Countywide Stormwater Pond Improvement Project: Impacts of the Hillsborough County Adopt A Pond Program by Anthony T. Betts A thesis submitted in partial fulfillment of the requirements for the degree of Master of Science De partment of Geography College of Arts and Sciences University of South Florida Major Professor: Kamal Alsharif Ph.D. Connie Mizak Ph.D. Philip Reeder Ph.D. Date of Approval: March 24 2011 Keywords: Stormwater Management, Nonpoint Pollution, Wa ter Quality, Public Participation Copyright 2011, Anthony T. Betts
i ACKNOWLEDGEMENTS A very special thanks to Dr. Kamal Alsharif for spearheading this project, continuously le ading me in the right direction and for your innumerable hours of hard work and fellowship. Thanks to Dr. Philip Reeder and Dr. Connie Mizak for co mprising my graduate committee and for invaluable advice and lasting guidance. Thanks t o Mr. John McGee for opening your office doors and working tirelessly on the behalf of this p roject. Thanks to Cora Bartolo, Kimberly Curtin, Shawna Feinman, and Marisa Sanchez for adopting this project as your own and for great determination in the field. Thanks to D r. Maya Trotz for equipment and guidance. And, thank you to the Hillsborough Coun ty Adopt A Pond program and the U niversity of S outh F lorida Department of Geography for valued assistance and funding
ii TABLE OF CONTENTS LIST OF TABLE S ................................ ................................ ................................ ............ iv LIST OF FIG URES ................................ ................................ ................................ ............. v ABSTRAC T ................................ ................................ ................................ .................... v i CHAPTER 1: INTRODUCTION ................................ ................................ ........................ 1 CHAPTER 2: LITERATURE REVIEW ................................ ................................ ............. 4 2.1 Imperviousness and Runoff Composition ................................ .......................... 4 2.2 Retention and Detention Pond Deficiencies ................................ ...................... 8 2.3 Pollutant Removal Efficiencies ................................ ................................ ......... 9 2.4 Retrofitting Stormwater Ponds ................................ ................................ ........ 12 2.5 Impact of Vegetation in Stormwater Management ................................ .......... 13 2.6 Science and Environmental Policy ................................ ................................ .. 14 2.7 Stormwater, Social Val ues, and Public Participation ................................ ...... 15 CHAPTER 3: RESEARCH DESI GN ................................ ................................ ................ 18 3.1 Problem Statement ................................ ................................ ........................... 18 3.2 Research Objectives ................................ ................................ ......................... 18 3.3 Experimental Hypotheses ................................ ................................ ................ 20 3.4 Null Hypothesis ................................ ................................ ............................... 21 CHAPTER 4: METHODOLOGY ................................ ................................ ..................... 22 4. 1 Sampling Pro tocol ................................ ................................ ............................ 22 4.2 Water Analysis ................................ ................................ ................................ 23 4.3 Vegetation Analysis ................................ ................................ ......................... 24 4.4 Measures of Activity ................................ ................................ ........................ 28 CHAPTER 5: STUDY AREA ................................ ................................ ........................... 30 5.1 Tampa Bay ................................ ................................ ................................ ....... 30 5.2 Climate ................................ ................................ ................................ ............. 31 5.3 Geology and Topography ................................ ................................ ................ 32 5.4 Land Use ................................ ................................ ................................ .......... 32 5.5 Hydrology ................................ ................................ ................................ ........ 33
iii CHAPTER 6: RESULTS AND DISCUSSION ................................ ................................ 35 6 .1 Data Characteristics ................................ ................................ ......................... 35 6.2 Co mparing Study Population s ................................ ................................ ......... 41 6.2.1 Water Quality Parameters ................................ ................................ 42 6.2.2 Vegetation Analysis ................................ ................................ .......... 43 6.2.3 Significance of Population Comparison ................................ ........... 43 6.3 Trend Analyses within AAP Population ................................ .......................... 44 6.3.1 Water Quality and Progra m Activity ................................ ............... 45 6.3.2 Vegetation and Program Activity ................................ ..................... 47 6.3.3 Significance of Trend Analyses ................................ ........................ 51 CHAPTER 7 : CON CLUSIONS ................................ ................................ ........................ 54 7 .1 Interpretations and Experimental Hypotheses ................................ ................. 54 7 .2 Future Research ................................ ................................ ............................... 55 7 .3 Recommendations to Enhance Program Outcomes ................................ ......... 57 7 .3 .1 Intensification ................................ ................................ ................... 57 7 .3.2 Diversification ................................ ................................ ................... 58 7 .4 Concluding Remarks ................................ ................................ ........................ 59 LIST OF REFERENCES ................................ ................................ ................................ ... 60 APPENDIX A: WATER QUALITY FIELD DATA SHEET ................................ ........... 65 APPENDIX B: VEGETATIO N FIELD DATA SHEET ................................ ................... 67 APPENDIX C: WATER QUALITY OBSERVATIONS ................................ .................. 70 APPENDIX D: VEGETATION D ATA ................................ ................................ ............ 77 APPENDIX E: MEASURES OF PROGRAM ACTIVITY ................................ .............. 82 APPENDIX F : STUDY VEGETATION SPECIES AND LVI PARAMETERS ............. 88
iv LIST OF TABLES TABLE 1: Mean pollutant concentrations for stormwater runoff ................................ 7 TABLE 2 : Mean removal eff iciencies by wet detention ponds ................................ ... 11 TABLE 3: Explanation of established Coeffi cient of Conservatism scoring .............. 26 TABLE 4 : Description of the m LVI scoring criteria ................................ ................... 28 TABLE 5 : Descriptive statistics for study observations ................................ .............. 41 TABLE 6 : Means comparison for study water quality parameters ............................. 42 TABLE 7 : Means comparison for study vegetation parameters ................................ .. 43 TABLE 8 : Results of regression analysis between TSS and Active Years ................. 4 6 TABLE 9 : Results of regression analysis between mLVI and Plants/Acre ................ 4 8 TABLE 10 : Results of regression analysis between mLVI and Cleanup Hours .......... 50 TABLE 11: Predicted outflow concentrati ons and mean AAP observations ................ 52 TABLE 12: Means comparison for predi cted pollutant concentrations ........................ 53
v LIST OF FIGURES FIGURE 1: Expan ding Conte mporary Stormwater Management ................................ 1 7 FIGUR E 2 : Segmentation of stormwater ponds ................................ ............................ 25 FIGURE 3 : Spatial distribution of study AAP participants ................................ .......... 31 FIGURE 4: Land Use in Hillsborough County ................................ ............................. 33 FIGURE 5: Spatial Distribution of Impervious Surfaces in Hillsborough County ....... 34 FIGURE 6 : Statistical distr ibution of observed mLVI scores ................................ ....... 36 FIGURE 7 : Statistical distribution of observed Invasive Plant percentages ................. 3 7 FIGURE 8 : Statistical distribution of observed Total Nitrogen concentrations ............ 37 FIGURE 9 : Statistical distribution of observed Total Phosphorus concentrations ....... 38 FIGURE 10 : Statistical distribution of observed Chlorophyll a concentrations ............. 38 FIGURE 11 : Statistical distribution of observed Turbidity values ................................ 3 9 FIGURE 12 : Statistical distribution of observed Dissolve Oxygen Saturations ............. 39 FIGURE 13 : Statistical distribution of observed Total Suspended Solids ...................... 40 FIGURE 14 : Statistical distribution of observed Water Clarity Depths ......................... 40 FIGURE 15 : Positive relationship between TSS and Active Years ................................ 46 FIGURE 16 : Positive relationship between mLVI and Plants /Acre ............................... 48 FIGURE 17 : Negative relationship between mLVI and Cleanup Hours ........................ 50
vi ABSTRACT Comparative research was conducted to assess the environmental impacts of the Adopt a Pond program, which operates throughout Hillsborough County, Florida. The Adopt a Pond program was established in 1992 and designed to address nonpoint pollution through outreach and stormwater pond enhancement. However, the program had never been thoroughly and scientifically evaluated. Therefore, assessments of water quality and ve getative characteristics were made at ninety Adopt a Pond participants and eleven control ponds to explore the potential impacts of the program on measurable environmental parameters Statistical a nalysis of the results failed to demonstrate any statistic ally significant environmental improvements associated with the Adopt a Pond program, and measures of program activity did not illustrate a consistently positive relationship. These results indicate a need to readdress the policies and implementation of th e program. Poor compliance by program volunteers evident by the limited span of group participation (mean = 2.5 years) and relatively low percentage of actively involved residents, is the most likely culprit for the unremarkable improvements in pond quali ty, as pond enhancement techniques are firmly established in the literature. Overall, these conclusions underline the need for an integrated evaluation component in policymaking and an adaptive management approach to environmental management. A more detail ed
vii analysis is warranted to provide time series data, which examines ponds both before and after entry to the program and after implementing landmark improvement measures In the end, the results of the study have provided a better understanding of the AAP and other similar restoration programs, and hopes to allow for enhancement of AAP program restoration practices.
1 C HAPTER 1: INTRODUCTION The Hillsborough County Adopt A Pond (AAP) program was established through cooperation with the Hillsborough Co unty Public Works Department and the Southwest Florida Water Management District (SWFWMD) in an effort to reduce the abundance of nonpoint and in partial compliance for National Pollutant Discharge Elimin ation System (NPDES) requirements for municipalities operating Municipal Separate Storm Sewer Systems (MS4) Designed as a volunteer based educational and outreach program, the AAP program facilitates the organization of concerned residents and assists in the rehabilitation of impaired stormwater ponds by providing educational material, expert pond assessment and restoration advice, contributions of emergent vegetation, and assistance with planting and other restoration activities. The AAP program has assis ted over three hundred resident groups since its inception and currently supports the restoration of nearly one hundred stormwater ponds throughout Hillsborough County. Over the last two decades, the program has realized great success as an educational pro gram and has been listed as an E nvironmental P rotection A gency (EPA) case study and model practice of the American Public Works Association; however, to improve rehabilitation practices and further reduce nonpoint pollution a thorough evaluation of the pro gram is necessary.
2 Therefore, a comparative study was conducted to assess the impacts of the Hillsborough County Adopt a Pon d (AAP) program on measurable environmental parameters within participating residential stormwater ponds. One hundred and three stor mwater ponds were randomly chosen from the study population of which eight four were ultimately evaluated for general water quality and vegetative characteristics. Addition ally, fifteen control ponds, selectively sampled in an effort to closely mimic the study population were chosen for evaluation, of which eleven were ultimately used for comparison. Water samples were collected, a nd laboratory analysis was conducted to determine the concentrations of four water quality parameters, including: total nitrog en, total phosphorus, total suspended solids (TSS), and chlorophyll a. Other water quality criteria, including: dissolved oxygen concentrations water temperature, specific conductivity, turbidity, pH, and water clarity were determined in the field. In ad dition, an emergent vegetation survey, based on protocol developed by the Florida Department of Environmental Protection (FDEP) for the Lake Vegetation Index (LVI), was conducted as a measure of disturbance and eutrophication in the stormwater ponds These results were then compared to identical assessments conducted on the eleven carefully chosen control ponds to illustrate any statistically significant impact of the AAP program. Similar nonpoint pollution reduction programs have been implemented across the country (Badics, 1993), including several in the Tampa Bay area. However, thorough scientific assessment of post rehabilitation conditions is severely limited in the existing scientific lite rature The proposed research is designed to provide the essen tial link between these sensibly designed programs, specifically the AAP program, and any realized improvements in environmental criteria, such as water quality and vegetative
3 composition. By providing this association, more accurate evaluation of the AAP program can be achieved, resulting in either necessary improvements or greater confidence in existing practices.
4 CHAPTER 2: LITERATURE REVIEW Stormwater retention and detention ponds are a common feature in the urban Florida landscape and elsewhere A recent study identified greater than one thousand stormwater ponds of various sizes in Hillsborough County alone (Su et al., 2004). For decades, these ponds have been constructed to control the increases in stormwater runoff associated with land develop ment and to mitigate the creation of impervious surfaces. However, since the ratification of the Clean Water Act in 1972, there has been an increasing interest in studying these entities for their ability to treat nonpoint source pollution and improve regi onal water quality. 2.1 Imperviousness and Runoff Composition Stormwater runoff can mobilize considerable quantities of nonpoint pollutants which represent a significant threat to surface water bodies. Numerous studies throughout the world have evaluate d the composition of stormwater runoff and results have shown that high levels of pollutant contamination are often found (Sartor et al., 1974; Graves et al., 2004). Furthermore, highly urbanized areas such as Hillsborough County must contend with numerou s and widely diverse sources of nonpoint pollution, which are intensified by the expansion of impervious surfaces (Xian et al., 2007). Studies have also
5 identified a wide range of pollutant compounds, including: heavy metals, fertilizers, sediments, and pe sticides (Graves et al., 2004). In addition, poorly maintained stormwater ponds can become hazardous pollutant sources, cultivating dangerous bacterial and algal species (Serrano and DeLorenzo, 2008). Increases in impervious surfaces, commonly attributed to urban development, are a fundamental contributor to declining surface water quality (EPCHC, 2006 ) Studies in Hillsborough County have shown that moderate water quality impacts can be expected in areas with greater than 10% imperviousness, while areas with greater than 25% imperviousness can anticipate severe water quality impacts (EPCHC, 2006). In essence, impervious surfaces act as barriers to natural infiltration, preventing groundwater recharge and increasing the overall volume of stormwater runoff. These increased flows essentially wash parking lots, highways, roofs, and driveways into the nearby stormwater system and can mobilize countless pollutants, including heavy metals, nutrients, and sediments (Xian et al. 2007). Recent research in the Tamp a Bay region conducted by Xian et al. (2007) combined satellite imagery and water quality monitoring to relate urban landscape characteristics with their respective contributions to nonpoint source pollution. The methodology employed GIS software to illust rate spatial relationships between these characteristics, including imperviousness, population density, and water quality degradation. The results showed that both impervious surfaces and population density had a high statistical correlation with increased nonpoint pollution. Escalated levels of nutrients, suspended sediments, heavy metals, and hydrocarbons were observed in areas with greater imperviousness and higher population densities.
6 Further illustrating the detrimental effects of impervious surfaces, research conducted by Sartor et al. (1974) examined the composition of street surface runoff. The research studied street sweeping practices across the United States and collected samples from twelve major cities to determine the composition of street sur face contaminants. While street surface runoff represents only one segment of urban runoff, contaminants from this source were determined to be significantly hazardous to receiving water bodies. A wide variety of contaminants were identified. While the mo st common contaminant was sediment; pesticides, heavy metals, fecal coliform bacteria, and excessive nutrients were also found. Furthermore, the study showed that the highest concentrations of pollutants were associated with fine particulates. Lastly, rout ine street sweeping was found not to be an effective means of reducing street surface contaminants, with well regimented sweeping programs providing only minimal improvements to runoff quality. Overall, the study illustrated the impacts of impervious surfa ces and emphasized the diverse and potentially harmful nature of urban runoff. Research conducted by Graves et al. (2004) compared water quality parameters in stormwater runoff samples from various land uses. The study found that runoff is commonly defici ent in dissolved oxygen and is often below the Florida State Class III water quality standard of 5.0 mg/L. However, submerged vegetation was found to increase dissolved oxygen as a byproduct of photosynthesis. Numerous pollutants were identified by the stu dy, including: pesticides, nutrients, heavy metals, and sediments. Overall, runoff from agricultural land uses was found to be the most impaired, followed by urban land uses and, finally, wetlands. The application of chemicals, such as
7 pesticides and ferti lizers, and the presence of vegetative filtration were identified as the dominate factors in determining runoff quality. A review of the literature, conducted by Harper and Baker (2007), has provided quantitative estimates of stormwater composition in sin gle family residential neighborhoods within the State of Florida. These estimations were derived by aggregating the results of seventeen, peer reviewed studies conducted to evaluate stormwater composition within the established land use and across the Stat e of Florida, including six sites in the Tampa Bay region. The results of this review were used to construct annual pollutant concentrations for several pollutants of interest, including: total phosphorus, total nitrogen, and total suspended solids, the me an results of which are displayed in the table below (Table 1). This information can be cautiously utilized to establish an approximation for stormwater composition within the given land use; however, Harper and Baker caution against the broad application of these results for this purpose, as composition varies significantly according to precipitation and other important factors. Table 1 Mean annual pollutant concentrations for stormwater runoff within seventeen, single family residential neighborhoods i n the state of Florida (Harper and Baker, 2007). Pollutant Mean Annual Concentrations (mg/L) Total Nitrogen 2.07 Total Phosphorus 0.372 Total Suspended Solids (TSS) 37.5
8 2.2 Retention and Detention Pond Deficiencies Non point pollution can create wide ranging impacts on surface water bodies due to the complex mixture of harmful substances. Consequently, stormwater ponds are often highly polluted water bodies (Bavor et al., 2001; Serrano and DeLorenzo, 2008) Understanding how pollutants affect natural p rocesses is essential for developing successful treatment. Studies have found that low dissolved oxygen, high nutrient concentrations, excessive fecal coliform bacteria, frequent algal blooms, and harmful chemicals are all common impairments observed in st ormwater ponds (Bavor et al., 2001; Serrano and DeLorenzo, 2008). Therefore, stormwater ponds often pose a significant threat to receiving water bodies and can contribute to degradation of regional water quality (Serrano and DeLorenzo, 2008). A study by S errano and DeLorenzo (2008) analyzed water samples taken from a stormwater detention pond and the receiving water body to illuminate any potential water quality hazards. The results indicated low dissolved oxygen levels, below 4 mg/L, for both the pond and the creek and demonstrated poor water quality that could potentially endanger aquatic organisms. Likewise, the levels of nitrogen and phosphorus exceeded United States Environmental Protection Agency (EPA) water quality standards for lakes and reservoirs, 0.41 and 0.048 mg/L respectively, and indicated highly eutrophic conditions in both water bodies. Additionally, algal blooms were commonly noted during the summer months, and the microcystin toxin was found in multiple samples. In addition, two of the fou r pesticides tested were found in water samples taken from the stormwater pond. Lastly, high levels of fecal coliform bacteria, exceeding the Environmental Protection Agency (EPA) standard for contact recreational use, 200
9 CFU/100 mL, were commonly observe d. Overall, the observations indicated that the stormwater pond was significantly impaired and represented a potential hazard to both the receiving creek and the health of adjacent humans and wildlife. Based on the data collected, five recommendations were suggested, including: increasing the vegetative buffer, utilization of biodegradable household chemicals, limiting the application of lawn chemicals, improved disposal of pet wastes, and the implementation of management techniques designed to control alga l blooms. Overall, this study clearly illustrates the potentially hazardous nature of stormwater ponds and underlines the need for an appropriate design and maintenance. 2.3 Pollutant Removal Efficiencies While stormwater ponds were primarily designed fo r flood control, important pollutant removal mechanisms continue to provide water treatment. Understanding these pathways can support efforts to improve the water treatment capacity of stormwater ponds and can contribute to improvements in regional water q uality. A study by Wong et al. (1999) identified stormwater pollutant removal mechanisms in both ponds and treatment wetlands for comparison. Three fundamental processes for stormwater pollutant removal were identified, including: sedimentation, biologica l and chemical uptake, and pollutant transformation. Pollutant storage was also identified as a crucial consideration for long term success in stormwater treatment. The results of the study showed that sedimentation was the dominate pollutant removal mecha nism, which was significantly enhanced by the presence of emergent vegetation. Open water ponds were found to effectively remove coarse to medium sized sediments.
10 However, fine sediments were less effectively removed due to the lengthy detention periods re quired for sedimentation. The additional vegetation present in the treatment wetland increased sedimentation of these fine sediment particles through mechanical processes. Consequently, greater amounts of stormwater pollutants were removed. Emergent vegeta tion also enhanced biological uptake of pollutants. In open water systems, biological uptake is typically accomplished by phytoplankton, which remains suspended in the water column and can be easily mobilized to receiving water bodies. However, in vegetate d systems, biological uptake is achieved by emergent vegetation and attached biofilms, both of which are significantly less mobile. Therefore, vegetated systems help to retain pollutants within the treatment system and pose less danger to nearby receiving water bodies. Research conducted by Bavor et al. (2001) evaluated sedimentation rates and pollutant removal efficiencies for a detention pond system and a constructed treatment wetland in Australia. The study was able to determine that a majority of the f ecal coliform bacteria, phosphorus, and nitrogen were associated with particles less than 2 m in size. The finest particles, those less than 2 m in size, settle least effectively, yet, contain the largest percentage of water quality contaminants. Since v egetated wetlands have been found to remove these fine particles more effectively than open water systems, the research suggests that constructed wetlands would provide a higher degree of stormwater treatment in comparison to detention ponds due to the inc reased presence of vegetation. A review of the literature, conducted by Harper and Baker (2007), has provided quantitative estimates of pollutant removal for wet detention ponds in the State of
11 Florida. These numerical estimates illustrate the failure of w et detention pond systems to meet the Florida Water Resource Implementation Rule (Chapter 62 40 FAC) requirement of 80% annual pollutant removal by stormwater treatment systems. The numerical estimates of mean pollutant removal calculated by Harper and Bak er are presented in the table below (Table 2). These estimates were derived by averaging the results of ten, peer reviewed studies conducted to evaluate wet detention systems within various land uses in the State of Florida, including two sites in the Tamp a Bay region. Removal efficiencies calculated for dry detention systems were comparable to those established for wet detention ponds. However, other stormwater management practices, including: source reduction and stormwater retention and reuse, were attri buted removal efficiencies of one hundred percent for the retained volumes. Table 2. Mean removal efficiencies by wet detention ponds for pollutants of interest (Harper and Baker, 2007). Pollutant Mean Removal Efficiency Total Nitrogen 37% Total Phosp horus 69% Total Suspended Solids (TSS) 77%
12 2 .4 Retrofitting Stormwater Ponds Non point pollution originates from a wide variety of sources that exist throughout a given watershed. This diffuse and pervasive nature creates much of the difficulties in tre ating urban runoff. However, stormwater ponds occupy a relatively key juncture in the journey from pollutant source to surface water body. This intermediary nature allows stormwater ponds to be used as effective points for water treatment. According to Ma rsalek et al. (1992), upgrading, or retrofitting, existing stormwater ponds can be an efficient means of increasing the capacity for treatment of stormwater runoff, resulting in improvements in overall water quality. Implementing improved water treatment t echnologies and BMPs into older, sometimes neglected, stormwater ponds has the potential to transform potential water quality hazards into functioning elements of the municipal stormwater system. The study also suggests that additional improvements through out the catchment should also be considered to preemptively reduce stormwater pollutants before entering the detention pond. Additionally, the study found that enhancing biological treatment of urban runoff through the establishment of rooted plants within the stormwater pond and maintaining natural vegetative buffers throughout the catchment, as well as more expensive structural upgrades, could result in higher quality discharges to receiving water bodies. Lastly, the study recommended increased public inv olvement as an integral component of any retrofitting effort.
13 2.5 Impact o f Vegetation in Stormwater Management The use of vegetation as a stormwater BMP is especially appealing, as it delivers numerous benefits while maintaining important elements of t he natural ecosystem. Several studies have evaluated the role of vegetation within established pollutant removal vegetation in the stormwater system can provide for the be tter use of macrophytes for pollutant removal. as a component of fundamental nutrient cycles. The study describes the biogeochemical cycles for carbon, nitrogen, phosphorus, and toxic organic substances. Sharp reduction oxidation (redox) gradients were identified as an integral component of nutrient transformations in wetland systems. These redox gradients were enhanced by the vegetative transportation of oxygen from the atmospher e to the root zone. Furthermore, the relocation of oxygen intensified pollutant removal mechanisms by creating numerous anaerobic and aerobic interfaces. This process was found to be especially critical for the removal of nitrogen, and the study suggests t hat plant biomass may be used as a direct recognized that these conditions, created in part by vegetation, have significant potential to remove numerous toxic organic compounds. Overall, the study clearly illustrated several pollutant removal pathways and emphasized the importance of vegetation in principal nutrient cycles. Research was conducted by Zheng et al. (2006) to determine the influence of emergent vegetation on infiltra tion ponds treating urban runoff. The experiment studied
14 two urban infiltration ponds, one containing rooted vegetation and the other unplanted. The results showed that the presence of vegetation did not significantly impact infiltration rates; however, th e presence of tall vegetation was responsible for substantially reducing the frequency and intensity of filamentous algal blooms. In the end, how ever, both ponds failed to meet water quality standards established for this case study as 20 mg/L biological o xygen demand (BOD) and 30 mg/L suspended solids. 2.6 Science and Environmental Policy Environmental policymakers often rely heavily on the existing scientific literature when developing new regulations. However, this relationship is somewhat complicated by the uncertain nature of scientific information and variable environmental and social parameters, which undoubtedly impact the outcomes of well founded environmental policies (Herrick and Sarewitz, 2000) Consequently, the literature suggests that ex pos t evaluations, which incorporate the complex and long term character of environmental processes, are best employed to assess environmental policies and allow for an adaptive management approach to environmental management (Herrick and Sarewitz, 2000; Mickw itz, 2003). Mickwitz (2003) contends that the field of e nvi ronmental policy evaluation is somewhat primitive due to fragmented concepts, a lack of standardized methodologies and currentl y limited application These inefficiencies are exaggerated by the complex nature of environmental problems and the often high levels of uncertainty associated with scientific knowledge, especially that reg arding geographically large and/or distant regions. However, in recent years, enviro nmental policy evaluations have g arnered
15 increasing interest including mandated ex ante and ex post policy evaluations in many countries around the world, and considerable effort is now directed toward developing effective and reliable evaluation instruments. In the end, Mickwitz argues that the results of any single evaluation cannot be relied on exclusively, but must be synthesized with existing knowledge, in an effort to enhance regulatory outcomes in complex, real world scenarios. Herrick and Sarewitz (2000) discuss the role of scie nce in environmental policymaking in much the same way. However, in this case, the authors contend that because scientific uncertainty invariably leads to contestable results, environmental policymaking decisions are often poorly suited by predictive scie ntific assessments. Instead, Herrick and Sarewitz advocate broader application of ex post evaluations less reliance on predictive assessments, and employment of adaptive management principles. This approach respects the limits of scientific assessment s an d promotes a more individualized approach to solving environmental problems that more accurately addresses the complexity of the environment and tailors practices to achieve the best possible outcome. 2.7 Stormwater, Social Values, and Public Participat ion Effective stormwater management can also be accomplished through public awareness and is often an integral component of a more comprehensive management approach. Systematically embodying a spectrum of values in stormwater management decisions, includi ng social dimensions, can allow for a more balanced approach (Taylor and Flet cher, 2005). Additionally, emerging approach es to stormwater management
16 involve expanding the traditional end of pipe solutions, such as retention and detention basins, and i ncorp concept, which addresses pollutants at every stage in the stormwater system including preventative actions and source control (Ryan and Brown, 2000). C ontemporary stormwater management policies in Australia provide an ex cellent case study embodying the s e approach es and two related articles will be briefly discussed below. Taylor and Fletcher (2005) discuss an innovative decision making strategy specifically bottom (TBL ) guidelines incorporate financial ecological, and social considerations into policymaking decisions seeking to replace traditional cost benefit analyses and reflect ing the core principles of sustainability. The primary objective of the TBL approach is t o create a more socially acceptable and participatory stormwater management system to improve urban water quality and include s the solicitation of not only expert technical advice but also the views and opinions of the general public. While the article ide ntifies some limitations and lacks thorough evaluation of program outcomes, the TBL approach highlights the growing trend toward greater public participation in environmental management and policymaking. Ryan and Brown (2000) investigate the movement tow ard expanding traditional stormwater management practices from end of pipe solutions to include a much broader scope of concern. This expansion often engages the general public in stormwater management, attempts to change social behaviors, and aims to red uce pollutant sources. Ryan and Brown describe this ideological shift as a moving locus, migrating along the spectrum of management options, from physical intervention to social action (Figure 1).
17 Community education is one of the more popular manifestatio ns of this approach; although, scientific evaluation of program outcomes is again limited. Overall, the shift from end of pipe solutions to non structural controls, such as education and behavior modifications, represents a considerable transformation in t he field of stormwater management and warrants closer scientific inspection. Figure 1 Expansion of traditional stormwater management practices to include a broader perspective (Ryan and Brown, 2000).
18 CHAPTER 3: RESEARCH DESIGN 3.1 Problem State ment Do the efforts of the Hillsborough County Adopt A Pond program improve the overall physical health of participating stormwater ponds, including water quality and vegetative composition? 3.2 Research Objectives The ove rall objectives of the research p roject are : Observe fundamental water quality characteristics of stormwater ponds in the AAP program and control ponds by measuring concentrations of dissolved oxygen, total nitrogen, total phosphorus, chlorophyll a total suspended solids (TSS) and spe cific conductivity in addition to, water temperature pH, water clarity and turbidity. Observe the overall composition of emergent vegetation within stormwater ponds in the AAP program and control ponds by implementing the modified Lake Vegetation Index protocol originally developed by the FDEP. Explore the relationship between varying levels of AAP program activity and measureable environmental parameters in corresponding stormwater ponds.
19 Understand how the AAP program impacts participating stormwate r ponds and the broader implications of the AAP program on polluted urban runoff and regional water quality. The intent and completion of this research project wa s important for numerous reasons. The AAP program has been in existence since 199 2 and utiliz es considerable financial, intellectual, and operational resources. Yet, the program had never been thoroughly and scientifically studied until this point The AAP program is strongly founded in the scientific literature However, innumerable environmental and anth ropogenic variables can affect the degree of success achieved by sound scientific quantitatively link environmental rehabilitation with realized improvements in envir onmental parameters, such as measures of water quality and vegetative composition. Lake (2001) elaborates on the significance of effective post rehabilitation assessment and argues that its absence is the major hindrance to the field of restoration ecology and the evolution of improved restoration tec hniques. Hence this research project contribute s to the broader scientific community by contributing valid scientific information to an area of acknowledged deficiency in the literature. Furthermore, the res earch conducted here provide s direct benefits to both the Hillsborough County Public Works Department and SWFWMD The observations made here have le d to a better understanding of the AAP program and could lead to the development of improved rehabilitation practices and overall enhancement of the AAP program. Furthermore, the addition of scientific data to ultimately reinforce AAP
20 practices will strengthen overall confidence in the program and could result in greater political, financial, and public support. In the end, the con clusions reached by this research project can be used to increase the ability of the AAP program to reach its stated goals, resulting in greater overall water quality throughout Hillsborough County. Additionally, several other nonpoin t pollution reduction programs similar to the AAP program have been implemented across the country (Badics, 1993), including in neighboring Pinellas and Pasco Counties. The res ults obtained from this research project can also have substantial implications for these programs and can provide valuable information for municipalities considering implementing similarly designed programs. Overall, this study can provide feedback and further scientific justification for comparable nonpoint pollution reduction progr ams throughout the water management district and the country. 3.3 Experimental Hypotheses The research methodologies were then designed to address the following experimental hypotheses: 1. The Adopt A Pond program reduces nutrient eutrophication and the prevalence of detrimental algal communities within participating stormwater ponds. 2. Adopt A Pond program activities lead to improvements in water quality criteria, including concentrations of dissolved oxygen, nutrients, turbidity, and others.
21 3 T he Adopt A Pond program reduces the prevalence of invasive plant species within the emergent zone of participating stormwater ponds. 4 Emergent vegetation communities within stormwater po nds participating in the Adopt A Pond pr ogram score higher on the modified Lake Vegetation Index, indicating more natural and beneficial plant communities. 3.4 Null Hypothesis The following serves as the null hypothesis for this research project: 1. The Hillsborough County Adopt A Pond program has no statistically sig nificant impact on vegetative communities and water quality parameters within participating stormwater ponds, when evaluated on this broad scale.
22 CHAPTER 4: METHODOLOGY The following methodologies were designed and employed for all study observatio ns. 4.1 Sampling Protocol Since 1992 there have been approximately three hundred participants in the AAP program. In order to appropriately evaluate the program a random number generator was utilized to select 103 ponds for observation from the comp lete list of participants of which ninety were ultimately evaluated The additional thirteen ponds were eliminated from the study due to limited site access In addition, fifteen control ponds were chosen in order to provide a baseline for comparison of which eleven ponds were accessible and ultimately evaluated The controls were carefully chosen based on several criteria in an effort to closely resemble the overall characteristics found in the AAP population The control pond selection process was aid ed by the use of GIS software and included the application of several attribute limiting measures to identify the control population First, a GIS data set containing all the hydrologic features of Hillsborough County (HCRED, 2004) was limited to include
23 were further limited to include only those waterbodies less than ten acres in size, as only two AAP participants were larger than this benchmark. Next, this information was overlaid with a residential land use map, and hydrologic features were excluded based on their affiliation with other land uses. This operation yielded 2,048 separate hydrologic features P olygons were then randomly selected from this list using a random number genera tor for further investigation. Those randomly selected features were then visually inspected using aerial imagery. Only those control features falling in the same quarter township, approximately nine square miles, of at least one AAP pond were chosen for f urther evaluation. This process continued until fifteen ponds were identified, of which eleven were accessible and ultimately evaluated. This sample selection process, although somewhat involved, was selected to provide a degree of r andomness to the study, while work ing to eliminate sampling bias in the control population. 4.2 Water Analysis All water quality parameters were tested using a snapshot observation method, obtaining all relevant information during a single visit to each pond. Furthermore, w a ter quality analysis of all 101 ponds was conducted within an eleven day time period to limit the influence of ever changing environmental variables, such as temperature and precipitation. Vegetation analysis was conducted over approximately two months, as these characteristics were seen as less vulnerable to temporal variation. Additionally, water quality observations were not gathered immediately following any measureable precipitation event.
24 Water samples were gathered fr om each pond and analyzed accord ing to EPA approved gen eral purpose, analytical methods (EPA, 2008) Total nitrogen, total phosphorus, and chlorophyll a concentrations were assessed at the Florida Lakewatch laboratory in Gainesville, Florida. Tota l suspended solids (TSS) concentrations w ere analyzed at the state certified Hillsborough County Environmental Protection Commission laboratory in Tampa, Florida Other water quality criteria, including: dissolved oxygen concentrations specific conductivity, pH, water temperature, and turbidity were determined in the field using a Hydrolab Quanta multifunction water quality meter and were noted on the field data sheet (Appendix A) Water clarity was measur ed using a 120 cm Secchi disk tube. The resulting water quality data has been statistically analyzed and compared to identical observations made at the selected control ponds in order to illustrate the existing impacts of the AAP program. 4. 3 Vegetation Analysis The vegetation survey was conducted within a modified framework originally dev eloped by the FDEP for the Lake Ve getation Index and described in the publication by Fore et al. (2007). All proposed modifications were made considering the overall integrity of the index, yet allow for its adaptation to the new application used in this s tudy. Th i s modified Lake Vegetation Index (mLVI) protocol was repeated at each study pond. Before entering the field the pond was divided into twelve numbered segments using standard GIS software (Figure 2 ). This pattern of sampling is designed to incorp orate differing vegetation patterns surrounding the pond within the vegetation
25 survey. A basic GIS map, overlaying aerial imagery, was produced to aid in delineating the segment boundaries in the field. Figure 2 Diagram illustrating the segmentation o f the stormwater pond into twelve sections for vegetative analysis (Fore et al., 2007) Within each segment, a single quadrat, measuri ng 3 meters by 3 meters, was constructed using pre cut PVC pipes. Quadrats were evenly centered within the chosen segment in order to develop an accurate overview of vegetation within the selected area. Furthermore, the quadra t was placed at the existing waterline and extend ed toward the center of the pond in order to encompass vegetation within the emergent zone. All emerge nt vegetation species within the quadra t were identified using various literature sources and personal knowledge. Lastly, the dominant species for each quadrat was visually determined and noted on the field data sheet (Appendix B).
26 This vegetation data was used to calculate t he m LVI score s for each stormwater pond according to FDEP standard operating procedure (FDEP, 2008). The m LVI equation incorporates four variables, including: percent native species, percent inva sive species, dominant coefficient of conservatism (C of C) score and percent sensitive species (Fore et al., 2007). The coefficient of conservatism (C of C) score is commonly used in the environmenta l and anthropogenic disturbances, such as eutrophication. A high average C of C value indicates a relatively stable environment, while a low C of C value signifies highly disturbed ecosystems which are typically of lower overall quality. A slightly more i n depth explanation of the established C of C scoring system can be s een in the table below (Table 3 ). Coefficients of conservatism (C of C) values have be en drawn from existing literature for the purpose of this study ( FDEP, 2008 ) (Appendix D) Table 3 Brief explanation of the scoring system for established coefficient of conservatism scores (Fore et al., 2007).
27 The three other variables mentioned in the m LVI equation are percent sensitive species, percent native species, and percent invasive species Sensitive species are defined as those plant species with C of C values greater than seven. A greater percentage of sensitive species would indicate a more stable environment with higher overall quality (Fore et al., 2007). Again, C of C values will be d erived from existing literature ( FDEP, 2008 ). The designation of native or invasive species will also be derived from existing literature (FLEPPC, 2009) (Appendix D) The process of calculating the final m LVI score wa s completed using the four variables described above. First, each variable was translated int o unit less scores based on their fifth and ninety fifth percentile s and calculated according to the scoring rules below (Table 4) For variables that decrease with disturbance, such as average C of C value, the lowest percentile is assigned a value of zero, while the highest perce ntile is assigned a value of one For variables that increase with disturbance, such as percent invasive species, the lowest percentile is assigne d a value of one while the highest percentile is assigned a value a zero. In deriving the scoring rule, values above and below the ninety fifth and fifth percentiles, respectively, were left out to buffer extreme values. According, when using the scoring rule, values less than zero were given a value of zero and values greater than one were assigned a value of one. In this way, each variable is converted into a unit less score with a value of between zero a nd one according to methodology established in Fore et al. (2007). The final m LVI is the average of the four unit less scores multiplied by a constant to adjust the scale to 0 100 for convenience (Fore et al., 2007). Additionally, the m LVI score was first calculated for each individual quadrat. Then, a simple average of the individ ual quadrat m LVIs was calculated to
28 m LVI which was then recorded for further statistical analysis (FDEP, 2008). Table 4 Description of the modified LVI scoring criteria used to calculate the final metric score where x equals the individual value for a given quadrat 5 th Percentile 95 th Percentile Scoring Rule % Native Species 33.3 100 % Invasive Species 0 60 % Sensitive Species 0 14.3 Dominant C of C 0 6.37 4.4 Measures of Activity Lastly, measures of activity were gathered from existing administrative records to explore trends within the AAP population. First, active years in the program were measured for each participating pond. Secondly, a sum of the emergent plants donated to each pond was established, and these results were then normalized by the size of the
29 pond. Lastly, p rogram administered cleanup hours, including mechanical and chemical removal of invasive species, were tallied. Statistical b ivariate correlations were then measured for each of the three measures of activity and the resulting water quality and vegetative parameters described above (Section 4.2 and 4.3). All statistically significant correlations were further investigated using simple linear regression in order to measure the direction and magnitude of the relationship. Lastly, this information was used to approximate the quantitative impact of AAP program activity on water quality and vegetative characteristics within participating stormwater ponds.
30 CHAPTER 5: STUDY AREA The Adopt A Pond program currently operates throughout Hillsborough County, Flo rida (Figure 3 ). Hillsborough County is located along the western coast of central Florida and is situated on Tampa Bay. Large portions of the county are highly urbanized with an estimated populati on of nearly 1.2 million people and a population densi ty of approximately 951 persons/mile 2 (approximately 367 persons/km 2 ) (U.S. Census Bureau, 2009). The largest city within Hillsborough County is Tampa. 5.1 Tampa Bay Hillsborough County is situated on Tampa Bay, a four hundred square mile (1,035 sq km) subtrop ical estuary (Greening, 2002). Due, in part, to the adjacent human population, portions of the bay are currently impaired according to EPA and FDEP standards for methyl mercury and general coliform contamination (EPCHC, 2006). Dredging, eutrophication, and chemical contaminants have all contributed to widespread degradation of water quality (TBEP, 2006). In recent years, considerable efforts have been allocated for Tampa Bay restoration projects, most notably, attempts to expand seagrass coverage by curtail ing nitrogen loads to the bay (Greening, 2002). Currently, the leading source of nitrogen contamination to Tampa Bay is urban runoff (EPHC, 2006).
31 Figure 3 Map illustrating the distribution of the study AAP ponds throughout Hillsborough County, Florida 5.2 Climate Hillsborough County has a humid subtropical climate described as exhibiting hot and humid summers with relatively mild and wet winters (FCC, 2010). The mean annual temperature of Hillsborough County is 73.1 F (22.83 C) and the mean annu al precipitation is 44.77 inches (113.72 cm). Hillsborough County typically experience s rather wet summer seasons, with approximately sixty percent of annual precipitation, 26.13 inches (66.37 cm), falling between the months of June through September (NCDC 2004). Summer precipitation typically consists of afternoon thunderstorms caused by a strong sea breeze and convective heating (FCC, 2010).
32 5 .3 Geology a nd Topography The topography of Hillsborough County is relatively flat and low lying, with the elev ation rising from sea level to approximately 160 feet (49 m) above sea level along the eastern edge of the county (Menke, 1961). Hillsborough County is part of the Gulf Coast Lowlands physiographic unit (Randazzo and Jones, 1997). The Gulf Coast Lowlands a re characterized by low relief and sandy clay soils interspersed with calcareous rock. Numerous sinkholes are located throughout Hillsborough County and are concentrated in the northwest region. The county overlies the Floridan Aquifer (van Beynen et al., 2007). 5. 4 Land Use Hillsborough County is 1,136 square miles (approximately 726,000 acres), much of which is highly urbanized. Approximately forty four percent of the county is considered to have an urban land use, twenty six percent of which is catego rized as urban residential areas. However, the county also has significant areas of agricultural land s and wetlands, nineteen and seventeen percent, respectively. Seven percent of Hillsborough County is considered upland forests and seven percent water (FC CD, 2005). The figure below visualizes the relative percentages of various land uses in Hillsborough County (Figure 4).
33 Figure 4. Land use in Hillsborough County by total land area (FCCD R 2005). 5. 5 Hydrology Three primary surface basins drain Hillsb orough County into Tampa Bay, including the Hillsborough, Alafia, and Little Manatee river systems (Menke, 1961). In addition, t he considerable human population present in Hillsborough County necessitates large areas of impervious surfaces. Based on data from 2001, 23% of Hillsborough County exceeds 10% imperviousness, while 17% of the county exceeds 25% imperviousness. These levels of imperviousness can be expected to generate moderate to severe impacts on water quality and has created considerable altera tions to the original surface hydrology of the region (EPCHC, 2006). The map below illustrates the distribution of impervious surfaces throughout Hillsborough County (Figure 5 ). 44% 19% 17% 7% 7% 3% 2% 1% Land Use In Hillsborough County Urban Agricultural Wetlands Water Upland Forests Open Land Rangelands Recreational
34 Figure 5 Map illustrating the distribution of impervious surfaces througho ut Hillsborough County, Florida (EPCHC, 2006).
35 CHAPTER 6: RESULTS AND DISCUSSION Each study parameter underwent initial evaluation to determine descriptive statistics and eliminate outlying observations, defined for the purpose of this study as value s lying outside three standard deviations from the m ean. Ultimately, ninety five ponds were used for the fina l statistical analysis, eighty four AAP participants and eleven control ponds. Then, independent sample t tests were calculated for all study param eters to compare the means of the t wo study populations. T his information was then analyzed to determine any variation between AAP participants and the background control population. Additionally measures of program activity, including: active years in t he program, amount of vegetation contributions, and program administered cleanup hours, were utilized to explore trends within the AAP population. Lastly, observations made for the AAP population were compared to those found by other researchers and availa ble in the literature. The following results were considered relevant to the study objectives. 6.1 Data Characteristics Both study populations illustrated a classically normal distribution for many study parameters (Figures 6 8 ). Other study parameters exhibited an approximately normal distribution with means shifted toward the upper or lower li mits of obse rvational
36 restrictions (Figure 9 1 3 ). The distribution of water clarity depths and TSS values for the study control ponds appears to have a somewha t bimodal distribution; however, it seems this may be a function of the limited number of observations in t he control population (Figure 1 3 and 1 4 ). Overall, after elimination of outlying observations, the data proved well suited for more advanced statisti cal analysis. All experimental observations can be found in Appendices C, D, and E. Additionally descriptive statistics for both study populat ions can be found below (Table 5 ). This basic analysis reveals comparable mean s for both study populations acros s most study parameters Furthermore, nearly all parameters can be characterized by relatively high standard deviations. Figure 6 Histograms illustrating the distribution of mLVI scores calculated for both study populations.
37 Figure 7 Histo grams illustrating the distribution of Invasive Plants Species percentages calculated for both study populations. Figure 8 Histograms illustrating the distribution of Total Nitrogen concentrations observed for both study populations.
38 Figure 9 Histograms illustrating the distribution of Total Phosphorus concentrations observed for both study populations. Figure 10 Histograms illustrating the distribution of Chlorophyll a concentrations observed for both study populations.
39 Figu re 11 Histograms illustrating the distribution of Turbidity values observed for both study populations. Figure 1 2 Histograms illustrating the distribution of Dissolved Oxygen Saturation percentages observed for both study populations.
40 Figur e 1 3 Histograms illustrating the distribution of Total Suspended Solids concentration s observed for both study populations. Figure 1 4 Histograms illustrating the distribution of Water Clarity depths observed for both study populations.
41 Table 5 Comparison of basic descriptive statistics for water quality and vegetative parameters in both study populations. AAP Mean Std Dev. Control Mean Std Dev. TSS [mg/L] 6.63 5.15 7.00 4.38 Chlorophyll a [g/L] 36.82 34. 93 43.24 38.21 Turbidity [NTU] 20.92 17.24 24.61 13.56 Water Clarity [cm] 85.23 30.97 80.63 34.10 D.O. [mg/L] 4.83 3.21 6.08 3.12 Oxygen Saturation [%] 61.97 45.68 81.53 43.52 Total Nitrogen [g/L] 1239.17 591.56 1030.00 378.39 Total Phosphorus [g/L ] 113.72 103.32 65.91 37.34 mLVI [units] 38.92 13.34 45.09 13.62 Invasive Species [percent] 28.07 12.35 18.00 13.72 6.2 Comparing Study Population s Comparisons were then made betwe en AAP participants and control ponds using independent sample t tests for both water quality and vegetative characteristics, to demonstrate any statistically significant deviation that may exist between the two study populations.
42 6.2.1 Water Quality Parameters Multiple water quality parameters were evaluated as d escribe d above (Section 4 .2 ) Independent sample t tests were performed to illustrate any significant differences between the two study populations. The results showed that mean total phosphorus concentrations were higher in AAP ponds than in control ponds at nin ety five percent confidence (p value = 0.005). Independent sample t tests failed to show any statistically significant difference between the means of the two study populations for all other w ater quality parameters The table below provides the probabilit ies for obtaining each water (Table 6 ). Table 6 Illustrates the results of the independent sample t tests for all water quality parameters. P Values Chlorophyll a [g/L] 0.606 Dissolved Oxygen [mg/L] 0.234 Water Clarity [cm] 0.678 Total Nitrogen [g/L] 0.129 Total Phosphorus [g/L] 0.005 Turbidity [NTU] 0.427 T.S.S. [mg/L] 0.798
43 6.2.2 Vegetation Analysis Invasive plant species percentages and mLVI metric scores were evaluated for all po nds as described above (Section 4.3), and independent sample t tests were performed to illustrate any significant differences between the two study populations. The results showed that mean invasive plant species percentages were higher in AAP ponds than i n control ponds at ninety five per cent confidence (p value = 0.039 ). Independent sample t tests failed to show any statistically significant difference between the mean mLVI scores of the two study populations The table below provides the probabilities fo r obtaining (Table 7 ). Table 7 Illustrates the results of the independent sampl e t tests for study vegetation parameters. 6.2.3 Significance of Population Comparison The comparison between AAP participants and control ponds indicated the AAP population had a significantly higher mean invasive species percentage and significantly higher mea n total phosphorus concentration both indicating general impairments in the AAP program. All other parameters, including mLVI scores, water clarity, turbidity, and P Value s m LVI [units] 0.1 81 Invasive Species [percent] 0.039
44 concentrations of dissolved oxygen, total suspended solids (TSS), total nitrogen, and chlorophyll a, were found to be stati stically identical. However, as it turns out, this comparison may not be entirely fair. The AAP program is strictly voluntary. Therefore, applicants are often driven to participate only if neighboring ponds exhibit some undesirable symptom, such as alga l blooms or an overgrowth of invasive species. Consequently, AAP applicants may enter the program at an impaired level when compared to background, control ponds, and comparison between these two populations ma y not be entirely legitimate. According to thi s scenario, it is quite possible that AAP program applicants have significantly improved since entry into the program, yet, still remain at an impaired level when compared to the control population. However, the analysis is useful in show ing how water qual ity and vegetative characteristics within AAP participants compare to similar control ponds throughout Hillsborough County. So, while the results are somewhat ambiguous, this analysis does indicate AAP ponds have significantly impaired mean invasive specie s percentages and mean total phosphorus concentrations when compared to other, similar ponds within Hillsborough County. 6. 3 Trend Analyse s within AAP Population Three measures of act ivity, derived from AAP administrative records, were used to explore trends within the AAP population. First, the length of time each pond was active in the program was calculated for each participant and described as the variable active years Secondly, a sum of the emergent plants donated to each pond was established, and these results were then normalized by the area of the pond. Lastly,
45 program administered cleanup hours were tallied for the tenure of AAP membership including resident administered maintenance and staff administered mechanical and chemical removal of inv asive species. Statistical correlations were then explored between these three variables, referred to collectively as measure s of program activity, and the study water quality and vegetative parameters in order to investi gate how program activity may impa ct the physical environment of study stormwater ponds 6.3.1 Water Quality and Program Activity Statistical bivariate correlations were explored between all water quality parameters and the three measures of program activity. Analysis showed a statistica lly significant and positive correlation between TSS and active years in the AAP program (R square = 0.064). Simple linear regression was then employed to explore this co rrelation. The results indicate that TSS concentrations seemingly increase as length o f program activity grows, an obviously undesirable, yet unexplained, phenomena. This relationship is illustrated below (Figure 1 5 ) and is statistically significant at ninety fi ve percent confidence (Table 8 ). All other study water quality parameters were n ot significantly correlated with measures of activity at ninety five percent confidence.
46 Figure 1 5 Illustrates the positive relationship between TSS concentrations and active years in the AAP program for study ponds. Table 8 Results of regression an alysis describing the relationship between TSS and Active Years in the AAP program, where TSS = 0.625(Active Years) + 4.907. R 2 Value F Value t Value p Value Std. Error Model 0.064 4.930 0.030 5.122 B 0 5.159 0.000 0.951 B 1 2.220 0.030 0.281
47 6.3.2 Vegetation and Program Activity An identical analysis was conducted on the two vegetative parameters to again explore potential correlations with the three measures of program activity. The analysis indicated a statistically significant and posit ive correlation between sample mean mLVI scores and the number of AAP donated p lants per acre. Again, s imple linear regression w as used to explore this relationship. T he results indicate that AAP program contributions of emergent vegetation subsequently im prove mLVI scores of corresponding ponds. The magnitude of the relationship indicates that a donation of approximately five hundred plants per acre could be expected to raise the mLVI score of the selected pond by one point. This relationship is displayed below (Figure 1 6 ) and is significant at ninety percent confidence (Table 9 ).
48 Figure 1 6 Illustrates the positive relationship between mLVI scores and plants/acre donated by the AAP programs. Table 9 Results of regression analysis describing the rel ationship between mLVI scores and AAP donated Plants/Acre, where mLVI = 0.00 2(Plants/Acre) + 35.482 R 2 Value F Value t Value p Value Std. Error Model 0.044 3.264 0.075 13.078 B 0 19.501 0.000 1.880 B 1 1.807 0.075 0.001
49 Additionally, the bi variate correlation analysis indicated a statistically sign ificant and negative relationship between sample mean mLVI scores and the number of AAP pro gram administered cleanup hours Again, simple linear regression was used to explore the relationship betw een the two variables The results indicated that mLVI score of a given pond were diminished as program administered cleanup hours increased. However, the LVI is designed to capture measures of disturbance; so, this finding is not entirely unexpected. The relationship is illustrated below (Figure 17) and was significant at ninety fi ve percent confidence (Table 10 ) All other bivariate correlations between measures of program activity and study vegetation parameters were found to be not statistically signifi cant.
50 Figure 1 7 Illustrates the negative relationship between mLVI scores and AAP program administered cleanup hours. Table 10 Results of regression analysis describing the relationship between mLVI scores and program administered Cleanup Hours, wh ere mLVI = 0.127(Cleanup Hrs) + 41.427 R 2 Value F Value t Value p Value Std. Error Model 0.146 8.053 0.007 9.980 B 0 22.521 0.000 1.839 B 1 2.838 0.007 0.45
51 6.3 .3 Significance of Trend Analyse s Measures of program activity and simple lin ear regression tools were implemented to explore trends within the AAP population, and illustrated several significant findings (Section 6.3.1. and 6.3.2.). However, the results failed to indicate any clear benefits of the AAP program, e.g. while a positiv e relationship was shown between mLVI scores and program donated plants per acre, a negative relationship was shown between mLVI scores and program administered cleanup hours. Additionally, a positive relationship was illustrated between TSS concentrations and the number of active years participating in the program. Therefore, no clear consensus can be drawn from the analysis. Overall, the results fail to indicate any clear benefit of AAP program participation for both water quality and vegetative compositi on. 6.4 Pond Performance in Comparison to the Literature Other similar studies in the literature provide valuable background information regarding the expected water quality in residential stormwater ponds (Sections 2.1 and 2.3). Subsequently, statistic al t tests were employed to explore how well water quality parameters in AAP program ponds compare to those found in the literature for similar ponds in the region. Harper and Baker (2007) provide quantitative estimates for both stormwater runoff contami nation and pollutant removal efficiencies for residential detention ponds (Section 2.1 and 2.3). This information was used to predict the outflow pollutant concentrations for similar ponds and compared to the mean values for study observations
52 made in AAP program ponds. The predicted outflow concentrations and mean AAP observations are shown below (Table 11). Table 11. Comparison of predicted outflow concentrations and mean AAP observations for select water quality parameters. Predicted Concentrations Mea n AAP O bservations Total Nitrogen [g/L] 1304.1 1239.17 Total Phosphorus [g/L] 115.32 113.72 Total Suspended Solids [mg/L] 8.625 6.63 Statistical t tests were then employed to determine whether AAP observations differed significantly from those valu able derived from the literature. The results indicate that mean total nitrogen and mean total phosphorus concentrations for AAP participan ts were comparable to those mea n values predicted in the literature at ninety five percent confidence. However, the m ean concentration of total suspended solids (TSS) for the AAP population was significantly lower than the mean value predicted in the literature, with mean values ranging from 0.9 to 3.0 mg/L less in AAP ponds than the value predicted in the literature at ninety five percent confidence. The results of all three analyses are illustrated below (Table 12) and show the probabilities for each test statistic calculated.
53 Table 12. Results of the statistical t tests comparing pollutant concentrations in AAP parti cipants to those predicted in the scientific literature. P Value s Total Nitrogen [g/L] 0.133 Total Phosphorus [g/L] 0.481 Total Suspended Solids [mg/L] 0.0004
54 CHAPTER 7 : CONCLUSIONS These results seemingly point to a broad scale ineffect iveness in the AAP program by failing to demonstrate any clear benefits of program participation. However, there are several complicating factors which demand further research and will be discussed below (Section 7 .2 ). Additionally, the AAP program may be nefit from an expanded approach to structural stormwater management, incorporating a variety of treatment options throughout the catchment. In the end, the se results clearly illustrate the need for a strong evaluation component when developing environmenta l policie s and rehabilitation projects. 7 .1 Interpretations and Experimental Hypotheses In the end, the observations made in this research project dictate the acceptance of the null hypothesis posed above (Section 3.4). No clear and demonstrable differen ces could be illustrated between AAP participants and background control ponds on this broad scale. While the phosphorus concentrations and invasive species percentages were shown to be significantly higher in AAP participants, all other environmental para meters were shown to be statistically identical. Additionally, measures of program activity failed to show any clear, directional impact of program participation. Lastly, mean TSS
55 concentrations were found to be lower in AAP participants than was predicted in the literature, but other water quality parameters were in line within expected ranges. Overall, we believe these results fail to show any distinct and reliable differences between the two study populations; therefore, the null hypothesis has been acce pted for the purposes of this study, and it is the finding of this research project that the Hillsborough Adopt A Pond program has no statistically significant impact on vegetative communities and water quality parameters within participating stormwater po nds, when evaluated on this broad scale. 7 .2 Future Research Several discrepancies were identified during the course of this research project, many of which may provide considerable opportunity for future research efforts. First as introduced above (Sec tion 6.2.3 ), the statistical comparison between AAP participants and study identified control ponds may not be an entirely equitable comparison, as the AAP program likely attracts ponds which exhibit some visible and undesirable symptom s of poor environmen tal quality, e.g. algae blooms or an overgrowth of invasive plant species. Consequently, applicants to the AAP program would be of lower overall environmental quality when compared to the broader population of stormwater ponds in Hillsborough County. There fore, future research on this topic should aim to provide a entering the AAP program, and evaluates the pond as it progresses through milestones in the AAP program. This t ime series of data would better evaluate the impact of AAP participation and would eliminate the potentially inequitable comparison to study
56 identified control ponds I ncorporat ing complementary observations collected from a comparable, and ideally adjacen t control pond c ould add another beneficial dimension to the study. Moreover, the AAP program has been primarily designed as an educational and outreach program, an aspect which has been excluded from this analysis and likely contributes considerable ben efit to the community. Furthermore, anecdotal evidence points to an overall community satisfaction with the AAP program. Residents seem to have a positive outlook regarding their interactions with the AAP program and appear content with changes in pond aes thetics and perceptions of environmental quality. However, systematic evaluations are necessary to scientifically define this relationship and provide some measure of educational and community benefits. Lastly, innumerable extraneous factors likely influe nced the results of environmental observations made in this study, many of which would provide for interesting analysis, including: the median income of house holds within the catchment and the age of the subdivision. Socio demographic characteristics can p rovide some insight as to how behavior impacts environmental health, and the age of the subdivision could potentially illustrate the impact of changing regulations in regards to stormwater pond construction and stormwater management. Overall, the foundatio n of water quality and vegetative observations established here could provide for a number of interesting studies in the future.
57 7 .3 Recommendations to Enhance Program Outcomes The conclusions reached here clearly illustrate some room for improvement regarding current AAP practices, and determining exactly how to improve prog ram outcomes is a complex task.. However, after evaluating the program and the available scientific literature, several avenues are apparent. 7 3 .1 Intensification The foundation al assumptions of the program are strongly based in the scientific literature, e.g. increasing vegetative buffers can reduce nonpoint source pollution ( Reddy ). However, due to the volunteer nature of the program, part icipation is somewhat deficient. AAP participants are typically active for relatively short periods (Mean = 2.5 years) and fail to account for the long time spans necessary for environmental processes to take hold. Furthermore, activity is often sporadic a catchment. Logistically this may be the only way to implement the program, as evoking volunteer participation of fifty percent or higher would be virtually impossible. However, t hese fa ctors likely combine to dampen the impact of AAP rehabilitation practices Therefore it is recommended that the AAP program focus and intensify its efforts in order to achieve improved program outcomes D irectly engaging only five househol ds within a catc hment of fifty to one hundred does not adequately address the scale of the problem, and limited results can be reasonably anticipated. Therefore, a ll efforts should be made to increase program participa tion perhaps through enhanced program rewards for nei ghborhoods achieving significantly high er levels of participation. In this way,
58 considerable change can be effected within engaged communities and enhanced program outcomes can be realized. 7 3 .2 Diversification In addition to a general intensification, a thoughtful diversification of AAP practices is also recommended. Currently, AAP efforts are directed toward one of two ends, either source control through education or enhancing stormwater ponds, what is essentially an end of pipe approach However, eff ective stormwater management is a complex and formidable challenge, one which cannot be wholly encompassed by this dichotomous appr oach. Instead, a broad range of prudent management techniques are recommended. This diversified approach should emb ody the t reatment train concept advanced by Ryan and Brown (2000) and embrace low impact development principles, changing not only the features of stormwater ponds and their nearest neighbors but also the characteristics of the catchment itself. Practically, this approach may include: reductions in impervious surfaces, increased bioretention spread throughout the catchment, and stormwater reuse projects, in addition to the educational and pond enhancement efforts currently bei ng achieved by the AAP program. In the end, to achieve effective stormwater management, nonpoint source pollutants should be addressed at every opportunity from source to sink, and incorporating this approach into existing AAP ideologies could results in improved program outcomes. Overall, d iversifying and int ensifying current efforts could be the essential component s necessary to achieve improve program outcomes However, i n the end, an
59 evolution in cultural norms and popular ideologies may be necessary to ultimately achieve stormwater manag ement of this character. 7 .4 Concluding Remarks Overall, water quality and vegetative analysis of ninety five stormwater ponds failed to demonstrate statistically significant benefits of the Hillsborough County Adopt A Pond program on this broad scale of analysis Further research is currently being implemented to more accurately define the problem and enhance AAP restoration techniques, including time series evaluation and controlled experiments designed to validate the foundational assumpt ions of the pr ogram and appraise potential alterations to current practices. In the end, these results poi nt to the broader need for ex post policy and post rehabilitation evaluat ion discussed above (Section 2.6 ). While environmental policies and rehabilitation plans are often strongly founded in the scientific literature, innumerable environmental and anth ropogenic variables can affect the degree of success achieved by Strong evaluation components, dr afted alongside environmental policies and restoration plans, can encourage an adaptive management approach to environmental management and ensure more widespread success.
60 LIST OF REFERENCES An dreas, B. K. and Lichvar, R.W. ( 1995 ) Floristic Index for Establishing Assessment Standards: A Case Study for Northern Ohio. Wetlands Research Program Technical Report WRP DE 8. United States Army Corps of Engineers, Waterways Experiment Station. Vicksburg, MS. Badics, R (1993) Development and Implementation of an Urban Nonpoint Pollution Educati onal and Informational Program. Seminar Publication: National Conference on Urban Runoff Management: Enhancing Urban Watershed Management at the Local, County, and State Levels Chicago, IL. 408 410. Bavor, H. J., Davies, C. M. and Sakadevan K (2001) Stormwater Treatment: Do Constructed Wetlands Yield Improved Pollutant Management Performance Over a Detention Pond System?. Water Science and Technology 44( 11 12 ), 565 570. Environm ental Protection Agency (EP A). (2008) Approved General Purpose Methods.
61 Florida Center for Community Design and Research (FCCDR). (2005). Hillsborough County General Information. Hillsborough Community Atlas. University of South Florida. < http://www.hillsborough.communityatlas.usf.edu > Accessed on March 25 2011. Florida Climate Center (FCC). (2010). Climate of Florida. Florida State University. < http://www.coaps.fsu.edu/climate_center/index.shtml >. Accessed on March 25 2011. Florida Department of Environmental Protection (FDEP). (2008) LT 7000: Determinatio n of FDEP Standard Operating Procedures. Florida Exotic Pest Plant Council (FLEPPC). ( 2009 ) List of Invasive Plant Species. Wildland Weeds 12( 4 ), 13 16. Fore, L. S ., Frydenborg, R., Wellendorf N., Espy, J., Frick, T., Whit ing, D., Jackson, J., and Patronis J (2007) Assessing the Biological Condition of Florida Lakes: Development of the Lake Vegetation Index (LVI) Florida Department of Environmental Protection. Graves, G. A., Wan, Y. and Fike D. L (2004) Water Qua lity Characteristics of Storm Water from Major Land Uses in South Florida. Journal of the American Water Resources Association. 40 ( 6 ), 1405 1419. Greening, H. (2002) Implementing the Tampa Bay Seagrass Restoration Management Strategy. Proceedings: Se agrass Management It's Not Just Nutrients!. St. Petersburg, FL. 29 37.
62 Harper, H. H. and Baker D. M (2007) Evaluation of Current Stormwater Design Criteria within the State of Florida. Final Report. Florida Department of Environmental Protectio n. Herrick C. and Sarewitz, D. (2000) Ex Post Evaluation: A More Effective Role for Scientific Assessments in Environmental Policy Science Technology and Human Values 25 ( 3), 309 331 Hillsborough County Real Estate Development (HCRED). (2004) Hyd ro. Survey and Mapping Division, GI S Section. Shapefile. Lake, P. S. (2001) On the Maturing of Restoration: Linking Ecological Research and Restoration. Ecological Management and Restoration 2(2), 110 115. Marsalek, J., Watt, W. E., and Henry D. (199 2) Retrofitting Stormwater Ponds for Water Quality Control Water Pollution Research Journal of Canada 27(2), 403 422. Menke, C. G. (1961) Water Resources of Hillsborough County, Florida Electronic. T allahassee, FL: United States Geologic Survey Mi ckwitz, P. (2003) A Framework for Evaluating E nvironmental Policy Instruments : Context and Key Concepts. Evaluation 9( 4 ), 415 436 National Climatic Data Center (NCDC). (2004) Climatology of the United States No. 20 1971 2000. National Oceanic and Atmosp heric Administration.
63 Reddy, K. R. and E. M (1997) Biogeochemical Indicators to Evaluate Pollutant Removal Efficiency in Constructed Wetlands. Water Science Technology. 35( 5 ), 1 10. Ryan, R and Brown R. (2000) The Value of Participation in Urban Watershed Management. Proceeding of the Water Environment Federation. Wa tershed 2000 Vancouver, Canada .18 1577 1594. Sartor, J. D., Boyd, G. B., and Agardy, F. J (1974) Water Pollution Aspects of Street Surface Contaminants. Journal of the Water Pollution Control Federation. 46( 3 ), 458 467. Serrano, L. and DeLorenzo M. E (2008) Water Quality and Restoration in a Coastal Subdivisio n Stormwater Pond. Journal of Environmental Managemen t. 88 43 52. Su, J., Ho C., and Tapia E. J (2004) Stormwater GIS. Conference Proceedings: ESRI Intern ational User Conference Tampa Bay Estuary Program ( TBEP ). (2006) Charting the Course: The Comprehensive C onservation and Management Plan for Tampa Bay. Bottom Stormwater Projects. T enth Annual Conference on Urban Drainage. Copenhagen, Denmark. U nited S tates Census Bureau. (2009) Hillsborough County, Florida. State and County QuickFacts
6 4 Van Bey nen, P., Feliciano, N., North, L., and Townsend K (2007) Application of the Karst Disturbance Index i n Hillsborough County, Florida. Environmental Management 39( 2 ), 261 277. Wong, T.H.F., Breen, P. F., and Somes, N. L. G. (1999) Ponds Vs Wetlands Performance Considerations in Stormwater Quality Management. Conference Proceedings: First South Pacific Conference on Comprehensive Stormwater and Aquatic Ecosystem Management. Auckland, New Zealand. 2 223 231. Xian, G., Crane, M., and Su J. (2007) An Analysis of Urban Development and Its Environmental Impact on the Tampa Bay Watershed. Journal of Environmental Management. 8(5), 965 976. Zheng, J., Nanbakhsh, H., and Scholz M. (2006) Case Study: Design and Operation of Sustainable Urban Infiltr atio n Ponds Treating Storm Runoff. Journal of Urban Planning and Development 132(1), 36 41.
65 APPENDIX A: WATER QUALITY FIELD DATA SHEET
67 APPENDIX B: VEGETATION FIELD DATA SHEET
70 APPENDIX C: WATER QUALITY OBSERVATIONS
71 A AP ID Name D.O. [mg/L] Tur bidity [NTU] Clarity [cm] TSS [mg/L] TP [g/L] TN [g/L] Chlorophyll a [g/L] 92 004 University Village 4.85 9.2 43 13 108 1160 76.9 92 021 Windsor Park 7.37 7 50.4 106 1000 61.5 93 035 Keystone Crossings 0.78 13.3 120 1 36 6 50 7 93 043 Northdale Section C 6.51 60.5 42.4 13 96 1520 133.3 93 055 Villager Place 1.26 47.5 55.4 13 2410 23.9 94 066 Country Place Unit 4 B 4.88 16.4 106.6 7 56 1270 10.8 94 074 Bloomingdale East 9.24 18.5 120 5 93 1080 9.6 94 084 Bloomingdale S ection R 2.6 12.8 78.2 4 120 1020 39.7 94 091 Henderson Subdivision 1.4 18.5 66.7 7 203 2080 197.7 95 182 Northdale Section K II 2.22 38 112.6 3 178 2040 30 95 213 Bloomingdale P Q 1.6 11.6 78.9 2 208 2650 1.1 96 223 Turner Trace 7.15 2.3 120 5 41 96 0 17.2 96 225 Stonegate 5.18 2.4 120 1 37 730 9 96 226 Twin Branch: Maverick 2.86 26.6 75.2 5 317 1650 38.3 96 227 Florida Aquarium 9 4.6 120 2 70 380 11.7 97 232 East Village 4.28 18.9 55.9 7 128 1400 75.2 97 233 Country Lakes 4.23 1.2 120 62 1060 64.2 97 234 Sugarwood 0.96 33.1 80.6 2 130 1050 11.2
72 AAP ID Name D.O. [mg/L] Turbidity [NTU] Clarity [cm] TSS [mg/L] TP [g/L] TN [g/L] Chlorophyll a [g/L] 97 238 Lake Chapman 4.35 7.4 120 20 79 1210 12.7 97 244 Twin Branch: Acre Saddle 3.72 20 61.3 8 442 1700 39.9 98 01 Stonehedge 8.45 30.1 43.3 14 61 1170 92.3 98 02 Avista Group 12.88 5.4 120 7 53 980 19.5 98 12 Twin Branch: Horseshoe 3.85 28.3 56.6 10 282 1610 5.4 98 19 Twelve Oaks Lake 7.62 6.9 120 6 35 580 32.6 98 22 The Cove 7.77 12.8 68.2 7 49 1020 31.7 98 23 Palm Ridge 0.65 34.1 62.6 22 2120 38 98 25 Trucious Pond 7.55 50.3 60.4 18 93 1660 147.1 98 27 Hickory Lakes Manor 0.7 69.5 92 1630 30.3 98 29 River Hills Country Club 8.47 7.9 52.6 7 93 820 21.5 99 04 Villas on the Green 5. 84 2.6 120 2 42 1420 9.2 99 05 Wolski Group 6.68 28.3 120 9 59 1120 34.7 99 06 Bristol Green 7.94 15.5 39.3 12 237 2850 38.7 99 07 Laurel Woods 13.32 66.7 40.2 22 87 1620 115.8 99 09 Pico Pond 5.34 8.6 100.8 3 108 650 18.9 99 13 Town Park 5.92 33.9 77 .8 7 44 900 24.8
73 AAP ID Name D.O. [mg/L] Turbidity [NTU] Clarity [cm] TSS [mg/L] TP [g/L] TN [g/L] Chlorophyll a [g/L] 99 20 Belle Meade 10.71 29.8 91.4 4 24 700 26.8 99 21 Country Crossings 9.82 15.7 94.8 2 61 870 21.1 00 05 Thompson East 1.09 36. 5 66 6 128 920 40.1 00 13 Kingfisher 1.72 19 82.4 7 147 2410 1.3 01 04 Twelve Oaks Smaller 7.62 4 69.8 3 38 880 29.1 01 06 River Close 10.35 35.4 49 16 497 1260 93.7 01 11 Cole Logan 1.81 22.6 120 2 22 640 18.2 01 12 Osprey Park Ponders 0.28 3.21 39 1 1 152 1070 59.6 01 15 Temple Terrace Woods 2.64 32.1 32.6 462 2450 67.3 02 01 Shadow Crest 2.38 1.1 110.8 4 64 640 20.1 02 06 Casa del Lago 2.48 70.3 120 1 50 820 53.1 02 11 Rustling Oaks 0.7 98.5 15 154 1320 46.8 02 14 1.45 44.3 120 2 63 950 18.9 02 15 Whisper Sound 5.46 4.2 62.3 3 74 1330 26.4 03 04 Falcon Creek Place 2.61 14 98.6 9 252 2060 45.6 03 15 Heathridge Park 7.15 12.7 58.3 7 59 950 30.7 03 16 Lake Ellen Woods 1.68 8 108.8 2 33 800 15.4
74 AAP ID Name D.O. [mg/L] Turbidity [NTU] Clarity [cm] TSS [mg/L] TP [g/L] TN [g/L] Chlorophyll a [g/L] 03 17 Reynoldswood Pond 2.16 0.2 120 0 46 990 12.4 0 4 0 4 B o y e t t e S p r i ng s: P ar kh ur st 0 6 2 9 7 6 4 2 7 2 9 7 1 5 9 0 3 4 4 04 10 Rosemere 2.84 4.4 120 9 21 860 10.5 04 17 NE Shadow Pond 1.68 8. 9 120 3 38 760 10.3 05 01 Cedar Creek 4.37 21.3 67.4 5 218 1120 70.5 06 01 Osprey Park 2.55 21.4 65.8 3 99 920 17.5 06 06 Brussels Boy III 5.83 49.6 120 2 21 610 8.8 06 07 Brussels Boy IV 10.15 20.4 120 1 13 1000 6 06 09 Hunters Glen 7.04 6.2 109.6 6 22 580 14.9 06 15 Palamino Ct. 3.87 11.5 53.8 8 259 1740 43.9 06 17 Nutrixan 0.6 15.6 102.2 7 37 1690 18.2 06 19 Crippenwood III 1.51 15.8 120 1 59 1170 12.4 06 24 Boyette Springs: Veteran 3.83 9.2 120 3 66 950 13.6 06 25 Pemberton Creek 1.04 35.2 73. 4 1 309 1190 7.6 06 29 Bloomingdale Section H 5.21 10.9 51.2 6 169 1140 50.2 06 33 Manorwood Circle 2.81 38.9 93.4 5 95 1790 33 06 34 Summer Springs 6.33 42.3 120 1 19 590 8.6
75 AAP ID Name D.O. [mg/L] Turbidity [NTU] Clarity [cm] TSS [mg/L] TP [g/L] TN [g/L] Chlorophyll a [g/L] 06 35 Lake Forest 3.11 7.7 42 14 88 1430 87 06 39 Lake St. Clair 7.33 9 120 2 10 530 9.2 07 02 Forest East 4.6 4 61 4 41 900 22 07 03 Forest North 5.6 10.3 38.7 10 62 1490 65.6 07 09 Looking Glass 4.3 17.6 99.8 12 140 1090 43.2 07 11 Lennard Longhorns 6.69 44.5 56.6 3 55 570 15.4 07 12 Tweedle Dee 2.29 58.1 120 4 209 1970 19.2 07 14 Dewey Rose 2.63 34.8 120 1 108 1070 16.4 08 12 Rolling Springs 8.32 20.3 45.6 7 75 940 37.8 08 13 Tarawood Subdivision 6.99 16.7 60.8 6 89 800 33 08 16 Carroll Grove Estates 5.14 67.3 120 4 57 530 39 09 01 Pinerose Yacht Club 0.91 22.7 7 295 3510 112 09 03 Valrico Oaks 12.22 20.5 50.5 15 81 1710 53.9 09 05 Golden Antler Pond 8.56 0 120 14 26 540 3.8 09 06 Plantation Greenbrook 7.34 8. 1 120 2 76 990 16.9 Control Pond 0 6.03 10.9 69.6 7 20 760 13.9 Control Pond 1 3.94 10 83.8 4 44 1080 37.5
76 AAP ID Name D.O. [mg/L] Turbidity [NTU] Clarity [cm] TSS [mg/L] TP [g/L] TN [g/L] Chlorophyll a [g/L] Control Pond 3 0.51 25.5 75.4 11 1 33 1450 138.6 Control Pond 4 2.72 36.6 120 3 61 920 10.6 Control Pond 5 9.04 33.8 45.4 12 56 1360 64.7 Control Pond 6 10.17 51.5 120 2 120 690 28.7 Control Pond 7 10.33 11.2 120 4 21 540 9.4 Control Pond 8 4.92 30 120 4 41 810 17.6 Contro l Pond 9 8.15 8.3 49.8 14 55 930 54.7 Control Pond 12 5.06 27.6 39.3 12 96 1830 70.6 Control Pond 13 6.04 25.3 43.6 4 78 960 29.3
77 APPENDIX D: VEGETATION DATA
78 AAP ID Name mLVI Score [units] Invasive Species [%] 92 004 University Village 30.5 0 30.2 92 021 Windsor Park 25.18 0 93 035 Keystone Crossings 41.33 20.91 93 043 Northdale Section C 45.92 20.35 93 055 Villager Place 42.28 24.87 94 066 Country Place Unit 4 B 28.33 40.67 94 074 Bloomingdale East 31.51 29.57 94 084 Bloomingdale Sect ion R 37.76 26.93 94 091 Henderson Subdivision 22.06 41.53 95 182 Northdale Section K II 75.80 5.0 95 213 Bloomingdale P Q 61.76 20.7 96 223 Turner Trace 44.65 22.58 96 225 Stonegate 33.01 36.32 96 226 Twin Branch: Maverick 39.21 35.48 96 227 Flor ida Aquarium 36.07 37.48 97 232 East Village 21.21 36.03 97 233 Country Lakes 16.64 47.87 97 234 Sugarwood 27.06 41.32 97 238 Lake Chapman 31.97 39.17 97 244 Twin Branch : Acres Saddle 29.82 39.59 98 01 Stonehedge 62.60 16.46 98 02 Avista Group 52.49 24.96 98 12 Twin Branch: Horseshoe 25.42 44.88 98 19 Twelve Oaks Lake 41.01 24.73
79 AAP ID Name mLVI Score [units] Invasive Species [%] 98 22 The Cove 31.31 33.35 98 23 Palm Ridge 22.08 43.26 98 25 Trucious Pond 51.09 15.13 98 27 Hickory Lakes Manor 41.75 23.25 98 29 River Hills Country Club 51.85 7.24 99 04 Villas on the Green 59.61 13.47 99 05 Wolski Group 53.92 23.0 99 06 Bristol Green 42.63 27.43 99 07 Laurel Woods 45.52 29.57 99 09 Pico Pond 8.46 58.77 99 13 Town Park 16.20 56.11 99 20 Be lle Meade 30.83 29.43 99 21 Country Crossings 29.66 34.33 0 0 0 5 T h o m p s o n E a s t 6 8 4 6 1 7 0 6 00 13 Kingfisher 32.18 45.16 01 04 Twelve Oaks Smaller 9.54 55.0 01 06 River Close 32.99 25.72 01 11 Cole Logan 48.16 16.42 01 1 2 Osprey Park Ponders 44.13 14.34 01 15 Temple Terrace Woods 31.83 39.24 02 01 Shadow Crest 41.44 16.69 02 06 Casa del Lago 37.62 31.94 02 11 Rustling Oaks 35.33 37.46 02 14 50.14 25.50 02 15 Whisper Sound 18.01 47.63
80 AAP ID Name mLVI S core [units] Invasive Species [%] 03 04 Falcon Creek Place 52.63 17.78 03 15 Heathridge Park 58.71 14.38 03 16 Lake Ellen Woods 39.39 21.98 03 17 Reynoldswood Pond 49.88 26.47 0 4 0 4 Boyette Springs: Parkhurst 46.81 17.42 0 4 10 Rosemere 24.13 32.35 04 17 NE Shadow Pond 29.61 33.65 05 01 Cedar Creek 62.06 1.67 06 01 Osprey Park 50.89 14.21 06 06 Brussels Boy III 43.15 16.82 06 07 Brussels Boy IV 57.27 16.33 06 09 Hunters Glen 47.52 16.23 06 15 Palamino Ct. 34.44 29. 08 06 17 Nutrixan 31.72 28.15 06 19 Crippenwood III 24.53 50.0 06 24 Boyette Springs: Veteran 37.39 23.18 06 25 Pemberton Creek 35.99 31.45 06 29 Bloomingdale Section H 34.29 30.31 06 33 Manorwood Circle 38.07 25.51 06 34 Summer Springs 57.31 10.73 06 35 Lake Forest 24.23 47.9 06 39 Lake St. Clair 52.20 11.42 07 02 Forest East 26.84 39.57 07 03 Forest North 33.80 38.54 07 09 Looking Glass 37.66 27.47
81 AAP ID Name mLVI Score [units] Invasive Species [%] 07 11 Lennard Longhorns 35.72 23.23 07 12 Tweedle Dee 54.51 18.31 07 14 Dewey Rose 61.52 26.43 08 12 Rolling Springs 38.88 23.56 08 13 Tarawood Subdivision 43.57 24.31 08 16 Carroll Grove Estates 39.87 31.49 09 01 Pinerose Yacht Club 34.04 35.66 09 03 Valrico Oaks 34.86 27.22 09 05 Golden Antler Pond 34.50 11.93 09 06 Plantation Greenbrook 23.15 38.65 Control Pond 0 67.34 0 Control Pond 1 49.72 24.10 Control Pond 3 45.63 23.9 Control Pond 4 45.0 14.86 Control Pond 5 52.53 5.84 Control Pond 6 40.07 24.08 Control Pond 7 32.64 22.71 Control Pond 8 17.19 47.54 Control Pond 9 52.49 0 Control Pond 12 35.24 23.52 Control Pond 13 58.18 11.44
82 APPENDIX E: MEASURES OF PROGRAM ACTIVITY
83 AAP ID Names Vegetation Donated [units/acre] Length of Activity [Years] Cle anup [Hours] 92 004 University Village 184.5 7 49 92 021 Windsor Park 0 0 0 93 035 Keystone Crossings 2 10 93 043 Northdale Section C 3596.2 2 12 93 055 Villager Place 3333.3 6 0 94 066 Country Place Unit 4 B 5170.0 3 94 074 Bloomingdale East 0 0 94 084 Bloomingdale Section R 163.5 3 94 091 Henderson Subdivision 204.7 1 95 182 Northdale Section K II 6230.8 2 95 213 Bloomingdale P Q 1229.2 1 96 223 Turner Trace 219.4 1 96 225 Stonegate 621.8 1 96 226 Twin Branch: Maverick 96 227 Florida Aquarium 2100.6 6 20 97 232 East Village 0 4 97 233 Country Lakes 277.2 1 97 234 Sugarwood 288.9 3
84 AAP ID Names Vegetation Donated [units/acre] Length of Activity [Years] Cleanup [Hours] 97 238 Lake Chapman 1520.7 5 97 244 Twin Branch: Acres Saddle 4 90 98 01 Stonehedge 98 02 Avista Group 98 12 Twin Branch: Horseshoe 4263.2 3 40 98 19 Twelve Oaks Lake 73.3 4 40 98 22 The Cove 3 98 23 Palm Ridge 660.5 2 98 25 Trucious Pond 476.3 12 40 98 27 Hickor y Lakes Manor 2954.5 1 98 29 River Hills Country Club 99 04 Villas on the Green 1454.1 1 99 05 Wolski Group 99 06 Bristol Green 938.5 3 99 07 Laurel Woods 4 99 09 Pico Pond 178.6 1 99 13 Town Park 1
85 AAP ID Name Vegetatio n Donated [units/acre] Length of Activity [Years] Cleanup [Hours] 99 20 Belle Meade 466.9 9 0 99 21 Country Crossings 1075.0 1 0 0 0 5 Thompson East 0 0 00 13 Kingfisher 6950.0 4 40 01 04 Twelve Oaks Smaller 831.0 3 12 0 01 06 River Close 1236.4 1 0 01 11 Cole Logan 730.3 1 100 01 12 Osprey Park Ponders 0 1 0 01 15 Temple Terrace Woods 2755.6 1 20 02 01 Shadow Crest 248.9 1 50 02 06 Casa del Lago 472.6 2 0 02 11 Rustling Oaks 614.3 4 130 02 14 4100.0 8 0 02 15 Whisper Sound 1181.9 1 30 03 04 Falcon Creek Place 1032.8 1 03 15 Heathridge Park 1925.0 2 0 03 16 Lake Ellen Woods 915.2 1
86 AAP ID Name Vegetation Donated [units/acre] Length of Activity [Years] Cleanup [Hours] 03 17 Reynoldswood Pond 4143.6 5 0 04 04 .09 36.5 66 6 128 920 40.1 Boyette Springs: Parkhurst 5721.9 3 04 10 Rosemere 1 04 17 NE Shadow Pond 186.7 3 05 01 Cedar Creek 3305.9 1 06 01 Osprey Park 0 3 0 06 06 Brussels Boy III 8333.3 1 0 06 07 Brussels Boy IV 1797 .3 1 06 09 Hunters Glen 1118.0 4 0 06 15 Palamino Ct. 1365.4 4 40 06 17 Nutrixan 3963.3 3 06 19 Crippenwood III 128.2 1 80 06 24 Boyette Springs: Veteran 140.7 30 06 25 Pemberton Creek 485.6 1 40 06 29 Bloomingdale Section H 184.7 5 50 06 33 Manorwood Circle 1051.2 3 10 06 34 Summer Springs 1311.7 4 0
87 AAP ID Name Vegetation Donated [units/acre] Length of Activity [Years] Cleanup [Hours] 06 35 Lake Forest 61.6 4 40 06 39 Lake St. Clair 112.4 3 30 07 02 Forest East 997.1 3 9 07 03 Forest N orth 337.9 3 24 07 09 Looking Glass 5103.8 1 10 07 11 Lennard Longhorns 1109.5 1 0 07 12 Tweedle Dee 2647.1 1 2 07 14 Dewey Rose 3360.0 2 0 08 12 Rolling Springs 2263.2 1 40 08 13 Tarawood Subdivision 875.0 1 10 08 16 Carroll Grove Estates 2 38 0 9 01 Pinerose Yacht Club 1893.2 2 20 09 03 Valrico Oaks 354.2 1 6.5 09 05 Golden Antler Pond 8591 1 0.75 09 06 Plantation Greenbrook 209.0 1 0
88 APPENDIX F : STUDY VEGETATION SPECIES AND LVI PARAMETERS
89 Scientific Name Coefficient of Conservatism Nativity FLEPPC Acer rubrum 4.65 Native Alternanthera philoxeroides 0 Exotic Cat II Ambrosia artemisiifolia 0.95 Native Ampelopsis arborea 3.25 Native Andropogon virginicus 3.44 Native Azolla caronliniana 1.81 Native Baccharis halimifolia 2.53 Native Bacopa caroliniana 5.31 Native Bacopa monnieri 4.49 Native Begonia cucullata 0 Exotic Cat II Bidens laevis 7.19 Native Bidens pilosa 1.64 Exotic Blechnum serrulatum 7.15 Native Boehmeria cylindrical 5.91 Native Bracharia mutica 0 Exot ic Cat I Canna flaccid 6.75 Native Carex albolutescens 3.47 Native Carex stipate 4.46 Native Carya aquatica 6.64 Native Centella asiatica 1.92 Native Cephalanthus occidentalis 6.99 Native Ceratopteris thalictroides 4.16 Native Chara spp. 3. 90 Native Colocasia esculenta 0 Exotic Cat I Commelina communis 2.0 Exotic Conyza Canadensis 1.01 Native
90 Scientific Name Coefficient of Conservatism Nativity FLEPPC Coreopsis spp. 2.8 Native Crinum americanum 8.67 Native Cynodon dactylon 0.29 Exotic Cyperus alternifolius 0 Exotic Cat II Cyperus esculentus 0 Exotic Cyperus haspen 5.68 Native Cyperus lanceolatus 2.04 Exotic Cyperus lecontei 2.33 Native Cyperus odoratus 4.25 Native Cyperus polystachyos 1.56 Native Cyperus surinamens is 2.03 Native Diascorea bulbifera 2.18 Exotic Cat I Dichromena colorata 6.18 Native Digitaria spp. 0.65 Exotic Diodia virginiana 4.96 Native Eclipta alba 3.22 Native Eichhornia crassipes 0 Exotic Cat I Eleocharis baldwiniii 2.82 Native Eleo charis interstincta 7.8 Native E rigeron quercifolius 3.31 Native Eupatorium capillifolium 0.83 Native Eustachys petraea 1.93 Native Fuirena scirpoidea 6.5 Native Galium spp. 5.22 Native Hydrilla verticillata 0 Exotic Cat 1 Hydrochloa carolinen sis 4.79 Native
91 Scientific Name Coefficient of Conservatism Nativity FLEPPC Hydrocotyle spp. 2.0 Native Hypericum fasciculatum 7.27 Native Hypericum mutilum 4.04 Native Ilex spp. 4.98 Native Imperata cylindrical 0 Exotic Cat 1 Iris virginica 7.09 Native Juncus effuses 3.25 Native Juncus marginatus 3.65 Native Juncus megacephalus 5.7 Native Kyllinga brevifolia 1.42 Native Lachnanthes caroliniana 3.76 Native Lachnocaulon spp. 8.1 Native Leersia hexandra 5.61 Native Lemna minor 3 .77 Native Liquidambar styraciflua 5.56 Native Ludwigia arcuata 5.32 Native Ludwigia grandiflora 1.44 Exotic Ludwigia octovalvis 4.09 Native Ludwigia palustris 4.77 Native Ludwigia peruviana 0.62 Exotic Cat I Ludwigia repens 5.2 Native Lygod ium japonica 0 Exotic Cat I L ythrum alatum 3.82 Native Micranthemum umbrosum 5.66 Native Micranthemum glomeratum 5.58 Native Mikania scandens 1.95 Native
92 Scientific Name Coefficient of Conservatism Nativity FLEPPC Musa spp. 0 Exotic Myrica ce rifera 3.82 Native Najas minor 3.64 Exotic Nasturtium officinale 2.93 Exotic Nitella spp. 7.28 Native Nuphar luteum 4.8 Native Nymphaea odorata 6.99 Native Nymphoides aquatic 6.09 Native Osmunda cinnamomea 6.44 Native Panicum abscissum 9.2 2 Native Panicum hemitomon 5.82 Native Panicum repens 0 Exotic Cat I Panicum verrucosum 6.83 Native Parthnocissus quienquefolia 3.43 Native Paspalidium geminatum 6.36 Native Paspalum dilatatum 4.33 Exotic Paspalum distichum 5.54 Native Paspa lum notatum 0.14 Exotic Paspalum setaceum 3.44 Native Persea palustris 8.31 Native Philodendron bipinnatifidum n/a Exotic Phyla nodiflora 1.92 Native Phyllanthus urinaria 0.22 Exotic Pistia stratiotes 0 Exotic Cat I Pluchea rosea 5.45 Native Polygonum hydropiperoides 4.02 Native
93 Scientific Name Coefficient of Conservatism Nativity FLEPPC Polygonum punctatum 4.02 Native Pontederia cordata 5.38 Native Proserpinaca pectinata 7.8 Native Ptilimnium capillaceum 2.73 Native Quercus laurif olia 5.14 Native Quercus nigra 4.14 Native Rhexia spp. 6.39 Native Ruellia brittoniana 0 Exotic Cat I Rhynchospora cephalantha 6.19 Native Rhynchospora microcephala 6.5 Native Richardia scabra 0 Exotic Rorippa floridana 2.93 Native Sabal pa lmetto 4.85 Native Sabatia grandiflora 7.09 Native Sacciolepsis indica 0.92 Exotic Sacciolepsis striata 5.35 Native Sagittaria lancifolia 4.96 Native Sagittaria subulata 5.0 Native Salix caroliniana 2.95 Native Salvinia minima 2.03 Exotic Cat I Sambucus Canadensis 1.48 Native Saururus cernuus 7.33 Native Schinus terebinthifolius 0 Exotic Cat I Scirpus cubensis 3.77 Exotic Scirpus validus 5.55 Native Scoparia dulcis 2.36 Native
94 Scientific Name Coefficient of Conservatism Nativity FL EPPC Serenoa repens 7.03 Native Sesbania herbacea 1.5 Native Sesbania punicea 0 Exotic Cat II Seteria geniculata 3.4 Native Smilax spp. 4.09 Native Spartina bakeri 5.98 Native Sphagnum spp. 7.43 Native Spirodela polyrhiza 2.95 Native Sten otaphrum secundatum 1.57 Native Taxodium distichum 7.21 Native Thalia geniculata 7.12 Native Tradescantia fluminensis 0 Exotic Cat I Triadica sebifera 0 Exotic Cat I Typha spp. 0.8 Native Urena lobata 0 Exotic Cat II Utricularia biflora 6.37 Na tive Vallisneria Americana 6.99 Native Vigna luteola 2.31 Native Vitus rotundifolia 1.18 Native Wedelia trilobata 0 Exotic Cat II Wolffiella floridana 4.27 Native Xyris spp. 6.55 Native All information derived from the Florida Department of En standard operating protocol for determining biological indices and the Florida Exotic Pest Plant Council (FDEP, 2008 and FLEPPC, 2009)
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Betts, Anthony Thomas.
Assessment of a countywide stormwater pond improvement project :
h [electronic resource] /
b impacts of the hillsborough county adopt-a-pond program
by Anthony Thomas Betts.
[Tampa, Fla] :
University of South Florida,
Title from PDF of title page.
Document formatted into pages; contains 102 pages.
(M.S.)--University of South Florida, 2011.
Includes bibliographical references.
Text (Electronic thesis) in PDF format.
ABSTRACT: Comparative research was conducted to assess the environmental impacts of the Adopt-a-Pond program, which operates throughout Hillsborough County, Florida. The Adopt-a-Pond program was established in 1992 and designed to address nonpoint pollution through outreach and stormwater pond enhancement. However, the program had never been thoroughly and scientifically evaluated. Therefore, assessments of water quality and vegetative characteristics were made at ninety Adopt-a-Pond participants and eleven control ponds to explore the potential impacts of the program on measurable environmental parameters. Statistical analysis of the results failed to demonstrate any statistically significant environmental improvements associated with the Adopt-a-Pond program, and measures of program activity did not illustrate a consistently positive relationship. These results indicate a need to readdress the policies and implementation of the program. Poor compliance by program volunteers, evident by the limited span of group participation (mean = 2.5 years) and relatively low percentage of actively involved residents, is the most likely culprit for the unremarkable improvements in pond quality, as pond enhancement techniques are firmly established in the literature. Overall, these conclusions underline the need for an integrated evaluation component in policymaking and an adaptive management approach to environmental management. A more detailed analysis is warranted to provide time series data, which examines ponds both before and after entry to the program and after implementing landmark improvement measures. In the end, the results of the study have provided a better understanding of the AAP and other similar restoration programs, and hopes to allow for enhancement of AAP program restoration practices.
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Alsharif, Kamal .
x Environmental Sciences
t USF Electronic Theses and Dissertations.