Alafia River Water Supply Project Hydrobiological Monitoring Program Year 9 Interpretive Report. Volume I Report. June 2009.

Transcription

1 Alafia River Water Supply Project Hydrobiological Monitoring Program Year 9 Interpretive Report Volume I Report June 2009 Prepared for 2575 Enterprise Road Clearwater, Florida Prepared by 5300 West Cypress Street Tampa, Florida & St. Petersburg, Florida

2 Contents Volume I Report Section Page Contents... i List of Tables...iv List of Figures... v Abbreviations and Acronyms...vii References and Relevant Literature...ix 1.0 Introduction Objective Regulatory Requirements HBMP Scope Reporting Units Indicators Sampling Design Additional HBMP Information HBMP Milestones through Water Year Report Organization Data Sources, Analyses, and Previous Reports Data Sources River Flow and Withdrawal Data Sources Salinity Data Sources Chlorophyll-a and Dissolved Oxygen Data Sources Plankton Data Sources Fish Data Sources Benthic Macroinvertebrate Data Sources Overview of Alafia River/Tampa Bypass Canal HBMP Data HBMP Sampling Site Selection Hydrology Water Quality Benthic Macroinvertebrates Plankton Fish Analytical Techniques Center of Abundance Abundance Weighted Salinity Temporal and Spatial Water Quality Analyses Salinity Variations Attributable to Withdrawals Dissolved Oxygen and Chlorophyll-a Thresholds and Exceedances Previous Interpretive Reports and MFL Report HBMP Year 3 Interpretive Report Alafia River Findings HBMP Year 6 Interpretive Report Summary of the Determination of Minimum Flows for the Lower Alafia River Estuary Analysis of Data through Water Year i HBMP Year 9 Interpretive Report June 2009

3 Contents 3.1. Introduction Reporting Unit and Study Period Description Hydrologic Conditions Flows and Withdrawals Flow at Bell Shoals Water Use Permit and EDOs Alafia River Withdrawals The Effect of Withdrawals on Flow Natural Variation in Flows Seasonal Kendall Tau Analyses for Trends in Flows Intra- and Inter-Annual Variations in Salinity Salinity Variations Attributable to Withdrawals Variations in Available Habitat Attributable to Withdrawals Intra- and Inter-annual Variations in Dissolved Oxygen and Chlorophyll-a Dissolved Oxygen and Chlorophyll-a Variations Attributable to Withdrawals Dissolved Oxygen Chlorophyll-a Intra- and Inter-Annual Variation of Fish and Invertebrates Intra- and Inter-Annual Variation of Fish and Shellfish Fish and Shellfish Density Fish and Shellfish Richness and Diversity Fish and Shellfish Taxa of Interest Intra- and Inter-Annual Variation of Zooplankton Zooplankton Density Zooplankton Richness and Diversity Zooplankton Taxa of Interest Intra- and Inter-Annual Variation of Benthic Invertebrates Key Fish and Invertebrate Variation Attributable to Flow or Flow Related Variables Key Fish and Invertebrate Variation Attributable to Withdrawals Vegetation Program Modifications Introduction HBMP Design and Program Issues Previously Authorized Design and Programmatic Modifications Discontinue Sampling in Stratum AR Change in Frequency of Alafia SAV Surveys Add Fixed-Location Water Quality Sample Station Change in Interpretive Report Frequency Total Organic Carbon and Dissolved Organic Carbon Discontinued Discontinued and Additional Avifaunal Surveys Changes to the Frequency of Vegetation Mapping Fixed-Station Vegetation Sampling Discontinued Additional Fish Sampling in Hillsborough Bay Adjacent to the Alafia River Proposed Program Modifications Potential Program Modifications Vegetation Benthic Macroinvertebrates Summary and Conclusions Flows Withdrawals ii HBMP Year 9 Interpretive Report June 2009

4 Contents 5.3. Observed vs. Reconstructed Flows Seasonal Kendall Tau Analyses for Trends in Flows Intra- and Inter-Annual Variations in Salinity Observed vs. Reconstructed Salinity Variations in < 2 psu, < 5 psu, and < 15 psu Habitat Attributable to Withdrawals Dissolved Oxygen and Chlorophyll-a Variations Attributable to Withdrawals Key Fish and Invertebrate Variation Attributable to Flow or Flow Related Variables Intra- and Inter-Annual Variation of Benthic Invertebrates Vegetation Volume II on CD. Additional tabular and graphical summaries of HBMP data collected from the lower Alafia River, the TBC/Palm River and McKay Bay, and the lower Hillsborough River primary reporting units. Appendix A - Summary of HBMP Indicators and Sampling Design for the Alafia River Appendix B - Numbers of Alafia River HBMP Benthic Samples Appendix C - Description of the LAMFE Model Appendix D - Detailed Description of the Methodology Used to Evaluate Dissolved Oxygen and Chlorophyll-a Appendix E - Natural Variation in Flows Appendix F - Intra- and Inter-annual Variations in Water Quality Appendix G - Time Series Plots of the Daily Mean Salinities by Stratum and Layer Appendix H - Time Series Plots of the Difference between Observed and Reconstructed Scenarios Appendix I - Cumulative Distribution Function (CDF) Plots of the Daily Median Salinity Values between Observed and Reconstructed Scenarios Appendix J - Time Series Plots of the Total Daily Habitat for each Salinity Class Appendix K - CDF Plots of the Total Daily Habitat for each Salinity Class Appendix L - Parameter Estimates from Regression Equations Developed to Estimate the Probability of an Exceedance Appendix M - Predicted Probabilities of Dissolved Oxygen Exceedances by Stratum and Depth Class Appendix N - Variation in Fish Density and Diversity Appendix O - Variation in Plankton Appendix P - Intra- and Inter-Annual Variation of Benthic Invertebrates Volume III on CD. Tabulated data from the various data tables maintained in the master HBMP database. iii HBMP Year 9 Interpretive Report June 2009

5 List of Tables Chapter 3 Table Table Table Summary of annual rainfall (inches) at the NOAA Plant City rain gage Rainfall (inches) at the NOAA Plant City rain gage Rainfall (inches) at the USGS Alafia River at Lithia rain gage Table Summary of daily calculated flows in the Alafia River at Bell Shoals Table Summary of daily Tampa Bay Water withdrawals (mgd) from the Alafia River by year Table Summary of daily Tampa Bay Water withdrawals (mgd) from the Alafia River by month Table Summary of Tampa Bay Water withdrawals as a proportion of calculated flow Table Summary of maximum daily withdrawal as a proportion of daily flow range Table Trend Tests of Calculated Alafia River Flow at Bell Shoals Table Table Table Table Table Table Table Table Table Table Classification table used to assess model validation in strata AR4 and AR5 Comparison of model R-square values for logistic regression models with additional data Classification table used to assess model validation Comparison of model R-square values for logistic regression models with additional data CPUE of fish taxa in the Alafia River summarized by Water Year and Gear Type Mean of Abundance Weighted Salinity by Water Year for Species of Interest in the Alafia River Center of Abundance by Water Year for Species of Interest in the Alafia River CPUE per sample of the plankton community in the Alafia River summarized by month Mean of abundance weighted salinity by Water Year for plankton species of interest in the Alafia River Center of abundance iv HBMP Year 9 Interpretive Report June 2009

6 List of Figures Chapter 1 Figure Chapter 3 Figure Figure Figure Figure HBMP reporting units Alafia River reporting unit Annual rainfall at the NOAA Plant City rain gage Monthly rainfall at the NOAA Plant City rain gage Monthly rainfall at the USGS Alafia River at Lithia gage Figure Daily calculated flow in the Alafia River at Bell Shoals Figure CDF of reconstructed flow in the Alafia River at Bell Shoals by period Figure CDF of reconstructed flow in the Alafia River at Bell Shoals for WY Figure CDF of reconstructed flow in the Alafia River at Bell Shoals for WY Figure CDF of reconstructed flow in the Alafia River at Bell Shoals WY Figure Daily calculated flow in the Alafia River at Bell Shoals Figure Alafia River HBMP and WUP Key Dates Figure Daily Tampa Bay Water withdrawal from the Alafia River Figure Daily Tampa Bay Water withdrawal from the Alafia River Figure CDF of Tampa Bay Water withdrawals from the Alafia River Figure CDF of Tampa Bay Water withdrawals from the Alafia River Figure Comparison of adjusted and calculated flow at Bell Shoals Figure Tampa Bay Water withdrawal as a proportion of calculated flow at Bell Shoals Figure Daily maximum Tampa Bay Water withdrawal as a proportion of daily flow range Figure Box plots of salinity across strata during multiple time periods Figure Box plots of salinity across strata during the designated Water Year Figure Salinity at defined depth and stratum for the period Figure Box plots of the difference in salinity between depth layers m and m Figure Alafia River salinity at defined depth range over time periods of interest Figure Box plots of salinity across strata during multiple time periods Figure Figure Figure Box and whisker plot of daily volume Box and whisker plot of daily bottom area Box and whisker plot of daily shoreline length Figure Alafia River dissolved oxygen at defined depth range over time periods of interest Figure Corrected chlorophyll-a in the Alafia River over time periods of interest Figure Uncorrected chlorophyll-a in the Alafia River over time periods of interest Figure Box plots of the difference in dissolved oxygen between depth layers m and m Figure Box plots of corrected chlorophyll-a across strata during multiple time periods Figure Box plots of uncorrected chlorophyll-a across strata during multiple time periods Figure Figure Figure Figure Figure Probability of Chlorophyll value > 15 ug/l under observed and reconstructed scenarios (Figures a-e for individual strata) Boxplots representing LN(CPUE+1) of fish for seines in Alafia River by water year Boxplots representing LN(CPUE+1) of fish for trawls in Alafia River by water year Number of fish species caught in seines in the Alafia River by water year Number of fish species caught in trawls in the Alafia River by water year v HBMP Year 9 Interpretive Report June 2009

7 List of Figures Figure Figure Figure Figure Figure Figure Figure Figure Figure Figure Figure Figure Figure Figure Figure Boxplots representing Shannon-Weiner diversity of fish for seines in Alafia River by month Boxplots representing Shannon-Weiner diversity of fish for trawls in Alafia River by month Boxplots representing LN(CPUE+1) of zooplankton in Alafia River by water year Boxplots representing LN(CPUE+1) of zooplankton in Alafia River by month Number of zooplankton species caught in seines in the Alafia River by water year Boxplots representing Shannon-Weiner diversity of zooplankton in Alafia River by month Boxplots representing Shannon-Weiner diversity of zooplankton in Alafia River by water year Taxa richness by month and water year Species richness versus salinity Shannon-Weiner diversity across months Inter-annual variation in Shannon-Weiner diversity Location of occurrence of polychaetes during Pre-Operational and Operational periods Salinity at time of sample collection for samples containing Polychaetes Location of occurrence of Amphipods during Pre-Operational and Operational periods Salinity at time of sample collection for samples containing Amphipods Figure Alafia River riverine vegetation Figure Alafia River total river-dependent wetland vegetation area by 100-meter river segment Figure Total areas of Alafia River riverine wetland vegetation by species in 2003, 2006, and 2009 Figure Percent changes in Alafia River vegetation areas by species, 2003 to 2009 vi HBMP Year 9 Interpretive Report June 2009

8 Abbreviations and Acronyms AR AGWMP BACI Chl-a DMS DOC DO EAV EMAP EPA EPCHC FDEP FFWCC FIM FMRI FWRI GIS HBMP HR JEI LAR LHR LPR MB MFL NOS NRC NWS PBS&J PR Alafia River Ambient Ground Water Monitoring Program Before/After/Control/Impact Chlorophyll-a Department of Marine Sciences Dissolved Organic Carbon Dissolved Oxygen Emergent Aquatic Vegetation Environmental Monitoring and Assessment Program Environmental Protection Agency (U.S.) Environmental Protection Commission of Hillsborough County Florida Department of Environmental Protection Florida Fish and Wildlife Conservation Commission FWRI Fisheries Independent Monitoring Program Florida Marine Research Institute Fish and Wildlife Research Institute (formerly Florida Marine Research Institute) Geographic Information System Tampa Bypass Canal/Alafia River Water Supply Projects Hydrobiological Monitoring Program Hillsborough River Janicki Environmental, Inc. Lower Alafia River Lower Hillsborough River Lower Palm River McKay Bay Minimum Flows and Levels National Oceanic Service National Research Council National Weather Service PBS&J, Inc. Palm River vii HBMP Year 9 Interpretive Report June 2009

9 Abbreviations and Acronyms PSU PPT QA/QC Rkm SAV SAS SOP Spp. SWAMP SWFWMD SWIM TBC TOC TSS USF USGS WUP Practical Salinity Units Parts per Thousand Quality Assurance/ Quality Control River Kilometer Submerged Aquatic Vegetation Software system developed by the SAS Institute, Cary, NC. Standard Operating Procedures Species (also Sp. ) Surface Water Monitoring Program Southwest Florida Water Management District Surface Water Improvement and Management Tampa Bypass Canal Total Organic Carbon Total Suspended Solids University of South Florida U.S. Geological Survey Water Use Permit viii HBMP Year 9 Interpretive Report June 2009

10 References and Relevant Literature Braun-Blanquet, J Plant Sociology. Oxford University Press. Oxford, UK. Brower, J.E., J.H. Zar and C.N. von Ende Field and Laboratory Methods for General Ecology. 3 rd Ed. Wm. C. Brown Publishers. Dubuque, IA. Campbell Scientific CR10X Measurement and Control Module Operator s Manual. Campbell Scientific, Inc. Logan, UT. Campbell Scientific PC208W Datalogger Support Software Instruction Manual. Campbell Scientific, Inc. Logan, UT. Chen, X. 2003a. An efficient finite difference scheme for simulating hydrodynamics in narrow rivers and estuaries. International Journal for Numerical Methods in Fluids. 42: Chen, X. 2003b. A Free-Surface Correction Method for Simulating Shallow Water Flows. Journal of Computational Physics, 189: Chen, X. 2004a. Using a piecewise linear bottom to fit the bed variation in a laterally averaged, z-coordinate hydrodynamic model. International Journal for Numerical Methods in Fluids. 44: Chen, X. 2004b. A Cartesian method for fitting the bathymetry and tracking the dynamic position of the shoreline in a three-dimensional, hydrodynamic model. Journal of Computational Physics, 200: Chen, X Simulating Hydrodynamics in the Lower Alafia River Estuary. Technical Report, Southwest Florida Water Management District, Tampa, Fla. Cochran, W.G Sampling Techniques. 3 rd Edition. John Wiley & Sons. New York, NY. Cochran, W.G., F. Mosteller, and J.W. Tukey Principles of sampling. Journal of the American Statistical Association 49: Dames and Moore Hydrobiologic Assessment of the Alafia and Little Manatee River Basins. Prep. For Southwest Florida Water Management District Alafia River Basin Board, Brooksville. Environmental Protection Commission of Hillsborough County (EPCHC) Hillsborough Independent Monitoring Program: Characterization of Pre-Operational ( ) Water Quality and Benthic Habitats. Prepared for Hillsborough County Water Resource Team. Tampa, Florida. Estevez, E.D. (Ed.) NOAA Estuary-of-the-Month Seminar Series no. 11. Tampa and Sarasota Bays: Issues, Resources, Status, and Management. U.S. Dept. Comm. NOAA. Washington, DC. 215 p. ix HBMP Year 9 Interpretive Report June 2009

11 References and Relevant Literature Furness, R.W. and J.J.D. Greenwood (eds.) Birds as Monitors of Environmental Change. Chapman and Hall. London, England. Godfrey, R.K., and J. W. Wooten Aquatic and Wetland Plants of the Southeastern United States. University of Georgia Press. Athens, GA. Grabe, S.A., D. J. Karlen, C. M. Holden, B. Goetting, T. Dix, S. Markham & C. Pearson. 2003b. Hillsborough Independent Monitoring Program: Pre-operational Characterization of Benthic Habitats of the Lower Hillsborough & Little Manatee Rivers. DRAFT. Prepared for Hillsborough County Water Resource Team, Tampa. Grabe, S.A., D. J. Karlen, C. M. Holden, B. Goetting, T. Dix, S. Markham & C. Pearson 2004b. Hillsborough Independent Monitoring Program: Pre-operational Characterization of Benthic Habitats of the Alafia & Little Manatee Rivers. DRAFT. Grabe, S.A., D. J. Karlen, L. Gutierrez-Antrim, C.M. Holden and B. Goetting Benthic Habitat Status of the Lower Hillsborough, Palm, Alafia and Little Manatee Rivers: Prep. for Southwest Florida Water Management District, Brooksville. Grabe, S.A., D.J. Karlen, C. M. Holden, B. Goetting, T. Dix, S. Markham & C. Pearson 2004a. Hillsborough Independent Monitoring Program: Pre-operational Characterization of Benthic Habitats of the Palm River, McKay Bay & Little Manatee Rivers. DRAFT. Grabe, S.A., D.J. Karlen, C.M. Holden, and B. Goetting. 2003a. Sediment contaminants and benthic assemblages in the Alafia, Palm, Alafia, and Little Manatee Rivers. Pages 14-1 to In: J.R. Pribble, A.J. Janicki, and H. Greening (eds.) Baywide Environmental Monitoring Report, Tampa Bay, Florida. Tampa Bay Estuary Program Tech. Publ. Grabe, S.A., C. Courtney, Z. Lin, D. Alberdi, H. Wilson, & G. Blanchard Environmental Monitoring & Assessment Program-Estuaries. West Indian Province 1993 Sampling. A Synoptic Survey of the Benthic Macroinvertebrates and Demersal Fishes of the Tampa Bay Estuarine System.. Environmental Protection Commission of Hillsborough County. Tech. Report # Tampa Bay National Estuary Program. Grant, P.J Gulls: A Guide to Identification. Academic Press. San Diego, CA. Gunther, A.J., J.A. Davis, D.D. Hardin, J Gold, D. Bell., J.R. Crick, G.M. Scelfo, J. Sericano, M. Stephenson Long-term bioaccumulation monitoring with transplanted bivalves in the San Francisco estuary. Marine Pollution Bulletin 38(3): Hayman, P., J. Marchant and J. Prater Shorebirds: An Identification Guide Houghton Mifflin. Boston, MA. HDR Engineering, Inc Environmental Assessment of the TBC, Tampa/Hillsborough County, Florida. Prep. for TBC Management Committee. Hosmer, D., and S. Lemeshow Applied Logistic Regression. Wiley & Sons. New York, NY. Janicki Environmental, An Analysis of Long-Term Trends in Tampa Bay Water Quality. Prepared for Tampa Bay Estuary Program. Janicki Environmental. St. Petersburg, FL. x HBMP Year 9 Interpretive Report June 2009

12 References and Relevant Literature Janicki Environmental, 2005c. Alafia River Isohaline Regression Models. Prepared for Southwest Florida Water Management District. Janicki Environmental. St. Petersburg, FL. Janicki Environmental, 2005d. Tampa Bypass Canal/McKay Bay Regression Results, Technical Memo Prepared for Southwest Florida Water Management District. Janicki Environmental. St. Petersburg, FL. Janicki Environmental. 2005a. Downstream Augmentation Project Environmental Assessment Strategy. Prepared for Tampa Bay Water. Janicki Environmental. St. Petersburg, FL. Janicki Environmental. 2005b. Alafia River EPCHC Salinity Regression Review. Prepared for Southwest Florida Water Management District. Janicki Environmental. St. Petersburg, FL. Kaufman, K A Field Guide to Advanced Birding. Peterson Field Guide Series. Houghton Mifflin Company. Boston, MA. Lewis, R.R. III and E.D. Estevez The Ecology of Tampa Bay: An Estuarine Profile. U.S. Fish Wildl. Serv. Biol. Rep. 85 (7-18). 132 pp. Morgan, B.J.T. and P.M. North (eds.) Statistics in Ornithology. Springer-Verlag. Berlin, Germany. In Billinger, D., et. al. (eds.). Volume 29 of Lecture Notes in Statistics. Mote Marine Laboratory Biological and Chemical Studies on the Impact of Stormwater Runoff Upon the Biological Community of the Hillsborough River, Tampa, FL. Prepared for: City of Tampa Department of Public Works. Mote Marine Laboratory Final Report. An Investigation of Relationships Between Freshwater Inflows and Benthic Macroinvertebrates in the Alafia River Estuary. Mote Marine Laboratory Tech. Rep prep. For SWFWMD. National Research Council Managing Troubled Waters. National Academy Press. Washington, DC. PBS&J Tampa Bypass Canal/Alafia River Water Supply Projects Hydrobiological Monitoring Program. Final Report prepared for Tampa Bay Water. PBS&J. Tampa, FL. PBS&J Tampa Bypass Canal/Alafia River Water Supply Projects Hydrobiological Monitoring Program Water Year 2000 Annual Data Report. Prepared for Tampa Bay Water. PBS&J. Tampa, FL. PBS&J Tampa Bypass Canal/Alafia River Water Supply Projects Hydrobiological Monitoring Program Water Year 2001 Annual Data Report. Prepared for Tampa Bay Water. PBS&J. Tampa, FL. PBS&J Tampa Bypass Canal/Alafia River Water Supply Projects Hydrobiological Monitoring Program Year 3 Interpretive Report. Prepared for Tampa Bay Water. PBS&J. Tampa, FL. xi HBMP Year 9 Interpretive Report June 2009

13 References and Relevant Literature PBS&J Tampa Bypass Canal/Alafia River Water Supply Projects Hydrobiological Monitoring Program Water Year 2003 Annual Data Report. Prepared for Tampa Bay Water. PBS&J. Tampa, FL. PBS&J Tampa Bypass Canal/Alafia River Water Supply Projects Hydrobiological Monitoring Program Water Year 2004 Annual Data Report. Prepared for Tampa Bay Water. PBS&J. Tampa, FL. PBS&J Tampa Bypass Canal Alafia River Water Supply Projects Hydrobiological Monitoring Program Year 6 Interpretive Report. Prepared for Tampa Bay Water. PBS&J. Tampa, FL. PBS&J Tampa Bypass Canal/Alafia River Water Supply Projects Hydrobiological Monitoring Program Water Year 2006 Annual Data Report. Prepared for Tampa Bay Water. PBS&J. Tampa, FL. PBS&J. 2008a. Tampa Bypass Canal/Alafia River Water Supply Projects Hydrobiological Monitoring Program Quality Assurance and Quality Control Plan Version 2.1. Prepared for Tampa Bay Water. PBS&J. Tampa, FL. PBS&J. 2008b. Tampa Bypass Canal/Alafia River Water Supply Projects Hydrobiological Monitoring Program Water Year 2007 Annual Data Report. Prepared for Tampa Bay Water. PBS&J. Tampa, FL. Peebles, E B Early life history of the sand seatrout, Cynoscion arenarius, in southwest Florida. Tampa, Florida, University of South Florida. Peebles E B. 2002b. An assessment of the effects of freshwater inflows on fish and invertebrate habitat use in the Peace River and Shell Creek estuaries. Report prepared by the University of South Florida College of Marine Science for the Southwest Florida Water Management District. Peebles, E.B Ontogenetic habitat and diet selection in estuarine-dependent fishes: comparisons of observed patterns with model predictions. Tampa, Florida, University of South Florida. Peebles, E.B a. An assessment of the effects of freshwater inflows on fish and invertebrate habitat use in the Alafia River estuary. Report prepared by the University of South Florida College of Marine Science for the Southwest Florida Water Management District. Peebles, E.B c. Temporal resolution of biological and physical influences on bay anchovy Anchoa mitchilli egg abundance near a river-plume frontal zone. Mar Ecol Prog Ser 237: Peebles, E.B., Flannery MS Fish nursery use of the Little Manatee River estuary (Florida): Relationships with freshwater discharge. Southwest Florida Water Management District, Brooksville, Florida. Peebles, E.B., Hall JR, Tolley SG Egg production by the bay anchovy Anchoa mitchilli in relation to adult and larval prey fields. Mar Ecol Prog Ser 131: xii HBMP Year 9 Interpretive Report June 2009

14 References and Relevant Literature Point Four Systems. Undated. OxyGuard Dissolved Oxygen Probe Users Manual. Point Four Systems, Inc. Port Moody, BC. Canada. SAS SAS/STAT User s Guide, Version 8. SAS Institute Inc. Cary, NC. Scott, S. L Field Guide to the Birds of North America. 2 nd Edition National Geographic Society. New York, NY. Shannon, C. E., & Weaver, W. 1949). The Mathematical Theory of Communication. Urbana IL: University of Illinois Press. Simon, J.L Tampa Bay estuarine system a synopsis. Florida Scientist. 37: Southwest Florida Water Management District An Analysis of Hydrologic and Ecological Factors Related to the Establishment of Minimum Flows for the Hillsborough River. Southwest Florida Water Management District (SWFWMD). 2004a. Southwest Florida Water Management District (SWFWMD). 2004b. Water Use Individual Permit No DRAFT. Southwest Florida Water Management District (SWFWMD). 2004c. Southwest Florida Water Management District (SWFWMD). 2004d. Southwest Florida Water Management District (SWFWMD) Minimum Flows for the Tampa Bypass Canal. Ecological Evaluation Section, Resource Conservation and Development Department, Southwest Florida Water Management District. Brooksville, FL. Southwest Florida Water Management District (SWFWMD). 2004e. The Determination of Minimum Flows for Sulphur Springs, Tampa, FL [DRAFT]. Southwest Florida Water Management District (SWFWMD) Results of a low flow study on the Lower Hillsborough River. Draft Report. Southwest Florida Water Management District (SWFWMD) Lower Hillsborough River Minimum Flows Re-evaluation Report. Southwest Florida Water Management District (SWFWMD). 2008a. Proposed Minimum Flows and Levels for the Lower Peace River and Shell Creek DRAFT. Southwest Florida Water Management District (SWFWMD). 2008b. Proposed Minimum Flows and Levels for Dona Bay/Shakett Creek below Cow Pen Slough DRAFT. Stanley, T.W., and S.S. Verner The U.S. Environmental Protection Agency s Quality Assurance Program. In: J.K. Taylor and T.W. Stanley (eds.) Quality Assurance for Environmental Measurements. American Society for Testing Materials. Philadelphia, PA. xiii HBMP Year 9 Interpretive Report June 2009

15 References and Relevant Literature Stevens Water Monitoring Systems SDI Encoder Instruction Stevens Water Monitoring Systems, Inc. Beaverton, OR. Stevenson, H.M. and B.H. Anderson The Birdlife of Florida. University Press of Florida. Gainesville, FL. Summers, J.K., and G. Maddox Design of the Status Monitoring Network. In: Overview of the Florida Department of Environmental Protection s Integrated Water Resource Monitoring Efforts and the Design Plan of the Status Network. Florida Department of Environmental Protection. Tallahassee, FL. Sykes, J.E Report to the National Marine Fisheries Service Biological Laboratory, St. Petersburg Beach, fiscal years 1970 and NMFS NOAA Tech. Mem. NMFS SER-2. Seattle, WA. Tampa Bay Water. 2005a. Water Use Permit (Alafia River Project) Water Year 2004 Annual Report Permit Condition 14A & B (draft). Tampa Bay Water. Clearwater, FL. Tampa Bay Water. 2005b. Water Use Permit (Tampa Bypass Canal Water Supply Project) Water Year 2004 Annual Report Permit Condition 16A & B (draft). Tampa Bay Water. Clearwater, FL. Taylor, J.K Quality Assurance of Chemical Measurements. Lewis Publishers. Boca Raton, FL. Taylor, J.L Polychaetous annelids and benthic environments in Tampa Bay, Florida. Ph.D. Diss. Univ. Fl., Gainesville. 1332p. Taylor, J.L., J.R Hall and C.H. Saloman Mollusks and benthic environments in Hillsborough Bay, Florida. Fish. Bull. 68: Thoemke, K.W The life history and population dynamics of four subtidal amphipods from Tampa Bay, Florida. Ph.D. Diss. USF, Tampa. WAR and SDI Second interpretive report Tampa Bypass Canal and Hillsborough River monitoring program. Prepared for West Coast Regional Water Supply Authority. Clearwater, FL. WAR and SDI Second Interpretive Report Tampa Bypass Canal and Hillsborough River Hydrobiological Monitoring Program. Prepared for West Coast Regional Water Supply Authority and City of Tampa. Water and Air Research, Inc. and SDI Environmental Services, Inc. (WAR and SDI) First progress report: Tampa Bypass Canal and Hillsborough River biological assessment and monitoring program. Prepared for West Coast Regional Water Supply Authority. Clearwater, FL. YSI Series YSI Environmental Operations Manual. YSI, Inc. Yellow Springs, OH. xiv HBMP Year 9 Interpretive Report June 2009

16 1.0 Introduction 1.1. Objective The Southwest Florida Water Management District (SWFWMD) issued Water Use Permits (WUPs) and (renewal/modifications of original Water Use Permits and ) to Tampa Bay Water for the Alafia River and the Tampa Bypass Canal/Hillsborough River Water Supply Projects, respectively. Development and implementation of comprehensive Hydrobiological Monitoring Programs (HBMPs) for both of these Water Supply Projects was required as specific conditions of approval for these Water Use Permits. Based on similar schedules for development and the close proximity of the two water supply projects, a single integrated HBMP was designed and implemented to address the permit requirements for both projects. This interpretive data report has been produced to meet special conditions 8A and 14B1 of the Alafia River Project WUP. An interpretive report for the Tampa Bypass Canal, McKay Bay, Hillsborough Bay, and Hillsborough River reporting units is scheduled for The initial HBMP design required comprehensive interpretive reports to be submitted every five years, with a single interim interpretive report submitted in 2003, three years after sampling began. In 2003, this schedule was modified to include comprehensive interpretive reports every three years, with reports due in 2006, 2009, etc. The Tampa Bypass Canal/Hillsborough River Water Use Permit was modified and renewed in August 2007, and specifies that interpretive reports will be prepared every 5 years with the next report due in For the Alafia River, the reporting schedule continues under the approved HBMP with this Year 9 Interpretative Report. This interpretive report includes data collected during HBMP field monitoring on the Alafia River from its inception in Water Year 2000 through the end of Water Year 2008 (April 2000 through September 2008). The report also includes data collected for other monitoring programs or studies during and prior to the HBMP where applicable. The HBMP interpretive reporting requirements are specified in both the Alafia River and Tampa Bypass Canal (TBC) project permits as follows: At the end of selected years specified in the final approved HBMP plan, the Permittee will submit Interpretive reports that will include comprehensive analyses of all data collected to date that specifically address the objectives of the HBMP. Qualitative and quantitative analyses shall be presented in the Interpretive reports to evaluate the interactions of hydrologic conditions and withdrawals on streamflow, [inundation of the river channel and its floodplain,] nutrient loading, salinity distributions in the estuary, and the response of related water quality and biological variables in the lower Alafia River, the lower Hillsborough River below Tampa Dam, TBC, Palm River, and McKay Bay. The Interpretive reports will also include an appendix that provides all raw data collected during the previous year, thus fulfilling the requirement for the Annual report for that year. Upon completion of each cycle of the HBMP, a draft HBMP 1-1 HBMP Year 9 Interpretive Report June 2009

17 Introduction Interpretive report shall be submitted to the District as part of the overall Annual report. The HBMP was initiated in April Results from previous years have been described in annual Data Reports (PBS&J, 2002; 2004; 2005; 2007; 2008b) and the Year 3 and Year 6 Interpretive Reports (PBS&J, 2003; 2006). Permitted water withdrawals began in Water Years 2002 and The harvesting of surface waters from the Tampa Bypass Canal and Alafia River was initiated on August 30, 2002 and February 7, 2003, respectively Regulatory Requirements As described above, development and implementation of a comprehensive Hydrobiological Monitoring Program was required as a specific condition of the water use permits for the Alafia River and Tampa Bypass Canal Water Supply Projects. In the Water Use Permit review process, all applicants must demonstrate that the proposed withdrawals or water uses: Will not cause adverse environmental impacts to wetlands, lakes, streams, estuaries, fish and wildlife, or other natural resources (40D-2.301(c)). The SWFWMD Basis of Review for Water Use Permits for withdrawals from natural surface waterbodies also requires that the following specific performance standards be met: Flow rates shall not deviate from the normal rate and range of fluctuation to the extent that: A. Water quality, vegetation, and animal populations are adversely impacted in streams and estuaries; B. Salinity distributions in tidal streams and estuaries are significantly altered as a result of withdrawals; or C. Recreational use or aesthetic qualities of the resource are adversely impacted. Tampa Bay Water provided reasonable assurance that the cited performance standards would be met during the Tampa Bypass Canal and Alafia River Water Supply Projects permit review process. However, implicit in the HBMP as a condition of permit approval, is a requirement (for the duration of the permit) that following the construction and operation of the permitted facilities Tampa Bay Water demonstrate continued compliance with the District performance standards. As a result, the minimal goal of the Alafia/TBC HBMP is to generate information at an appropriate scale and resolution to determine if the permitted water supply projects are in compliance with applicable District rules for water use. Accordingly, the programmatic goal of the HBMP was articulated in the District approved HBMP Design Document (PBS&J, 2000): The goal of the HBMP is to ensure that, following the implementation of the permitted surface water withdrawals, flows in the Tampa Bypass Canal, 1-2 HBMP Year 9 Interpretive Report June 2009

18 Introduction Hillsborough River and Alafia River do not deviate from the normal rate and range of fluctuation to the extent that: water quality, vegetation, and animal populations are adversely impacted in streams and estuaries; salinity distributions in tidal streams and estuaries are significantly altered as a result of withdrawals; or recreational use or aesthetic qualities of the resource are adversely impacted. The Design document also established programmatic objectives to address the District s process for evaluating compliance with Water Use Permits. Accordingly, the programmatic objectives of the HBMP as articulated by the Focus Group were to: document existing conditions in the potentially affected waterbodies; enable the detection of changed conditions in the potentially affected waterbodies; determine if the detected changed conditions are attributable to reductions in freshwater inflows; provide a scientifically defensible means to evaluate whether the permitted surface water withdrawals are causing or significantly contributing to the detected changed conditions; determine whether the detected changed conditions constitute, or could result in, unacceptable adverse impacts; and recommend appropriate management actions or operational changes designed to eliminate or mitigate unacceptable adverse impacts, if they occur or are expected to occur. As reflected in the listed objectives, the overall purpose and scope of the HBMP extend beyond just data acquisition, analysis and reporting. The HBMP also incorporates programmatic criteria that have been designed to ensure that the permitted withdrawals do not result in violations of District rules throughout the lifetime of the permits. 1-3 HBMP Year 9 Interpretive Report June 2009

19 Introduction 1.3. HBMP Scope Reporting Units The HBMP study area consists of five potentially affected waterbodies: The lower Alafia River below Bell Shoals Road The Tampa Bypass Canal/Palm River McKay Bay The lower Hillsborough River below the City of Tampa dam Hillsborough Bay These geographic areas of concern or reporting units are shown in Figure This report addresses only the lower Alafia River reporting unit Indicators The HBMP has three monitoring program elements: Hydrology / Water quality Biota Habitat / Vegetation During the design of the HBMP, critical indicators were identified for each monitoring element in each reporting unit. Critical indicators are units of measure that describe the status of the statistical populations or subpopulations of interest, usually in response to some environmental stressor. Structural and hydrobiological differences among the reporting units necessitate slightly different groups of critical indicators for each. Critical indicator lists are shown in Appendix A Sampling Design Sampling design is defined at length in the HBMP QA/QC Plan and previous data and interpretive reports (PBS&J, 2001; 2003; 2004; 2005; 2008a). The HBMP employs both randomly selected and fixed station sampling. Spatial and temporal strata, the number of samples to be collected within each stratum, and other parameters are summarized for each reporting unit in Appendix A Additional HBMP Information Additional information regarding specific procedures for sample collection and analysis is provided in the project s quality control plan, Tampa Bypass Canal/Alafia River Water Supply Projects Hydrobiological Monitoring Program Quality Assurance and Quality Control Plan, Version 2.1 (PBS&J, 2008a). 1-4 HBMP Year 9 Interpretive Report June 2009

20 Introduction 1.4. HBMP Milestones through Water Year 2008 Water Year 1999 Mar-99: SWFWMD issues Tampa Bypass Canal Water Supply Project WUP Jul-99: SWFWMD issues Alafia River Water Supply Project WUP May to Sept-99: Conducted HBMP Design Workshops Water Year 2000 (HBMP Year 1) Nov-99: Submitted HBMP Design Report to SWFWMD Dec-99: Tampa Bay Water Board approves HBMP design Apr-00: Initiated monthly water quality sampling and first bimonthly bird survey May-00: Initiated monthly fish and plankton sampling Jun-00: Initiated monthly benthos sampling Sep-00: Submitted revised HBMP Final Design Report to SWFWMD (incorporating EPCHC and SWFWMD comments) Water Year 2001 (HBMP Year 2) Oct-00: Conducted first annual vegetation survey Dec-00: Completed continuous recorder installations May-01: First HBMP Annual Meeting Jul-01: First Annual Data Report (Water Year 2000) submitted to SWFWMD Water Year 2002 (HBMP Year 3) Nov-01: SWFWMD approved change in Alafia SAV survey to every 5 years Aug-02: TBC project and surface water treatment plant on-line for production Water Year 2003 (HBMP Year 4) Oct-02: Alafia project on-line for testing Feb-03: Alafia project on-line for production Jul-03: HBMP Pre-Operational Interpretative Report (WY ) submitted to SWFWMD Water Year 2005 (HBMP Year 6) Oct-04: Discontinued total organic carbon and dissolved organic carbon sampling Oct-04: Added additional fish sampling stratum at the mouth of the Alafia River Water Year 2006 (HBMP Year 7) Jul-06: HBMP Interpretative Report (WY ) submitted to SWFWMD Water Year 2008 (HBMP Year 9) Aug-08: Original YSI continuous recorders sondes and Stevens loggers replaced as necessary and new loggers put in reserve for future replacement 1-5 HBMP Year 9 Interpretive Report June 2009

21 Introduction 1.5. Report Organization This document includes an introduction, an overview of data sources and methodologies, the results of data analyses for the Alafia River, a discussion of the findings, and recommendations for any programmatic modifications. This information is organized into the following sections, as described below. Section 1.0 provides a brief overview and background for the Alafia River/Tampa Bypass Canal Hydrobiological Monitoring Program, describes other relevant studies in the reporting units, and summarizes the report organization. Section 2.0 provides a description of data sources and analyses utilized in the report. Section 3.0 provides summaries of tabular and graphical data analyses of historical data and HBMP data collected from the lower Alafia River with supporting narrative discussions. This section was designed to answer questions about river flow, Tampa Bay Water withdrawals, water quality and biotic indicators in the lower Alafia River. These questions were: 1. What were the daily flows in the Alafia River during the study period, and how did these flows compare to the historical flow record? 2. What were the daily Tampa Bay Water withdrawals from the Alafia River during the study period, and how did these withdrawals affect daily flows? 3. What was the intra- and inter-annual variation in salinity in the Alafia River during the study period? 4. What portion of the intra- and inter-annual variation in salinity was attributable to Tampa Bay Water withdrawals? 5. What was the intra- and inter-annual variation in chlorophyll-a and dissolved oxygen in the Alafia River during the study period? 6. Can any portion of the intra- and inter-annual variation in chlorophyll-a and dissolved oxygen be attributed to Tampa Bay Water withdrawals? If so, what portion? 7. What were the estimated volumes and areas of habitat under different isohalines in portions of the Alafia River during the study period? 8. Were there any changes to Alafia River volumes and areas of habitat under different isohalines attributable to Tampa Bay Water withdrawals during the study period? 9. Was there a relationship between flow/salinity and plant species cover and composition at the Alafia River fixed vegetation stations from ? 10. What were the intra-and inter-annual variation in the fish, plankton, and benthos species composition, abundance, and diversity and spatial/temporal distribution of MFL biotic indicators in the Alafia River during the study period? 11. To what extent did variation in Alafia River flow or flow related variables (e.g. salinity) affect the intra- and inter-annual variation in the species composition, abundance and diversity of biotic components and spatial/temporal distribution of MFL biotic indicators? 12. If there were changes in Alafia River flows, salinity, habitat areas or volumes, vegetation, chlorophyll-a, dissolved oxygen, fish, plankton or benthos that were clearly attributable to 1-6 HBMP Year 9 Interpretive Report June 2009

22 Introduction Tampa Bay Water withdrawals, did these changes constitute an unacceptable environmental impact? Section 4.0 summarizes previously approved changes to the monitoring program as well as potential future changes. Section 5.0 provides a summary of the major findings and conclusions of this interpretive report. 1-7 HBMP Year 9 Interpretive Report June 2009

23 r ive hr ug oro ls b H il McKay Bay Lower Palm River Alafia River Hillsborough Bay Reportig Unit Boundary Miles Figure HBMP Reporting Units

24 2.0 Data Sources, Analyses, and Previous Reports 2.1. Data Sources This section provides an overview of the data sources and analyses utilized in this report. The entities that provided data for this report are identified and brief descriptions of some of the sampling procedures are included. The methods used to analyze the data are described River Flow and Withdrawal Data Sources River flow and withdrawal data used in this report were obtained from the Tampa Bay Water enterprise database. Flow data are measured by the USGS gage (# ) in the Alafia River at Lithia Salinity Data Sources Salinity data were collected by water column profile measurements during plankton, fish, benthic and water quality sampling as part of the Tampa Bay Water HBMP beginning in April 2000 (for a description of procedures for sample collection, see the Quality Assurance and Quality Control Plan, PBS&J, 2008a). In addition to the Tampa Bay Water HBMP, available salinity data were compiled from several other monitoring programs. Studies completed by the Southwest Florida Water Management District (SWFWMD) provided profile salinity data from a number of stations for the Alafia River (Rkm ; April July 1987 and January 1999 September 2002). Water column surface, mid-depth, and bottom salinities were recorded monthly by the Environmental Protection Commission of Hillsborough County (EPCHC) as part of their monitoring program. These data were collected at fixed station locations in each reporting unit. Alafia River data for the period from April 1975 to September 2008 were taken from stations 74 (Rkm 1.67), 114 (Rkm 18.15) and 153 (beginning September 1999; Rkm 7.97). Salinity data were also collected by the Fisheries Independent Monitoring Program (FIM) of the Florida Fish and Wildlife Research Institute (FWRI) during routine fish sampling. In addition to sampling conducted for the Tampa Bay Water HBMP, sampling for other objectives produced salinity data for the Alafia River for the period March 1989 to December Finally, salinity data were compiled from observations reported by the Tampa Bay Estuary Program Benthic Program for the Alafia River. These data span from September 1993 to October HBMP Year 9 Interpretive Report June 2009

25 Data Sources, Analyses and Previous Reports Chlorophyll-a and Dissolved Oxygen Data Sources Like salinity, dissolved oxygen data were collected by water column profile measurements during plankton, fish, benthic and water quality sampling as part of the Tampa Bay Water HBMP beginning in April Dissolved oxygen data were also compiled from several other monitoring programs. Studies completed by the SWFWMD provided profile dissolved oxygen data from the stations described above for salinity. Water column surface, mid-depth, and bottom dissolved oxygen measurements were recorded monthly by the EPCHC as part of the Independent Monitoring Program and Ambient Monitoring Program. The frequency and distribution of these measurements are the same as that described above for EPCHC salinity measurements. Dissolved oxygen data were also collected by the FIM Program of the Florida Fish and Wildlife Research Institute during routine fish sampling. Additional dissolved oxygen data were compiled from observations reported by the Tampa Bay Estuary Program Benthic Program for the Alafia River. These data span from September 1993 to October Chlorophyll-a data were collected at randomly selected stations on a once monthly basis for the Tampa Bay Water HBMP for the period April 2000 through September Values reported by the HBMP are chlorophyll-a corrected for phaeophytin. Chlorophyll-a data (both uncorrected and corrected for phaeophytin) are also collected by the EPCHC for the Alafia River stations listed above. Values corrected for phaeophytin are available beginning in January 2005; values prior to this date are uncorrected for phaeophytin. SWFWMD sampling included chlorophyll-a data (uncorrected for phaeophytin) for the period June 1999 to September Plankton Data Sources Plankton data used for this report were collected as part of the HBMP monthly sampling and include invertebrate zooplankton and ichthyoplankton. A brief description of plankton sampling is given in Section Fish Data Sources Two fish data sets were used in this report, though both sets of data were collected by the same group. Fish population sampling conducted by the Florida Fish and Wildlife Institute s Fisheries Independent Monitoring Program (FIM) began in May The sampling process followed standard FIM protocol for HBMP samples. FIM conducts additional non-hbmp sampling in the Alafia River. Available data were included in the analyses presented in this report as applicable Benthic Macroinvertebrate Data Sources For this report, only data collected as part of HBMP from (n=1,318) were considered. Samples have been collected since June 2000 and sampling is still on-going. Data for samples collected after the end of Water Year 2007 are not yet available. Thus, data from June September 2007 were considered for this report, although not all samples collected in 2005, 2006, and 2007 have had their laboratory processing completed (Appendix B). 2-2 HBMP Year 9 Interpretive Report June 2009

26 Data Sources, Analyses and Previous Reports 2.2. Overview of Alafia River/Tampa Bypass Canal HBMP Data HBMP sampling methods and rationale are discussed in detail in the HBMP quality assurance/quality control plan (PBS&J, 2008a), the HBMP design document (PBS&J, 2000), and several previous data and interpretive reports (PBS&J, 2001; 2002a; 2003; 2004; 2005; 2006). The HBMP collects water quality, benthic macroinvertebrate, zooplankton, and fish samples monthly in each of the four reporting units. An overview and detailed description of the methods used for water quality sampling and analysis are provided in the HBMP design document (Tampa Bypass Canal/Alafia River Water Supply Projects Hydrobiological Monitoring Program (PBS&J, 2000)) and the QA/QC plan (Tampa Bypass Canal/Alafia River Water Supply Projects Hydrobiological Monitoring Program Quality Assurance and Quality Control Plan, Version 2.1 (PBS&J, 2008a)) HBMP Sampling Site Selection As specified in the HBMP design document, all but one of the monthly Alafia River sample sites (stations) for water quality, fish, benthos, and plankton are randomly selected. There is a fixed water quality sampling station at the mouth of the Alafia River. This station corresponds to EPCHC Station 8. Sampling stations for water quality, fish, and benthos are randomly selected each month. Sampling stations for plankton and for fixed-station vegetation monitoring were randomly selected at the beginning of the project and will remain fixed for the project duration. Sampling stations for the Alafia River are identified by stratum and location relative to the mouth of the river. Thus, the station in Alafia River Stratum 1, 1000 meters from the mouth of the river, is identified as AR The prefix AR1 designates the river and stratum and the suffix identifies the distance from the mouth of the river. All potential stations and their corresponding latitude and longitude have been determined and are listed in the project database. Stations are chosen in each stratum by randomly selecting from the list of potential stations Hydrology Flow in the Alafia River at Lithia is monitored by the USGS (gage # ). Flow from Lithia Springs Major is monitored on a regular basis by Tampa Bay Water. Tampa Bay Water provided data for production from the Alafia River Water Quality Water quality samples and profile measurements were taken at selected stations once a month in the Alafia River. Additional samples were taken during the summer wet-season as detailed in the HBMP QA/QC plan and design document. Water column casts or profiles were performed at each station. 2-3 HBMP Year 9 Interpretive Report June 2009

27 Data Sources, Analyses and Previous Reports The HBMP maintains one continuous water quality recorder on the Alafia River that was installed in Water Year 2001 as part of the HBMP. In addition, the USGS maintains three realtime water quality recorders on the Alafia River Benthic Macroinvertebrates Benthos samples were collected once a month in each of the seven Alafia River strata utilizing a Young-modified Van Veen grab sampler. Sampling began in June of A greater number of samples were taken during summer wet-seasons (i.e. June-August) when additional samples were collected in an inset stratum (PBS&J 2000) than during other months (Appendix B). Water profile measurements were performed at each station. Additional information on the collection and processing of benthic macroinvertebrate samples is provided in the HBMP QA/QC Plan (PBS&J 2008a). The sample collection and analysis techniques of the HBMP are compatible with the Tampa Bay Estuary s Benthic Monitoring Program for Tampa Bay (Grabe et al., 1995). Available data from HBMP benthic macroinvertebrate samples through September 2007 are presented in this report Plankton Plankton collections were made monthly in the Alafia River. The sampled locations within each reporting unit were selected using a one time stratified-random approach. Dates of sampling were chosen to correspond with the occurrence of night-time flood tides. Night-time zooplankton catches are known to be generally larger than daytime catches. This phenomenon was confirmed during preliminary sampling of the lower Alafia River. Similarly, existing data indicate that during flood tides the estuarine water column tends to contain more organisms that are moving upstream or are trying to maintain position within the estuary. Ebb tidal waters tend to contain more organisms that are in the process of leaving the estuary. Nighttime flood tides were therefore chosen as the standard conditions for zooplankton sampling. A water column profile was performed at the end of each tow. Zooplankton data collected as part of the HBMP include invertebrate zooplankton and ichthyoplankton. Zooplankton were sampled by towing a 500 µm Nitex mesh, 0.5 m diameter mouth, conical (3:1) plankton net. Standard deployment consisted of a three-step oblique tow that divides the net s fishing time equally between bottom, mid-depth, and surface waters. The standard tow duration was 5 minutes at a boat speed of 1.0 to 1.5 m/s. Due to variability in ambient flow velocities and net clogging, the volume of water sampled during each tow ranged from approximately 30 to 70 cubic meters. Each tow was initiated from a fixed station located within the sampling strata of each reporting unit. Sampling was conducted in all river strata except Alafia River stratum AR-7 due to shallow water and the high incidence of bottom snags. Additional information on the collection and processing of zooplankton samples is provided in the HBMP QA/QC Plan. 2-4 HBMP Year 9 Interpretive Report June 2009

28 Data Sources, Analyses and Previous Reports Fish Sites were selected on a stratified random basis each month. Fish sampling was conducted at selected stations once monthly on the Alafia River. The sampling effort in each stratum consisted of deploying two 21-m boat set seines and one 6.1-m otter trawl. Most of the animals traditionally sampled by FWRI s FIM Program were included in this effort. These included all fishes, blue crabs, stone crabs, horseshoe crabs, and penaeid shrimp. Water profile and Secchi depth measurements were performed at each station Analytical Techniques Center of Abundance Center of abundance (COA) statistics are presented in this report for certain fish and invertebrate taxa collected in the Alafia River. This statistic describes the average position of occurrence for a given taxon over the sampling time period. For the linear Alafia River that is divided into spatial strata along a gradient, the COA can be described in terms of river kilometer (Rkm). Center of abundance was calculated by weighting the location of occurrence by the number of organisms of the given species collected at that location and is calculated as: COA NK N where N is the number or density of individuals collected per deployment K is distance in kilometers upstream from the river mouth Abundance Weighted Salinity Abundance weighted salinity (AWS) is a statistic that describes the salinity range in which a given taxon is found to be most abundant. They were calculated for certain fish and invertebrate taxa in the Alafia River. Abundance weighted salinity weights the salinity at each sample collection site by the number or density of organisms of the given species collected at that location and was calculated as: S N NS N where N is the number or density of individuals collected per sample S is salinity at the sample point 2-5 HBMP Year 9 Interpretive Report June 2009

29 Data Sources, Analyses and Previous Reports Temporal and Spatial Water Quality Analyses Several types of graphs were produced to examine the temporal and spatial variability of salinity, dissolved oxygen and chlorophyll-a (corrected and uncorrected for phaeophytin) in the Alafia River. All graphs are presented in the appropriate Appendix. Data collected from all sources were included in the plots. Scatter plots of salinity and dissolved oxygen versus river kilometer were created for each of four depth delineations (0.0 to 0.3 m, 0.3 to 1.0 m, 1.0 to 2.0 m, and greater than 2.0 m). Additionally, different symbols were utilized to distinguish samples taken during three different time periods. These time periods were delimited by the baseline period established in the Year 3 Interpretive Report (PBS&J, 2003), the start of the Tampa Bay Water HBMP, and the date of initial withdrawals in the reporting unit. The first time period (baseline period) was defined as 1975 (beginning of Alafia baseline period as established in the Year 3 Interpretive Report (PBS&J, 2003)) through the start of the HBMP. The second period (preoperational HBMP) began in April 2000 (as the start of the HBMP) and continued up to the date of first withdrawal (February 7, 2003). The final period (operational HBMP) was considered to be the time of first withdrawal through the end of Water Year 2008 (September 2008). Box and whisker plots were created by combining all data sources from all depths to display descriptive statistics of salinity across months by river stratum. The upper and lower edges of the box represent the 75th and 25th percentiles, respectively, while the line in the box represents the median. The whiskers on the box represent the 10th and 90th percentiles and dots represent extreme values falling outside the 10th and 90th percentiles. A second set of box and whisker plots were created that combined all depths to display the above statistics for each of four time periods per river stratum. These time periods were delimited by the baseline period established in the Year 3 Interpretive Report (PBS&J, 2003), the start of the Tampa Bay Water HBMP, and the date of initial withdrawals in the reporting unit. The first time period (Period of Record) was considered to be the start of the baseline period (January 1, 1975) through the end of Water Year 2008 (September 20, 2008). The second time period (Study Period) began in April 2000 (with the initiation of the HBMP) and continued through the end of Water Year The third time period (Pre-Operational) began in April 2000 (as the start of the HBMP) and continued up to the date of first withdrawal (February 7, 2003). The final period (Operational) was considered to be the time of first withdrawal through the end of Water Year 2008 (September, 2008). A final set of box and whisker plots displayed the same univariate statistics for the above defined depth delineations (by river stratum) per quarter for all water years of the Tampa Bay Water HBMP period. Finally, cumulative distribution (cdf) of salinity and dissolved oxygen plots were created for the Alafia River by depth range and river stratum. These plots compare the four time periods described for box plots above. 2-6 HBMP Year 9 Interpretive Report June 2009

30 Data Sources, Analyses and Previous Reports Salinity Variations Attributable to Withdrawals In order to answer the question "what portion of the intra- and inter-annual variation in salinity was attributable to Tampa Bay Water withdrawals?" two hydrodynamic model scenarios were made using the Laterally Averaged Model for Estuaries (LAMFE) developed by SWFWMD staff (Chen 2003a, 2003b, 2004a, 2004b, 2005). A description of the LAMFE model is provided Appendix C. The Observed Scenario consisted of simulating the actual conditions that occurred, including the Tampa Bay Water withdrawals. The Reconstructed Scenario consisted of adding the Tampa Bay Water withdrawals back to the observed flows in order to simulate what would have happened if the Tampa Bay Water withdrawals had not occurred. The conditions of the WUP for Tampa Bay Water withdrawals from the Alafia River were temporarily modified by SWFWMD Executive Order on several occasions (further described in Section 3.2.2) due to a prolonged drought and resultant water shortage emergency. The WUP conditions were modified between August 3, 2007 and October 31, The WUP conditions were again modified for the period July 22, 2008 through September 30, To be conservative in the following analyses, the periods of the emergency withdrawals were included in the comparisons. In order to evaluate the magnitude, spatial extent and temporal extent of changes in salinity resulting from the Tampa Bay Water withdrawals, a series of graphics are presented and discussed. These graphics include: Time series plots of the Observed and Reconstructed mean daily salinity by stratum and layer; Time series plots of the difference in daily mean salinity (Observed - Reconstructed) by stratum and layer; Cumulative distribution function (CDF) plots of the difference in daily mean salinity (Observed - Reconstructed) by stratum and layer. In addition to these plots, a series of additional indicators were analyzed. These indicators have been used in development of Minimum Flows and Levels by the SWFWMD (SWFWMD 2006, 2008a, 2008b) to quantify the amount of available habitat (volume, bottom area, and shoreline length) that falls into different salinity classes and understand how Tampa Bay Water withdrawals influence the amount of available habitat. The graphics include: Time series plots of the Observed and Reconstructed daily volume, bottom area, and shoreline length within certain salinity classes (< 2 psu, < 5 psu, and < 15 psu) for the entire modeling domain; CDF plots of the Observed and Reconstructed daily volume, bottom area, and shoreline length within certain salinity classes (< 2 psu, < 5 psu, and < 15 psu) for the entire modeling domain; Box and whisker plots of the Observed and Reconstructed daily volume, bottom area, and shoreline length within certain salinity classes (< 2 psu, < 5 psu, and < 15 psu) for the entire modeling domain. 2-7 HBMP Year 9 Interpretive Report June 2009

31 Data Sources, Analyses and Previous Reports Dissolved Oxygen and Chlorophyll-a Thresholds and Exceedances To evaluate the potential effects of Tampa Bay Water withdrawals on water quality (dissolved oxygen and chlorophyll-a) within the HBMP reporting units, logistic regression models were developed. These models predict the probability of a sample being in exceedance of a threshold value. A binomial was used to assign values to dissolved oxygen and chlorophyll-a samples based on their relationship to the established threshold values. The exceedance thresholds used were obtained from independent scientific studies by the SWFWMD, the University of South Florida, and the Tampa Bay Estuary Program (TBEP). These studies were based on data from HBMP rivers and other tidal streams in southwest Florida. A 2.5 mg/l threshold for dissolved oxygen has been identified by the SWFWMD and USF researchers as an appropriate threshold value for describing adverse effects on biotic communities in the Tampa Bay s Lower Hillsborough River (SWFWMD 2006). The 15 ug/l chlorophyll-a value was based on studies conducted for the Tampa Bay Estuary Program and accepted by FDEP and EPA and used as a scientifically-based and protective target by the Tampa Bay Nitrogen Management Consortium. A copy of the FDEP acceptance letter is provided in Appendix D. For both dissolved oxygen and chlorophyll-a, these target threshold values were derived by local experts with in-depth knowledge of the Tampa Bay ecosystem and reflect appropriate site-specific thresholds which relate to management goals and actions within the Tampa Bay estuarine waters. For this analysis, data values in exceedance of the threshold (chl-a > 15, DO < =2.5) were assigned the number 1 while the remaining values were assigned as zero. Logistic regression was then performed using SAS (SAS STAT Users Guide, 1989) for each HBMP reporting unit by the a priori designated stratum assigned for the HBMP program. Bottom dissolved oxygen levels were considered for the DO analysis while sample levels for chlorophyll-a were either surface or mid-water depending on the sampling program design. Programs with varying design protocols were analyzed separately. Independent variables considered as part of the regression analysis included river flows and sample depths where applicable. Antecedent flows were considered for chlorophyll-a analysis. For the analysis of dissolved oxygen data, the effects of bottom depth on the probability of obtaining a sample with a value exceeding the established threshold criteria (i.e., Py=1 x) was included as a covariate after natural log transformation. The general model structure was defined as: where p g log β β x+βx 1 p (y) (y) (y) p(y) = probability of exceedance as a function of x g(y) = Logit transformation of the odds of exceedance x1 = flow or antecedent flow condition x2 = covariate such as bottom depth, if necessary ß0, ß1, and ß2 regression coefficients 2-8 HBMP Year 9 Interpretive Report June 2009

32 Data Sources, Analyses and Previous Reports Evaluation of the logistic regression models included calculating a Generalized R 2 statistic and evaluating the predictive capacity of the model using Receiver Operator Curves (ROC) (SAS STAT Users Guide, 1989). The computation of R 2 can be derived by comparing the maximum likelihood estimate of the intercept only model to the maximum likelihood estimate for the specified model where R LO ( ) 1 [ ] L( ) 2 2/ n L(O) = Maximum likelihood estimate under intercept only model L(B) = Maximum likelihood estimate under specified model N = Sample size The R 2 statistic was then rescaled to conform to the typical inference regarding the coefficient of determination that can reach a maximum value of 1. Receiver Operator Curves were also used to assess the predictive capacity of the logistic regression models. The ROC curves are a graphical means of assessing the predictive capacity of the logistic regression model to classify observations as being events or non events. Curves with more area under the curve have better predictive capacity than those with less area under the curve. The ROC curves use three measures of predictive accuracy; sensitivity, specificity and false positive rate. These can be explained using the matrix below. Classification describing measures of predictive accuracy from a logistic regression model. Exceedance Non-Exceedance where Exceedance a b Non-Exceedance c d Sensitivity =a/a+c Specificity = d/b+d Sensitivity is the proportion of true events that the model predicts as an event Specificity is the proportion of non-events that the model predicts as non-events False positive rate is the number of non-events the model predicts as events (c) Both sensitivity and specificity vary depending on the probability cutpoint used to classify observations as events or non events. The specificity is subtracted from 1 such that both sensitivity and 1-specificity increase as the probability cutpoint decreases. ROC curves were used only to compare strata with respect to their predictive capacity within each of the HBMP reporting units assessed. The ROC curves provide a valuable graphical illustration of the relative predictive capacity of the models within each reporting unit. 2-9 HBMP Year 9 Interpretive Report June 2009

33 Data Sources, Analyses and Previous Reports To assess the effects of Tampa Bay Water withdrawals, only flows at or above the minimum flow for operational range of withdrawals were considered. Once the predicted relationships were established, strata with significant observed relationships between DO and chlorophyll-a and flow were chosen to estimate the effects of withdrawals on the frequency of predicted water quality exceedances. For this estimation, withdrawals by Tampa Bay Water were added back into the flow calculations to constitute a Reconstructed flow term. The period of record corresponding to the Tampa Bay Water operational phase was subset and a prediction was generated for each date in the time series for both the observed and reconstructed flow scenarios. The logit estimates were transformed into predicted probabilities using the equation exp(log it) Py ( 1 x) 1 exp(logit) When depth was a significant factor in the assessment, predictions were generated at the 25%, 50% and 75% percentile of depth for each stratum. A jackknife estimation procedure (C table option: SAS STAT Users Guide) was used to select an appropriate cutpoint for classifying observations as exceedances based on their predicted probability of exceedance. The change in predicted probability of exceedance as well as the frequency of predicted exceedances was then compared between the observed and reconstructed time series. To account for the uncertainty of the estimate of the mean probability of exceedance, 95 % confidence intervals were generated for each prediction of observed and reconstructed flows. The difference between observed and reconstructed flows could then be assessed based on; 1) the difference in exceedance probability, 2) whether or not the probability would classify the result as an exceedance and 3) include the uncertainty in estimating the true exceedance probability as a function of flow (Hosmer and Lemeshow, 1989). A more detailed description of the process to define a significant difference attributable to withdrawal is provided in Appendix D Previous Interpretive Reports and MFL Report This section provides a brief summary of select reports related to the Year 9 Interpretive Report HBMP Year 3 Interpretive Report Alafia River Findings The objectives of the HBMP Year 3 Interpretive Report were to summarize existing preoperational data and define baseline conditions in the HBMP reporting units with respect to streamflow, salinity distributions, and related water quality and biological variables. Both preoperational HBMP data as well as historic data collected as part of other monitoring programs were analyzed to meet this objective. Baseline conditions established for the independent and dependent variables were intended to be used as the basis for assessing future changes in those variables, and for determining potential cause and effect relationships with the permitted surface water withdrawals. While the Year 3 report analyzed data for all HBMP reporting units, only summaries of major findings specifically pertaining to the Lower Alafia River are provided below HBMP Year 9 Interpretive Report June 2009

34 Data Sources, Analyses and Previous Reports Definition of the baseline period Baseline periods were defined based on a review of long-term flow records, and consideration of anthropogenic impacts. The baseline period for the Alafia River was defined as 1975 to December There are data available for the time period prior to However it has been determined that there was a substantial anthropogenic influence on the Alafia River flow regime due to the phosphate mining practices that were employed in that time period. Inspection of the flow record indicates that the apparent influence of these point source discharges on flows ceased after Evaluation of available water quality data also supports this change in conditions. Rainfall Analyses of long-term rainfall patterns in the Alafia and Hillsborough River watersheds showed that repeating patterns of sequential years with lower than average rainfall have occurred throughout the recent historic period ( , , ). The majority of the pre-operational HBMP monitoring data was collected during the drought that occurred from 1999 to early Hydrology Daily Alafia River flows at Bell Shoals were estimated for the baseline period utilizing both measured and modeled flows. Analyses indicated that while there have been notable short-term variations in yearly flows, there have neither been any marked systematic changes in the overall pattern of yearly total flows, nor have there been any systematic breaks in the relationship between watershed rainfall and river flow patterns. Kendall s Seasonal Tau trend analyses did not indicate the presence of any progressive change (trend) when mean flows were compared on a monthly basis. However, when yearly flow percentiles were analyzed over this period, statistically significant declines (at or just under P=0.05) were observed in both the Q10 and Q25 percentiles. Comparisons of cumulative distribution functions of daily flows between the baseline period and the pre-operational HBMP monitoring period indicated that the existing pre-withdrawal HBMP data covered a sub-period when Alafia River flow was lower than during the overall baseline period. Water Quality Surface salinities between 20 to 35 psu commonly occurred in the lower Alafia River, extending upstream from the river s mouth to the vicinity of river kilometer 7.0. Saltwater at the surface seldom extended upstream of river kilometer 13.0, and the reach of the river upstream of river kilometer 17.0 was typically characterized by freshwater (<0.5 psu) conditions year round. During seasonal high flow conditions, very low (near zero) surface salinities extended downstream to the river s mouth. Thus, the greatest observed variations in surface salinities occurred in the typically higher salinity reaches of the lower Alafia River HBMP Year 9 Interpretive Report June 2009

35 Data Sources, Analyses and Previous Reports Near-bottom salinities were considerably higher than corresponding surface salinities from the river s mouth upstream to approximately river kilometer Extensive reaches of the lower Alafia River were normally characterized by marked salinity stratification. Exceptions to the normal pattern of salinity stratification occurred during prolonged periods of both very low freshwater inflow when high surface and bottom salinity waters extended far upstream, and during very high river flow when freshwater conditions extended from the surface to the bottom downstream to near the river s mouth. Under prolonged periods of very low river flow such as occurred during much of the pre-operational HBMP monitoring period, measurable salinity at the river bottom was observed extending upstream of river kilometer 17.0 into the normally freshwater reaches of the lower Alafia River. A notable characteristic of surface dissolved oxygen (DO) concentrations in the Alafia River was the relatively frequent occurrences of very high (supersaturated) DO levels that are often observed between the river s mouth and the upstream area near river kilometer These exceptionally high ambient dissolved oxygen concentrations are indicative of very high primary production by the dense phytoplankton blooms (measured as chlorophyll-a) that have frequently been observed in the middle and lower reaches of the river. Both surface and bottom dissolved oxygen concentrations in the lower and middle river segments were observed to fall below the state single sampling event standard for estuarine waters (4.0 mg/l). This is in marked contrast with similar data for the upper freshwater Alafia River segments where concentrations almost always meet or exceed this standard. Benthic Macroinvertebrates The most frequently occurring benthic macroinvertebrate taxa in the Alafia River tended to fall into one of five different groups based on distribution. The first group includes taxa that were most frequent in the lower 4 kilometers of the Alafia River. The most frequent taxa present in this zone included amphipods, a brachiopod, polychaetes, arthropods, and bivalves. The taxa fell in an area where the regression models predicted mean surface salinities of at least 10 to 15 psu and significantly higher bottom salinities. The organisms in this group tended to be frequent at least through kilometer 3 or 4. Although the HBMP dataset is limited, these data did suggest that a future increase in the frequency of these taxa in the upstream kilometers could indicate a change in salinity or phytoplankton production regimes. Another group of taxa were most frequent in samples from the lower 9 kilometers of the Alafia River. They included polychaetes, bivalves, Nemertea, and amphipods. The taxa extended across a broad salinity regime and were also frequent in areas where dense phytoplankton blooms were common. The regression models predicted mean salinities ranging from 3 psu to nearly 20 psu across the river kilometers where these taxa frequently occurred. These taxa were also some of the most abundant organisms in the Alafia River. Though ecologically important due to their high numbers and broad distribution, they are probably quite tolerant of changing conditions. As such, their frequencies of occurrence are likely to be less than optimal indicators of small shifts in salinity or primary production HBMP Year 9 Interpretive Report June 2009

36 Data Sources, Analyses and Previous Reports A third group of taxa included those that were most frequent in the lower 14 kilometers of the river. This is essentially the entire zone of the Alafia River affected by brackish water. Only one taxa, the amphipod Grandidierella bonnieroides, occurred in at least thirty percent of the samples in this zone. As with the taxa in the group above, Grandidierella bonnieroides is probably an important component of the ecosystem through its sheer abundance and broad range. Its frequency of occurrence is probably less of an indicator than its abundance. A fourth category of taxa included those that were most frequent in the middle kilometers of the Alafia River, roughly from river kilometers 6 through 14. The most frequent of these were polychaetes, isopods, and bivalves. These taxa were centered in the area where some of the highest phytoplankton blooms have been observed, at the interface of brackish and fresh water, and at the upstream extent of significant marsh vegetation. The frequencies of occurrence of most highly estuarine or primarily fresh water taxa diminished rapidly around kilometer 10. The taxa in this group were most frequent around kilometer 10 and diminished upstream and downstream. Their frequencies of occurrence also corresponded with the inset stratum. These taxa might be good indicators of changes in salinity or primary production regimes because their distribution corresponds with the areas that models suggested were most likely to experience changes in salinity should any occur. However, these taxa were also located in a zone that exhibits some of the highest natural variation in salinity and primary production. As such, these taxa might also be among the least sensitive to subtle changes in water quality. The final group of taxa were most frequent in the uppermost kilometers of the Alafia River and absent or nearly absent in the lower kilometers. These taxa were almost entirely insects with the exception of one oligochaete. The regression models predicted that mean surface salinity drops from approximately 2 psu at Rkm 9 to very close to fresh water at Rkm 11 and fresh water at Rkm 13. The composition and distribution of this final group of taxa were consistent with that prediction. These taxa are frequently associated with freshwater systems and as such should be good indicators of significant salinity changes in the freshwater and very low salinity areas of the river. Their downstream distribution may be determined by washout from upper kilometers. These taxa may not be good indicators of subtle salinity changes at the lower end of their range as their distribution might be the result of flow regime rather than salinity regime. These taxa also typically occur in areas with relatively low phytoplankton production and as a result are not likely to be good indicators of changes in primary production patterns. Unidentified chironomids were common downstream through kilometer 10 especially during the wet season. These may be unidentifiable individuals from the chironomid taxa that are frequent in higher kilometers. They might also have been washed down from points upstream of the study area and represent taxa that are otherwise rare in the Alafia River reporting unit. The sheer number of unidentified chironomids probably warrants a grouping of all chironomids into family or higher levels for purposes of future comparisons rather than analyzing them at the lowest, identified taxonomic level. Zooplankton and Fish 2-13 HBMP Year 9 Interpretive Report June 2009

37 Data Sources, Analyses and Previous Reports In addition to frequency and abundance, the spatial distribution of zooplankton and fish were examined during the pre-operational HBMP monitoring period. Unlike benthic macroinvertebrates, zooplankton and fish are motile, and their spatial distribution typically varies over both short and long-term time scales. The temporal variability in the spatial distribution of planktonic organisms in response to changes in freshwater inflow in the reporting units is expected to be a useful tool in assessing ecological responses in the post-operational period. For this report, the two primary measures of spatial distribution with respect to changes in freshwater inflow evaluated included the center of abundance (COA) and abundance weighted salinity (AWS). The maintenance of a constant COA across a range of flows by a given taxa would indicate that this taxa has an affinity for a certain fixed habitat, and the behavioral and/or physical capabilities to control its horizontal position, within the estuary. The maintenance of a constant AWS across a range of flows by a given taxa would indicate that this taxa has an affinity for a certain preferred salinity regime, and the behavioral and/or physical capabilities to control its horizontal position, within the estuary. Baseline mean COA and AWS were calculated for all zooplankton and fish taxa over the entire pre-operational monitoring period. Because of the large number of taxa collected, the temporal variability in COA and AWS was assessed only for selected indicator species. Indicator species for invertebrate zooplankton, ichthyoplankton, and fish were selected by USF and FMRI researchers based on professional judgment with respect to ecological importance, as well as the observed frequency and abundance. The baseline analyses presented in the Year Three report showed that the selected zooplankton and fish indicator species generally exhibited a high degree of variability in both COA and AWS over a wide range of freshwater inflows during the pre-operational monitoring period. These results indicated that the selected taxa either do not have a strong affinity for fixed habitats or preferred salinity regimes within the reporting units, or they lack the behavioral and/or physical capabilities to control their horizontal position within the estuary. It was concluded that the spatial distribution of zooplankton and fish is likely controlled more by complex trophic factors such as the density and distribution of phytoplankton populations, which may in turn be more directly affected by changes in freshwater inflow. Vegetation Although the Alafia River contained by far the most herbaceous vegetation of any HBMP reporting unit, wetland vegetation was scarce above the upstream extent of the broad needlerush marshes at Rkm 6. Observed changes in wetland vegetation coverage during the HBMP study period (2000 through 2002) were almost exclusively human induced. Vegetation was mowed, areas had been cleared for dock construction, and shorelines had been excavated, stabilized, and planted with other wetland species. In fact, the extent of direct human impacts on shoreline vegetation observed just during the HBMP recording period exceeded the changes that could be reasonably expected from moderate changes in the salinity regimes of each of the rivers HBMP Year 6 Interpretive Report 2-14 HBMP Year 9 Interpretive Report June 2009

38 Data Sources, Analyses and Previous Reports Primary objectives for the HBMP Year 6 Interpretive Report submitted to the SWFWMD in 2006 were to summarize all data collected through September Additionally, analyses were conducted to compare data collected during the baseline period established in the Year 3 report, the HBMP pre-operational period, and the initial operational period of the HBMP. Both HBMP data as well as data collected as part of other monitoring programs were analyzed to meet these objectives. The report was designed to answer ten questions about river flow, Tampa Bay Water withdrawals, water quality, and biotic indicators in each respective reporting unit. These questions were: 1. What were the daily flows in each reporting unit during the study period, and how did these flows compare to the historical flow record? 2. What were the daily Tampa Bay Water withdrawals from each reporting unit during the study period, and how did these withdrawals affect daily flows? 3. What was the intra- and inter-annual variation in salinity in each reporting unit during the study period? 4. What portion of the intra- and inter-annual variation in salinity was attributable to Tampa Bay Water withdrawals? 5. How did changes in salinity attributable to changes in flow compare to the predicted salinity vs. flow relationships used during the WUP process? 6. What was the intra- and inter-annual variation in chlorophyll-a and dissolved oxygen in each reporting unit during the study period? 7. What portion of the intra- and inter-annual variation in chlorophyll-a and dissolved oxygen was attributable to Tampa Bay Water withdrawals? 8. What was the intra- and inter-annual variation in the species composition, abundance and spatial/temporal distribution of key biotic indicators in each reporting unit during the study period? 9. To what extent did variation in flow or flow related variables (e.g. salinity) affect the intraand inter-annual variation in the species composition, abundance and spatial/temporal distribution of key biotic indicators? 10. To what extent did the variation in flow or flow related variables attributable to Tampa Bay Water withdrawals affect the intra- and inter-annual variation in the species composition, abundance and spatial/temporal distribution of key biotic indicators? While the Year 6 report analyzed data for all HBMP reporting units, only summaries of major findings specifically pertaining to the Lower Alafia River are provided below HBMP Year 9 Interpretive Report June 2009

39 Data Sources, Analyses and Previous Reports Tampa Bay Water Withdrawals Withdrawals from the Alafia River began on February 7, Median withdrawals from 2003 through September 2005 were highest in the months of November through February. However, the highest values for maximum withdrawal occurred in the months of June through August. There was a very large difference between the mean and median in the wettest months. This was a result of sporadic daily withdrawals of large amounts of water, interspersed with days where no withdrawal occurred. In each succeeding year since 2003 (when withdrawals began), a greater portion of the possible, maximum permitted-withdrawals was taken following initial facility start-up issues and completion of the regional reservoir. However, Water Year 2005 was the only year where withdrawals were close to the maximum permitted levels for most of the year. Alafia River Flows There was a great deal of variability in Alafia River median flows during the HBMP study period, especially between the high flows in Water Years , and low median flow (drought condition) in Reconstructed flows (the sum of measured flow and withdrawal quantities) were used to simulate flow conditions if the Tampa Bay Water withdrawals had not occurred. The cumulative distributions of measured flows and their corresponding reconstructed flows were much more similar than the cumulative distributions of preoperational and operational flows. This suggests that withdrawals had much less of an effect on flow than did natural inter-annual variability. Analyses of Salinity Alafia River surface waters were typically fresh at the upstream strata (above Rkm 13), while there was much variability in surface salinity in the lower reaches of the river. During periods of relatively high flow, near-zero surface salinity extended downstream to the river s mouth. Salinities observed during the operational HBMP period (February 2003 to September 2005) were generally lower than salinities during the preoperational HBMP period (April 2000 to January 2003). Reconstructed salinities were modeled for the Alafia River to compare salinity values that would have occurred in the absence of withdrawals to those actually observed during withdrawals. Observed salinity values were slightly higher than reconstructed values for strata AR1 through AR6 although differences in values were typically less than 0.5 psu for all layers. In AR7, there were no differences between observed and reconstructed salinities in any layer during the entire study period. Observed versus reconstructed salinity differences were most likely to occur in the Alafia River water column bottom layer and least likely to occur in the surface layer. When they occurred in the middle and bottom layers, these differences were most likely to occur from Rkm 5 to Rkm 10 (strata AR3 and AR4 or just downstream of the I-75 Bridge to just downstream of Buckhorn Springs). When these differences occurred in the surface layer, they were most likely to occur in Rkm 5 (the lower part of stratum AR3 or the downstream side of the I-75 Bridge) HBMP Year 9 Interpretive Report June 2009

40 Data Sources, Analyses and Previous Reports The locations of various isohalines in the Alafia River were also modeled with and without Tampa Bay Water withdrawals. With few exceptions, modeled isohaline locations for the with and without withdrawal scenarios were less than 0.2 km apart. The greatest differences between the two scenarios were found in 2005 when the withdrawals from the river were greatest. The greatest differences occurred for the lower salinity isohalines (0.5 and 5 psu), although the 90th percentile difference between the two scenarios was less than 0.25 km for all the isohalines examined. This suggests the effect of the withdrawals on isohaline locations in the Alafia River was relatively small during the operational period. Analyses of Dissolved Oxygen and Chlorophyll High levels of dissolved oxygen were often observed throughout the study period in surface waters between the river s mouth and the area near Rkm 13. Observations of exceptionally high dissolved oxygen levels may correspond to exceptionally intense phytoplankton blooms (as measured by chlorophyll-a) that have been noted to occur in the mid and lower reaches of the Lower Alafia River. Chlorophyll-a values were generally low and exhibited far less seasonal variation in the characteristically freshwater reach of the river above Rkm 14. In the middle and lower reaches of the river, chlorophyll-a concentrations varied across wide ranges as a result of periodic occurrences of very high phytoplankton densities. Models were developed to determine the frequency of exceedance for threshold values (<2.5 mg/l for dissolved oxygen and >15 ug/l for chlorophyll-a, see Section 2) for dissolved oxygen and chlorophyll-a under the observed and reconstructed scenarios. The dissolved oxygen difference was minimal with no greater than a ten-percent change in the exceedance probability in any stratum. The effects were stratum specific with reconstructed flows resulting in an increased exceedance rate in the lower strata and a decreased exceedance rate in the upper strata. The maximum increase in the number of dissolved oxygen exceedances due to withdrawals was five days. In general, the relationship between chlorophyll-a and flow was weak. Biological Analyses Comparisons of observed and reconstructed flows in the Alafia River suggested that Tampa Bay Water withdrawals have had little effect on water quality parameters of concern for fish. Modeling salinity changes suggested that strata AR3, AR4 and AR5 were the most likely to see changes in salinity as a result of withdrawals; however, the difference between observed and reconstructed flow was never more than 2 psu and rarely lasted more than one day. Within the context of natural intra-daily variation in salinity, the predicted effect of withdrawals did not appear to be large enough to affect the key biotic indicators addressed as part of these analyses. The effect of withdrawals on dissolved oxygen and chlorophyll levels may be more critical with respect to the potential for adverse impacts to key fish indicator species; however there was no evidence to suggest that Tampa Bay Water withdrawals had a significant effect on the probability of exceeding a threshold DO level that would indicate an undesirable condition for the key biotic indicators. The poor relationships between flow and chlorophyll-a exceedance 2-17 HBMP Year 9 Interpretive Report June 2009

41 Data Sources, Analyses and Previous Reports suggest it is unlikely that Tampa Bay Water withdrawals had a significant effect on fish, plankton, or benthic macroinvertebrate distribution, abundance, or species composition Summary of the Determination of Minimum Flows for the Lower Alafia River Estuary At the end of 2008, the SWFWMD released a report with the proposed minimum flows for the Lower Alafia River Estuary (SWFWMD 2008). This document includes extensive analyses of environmental data performed to establish minimum flows for the river and determine allowable withdrawals. A brief summary of this lower Alafia MFL document is provided here. Background Florida Statutes (Section ) mandate that the Water Management Districts protect water resources from significant harm through the establishment of minimum flows and levels (MFLs) for streams and rivers. These MFLs are intended to function as standards for water levels (in lakes and streams) or flow rates (for streams) for permitting purposes should applicants request withdrawal volumes from surface and/or ground water. For the purposes of the Lower Alafia River Minimum Flow and Level (LAR MFL), the LAR was defined as the reach between the river s mouth in Hillsborough Bay up to Bell Shoals Road, a distance of 11.3 miles (18.2 kilometers). Since this area of the Alafia River is tidal in its entire extent, the LAR MFL was based on determining flow impacts on water quality and biological communities for estuarine systems. Studies focused on the relationships between river flow and salinity, dissolved oxygen, phytoplankton levels, macroinvertebrates, fish, and shoreline vegetation. The percent-of-flow method used by SWFWMD for the LAR MFL is based on determining the percentage of the daily flow of the Alafia River (including areas upstream of the Lower Alafia River) that could be removed without causing significant harm to the river's ecology or biological productivity. The method is designed to protect the seasonally-varying flow regime of the LAR, and the ecosystems that have evolved in conjunction with such seasonality. Using a seasonally-varying flow regime, the SWFWMD has determined that the allowable withdrawal percentage might be expected to vary seasonally. Based on analyses of long-term flow records for the Alafia River, the period from was chosen as a suitable baseline for evaluating the effects of a series of potential flow reductions in order to determine minimum flows for the LAR. Model Choices The SWFWMD s LAR MFL report used two basic model approaches for developing relationships between flows and various biological and/or water chemistry metrics. The two basic approaches were the use of empirical (i.e., statistical) models, and the use of a twodimensional hydrodynamic model. For the LAR, the SWFWMD concluded that currents and salinity distributions in the Alafia River generally vary mostly along upstream-downstream 2-18 HBMP Year 9 Interpretive Report June 2009

42 Data Sources, Analyses and Previous Reports gradients and gradients within the water column. Due to the narrow and rather straight nature of the LAR s channel, it was concluded that a two-dimensional hydrodynamic model (rather than a three-dimensional model) would be sufficient. The SWFWMD s LAR MFL used an updated version of the Laterally Averaged Model for Estuaries, or LAMFE, to simulate hydrodynamics and salinity transport. This model is viewed as being a significant improvement over a more common hydrodynamic model, the CE-QUAL- W2 model. The spatial boundaries used in this model encompassed more than 14 miles of the Alafia River, from its discharge into Hillsborough River to more than 3 miles above the farthest upstream tidal influences. The model also incorporated, in its uppermost reaches, those portions of the LAR that are higher (in elevation) than the highest tidal levels. For flow estimation using empirical models to predict the response of fish, salinity, chlorophylla, and dissolved oxygen concentrations, the gaged inflow to the upper estuary was used as the measure of flow. For flow estimation using the hydrodynamic model, additional flows from the ungaged portion of the river were incorporated. Overall Responses of Various Indicators to Flow For the purposes of the LAR MFL efforts, the area of interest was delimited as that portion of the Alafia River below Bell Shoals Road down to the mouth of the river, where it enters Hillsborough Bay. Consequently, responses outlined below are for water quality parameters and/or biological indicators within the LAR itself, and not for the larger LAR Hillsborough Bay complex. The overall responses examined include the following: Maintenance of adequate salinity for various macroinvertebrates Maintenance of adequate salinity for oysters in the lower river Maintenance of salinity regimes for protecting low salinity shoreline vegetation Maintaining the nursery function of the LAR for finfish and shellfish Avoiding flow regimes associated with abnormally low dissolved oxygen levels Avoiding flow regimes associated with abnormally high levels of chlorophyll-a The SWFWMD used a threshold value of 15% reduction in habitat as one that would cause significant harm to the biological resources of the Lower Alafia River. However, the report notes that extensive data collection on the Lower Alafia River is continuing and is periodically reexamined in the HBMP process. These data also allow for periodic reevaluations of changes in habitat availability to population parameters in order to better determine significant harm. The results of these assessments are described below for each resource management goal identified for the Alafia River. Maintenance of adequate salinity for various macroinvertebrates 2-19 HBMP Year 9 Interpretive Report June 2009

43 Data Sources, Analyses and Previous Reports Amphipods, mysid shrimp and various species of polychaete worms can be strongly associated with the benthos, with little possibility of migrating should conditions be such that growth and/or reproduction are unlikely. As these organisms are also important food sources for a number of commercially and/or recreationally important species of fish, flow regimes that protect and maintain an adequate salinity regime for macroinvertebrates were carefully examined for the LAR MFL. Using data sets that involved the simultaneous collection of both benthic invertebrates and salinity levels in various Tampa Bay tributaries, it was found that somewhat distinct differences existed for areas with salinities averaging less than 7 psu, as opposed to areas with salinities between 7 and 15 psu. For the LAR alone, the differentiation between benthic community types occurred when comparing areas less than 6 psu with those areas averaging 6 to 15 psu. The SWFWMD then used the LAMFE model to simulate the amount of bottom area in the LAR within different salinity zones, using a continuous model run representing the period of May 1999 to December Average daily estimates of the area of the bottom of the LAR with salinities less than 1, 6 and 15 psu were then calculated, and the SWFWMD then estimated the flow changes required to cause a cumulative (though space and time) reduction of these areas of greater than 15%. Maintenance of adequate salinity for oysters in the lower river In a recent study on the health of oysters (Crassostrea virginica) in the LAR, it was concluded that low flow conditions that could cause salinities to exceed 28 psu for extended periods of time (e.g., more than 2 months) could allow for degradation of existing oyster reefs. Should salinities exceed 28 psu for more than two months, harm would be expected due to increased abundance of oyster predators, and increased disease. To ensure proper survival of juvenile oysters, salinities within the area where oyster reefs are found or desired should not be continuously below 5 psu for more than two weeks. However, high flows capable of dropping salinities to lethal or near lethal levels are not a topic appropriately addressed through an MFL. Instead, the SWFWMD used both the LAMFE model and derived empirical salinity models to determine the flow reductions that would results in a more than 15% increase in the period of time that portions of the LAR would experience salinity values greater than 28 psu. Maintenance of salinity regimes for protecting low salinity shoreline vegetation Mangroves and salt marsh vegetation are found in the LAR, with mangroves being found primarily west of I-75, and salt marsh vegetation located east of US 41 to just east of I-75. Brackish water and freshwater marsh vegetation is found upstream (east) of I-75. The South Florida and Suwannee Water Management Districts have used the location of the 2 psu isohaline (the location of the 2 psu surface salinity value) as an appropriate metric to protect freshwater floodplain wetlands in tidally-influenced rivers. Additionally, a previous study determined that cattails, sawgrass and bulrush in tidally-influenced rivers were mostly limited to areas where median salinity values were less than 4 psu HBMP Year 9 Interpretive Report June 2009

44 Data Sources, Analyses and Previous Reports The SWFWMD thus used empirical modeling to predict the locations of the 0.5, 2, 4, 11 and 18 psu isohalines in the LAR, with various flow regimes. These results were then used in conjunction with information on shoreline length and vegetation distribution patterns to predict the influence of flow reductions on the amount of vegetated shoreline that would exceed guidance salinity levels, expressed as median values. Predictions based on the 19 percent flow reductions yielded relatively small reductions in percent total shoreline upstream of the isohalines, with a maximum reduction of 12% for the 0.5 psu isohaline. Maintaining the nursery function of the LAR for finfish and shellfish The LAR, as is the case with most tidally-influenced rivers, plays an important role as habitat for a variety of commercially and recreationally important species of finfish and shellfish. Data on the abundance of species such as snook, mullet, redfish, pink shrimp, and blue crabs have been collected and summarized in previous studies that have found that the distribution and abundance of most species can be related to differences in rates of freshwater inflow. Although important exceptions occur, the center of abundance of most species moves downstream with increased flows. However, abundance itself can vary both positively and negatively with increased flows, depending upon the species examined. An upstream shift in the center of abundance of a species due to decreasing flows might result in considerable impacts to that population, as the width and available habitat often decreases in a non-linear manner as one moves upstream in tidally-influenced rivers. For a number of species, the variability in the relationships between flow and abundance (where such relationships were found) was too great to be useful. Of those species where such a relationship could be developed, the relationship between flow and the catch per unit effort for juvenile redfish (Sciaenops ocellatus) was given the greatest weight due to the significant relationship between freshwater inflow and the abundance of this economically important gamefish species. Consequently, the flow reduction amount predicted to result in a 15% reduction in catch per unit effort of redfish was chosen as the primary protective criteria for preserving the nursery function of the LAR. Avoiding flow regimes associated with abnormally low dissolved oxygen levels The SWFWMD noted that the relationship between dissolved oxygen (DO) and flow differs considerably between the upper and lower reaches of the Alafia River. In the LAR, bottom water DO values decreased with increased flow for areas west (downstream) of I-75. East (upstream) of I-75, DO values increase with higher flows. These relationships were thought to be related to the same phenomenon the location of the salt wedge and its ability to stratify the water column. With low flows, the salt wedge moves upstream resulting in low DO levels in the LAR east of I-75. Under higher flow conditions, the salinity wedge retreats downstream, and stratification-induced low DO levels are found in the lower reaches of the river, as far downstream (west) as the US 41 bridge. The SWFWMD used two techniques to assess the relationships between flows and DO levels. The first technique predicted DO as a function of temperature and salinity, with temperatures 2-21 HBMP Year 9 Interpretive Report June 2009

45 Data Sources, Analyses and Previous Reports normalized to median values for locations. The predicted DO level, based on model output salinity and using median temperature values, was assessed under a variety of flow conditions. In essence, this technique used modeled salinity to predict DO levels, with temperature held constant. In addition, the SWFWMD also used regression techniques to predict changes in bottom water DO with various flow regimes. However, this approach was complicated by the previously described phenomenon in which the stratification-driven hypoxic water condition migrated downstream with high flows and upstream with low flows. Without an ability to prioritize different areas as being more or less important habitats, these results were determined to be of limited value for developing protective guidance for MFL purposes. Avoiding flow regimes associated with abnormally high levels of chlorophyll-a The LAR is characterized by extremely high levels of chlorophyll-a (Chl-a), an indicator of phytoplankton biomass. Elevated levels of Chl-a found in the LAR (in excess of 600 μg/l) can lead to reduced levels of DO. When the phytoplankton die and decompose, the bacteria associated with that decomposition can reduce DO to unsatisfactory levels. As low levels of DO are problematic the occurrence of elevated Chl-a values should be an important management concern, as they relate to the MFL guidance for the LAR. The SWFWMD determined that Chl-a levels in excess of 30 μg/l were not related to inflow rates in the upstream and downstream reaches of the LAR. In other portions of the LAR, levels of Chl-a increase with decreasing flows. These results partially support the theory that residence time, more so than nutrient loading, affects phytoplankton abundance in the LAR. The literature indicates that the distribution of zooplankton and some fish species can track the location of the Chl-a maximum zone, there is value in protecting flow regimes such that the Chla maximum does not move upstream into an area with less physical complexity. That is, this approach is useful to ensure that phytoplankton, zooplankton, and various fish species co-occur in areas with both suitable water quality and suitable physical complexity. Consequently, the SWFWMD used empirical modeling to predict the movement of the Chl-a maximum with various flow reduction scenarios, and to determine whether a low-flow threshold could be developed using the location of the Chl-a maximum, based on any breakpoints in the flow-location relationship. It was determined that the proposed minimum flow (19%) tends to shorten the length of river over which the peak chlorophyll concentration moves as flow reductions during high flow periods move the downstream positions of the Chl-a maximum upstream, but the low-flow threshold (120 cfs) keeps the low flow position similar to the baseline condition. Other Indicators 2-22 HBMP Year 9 Interpretive Report June 2009

46 Data Sources, Analyses and Previous Reports Based on data from plankton tows, the comb jelly (Mnemiopsis sp.) appeared to be most abundant in the LAR during low flow periods. This planktonic organism has been shown to be a highly efficient predator of zooplankton and larval fish. Flow data related to the abundance of Mnemiopsis sp. were used to support the 120 cfs low-flow threshold. Summary of Proposed MFL Guidance The proposed MFL for the LAR is a maximum reduction of nineteen percent (19%), with a lowflow threshold of 120 cfs (or about 77 mgd). Flow values for the LAR MFL reflect the sum of flows at Bell Shoals Road plus discharges from Buckhorn Springs. The establishment of a low-flow threshold would prohibit withdrawals when flows are below 120 cfs. While this is not a common event on an annual basis, it is much more common during the dry season. For example, daily flows are less than 120 cfs more than 20% of the days (on average) during March, April, May and June. Daily flows are less than 120 cfs more than 50% of the time during May. The 120 cfs low-flow threshold is nearly identical to the current lowflow threshold under Tampa Bay Water s existing permit, which is set at 124 cfs. Currently, Mosaic Fertilizer withdraws water from either Lithia or Buckhorn Springs, without any low-flow thresholds involved in their permit. This proposed MFL would require Mosaic to stop withdrawing water from these sources when flows from the combined sources of the Alafia River at Bell Shoals Road and Buckhorn Springs drop below 120 cfs, or offset reduced flow with augmentation from alternative sources of water HBMP Year 9 Interpretive Report June 2009

47 3.0 Analysis of Data through Water Year Introduction This section summarizes flow, water quality, and biological data collected in the lower Alafia River from 1975 through Data collected by the Alafia River/TBC HBMP from April 2000 through September 2008 are included in these summaries. Tampa Bay Water began withdrawing water from the lower Alafia River in early The potential effects of these withdrawals on river flow, salinity, dissolved oxygen concentrations, chlorophyll-a concentrations, fish and invertebrates are also analyzed and discussed in this section Reporting Unit and Study Period Description The Water Year 2003 data report (PBS&J, 2004), Year 3 interpretive report (PBS&J, 2003), and HBMP QA/QC document (PBS&J, 2008a) describe the Alafia River reporting unit (Figure 3.1.1), watershed, and river channel in detail. The period of record for Alafia River flow data is from 1975 through September While flow data preceding 1975 are available for the Alafia River, several factors, including discharges from phosphate mining-related facilities, affected Alafia River flow prior to These discharges had a substantial impact on river flow, particularly during low flow conditions. The flow record suggests that the influence of these point source discharges on flows ceased after Evaluation of available water quality data also supports this change in discharge conditions (PBS&J, 2004) Hydrologic Conditions There is no consistent trend in annual rainfall over the period of record at the NOAA Plant City rain gage (Figure 3.1.2). Median annual rainfall was slightly lower, and less variable during the study period than the period of record median (Table 3.1.1). During the pre-operational period (Water Year ) rainfall was less than normal and very stable, while during the operational period rainfall was slightly below normal and slightly more variable relative to the period of record. Water Years 2003 (76.7 inches) and 2004 (61.4 inches) were the wettest years during the study period, while Water Years 2000 (47.3 inches) and 2007 (39.6 inches) were the driest (Table 3.1.2). The period of record indicates that the normal wet season at the NOAA Plant City rain gage is June through September with the remainder of the year receiving less rainfall (Figure 3.1.3). March tends to have more rainfall than the remainder of the dry season (October through May; Figure 3.1.4). The period of record at the USGS Alafia River at Lithia rain gage is much shorter (beginning in July 1994) than the NOAA Plant City rain gage. Seasonal patterns in rainfall at the Alafia River at Lithia rain gage were the same as the pattern at the Plant City gage, with rainfall being highest in June through September (Table 3.1.3). The exception to that pattern was the 16.3 inches of rain that fell in December of Water Year 2003 (December of calendar year 2002) which was the highest rainfall amount of any month in the period of record for that gage. Total 3-1 HBMP Year 9 Interpretive Report June 2009

48 Analysis of Data through Water Year 2008 annual rainfall was lower at the Alafia River at Lithia gage than the Plant City gage for all study period years except Water Year 2005, during which rainfall totals were very similar Flows and Withdrawals Flow at Bell Shoals Alafia River flows at Bell Shoals were estimated for the time period using a combination of measured and modeled flows. Daily gage values from the Alafia River at Lithia (USGS gage ) were used to estimate flow at Bell Shoals by applying the correction formula specified in the project Water Use Permit. This correction formula accounts for additional inflow from Lithia Springs and the ungaged drainage area between Lithia and Bell Shoals. Mean monthly flow from Buckhorn Springs was calculated and these data were added to the corrected value for Bell Shoals to calculate the final Alafia Flow value used for analyses in this report. Missing values for Buckhorn Springs were filled using model linear interpolation from existing data. Because the existing data for these springs did not cover the entire baseline period, statistical models were developed for each spring using actual measured values (PBS&J, 2003). For the purposes of this report the following terminology is utilized to describe Alafia River flows: Calculated Flow at Bell Shoals = (Alafia River at Lithia Flow*1.117) +Discharge from Lithia Springs Major Adjusted flow at Bell Shoals Road = (Alafia River at Lithia flow * 1.117) + Discharge from Lithia Springs Major Tampa Bay Water Withdrawal Observed Flow = Adjusted Flow at Bell Shoals Road + Buckhorn Springs Flows Reconstructed Flow = Calculated Flow at Bell Shoals Road + Buckhorn Springs Flows Calculated daily flow in the Alafia River at Bell Shoals is displayed in Figure Summary statistics for calculated flow in the Alafia River at Bell Shoals during the study period (Table 3.2.1) indicate that the study period flow regime has been remarkably similar to the period of record. This is likely due in some part to the study period being roughly one fourth the period of record. The standard deviation is higher in the study period than the period of record indicating a greater variability in flows than would be considered normal. The maximum and minimum flows of the period of record occurred during the study period. The study period years have been characterized by either extreme high or low flows. Water Years 2003 through 2005 were characterized by higher than normal flows (as determined by mean flow) and the other study period years were characterized by lower than normal flows. This is further supported by the distribution of flows (Figures ). The study period median was nearly identical to the period of record median, however during the study period low flows tended to be lower, and high flows tended to be higher than the corresponding period of record flows. 3-2 HBMP Year 9 Interpretive Report June 2009

49 Analysis of Data through Water Year 2008 The pre-operational period is the portion of the study period prior to the initiation of withdrawals on February 7, The pre-operational period is characterized by extremely low flows relative to the period of record or the operational period (February 7, 2003 through Water Year 2008). On an annual basis, Water Years were extremely high flow years, while the subsequent three years ( ) have had flow regimes similar to or drier than the period of record. Seasonal flow patterns during the study period match the expected pattern (Figure 3.2.6), with higher flows in June through October and relatively lower flows throughout the rest of the year Water Use Permit and EDOs The water use permit (WUP) for Tampa Bay Water withdrawals from the Alafia River was issued on July 27, 1999 with an expiration date of December 31, The WUP allowed for withdrawals under the following restrictions: No withdrawals when calculated flow in the Alafia River at Bell Shoals Road is less than 80 mgd (124 cfs) When calculated flow in the Alafia River at Bell Shoals is at or above 80 mgd withdrawals may not exceed 10% of calculated flow At no time may withdrawals exceed 51.7 mgd (80 cfs) This withdrawal schedule was temporarily amended (EDO SWF ) on August 3, 2007 due to a water shortage emergency. The schedule amendments were as follow: No withdrawals when calculated flow in the Alafia River at Bell Shoals Road is less than 80 mgd (124 cfs) When calculated flow in the Alafia River at Bell Shoals is at or above 80 mgd withdrawals may not exceed 19% of calculated flow At no time may withdrawals exceed 51.7 mgd (80 cfs) EDO SWF was originally set to expire on August 29, On that date it was modified to increase the maximum allowable withdrawal to 60 mgd, and was reset to expire September 26, On that date the modified EDO was extended to October 31, On July 22, 2008 EDO SWF was issued. The withdrawal schedule in this EDO was the same as the schedule in the modified EDO SWF EDO SWF expired on September 30, A timeline of HBMP and WUP key dates is provided in Figure Alafia River Withdrawals The Alafia River pump station is located at Bell Shoals Road. Withdrawals from the Alafia River began on February 7, Data regarding withdrawals were compiled from Tampa Bay Water operating records. Daily withdrawals over the operating period are depicted in Figures and Mean withdrawals were highest in Water Year 2005 and lowest in Water Year 2003 (Table 3.2.2). Median withdrawals were zero in Water Years 2003 and 2008 and were highest in 3-3 HBMP Year 9 Interpretive Report June 2009

50 Analysis of Data through Water Year 2008 Water Year Withdrawals increased annually from Water Year 2003 to Water Year 2005 (Figure ) and were variable in subsequent years (Figure ). On an intra-annual basis mean withdrawals were highest in July through October and lowest April through June (Table 3.2.3) The Effect of Withdrawals on Flow Calculated flow is the flow that would have occurred in the absence of withdrawals. When these flows are compared with the adjusted flows very little difference is apparent (Figure ). When withdrawals are expressed as a proportion of calculated flow (withdrawal/calculated flow) the mean increases from Water Year 2003 to 2005, and remains between 5 and 8 percent through 2008 (Table 3.2.4, Figure ). The high end (upper percentiles) of withdrawals increased relative to flow in Water Years 2007 and This is due to the issuing of EDOs that increased the proportion of water available for withdrawal. Despite the increases in the upper range, mean proportion was consistent (0.05 to 0.08) from Water Years 2004 through For Water Years the inter-annual range of the 75th percentile of proportion is only In order to assess the impact of withdrawals relative to the natural variation in flows, daily maximum withdrawal was compared to the daily range in flows (Figure ). The range of flows (maximum flow-minimum flow) was determined for each day of the year (July 1, July 2, etc.) in the period of record. The maximum withdrawal that has occurred on each day of the year was identified, and daily maximum withdrawal was divided by daily range. The months during which withdrawal is highest relative to the natural range of flows are November through February (mean value, Table 3.2.5). The highest value at any time is 0.29 which occurred in August. To date withdrawals have not exceeded 29% of the measured daily variability in flow from the period of record. This metric provides perspective on the scale of withdrawals relative to natural variability in the system Natural Variation in Flows Calculated Alafia River flows at Bell Shoals were calculated as described in section Daily flows were calculated for the entire reference period. In addition, average values for the following series of intervals were subsequently determined using preceding daily flows. 3-day average 10-day average 30-day average 60-day average 90-day average 120-day average Annual minimum, mean and maximum values were next computed for each year of the Alafia River HBMP reference period. Time-series plots of the annual minimums, means and maximums for each of the averaged lagged flows (3-days through 120-days) were plotted for Alafia River at Bell Shoals flows over the 34-years covered by the HBMP reference period. 3-4 HBMP Year 9 Interpretive Report June 2009

51 Analysis of Data through Water Year 2008 Appendix E contains graphics for minimum, mean and maximum values of flows combined on a single graphic for each of the six average lagged intervals. Additionally individual graphics for the annual minimum, mean and maximum values separately for each of the six average calculated lagged terms are also available in Appendix E. These graphs include annual flow metric values as well as a fitted, smoothed line, which was plotted using a SAS (Statistical Analysis Software) cubic spline method that minimizes both the linear combination of the sums of squares of the residuals of the fit as well as the integral of the square of the second derivative. The results of the presented graphics indicate similar patterns for each of the six selected lagged flow intervals. Minimum Flows The long-term patterns of annual minimum flows for each of the six selected averaged intervals of lagged flows suggest slight declines, which have been primarily influenced by the combined extended and droughts. Mean Flows In comparison, the long-term patterns of mean annual Alafia River at Bell Shoals flows show patterns characterized by increases from the early 1990s through 2005, followed by sharp declines during the recent drought. Maximum Flows The long-term patterns exhibited by the annual maximum flows for each of the six lagged intervals are generally similar to those of the annual means. Maximum annual flows determined for intervals between 3 and 120 days show increases beginning in the early 1990s that continue until the start of the ongoing drought in Seasonal Kendall Tau Analyses for Trends in Flows Watershed flows can vary both spatially and temporally over both small and large scales due to natural variations in rainfall, as well as anthropogenic influences. The term "trends" is used here to refer to progressive changes over time in a flow metric (such as the monthly mean level), while "seasonal" and shorter term oscillating patterns are due to repeating natural processes. Researchers have proposed a number of parametric and nonparametric (distribution-free) statistical methods for determining the presence or absence of trends, some of which are more robust than others (see definitions below). The objective of these tests is to separate a pattern (trend) from the noise of repeating seasonal and/or random unexplained variations in the data. The ability to detect and quantify, or determine the absence of, progressive changes over time is imperative to developing a framework and basis for future management decisions. Parametric versus Nonparametric Methods. A basic assumption of most parametric statistical tests is that the data distribution is approximately normally distributed (or that it can be transformed to be so). The general overall robustness of parametric tests is dependent on this underlying assumption and provides resistance to the influence of outlier data. However, environmental data in general, and flow and rainfall data in particular, often violate this key underlying assumption of the most commonly applied parametric procedures. Therefore, nonparametric tests are usually considered more robust when analyzing many kinds of environmental data. 3-5 HBMP Year 9 Interpretive Report June 2009

52 Analysis of Data through Water Year 2008 Robustness, Resistance, and Influence. Robustness refers to the insensitivity to violations of the basic assumptions of a particular statistical procedure. The term resistance by comparison is used to refer to the insensitivity to outliers, while the word influence is used to describe the effect of extreme observations on summary measures. Kendall Tau and the seasonal Kendall Tau tests are nonparametric statistical tests widely used to analyze data for trends where normality cannot be assumed. These methods can be used to determine whether data values are increasing, declining, or remaining relatively level over time. This is accomplished by computing a statistic (Tau) based on the differences among all possible data pairs, thus representing the net direction of movement of the time-series data. The number of positive differences minus the number of negative differences is then determined and this is used to calculate the Mann-Kendall Tau statistic. If the time-series data are systematically increasing (or decreasing) over time, then the resulting computed Tau statistic will be a relatively large positive (or negative) value. If, however, the change over time is negligible, then the number of positive pairs and the number of negative pairs will be approximately equal, and the Tau statistic will be small. The Tau statistic can thus be viewed as an estimate of the median slope of the set of slopes estimated for the lines connecting all possible pairs of data. In addition to the Tau the following additional statistics can be determined. P-values without correction for serial correlations (applicable for trend tests using annual values) P-values statistically corrected to account for serial correlations (used in testing for trends using monthly values) The slope, which indicates the magnitude of the relative rate of change, and the sign indicates an increasing or decreasing change over time (trend) The Seasonal Kendall Tau test incorporates an additional factor to account for seasonal variation. When analyzing monthly data, each month is viewed as a "season" and this method is therefore directly applicable to flow and rainfall data, which are characterized by strong seasonal patterns. As in parametric tests, hypothesis testing for a trend is based on the null hypothesis that there is no trend. The null hypothesis can only be rejected if the Tau statistic is sufficiently large at a given level of probability (p-value). Statistical tests were conducted using SAS programming code developed by the US Environmental Protection Agency (USEPA) for nonparametric analysis of water quality and other environmental data. The USEPA SAS code was based on Seasonal Kendall Tau program code originally developed by the USGS to test for trends in flows and water quality data. This SAS code provides two alternative methods for determining if data exhibit a statistically significant trend at a given level of probability. The first method assumes that the seasonal data are independent, while the second method corrects (or de-trends) for serial autocorrelations within the data. Since monthly flow (and rainfall) data are often serially correlated (the values in many months are similar to either the preceding or following months), probability values corrected for serial correlations were used for tests of trends between selected intervals of time. 3-6 HBMP Year 9 Interpretive Report June 2009

53 Analysis of Data through Water Year 2008 Table provides summary results of tests for trends of Alafia River at Bell Shoals flows over the reference period using both the Seasonal Kendal Tau and Kendal Tau procedures. The Seasonal Kendall Tau method was used to test for trends of mean and median monthly flows over the 34-year time interval. As indicated in Table 3.2.6, while both the resulting Tau and slope statistics were negative, neither of these flow metrics indicated the presence of a statistically significant, systematic trend in mean or median flows between 1975 and In addition, the Kendall Tau procedure was used to test for statistically significant trends over the same time interval using annual values for the following series of flow statistics. Mean- this average monthly value is usually above the median when evaluating flow data P5 Percentile low flow value that was exceeded ninety-five percent of the time P10 Percentile low flow value that was exceeded ninety percent of the time P25 Percentile low flow value that was exceeded seventy-five percent of the time P50 Percentile or median value, half of the monthly values were both greater and less P75 Percentile high flow value that was exceeded only twenty-five percent of the time P90 Percentile high flow value that was exceeded only ten percent of the time P95 Percentile high flow value that was exceeded only five percent of the time Table indicates that the high flow (P90 and P95 Percentiles) Tau and slope statistics were positive, while those for the lower flow statistics were negative. However, again none of these patterns (or trends) was statistically significant Intra- and Inter-Annual Variations in Salinity Section 2.5 contains a description of salinity data sources and analyses performed. Specific figures are included in this chapter to highlight trends; additional figures are provided in Appendix F. Examination of river kilometer and river stratum versus salinity (for all depth ranges) indicated that there was generally a strong longitudinal salinity gradient running from higher salinities near the river mouth to freshwater conditions upstream. As seen in Figure 3.3.1, surface waters (0 to 0.3 m) were typically fresh at the upstream strata, while there was much variability in surface salinity at the lower reaches of the river. During periods of relatively higher flow, near-zero surface salinities extended downstream to the river s mouth. For example, during the unusually wet Water Year 2003, median surface water salinities were usually less than 5 psu for all sampled strata of the river except AR1 (Figure 3.3.2). Seasonal differences in surface salinity are evident in Figure Median surface salinity in the wetter months of July October was lower than other times of the year over the period of record. Salinity generally increased with depth, as indicated by Figure This suggests that extensive reaches of the lower Alafia River are characterized by marked salinity stratification. However, during periods of relatively high flow (e.g., Water Year 2003) median salinity differences between surface and deeper waters were notably reduced. During extreme low flow periods, as occurred during the preoperational period of the HBMP, relatively high salinity extended far upstream in the bottom water layer (Figure 3.3.5). 3-7 HBMP Year 9 Interpretive Report June 2009

54 Analysis of Data through Water Year 2008 Salinities observed during the operational HBMP period (February September 2008) were generally lower than salinities during the preoperational HBMP period (April January 2003; Figure 3.3.6) Salinity Variations Attributable to Withdrawals A description of the methods utilized for the following analyses is provided in section Time series plots of the daily mean salinities by stratum and layer are presented in Appendix G. The black lines represent the observed scenario and blue lines represent the reconstructed scenario. In addition, time series plots of the difference between the two scenarios (Observed - Reconstructed) are presented in Appendix H. These graphics illustrate the following: As expected, salinity in both the observed and reconstructed scenarios decreased with distance upstream. Also, the typical seasonal pattern of lower salinities during the wet season (June-October) and higher salinities during the dry season (November-May) is documented. For the observed and reconstructed scenarios, the lowest salinity occurred in wet seasons of 2003 and 2004, while the salinity values were higher in 2007 and 2008 as the drought conditions persisted. In AR1, the observed and reconstructed scenario salinities ranged from 0 to 32.8 psu. In AR2, salinity ranged from 0 to 32.1 psu in both the observed and reconstructed scenarios. In AR3, salinity ranged from 0 to 29.6 psu in the observed and reconstructed scenarios. In AR4, salinity ranged from psu in the observed scenario. Salinity in the reconstructed scenario had a slightly lower range, between 0 and 27.6 psu. In AR5, salinity ranged from psu in the observed scenario and between 0 and In AR6, salinity ranged from psu in the observed scenario and from 0 to 15.8 psu in the reconstructed scenario. In AR7, salinity ranged from 0 to 14.1 psu in both scenarios. In AR8, salinity values were zero for both scenarios. Salinity was higher for both the observed and reconstructed scenario in bottom layers, lower in middle layers and lowest in surface layers. No differences between bottom, middle and surface layers were found in AR8, as it is entirely fresh. In AR1 and AR2, the average differences between the observed and reconstructed scenario were less than or equal to 0.2 psu for the entire time period for all layers. The differences were smallest in the bottom layer, slightly larger in the middle layer, and the largest in the surface layer. However, the largest daily difference, seen in the bottom layer of AR2, was only a difference of 0.8 psu. AR3 had differences of less than or equal to 1.2 psu for the time period between all layers. AR4 had differences of less than or equal to 2.6, 1.9, and 1.5 psu for the time period for the bottom, middle, and surface layers, respectively. The greatest differences between observed and reconstructed values in AR5 was less than 3-8 HBMP Year 9 Interpretive Report June 2009

55 Analysis of Data through Water Year 2008 or equal to 2.8 psu in the bottom layer. AR6 had differences of less than or equal to 2.9 psu for the time period. Greatest differences were found in bottom waters (2.9 psu) and decreased through middle (2.2 psu) and surface layers (1.5 psu). AR7 had differences of less than or equal to 2.8 psu for the time period. Greatest differences were found in bottom waters (2.8 psu) and decreased through the middle (2.1) and surface layers (0.4 psu). AR8 had salinities of zero for the entire time period and therefore showed no differences between scenarios or layers. The cumulative distribution function (CDF) plots of the daily median salinity values between observed and reconstructed scenarios are presented in Appendix I. To aid in the interpretation of these plots, the 50th (red hashed line), 75th (green hashed line) and 90th (cyan hashed line) percentiles are denoted in the plots. For example, if you follow the horizontal green hashed line to where it intersects the y-axis, the difference in salinities between the two scenarios will be less than or equal to that value 75% of the time. The following observations can be made by looking at the plots: For all strata, differences in 50th percentile (median) values ranged from 0 to 0.2 psu for bottom, middle and surface layers. In ARl, AR2, and AR3, 90% of observations had a difference of less than 0.5 psu for bottom, middle and surface layers. The greatest difference between observed and reconstructed values occurred in AR4 and AR5, although 90% of these differences were less than or equal to 0.7 psu for bottom, middle and surface layers. In AR6, 90% of observations had a difference of less than 0.2 psu for bottom, middle and surface layers. In AR7 and AR8, 90% of the values showed a change of less than or equal to 0.01 psu for bottom, middle and surface layers Variations in Available Habitat Attributable to Withdrawals In addition to the plots that address changes in salinity by stratum and layer, additional plots were used to determine the change in available habitat (volume, bottom area, and shoreline length). Time series plots of the total daily habitat for each salinity class (< 2 psu, < 5 psu, and < 15 psu) are shown in Appendix J. The black lines represent the observed scenario and blue lines represent the reconstructed scenario. These graphics illustrate the following: The daily volume of water < 2 psu in both the Observed and Reconstructed scenarios varied from 0.1 to 7.2 million cubic meters. There is always some volume of water < 2 psu given that the upstream portion of the model domain remains fresh. As expected, the volume of water < 2 psu increases during the wet season as flows increase and decreases during the dry season when flows are lower. As was seen in the time series plots of salinity by stratum and layer, the volume of low salinity water decreased in 2007 and 2008 as drought conditions intensified. The daily volume of water < 5 psu in both the Observed and Reconstructed scenarios 3-9 HBMP Year 9 Interpretive Report June 2009

56 Analysis of Data through Water Year 2008 varied from 0.1 to 7.3 million cubic meters. Comparing the daily volume of water < 15 psu in the two scenarios, the volume varied between 0.6 and 7.3 million cubic meters for both scenarios. The daily bottom area of water < 2 psu in both the Observed and Reconstructed scenarios varied from 2.6 to 34.7 hectares. As expected, the bottom area of water < 2 psu increases during the wet season as flows increase and salinities decrease. CDF plots of the total daily habitat for each salinity class (< 2 psu, < 5 psu, and < 15 psu) are shown in the Appendix K. The black lines represent the observed scenario and blue lines represent the reconstructed scenario. The following observations can be made from studying the graphics: CDF plots of the daily volume < 2, < 5, and < 15 psu have tails that are identical. This is expected as no withdrawals are allowed when the flow is below the low flow threshold, which corresponds to the left tail of the plot. When flows are beyond a certain threshold on the high side (the right tail of the plot), there is a negligible difference between the two scenarios because the percent of water that is withdrawn is very small relative to the total flow in the system. Differences between the plots are detected in the range of 10% and 90% of the time, however, these differences are very small. As seen with volumes, CDF plots of bottom area and shoreline length reveal the same pattern of identical tails and very small differences in the range of 10% to 90% of the time. Box and whisker plots of the total daily habitat for each salinity class (< 2 psu, < 5 psu, and < 15 psu) are shown in Figures to The black boxes represent the observed scenario and blue boxes represent the reconstructed scenario. The boxes represent the inter-quartile range (25th, 50th [median], and 75th percentiles) while the whiskers represent the 5th and the 95th percentiles. The box and whisker plot is equivalent to looking at vertical slices from the CDF plot at the 5th, 25th, 50th, 75th, and 95th percentiles of time. These graphics illustrate the following: As expected, the box and whisker plots confirm what was seen in the CDF plots. The box and whisker plot of the daily volume < 2, < 5, and < 15 psu for the two scenarios are very similar to each other, suggesting little difference between the two scenarios. The box and whisker plots of the bottom area and shoreline length < 2, <5, and < 15 psu confirm that the two scenarios are quite similar. In conclusion, salinity decreased with distance upstream in the river. Salinity increased with increased depth. Observed salinity values were slightly higher than reconstructed values, although 90% of the differences in values were less than 0.7 psu for all layers. In AR8 there were no differences between observed and reconstructed values in any layer during the entire study period. Analysis of additional habitat metrics (volume, bottom area, and shoreline length < 2, < 5, and < 15 psu) revealed little difference between the Observed and Reconstructed scenarios. As expected, the available low salinity habitat was slightly less under the Observed Scenario. It should be noted that days when emergency withdrawals occurred were included in these 3-10 HBMP Year 9 Interpretive Report June 2009

57 Analysis of Data through Water Year 2008 analyses. These withdrawals were higher than the current permit allows, but the documented changes in salinity were still quite small Intra- and Inter-annual Variations in Dissolved Oxygen and Chlorophylla Section contains a description of dissolved oxygen and chlorophyll data sources and analyses performed. Specific figures are included in this chapter to highlight trends; additional figures are provided in Appendix F. As Figure illustrates, high levels of dissolved oxygen were often observed throughout the study period between the river s mouth and the upstream area near Rkm 13. Observations of exceptionally high dissolved oxygen levels may correspond to exceptionally intense phytoplankton blooms (as measured by chlorophyll-a) that have been noted to occur in the mid and lower reaches of the lower Alafia River (Figures and 3.6.3). Deeper water dissolved oxygen measurements were typically lower than corresponding surface values (Figure 3.6.4), particularly at the lower and middle reaches of the river. Chlorophyll-a values were generally low (Figure 3.6.2) and exhibited far less seasonal variation in the characteristically freshwater reach of the river (Stratum AR7; Figures and 3.6.6). In the middle and lower reaches of the river, chlorophyll-a concentrations exhibited very wide ranges of variability, most likely due to the periodic occurrences of very high phytoplankton densities Dissolved Oxygen and Chlorophyll-a Variations Attributable to Withdrawals Dissolved Oxygen The rationale for choosing a 2.5 mg/l dissolved oxygen concentration threshold was discussed in Section This threshold has been determined by SWFWMD and others as appropriate for southwest Florida estuarine systems. Logistic regressions generated for the previous interpretive report (PBS&J 2006) demonstrated that inflow and bottom depth were significant contributing factors to the probability of observing a DO less than 2.5 mg/l in the Alafia River. Further, the effects of inflow were stratum specific with increasing flows increasing the probability of a low DO value in the lower Alafia strata (i.e. AR1 and AR2) and decreasing the probability of exceedance in strata AR3, AR4 and AR5. Strata AR4 and AR5 (where increasing inflows decreased the DO exceedance probabilities) had the strongest relationship between inflow and the probability of exceedance. To evaluate the influence of Tampa Bay Water withdrawals on threshold exceedances for both DO and chlorophyll, the regression equations developed for the previous Year Six report were used first to estimate the probability of an exceedance under Observed and Reconstructed inflows for the operational period. The parameter estimates for these models can be found in Appendix L. The parameter estimates from the 2006 report were used to generate predictions for 3-11 HBMP Year 9 Interpretive Report June 2009

58 Analysis of Data through Water Year 2008 each date in the operational period and compare the differences between observed and reconstructed flows to identify the potential effects of Tampa Bay Water withdrawals. For DO, predictions were generated at three bottom depth levels corresponding to the 25 th, 50 th and 75% percentile of bottom depths where samples were collected in the stratum evaluated. Secondly, the regression estimates were used along with probability cut points to predict DO exceedances and compare the predictions to observed data collected between 2006 and Finally attempts were made to improve the regressions by incorporating data collected between 2006 and 2008 and re-fitting the logistic regressions. To examine the effects of Tampa Bay Water withdrawals, the difference in predicted probabilities between Observed and Reconstructed scenarios was calculated along with the upper and lower 95% confidence limits (see Appendix D for details). These probabilities could then be compared to assess if the estimated difference in exceedance probability was outside the range of model uncertainty. A prediction was classified as an exceedance due to withdrawals when: the observed probability was greater than the reconstructed probability, the confidence limits did not overlap, and where the predicted probability was greater than the established cut point. The results of the analysis suggested that the effects of withdrawals were minimal with a median difference of less than a one percent change in predicted probability due to withdrawals and a maximum increase of 15% in the deeper portion of AR5 (Appendix M). When considering the model uncertainty, there was not a single additional exceedance predicted that could be attributed to Tampa Bay Water withdrawals over the operational period given the criteria established above. To test the predictive capacity of the logistic regression model, the existing regression from the 2006 report was used to predict exceedances and compare predictions to empirical data collected since 2006 as a validation exercise. Strata AR4 and AR5 were selected for this comparison as they were identified as the parts of Alafia River where reduced inflows were most likely to result in increased exceedances of the DO threshold. A valid model would correctly predict both exceedances and non-exceedances the majority of the time. Correctly predicting an exceedance ( sensitivity ) would be considered adequate when it occurred 80% of the time (80% power), while a minimal false positive rate (incorrectly predicting an exceedance where one did not occur) was desired. In AR4 the model sensitivity was lower than desired, misclassifying exceedances and non-exceedances over 50% of the time; however, in AR5 the model sensitivity was 73% and the false positive rate was 14% which suggests that the model for AR5 is approaching criteria that is considered reasonable for model validation (Table 3.7.1). Attempts to improve the model performance by incorporating the data acquired between January 2006 and September 2008 and refitting the regression equation yielded no improvement in model performance compared to the original model (Table 3.7.2) Chlorophyll-a 3-12 HBMP Year 9 Interpretive Report June 2009

59 Analysis of Data through Water Year 2008 As stated in the last interpretive report for the Alafia River (PBS&J 2006), the analysis to determine the degree to which Tampa Bay Water withdrawals effected the probability of observing a chlorophyll value exceeding 15 ug/l was restricted to flows at Bell Shoals Road within Tampa Bay Water operational range up to 1000 cfs (i.e. 112 cfs cfs). No exceedances were observed in the Alafia River when flows at Bell Shoals Road were greater than 1000 cfs. Results of the logistic regression analysis for the previous report indicated that the probability of exceeding a threshold chlorophyll value was flow-dependent in river strata AR2, AR3, AR4 and AR5 and at the EPC station 74. In general, the relationship between the probability of a chlorophyll-a exceedance and flow was weak as indicated by the ROC curves and the associated R-square statistic. The difference between observed and reconstructed flows revealed a minimal predicted effect of withdrawals. Evaluating the difference in predicted probability of exceedance for the operational time period suggested that again there was a minimal difference in the predicted probability of exceedance between Observed and Reconstructed scenarios. The median difference was less than 1 % for any stratum and the maximum change in any stratum was 11% found in stratum AR3. All reconstructed probabilities were within the model uncertainty (Figures 3.7.1a-e). Given the criteria established above not a single chlorophyll exceedance could be attributed to Tampa Bay Water withdrawals over the operational period. Model validation for the chlorophyll logistic models suggested that the models had a high degree of sensitivity but lacked specificity. This indicates that the model over-predicts the frequency of chlorophyll exceedances in most strata (Table 3.7.3). Attempts to improve the model performance by incorporating the data acquired between January 2006 and September 2008 and refitting the regression equation yielded no improvement in model performance compared to the original model (Table 3.7.4) Intra- and Inter-Annual Variation of Fish and Invertebrates Intra- and Inter-Annual Variation of Fish and Shellfish Fish population sampling conducted by the Florida Fish and Wildlife Institute s Fisheries Independent Monitoring Program (FIM) began in May The sampling process followed standard FIM protocol for HBMP samples. FIM conducts additional non-hbmp sampling in the Alafia River. Available data were included in the Year Nine analyses for the Alafia River as applicable Fish and Shellfish Density Density is described in terms of catch per unit effort (CPUE), which has been normalized to number of individuals per 100 square meters. Box and whisker plots of per sample natural log transformed abundance (LN(CPUE+1)) by gear type in the Alafia River are presented for each Water Year in the study period in Figures and and percentiles are presented in Table 3-13 HBMP Year 9 Interpretive Report June 2009

60 Analysis of Data through Water Year The boxes show the mean (dot), median line, 25th and 75th percentiles (top and bottom of box) and minimum/maximum values (whisker lines). The notches around the median line indicate the 95% confidence interval of the median. In all years, mean and median CPUE were quite similar. The lowest mean catch level for seines was in Water Year 2005, while the lowest mean catch for trawls was in In addition, box and whisker plots of CPUE by stratum and by calendar month are presented in Appendix N. The frequency with which each identified taxon occurred in the samples, summarized by Water Year is presented in Appendix N. Table displays the mean abundance weighted salinity (AWS) for taxa of interest in the Alafia River, summarized for each Water Year in the study period. Table displays mean center of abundance (COA) for taxa of interest in the Alafia River, described by river kilometer (Rkm) Fish and Shellfish Richness and Diversity Richness is a measure of the number of species occurring in a given time period. Figures and are scatterplots of monthly richness for each Water Year in the study period. Each point on the plot represents the species richness (number of species) for a water year. A general seasonal cycle of richness is seen, with lower values in January and February and higher values in June and July. The highest richness of any month within the HBMP period occurred in July of 2008, while the lowest occurred in August of The Shannon-Weiner Index is a measure of diversity that accounts for richness and evenness of a population (Shannon and Weaver, 1949). Shannon-Weiner index values were calculated for each month and year in the study period. Figures and are box and whisker plots of the Shannon-Weiner Index values by calendar month for seines and trawls, respectively. Values are fairly consistent across all months, with mean and median being very close. For the seines, slight increases in diversity were seen for March to April and August to October. For trawls, slight increases in diversity were seen in June and October to December. Values for mean and median diversity are relatively consistent across the nine years of the study period, although Water Year 2000 for the seines and Water Year 2003 for the trawls had slightly lower values than the other years (see plots in Appendix N) Fish and Shellfish Taxa of Interest The taxa discussed in this section were selected from the list of indicator species identified previously by the HBMP (PBSJ 2006). The selection of these species was qualitatively based on a combination of abundance, catch frequency, and economic importance. Anchoa mitchilli Bay Anchovy Box and whisker plots depicting CPUE of A. mitchilli by month for seines and trawls, respectively are presented in Appendix N. There was a small peak in catch in May-June for seines and another peak in October-November for trawls. Whether seines or trawls were used, eight months had a median abundance of zero. Mean catch was always higher than the median for both seines and trawls. The high values for 75 th percentile (relative to median) are indicative of the schooling nature of this fish (Appendix N); i.e. catches of this species tend to be either 3-14 HBMP Year 9 Interpretive Report June 2009

61 Analysis of Data through Water Year 2008 very high, or, more frequently, close to zero. The mean AWS for A. mitchilli ranged from 2.8 in Water Year 2003 to 22.3 in Water Year 2000 (Table 3.8.2). The COA ranged from Rkm 3.9 to 8.0 (Table 3.8.3). Catch frequency for A. mitchilli was generally high, ranging from 0.63 in Water Year 2002, to 0.36 in Water Year 2007 (Appendix N). Callinectes sapidus Blue Crab Box and whisker plots depicting CPUE of C. sapidus in the Alafia River by month for seines and trawls, respectively are presented in Appendix N. Because C. sapidus is a bottom dwelling organism, we will focus of trawl data. Mean catch was highest from November through May, with a peak in April. Median catch was zero from July to October. The mean CPUE in trawls was highest in 2004, and lowest in 2008 (Appendix N). Mean abundance weighted salinity ranged from 13.1 in Water Year 2003 to 25.1 in Water Year 2000 (Table 3.8.2). Mean center of abundance varied annually between Rkm 2.5 and 4.7 (Table 3.8.3). Catch frequency for C. sapidus was generally high, ranging from 0.46 in Water Year 2005, to 0.16 in Water Year 2003 (Appendix N). Leiostomus xanthurus Spot Box and whisker plots depicting CPUE for L. xanthurus in the Alafia River by month for seines and trawls, respectively are presented in Appendix N. Mean catch was highest in the months of February through May. The median CPUE value was zero for all months for seines and trawls. With the exception of February and March for seines, the 75 th percentile CPUE was zero for all other months and gear types. Water Year 2003 was an exceptional year for the recruitment of Spot in the Alafia River (Appendix N). Mean AWS ranged from 6.5 in 2003 to 24.9 in 2002 (Table 3.8.2). Center of abundance ranged from Rkm 3.0 in Water Year 2004, to Rkm 7.6 in Water Year 2000 (Table 3.8.3). Catch frequency for L. xanthurus was variable, ranging from 0.30 in Water Year 2003, to 0.01 in Water Year 2006 (Appendix N). Menidia spp. Silversides Box and whisker plots depicting CPUE for Menidia spp. in the Alafia River by month for seines and trawls, respectively are presented in Appendix N. Mean catch was highest from April through August and lowest from December through March for the seines. For trawls, the 50 th percentile (median) and 75 th percentile CPUE values were zero for all months. The mean and median percentile were highest in 2000, and lowest in 2003 (Appendix N). Mean abundance weighted salinity for Menidia spp. ranged from 4.0 in 2004 to 12.5 in 2002 (Table 3.8.2). Center of abundance ranged from Rkm 4.9 in Water Year 2003 to Rkm 8.6 in Water Year 2001 (Table 3.8.3). Catch frequency for Menidia spp. was consistently high, ranging from 0.60 in 2002 to 0.39 in 2005 (Appendix N). Sciaenops ocellatus Red Drum Box and whisker plots depicting CPUE for S. ocellatus in the Alafia River by month for seines and trawls, respectively are presented in Appendix N. Mean catch was highest in the months of October through March in the seines, though the median was zero for all months. Mean CPUE was highest from Water Year 2003 through 2005 (Appendix N). Mean abundance weighted salinity for S. ocellatus ranged from 5.7 in 2003 to 21.9 in 2000 (Table 3.8.2). Center of 3-15 HBMP Year 9 Interpretive Report June 2009

62 Analysis of Data through Water Year 2008 abundance ranged from Rkm 0.8 in Water Year 2000 to 4.5 in Water Year 2001 (Table 3.8.3). Catch frequencies ranged from 0.02 in 2006 to 0.23 in 2003 and 2005 (Appendix N) Intra- and Inter-Annual Variation of Zooplankton Zooplankton data collected as part of the HBMP include invertebrate zooplankton and ichthyoplankton. Sampling was conducted in all river strata except Alafia River stratum AR-7 due to shallow water and the high incidence of bottom snags Zooplankton Density Density is described in terms of catch per unit effort (CPUE), which has been normalized to number of 100s of individuals per cubic meter for invertebrate zooplankton and ichthyoplankton. Figure is a box and whisker plot of per sample natural log transformed abundance (LN(CPUE + 1)) in the Alafia River summarized for each Water Year in the study period. The boxes show the mean (dot), median line, 25th and 75th percentiles (top and bottom of box) and minimum/maximum values (whisker lines). The notches around the median line indicate the 95% confidence interval of the median. In all years, mean and median catches were quite similar. There appears to be a pattern of alternating median abundance, whereby a year of high catch is followed by a year with lower catch. Median and mean catches were elevated in March through June and November through December (Figure and Table 3.8.4). The frequency with which each taxon occurred in the samples, summarized by Water Year is presented in Appendix O. Table displays the mean abundance weighted salinity (AWS) for the taxon of interest in the Alafia River, summarized for each Water Year in the study period. Table displays mean center of abundance (COA) for the taxa of interest in the Alafia River, described by river kilometer (Rkm) Zooplankton Richness and Diversity Richness is a measure of the number of species occurring in a given time period. Figure is a scatterplot of monthly richness for each Water Year in the study period. Each point on the plot represents the species richness (number of species) for a water year. Richness was lowest in the months of December through February, and consistently high for the rest of the year. No Water Year stood out as having consistently high richness. The highest richness of any month occurred in December of 2000, while the lowest occurred in January of The Shannon-Weiner Index is a measure of diversity that accounts for richness and evenness of a population (Shannon and Weaver, 1949). Shannon-Weiner index values were calculated for each month and year in the study period. Figure is a box and whisker plot summarizing the Shannon-Weiner Index values by month. Mean and median Shannon-Weiner values were similar within each month. Mean and median diversity values were highest from July through September and lowest in December. Figure is a box and whisker plot summarizing Shannon-Weiner values by Water Year. Median diversity values were between 1.7 and 2.3 during every year in the study period. Mean and median diversity was lowest in HBMP Year 9 Interpretive Report June 2009

63 Analysis of Data through Water Year Zooplankton Taxa of Interest Ichthyoplankton The data from Dr. Ernst Peebles were subset for the following analyses. The individuals analyzed here are the same individuals selected for analysis in the 2003 Interpretive Report (PBS&J, 2003) and justifications for their selection can be found in that document. Only data for Anchoa mitchilli in the juvenile life history stage were analyzed. For all other ichthyoplankton taxa of interest all life stages except the egg stage were combined and analyzed. Anchoa mitchilli A box and whisker plot of CPUE for A. mitchilli in the Alafia River, summarized by month is presented in Appendix O. Median catch was above zero in all months. Mean and median CPUE were highest in November, with another lesser spike in May. Mean catch varied between 2.3 in Water Year 2005 and 4.3 in Water Year 2008 (Appendix O). Table describes AWS for zooplankton taxa of interest in the Alafia River, by Water Year. The lowest AWS for A. mitchilli was 4.1 in 2003, while the highest, 11.9 occurred in Water Year Center of abundance was lowest in Water Year 2005 (Rkm 6.2) and highest in 2002 (Rkm 8.4) (Table 3.8.6). Brevoortia smithi A box and whisker plot of CPUE for B. smithi in the Alafia River, summarized by month is presented in Appendix O. B. smithi were present only in the months of March through July. Median and 75 th percentile CPUE were zero for all months. Mean CPUE was slightly higher from April through June. Mean CPUE declined annually reaching zero in 2006 and then rose slightly to 2008 (Appendix O). Table describes AWS for zooplankton taxa of interest in the Alafia River, by Water Year. The lowest AWS for B. smithi was 0.1 in 2005, while the highest, 20.5 occurred in Water Year Center of abundance was lowest in Water Year 2005 (Rkm 4.0) and highest in 2002 (Rkm 9.5) (Table 3.8.6). Cynoscion arenarius A box and whisker plot of CPUE for C. arenarius in the Alafia River, summarized by month is presented in Appendix O. Mean CPUE was higher from April through September, peaking from May to July. Median catch was zero for all years. Mean CPUE varied annually from 0.1 to 0.4 without a clear pattern (Appendix O). Table describes AWS for zooplankton taxa of interest in the Alafia River, by Water Year. The lowest AWS for C. arenarius was 12.8 in 2005, while the highest, 29.6 occurred in Water Year Center of abundance was lowest in Water Year 2007 (Rkm 0.4) and highest in 2005 (Rkm 2.0) (Table 3.8.6). Gobiesox strumosus A box and whisker plot of CPUE for G. strumosus in the Alafia River, summarized by month is presented in Appendix O. Mean CPUE peaked in April and May. Median catch was zero in all months. Median catch was zero for all years. Mean CPUE varied annually from 0.04 to 0.4 without a clear pattern (Appendix O). Table describes AWS for zooplankton taxa of interest in the Alafia River, by Water Year. The lowest AWS for G. strumosus was 6.0 in 2003, 3-17 HBMP Year 9 Interpretive Report June 2009

64 Analysis of Data through Water Year 2008 while the highest, 28.3 occurred in Water Year Center of abundance was lowest in Water Year 2008 (Rkm 1.0) and highest in 2003 (Rkm 8.0) (Table 3.8.6). Trinectes maculatus A box and whisker plot of CPUE for T. maculatus in the Alafia River, summarized by month is presented in Appendix O. T. maculatus were caught in all months except December. Mean CPUE was highest from May through September, peaking in June. Median catch was zero for all years except Water Year Mean CPUE ranged from 0.2 to 0.9 with no distinct pattern (Appendix O). Table describes AWS for zooplankton taxa of interest in the Alafia River, by Water Year. The lowest AWS for T. maculatus was 4.8 in 2003, while the highest, 19.9 occurred in Water Year Center of abundance was lowest in Water Year 2006 (Rkm 2.2) and highest in 2003 (Rkm 7.9) (Table 3.8.6). Invertebrate Zooplankton The data from the HBMP Plankton program were subset for the following analyses. The individuals analyzed here are the same individuals selected for analysis in the 2003 Interpretive Report (PBS&J, 2003) and justifications for their selection can be found in that document. Order Mysidacea Mysid Shrimps A box and whisker plot of mysid shrimp CPUE in the Alafia River, summarized by month is presented in Appendix O. Median CPUE was above zero for all months except June to August. There were two peaks in the mean CPUE for mysids, one in April and another in November. Mean CPUE was lowest in Water Years 2000 and 2003 (Appendix O). Table lists the AWS for mysid shrimps in the Alafia River by Water Year. The lowest AWS was 9.9 in 2005, while the highest, 19.0, occurred in Water Year Center of abundance was lowest in Water Year 2003 (Rkm 1.3) and highest in 2002 (Rkm 6.3) (Table 3.8.6). Americamysis almyra A box and whisker plot of CPUE for the mysid shrimp Americamysis almyra in the Alafia River, summarized by month is presented in Appendix O. Mean and median CPUE were bimodally distributed with peaks in November and March-April. The catch statistics were lower in June through August. Median annual CPUE varied from 1.3 in 2000 to 19 in 2004 (Appendix O). The lowest AWS for A. almyra was 6.6 in 2006, while the highest, 16.6, occurred in Water Year 2000 (Table 3.8.5). Center of abundance was lowest in Water Year 2000 (Rkm 5.0) and highest in 2008 (Rkm 10.2) (Table 3.8.6). Acartia tonsa A box and whisker plot of CPUE for the copepod Acartia tonsa in the Alafia River, summarized by month in presented in Appendix O. There was no consistent pattern for catch of A. tonsa. Mean catch was highest in November and December, while median values were zero for all months. Mean CPUE ranged from 0.2 in water year 2000 to 1.4 in water year 2004 (Appendix O). Table describes AWS for zooplankton taxa of interest in the Alafia River, by Water Year. The lowest AWS for A. tonsa was 15.6 in 2003, while the highest, 27.4, occurred in Water Year Center of abundance was lowest in Water Years 2000 and 2003 (Rkm 0.5) and highest in 2007 (Rkm 1.9) (Table 3.8.6) HBMP Year 9 Interpretive Report June 2009

65 Analysis of Data through Water Year 2008 Edotea triloba A box and whisker plot of CPUE for the isopod Edotea triloba in the Alafia River, summarized by month in presented in Appendix O. Mean and median catch were highest in the months of April through June, and lowest in October. Mean CPUE was highly variable on an annual basis, with no distinct pattern. Mean catch was much higher in Water Years 2000 and 2008 (Appendix O). Table describes AWS for zooplankton taxa of interest in the Alafia River, by Water Year. The lowest AWS for E. triloba was 9.7 in 2004, while the highest, 17.8 occurred in Water Year Center of abundance was lowest in Water Year 2003 (Rkm 3.2) and highest in 2000 (Rkm 8.0) (Table 3.8.6). Mnemiopsis mccrady A box and whisker plot of CPUE for the ctenophore Mnemiopsis mccradyi in the Alafia River, summarized by month is presented in Appendix O. Mean catch was highest in the months of April through June, and consistently low for the rest of the year. The 75 th percentile catch was zero for all months, so Mnemiopsis mccradyi was collected in less than 25% of the samples. Mean CPUE varied considerably, with a minimum of 0.01 in 2006 and a maximum of 1.0 in Water Year 2000 (Appendix O). Table describes AWS for zooplankton taxa of interest in the Alafia River, by Water Year. The lowest AWS for M. mccradyi was 4.9 in 2005, while the highest, 24.5 occurred in Water Year Center of abundance was lowest in Water Year 2006 (Rkm 1.5) and highest in 2005 (Rkm 7.8) (Table 3.8.6). Palaemonetes pugio A box and whisker plot of CPUE for the grass shrimp Palaemonetes pugio in the Alafia River, summarized by month is presented in Appendix O. Median catch was zero in all months. Mean CPUE was highest from June to October, however the 75 th percentile CPUE was zero for all months except July and August. Mean CPUE was less than one for all water years in the study (Appendix O). Table describes AWS for zooplankton taxa of interest in the Alafia River, by Water Year. The lowest AWS for P. pugio was 0.3 in 2006, while the highest, 9.5 occurred in Water Year Center of abundance was lowest in Water Year 2005 (Rkm 2.8) and highest in 2006 (Rkm 10.0) (Table 3.8.6) Intra- and Inter-Annual Variation of Benthic Invertebrates Specific figures are included in this chapter to highlight trends; supplemental figures are provided in Appendix P. Taxa richness (mean, by year, of all samples in each month) displayed a general seasonal cycle: highest values occurred in the winter and early spring, and the lowest values occurred during the summer months (Figure ). Taxa richness was generally highest during Water Years and lowest during Taxa richness followed a general seasonal cycle with highest values in the winter and early spring, and lowest values observed during the summer months. Taxa richness was generally highest during Water Years and lowest during The seasonal cycle in richness follows the seasonal variation on salinity. There was a general increase in numbers of taxa with salinity (Figure ). At any given salinity, taxa 3-19 HBMP Year 9 Interpretive Report June 2009

66 Analysis of Data through Water Year 2008 richness tended to be higher during the Operational Period than during the Pre-Operational Period, although the numbers of taxa ranged widely at any given salinity. There was little variation in observed Shannon-Wiener diversity across months (Figure ). A slight decline in diversity was found during the summer months and the highest median diversity values occurred in May and November. Inter-annual variation was considerable but with no apparent temporal trend (Figure ). Polychaetes and amphipods were selected as faunal groups of particular interest because of their contributions to the diets of finfish (Peebles, 1993; Peebles, 2002). Within the Alafia River study area, these groups are represented by at least 85 and 30 taxa, respectively (Appendix P). Polychaetes were collected throughout most the river and were slightly more widespread during the Pre-Operational Period than during the Operational Period (even though more samples have been collected during the Operational Period) (Figure ). There was considerable overlap between the Pre-Operational and Operational periods in the locations of samples that contained polychaetes. Most of samples that contained polychaetes occurred at salinities between ~1 and 22.5 psu (median ~11 psu) during the Pre-Operational period and between ~1 and 19 psu (median ~8 psu) during the Operational Period (Figure ). Amphipods were collected throughout most of the river and were slightly more widespread both upriver and downriver during the Pre-Operational Period than during the Operational Period despite the fact that more samples have been collected during the Operational Period (Figure ). There was little difference in the locations of samples that contained amphipods during the Pre-Operational and Operational periods. Most of the samples that contained amphipods occurred at salinities between ~3 and 26 psu (median ~13.5 psu) during the Pre-Operational period and between ~2 and 20 psu (median ~9 psu) during the Operational Period (Figure ). Several benthic taxa were identified as species of interest based upon a Principal Components Analysis (PCA) that identified resource-based salinity classes (based upon the ranges of salinities in which individual taxa occur in the Alafia River; see Section 2). The selected taxa were characteristic of the Oligohaline (<8 psu) and Mesohaline (8-16 psu) salinity classes. The six Oligohaline taxa of interest are: 1. Chironomus spp. (Diptera) larvae; 2. Corbicula fluminea (Asian clam); 3. Polymesoda carolinae (Carolina marsh clam); 4. Polypedilum halterale Group larvae (Diptera); 5. Polypedilum scalaneum Group larvae (Diptera); and 6. Tagelus plebeius (Stout Razor Clam). The tube-building amphipod Grandidierella bonnieroides was important in distinguishing the Oligohaline and Mesohaline salinity classes in the PCA HBMP Year 9 Interpretive Report June 2009

67 Analysis of Data through Water Year 2008 Species typical of Mesohaline salinity class included: 1. Cyathura polita (Isopoda); 2. Edotea triloba (Isopoda); 3. Laeonereis culveri (Culver s sandworm); and 4. Mytilopsis leucophaeata (Dark False Mussel). Chironomus spp. larvae were present in all strata during both periods. They were more frequently encountered during the Operational Period than during the Pre-Operational Period in all strata except Stratum 5 (Appendix P). Densities were generally greater during the Operational period. The greatest differences in both occurrence and abundance from Pre-operational to Operational periods occurred in Stratum 4. Median densities of Chironomus spp. larvae were similar for all months, although the highest densities were observed during winter-early spring and the lowest densities during September. Median densities were also similar across Water Years. The lowest density values were observed during and the highest densities occurred in Densities of Chironomus spp. larvae generally declined as salinity increased although during the Operational Period highest densities tended to occur at salinities of ~5 psu, although relatively high densities were found to occur at salinities as high as psu. Corbicula fluminea is an exotic species that prefers freshwater but can also thrive in low salinity waters. Corbicula was more frequently encountered during the Operational Period than during the Pre-Operational Period and its distribution extended further downstream during the Operational Period as well (Appendix P). Densities were also greater during the Operational period in every stratum that Corbicula was found. Median densities of Corbicula were similar across all months, although highest densities tended to occur during January and February. Median densities were also similar across Water Years, although highest values occurred in Densities of Corbicula generally declined as salinity increased, although during the Operational Period relatively high densities occurred at salinities as high as 15 psu. Polymesoda carolinae were more frequently collected and more abundant during the Operational Period than during the Pre-Operational Period in strata AR1 and AR3-AR5 (Appendix P). The greatest differences in both occurrence and abundance from Pre-operational to Operational periods occurred in Stratum AR3. Median densities of Polymesoda were similar for all months and years. Highest densities were observed during February and in Densities of Polymesoda larvae tended to be higher at Oligohaline salinities. Chironomid larvae in the Polypedilum halterale Group (four species) were more frequently encountered during the Operational Period than during the Pre-Operational Period in all strata except Stratum AR5 (Appendix P). Densities were also generally greater during the Operational period, regardless of Stratum. The greatest differences in both occurrence and abundance from Pre-operational to Operational periods occurred in Stratum AR4. Median densities of Polypedilum halterale Group larvae were similar for all months, although the highest densities were observed during winter-early spring and the lowest densities during September. Median densities were also similar across Water Years. The lowest density values were observed during 3-21 HBMP Year 9 Interpretive Report June 2009

68 Analysis of Data through Water Year and the highest densities occurred in Densities of Polypedilum halterale Group larvae generally declined as salinity increased although during the Operational Period highest densities tended to occur at salinities of ~5 psu and relatively high densities were found to occur at salinities as high as ~15-20 psu. Polypedilum scalaenum Group larvae (two species) were more frequently encountered during the Operational Period than during the Pre-Operational Period in all strata in which they occurred (Appendix P). Densities were considerably greater during the Operational period, regardless of stratum. The greatest differences in both occurrence and abundance from Pre- Operational to Operational periods occurred in Stratum AR6. Median densities of Polypedilum scalaenum Group larvae were similar for all months, although the highest densities were observed during winter-early spring and the lowest densities during September, a pattern similar to larvae in the Polypedilum halterale Group (above). Median densities were also similar across Water Years. The lowest density values were observed during and the highest densities occurred in Densities of Polypedilum scalaenum Group larvae generally declined as salinity increased, although during the Operational Period relatively high concentrations occurred at salinities as high as almost 20 psu. Tagelus plebeius were more frequently encountered and more abundant during the Operational Period in strata AR1 and AR3 (Appendix P). Occurrence and abundance were slightly greater during the Pre-operational period than during the Operational period in strata AR2, AR4, and AR5. The greatest differences in both occurrence and abundance from Pre-operational to Operational periods occurred in Stratum 3 (Operational>Pre-Operational). Median densities of Tagelus plebeius were similar for all months, although maximum densities were variable. Median densities were also similar across Water Years. The lowest density values were observed during 2000 and 2007 and the highest densities occurred in Densities of Tagelus plebeius did not show any meaningful relationship with salinity, however at any given salinity, densities were higher during the Operational Period. Grandidierella bonnieroides was more frequently encountered and more abundant during the Operational Period in strata AR1 through AR5 (Appendix P). The greatest differences in abundance from Pre-operational to Operational periods occurred in Stratum 3 (Operational>Pre- Operational). Median densities of Grandidierella were similar for all months, although the maximum densities were variable. Median densities were also similar across Water Years. The lowest density values were observed during 2000 and the highest densities occurred in Densities of Grandidierella tended to be higher at salinities between ~10 and 20 psu and, at these salinities, densities were generally higher during the Operational Period. Cyathura polita was found in all Strata during both the Pre-Operational and Operational periods (Appendix P). This isopod was most frequently encountered and most abundant during the Operational Period in Stratum AR3. Densities were extremely low in strata AR6 and AR7 during both periods. The greatest concentrations were found in AR3 and AR2 during the Operational Period. Median densities of Cyathura were similar for all months, although the highest densities occurred in May. Median densities were also similar across Water Years. The lowest density values were observed during 2000 and the highest densities occurred in HBMP Year 9 Interpretive Report June 2009

69 Analysis of Data through Water Year 2008 Densities of Cyathura tended to be higher at salinities between ~10 and 20 psu during the Operational Period. There was less evidence of a relationship between abundance and salinity during the Pre-Operational period. Edotia triloba was most frequently encountered during the Operational Period in strata AR2 and AR3 (Appendix P). Densities were extremely low in the three uppermost strata. Even though Edotia occurred with similar frequency in strata AR2 and AR3 during the operational Period, densities were much higher in AR3. Median densities of Edotia were similar for all months, although the highest densities occurred in April and May. Median densities were also similar across Water Years, while the highest densities occurred in Densities of Edotia tended to show little relationship to salinity. Laeonereis culveri was present in each stratum during both periods (Appendix P). Laeonereis was more frequently encountered during the Pre-Operational Period in strata AR5-AR7 whereas during the Operational Period Laeonereis occurred more frequently in strata AR1-AR4. Laeonereis occurred most frequently in strata AR3 and AR4 during the Operational period. Densities were relatively low in most strata during the Pre-Operational Period and were most abundant in Strata AR3-AR5 during the Operational period. Median densities of Laeonereis were similar for all months, although the highest densities occurred in February, May, June, and November. Median densities were also similar across Water Years. The lowest density values occurred during 2005 and higher densities occurred in 2001, 2002, 2006, and 2007, with the highest densities occurring in Laeonereis tended to be more abundant at salinities of ~5 to 15 psu during the Operational period. Mytilopsis leucophaeata was common upstream of AR2 (Appendix P). Unlike the taxa discussed above, Mytilopsis was not always more frequently collected during the Operational period. Densities were generally higher during the Pre-Operational period especially in Strata AR6 and AR3. Median densities of Mytilopsis were similar for all months, although the highest densities occurred in May, June, and August. Median densities were also similar across Water Years. The lowest density values occurred during 2005 with higher densities in 2002, 2003, 2006, and Mytilopsis tended to be relatively abundant at salinities as high as ~25 psu but were virtually absent above 30 psu. Salinity was shown to vary seasonally, spatially, and inter-annually (Section 3.3). The univariate benthic community and selected taxa metrics showed a relationship to these salinity trends. Taxa richness (and Shannon-Wiener diversity) underwent a general seasonal cycle that mirrored the salinity cycle: numbers of taxa and diversity were lowest during months when salinity was lowest and were highest when salinity was highest. Taxa richness and diversity tended to be higher in 2006 and 2007, when salinities were relatively high, than in , when salinities were relatively low. Most of the individual taxa examined exhibited a similar temporal pattern: higher occurrences and densities during the Operational Period, regardless of river stratum. Salinities were generally lower during the Operational Period than during the Pre-Operational period (Section 3.3). Taxa 3-23 HBMP Year 9 Interpretive Report June 2009

70 Analysis of Data through Water Year 2008 that were both more abundant and more frequently collected during the Operational Period included: 1. Cyathura polita 2. Corbicula fluminea 3. Polymesoda carolinae; and 4. Polypedilum scalaenum Group larvae. Taxa that were more abundant during the Operational Period but occurred at similar frequencies in each period included: 1. Chironomus spp. 2. Edotia triloba 3. Grandidierella bonnieroides 4. Laeonereis culveri; and 5. Polypedilum halterale Group larvae. Mytilopsis leucophaeata exhibited a strikingly different pattern than the taxa listed above. Mytilopsis was much more abundant during the Pre-Operational period when salinities were generally higher. Additionally, the occurrence of Mytilopsis did not conform to a consistent pattern. In some strata Mytilopsis was more frequently collected during the Pre-Operational period, in others during the Operational Period. There were noticeable taxon specific differences in the benthos of the Alafia River between Pre- Operational and Operational periods. Most of the taxa selected based on their salinity distribution tended to be more abundant after withdrawals had commenced. However, the salinities during the Operational period tended to be lower than during the Pre-Operational period when these taxa were less abundant. The changes in taxa richness and diversity showed relationships to both seasonal salinity cycles and inter-annual differences Key Fish and Invertebrate Variation Attributable to Flow or Flow Related Variables Variation in key biotic indicators was attributable to flow and flow related variables in the Alafia River throughout the study period. Variations in AWS and COA for all the key indicators fluctuated in response to variations in freshwater inflow with a general pattern of the central tendency for salinity reflecting the effects of the negative relationship between freshwater inflow and salinity. As inflows decreased, the AWS generally increased and the COA moved up river. Analyses from previous HBMP reports (PBS&J, 2004) have suggested that key fish indicators (e.g., Sand Seatrout, Hogchoker, and Bay Anchovy) move upstream and decrease in abundance during low flows and may be displaced from the river during extreme high flow conditions HBMP Year 9 Interpretive Report June 2009

71 Analysis of Data through Water Year 2008 Freshwater inflows not only affect water velocity and salinity, but also affect dissolved oxygen levels and chlorophyll-a production in the estuarine portions of the Alafia River. The effects of increased flows are geographically specific. Increased flows appear to have positive effects on dissolved oxygen levels in the upper HBMP strata of the Alafia River and negative effects on dissolved oxygen in the lower HBMP strata of the Alafia River. Vertical water column stratification and water depth are also important considerations affecting dissolved oxygen levels. MacDonald et al (2006) found that species richness and abundance decreased at dissolved oxygen levels of 2 mg/l or less in fish samples collected by small otter trawls which sample river channels and adjacent waters greater than 1.0 m in depth. This relationship was not observed in the shallow water seine data due to the smaller sample size for low DO condition. Deeper waters have more low DO events and therefore pose more frequent potential impacts than the shallow water habitats along the shoreline. Matheson et al. (2005) found species specific relationships between abundance and inflows in the tidal Alafia River though most relationships exhibited negative responses to increased flows. Those species that exhibited positive relationships tended to be oligohaline species such as the Hogchoker, Seminole Killifish and Coastal Shiner which may indicate increased utilization of the downstream habitats by species that prefer low salinity environments when flows increase. In general, while these results describe some empirical relationships, they were not robust enough to use as assessment tools Key Fish and Invertebrate Variation Attributable to Withdrawals Comparisons of observed and reconstructed flows in the Alafia River suggest that Tampa Bay Water withdrawals have had little observable effect on water quality parameters of concern for fishes. Modeling salinity changes has suggested that strata AR3, AR4 and AR5 may be the most sensitive with respect to changes in salinity. However, the difference between observed and reconstructed flow was never more than 2 psu. Within the context of natural intra-daily variation in salinity, the predicted effect of withdrawals does not appear to be of a magnitude large enough to affect the key biotic indicators addressed as part of these analyses. The effects of alterations of freshwater inflows on dissolved oxygen and chlorophyll-a levels may be most critical with respect to the potential for adverse impacts to key fish indicator species. There was no evidence to suggest that Tampa Bay Water withdrawals had a significant effect on the probability of exceeding a threshold DO, which would create an undesirable condition for the key biotic indicators. There is a poor relationship between flow (within the withdrawal range) and chlorophyll-a exceedances. This makes it highly unlikely that any inferences can be made to directly relate the effects of Tampa Bay Water withdrawals to effects on chlorophyll-a levels. Given the lack of association between Tampa Bay Water withdrawals and changes in salinity (section 3.4), dissolved oxygen (section 3.7.1) and chlorophyll (section 3.7.2) which are principal forces affecting the abundance patterns of fish, plankton and benthos population (along with natural variation, seasonal recruitment patterns and episodic events such as red tide blooms in the coastal and estuarine waters of Tampa Bay), it is unlikely that changes in the abundance or distributional patterns of these biota can be attributed to Tampa Bay Water withdrawals with confidence that other factors are not confounding that interpretation HBMP Year 9 Interpretive Report June 2009

72 Analysis of Data through Water Year Vegetation Vegetation monitoring on the Alafia River currently consists of mapping all riverine wetland vegetation once every three years in the September through December period. The results of mapping events performed in Water Years 2003, 2006, and 2009 are described here. Eighteen different emergent vegetation associations were mapped on the banks of the Alafia River (Figure ). These included: Brazilian pepper Cattail Cattail/needlerush Cattail/needlerush/leather fern Common reed Cordgrass Freshwater marsh Mangrove swamp Needlerush Needlerush/cattail Needlerush/leather fern Needlerush/leather fern/mangrove Other wetland forest Sawgrass/needlerush Sawgrass Sawgrass/needlerush/leather fern Wetland coniferous forest Wetland hardwood forest These vegetation associations were aggregated into the following thirteen analysis groups in order to characterize the emergent wetland vegetation on the Alafia River: Mangrove Swamp Needlerush Needlerush/Leather Fern Wetland Hardwood Forest Mixed Herbaceous Wetland Cattail Brazilian Pepper Needlerush/Cattail Wetland Coniferous Forest Common reed Sawgrass Cordgrass Popash/Willow 3-26 HBMP Year 9 Interpretive Report June 2009

73 Analysis of Data through Water Year 2008 There were a total of 92.9, 93.3, and 94.2 acres of emergent, wetland vegetation in the Alafia River reporting unit in Water Years 2003, 2006, and 2009 respectively. The distribution of vegetation by 100-meter river segment is shown in Figure The lower five kilometers of the river contain more than 76 percent of the vegetation in the reporting unit. River kilometer 4 alone contains 20 percent of the vegetation in the reporting unit. The lower 10 kilometers of the river contain 97 percent of the emergent wetland vegetation in the reporting unit. Much of the vegetation in the lower third of the river exists in large mangrove swamps or needlerush marshes. These large wetland areas generally end above RKm 6 as the river becomes more incised. Needlerush and assemblages with dominant needlerush components comprise over 45 percent of wetland vegetation on the river, the greatest area of any vegetation group. It is confined between RKm 2.5 and RKm 9 with the largest areas occurring between RKm 2.8 and RKm 6.5. The majority of the vegetation in RKm 4 is needlerush. Mangroves comprise over 40 percent of the vegetation in the reporting unit. The mangroves are confined to the mouth of the river below RKm 5. Over 85 percent of the mangroves are located below RKm 3.5. Vegetation changes in the 2003 to 2006 and 2006 to 2009 periods were very small (Figure ). The percent change of wetland species areas in the 2003 to 2006 and 2006 to 2009 time periods is shown in Figure The largest percent changes occurred in cattail and Brazilian pepper assemblages. Changes in areas for all other species were less than 2%, with the majority being well less than half a percent. Because Brazilian pepper is an invasive exotic species and Cattail is often a nuisance species, these two assemblages are subject to disturbance from vegetation management practices. These assemblages also occur in narrow bands along developed areas of the river bank making them even more subject to human disturbance unrelated to flow or salinity modifications. The fall of Water Year 2003 represented the end of a very dry, low rainfall, low flow period and beginning of a fairly wet period. Most of the years between 2003 and 2006 were fairly high rainfall and high flow years. The fall of Water Year 2009 was preceded by two low rainfall, low flow years. The very small changes in vegetation observed between periods with large natural variations in flow and salinity suggest that it will be difficult if not impossible to measure the effects of withdrawals on the Alafia River wetland vegetation communities HBMP Year 9 Interpretive Report June 2009

74 Table Summary of annual rainfall (inches) at the NOAA Plant City rain gage Time Period Maximum 90th Percentile 75th Percentile Mean Median 25th Percentile 10th Percentile Minimum Standard Deviation Period of Record Study Period Pre-operational Period Operational Period Period of Record is 1893-WY-2008 Study Period is Apr-2000 through WY2008 Pre-Operational Period is Apr-2000 through Jan-2003 Operational Period is Feb-2003 through WY2008 WY 2008 Alafia HBMP Interpretive Report

75 Table Rainfall (inches) at the NOAA Plant City rain gage Water Year Total Oct Nov Dec Jan Feb Mar Apr May Jun Jul Aug Sep WY 2008 Alafia HBMP Interpretive Report

76 Table Rainfall (inches) at the USGS Alafia River at Lithia rain gage Water Year Total Oct Nov Dec Jan Feb Mar Apr May Jun Jul Aug Sep

77 Table Summary of daily calculated flows in the Alafia River at Bell Shoals Time Period Maximum 90th Percentile 75th Percentile Mean Median 25th Percentile 10th Percentile Minimum Standard Deviation Period of Record Study Period Pre-Operational Period Operational Period WY WY WY WY WY WY WY WY WY Period of Record is 1975-WY-2008 Study Period is Apr-2000 through WY2008 Pre-Operational Period is Apr-2000 through Jan-2003 Operational Period is Feb-2003 through WY2008 Calculated Flow = (Alafia River at Lithia*1.117)+Discharge from Lithia Springs Major WY 2008 Alafia HBMP Interpretive Report

78 Table Summary of daily Tampa Bay Water withdrawals (mgd) from the Alafia River Water Year Maximum 90th Percentile 75th Percentile Mean Median 25th Percentile 10th Percentile Minimum Standard Deviation Water Years 2007 and 2008 include EDO based withdrawal schedule WY 2008 Alafia HBMP Interpretive Report

79 Table Summary of daily Tampa Bay Water withdrawals (mgd) from the Alafia River Month Maximum 90th Percentile 75th Percentile Mean Median 25th Percentile 10th Percentile Minimum Standard Deviation JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC WY 2008 Alafia HBMP Interpretive Report

80 Table Summary of Tampa Bay Water withdrawals as a proportion of calculated flow Water Year Maximum 90th Percentile 75th Percentile Mean Median 25th Percentile 10th Percentile Minimum Standard Deviation Water Years 2007 and 2008 include EDO based withdrawal schedule WY 2008 Alafia HBMP Interpretive Report

81 Table Summary of maximum daily withdrawal as a proportion of daily flow range MONTH Maximum 90th Percentile 75th Percentile Mean Median 25th Percentile 10th Percentile Minimum Standard Deviation JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC

82 Table Trend Tests of Calculated Alafia River Flow at Bell Shoals Trend Test Tau Value Seasonal Kendall Tau of Monthly Values Un- Adjusted Probability Adjusted Probability Slope Monthly Mean Flow Month Median Flow Kendall Tau of Annual Values Annual Mean Flow NA Annual P5 Flow NA Annual P10 Flow NA Annual P25 Flow NA Annual P50 Flow NA Annual P75 Flow NA Annual P90 Flow NA Annual P95 Flow NA 6.343

83 Table Classification table used to assess model validation in strata AR4 and AR5 Stratum Observed Predicted Non-exceedance Exceedance AR4 Non-exceedance 75% 25% Exceedance 51% 49% AR5 Non-exceedance 86% 14% Exceedance 27% 73% Table Comparison of model Rsquare values for logistic regression models with additional data Stratum Old R 2 New R 2 AR AR AR AR AR AR6 NS 0.25 EPC Table Classification table used to assess model validation Observed Predicted Non-exceedance Exceedance AR2 Non-exceedance 20% 80% Exceedance 23% 77% AR3 Non-exceedance 23% 77% Exceedance 8% 92% AR4 Non-exceedance 30% 70% Exceedance 13% 86% AR5 Non-exceedance 47% 52% Exceedance 23% 77% Table Comparison of model Rsquare values for logistic regression models with additional data Stratum Old R2 New R2 AR AR AR AR EPC

84 TABLE CPUE of fish taxa in the Alafia River summarized by Water Year and Gear Type Water Year Gear Mean CPUE 90th Percentile CPUE 75th Percentile CPUE Median CPUE 25th Percentile CPUE 10th Percentile CPUE 2000 Seine 3, , Seine , Seine Seine , Seine , Seine Seine , Seine 1, , Seine , Trawl Trawl Trawl Trawl Trawl Trawl Trawl Trawl Trawl WY 2008 Alafia HBMP Interpretive Report

85 TABLE Mean of Abundance Weighted Salinity by Water Year for Species of Interest in the Alafia River Taxon Common Name Anchoa mitchilli Bay anchovy Archosargus probatocephalus Sheepshead Bairdiella chrysoura Silver perch Brevoortia spp. Menhaden Callinectes sapidus Blue crab Centropomus undecimalis Snook Cynoscion arenarius Sand seatrout Cynoscion nebulosus Spotted seatrout Eucinostomus harengulus Tidewater mojarra Eucinostomus spp. Jenny/Mojarra Eugerres plumieri Striped mojarra Farfantepenaeus duorarum Pink shrimp Fundulus seminolis Seminole killifish Gambusia holbrooki Eastern mosquito fish Gobiosoma spp. Goby Lagodon rhomboides Pinfish Leiostomus xanthurus Spot Lucania parva Rainwater killifish Menidia spp. Silversides Menticirrhus americanus Southern kingfish Microgobius gulosus Clown goby Mugil cephalus Striped mullet Mugil curema White mullet WY 2008 Alafia HBMP Interpretive Report

86 TABLE (cont.) Mean of Abundance Weighted Salinity by Water Year for Species of Interest in the Alafia River Taxon Common Name Opisthonema oglinum Atlantic thread herring Poecilia latipinna Sailfin molly Sciaenops ocellatus Red drum Trinectes maculatus Hogchoker WY 2008 Alafia HBMP Interpretive Report

87 TABLE Center of Abundance by Water Year for Species of Interest in the Alafia River Taxon Common Name Anchoa mitchilli Bay anchovy Archosargus probatocephalus Sheepshead Bairdiella chrysoura Silver perch Brevoortia spp. Menhaden Callinectes sapidus Blue crab Centropomus undecimalis Snook Cynoscion arenarius Sand seatrout Cynoscion nebulosus Spotted seatrout Eucinostomus harengulus Tidewater mojarra Eucinostomus spp. Jenny/Mojarra Eugerres plumieri Striped mojarra Farfantepenaeus duorarum Pink shrimp Fundulus seminolis Seminole killifish Gambusia holbrooki Eastern mosquito fish Gobiosoma spp. Goby Lagodon rhomboides Pinfish Leiostomus xanthurus Spot Lucania parva Rainwater killifish Menidia spp. Silversides Menticirrhus americanus Southern kingfish Microgobius gulosus Clown goby Mugil cephalus Striped mullet Mugil curema White mullet WY 2008 Alafia HBMP Interpretive Report

88 TABLE Center of Abundance by Water Year for Species of Interest in the Alafia River Taxon Common Name Opisthonema oglinum Atlantic thread herring Poecilia latipinna Sailfin molly Sciaenops ocellatus Red drum Trinectes maculatus Hogchoker WY 2008 Alafia HBMP Interpretive Report

89 TABLE CPUE per sample of the plankton community in the Alafia River summarized by month Month Mean CPUE 90th Percentile CPUE 75th Percentile CPUE Median CPUE 25th Percentile CPUE 10th Percentile CPUE Oct 1, , , Nov 4, , , , Dec 2, , , , Jan 1, , , Feb 1, , , Mar 3, , , , , Apr 14, , , , , May 12, , , , , Jun 7, , , , Jul 6, , , Aug 3, , , Sep 2, , , WY 2008 Alafia HBMP Interpretive Report

90 TABLE Mean of abundance weighted salinity by Water Year for plankton species of interest in the Alafia River Taxon Fish, Brevoortia smithi Fish, Anchoa mitchilli Fish, Gobiesox strumosus Fish, Cynoscion arenarius Fish, Trinectes maculatus Isopod, Edotea triloba Mysids (juveniles) Mysid, Americamysis almyra Copepod, Acartia tonsa Ctenophore, Mnemiopsis mccradyi Shrimp, Palaemonetes pugio WY 2008 Alafia HBMP Interpretive Report

91 TABLE Center of abundance Taxon Fish, Brevoortia smithi Fish, Anchoa mitchilli Fish, Gobiesox strumosus Fish, Cynoscion arenarius Fish, Trinectes maculatus Isopod, Edotea triloba Mysids (juveniles) Mysid, Americamysis almyra Copepod, Acartia tonsa Ctenophore, Mnemiopsis mccradyi Shrimp, Palaemonetes pugio WY 2008 Alafia HBMP Interpretive Report

92 Figure Alafia River Reporting Unit.

93 Rainfall (inches) Year Figure Annual rainfall at the NOAA Plant City rain gage WY 2008 Alafia HBMP Interpretive Report

94 Period of Record Study Period Pre-Operational Operational 14 Rainfall (Inches) JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC Month Figure Monthly rainfall at the NOAA Plant City rain gage WY 2008 Alafia HBMP Interpretive Report

95 Rainfall (Inches) Period of Record Study Period Pre-Operational Operational JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC Month Figure Monthly rainfall at the USGS Alafia River at Lithia gage WY 2008 Alafia HBMP Interpretive Report

96 Flow (cfs) Year Figure Daily calculated flow in the Alafia River at Bell Shoals WY 2008 Alafia HBMP Interpretive Report

97 Cumulative Percent (%) Period of Record Study Period Pre-Operational Operational Log10 Calculated Flow (cfs) Figure CDF of calculated flow in the Alafia River at Bell Shoals by period WY 2008 Alafia HBMP Interpretive Report

98 Cumulative Percent (%) Period of Record WY2000 WY2001 WY Log10 Calculated Flow (cfs) Figure CDF of calculated flow in the Alafia River at Bell Shoals for WY WY 2008 Alafia HBMP Interpretive Report

99 Cumulative Percent (%) Period of Record WY2003 WY2004 WY Log10 Calculated Flow (cfs) Figure CDF of calculated flow in the Alafia River at Bell Shoals for WY WY 2008 Alafia HBMP Interpretive Report

100 Cumulative Percent (%) Period of Record WY2006 WY2007 WY Log10 Calculated Flow (cfs) Figure CDF of calculated flow in the Alafia River at Bell Shoals for WY WY 2008 Alafia HBMP Interpretive Report

101 Period of Record Study Period Pre-Operational Operational 8000 Flow (cfs) JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC Month Figure Daily calculated flow in the Alafia River at Bell Shoals WY 2008 Alafia HBMP Interpretive Report

102 Figure Alafia River HBMP and WUP Key Dates EDO SWF Expires EDO SWF Issued HBMP Design Accepted by TBW Initial WUP Issued Field Sampling Initiated Continuous Recorders installed Int. Report Submitted Alafia Production begins Int. Report Submitted EDO SWF Issued EDO SWF Modified EDO SWF Expires WY 2008 Alafia HBMP Interpretive Report

103 Withdrawal (mgd) JAN03 JAN04 JAN05 JAN06 JAN07 JAN08 JAN09 Year Figure Daily Tampa Bay Water withdrawal from the Alafia River WY 2008 Alafia HBMP Interpretive Report

104 Withdrawal (mgd) Water Year Figure Daily Tampa Bay Water withdrawal from the Alafia River WY 2008 Alafia HBMP Interpretive Report

105 Cumulative Percent (%) Operating Period WY2003 WY2004 WY Withdrawal (mgd) Figure CDF of Tampa Bay Water withdrawals from the Alafia River WY 2008 Alafia HBMP Interpretive Report

106 Cumulative Percent (%) Operating Period WY2006 WY2007 WY Withdrawal (mgd) Figure CDF of Tampa Bay Water withdrawals from the Alafia River WY 2008 Alafia HBMP Interpretive Report

107 Calculated Flow Adjusted Flow Flow (cfs) JAN03 JAN04 JAN05 JAN06 JAN07 JAN08 JAN09 Year Figure Comparison of adjusted and calculated flow at Bell Shoals WY 2008 Alafia HBMP Interpretive Report

108 Proportion of calculated flow Water Year Figure Tampa Bay Water withdrawal as a proportion of calculated flow at Bell Shoals WY 2008 Alafia HBMP Interpretive Report

109 Proportion of daily reconstructed flow range JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC Month Figure Daily maximum Tampa Bay Water withdrawal as a proportion of daily flow range WY 2008 Alafia HBMP Interpretive Report

110 Depth=0 to 0.3 m Period of Record Study Period Pre-Operational Operational Salinity (PSU) AR1 AR2 AR3 AR4 AR5 AR6 AR7 River Stratum Figure Box plots of salinity across strata during multiple time periods WY 2008 Alafia HBMP Interpretive Report

111 Water Year=2003 Depth=0 to 0.3 m Quarter 1 Quarter 2 Quarter 3 Quarter 4 Salinity (PSU) AR1 AR2 AR3 AR4 AR5 AR6 AR7 River Stratum Figure Box plots of salinity across strata during the designated Water Year WY 2008 Alafia HBMP Interpretive Report

112 40 Stratum=AR1 Depth Range=0 to 0.3 m Salinity (psu) JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC Month Figure Salinity at defined depth and stratum for the period WY 2008 Alafia HBMP Interpretive Report

113 30 25 Period of Record Study Period Pre-Operational Operational 20 Salinity (PSU) AR1 AR2 AR3 AR4 AR5 AR6 AR7 River Stratum Figure Box plots of the difference in salinity between depth layers m and m WY 2008 Alafia HBMP Interpretive Report

114 Depth Range=1.0 to 2.0 m APR-75 to MAR-00 APR-00 to JAN-03 FEB-03 to SEP-08 Salinity (PSU) River Kilometer Figure Alafia River salinity at defined depth range over time periods of interest WY 2008 Alafia HBMP Interpretive Report

115 Period of Record Study Period Pre-Operational Operational Salinity (PSU) AR1 AR2 AR3 AR4 AR5 AR6 AR7 River Stratum Figure Box plots of salinity across strata during multiple time periods WY 2008 Alafia HBMP Interpretive Report

116 Volume (mil. m^3) 8 Observed Scenario Reconstructed Scenario 7 ALAFIA RIVER xxx Volume < 2 psu < 5 psu < 15 psu Figure Box and whisker plot of daily volume WY 2008 Alafia HBMP Interpretive Report

117 Bottom Area (hectares) 40 Observed Scenario Reconstructed Scenario ALAFIA RIVER xxx Bottom Area < 2 psu < 5 psu < 15 psu Figure Box and whisker plot of daily bottom area WY 2008 Alafia HBMP Interpretive Report

118 Shoreline Length (km) 50 Observed Scenario Reconstructed Scenario ALAFIA RIVER xxx Shoreline Length < 2 psu < 5 psu < 15 psu Figure Box and whisker plot of daily shoreline length WY 2008 Alafia HBMP Interpretive Report

119 25 20 Depth Range=0.3 to 1.0 m APR-75 to MAR-00 APR-00 to JAN-03 FEB-03 to SEP-08 DO (mg/l) River Kilometer Figure Alafia River dissolved oxygen at defined depth range over time periods of interest WY 2008 Alafia HBMP Interpretive Report

120 APR-75 to MAR-00 APR-00 to JAN-03 FEB-03 to SEP Chl-a (ug/l) River Kilometer Figure Corrected chlorophyll-a in the Alafia River over time periods of interest WY 2008 Alafia HBMP Interpretive Report

121 Chl-a (ug/l) APR-75 to MAR-00 APR-00 to JAN-03 FEB-03 to SEP River Kilometer Figure Uncorrected chlorophyll-a in the Alafia River over time periods of interest WY 2008 Alafia HBMP Interpretive Report

122 18 15 Period of Record Study Period Pre-Operational Operational 12 DO (mg/l) AR1 AR2 AR3 AR4 AR5 AR6 AR7 River Stratum Figure Box plots of the difference in dissolved oxygen between depth layers m and m WY 2008 Alafia HBMP Interpretive Report

123 Period of Record Study Period Pre-Operational Operational 350 Chl-a (ug/l) AR1 AR2 AR3 AR4 AR5 AR6 AR7 River Stratum Figure Box plots of corrected chlorophyll-a across strata during multiple time periods WY 2008 Alafia HBMP Interpretive Report

124 Chl-a (ug/l) Period of Record Study Period Pre-Operational Operational AR1 AR2 AR3 AR4 AR5 AR6 AR7 River Stratum Figure Box plots of uncorrected chlorophyll-a across strata during multiple time periods WY 2008 Alafia HBMP Interpretive Report

125 P(y=1 x) ALAFIA RIVER Operational Period Stratum=AR Alafia Flow (cfs) Observed Reconstructed Upper 95% CI Lower 95% CI Figure 3.7.1a Probability of Chlorophyll value > 15 ug/l under observed and reconstructed scenarios WY 2008 Alafia HBMP Interpretive Report

126 P(y=1 x) ALAFIA RIVER Operational Period Stratum=AR Alafia Flow (cfs) Observed Reconstructed Upper 95% CI Lower 95% CI Figure 3.7.1b Probability of Chlorophyll value > 15 ug/l under observed and reconstructed scenarios WY 2008 Alafia HBMP Interpretive Report

127 P(y=1 x) ALAFIA RIVER Operational Period Stratum=AR Alafia Flow (cfs) Observed Reconstructed Upper 95% CI Lower 95% CI Figure 3.7.1c Probability of Chlorophyll value > 15 ug/l under observed and reconstructed scenarios WY 2008 Alafia HBMP Interpretive Report

128 P(y=1 x) ALAFIA RIVER Operational Period Stratum=AR Alafia Flow (cfs) Observed Reconstructed Upper 95% CI Lower 95% CI Figure 3.7.1d Probability of Chlorophyll value > 15 ug/l under observed and reconstructed scenarios WY 2008 Alafia HBMP Interpretive Report

129 P(y=1 x) ALAFIA RIVER Operational Period Stratum=EPC Alafia Flow (cfs) Observed Reconstructed Upper 95% CI Lower 95% CI Figure 3.7.1e Probability of Chlorophyll value > 15 ug/l under observed and reconstructed scenarios WY 2008 Alafia HBMP Interpretive Report

130 12.5 Alafia River 10.0 LN(CPUE+1) Water Year Figure Boxplots representing LN(CPUE+1) of fish for seines in Alafia River by water year WY 2008 Alafia HBMP Interpretive Report

131 10.0 Alafia River 7.5 LN(CPUE+1) Water Year Figure Boxplots representing LN(CPUE+1) of fish for trawls in Alafia River by water year WY 2008 Alafia HBMP Interpretive Report

132 No. of species 60 Alafia River xx Monthly Richness (number of species) for the HBMP Study Period Oct Nov Dec Jan Feb Mar Apr May Jun Jul Aug Sep Month Figure Number of fish species caught in seines in the Alafia River by water year WY 2008 Alafia HBMP Interpretive Report

133 No. of species Alafia River xx Monthly Richness (number of species) for the HBMP Study Period Oct Nov Dec Jan Feb Mar Apr May Jun Jul Aug Sep Month Figure Number of fish species caught in trawls in the Alafia River by water year WY 2008 Alafia HBMP Interpretive Report

134 4 Alafia River 3 Diversity Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Month Figure Boxplots representing Shannon-Weiner diversity of fish for seines in Alafia River by month WY 2008 Alafia HBMP Interpretive Report

135 4 Alafia River 3 Diversity Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Month Figure Boxplots representing Shannon-Weiner diversity of fish for trawls in Alafia River by month WY 2008 Alafia HBMP Interpretive Report

136 15.0 Alafia River 12.5 LN(CPUE+1) Water Year Figure Boxplots representing LN(CPUE+1) of zooplankton in Alafia River by water year WY 2008 Alafia HBMP Interpretive Report

137 15.0 Alafia River 12.5 LN(CPUE+1) Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Month Figure Boxplots representing LN(CPUE+1) of zooplankton in Alafia River by month WY 2008 Alafia HBMP Interpretive Report

138 No. of species Alafia River xx Monthly Richness (number of species) for the HBMP Study Period Oct Nov Dec Jan Feb Mar Apr May Jun Jul Aug Sep Month Figure Number of zooplankton species caught in seines in the Alafia River by water year WY 2008 Alafia HBMP Interpretive Report

139 4 Alafia River 3 Diversity Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Month Figure Boxplots representing Shannon-Weiner diversity of zooplankton in Alafia River by month WY 2008 Alafia HBMP Interpretive Report

140 4 Alafia River 3 Diversity Water Year Figure Boxplots representing Shannon-Weiner diversity of zooplankton in Alafia River by water year WY 2008 Alafia HBMP Interpretive Report

141 Number of Taxa Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Figure Taxa richness by month and water year WY 2008 Alafia HBMP Interpretive Report

142 70 60 Operational Pre-Operational 50 Species Richness Salinity (ppt) Figure Species richness versus salinity WY 2008 Alafia HBMP Interpretive Report

143 5 4 Diversity Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Figure Shannon-Weiner diversity across months WY 2008 Alafia HBMP Interpretive Report

144 5 4 Diversity Figure Inter-annual variation in Shannon-Weiner diversity WY 2008 Alafia HBMP Interpretive Report

145 Location (km) Operational Pre-Operational Figure Location of occurrence of polychaetes during Pre-Operational and Operational periods WY 2008 Alafia HBMP Interpretive Report

146 40 30 Salinity (ppt) Operational Pre-Operational Figure Salinity at time of sample collection for samples containing Polychaetes WY 2008 Alafia HBMP Interpretive Report

147 Location (km) Operational Pre-Operational Figure Location of occurrence of Amphipods during Pre-Operational and Operational periods WY 2008 Alafia HBMP Interpretive Report

148 40 30 Salinity (ppt) Operational Pre-Operational Figure Salinity at time of sample collection for samples containing Amphipods WY 2008 Alafia HBMP Interpretive Report

149 Figure Alafia River riverine vegetation